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An Evaluation of Vegetation and Wildlife Communities in Mitigation and Natural Wetlands of West Virginia
Collins K. Balcombe
Thesis submitted to the Davis College of Agriculture, Forestry, and Consumer Sciences
at West Virginia University in partial fulfillment of the requirements
for the degree of
Master of Science in
Wildlife and Fisheries Resource Management
James T. Anderson, Ph.D, Chair Ronald H. Fortney, Ph.D.
William N. Grafton Walter S. Kordek
James S. Rentch, Ph.D.
Morgantown, West Virginia 2003
Key Words: Wetland mitigation, wetland restoration, wetland management, mitigation wetland, constructed wetland, reference
wetland
ABSTRACT
An Evaluation of Vegetation and Wildlife Communities in Mitigation and Natural Wetlands of West Virginia
Collins K. Balcombe
The goal of this study was to evaluate the relative success of mitigation wetlands in West Virginia in supporting vegetation, invertebrate, and wildlife communities. Eleven mitigation wetlands were compared to 4 naturally occurring reference wetlands. For all vegetation species sampled, species richness (no. species/quadrat; P = 0.035), evenness (P = 0.033), and diversity (P = 0.025) were higher in mitigation than reference wetlands. Mean weighted averages per quadrat were similar between mitigation and reference wetlands (P = 0.242). Differences in vegetation composition between wetland types were reflected through ordination using Detrended Correspondence Analysis (DCA). Both mitigation and natural wetlands met criteria for hydrophytic vegetation according to the 1987 U.S. Army Corp of Engineers Wetland Delineation Manual. Overall invertebrate familial richness, diversity, density, and biomass were similar between mitigation and reference wetlands (P > 0.05). Within open water habitats, benthic density was higher in reference wetlands, but nektonic biomass was higher in mitigation wetlands (P < 0.05). Mitigation wetlands generally contained more abundant individual taxa than reference wetlands. Bird species richness (P = 0.711), diversity (P = 0.314), and abundance (P = 0.856) were similar between mitigation and reference wetlands. Waterbird (P = 0.013) and waterfowl (P = 0.013) abundance were higher in mitigation than reference wetlands. Frog species richness (P = 0.023), Wisconsin index value (P < 0.001), and abundance (P < 0.001) were higher in mitigation than reference wetlands. American bullfrog (Rana catesbeiana; WI: P = 0.033; A: P = 0.038), green frog (R. clamitans; WI: P = 0.012; A: P = 0.018), and pickerel frog (R. palustris; WI: P = 0.003; A: P = 0.005) were higher in mitigation wetlands. Habitat Suitability Index (HSI) scores for all 8 species combined were similar (P = 0.489) between wetland types. Red-winged blackbird (Agelaius phoeniceus; P = 0.001) and beaver (Castor canadensis; P = 0.037) HSI values were higher in natural than mitigation wetlands. All other species� SI values were similar between wetland types. Differences in vegetation and invertebrate community composition and structure likely contribute to differences in wildlife communities between wetland types, although Canonical Correspondence Analysis revealed no correlation between environmental variables and wildlife abundance. These data indicate that mitigation wetlands in West Virginia currently meet and exceed reference standards, although more time is needed for wetland stabilization. Numerous management strategies should be incorporated to facilitate colonization and proliferation of diverse wildlife taxa among current or future mitigation wetland.
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ACKNOWLEDGMENTS
I thank the following individuals for their assistance with the field sampling
conducted for this project: Sheri L. Helon, Seth R. Lemley, Joseph D. Osbourne,
Todd J. Polesiak, and Andrew K. Zadnik.
A special thanks is extended to George E. Seidel for assistance with statistical
analysis. A special thanks also is extended to my graduate committee, in particular
my advisor James T. Anderson, whose advice and genuine support afforded me the
opportunity to conduct this exciting research. I thank the West Virginia University
Davis College of Agriculture, Forestry, and Consumer Sciences (McIntire-Stennis
Program) for providing the majority of funds for my project. I also thank the West
Virginia Division of Natural Resources for funding and resources, as well as the West
Virginia Division of Highways, West Virginia Department of Environmental
Protection, and Trus Joist MacMillan for permission to conduct my research on
respective properties.
Finally, I thank my family, especially my mother, for supporting me in my
endeavors to become a wildlife biologist. A special dedication is extended to my
father, Douglas H. Balcombe, whose memory continues to inspire me to accomplish
high levels of achievement.
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CHAPTER I............................................................................................................... 1 A LITERATURE REVIEW OF WETLAND VALUE, FUNCTION, AND MITIGATION SUCCESS: PROJECT OVERVIEW ........................ 1 ABSTRACT.................................................................................................................. 2
Wetland value ........................................................................................................... 3 Vegetation and wildlife use ...................................................................................... 5 Wetland protection.................................................................................................... 7 Mitigation success..................................................................................................... 8
JUSTIFICATION ....................................................................................................... 10 OBJECTIVES............................................................................................................. 11 STUDY SITES............................................................................................................ 13
Overview of West Virginia..................................................................................... 13 AREA 1................................................................................................................... 14 AREA 2................................................................................................................... 16 AREA 3................................................................................................................... 18 AREA 4................................................................................................................... 22
QUALITY CONTROL............................................................................................... 24 LITERATURE CITED ............................................................................................... 25 TABLES ..................................................................................................................... 32 FIGURES.................................................................................................................... 36 CHAPTER II ........................................................................................................... 57 A COMPARISON OF VEGETATION COMMUNITITES IN MITIGATION AND NATURAL WETLANDS IN THE MID-APPALACHIANS................................................................................................. 57 ABSTRACT................................................................................................................ 58 INTRODUCTION ...................................................................................................... 59 METHODS ................................................................................................................. 62
Study sites ............................................................................................................... 62 Vegetation community sampling ............................................................................ 63 Data analyses .......................................................................................................... 64
RESULTS ................................................................................................................... 66 DISCUSSION............................................................................................................. 69 MANAGEMENT IMPLICATIONS .......................................................................... 74 LITERATURE CITED ............................................................................................... 78 TABLES ..................................................................................................................... 89 FIGURES.................................................................................................................... 91 CHAPTER III ......................................................................................................... 96 AQUATIC MACROINVERTEBRATE COMMUNITY STRUCTURE IN MITIGATION WETLANDS OF WEST VIRGINIA ............................ 96 ABSTRACT................................................................................................................ 97 INTRODUCTION ...................................................................................................... 98 METHODS ............................................................................................................... 102
Study sites ............................................................................................................. 102 Invertebrate sampling............................................................................................ 103
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Statistical analyses ................................................................................................ 104 RESULTS ................................................................................................................. 105
Taxa occurrence .................................................................................................... 105 Mitigation versus reference wetlands ................................................................... 105 Emergent versus open water habitats.................................................................... 108
DISCUSSION........................................................................................................... 108 Mitigation versus reference wetlands ........................................................................ 108 Emergent versus open water habitats.................................................................... 117 Future considerations ............................................................................................ 119 Management options............................................................................................. 121
LITERATURE CITED ............................................................................................. 125 TABLES ................................................................................................................... 137 CHAPTER IV ....................................................................................................... 144 WILDLIFE HABITAT USE IN MITIGATION AND NATURAL WETLANDS OF WEST VIRGINIA ............................................................. 144 ABSTRACT.............................................................................................................. 145 STUDY AREA ......................................................................................................... 151 METHODS ............................................................................................................... 152
Avian Communities .............................................................................................. 152 Anuran Communities ............................................................................................ 153 Habitat Quality...................................................................................................... 154 Statistical Analyses ............................................................................................... 157
RESULTS ................................................................................................................. 159 Avian Communities .............................................................................................. 159 Anuran Communities ............................................................................................ 160 Habitat Quality...................................................................................................... 161
Red-winged Blackbird.-- ................................................................................... 161 Beaver.--............................................................................................................ 162 Muskrat.--.......................................................................................................... 162 Mink.--............................................................................................................... 162 Great Blue Heron.-- .......................................................................................... 163 Wood Duck.-- .................................................................................................... 163 Red-spotted Newt.--........................................................................................... 164 Snapping Turtle.-- ............................................................................................. 165
DISCUSSION........................................................................................................... 165 Avian Communities .............................................................................................. 165 Anuran Communities ............................................................................................ 170 Habitat Quality...................................................................................................... 177
Red-winged Blackbird.-- ................................................................................... 177 Beaver.--............................................................................................................ 178 Muskrat.--.......................................................................................................... 179 Mink.--............................................................................................................... 180 Great Blue Heron.-- .......................................................................................... 181 Wood Duck.-- .................................................................................................... 184 Red-spotted Newt.--........................................................................................... 187 Snapping Turtle.-- ............................................................................................. 188
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Conclusions.-- ................................................................................................... 190 CONCLUSIONS....................................................................................................... 194 MANAGEMENT IMPLICATIONS ........................................................................ 196 LITERATURE CITED ............................................................................................. 206 TABLES ................................................................................................................... 228 CHAPTER V......................................................................................................... 234 VEGETATION, INVERTEBRATE, AND WILDLIFE COMMUNITY RANKINGS AND HABITAT ANALYSIS OF MITIGATION WETLANDS IN WEST VIRGINIA .............................................................. 234 ABSTRACT.............................................................................................................. 235 INTRODUCTION .................................................................................................... 236 METHODS ............................................................................................................... 240
Study sites ............................................................................................................. 240 Vegetation community sampling .............................................................................. 242 Wetland delineation .............................................................................................. 242 Invertebrate sampling............................................................................................ 243 Avian and anuran communities ............................................................................ 244 Habitat quality....................................................................................................... 244 Statistical analyses ................................................................................................ 245
RESULTS ................................................................................................................. 249 Wetland rankings .................................................................................................. 249 Canonical Correspondence Analysis .................................................................... 251 Wetland delineation .............................................................................................. 252
DISCUSSION........................................................................................................... 253 Wetland rankings .................................................................................................. 253 Environmental data ............................................................................................... 256 Mitigation success................................................................................................. 258 Conclusions........................................................................................................... 259
LITERATURE CITED ............................................................................................. 262 TABLES ................................................................................................................... 274 FIGURES.................................................................................................................. 297 APPENDICES ...................................................................................................... 307
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CHAPTER I. LIST OF TABLES Table 1. List of 11 mitigation and 4 reference wetland study sites in West Virginia, including site name, year constructed, size (ha), source builder, Universal Transverse Mercator (UTM) coordinates, 7.5 minute quadrangle, basin, and watershed, 2001-2002�������������������������������..33 Table 2. Universal Transverse Mercator (UTM) coordinates of frog, bird, and vegetation sampling locations for 11 reference and 4 mitigation wetlands of West Virginia, 2001-2002�������������������������������..34 CHAPTER I. LIST OF FIGURES Figure 1. Study site locations for mitigation and reference wetlands in West Virginia, 2001-2002�������������������������������..37 Figure 2. Location of the Altona Marsh reference wetland on the Middleway 7.5 minute quadrangle, West Virginia, 2001-2002���������������38 Figure 3. Location of the Walnut Bottom mitigation wetland on the Old Fields 7.5 minute quadrangle, West Virginia, 2001-2002���������..�����..39 Figure 4. Location of the Elder Swamp reference wetland and the VEPCO mitigation wetland on the Mt. Storm 7.5 minute quadrangle, West Virginia, 2001-2002���40 Figure 5. Location of the Buffalo Coal mitigation wetland on the Davis 7.5 minute quadrangle, West Virginia, 2001-2002������������������41 Figure 6. Location of the Elk Run mitigation wetland on the Davis 7.5 minute quadrangle, West Virginia, 2001-2002������������������42 Figure 7. Location of the Meadowville reference wetland and the Sugar Creek mitigation wetland on the Nestorville 7.5 minute quadrangle, West Virginia, 2001-2002�������������������������������..43 Figure 8. Location of the Leading Creek mitigation wetland on the Montrose 7.5 minute quadrangle, West Virginia, 2001-2002���������������44 Figure 9. Location of the Sand Run mitigation wetland on the Buckhannon 7.5 minute quadrangle, West Virginia, 2001-2002���������������45 Figure 10. Location of the Triangle and Trus Joist MacMillan mitigation wetlands on the Century 7.5 minute quadrangle, West Virginia, 2001-2002��������..46
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Figure 11. Location of the Muddlety reference wetland and the Enoch Branch mitigation wetland on the Widen 7.5 minute quadrangle, West Virginia, 2001-2002�������������������������������..47 Figure 12. Location of the Bear Run mitigation wetland on the Glenville 7.5 minute quadrangle, West Virginia, 2001-2002������������������48 Figure 13. Photograph of the Altona Marsh reference wetland, West Virginia, summer, 2001���������������������������...49 Figure 14. Photograph of the Walnut Bottom mitigation wetland, West Virginia, summer, 2001���������������������������...49 Figure 15. Photograph of the Elder Swamp reference wetland, West Virginia, summer, 2001���������������������������...50 Figure 16. Photograph of the VEPCO mitigation wetland, West Virginia, summer, 2001�������������������������������..50 Figure 17. Photograph of the Buffalo Coal mitigation wetland, West Virginia, summer, 2001���������������������������...51 Figure 18. Photograph of the Elk Run mitigation wetland, West Virginia, spring, 2001�������������������������������..51 Figure 19. Photograph of the Meadowville reference wetland, West Virginia, summer, 2001���������������������������...52 Figure 20. Photograph of the Leading Creek mitigation wetland, West Virginia, winter, 2001����������������������������.52 Figure 21. Photograph of the Sugar Creek mitigation wetland, West Virginia, summer, 2001���������������������������...53 Figure 22. Photograph of the Sand Run mitigation wetland, West Virginia, summer, 2001�������������������������������..53 Figure 23. Photograph of the Triangle mitigation wetland, West Virginia, summer, 2001�������������������������������..54 Figure 24. Photograph of the Trus Joist MacMillan mitigation wetland, West Virginia, summer, 2001�����������������������...54 Figure 25. Photograph of the Muddlety reference wetland, West Virginia, summer, 2001�������������������������������..55
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Figure 26. Photograph of the Enoch Branch mitigation wetland, West Virginia, summer, 2001���������������������������...55 Figure 27. Aerial photograph of the Bear Run mitigation wetland, West Virginia, fall, 2001�����������������������������..56 CHAPTER II. LIST OF TABLES Table 1. Total cover, richness, evenness, and diversity per 0.05 ha quadrat of native and nonnative species, as well as weighted averages and Wetland Indicator Statuses for 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002�������������������������������..90 CHAPTER II. LIST OF FIGURES Figure 1. Detrended Correspondence Analysis of vegetation quadrats for all species within 11 mitigation (n = 45) and 4 reference (n = 15) wetlands in West Virginia, 2001-2002. Two letter abbreviations with numbers represent individual quadrats at each wetland����������������������������.92 Figure 2. Detrended Correspondence Analysis of vegetation quadrats for native species only within 11 mitigation (n = 45) and 4 reference (n = 15) wetlands in West Virginia, 2001-2002. Two letter abbreviations with numbers represent individual quadrats at each wetland.�����������������������.93 Figure 3. Detrended Correspondence Analysis of vegetation quadrats for all species within 11 mitigation (n = 45) sites in West Virginia, 2001-2002. Quadrats were ordinated using age as a categorical variable. Two letter abbreviations with numbers represent individual quadrats at each wetland.���������������94 Figure 4. Detrended Correspondence Analysis of vegetation quadrats for all species within 11 mitigation (n = 45) sites in West Virginia, 2001-2002. Quadrats were ordinated using actual age as a quantitative variable. Two letter abbreviations with numbers represent individual quadrats at each wetland.�����������.95 CHAPTER III. LIST OF TABLES Table 1. Benthic invertebrate richness (no. families/wetland), diversity, density (no./m2) and biomass (g/m2) between mitigation (n =11) and reference (n = 4) wetlands across emergent areas, open water areas, and entire wetland complexes, 2001-2002 with comparisons of all invertebrate taxa and the 9 most common taxa (i.e., >100 individuals)����...�������������������138 Table 2. Nektonic invertebrate richness (no. families/wetland), diversity, density (no./L) and biomass (g/L) between mitigation (n = 11) and reference (n = 4) wetlands
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across emergent areas, open water areas, and entire wetland complexes, West Virginia, 2001-2002 with comparisons of all invertebrate taxa and the 13 most common taxa (i.e., >100 individuals)������������������140 Table 3. Benthic and nektonic invertebrate familial richness (no. families/wetland), diversity, density (benthic: no./m2; nektonic: no./L) and biomass (benthic g/m2; nektonic: g/L) between emergent and open water areas of mitigation wetlands (n = 11) in West Virginia, 2001-2002 with comparisons of all taxa and for the 9 most common (abundant) benthic and 13 most common nektonic taxa (i.e., >100 individuals)����������������������������142 Table 4. Benthic and nektonic invertebrate familial richness (no. families/wetland), diversity, density (no./L), and biomass (g/L) among emergent, open water, and scrub-shrub areas of the Elder Swamp reference wetland (n = 1), West Virginia, 2001-2002 with density and mass comparisons of all taxa and for the 9 most common (abundant) benthic taxa and 13 most common nektonic taxa (i.e., >100 individuals)����143 CHAPTER IV. LIST OF TABLES Table 1. Optimal Suitability Index (SI) scores of 38 habitat variables evaluated for Habitat Suitability Index models on 8 wildlife species in mitigation (n = 11) and natural (n = 4) wetlands in West Virginia, 2001-2002�����������..229 Table 2. Richness (no. species/0.78 ha), diversity (per 0.78 ha), and abundance (no.birds/0.78 ha) comparisons for avian communities between mitigation (n = 11) and natural (n = 4) wetlands in West Virginia, 2001-2002���������...231 Table 3. Wisconsin Index value and abundance per wetland for all anuran species combined and for each of 7 species heard at mitigation (n = 11) and natural (n = 4) wetlands, West Virginia, 2001-2002������������������.232 Table 4. Mean Suitability Index (SI) values between mitigation (n = 11) and natural (n = 4) wetlands of Habitat Suitability Index models for 8 wildlife species, West Virginia, 2001-2002������������������������...233 CHAPTER V. LIST OF TABLES Table 1. List of 11 mitigation and 4 reference wetland study sites in West Virginia, including site name, year constructed, size (ha), source builder, Universal Transverse Mercator (UTM) coordinates, 7.5 minute quadrangle, basin, and watershed, 2001-2002�������������������������������275 Table 2. Actual means and ranks of vegetation richness (no.species/plot), evenness, evenness (native species only), diversity, diversity (native species only), and
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weighted average, as well as total mean and scaled ranks for 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002�������������..276 Table 3. Actual mean and ranks of benthic and nektonic invertebrate richness (no.families/wetland), diversity, density, and mass, as well as total mean and scaled ranks for 11 mitigation and 11 reference wetlands in West Virginia, 2001-2002�.278 Table 4. Actual means and ranks of avian richness (no. birds/0.78 ha plot) and diversity, and abundance (no.indiv./0.78 ha plot) for all birds, waterbirds, waterfowl, and passerines, as well as total mean and scaled ranks of 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002�������������..280 Table 5. Actual means and ranks of anuran richness (no.species/wetland), Wisconsin Index (WI), and abundance for all species and for 7 individual species, as well as total mean and scaled ranks of 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002����������������������������..282 Table 6. Actual Habitat Suitability Index (HSI) values and ranks of 8 species, as well as total and scaled ranks of 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002����������������������������..284 Table 7. Vegetation, invertebrate, avian, anuran, and Habitat Suitability Index (HSI) ranks, as well as total mean and scaled ranks for 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002�����������������..286 Table 8. Summary of parameters including general structure and intraset correlation coefficients for all environmental variables in the canonical correspondence analysis of all avian species abundance within all wetlands (n = 15) and for mitigation wetlands only (n = 11) in West Virginia, 2001-2002������������288 Table 9. Summary of parameters including general structure and intraset correlation coefficients for all environmental variables in the canonical correspondence analysis of waterbird species abundance within 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002����������������������..289 Table 10. Summary of parameters including general structure and intraset correlation coefficients for all environmental variables in the canonical correspondence analysis of anuran species abundance within all wetlands (n = 15) and for mitigation wetlands only (n = 11) in West Virginia, 2001-2002���������������...290 Table 11. Summary of parameters including general structure and intraset correlation coefficients for all environmental variables in the canonical correspondence analysis of benthic invertebrate familial abundance within all wetlands (n = 15) and for mitigation wetlands only (n = 11) in West Virginia, 2001-2002�������...291
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Table 12. Summary of parameters including general structure and intraset correlation coefficients for all environmental variables in the canonical correspondence analysis of nektonic invertebrate familial abundance within all wetlands (n = 15) and for mitigation wetlands only (n = 11) in West Virginia, 2001-2002�������...292 Table 13. Species codes and common names of all avian and waterbird species included in canonical correspondence analysis of 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002�����������������..293 Table 14. Species codes and common names of 7 anuran species included in canonical correspondence analysis of 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002������������������������...294 Table 15. Species codes and common names of benthic and nektonic invertebrates included in canonical correspondence analysis of 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002�����������������..295 CHAPTER V. LIST OF FIGURES Figure 1. Canonical correspondence analysis ordination of all avian species on 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002, based on 5 environmental variables: open = % open water; emveg = % emergent vegetation; vegh = vegetation diversity; invertbh = invertebrate benthic diversity; invertnh = invertebrate nektonic diversity.�������������������..�298 Figure 2. Canonical correspondence analysis ordination of all avian species on 11 mitigation wetlands in West Virginia, 2001-2002, based on 7 environmental variables: age, size, open = % open water; emveg = % emergent vegetation; vegh = vegetation diversity; invertbh = invertebrate benthic diversity; invertnh = invertebrate nektonic diversity�����������������������������..299 Figure 3. Canonical correspondence analysis ordination of all waterbird species on 11 mitigation wetlands in West Virginia, 2001-2002, based on 7 environmental variables: age, size, open = % open water; emveg = % emergent vegetation; vegh = vegetation diversity; invertbh = invertebrate benthic diversity; invertnh = invertebrate nektonic diversity�����������������������������..300 Figure 4. Canonical correspondence analysis ordination of all anuran species on 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002, based on 5 environmental variables: open = % open water; emveg = % emergent vegetation; vegh = vegetation diversity; invertbh = invertebrate benthic diversity; invertnh = invertebrate nektonic diversity��������������������...301
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Figure 5. Canonical correspondence analysis ordination of all anuran species on 11 mitigation wetlands in West Virginia, 2001-2002, based on 7 environmental variables: age, size, open = % open water; emveg = % emergent vegetation; vegh = vegetation diversity; invertbh = invertebrate benthic diversity; invertnh = invertebrate nektonic diversity�����������������������������302 Figure 6. Canonical correspondence analysis ordination of benthic invertebrate families on 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002, based on 4 environmental variables: open = % open water; emveg = % emergent vegetation; subm = % submergent vegetation; vegh = vegetation diversity���303 Figure 7. Canonical correspondence analysis ordination of benthic invertebrate families on 11 mitigation wetlands in West Virginia, 2001-2002, based on 6 environmental variables: age, size, open = % open water; emveg = % emergent vegetation; subm = % submergent vegetation; vegh = vegetation diversity���304 Figure 8. Canonical correspondence analysis ordination of nektonic invertebrate families on 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002, based on 4 environmental variables: open = % open water; emveg = % emergent vegetation; subm = % submergent vegetation; vegh = vegetation diversity���305 Figure 9. Canonical correspondence analysis ordination of nektonic invertebrate families on 11 mitigation wetlands in West Virginia, 2001-2002, based on 6 environmental variables: age, size, open = % open water; emveg = % emergent vegetation; subm = % submergent vegetation; vegh = vegetation diversity���306 LIST OF APPENDICES Appendix 1. Average percent cover/1.0 m2 quadrat of all herbaceous vegetation species sampled in 11 mitigation (n = 45) and 4 reference (n = 15) wetlands in West Virginia, 2001-2002�������������������������������308 Appendix 2. Species list, origin (O), and average cover (AC) of all herbaceous vegetation species sampled, and vegetation species that were seen but not sampled (SBNS) per plot at the Walnut Bottom mitigation wetland, 2001-2002�����313 Appendix 3. Species list, origin (O), and average cover (AC) of all herbaceous vegetation species sampled, and vegetation species that were seen but not sampled (SBNS) per plot at the VEPCO mitigation wetland, 2001-2002�������...314 Appendix 4. Species list, origin (O), and average cover (AC) of all herbaceous vegetation species sampled, and vegetation species that were seen but not sampled (SBNS) per plot at the Buffalo Coal mitigation wetland, 2001-2002������316
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Appendix 5. Species list, origin (O), and average cover (AC) of all herbaceous vegetation species sampled, and vegetation species that were seen but not sampled (SBNS) per plot at the Elk Run mitigation wetland, 2001-2002�������...317 Appendix 6. Species list, origin (O), and average cover (AC) of all herbaceous vegetation species sampled, and vegetation species that were seen but not sampled (SBNS) per plot at the Leading Creek mitigation wetland, 2001-2002�����.318 Appendix 7. Species list, origin (O), and average cover (AC) of all herbaceous vegetation species sampled, and vegetation species that were seen but not sampled (SBNS) per plot at the Sugar Creek mitigation wetland, 2001-2002������323 Appendix 8. Species list, origin (O), and average cover (AC) of all herbaceous vegetation species sampled, and vegetation species that were seen but not sampled (SBNS) per plot at the Sand Run mitigation wetland, 2001-2002�������.325 Appendix 9. Species list, origin (O), and average cover (AC) of all herbaceous vegetation species sampled, and vegetation species that were seen but not sampled (SBNS) per plot at the Triangle mitigation wetland, 2001-2002�������...327 Appendix 10. Species list, origin (O), and average cover (AC) of all herbaceous vegetation species sampled, and vegetation species that were seen but not sampled (SBNS) per plot at the Trus Joist MacMillan mitigation wetland, 2001-2002��..329 Appendix 11. Species list, origin (O), and average cover (AC) of all herbaceous vegetation species sampled, and vegetation species that were seen but not sampled (SBNS) per plot at the Enoch Branch mitigation wetland, 2001-2002�����..331 Appendix 12. Species list, origin (O), and average cover (AC) of all herbaceous vegetation species sampled, and vegetation species that were seen but not sampled (SBNS) per plot at the Bear Run mitigation wetland, 2001-2002�������.332 Appendix 13. Species list, origin (O), and average cover (AC) of all herbaceous vegetation species sampled, and vegetation species that were seen but not sampled (SBNS) per plot at the Altona Marsh reference wetland, 2001-2002������333 Appendix 14. Species list, origin (O), and average cover (AC) of all herbaceous vegetation species sampled, and vegetation species that were seen but not sampled (SBNS) per plot at the Elder Swamp reference wetland, 2001-2002������334 Appendix 15. Species list, origin (O), and average cover (AC) of all herbaceous vegetation species sampled, and vegetation species that were seen but not sampled (SBNS) per plot at the Meadowville reference wetland, 2001-2002������.335
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Appendix 16. Species list, origin (O), and average cover (AC) of all herbaceous vegetation species sampled, and vegetation species that were seen but not sampled (SBNS) per plot at the Muddlety reference wetland, 2001-2002�������..336 Appendix 17. Woody and herbaceous vegetation species that were planted at 3 mitigation wetland sites, West Virginia, 2001-2002������������.337 Appendix 18-1. Bird, frog, and vegetation sampling points as well as dominant vegetation at the Altona Marsh reference wetland, West Virginia, 2001-2002��.338 Appendix 18-2. Wetland classification (Cowardin et al. 1979) where PEM = palustrine emergent, PF = palustrine forested, PSS = palustrine scrub-shrub, and PUB = palustrine unconsolidated bottom, of the Altona Marsh reference wetland, West Virginia, 2001-2002������������������������...339 Appendix 19-1. Bird, frog, and vegetation sampling points as well as dominant vegetation at the Walnut Bottom mitigation wetland, West Virginia, 2001-2002�340 Appendix 19-2. Wetland classification (Cowardin et al. 1979) where PEM = palustrine emergent, PSS = palustrine scrub-shrub, and PUB = palustrine unconsolidated bottom, of the Walnut Bottom mitigation wetland, West Virginia, 2001-2002����������������������������..340 Appendix 20-1. Bird, frog, and vegetation sampling points as well as dominant vegetation at the Elder Swamp reference wetland, West Virginia, 2001-2002��.341 Appendix 20-2. Wetland classification (Cowardin et al. 1979) where PEM = palustrine emergent, PF = palustrine forested, PSS = palustrine scrub-shrub, and PUB = palustrine unconsolidated bottom of the Elder Swamp reference wetland, West Virginia, 2001-2002������������������������...342 Appendix 21-1. Bird, frog, and vegetation sampling points as well as dominant vegetation at the VEPCO mitigation wetland, West Virginia, 2001-2002����343 Appendix 21-2. Wetland classification (Cowardin et al. 1979) where N/A = no applicable classification, PEM = palustrine emergent, PSS = palustrine scrub-shrub, and PUB = palustrine unconsolidated bottom of the VEPCO mitigation wetland, West Virginia, 2001-2002������������������������...344 Appendix 22-1. Bird, frog, and vegetation sampling points as well as dominant vegetation at the Buffalo Coal mitigation wetland, West Virginia, 2001-2002��345 Appendix 22-2. Wetland classification (Cowardin et al. 1979) where N/A = no applicable classification, PEM = palustrine emergent, PSS = palustrine scrub-shrub, and PUB = palustrine unconsolidated bottom of the Buffalo Coal mitigation wetland, West Virginia, 2001-2002����������������������..346
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Appendix 23-1. Bird, frog, and vegetation sampling points as well as dominant vegetation at the Elk Run mitigation wetland, West Virginia, 2001-2002����347 Appendix 23-2. Wetland classification (Cowardin et al. 1979) where N/A = no applicable classification, PEM = palustrine emergent, PSS = palustrine scrub-shrub, and PUB = palustrine unconsolidated bottom of the Elk Run mitigation wetland, West Virginia, 2001-2002������������������������...348 Appendix 24-1. Bird, frog, and vegetation sampling points as well as dominant vegetation at the Meadowville reference wetland, West Virginia, 2001-2002��..349 Appendix 24-2. Wetland classification (Cowardin et al. 1979) where N/A = no applicable classification, PEM = palustrine emergent, and PSS = palustrine scrub-shrub, of the Meadowville reference wetland, West Virginia, 2001-2002����350 Appendix 25-1. Bird, frog, and vegetation sampling points as well as dominant vegetation at the Leading Creek mitigation wetland, West Virginia, 2001-2002�.351 Appendix 25-2. Wetland classification (Cowardin et al. 1979) where N/A = no applicable classification, PEM = palustrine emergent, PSS = palustrine scrub-shrub, and PUB = palustrine unconsolidated bottom of the Leading Creek mitigation wetland, West Virginia, 2001-2002������������������...352 Appendix 26-1. Bird, frog, and vegetation sampling points as well as dominant vegetation at the Sugar Creek mitigation wetland, West Virginia, 2001-2002��.353 Appendix 26-2. Wetland classification (Cowardin et al. 1979) where N/A = no applicable classification, PEM = palustrine emergent, PSS = palustrine scrub-shrub, and PUB = palustrine unconsolidated bottom of the Sugar Creek mitigation wetland, West Virginia, 2001-2002����������������������..354 Appendix 27-1. Bird, frog, and vegetation sampling points as well as dominant vegetation at the Sand Run mitigation wetland, West Virginia, 2001-2002���.355 Appendix 27-2. Wetland classification (Cowardin et al. 1979) where N/A = no applicable classification, PEM = palustrine emergent, PSS = palustrine scrub-shrub, and PUB = palustrine unconsolidated bottom of the Sand Run mitigation wetland, West Virginia, 2001-2002����������������������..356 Appendix 28-1. Bird, frog, and vegetation sampling points as well as dominant vegetation at the Triangle mitigation wetland, West Virginia, 2001-2002����357 Appendix 28-2. Wetland classification (Cowardin et al. 1979) where N/A = no applicable classification, PEM = palustrine emergent, PSS = palustrine scrub-shrub,
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and PUB = palustrine unconsolidated bottom of the Triangle mitigation wetland, West Virginia, 2001-2002����������������������..358 Appendix 29-1. Bird, frog, and vegetation sampling points as well as dominant vegetation at the Trus Joist MacMillan mitigation wetland, West Virginia, 2001-2002�������������������������������359 Appendix 29-2. Wetland classification (Cowardin et al. 1979) where PEM = palustrine emergent, PSS = palustrine scrub-shrub, PUB = palustrine unconsolidated bottom, and PUS = palustrine unconsolidated shore, of the Trus Joist MacMillan mitigation wetland, West Virginia, 2001-2002��������������..360 Appendix 30-1. Bird, frog, and vegetation sampling points as well as dominant vegetation at the Muddlety reference wetland, West Virginia, 2001-2002���...361 Appendix 30-2. Wetland classification (Cowardin et al. 1979) where PEM = palustrine emergent, PSS = palustrine scrub-shrub, and PUB = palustrine unconsolidated bottom of the Muddlety reference wetland, West Virginia, 2001-2002�������������������������������362 Appendix 31-1. Bird, frog, and vegetation sampling points as well as dominant vegetation at the Enoch Branch mitigation wetland, West Virginia, 2001-2002�..363 Appendix 31-2. Wetland classification (Cowardin et al. 1979) where N/A = no applicable classification, PEM = palustrine emergent, PSS = palustrine scrub-shrub, and PUB = palustrine unconsolidated bottom of the Enoch Branch mitigation wetland, West Virginia, 2001-2002������������������...364 Appendix 32-1. Bird, frog, and vegetation sampling points as well as dominant vegetation at the Bear Run mitigation wetland, West Virginia, 2001-2002���..365 Appendix 32-2. Wetland classification (Cowardin et al. 1979) where N/A = no applicable classification, PEM = palustrine emergent, and PUB = palustrine unconsolidated bottom of the Bear Run mitigation wetland, West Virginia, 2001-2002�������������������������������366 Appendix 33. Number of benthic individuals collected by family and wetland from emergent (E) and open water (O) areas, as well as for the entire complex (total) for 11 mitigation wetlands in West Virginia, 2001-2002�������������.367 Appendix 34. Number of nektonic individuals collected by family and wetland from emergent (E), open water (O), and scrub-shrub (SS) areas, as well as for the entire complex (total) for 4 reference wetlands in West Virginia, 2001-2002�����369
xviii
Appendix 35. Number of nektonic individuals collected by family and wetland from emergent (E) and open water (O) areas, as well as for the entire complex (total) for 11 mitigation wetlands in West Virginia, 2001-2002�������������.371 Appendix 36. Number of individuals collected by family and wetland from emergent (E), open water (O), and scrub-shrub (SS) areas, as well as for the entire complex (total) for 4 reference wetlands in West Virginia, 2001-2002��������...374 Appendix 37. Species list of all birds sampled inside and outside 50 m radius plots (number of birds per point count) in 11 mitigation and 4 natural wetlands in West Virginia, 2001-2002������������������������...377 Appendix 38. Number of birds sampled inside 50 m radius plots (I), outside plots (O) and totals for 11 mitigation wetlands in West Virginia, 2001-2002������..380 Appendix 39. Species list of all birds sampled inside 50 m radius plots (I), outside plots (O) and totals for 4 natural wetlands in West Virginia, 2001-2002����..383 Appendix 40. Species lista of all frogs sampled by survey period in 11 mitigation wetlands in West Virginia (WB = Walnut Bottom, VO = Vepco, BC = Buffalo Coal, ER = Elk Run, LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus Joist MacMillan, EB = Enoch Branch, and BR = Bear Run), 2001-2002��.��������������������������.387 Appendix 41. Species lista of all frogs sampled by survey period in 4 natural wetlands in West Virginia (AM = Altona Marsh, ES = Elder Swamp, MV = Meadowville, and MY = Muddlety), 2001-2002�������������...388 Appendix 42. A comparison of actual mean values of all variables measured within the beaver, muskrat, mink, great blue heron, red-winged blackbird, wood duck, snapping turtle, and red-spotted newt Habitat Suitability Index models between mitigation (n = 11) and natural (n = 4) wetlands in West Virginia, 2001-2002��389 Appendix 43. Actual and Suitability index (SI) mean values for variables measured within the beaver, muskrat, mink, great blue heron, red-winged blackbird, wood duck, snapping turtle, and red-spotted newt Habitat Suitability Index models between mitigation (n = 11) and natural (n = 4) wetlands in West Virginia, 2001-2002��392 Appendix 44. Variable measurements and Suitability Index (SI) values for the red-winged blackbird Habitat Suitability Index model for mitigation (n = 11) and natural (n = 4) wetlands in West Virginia (mitigation sites: WB = Walnut Bottom, VO = Vepco, BC = Buffalo Coal, ER = Elk Run, LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus Joist MacMillan, EB = Enoch Branch, and BR = Bear Run; natural sites: AM = Altona Marsh, ES = Elder Swamp, MV = Meadowville, and MY = Muddlety), 2001-2002�������������...396
xix
Appendix 45. Variable measurements and Suitability Index (SI) values for the beaver Habitat Suitability Index model for mitigation (n = 11) and natural (n = 4) wetlands in West Virginia (mitigation sites: WB = Walnut Bottom, VO = Vepco, BC = Buffalo Coal, ER = Elk Run, LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus Joist MacMillan, EB = Enoch Branch, and BR = Bear Run; natural sites: AM = Altona Marsh, ES = Elder Swamp, MV = Meadowville, and MY = Muddlety), 2001-2002�����������������������398 Appendix 46. Variable measurements and Suitability Index (SI) values for the muskrat Habitat Suitability Index model for mitigation (n = 11) and natural (n = 4) wetlands in West Virginia (mitigation sites: WB = Walnut Bottom, VO = Vepco, BC = Buffalo Coal, ER = Elk Run, LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus Joist MacMillan, EB = Enoch Branch, and BR = Bear Run; natural sites: AM = Altona Marsh, ES = Elder Swamp, MV = Meadowville, and MY = Muddlety), 2001-2002�������������������������������400 Appendix 47. Variable measurements and Suitability Index (SI) values for the mink Habitat Suitability Index model for mitigation (n = 11) and natural (n = 4) wetlands in West Virginia (mitigation sites: WB = Walnut Bottom, VO = Vepco, BC = Buffalo Coal, ER = Elk Run, LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus Joist MacMillan, EB = Enoch Branch, and BR = Bear Run; natural sites: AM = Altona Marsh, ES = Elder Swamp, MV = Meadowville, and MY = Muddlety), 2001-2002�����������������������403 Appendix 48. Variable measurements and Suitability Index (SI) values for the great-blue heron Habitat Suitability Index model for mitigation (n = 11) and natural (n = 4) wetlands in West Virginia (mitigation sites: WB = Walnut Bottom, VO = Vepco, BC = Buffalo Coal, ER = Elk Run, LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus Joist MacMillan, EB = Enoch Branch, and BR = Bear Run; natural sites: AM = Altona Marsh, ES = Elder Swamp, MV = Meadowville, and MY = Muddlety), 2001-2002���������������������.405 Appendix 49. Variable measurements and Suitability Index (SI) values for the wood duck Habitat Suitability Index model for mitigation (n = 11) and natural (n = 4) wetlands in West Virginia (mitigation sites: WB = Walnut Bottom, VO = Vepco, BC = Buffalo Coal, ER = Elk Run, LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus Joist MacMillan, EB = Enoch Branch, and BR = Bear Run; natural sites: AM = Altona Marsh, ES = Elder Swamp, MV = Meadowville, and MY = Muddlety), 2001-2002���������������������.408 Appendix 50. Variable measurements and Suitability Index (SI) values for the snapping turtle Habitat Suitability Index model for mitigation (n = 11) and natural (n = 4) wetlands in West Virginia (mitigation sites: WB = Walnut Bottom, VO = Vepco, BC = Buffalo Coal, ER = Elk Run, LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus Joist MacMillan, EB = Enoch Branch, and BR =
xx
Bear Run; natural sites: AM = Altona Marsh, ES = Elder Swamp, MV = Meadowville, and MY = Muddlety), 2001-2002�������������...410 Appendix 51. Variable measurements and Suitability Index (SI) values for the red-spotted newt Habitat Suitability Index model for mitigation (n = 11) and natural (n = 4) wetlands in West Virginia (mitigation sites: WB = Walnut Bottom, VO = Vepco, BC = Buffalo Coal, ER = Elk Run, LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus Joist MacMillan, EB = Enoch Branch, and BR = Bear Run; natural sites: AM = Altona Marsh, ES = Elder Swamp, MV = Meadowville, and MY = Muddlety), 2001-2002������������������������413 Appendix 52. Common and scientific names of all birds included in Analysis of Variance models used to calculate metrics for wetland rankings and in Canonical Correspondence Analyses (CCA) on 11 mitigation and 4 reference wetlands, West Virginia, 2001-2002������������������������...415
1
CHAPTER I
A LITERATURE REVIEW OF WETLAND VALUE, FUNCTION,
AND MITIGATION SUCCESS: PROJECT OVERVIEW
COLLINS K. BALCOMBE balcster@hotmail.com
West Virginia University Division of Forestry
PO Box 6125 Morgantown, WV 26505-6125
2
ABSTRACT
Wetlands are extremely valuable to both people and wildlife, but
unfortunately, wetlands have continually been destroyed for decades with little or no
compensation. Section 404 of the Clean Water Act authorized the U.S. Army Corps
of Engineers to issue permits for dredging and filling practices affecting wetlands.
The �no net loss� policy of 1987 introduced mitigation as the leading tool in
combating wetland loss in the U.S. Damages to wetland functions have begun to be
mitigation by creating compensatory wetlands that must equal or exceed the functions
of destroyed sites. Although no general definition of mitigation success is accepted,
most researchers focus on evaluating wetland functions as a measure of the success of
mitigation. By comparing mitigation sites to naturally occurring reference wetlands,
which are assumed to represent optimal standards of comparison, researchers can
gauge the success of wetland mitigation. Only 2 studies of limited scope have been
conducted in West Virginia on mitigation success, so there was a need for a
comprehensive evaluation on the success of mitigation wetlands in the state. This
study compared vegetation and wildlife communities in 11 mitigation wetlands to
communities existing in 4 reference wetlands. The objectives of this study were to
compare vascular plant community composition and structure, breeding bird
diversity, richness, and abundance, frog richness and abundance, macroinvertebrate
richness, diversity, density, and biomass, and wildlife habitat quality using Habitat
Suitability Index models for 8 wetland-dependent wildlife species. The results of this
study should further our knowledge of wetland ecosystems by providing data that are
regionally applicable to wetland protection and management.
This chapter is written in the style of The Journal of Wildlife Management
3
Wetland value
Wetland habitat in the U.S. is a precious resource that holds many values to
society and wildlife alike. Wetlands provide economic support and recreation for
many people, maintain water quality and quantity, and support numerous plant and
animal species (Wharton et al. 1982, Feierabend and Zelazny 1987, Ernst and Brown
1989). Wetlands hold an aesthetic value to millions of people, and provide various
recreational opportunities including hunting, fishing, and bird watching. Wetlands
also assist in the production of timber and the commercial harvesting of fish and
shellfish species (Johnson 1979, Feierabend and Zelazny 1987, Browder et al. 1989,
National Cooperative Highway Research Program 1996). Wetlands are valuable
ecosystems because they can reduce flood potential by storing rainwater, act as
buffers against storms, or recharge groundwater. They also can improve water
quality by removing organic and inorganic nutrients and toxins from water supplies
(Verry and Boelter 1979, Heimburg 1984, Sather and Smith 1984). This not only
benefits society, but wildlife and plant communities as well.
Wetlands are extremely important to wildlife. More than 50% of the 800
species of protected migratory birds rely on wetlands in some way (Wharton et al.
1982). Although wetlands comprise only about 5% of land in the U.S., about 50% of
all rare and endangered wildlife species are either located in wetlands or depend on
them in some way (Williams and Dodd 1979, Ernst and Brown 1989, Mitsch and
Gosselink 2000). Ernst and Brown (1989) listed 63 plant and 34 animal species as
endangered, threatened, or candidates for listing in forested wetlands throughout the
U.S. In West Virginia, Evans and Wilson (1982) reported 35 species of mammals, 71
4
species of birds, and 41 species of reptiles and amphibians in and around wetlands.
Numerous fish and shellfish species also rely on wetlands, with over 95% of the
nation�s harvest coming from wetlands (Feierabend and Zelazny 1987).
Because so many wildlife species have adapted to the unique habitat features
of wetlands, it is obvious that the destruction and degradation of wetlands negatively
affects biodiversity. Hudson (1991) concluded that wetland destruction in California
has the potential to negatively affect about 220 animal and 600 plant species.
Similarly, Gibbs (1993) used a model that predicted significant losses in turtles, small
birds, and small mammals due to losses of small wetlands. Harris (1988) reported
steady declines in certain waterfowl species due to losses in wetland habitat including
a 35% decline in mallard (Anas platyrhynchos) and a 50% decline in northern pintail
(A. acuta) from 1955 to 1985. While mallard populations have stabilized in recent
years, northern pintail populations currently remain well below population objectives
by the North American Waterfowl Management Plan (Williams et al. 1999). This is
probably attributable to the loss of 38% of the prairie pothole wetlands in the U.S.
(Dahl 1990). Other studies have shown that wetland losses negatively affect
amphibian assemblages (Kolozsvary and Swihart 1999, Lehtinen et al. 1999,
Semlitsch 2002). Conversely, Hickman (1994) revealed increases in biodiversity at
locations where wetlands have been created or restored in a disturbed landscape.
Recognizing the significant values wetlands possess, federal, state, and local
agencies have embraced a �no net loss� policy (National Wetland Policy Forum
1988). This policy seeks to replace lost wetland habitat with new habitat by restoring
and/or constructing wetlands. The federal government defines mitigation activities to
5
include avoidance of impacts, minimization of impacts, site restoration, or
replacement of unavoidable losses (40 CFR Part 1508.20). Wetland mitigation may
compensate for losses caused by (1) agricultural practices that cause sedimentation,
soil subsidence, and herbicide and pesticide accumulations, (2) irrigation and urban
water developments, (3) construction of roads, levees, or canals, (4) wetland and
wildlife management practices including flooding, draw-downs, and farming, and (5)
industrial and military developments. The �no net loss� policy has helped maintain
the numerous benefits of wetlands and their surrounding ecosystems while
accommodating the need for human development.
Vegetation and wildlife use
The term indicator species is often used to describe a species whose presence
represents the health of a community (Robinson and Bolen 1989). Because no single
species can be used to assess the health of an entire community, it is important to
evaluate species-groups or representative taxa that have narrow environmental
tolerances (Graul and Miller 1984), and unique dietary needs that place them at
integral positions within trophic levels.
It is difficult, however, to identify, measure, interpret, or monitor indicators of
biodiversity. Lindenmayer et al. (2000) pointed out some problems associated with
taxon-based indicator species. First, certain taxa can have different responses to
disturbance (Davies and Margules 1998). Some indicators can have high threshold
responses to some environmental conditions, while others may have low thresholds.
In addition, they argue that marked changes in the abundance of some taxa are rarely
synchronous across all taxa. Weaver (1994) mentions that it is difficult to choose an
6
appropriate scale over which one taxa can indicate status of an associated taxa.
Indeed, studies show that caution should be used in determining which indicator
species to use in assessing biodiversity. However, the use of indicator species is
project-specific, whether being used to indicate presence of other species, to assess
human abiotic conditions such as pollution, to serve as early warning indicators of
environmental changes, or as in this study, to assess the the efficacy of efforts to
mitigate disturbance effects. Thus, although the arguments presented above are
legitimate with respect to some projects, general statements about the invalidity of
taxon-based indicator species should be avoided. Numerous studies have
successfully used taxon-based indicators to assess functions of created or restored
wetlands, many of which are discussed below.
My study includes all species within representative taxa (i.e., birds, anurans,
invertebrates) in its assessment of function and does not weigh the abundance of any
species or taxa more heavily than another; nor does it seek to use one species as a
representative or surrogate of another. This study compares diversity, richness, and
abundance of all species and/or taxa to assess the level at which created wetlands are
functioning. As mentioned, wetlands have numerous functions that relate to
hydrological, biogeochemical, and ecological processes. Vegetation, birds,
amphibians and macroinvertebrates are of particular importance when assessing
wetland health because they likely are intricately involved in the complex interactions
that contribute to these functions. They are relatively easy to sample, are conspicuous
by sight and sound, and simple to recognize in the field (Ralph et al. 1993, Casey and
Record, unpublished data, Dodson 2001). Hence, these species supply consistent and
7
reliable data sets that are compatible with field research. Mammals and reptiles were
excluded because of difficulty in adequate sampling. Instead, I used Habitat
Suitability Index models to evaluate habitat for select mammal and reptile species.
Wetland protection
Wetland destruction and degradation has plagued the United States for
decades. The wetland resource base in the 1980s was only 47% of what was present
in the 1780s (Dahl 1990), with a total loss of 47.3 million ha. This destruction is
largely due to the draining or filling of wetlands for agricultural purposes, which for
many years, was subsidized by policies of the federal government (National Research
Council 1995). A concern for the comprehensive protection of wetlands has been
embraced only within the past 2 decades, and the influx of political support for such
protection has resulted in landmark legislation aimed at preserving these valuable
ecosystems.
The Federal Water Pollution Control Act was passed in 1972 in an effort to
restore and maintain the chemical, physical, and biological integrity of the nation�s
navigable waterways. The Act was amended in 1977 as the Clean Water Act, which
included all waters in the U.S., from oceans to inland freshwater wetlands (33 CFR
320). Specifically, Section 404 of the Clean Water Act (40 CFR Part 230.1)
authorizes the Army Corps of Engineers to issue permits for dredging and filling
practices affecting wetlands. Permits issued by the government has promulgated the
construction of thousands of ha of wetlands in the U.S. as a requirement for
mitigation of wetland losses. The �no-net-loss� policy for wetlands endorsed in the
late 1980s, introduced wetland mitigation as the leading tool in combating wetland
8
loss in the U.S. (Jones and Boyd 2000, Mitsch and Gosselink 2000). Damages to
wetland functions have begun to be mitigation by creating compensatory wetlands
that must equal or exceed the functions of the damaged site (Zedler 1996).
Mitigation success
On paper, the �no net loss� policy appears to be working with a gain of about
50,000 ha of wetland and associated uplands in the U.S. from October 1993 to
September 1999 (Mitsch and Gosselink 2000). Caution must be taken, however,
because a net gain in wetland area yields little insight into the actual success of
wetland mitigation in terms of wetland function. Although no generally accepted
definition of mitigation success has been approved, the major focus of researchers has
been on the evaluation of wetland function as a measure of the success of mitigation
wetlands (Wentworth et al. 1988, Atkinson et al. 1993, Reinartz and Warne 1993,
Niswander and Mitsch 1995, Wilson and Mitsch 1996, Campbell et al. 2002).
Wetland functions are, indeed, useful in compensatory mitigation because they allow
expression of the multifaceted nature of ecosystems and provide perspectives around
which performance standards can be designed (Brinson and Rheindhardt 1996).
These standards often come in the form of wetland �templates�, called reference
wetlands, that can guide the design and monitoring of mitigation wetlands. Many
studies have incorporated reference wetlands into monitoring mitigation wetland
function (Confer and Niering 1992, Havens et al. 1995, Moore et al. 1999, Stolt et al.
2000, Campbell et al. 2002).
Several approaches to assessing wetland function have been used by
researchers. The first functional assessment technique for regulatory purposes
9
emerged from the U.S. Army Corps of Engineers in 1975. Functions incorporated by
the U.S. Army Corps of Engineers were public interest, support of food chains and
wildlife habitat, education and recreation, erosion prevention, reduction of storm or
flood damage, ground water discharge and recharge, water purification, and
maintenance of biodiversity (33 CFR 320.4). The Method for Wetland Functional
Assessment, also called FHWA (Federal Highway Wetland Assessment), was
developed by the Federal Highway Administration (Adamus 1983, Adamus and
Stockwell 1983) and directly ranks effectiveness, opportunity, and significance values
of wetlands. The Wetland Evaluation Technique (WET), a modification of FHWA,
ranks functional probabilities and considers physical, chemical, and biological
functions of wetlands including ground-water flow, flood flow alteration, sediment
stabilization, sediment/toxicant retention, nutrient removal/transformation, production
export, wildlife diversity/abundance, aquatic diversity/abundance, recreation, and
uniqueness/heritage (Adamus 1983, Adamus and Stockwell 1983). The
Environmental Monitoring Assessment Program (EMAP) of 1988 focuses on
determining the ecological function of a group of wetlands in a region by comparing
the function of a statistical sample of wetlands to reference wetlands (Novitzki et al.
1994). The Hydrogeomorphic (HGM) approach, developed by Brinson (1993)
incorporates features of the other 2 methods and includes the comparison of regional
wetland data sets based on geomorphic setting, water source, and hydrodynamics
health.
As mentioned, most researchers today embrace the use of reference wetlands
in assessing mitigation success. This technique assumes that reference wetland�s
10
structural components and physical, chemical, and biological processes have reached
a dynamic equilibrium that has enabled them to represent the highest, sustainable
functional capacity of a wetland (Smith et al. 1995). Researchers, therefore, can
define mitigation success in terms of whether constructed wetlands have developed
sustainable functional attributes similar to those that have been reached by reference
wetlands.
JUSTIFICATION
Wetland degradation and destruction has occurred in the U.S. for many
decades, but the need to compensate for these losses has only been realized within the
past 20 years. West Virginia has played an active role in wetland mitigation, but only
2 studies have been conducted in the state that have evaluated the functional attributes
of these wetlands (R.H. Fortney, West Virginia University unpublished report,
Johnson et al. 2000). A major aspect of this unpublished report included the
evaluation of wildlife and vascular plant communities as an indicator of the
development of biological and ecological attributes in mitigation wetlands towards
reference standards. This study was extremely valuable in evaluating wetland
function and success and set the stage for the development of future projects of
similar design. However, the study was relatively limited in scope and addressed
only 6 wetlands within a limited area.
The mitigation wetlands evaluated in this study, coupled with their respective
reference wetlands, provide an opportunity for the study of wetland function and
mitigation success across West Virginia. This study was a comprehensive evaluation
11
of 15 wetlands, and included an assessment of wildlife and plant communities and
wildlife habitat suitability. The results should further our knowledge of wetland
ecosystems by providing data that are regionally applicable to wetland protection and
management. These data also could be used to establish protocols for the continued
monitoring of these and other mitigation wetlands in West Virginia. Finally, this
study should be valuable in the selection of future mitigation projects that will have
the highest probability of success.
OBJECTIVES
The purpose of this study was to determine if the mitigation wetland sites in
West Virginia have developed ecological functions similar to naturally functioning
reference wetlands. The objectives were to:
1) compare vascular plant community composition and structure;
2) compare vascular plant species diversity and richness;
3) compare breeding bird diversity, richness, and abundance;
4) compare anuran species richness and abundance;
5) compare macroinvertebrate familial richness, diversity, density, and biomass;
and
6) evaluate habitat suitability for a variety of wildlife species using standardized
models.
It was hypothesized that natural wetlands would support more vegetation
species adapted to wet environments (i.e., more facultative and obligate wetland plant
species; see Chapter II for definitions). Thus, I anticipated that weighted averages
12
(Chapter II) would be lower in natural wetlands. Because it is likely that reference
wetlands are wetter relative to mitigation sites, and because mitigation sites tend to
provide more disturbed habitat, I expected natural wetlands to support less nonnative
plant species than mitigation wetlands. Hence, I predicted reference wetlands to have
a lower vascular plant species richness and diversity than mitigation wetlands.
Because the mitigation sites are ≥ 5 years old, with some ≥ 10 years, I
anticipated finding high species richness, diversity, and abundance of vascular plants
and wildlife in mitigation wetlands. Hence, I expected to find evidence that showed
mitigation wetlands are developing toward reference standards. However, due to the
proximity of mitigation sites to human disturbances (i.e., roads), and the relatively
limited development time of these sites towards natural conditions, I expected
wildlife indices to be higher in reference wetlands than in mitigation wetlands. I
predicted that habitat suitability would vary among each evaluated species between
mitigation and reference wetlands, but that overall, reference wetlands would score
higher habitat suitability indices for all evaluated species combined.
As such, the following null hypotheses were tested.
1. Vascular plant community composition and structure were similar between
mitigation and reference wetlands.
2. Vascular plant species diversity and richness were similar between mitigation
and reference wetlands.
3. Breeding bird diversity, richness, and abundance were similar between
mitigation and reference wetlands.
13
4. Anuran species richness, and abundance were similar between mitigation and
reference wetlands.
5. Macroinvertebrate familial richness, diversity, density, and biomass were
similar between mitigation and reference wetlands.
6. Habitat suitability indices for all evaluated species were similar between
mitigation and reference wetlands.
STUDY SITES
Overview of West Virginia
West Virginia can be classified into 3 regions (Fenneman 1938; Figure 1).
The unglaciated Western Hill section is the largest province in West Virginia, and
includes the Appalachian Plateau between the Ohio River and the mountainous area
to the east. It is a mature plateau with moderate to strong relief in the south
consisting of numerous rolling hills. Most of the hills in the northern and western
portions of the state are ≤ 450 m in elevation. Southern sections of this region,
however, reach elevations ≥ 900 m and can exceed 1,000 m.
The Allegheny Mountain section includes the high mountains that lie in the
Cheat River system and in the headwaters of the North Branch of the Potomac River.
This section contains the highest elevations in West Virginia with many ridges
reaching between 1,200 m and 1,375 m in elevation. The highest point in the state,
Spruce Knob on Spruce Mountain in Pendleton County, is located in this region and
peaks at 1,482 m. This section contains the Allegheny Mountains that extend
northward from West Virginia into western Maryland and central Pennsylvania.
14
These mountain ranges are oriented in a northeast-southwest direction with deep,
narrow valleys in between.
The Ridge and Valley province is located east of the Allegheny Front, and is
drained primarily by the Potomac River. This region is a lowland area that, as its
name implies, contains numerous interspersed ridges that form a narrow belt along
the eastern margin of the state. The elevation of valley floors ranges from 300 to 400
m with ridges reaching ≥ 1,219 m in elevation.
Fifteen wetlands were evaluated including 11 mitigation wetlands and 4
reference wetlands (Figure 1). The study sites were condensed into 4 areas for
comparison with each area containing 1 reference wetland, although for statistical
purposes, all mitigation sites were compared to all reference sites. Reference sites
were chosen for each area based on their similarity in geographic location, elevation,
size, vegetative structure, and hydrology to mitigation sites. Since the reference
wetlands are relatively larger than mitigation sites, only portions of reference sites
resembling conditions to mitigation wetlands were selected for study. Monthly
average temperature for 2001-2002 ranged from 3.3 to 21.4°C ( x = 10.3, SE = 0.6)
and monthly precipitation ranged from 2.9 to 22.3 cm ( x = 10.0, SE = 0.7; National
Weather Service 2003). A summary of mitigation and reference sites are provided in
Table 1. I also provided a list of Universal Transverse Mercator (UTM) coordinates
for vegetation, avian, and anuran sampling points for all wetlands in Table 2.
AREA 1
The 2 study sites in this area are located within the South Branch of the
Potomac River drainage basin. They are located within the Ridge and Valley
15
physiographic region, which is typified by lowland areas containing interspersed
ridges, and a parallel drainage pattern (Fenneman 1938). Average elevation is about
252 m. Both wetlands in this area were classified as palustrine emergent persistent
wetlands (Cowardin et al. 1979).
Altona Marsh reference wetland
This reference site was chosen to represent the Walnut Bottom mitigation
wetland. It is located in Jefferson County (4353000 N 768600 E, Middleway 7.5
minute quad) on the eastern panhandle of the state 2.5 km west of Charles Town off
State Route 51 (Figures 2 & 13). It is located within the Shenandoah River floodplain
at an elevation of 170 m. The size of the area chosen for study was 15.2 ha. This
wetland contains a marl substrate (mixture of clay, calcium, and magnesium
carbonate) overlaid on a bed of limestone. It is typified by open water areas (0.7 ha)
surrounded by seasonally flooded meadows dominated by herbaceous communities
(10.2 ha) of broad-leaved cattail (Typha latifolia), Baltic rush (Juncus balticus), and
marsh fern (Thelypterus palustris). Shrub thickets (2.8 ha) of glaucous willow (Salix
discolor) and silky cornel (Cornus amomum) are prevalent on the western portion of
the wetland, as well as forested communities (1.6 ha) consisting of sycamore
(Platanus occidentalis),, and white ash (Fraxinus. americana).
Walnut Bottom
This wetland was built by the Division of Highways (DOH) in 1997 as
mitigation for the construction of a major highway named Appalachian Corridor H. It
is located in Hardy County (4334210 N 673914 E, Old Fields 7.5 minute quad), 2.0
km north of Moorefield off U.S. Route 220 (Figures 3 & 14). Located on the South
16
Branch of the Potomac watershed, it is at an elevation of 335 m. Walnut Bottom is
9.5 ha in size and consists of 3 main cells separated by 2 dikes. The upper, middle,
and lower cells are about 2.5, 3.0, and 4.0 ha, respectively. Permanently flooded
open water ponds are surrounded by wet meadows consisting of emergent vegetation
dominated by cattail, spikerush (Eleocharis tenuis), and reed canarygrass (Phalaris
arundinacea).
AREA 2
Study sites in this area are located north of Canaan Valley within the Cheat
and Potomac River drainage basins. They also are located within the Appalachian
Plateaus physiographic region that is typified by high elevations within the Allegheny
mountains, and a dendritic drainage pattern (Fenneman 1938). The wetlands in this
area average 954 m in elevation, making them the highest elevation wetlands in the
study. All were classified as palustrine systems dominated by persistent emergents
(Elder Swamp, VEPCO [Virginia Electric Power Company], and Buffalo Coal) or
open water (Elk Run; Cowardin et al. 1979).
Elder Swamp reference wetland
This reference wetland was chosen to represent the VEPCO, Buffalo Coal,
and Elk Run mitigation wetlands. Elder Swamp is located in Tucker County
(4340000 N 642200 E, Mt. Storm Lake 7.5 minute quad) within the Blackwater River
watershed. It is located off State Route 93, about 8.0 km east of Thomas, at an
elevation of 1,000 m (Figures 4 & 15). Within Elder Swamp, the area chosen for
study was 28.0 ha in size (10.1 ha emergent, 6.5 ha open water, 9.9 ha scrub-shrub,
and 1.5 ha forest). This wetland has diverse habitats with extensive shrub thickets
17
consisting of speckled alder (Alnus incana) and red chokeberry (Pyrus arbutifolia) as
well as forested areas consisting of red spruce (Picea rubens). Emergent vegetation is
dominated by swamp dewberry (Rubus hispidis) and broad-leaved cattail.
VEPCO
Located in Tucker County (4337900 N 641300 E, Mt. Storm Lake 7.5 minute
quad) within the Blackwater River watershed at an elevation of 1,036 m, this site was
built in 1995 as mitigation for the creation of the Phase A Flue Gas Desulfurization
By-Product Facility by Virginia Power Electric Company at the Mount Storm Power
Station. The A-Frame Road mitigation site (referred to as VEPCO) is located about
0.8 km from the impact site off State Route 93 (Figures 4 & 16). It is only 3.0 km
from Elder Swamp. The total mitigation area is 7.0 ha in size, consisting of 5.9 ha
emergents, 0.9 ha open water, and 0.2 ha scrub-shrub areas. This site consists of 4
cells. The 3 cells east of the A-frame road are separated by a series of dikes and each
consists of 1 or 2 open water areas separated by temporarily flooded emergent
vegetation dominated by common rush (Juncus effusus). The cell to the west, also
dominated by common rush, contains 1 speckled alder community near the road. A
list of vegetation species planted at this site during construction is provided in Table
3.
Buffalo Coal
This wetland also is located in Tucker County (4332100 N 630900 E, Davis
7.5 minute quad) at an elevation of 940 m within the Cheat River basin in the
Blackwater River watershed. It was constructed in 1981 as mitigation for the
destruction of 12.1 ha of wetlands resulting from mining activities committed by
18
Davis Trucking Company. It is situated near the State Route 32 and 93 interchange
about 2.0 km from Thomas (Figure 5 & 17). It is 9.0 ha in size, consisting of 6.2 ha
emergents, 2.3 ha open water, and 0.5 ha scrub-shrub areas. This site consists of 4
open water ponds separated by semi-permanently flooded emergent areas dominated
by common rush and cattail. This site contains glade St. Johns Wort (Hypericum
densiflorum) and spiraea (Spiraea alba) shrub thickets.
Elk Run
This site is located within Grant County (4342000N 636250 E, Davis 7.5
minute quad) in the north branch of the Potomac River basin within the Elk Run
watershed (Figure 6 & 18). It was constructed in 1981 as mitigation for the Island
Creek Coal Company�s creation of the Alpine Mine Complex Treated Water
Impoundment. Elk Run is 3.8 ha in size consisting of 0.4 ha emergents, 3.3 ha open
water, and 0.1 ha scrub-shrub areas. It is located at an elevation of 840 m. This site
represents the enhancement and expansion of existing wetlands through the creation
of water control structures. Currently, it consists of 2 cells connected by a large dike.
The first cell is a large permanently flooded open water pond while the second cell is
temporarily flooded and dominated by rough arrowwood (Viburnum dentatum) and
cattail.
AREA 3
All 5 wetland study sites in this area are located within the Tygart Valley
River drainage basin within the towns of Buckhannon, Elkins, and Belington. They
also are located in the Appalachian Plateaus region as well as the extreme western
portion of the Allegheny Mountain physiographic region that is generally typified by
19
low hills and narrow valleys and a dendritic drainage pattern, similar to the Western
Hill section (Fenneman 1938). Mitigation wetlands in this area average 496 m in
elevation. All can be classified as palustrine emergent persistent wetlands, except for
Meadowville, which is scrub-shrub (Cowardin et al. 1979).
Meadowville reference wetland
This natural wetland was used as a reference site to represent the Leading
Creek, Sugar Creek, Sand Run, Triangle, and Trus Joist MacMillan mitigation
wetlands. This wetland is located in the Laurel Creek watershed in Barbour County
(4330920 N 593940 E, Nestorville 7.5 minute quad) just north of Meadowville off of
State Route 92 (Figure 7 & 19). It is part of a bottomland wetland complex along
Glady Fork, that is a tributary of Sugar Creek. At an elevation of 570 m, it is 6.6 ha
in size, consisting of 2.0 ha emergents and 4.6 ha scrub-shrub areas. This wetland has
a semi-permanently flooded to saturated hydrologic regime with diverse vegetative
cover composed of scrub-shrub and emergent vegetation. It is dominated by
graminoid and forb emergent (persistent) vegetation including sedges (Carex spp.),
rice cutgrass (Leersia oryzoides), and cattail. The wetland also contains well
developed shrub thickets containing spiraea, swamp rose (Rosa palustris), brookside
alder (Alnus serrulata), and silky cornel.
Leading Creek
This wetland is Located in Randoph County (4321563 N 602550 E, Montrose
7.5 minute quad), 1.0 km south of Montrose off of U.S. Route 219 (Figure 8). It is
located within the Leading Creek watershed at an elevation of 600 m. This wetland is
8.6 ha in size, consisting of 6.5 ha emergents, 1.9 ha open water, and 0.2 ha scrub-
20
shrub areas. This wetland was built in 1995 by DOH as mitigation for Corridor H.
This complex wetland consists of cells located on both sides of Leading Creek. The
first cell, located north of Leading Creek, contains diverse graminoid and forb
persistent emergent vegetation communities dominated by common rush and wool
grass (Scirpus cyperinus). The second major area, located south of Leading Creek,
can be further divided into 3 cells, all of which are open water ponds surrounded by
stands of common rush and cattail. A wet meadow dominated by common rush exists
west of the southern-most open water cell east of Leading Creek.
Sugar Creek Like Leading Creek, Sugar Creek was constructed in 1995 by the DOH as
mitigation for Corridor H. It is situated within the Laurel Creek watershed in Barbour
County (4328850 N 591470 E, Belington 7.5 minute quad; Figure 7). At an elevation
of 478 m, it is 6.8 ha in size, consisting of 5.1 ha emergents, 1.2 ha open water, and
0.5 ha scrub-shrub areas. This wetland contains an upstream section and a
downstream section. The upstream portion is a combination of small, excavated
depressions with open water or saturated soils and emergent herbaceous vegetation
dominated by reed canarygrass. Another 0.5 ha of area exists at the extreme upstream
portion of the wetland and is composed of patches of scrub-shrub and young forested
stands. Common species include laurel oak (Quercus laurifolia), crab apple (Pyrus
coronaria), hazelnut (Corylus americana), and hawthorn (Crataegus spp.) The
downstream section of the wetland included a large contiguous area containing both
vegetated and unvegetated ponds, as well as temporarily flooded areas dominated by
various sedges.
21
Sand Run This wetland was constructed by DOH in 1992 to mitigate for the construction
of Corridor H. Located in the Sand Run watershed, this site is 3.0 ha in size (2.0 ha
open water and 1.0 ha emergents), with about 0.4 ha of wetland existing before
construction. At an elevation of about 472 m, Sand Run is located in Upshur County
(4315060 N 573140 E, Buckhannon 7.5 minute quad) 6.8 km east of Buckhannon off
U.S. Route 33 between Sand Run River and an embankment on the north side of U.S.
Route 33 (Figure 9). It is about 8.0 km from the confluence of the Sand Run and
Buckhannon Rivers. The hydrologic regime varies dramatically during the growing
season. Sand Run does not have a persistent water source during summer months,
with about three quarters of the site having standing water during spring and summer,
and only one-sixth to one-fourth of the site having standing water in August.
Nonetheless, Sand Run can be described as a large open water pond that supports
common rush and cattail communities in its western section, along with a few
buttonbush (Cephalanthus occidentalis) shrubs.
Triangle
This wetland also was constructed in 1992 by DOH as mitigation for Corridor
H. It is 3.1 ha in size, 0.3 ha of which existed as a wetland prior to its construction.
This site consists of 2.5 ha emergents, 0.4 ha open water, 0.2 ha scrub-shrub areas and
a few patches of forested areas. It is located in Upshur County (4316950 N 568500
E, Century 7.5 minute quad) less than 1,000 m downstream of the Buckhannon city
limits on the floodplain of the Buckhannon River (Figure 10). It features 2 separate
sections: an upper section on the north side with an elevation of about 429 m, and a
22
lower section on the south end with an elevation of about 428 m. Three basic habitat
or vegetation types exist in both areas. These include marsh habitats dominated by
rice cutgrass and purple loosestrife (Lythrum salicaria) that are contiguous with open
water areas, scattered wet meadows dominated by cattail, and bottomland overflow
habitats that were located along the margins of the wetland.
Trus Joist MacMillan
This wetland was created in 1994 as mitigation for the construction of the
Trus Joist MacMillan engineered wood plant. Like Triangle, this site is located
within the Buckhannon River watershed in Upshur County (4318340 N 569560 E,
Century 7.5 minute quad) at an elevation of 430 m (Figure 10). It is 3.2 ha in size,
consisting of 1.9 ha emergents, 0.8 ha open water, and 0.5 ha scrub-shrub areas. This
site consists of 2 major sections. The eastern section is dominated by a moderately
fished open water pond with a few seasonally flooded emergent areas dominated by
common rush and cattail along the perimeter. The western section is dominated by
brookside alder (Alnus serrulata) and possesses small patches of marsh habitat
dominated by cattail and rice cutgrass.
AREA 4
Study sites in this area are located within the Western Hills physiographic
region that is typified by low hills and narrow valleys, and a dendritic drainage
pattern (Fenneman 1938). Located within the Little Kanawha and Gauley River
drainage basins, these sites average 500 m in elevation. Both constructed sites are
classified as palustrine unconsolidated bottom, while the reference site is palustrine
scrub-shrub (Cowardin et al. 1979).
23
Muddlety reference wetland This site is situated within the Muddlety Creek watershed at an elevation of
590 m. Located in Nicholas County (4248480 N 516790 E, Widen 7.5 minute quad),
this natural wetland was used as the reference site to represent the Enoch Branch and
Bear Run mitigation wetlands. Muddlety is located off U.S. Route 19 about 4.0 km
north of Summersville (Figure 11). It is a semipermanently flooded to permanently
flooded bottomland complex dominated by shrub thickets consisting of swamp rose
and silky cornel, as well as emergent marshes of burreed (Sparganium americanum)
and cattail. These areas are contiguous with 2 open water ponds surrounded by
smartweed (Polygonum hydropiperoides).
Enoch Branch This site was created by DOH in 1997 as compensatory mitigation for the
construction of U.S. Route 19 (Corridor L). It is located in Nicholas County
(4247300 N 514550 E, Widen 7.5 minute quad) off U.S. Route 19 (Figure 11). It is
about 1.5 km from the Muddlety reference wetland. Enoch Branch is situated in the
Muddlety Creek watershed at an elevation of 620 m. It contains 2 main cells totaling
3.4 ha in size, consisting of 1.0 ha emergents, 2.0 ha open water, and 0.4 ha scrub-
shrub areas. Both cells are semipermanently to permanently flooded open water
ponds with patches of common rush. The western cell contains brookside alder along
its perimeter.
Bear Run
This site was constructed as a mine reclamation project mitigating for the
Abandoned Mine Land Program in 1993. At an elevation of 265 m, the site is located
within the Little Kanawha River watershed about 4.0 km north of Sand Fork in
24
Gilmer County (4305780 N 519750 E, Glenville 7.5 minute quad; Figure 12). It is
6.2 ha in size, consisting of 1.4 ha emergents and 4.8 ha open water areas. This site
consists of a series of dikes and channels that connect 12 semi-permanent to
permanently flooded open water ponds, some of which are moderately used by
fisherman. Persistent emergent communities of spikerush (Eleocharis
quadrangulata) and cattail have been established at the 3 upper-most cells
(southeast).
QUALITY CONTROL
Plant identification was performed by experts in field botany: Dr. Ronald H.
Fortney, William N. Grafton, and Dr. James S. Rentch. Aquatic macroinvertebrate
familial taxonomy was performed by myself and confirmed by Dr. James T.
Anderson. Avian and anuran species calls were learned using various audiotapes and
confirmed by field technicians knowledgeable in respective taxa. If an avian species�
call could not be identified, it was recorded using a handheld tape recorder and
presented to Greg Forcey, an ornithologist at West Virginia University, for
identification. Dr. James T. Anderson reviewed all methodologies and techniques
incorporated into data collection for this project. Dr. George Seidel and James T.
Anderson assisted in all statistical analyses.
25
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ecology of bottomland hardwood swamps of the southeast: a community
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USA.
Williams, B. K., M. D. Koneff, and D. A. Smith. 1999. Evaluation of waterfowl
conservation under the North American Waterfowl Management Plan.
Journal of Wildlife Management 63:417-440.
Williams, J. D., and C. K. Dodd, Jr. 1979. Importance of wetlands to endangered
and threatended species. Pages 565-575 in P. E. Greeson, J. R. Clark, and J.
E. Clark, editors. Wetland functions and values: the state of our
understanding. American Water Resources Association, Minneapolis,
Minnesota, USA.
Wilson, R. F., and W. J. Mitsch. 1996. Functional assessment of five wetlands
constructed to mitigate wetland loss in Ohio, USA. Wetlands 16:436-451.
Zedler, J. B. 1996. Coastal mitigation in southern California: the need for a regional
restoration strategy. Ecological Applications 6:84-93.
32
CHAPTER I
TABLES
33
Table 1. List of 11 mitigation and 4 reference wetland study sites in West Virginia, including site name, year constructed, size
(ha), source builder, Universal Transverse Mercator (UTM) coordinates, 7.5 minute quadrangle, basin, and watershed, 2001-
2002.
Site name Year Size (ha) Source UTM Y UTM X Quad Basin Watershed
Altona Marsha N/A 15.2 N/A 4353000 768600 Middleway Shenandoah River Shenandoah River Walnut Bottom 1997 9.5 Division of Hwys 4334210 673914 Old Fields S. Branch of Potomac R. S. Branch of Potomac R.
Elder Swamp N/A 28.0 N/A 4340000 642200 Mt. Storm Lake Cheat River Blackwater River VEPCO 1995 7.0 VA Electric Power 4337900 641300 Mt. Storm Cheat River Blackwater River Buffalo Coal 1981 9.0 Davis Trucking Co. 4332100 630900 Davis Cheat River Blackwater River Elk Run 1981 3.8 Island Crk Coal Co. 4342000 636250 Davis N. Branch of Potomac R. Elk Run
Meadowville N/A 6.5 N/A 4330920 593940 Nestorville Tygart Valley Laurel Creek Leading Creek 1995 8.6 Division of Hwys 4321563 602550 Montrose Tygart Valley Leading Creek Sugar Creek 1995 6.8 Division of Hwys 4328850 591470 Belington Tygart Valley Laurel Creek Sand Run 1992 3.0 Division of Hwys 4315060 573140 Buckhannon Tygart Valley Sand Run Triangle 1992 3.1 Division of Hwys 4316950 568500 Buckhannon Tygart Valley Buckhannon River Trus Joist MacMillan 1994 3.2 TJM Timber Co. 4318340 569560 Century Tygart Valley Buckhannon River
Muddlety N/A 10.4 N/A 4248480 516790 Widen Gauley River Muddlety Creek Enoch Branch 1997 3.4 Division of Hwys 4247300 514550 Widen Gauley River Muddlety Creek Bear Run 1993 6.2 WV Dept Env. Prot. 4305780 519750 Glenville Little Kanawha Little Kanawha a Site names in bold indicate reference wetlands for mitigation wetland sites (listed below) in each of 4 areas
34
Table 2. Universal Transverse Mercator (UTM) coordinates of frog, bird, and
vegetation sampling locations for 11 reference and 4 mitigation wetlands of West
Virginia, 2001-2002.
Sampling Frog Bird Vegetation Site Location UTM x UTM y UTM x UTM y UTM x UTM y
Altona Marsh 1 769021 4353041 768650 4353220 768910 4353968 2 768895 4353102 768895 4353102 768822 4353990 3 768765 4353166 769021 4353041 768519 4354049 4 768650 4353220 Bear Run 1 519909 4305421 520030 4305259 519931 4305302 2 519568 4305630 519823 430511 519993 4305220 3 519385 4305645 519834 4306012 4 519745 4305835 519864 4306208 5 519834 4306012 519385 4305645 6 519864 4306208 7 519860 4306457 8 519778 4306668 9 520028 4305216 Buffalo Coal 1 630468 4332098 630468 4332098 630586 4332228 2 630615 4332393 630615 4332393 630473 4332276 3 630550 4332301Elder Swamp 1 642831 4340116 642938 4340275 642855 4340183 2 642655 4340014 642455 4339898 642283 4339944 3 642938 4340275 642244 4340061 4 642455 4339898 642715 4340215 5 642560 4340127 6 642902 4340162Elk Run 1 635944 4341361 635944 4341361 635908 4341459Enoch Branch 1 514750 4247118 514750 4247118 514298 4247610 2 514725 4247588 514725 4247588 514329 4247575 3 514451 4247598 4 4E+06 514445 Leading Creek 1 602411 4321303 602416 4321263 602443 4321238 2 602419 4321176 602427 4321029 602383 4320929 3 602433 4321030 602388 4320824 602428 4321316 4 602451 4320910 602681 4321442 602318 4320657 5 602376 4320763 602414 4321077 6 602670 4321444 602652 4321213
35
Sampling Frog Bird Vegetation Site Location UTM x UTM y UTM x UTM y UTM x UTM y
7 602706 4321285 602613 4321207 8 602659 4321164 9 602618 4321153Meadowville 1 593788 4331027 593848 4330999 594089 4331112 2 593953 4331014 594102 4330912 594021 4331138 3 594102 4330912 594062 4331077 4 594080 4330830Muddlety 1 516686 4248376 516686 4248376 516701 4248734 2 516802 4248364 516769 4248376 516686 4248411 3 516719 4248751 Sand Run 1 573089 4315098 573089 4315098 572978 4315016 2 573102 4315024 3 573054 4315069Sugar Creek 1 591662 4328892 591662 4328892 591566 4328808 2 591566 4328885 591610 4328547 591575 4328902 3 591454 4328883 591345 4328874 4 591337 4328886 591337 4328829 5 591445 4328823 591450 4328780 6 591517 4328773 7 591570 4328540 8 591834 4328184 Trus Joist MacMillan 1 569507 4318093 569655 4318004 569666 4318077 2 569370 4318072 569554 4318107 3 569798 4318046 4 569565 4318016Triangle 1 568425 4316961 568425 4316961 568297 4316864 2 568361 4316886 3 568504 4316956 4 568543 4316977 5 568417 4316910VEPCO 1 641389 4337912 641233 4337916 641485 4337864 2 641233 4337911 641130 4337811 641299 4337910 3 641137 4337809 641156 4337958 4 641038 4337903 641097 4337786Walnut Bottom 1 673892 4334147 673888 4334197 674333 4334501 2 674009 4334281 674038 4334339 674271 4334480 3 674172 4334339 674239 4334576 4 674174 4334679
Table 2. Continued.
36
CHAPTER I
FIGURES
37
Figure 1. Study site locations for 11 mitigation and 4 reference wetlands in West
Virginia, 2001-2002.
38
Figure 2. Location of the Altona Marsh reference wetland on the Middleway 7.5
minute quadrangle, West Virginia, 2001-2002.
39
Figure 3. Location of the Walnut Bottom mitigation wetland on the Old Fields 7.5
minute quadrangle, West Virginia, 2001-2002.
40
Figure 4. Location of the Elder Swamp reference wetland and the VEPCO mitigation
wetland on the Mt. Storm 7.5 minute quadrangle, West Virginia, 2001-2002.
41
Figure 5. Location of the Buffalo Coal mitigation wetland on the Davis 7.5 minute
quadrangle, West Virginia, 2001-2002.
42
Figure 6. Location of the Elk Run mitigation wetland on the Davis 7.5 minute
quadrangle, West Virginia, 2001-2002.
43
Figure 7. Location of the Meadowville reference wetland and the Sugar Creek
mitigation wetland on the Nestorville 7.5 minute quadrangle, West Virginia, 2001-
2002.
44
Figure 8. Location of the Leading Creek mitigation wetland on the Montrose 7.5
minute quadrangle, West Virginia, 2001-2002.
45
Figure 9. Location of the Sand Run mitigation wetland on the Buckhannon 7.5
minute quadrangle, West Virginia, 2001-2002.
46
Figure 10. Location of the Triangle and Trus Joist MacMillan mitigation wetlands on
the Century 7.5 minute quadrangle, West Virginia, 2001-2002.
47
Figure 11. Location of the Muddlety reference wetland and the Enoch Branch
mitigation wetland on the Widen 7.5 minute quadrangle, West Virginia, 2001-2002.
48
Figure 12. Location of the Bear Run mitigation wetland on the Glenville 7.5 minute
quadrangle, West Virginia, 2001-2002.
49
Figure 13. Photograph of the Altona Marsh reference wetland, West Virginia,
summer, 2001.
Figure 14. Photograph of the Walnut Bottom mitigation wetland, West Virginia,
summer, 2001.
50
Figure 15. Photograph of the Elder Swamp reference wetland, West Virginia,
summer, 2001.
Figure 16. Photograph of the VEPCO mitigation wetland, West Virginia, summer,
2001.
51
Figure 17. Photograph of the Buffalo Coal mitigation wetland, West Virginia,
summer, 2001.
Figure 18. Photograph of the Elk Run mitigation wetland, West Virginia, early
spring, 2001.
52
Figure 19. Photograph of the Meadowville reference wetland, West Virginia,
summer, 2001.
Figure 20. Photograph of the Leading Creek mitigation wetland, West Virginia,
winter, 2001.
53
Figure 21. Photograph of the Sugar Creek mitigation wetland, West Virginia,
summer, 2001.
Figure 22. Photograph of the Sand Run mitigation wetland, West Virginia, summer,
2001.
54
Figure 23. Photograph of the Triangle mitigation wetland, West Virginia, summer,
2001.
Figure 24. Photograph of the Trus Joist MacMillan mitigation wetland, West
Virginia, summer, 2001.
55
Figure 25. Photograph of the Muddlety reference wetland, West Virginia, summer,
2001.
Figure 26. Photograph of the Enoch Branch mitigation wetland, West Virginia,
summer, 2001.
56
Figure 27. Aerial photograph of the Bear Run mitigation wetland, West Virginia,
fall, 2001.
57
CHAPTER II
A COMPARISON OF VEGETATION COMMUNITITES IN
MITIGATION AND NATURAL WETLANDS IN THE MID-
APPALACHIANS
COLLINS K. BALCOMBE balcster@hotmail.com
West Virginia University Division of Forestry
PO Box 6125 Morgantown, WV 26505-6125
58
ABSTRACT
Wetland destruction has plagued the U.S. for decades, and the need to
compensate for these losses has only been embraced within the last 20 years.
Because so many compensatory mitigation wetlands have been created, there is a
need to assess the success of these valuable ecosystems. The goal of this study was to
evaluate the relative success of mitigation wetlands in West Virginia in supporting
hydrophytic vegetation communities. Naturally occurring reference wetlands were
used to compare vegetation community structure among 11 mitigation sites
throughout the state. Comparisons were made using a 2 × 2 factorial analysis of
variance (ANOVA) following PC-ORD software analyses. For all species sampled,
mean total percent cover across all sampling quadrats per wetland was similar
between mitigation ( x = 39.2, SE = 6.09) and reference ( x = 54.4, SE = 9.03)
wetlands (P = 0.195; Table 3). Species richness (P = 0.035), evenness (P = 0.033),
and diversity (P = 0.025) were higher in mitigation (richness: x = 12.9 species/plot,
SE = 1.07, evenness: x = 0.32, SE = 0.03, diversity: x = 1.83, SE = 0.11) than
reference (richness: x = 8.25, SE = 1.59, evenness: x = 0.17, SE = 0.05 diversity: x
= 1.29, SE = 0.17) wetlands. Mean weighted averages were similar between
mitigation ( x = 0.65, SE = 0.11) and reference ( x = 0.89, SE = 0.16) wetlands (P =
0.242). Differences in species composition between wetland types were reflected
through ordination using Detrended Correspondence Analysis (DCA). Ordination
also yielded correlations between species composition and age of mitigation
wetlands. Although mitigation and reference sites contained similar numbers of
This chapter is written the style of Ecological Applications.
59
nonnative species (P > 0.05), an evaluation of native species only yielded similar
species richness and evenness indices between wetland types (P > 0.05). Both
mitigation and natural wetlands met criteria for hydrophytic vegetation according to
the 1987 U.S. Army Corps of Engineers Wetland Delineation Manual. These data
suggest that mitigation wetlands in West Virginia adequately support hydrophytic
vegetation and appear to be developing towards reference standards.
Key words: constructed wetland, mitigation wetland, man-made wetland,
reference wetland, wetland mitigation, wetland management, hydrophytic vegetation
INTRODUCTION
Wetlands are extremely valuable to both people and wildlife. They provide
such functions as flood storage, ground-water recharge, nutrient cycling, pollutant
removal, and wildlife and recreational habitat (Mitsch and Gosselink 2000).
Unfortunately, there has been a > 50% decline in the U.S. wetland resource base
within the past 200 years (Dahl 1990). It was not until 1977, with the passage of
amendments to the Clean Water Act, that wetlands began to be protected (33 CFR
320). Specifically, Section 404 of the Clean Water Act (40 CFR Part 230.1)
authorized the Army Corps of Engineers to issue permits for dredging and filling
practices affecting wetlands. Permit requirements outlined by the government have
promulgated the construction of thousands of hectares of wetlands in the U.S. as a
need to mitigate for wetland losses. The �no-net-loss� policy for wetlands was
endorsed in the late 1980s, and it introduced wetland mitigation as the leading tool in
60
combating wetland loss in the U.S. (Jones and Boyd 2000, Mitsch and Gosselink
2000).
Because so many compensatory wetlands have been created, there is a need to
assess the success of these wetlands. But monitoring of mitigation wetlands has been
sporadic, and various mitigation programs have lacked the tools necessary to enforce
and monitor mitigation success (Lewis 1992, National Research Council 2001).
Those that have evaluated success found that permit-linked mitigation projects had
low success rates (Eliot 1985, Race 1985, Mager 1990, Holland and Kentula 1992,
Zedler and Callaway 1999, Robb 2002). One problem stems from the definition of
mitigation success itself, which often varies by project objectives. Whether these
objectives include the adequate development of soils or hydrology or the ability to
support wildlife, most researchers agree that mitigation wetland function should equal
or exceed those functions lost to development or destruction. Thus, a concerted effort
is underway to evaluate a variety of mitigation wetland functions in hopes of
understanding the dynamics involved in adequately replacing lost wetland function.
Vegetation community structure provides a valuable indicator of wetland
function. Vegetation plays a distinct role in the identification of wetlands (Hall and
Penfound 1939, Penfound 1952, Martin et al. 1953, Dix and Smeings 1967), and is
currently used in wetland delineation (USACE 1987, Tiner 1999). Research has
shown that higher structural diversity of vegetation leads to higher wildlife species
diversity (MacArthur and MacArthur 1961, Evans and Wilson 1982, Anderson et al.
1999, King et al. 2000, Naugle et al. 2000). Vegetation within wetlands is important
because its composition determines (1) type, quantity, and nutritive quality of plant
61
foods available (De Szalay and Resh 1997, Anderson and Smith 1998), (2)
distribution, density, and structure of cover (Hays et al. 1981, Anderson et al. 1999),
(3) quantity and type of substrate for invertebrates (Murkin et al. 1992, Anderson and
Smith 1999, 2000, King et al. 2000), and (4) water chemistry (Goslee et al.1997,
Castelli et al. 2000). For these reasons, vegetation analysis has been widely used to
assess wetland function (Wentworth et al. 1988, Reinartz and Warne 1993, Wilson
and Mitsch 1996, Goslee et al. 1997, Castelli et al. 2000, Campbell et al. 2002).
An evaluation of wetland function provides limited insight into mitigation
success unless a standard of comparison is used to gauge the relative success of
mitigation wetlands in performing a specific function. In an effort to evaluate the
success of created and restored wetlands, numerous studies evaluating a range of
wetland functions have embraced the use of naturally occurring reference wetlands to
represent optimal habitat conditions (Brinson 1993, Brinson and Rheinhardt 1996,
Wilson and Mitsch 1996, Ashworth 1997, Brown and Smith 1998, Stolt et al. 2000).
Likewise, much research has been conducted on the structure and composition of
vegetation communities in mitigation wetlands relative to reference wetlands (Confer
and Niering 1992, Parikh and Gale 1998, Brown 1999, Moore et al. 1999, Campbell
et al. 2002).
Few studies, however, have been conducted on wetland function and
mitigation success in the Appalachians, and only 1 major study was conducted in
West Virginia (R. H. Fortney, unpublished report), and it was limited in scope and
only evaluated 3 constructed wetlands. It is clear that an evaluation of vegetation
communities should provide valuable insight into the framework needed to monitor
62
mitigation success in the future. As such, I tested the null hypothesis that wetland
vegetative community composition and structure was similar between mitigation and
natural (reference) wetlands in West Virginia.
METHODS
Study sites
This study was conducted in West Virginia, which is situated in the mid-
Appalachian region of the U.S. Fifteen wetlands were evaluated across the state
including 11 mitigation (Walnut Bottom, VEPCO, Buffalo Coal, Elk Run, Leading
Creek, Sugar Creek, Sand Run, Triangle, Trus Joist MacMillan, Enoch Branch, and
Bear Run) wetlands and 4 reference (Altona Marsh, Elder Swamp, Meadowville, and
Muddlety) wetlands (Chapter I). All mitigation sites were constructed except for
Triangle, Elk Run, and Sand Run, which were combinations of created and restored
wetlands. The study sites were condensed into 4 areas for comparison with each area
representing a different geomorphic setting within the state. One reference wetland
was chosen for each area based on its similarity in location, elevation, size, vegetative
structure, and hydrology to mitigation sites. Since the reference wetlands are
relatively larger than mitigation sites, only portions of reference sites resembling
conditions to mitigation wetlands were selected for study.
Mitigation study sites were created as compensation for such human activities
as industrial development, mining, or road construction. Almost every wetland was
located near some form of human disturbance, with many lying adjacent to roads with
moderate to heavy traffic. To allow for a standardized minimum time of
63
development, all sites chosen were ≥5 years old. Sites ranged in age from 5-21 years
old ( x = 10.0, SE = 1.7) and in size from 3.0 to 9.5 ha ( x = 5.8, SE = 0.8). Elevation
ranged from 265-1,036 m ( x = 586, SE = 75.9). All were classified as palustrine
emergent or unconsolidated bottom wetlands (Cowardin et al. 1979).
Reference sites were selected based on their similarity in structure and
proximity to the mitigation sites. They ranged in elevation from 170-1,000 m ( x =
582, SE = 169.5), and size ranged from 6.5- 28.0 ha ( x = 15.1, SE = 4.7). All were
classified as palustrine emergent or palustrine scrub-shrub wetlands (Cowardin et al.
1979). Detailed mitigation and reference site descriptions are provided in Chapter I.
Vegetation community sampling
Vegetation sampling occurred in June and July of 2001, and in July of 2002.
Sampling was conducted according to Stephenson and Adams (1986). Plant
communities were first stratified based on distinct communities present.
Representative communities were sampled using randomly placed permanently
marked 0.05 ha quadrats (25 × 20 m). At each wetland, at least 1 quadrat was used to
sample each distinct plant community. More quadrats were established depending on
the size and variability of the community.
Within each quadrat all live stems of trees (≥ 10 cm diameter at breast height,
DBH) and small trees (2.5 to 9.9 cm DBH) were measured at dbh and counted to
species. In addition, saplings (individuals < 2.5 cm DBH but ≥ 1.0 m tall) were
counted. Within each 0.05 ha quadrat, 2 5.0 × 5.0 m plots were placed evenly along
the center line of the transect. Within these plots, seedlings (individuals > 10 cm but
64
less than < 1.0 m tall) and shrubs (including woody vines) were counted to species.
Five 1.0 × 1.0 m plots were placed along the same center line. Within these plots,
small seedlings (individuals ≤ 10 cm tall) were counted to species. In addition,
percent cover of herbaceous plants, exposed substrate, woody debris, and bryophytes
were recorded. Plant identifications were made using Radford et al. (1968),
Strausbaugh and Core (1977), and Gleason and Cronquist (1991). Nomenclature and
taxonomic authority were based on Kartesz (1999). All cover values for herbaceous
plants were estimated using the following cover class rating scale: 1-5% = 1, 6-25% =
2, 26-50% = 3, 51-75% = 4, 76-95% = 5, 96-100% = 6 (Daubenmire 1968). Percent
of hydrophytic vegetation sampled within quadrats also was calculated following the
basic rule in the 1987 U.S. Army Corps of Engineering Wetland Delineation Manual
(USACE 1987).
Vegetation mapping was conducted using a Geographic Information System
(GIS) and ArcView software. Maps of dominant vegetation communities were
mapped on aerial photos (1.0 m resolution) taken by the West Virginia Natural
Resources Analysis Center (NRAC) during leaf off in 2001 and 2002. If recent aerial
photography was unavailable, vegetation communities were digitized on 1996-1997
digital ortho-quarter quads (DOQQs) obtained from the West Virginia Department of
Environmental Protection (DEP). Wetlands also were classified and digitized
according to Cowardin et al. (1979).
Data analyses
Mitigation and reference wetlands were compared by calculating species
richness, diversity, and evenness using PC-ORD software (McCune and Mefford
65
1999) for each quadrat within the wetlands. Statistics were calculated for all species
combined and for native species only. Native species status was assigned based on
Harmon and Ford-Werntz (2002). Diversity was calculated using the Shannon-
Weiner Index (Shannon and Weaver 1949). Average cover was calculated for each
species and totaled to get a total coverage for each quadrat. These values were
averaged to obtain mean total coverage for each wetland. In addition, each species
was assigned the following wetland indicator status (WIS) values: Obligate = 1,
Facultative Wetland = 2, Facultative = 3, Facultative Upland = 4, and Upland = 5
(U.S. Fish and Wildlife Service 1996). From coverage and WIS values, weighted
averages (Carter et al. 1988, Wentworth et al. 1988, and Atkinson et al. 1993) were
calculated based on the following formula:
Weighted average = (y1u1 + y2u2 + ��.ymum)/100
where y1y2 = relative basal area (trees and small trees) or relative cover estimates
(herbaceous plants) for each species, and u1u2 = the WIS for each species (Atkinson et
al. 1993). Also using PC-ORD software, Detrended Correspondence Analysis (DCA)
was used to graphically evaluate similarities in vegetative composition (Hill 1979).
Detrended Correspondence Analysis is an eigenanalysis ordination technique that
uses reciprocal averaging and chi-square distance measures to spatially organize
vegetation quadrats based on species composition. Average cover values were used
as inputs in DCA and all rare species were downweighted.
A 2×2 factorial analysis of variance (ANOVA) model was used in SAS (SAS
Institute 1988) with area as a blocking factor. The independent variables tested were
year, type (mitigation vs. reference), and year× type interactions with dependent
66
variables being total cover, richness, diversity, evenness, and weighted averages.
Assumptions of normality were tested with the univariate procedure in SAS, and
Levene�s Test was used for homogeneity of variances. Square-root and quarter-root
transformations were used to convert dependent variables that did not meet the
aforementioned assumptions (Dowdy and Wearden 1991).
RESULTS
A total of 175 plant species was recorded in 60 quadrats within both
mitigation and reference wetlands (Appendix 1). In mitigation sites, 129 species were
recorded in 45 quadrats, 23 of which were nonnative (17.8%; Appendices 2-12).
Within reference sites, 62 species were sampled in 15 quadrats, 2 of which were
nonnative (3.2%; Appendices 13-16). Overall, the number of nonnative species were
not different in mitigation and reference wetlands (F1,10 = 3.22, P = 0.103; Table 1).
A total of 123 species were observed (seen) but not sampled in mitigation quadrats,
and 34 species were observed but not sampled in reference quadrats. A list of
vegetation species planted during wetland construction is provided in Appendix 17.
For all species sampled, total average cover was similar between mitigation
and reference wetlands (F1,10 = 1.93, P = 0.195; Table 1). Mean species richness
(F1,10 = 5.97, P = 0.035), evenness (F1,10 = 6.15, P = 0.033), and diversity (F1,10 =
6.92, P = 0.025) were higher in mitigation wetlands (Table 1). Mean weighted
averages were similar between wetland types (F1,10 = 1.54, P = 0.242).
Different results were obtained upon evaluating species native only to West
Virginia. Species richness (F1,10 = 4.7, P = 0.055) and evenness (F1,14 = 4.44 , P =
67
0.061) were similar between mitigation and reference wetlands (Table 1). However,
species diversity remained higher in mitigation wetlands (F1,10 = 5.15, P = 0.047).
Percent of species by wetland indicator status were calculated for all species,
both sampled and observed but not sampled, within quadrats (Table 1). Although
83.8% of the vegetation sampled was hydrophytic in mitigation wetlands, and 94.3%
was hydrophytic in reference wetlands, no difference was detected between wetland
types (F1,10 = 2.89, P = 0.119).
Results of Detrended Correspondence Analyses are shown in Figures 1-4.
Each point on the graph represents individual quadrats. Points that are close together
represent quadrats that have similar species composition, while points that are further
apart indicate quadrats that share fewer species in common. Ordination for all 60
quadrats in both wetland types are displayed in Figure 1 for all herbaceous species
and in Figure 2 for native species only. In Figure 1, mitigation sites were ordinated
below Axis 1, while reference sites were located above the axis (Axis 1: R2 = 0.08;
Axis 2: R2 = 0.18). The two major groupings along this axis reflect differences in
vegetative composition between mitigation and reference wetlands. Similarly,
mitigation sites appeared to show correlation with Axis 2, whereas reference sites
were concentrated in the upper right section of the ordination with a slight correlation
with axis 2. Figure 2 represents an ordination of native species only. Similar to
Figure 1, mitigation sites were ordinated below Axis 1 and appeared to show
correlation with Axis 2 (Axis 1: R2 = 0.07; Axis 2: R2 = 0.18). However, the
differences in clusters are less pronounced between wetland types, indicating a more
similar vegetation composition of native species.
68
Figures 3 and 4 represent ordination with wetland age as a secondary matrix
for all 45 plots within mitigation wetlands. Figure 3 represents ordination of
vegetation plots with wetland age as a categorical variable where wetlands were
evaluated based on whether they were < 10 years old or ≥ 10 years old. This figure
reveals a cluster of older wetlands in the bottom center of the ordination, while
younger wetlands are dispersed more evenly over the entire graph (Axis 1: R2 = 0.41;
Axis 2: R2 = 0.25). Thus, species composition appears to be more similar within
older wetlands than within younger ones. Figure 4 represents ordination of plots with
the actual age of every vegetation plot. This figure also supports the assertion that
wetland age affects species composition. Based on the ordination, wetland age is
correlated with axis 2 along an age gradient where older wetlands are situated on the
bottom of the graph and younger wetlands are located towards the top (Axis 1: R2 =
0.41; Axis 2: R2 = 0.25).
Submerged aquatic vegetation successfully developed at 10 of 11 mitigation
sites. Only VEPCO lacked submerged aquatic vegetation. These included such
species as water thread pondweed (Potamogeton diversifolius Raf.) and snailseed
pondweed (P. spirillus Tuck.). Woody vegetation also had been established, either
within or along the perimeter, at 10 of 11 constructed sites (Walnut Bottom lacked
shrubs). Dominant shrub species included alder (Alnus serrulat. Spreng.), St. John�s
wort (Hypericum densiflorum L.), and buttonbush (Cephalanthus occidentalis L.).
All 4 reference sites supported relatively more dense shrub thickets than mitigation
sites. Dominant shrub communities within reference sites consisted of silky cornel
(Cornus amomum Mill.), alder, arrow-wood (Viburnum recognitum Fern.), and
69
swamp rose (Rosa palustris Marsh.). Geographic Information System maps
representing dominant vegetation with bird, frog, and vegetation sampling points, as
well as Cowardin et al. (1979) wetland classifications for all 15 wetlands are in
Appendices 18-32.
DISCUSSION
It appears that hydrophytic vegetation has successfully been established at the
constructed wetland sites I evaluated in the mid-Appalachians. It is not surprising
that hydrophytic vegetation has been established so early in mitigation sites. Studies
show that hydrophytic vegetation often establishes within 3 to 5 years after
construction (Erwin and Best 1985, Confer and Niering 1992, Reinartz and Warne
1993, Mitsch et al. 1998, Brown 1999). Some studies have shown reference wetlands
to have more vegetative cover than constructed sites, which can be attributed to
differences in maturity (Confer and Niering 1992, Havens et al. 1995, Brown 1999).
However, I found similar vegetation coverage between wetland types. Indeed, this
could indicate vegetation development toward reference standards, but these wetlands
are relatively young and unstable, and as such, support a wider variety of species that
have adapted to these disturbed environments. This is supported by the higher
species richness and diversity found in mitigation sites. Furthermore, almost every
constructed site (except VEPCO and Buffalo Coal) is adjacent or connected to
streams, rivers, or other wetlands, that can act as seed sources for pioneer species.
Other studies also have shown higher species richness in constructed wetlands
(Parikh and Gale 1998). However, Jarman et al. (1991) and Brown (1999) found
70
similar richness values between wetland types in Massachusetts and New York,
respectively, and Campbell et al. (2002) found lower species richness in created
wetlands than in natural wetlands in Pennsylvania. Although age was a factor in
determining species richness among mitigation sites (younger sites displayed higher
species richness), location to seed sources probably accounted for lower richness in
mitigation sites overall in Pennsylvania (Campbell et al. 2002). Reinartz and Warne
(1993) also observed correlations with distance to seed sources. They found
decreases in species richness and diversity with increasing distance to nearest wetland
seed source. Indeed, nearby wetlands and streams can be excellent vectors of plant
propagules. As such, special plantings of herbaceous and woody vegetation, except
for initial vegetative cover and erosion control, may not be needed for certain
constructed wetlands. However, some newly created wetlands should be seeded with
native wetland species to prevent monoculture development and increase overall
diversity (Levine and Willard 1990, Reinartz and Warne 1993).
Evenness also was higher in mitigation sites. Hence, although mitigation sites
supported a higher number of species and a greater diversity than reference sites,
individual species were more evenly distributed among quadrats in mitigation sites.
Since reference sites are more stable, well-adapted species have been allowed
sufficient time to exclude species. Consequently, certain species display a clear
dominance over others. Some common dominant species that occurred at reference
sites included blue-joint grass (Calamagrostis canadensis Michx.), rice cutgrass
(Leersia oryzoides L.), marsh fern (Thelypteris palustris Schott), cattail (Typha
latifolia L.), and boat-leaved sphagnum (Sphagnum palustre L.). Cattail, for instance,
71
is tall at maturity, and has a low photosynthetic area with a clonally-spreading root
system. This allows it to form vegetative monocultures (Boutin and Keddy 1993).
Although cattail was prevalent in mitigation wetlands, monocultures had not yet
developed, except perhaps in Triangle. It will be important to monitor the spread of
this species since it is known to inhibit the development of diverse vegetation
communities by excluding other native species� colonization (Erwin 1990).
Overall, submerged aquatic vegetation (SAV) has successfully established
within most mitigation sites. One of the sites that contained minimal (0.7%) SAV
(Trus Joist MacMillan) supported a population of carp (Cyprinus carpio L.), which
are known to feed on SAV (McKnight and Hepp 1995). The VEPCO site probably
lacked SAV for a variety of reasons. These include light availability due to
suspended solids or chlorophyll concentrations, or other physical, geological, or
geochemical parameters (Koch 2001). Submerged aquatic vegetation has been on the
decline for many years and is known to increase water quality (Dennison et al. 1993).
As well, it is a vital component to the diet of numerous waterfowl species (McKnight
and Hepp 1995). The success of mitigation wetlands in West Virginia in supporting
SAV should be monitored to ensure the continued benefits associated with these
valuable wetland plant species.
The presence of woody vegetation was confirmed at almost every mitigation
wetland. Even the youngest site (5 years old; Enoch Branch) contained brookside
alder (Alnus serrulata) communities in and around the wetland, but I suspect that this
species was planted during construction based on linear stocking patterns along the
perimeter. However, another wetland of the same age (Walnut Bottom) did not
72
contain woody vegetation. Data on vegetation plantings were unavailable for this
site. There is a possibility that no shrubs were planted during its construction, so this
site simply may be too young to have developed shrub thickets. This is not surprising
considering woody vegetation generally takes longer to develop in constructed sites
(Niswander and Mitsch 1995). Shrub development has possibly been minimized at
Bear Run due to design constraints. This site consists of a series of steeply graded
open water ponds that have created hydrologic gradients incompatible with shrub
growth.
Although no statistical difference was detected in the number of nonnative
species between constructed and natural wetlands, the number of nonnative species
was higher in mitigation sites. In fact, only 2 nonnative species were observed at 1
reference site (Meadowville), whereas a combined total of 23 species were observed
at 10 of 11 constructed sites. The minimal coverage of hydrophytic vegetation, along
with a relatively small sampling effort (1 transect established), may explain why Bear
Run appears to lack nonnative species. The most common nonnative species were
purple loosestrife (Lythrum salicaria L.), clover (Trifolium spp. L.), crown vetch
(Coronilla varia L.), and hedge bedstraw (Galium mollugo L.). I suspect that a larger
data set would have yielded significant differences.
Weighted average and percentage of wetland indicator species were used as
indicators of hydrophytic vegetation. Both mitigation and reference sites contained >
50% OBL, FACW, and FAC species (excluding FAC-) thus meeting the hydrophytic
vegetation criteria outlined by the U.S. Army Corps of Engineers (1987). In fact,
every mitigation site met hydrophytic vegetation criteria according to the manual.
73
Similar results were obtained at constructed wetlands in Ohio (Wilson and Mitsch
1996) and Wisconsin (Reinartz and Warne 1993). It was interesting that weighted
averages were similar between mitigation and reference wetlands. Weighted
averages were expected to be lower in mitigation sites because they appeared to be
wetter. However, statistical results indicated that the percentage of hydrophytic
vegetation was similar between wetland types. Other studies have yielded differing
results between mitigation and natural wetlands (Brown 1999, Campbell et al. 2002).
Nonetheless, it appears that mitigation wetlands continue to support adequate
hydrophytic vegetation communities in West Virginia.
Using Detrended Correspondence Analysis, differences in vegetative
composition were revealed that supported results obtained using univariate
procedures. The ordination of vegetation quadrats in Figures 1 and 2, for instance,
likely reflects differences in species richness, diversity, and evenness observed
between these two wetland types using ANOVA models. Upon removing nonnative
species from statistical analyses, richness, diversity, and evenness were similar
between mitigation and reference wetlands. This similarity is illustrated in Figure 2
where wetland quadrats were ordinated using only native species. Detrended
Correspondence Analysis also revealed the effect of age on vegetation composition.
The ordination of quadrats in Figures 3 and 4 may indicate a trend towards decreased
richness and diversity with increasing wetland age. Although Reinartz and Warne
(1993) observed increases in total cover, richness, and diversity with constructed
wetland age, studies have shown that vegetation richness can decrease with time
(Parikh and Gale 1998). It is expected, however, that pioneer species will be
74
competitively excluded as time elapses in mitigation wetlands, thus narrowing the gap
in species composition between wetland types. Increased organic matter
accumulation may account for this, but many years may be required for sufficient
surface accumulation (Bishel-Machung et al. 1996, Atkinson and Cairns 2001). Data,
however, currently suggest a lack of organic matter accumulation in some mitigation
wetlands evaluated in this study (R.H. Fortney, unpublished report). The effects of
organic matter accumulation on vegetative structure at these wetlands definitely
should be monitored.
MANAGEMENT IMPLICATIONS
Compensatory mitigation is a leading tool in counteracting the destruction of
wetlands. There is a need to assess the success of mitigation wetlands in replacing
functions lost during wetland destruction. The establishment of hydrophytic
vegetation communities is crucial to the functioning of any wetland. It not only
determines water chemistry, it affects abundance and distribution of wildlife and
invertebrate communities. Many researchers would agree that defining mitigation
success should be made with caution, especially for relatively young wetlands (0-10
yrs). Wilson and Mitsch (1996) recommend giving freshwater wetlands 15-20 years
before judging their success, and Frenkel and Morlan (1991) recommend waiting at
least 50 years for certain forested and coastal wetlands. An ecological model
developed by Jorgensen (1994) shows that the further initial conditions are from a
natural state, the longer it will take for that system to reach or approach that steady
state. His model predicts at least 15 years would be needed to achieve natural
75
conditions. Research definitely shows that constructed wetlands should be allowed
time to develop, during which time it is imperative to continually assess permit-
compliance and the development of functional attributes.
The average age of studied mitigation sites in West Virginia was 10 years, and
although this is young relative to the optimal ages outlined above to assess mitigation
success, I am still confident adequate conclusions can still be made as to the current
trajectory of these sites. Although much can be learned about vegetation community
dynamics by studying newly created wetlands at any time period, I recommend
waiting a minimum of 10 years to accurately assess the status of vegetation
communities in mitigation wetlands relative to natural wetlands. This would allow
more time for the accumulation of organic matter, which is crucial to wetland
stabilizaton. Even then, caution should be made regarding stochastic events, beaver
(Castor canadensis) activity, or other factors that may influence community structure.
I also recommend seeding newly constructed wetlands with native plant species.
Constructed wetlands will eventually develop healthy native vegetation communities
under natural seeding conditions, but this may take years to occur, and manual
seeding can jump start the growth and production of native vegetation in a disturbed
environment that normally favors exotic species proliferation (Levine and Willard
1990, Reinartz and Warne 1993, Kaplan et al. 1998). Cattail, in particular, can
quickly prevent the establishment of other desirable native species by forming dense,
monotypic stands, so preemptive competition through manual seeding may allow
other perennial clonal species to occupy space that normally would be taken over by
cattail (Reinartz and Warne 1993). Since budgetary constraints are often placed on
76
wetland construction projects, it is important that manual seeding be relatively
inexpensive. A simple, low-cost method employed by Reinartz and Warne (1993)
consisted of simply scattering seeds of native species with no special preparation or
planting techniques. In their study, this technique increased species diversity,
richness, and cover of native wetland species within 2 years compared to unseeded
wetlands.
Future studies should monitor changes in vegetative composition and structure
within these mitigation sites. Some sites are located adjacent to major highways,
which may result in continued sedimentation and accumulation of pollutants
(Trombulak and Frissell 2000, Bridges and Semlitsch 2002). This could dramatically
affect vegetation development, although such accumulation is currently nonexistent
or minimal at the mitigation sites evaluated in this study. Moreover, the impact of
invasive species such as purple loosestrife and reed (Phragmites Trin.) and aggressive
colonizers such as reed canary-grass (Phalaris arundinacea L.) and cattail on overall
species richness, diversity, and evenness, should be monitored. Studies have shown
that within a relatively short time period (i.e., < 10 yrs), vegetation communities can
shift dramatically in composition (Confer and Niering 1992, Parikh and Gale 1998,
Moore et al. 1999). It will be important, as well, to continually monitor changes in
hydrology at these sites. The hydrologic regime in constructed wetlands greatly
affects the development of vegetation communities comparable with natural wetlands
(Confer and Niering 1992, Niswander and Mitsch 1995, Craft et al. 2002). Finally,
the occurrence of rare species should be monitored. This study precluded a
comparison of rare species� occurrence between mitigation and natural wetlands.
77
This comparison likely would have revealed the relative importance of natural
wetlands to rare plant communities in the state. Research definitely should continue
to monitor the progress of vegetation development in constructed wetlands relative to
naturally functioning systems. Indeed, the performance of mitigation wetlands would
be gauged more effectively if more reference wetlands were incorporated into future
studies. This would better encompass the variation in wetland function among
natural wetlands in the mid-Appalachians.
Future studies also should address differences in vegetative structure and
composition between the constructed wetlands and the wetlands destroyed that they
were designed to compensate for. Little information was obtained regarding status of
vegetation communities in impacted wetlands for this study. This has been a problem
for numerous mitigation studies (National Research Council 2001), thus emphasizing
the need for more reliable record keeping involving such important projects.
Nonetheless, by identifying specific methodologies to evaluate metrics indicative of
vegetation community health, and by providing a sound experimental design using
statistical procedures, this project provides an excellent opportunity for the
development of standardized protocols that will ensure adequate compliance with
Section 404 of the Clean Water Act. Future functional evaluations of these and other
mitigation wetlands in West Virginia will provide further insight into the dynamics
involved in constructing wetlands that most closely mimic natural systems. The
hydrogeomorphic approach to wetland function may provide a tool to accomplish this
goal, although no regional subclasses or functional models have yet been established
within the state.
78
Although wetland vegetation is critical in maintaining the basic processes of
wetland ecosystems, the presence of hydrophytic vegetation alone does not
necessarily indicate functional equivalence with naturally occurring wetlands
(D�Avanzo 1986, Reinartz and Warne 1993). Thus, it is important to evaluate other
functions of constructed wetlands. Chapters III and IV address this need by
evaluating the ability of mitigation wetlands in West Virginia to support invertebrate
and vertebrate communities.
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CHAPTER II
TABLES
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Table 1. Total cover, richness, evenness, and diversity per 0.05 ha quadrat of native
and nonnative species, as well as weighted averages and Wetland Indicator Statuses
for 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002.
a Differing letters following means indicate a significant difference between mitigation and reference wetlands at the P < 0.05 level. bOBL = obligate, FACW = facultative wetland, FAC = facultative, FACU = facultative upland, and UPL = upland. cAs defined by the U.S. Army Corps of Engineers (1987): percent OBL, FACW, FAC+, and FAC.
Mitigationa Referencea
Index x SE x SE Total percent cover 39.2a 6.1 54.4a 9.0 Richness 13.0a 1.1 8.3b 1.6 Richness (natives) 12.0a 1.1 8.1a 1.5 Richness (nonnatives) 0.98a 0.26 0.19a 0.36 Evenness 0.32a 0.03 0.17b 0.05 Evenness (natives) 0.29a 0.04 0.17a 0.05 Diversity 1.83a 0.11 1.29b 0.07 Diversity (natives) 1.72a 0.12 1.27b 0.17 Weighted average 0.65a 0.11 0.89 0.16 Wetland Indicator Statusb OBL 43.8 5.1 55.2 7.7 FACW 34.7 3.0 35.2 7.2 FAC 7.1 1.3 3.4 2.6 FACU 11.0 2.4 5.0 3.1 UPL 3.4 1.2 0.6 0.6 Percent hydrophytic vegetationc 83.8a 3.2 94.3a 3.4
91
CHAPTER II
FIGURES
92
BC1
BC2
BC3
BR1
BR2
ES1 ES2ES3ES4
ES5
ES6
ES7
ER1
EB1
EB2
EB3
EB4LC1
LC2
LC3
LC4
LC5
LC6LC7
LC8
LC9
MV1
MV2
MV3
MV4
MD1
SR1
SR2
SR3SR4SC1
SC2
SC3SC4
SC5
TJM1
TJM2
TJM3TJM4
TR3
TR2
TR1
TR4
TR5
VP1
VP2VP3
VP4
WB1
WB2
WB3
WB4
AM1
AM2
AM3
Axis 1
Axis
2
MitigatedReference
Figure 1. Detrended Correspondence Analysis of vegetation quadrats for all species
within 11 mitigation (n = 45) and 4 reference (n = 15) wetlands in West Virginia,
2001-2002. Two letter abbreviations with numbers represent individual quadrats at
each wetland.
93
BC1
BC2
BC3
BR1BR2
ES1 ES2ES3
ES4 ES5
ES6
ES7ER1
EB1
EB2
EB3
EB4
LC1
LC2
LC3LC4
LC5LC6
LC7
LC8
LC9
MV1
MV2
MV3
MV4
MD1
SR1SR2
SR3SR4
SC1
SC2 SC3
SC4SC5
TJM1
TJM2
TJM3TJM4
TR3
TR2
TR1
TR4
TR5
VP1VP2 VP3
VP4
WB1
WB2WB3
WB4
AM1
AM2
AM3
Axis 1Ax
is 2
MitigatedReference
Figure 2. Detrended Correspondence Analysis of vegetation quadrats for native
species only within 11 mitigation (n = 45) and 4 reference (n = 15) wetlands in West
Virginia, 2001-2002. Two letter abbreviations with numbers represent individual
quadrats at each wetland.
94
BC1
BC2BC3
BR1
BR2
ER1
EB1
EB2
EB3
EB4
LC1
LC2
LC3LC4
LC5
LC6
LC7
LC8
LC9
SR1SR2
SR3
SR4
SC1SC2
SC3
SC4
SC5
TJM1
TJM2
TJM3
TJM4
TR3
TR2
TR1
TR4
TR5
VP1
VP2
VP3
VP4
WB1
WB2
WB3WB4
Axis 1Ax
is 2 Age
< 10 yrs old>= 10 yrs old
Figure 3. Detrended Correspondence Analysis of vegetation quadrats for all species
within 11 mitigation (n = 45) sites in West Virginia, 2001-2002. Quadrats were
ordinated using age as a categorical variable. Two letter abbreviations with numbers
represent individual quadrats at each wetland.
95
BC1
BC2
BC3
BR1
BR2
ER1
EB1
EB2
EB3
EB4
LC1
LC2
LC3LC4
LC5
LC6
LC7
LC8
LC9
SR1SR2
SR3
SR4
SC1
SC2
SC3
SC4SC5
TJM1
TJM2
TJM3
TJM4
TR3
TR2
TR1
TR4
TR5
VP1
VP2
VP3
VP4
WB1
WB2
WB3
WB4
Axis 1
Axis
2
Figure 4. Detrended Correspondence Analysis of vegetation quadrats for all species
within 11 mitigation (n = 45) sites in West Virginia, 2001-2002. Quadrats were
ordinated using actual age as a quantitative variable. Larger triangles represent older
quadrats. Two letter abbreviations with numbers represent individual quadrats at
each wetland.
96
CHAPTER III
AQUATIC MACROINVERTEBRATE COMMUNITY
STRUCTURE IN MITIGATION WETLANDS OF WEST
VIRGINIA
COLLINS K. BALCOMBE balcster@hotmail.com
West Virginia University Division of Forestry
PO Box 6125 Morgantown, WV 26505-6125
97
ABSTRACT
Many wetlands have been constructed in West Virginia as mitigation for a
variety of human disturbances, but no comprehensive evaluation on their success has
been conducted. Macroinvertebrates are extremely valuable to the functioning of
wetland ecosystems. As such, invertebrates were chosen as surrogates for wetland
health in the evaluation of benthic and nektonic invertebrate communities in 11
mitigation and 4 reference wetlands in West Virginia. Overall familial richness,
diversity, density and biomass were similar between mitigation and reference
wetlands (P > 0.05). Within open water habitats, benthic density was higher in
reference wetlands, but nektonic biomass was higher in mitigation wetlands (P <
0.05). Within benthic samples, Planorbidae density (P = 0.020) and biomass (P =
0.024) were higher across emergent habitats in reference wetlands. Benthic
Oligochaeta density (P = 0.012) and biomass (P = 0.001) were higher across open
water habitats in mitigation wetlands. All other benthic taxa were similar between
wetland types. Among the most common nektonic orders, Isopoda density (P =
0.015) and biomass (P = 0.025), as well as Odonata biomass (P = 0.039) were higher
in reference wetlands. Gastropoda biomass was higher in mitigation wetlands (P =
0.023). Ephemeroptera (P = 0.043), Hemiptera (P = 0.028), and Odonata (P = 0.040)
densities also were higher in mitigation wetlands, but only across emergent habitats.
Among the most abundant nektonic families collected, Physidae, Planorbidae, and
Corixidae density and biomass were higher in mitigation wetlands (P < 0.05).
Caenidae density (P = 0.029) and Coenagionidae biomass (P = 0.041) also were
higher in mitigation wetlands. In addition, Veliidae was higher in mitigation
This chapter is written in the style of Ecological Applications.
98
wetlands, but only across emergent habitats (P = 0.049). Within mitigation wetlands,
emergent areas contained higher richness (benthic: P = 0.001; nektonic: P = 0.018)
and diversity (benthic: P = 0.001; nektonic: P = 0.006), as well as nektonic density (P
< 0.001) and biomass (P < 0.001) than open water areas. Differences in invertebrate
community structure between mitigation and reference wetlands are attributable to
differences in hydroperiod and vegetative community composition and structure.
These data indicated that mitigation wetlands currently support abundant and
productive invertebrate communities, and as such, provide quality habitat for wetland
dependent wildlife species, especially waterbirds and anurans. Wetland construction
should focus on maintaining moderate hydroperiods (6 months) with equal ratios of
emergent and open water habitat with diverse vegetation communities.
Key words: macroinvertebrates, invertebrates, mitigation wetland, wetland
construction, wetlands, wildlife
INTRODUCTION
Wetlands provide important habitat for numerous species of wildlife, fish,
waterfowl, shorebirds, and neotropical birds. Unfortunately, wetland destruction has
plagued the U.S. for many decades, but recent legislation has mandated the protection
of these valuable ecosystems. Today, wetlands and streams are the only ecosystems
regulated on both public and private lands in the U.S. (National Research Council
1995). After the Clean Water Act of 1972, the �no net loss� policy was enacted in the
late 1980s with the goal of sustaining positive gains in the wetland resource base. On
paper, the �no net loss� policy appears to be working with an estimated 50,000 ha of
99
wetlands in the U.S. being gained from October 1993 to September 1999 (Mitsch and
Gosselink 2000). However, these statistics only reflect compensation of the area of
wetland lost, and do not pertain to gains or losses in wetland function. Numerous
studies have written about our inability to successfully mitigate for wetland
destruction (Race 1985, Erwin 1990, Reinartz and Warne 1993). Although the
definition of success varies depending upon project objectives, most agree that
compensatory wetlands should replace functions lost during wetland destruction. To
gain further insight into the success of our legislation in protecting wetlands, one
must evaluate this success in terms of wetland function. Since the 1980s, numerous
studies have sought to assess the success of mitigation wetlands in properly
supporting hydrology, soils, vegetation, and wildlife (Wentworth et al. 1988, Jarman
et al. 1991, Reinartz and Warne 1993, Niswander and Mitsch 1995, Wilson and
Mitsch 1996, Campbell et al. 2002). While these functions are crucial to wetland
ecosystem integrity, it may be logistically impossible to evaluate all of these
functions when determining the success of a mitigation wetland.
While wetland creation and restoration has been conducted widely throughout
the U.S., research has only begun to determine if compensatory wetlands are
replacing invertebrate habitat and communities of natural wetlands destroyed by
development (Streever and Crisman 1993, Reaves and Croteau-Hartman 1994,
Scatolini and Zedler 1996, Ashley et al. 2000, Fairchild et al. 2000). For a variety of
reasons, invertebrates are extremely important in the functioning of wetlands, and
thus can be viewed as surrogates for wetland health. First, from a logistic standpoint,
they make good study specimens because they are abundant, readily surveyed, and
100
taxonomically rich (Dodson 2001). Long-term hydrologic cycles, water quality, and
habitat type associated with wetlands influence many adaptive strategies of
invertebrates (Wiggins et al. 1980, Doupe and Horwitz 1995, Brooks 2000). Hence,
researchers have used invertebrates to quantify and qualify water quality in wetland
ecosystems (Wallace et al. 1996). In turn, invertebrates contribute to other wetland
functions by assisting in litter decomposition, nutrient cycling (Cummins 1973,
Merritt et al. 1984) and plant community regulation (Weller 1994). Thus,
invertebrates indirectly aid in the transfer of nutrients from the sediments, detritus,
and water column to higher-level organisms. They also have direct impacts on
wildlife species that depend on them for food. Because numerous avian species,
particularly waterfowl and other waterbirds, depend on invertebrates for food
(Gonzalez et al. 1996, De Szalay and Resh 1996, Davis and Smith 1998, Anderson
and Smith 1998, 1999; Anderson et al. 2000), researchers can assess avian
productivity by sampling invertebrates. As well, they are important dietary
components of anurans (Green and Pauley 1987, Anderson et al. 1999, Lima and
Magnusson 2000), making them good indicators of anuran populations. Recently,
invertebrates have even been used as indicators in delineating wetland boundaries
(Euliss et al. 2002). It is clear that invertebrates play a vital role in wetland function
and thus, are integral in analyzing the health of these ecosystems. The extensive loss
of wetlands further increases the value of ecological functions performed by
remaining wetlands, and the production of aquatic invertebrates is one such function
that should not be ignored.
101
Despite numerous studies indicating the significance of invertebrates in
shaping wetland ecosystem health, few studies have monitored the ability of restored
and constructed wetlands in supporting healthy invertebrate populations in the mid-
Appalachians (Johnson et al. 2000). Many studies that do exist preclude a
comprehensive evaluation of all invertebrate taxa, and instead, focus on specific taxa
deemed important to wetland health (Streever and Crisman 1993, Streever et al. 1995,
1996, Ashley et al. 2000, Fairchild et al. 2000, Johnson et al. 2000). Only 2 studies
have evaluated the success of constructed wetlands in West Virginia, and 1 of them
(R.H. Fortney, unpublished report) excluded an evaluation of invertebrates while the
other evaluated production of only 1 taxa in 1 constructed wetland (Johnson et al.
2000). As such, there is a need to evaluate the current ability of mitigation wetlands
in the mid-Appalachian, and in particular West Virginia, in supporting diverse
invertebrate populations. Likewise, in order to maintain the significant role
invertebrates play in the development of wetland ecosystems across this region, there
is a need to identify wetland habitat characteristics that are associated with existing
invertebrate populations. Therefore, researchers can develop adequate monitoring
protocols and construct future wetlands that are compatible with invertebrate
proliferation. This study sought to evaluate the success of mitigation wetlands in
supporting invertebrate communities in West Virginia. Natural (reference) wetlands
were used as standards of comparison since these areas are considered relatively
stable and undisturbed (Brinson 1993, Brinson and Rheinardt 1996, Wilson and
Mitsch 1996). Thus, the objective of this study was to test the null hypothesis that
invertebrate familial richness, diversity, density, and biomass were equal between
102
mitigation and reference wetlands. These data should be helpful in the creation of
future mitigation wetlands, and also in the establishment of monitoring protocols for
these and other wetlands in the region.
METHODS
Study sites
Eleven mitigation (Walnut Bottom, VEPCO, Buffalo Coal, Elk Run, Leading
Creek, Sugar Creek, Sand Run, Triangle, Trus Joist MacMillan, Enoch Branch, and
Bear Run) and 4 reference (Altona Marsh, Elder Swamp, Meadowville, and
Muddlety) wetlands from the northern two-thirds of West Virginia were evaluated for
this study. A minimum standardized time of development of 5 years was chosen for
all mitigation study sites. They ranged in age from 5-21 years old ( x = 10.0, SE =
1.7), and ranged in size from 3.0-10.0 ha ( x = 5.8, SE = 0.80). Similarly, they
ranged in elevation from 265-1,036 m ( x = 586, SE = 75.9). Mitigation sites were
created to compensate for wetland losses sustained in West Virginia for many human
activities including highway development and industrial development, as well as
mining. Almost all mitigation study sites were located near some form of human
disturbance. In fact, many were located adjacent to roads with moderate to heavy
traffic. All were classified as either palustrine emergent or unconsolidated bottom
wetlands with seasonally to permanently flooded hydrologic regimes (Cowardin et al.
1979).
Each of the 4 areas was represented by 1 reference wetland, which was
chosen based on its similarity in location, elevation, size, vegetative structure, and
103
hydrology to mitigation sites within that area (Chapter I). Only portions of reference
sites resembling conditions (i.e., size, hydrology, vegetation) similar to mitigation
sites were selected for study. All had established stable emergent, scrub-shrub, and
forested wetland communities. They ranged in elevation from 170-1,000 m ( x =
582, SE = 169.5) and ranged in size from 6.5-28.0 ha ( x = 15.1, SE = 4.7). All were
classified as palustrine emergent or scrub-shrub wetlands with seasonally to
permanently flooded hydrologic regimes (Cowardin et al. 1979). Detailed mitigation
and reference site descriptions are provided in Chapter I.
Invertebrate sampling
I conducted invertebrate sampling according to Anderson and Smith (1996,
2000) during the summers of 2001 and 2002. Specifically, I collected 620 samples in
July and September of 2001 and another 620 samples in April and June of 2002.
Samples were collected at different times both years to collect a greater diversity of
taxa. Wetlands were stratified based on wetland classification (Cowardin et al. 1979),
and specimens were collected at 10 random points within open water, emergent, and
scrub-shrub (if they existed) areas of each wetland. At each point, I used a 5 cm
diameter core (15 cm deep) and a 7.5 cm diameter water column sampler (Swanson
1983) to collect nektonic and benthic specimens, respectively. Water column
samples were sieved in the field using a 500-micron sieve (Huener and Kadlec 1992)
and preserved in 70% ethanol. Benthic samples were placed in bags, refrigerated, and
processed using an elutriator (Magdych 1981) within 10 days of collection (Anderson
and Smith 2000). Invertebrates were identified and counted to family using
McCafferty (1981), Pennak (1989), and Merritt and Cummings (1984). Familial
104
richness was expressed as the number of families/wetland, and abundance (no.
individuals) was converted into density estimates (no./m² or no./L). Biomass (g/m² or
g/L) was obtained by oven-drying samples at 55°C for ≥48 hours to a constant mass
(0.0001 g) and using an analytical scale.
Statistical analyses
Mitigation and reference wetlands were compared using SAS (SAS Institute
1988). Invertebrate familial richness, diversity, biomass, and density were compared
using a split-plot Analysis of Variance (ANOVA) model, with wetland type
(mitigation vs. reference) as the first split and time as the second split. I incorporated
a repeated measures design for 2 survey periods, which were repeated both years.
The independent variables tested were wetland type and sampling period and type×
sampling period interactions with dependent variables being richness, diversity,
biomass, and density. Familial diversity was calculated using the Shannon-Weiner
Index (Shannon and Weaver 1949). To decrease variability, geographic area was
included as a blocking factor for all analyses, except when comparing invertebrate
indices between subtypes (emergent vs. open water) within mitigation wetlands. In
this case, site was used as a blocking factor. In addition to comparisons of all
invertebrate taxa, comparisons were made between wetland types for the most
abundant orders and families observed. All families used for this analysis contained
at least 100 individuals. I also used an ANOVA to test for differences between scrub-
shrub, emergent, and open water invertebrate communities within the Elder Swamp
reference wetland. If differences were observed in invertebrate communities,
Tukey�s (HSD) Honestly Significantly Difference test was used to test pairwise
105
comparisons of means. Assumptions of normality were tested with the univariate
procedure in SAS (SAS Institute 1988), and Levene�s Test was used for homogeneity
of variances. Rank and log transformations were used to convert dependent variables
that did not meet the aforementioned assumptions (Dowdy and Wearden 1991).
Specifically, log transformations were used for within subtype comparisons, and rank
transformations were used to analyze familial density and biomass of common taxa.
RESULTS
Taxa occurrence A total of 10,824 benthic and nektonic individuals were sampled, 6,350 of
which occurred in mitigation sites and 4,474 occurred in reference sites. Within
benthic samples, 3,173 individuals from 38 families were sampled in mitigation
wetlands (Appendix 33) while 3,799 individuals from 25 families were sampled in
reference wetlands (Appendix 34). Within nektonic samples, 3,177 individuals from
70 families were sampled in mitigation wetlands (Appendix 35), and 675 individuals
from 50 families were sampled in reference wetlands (Appendix 36).
Mitigation versus reference wetlands
Overall benthic (P = 0.984; Table 1) and nektonic (P = 0.101; Table 2)
familial richness was similar across wetland complexes of mitigation and reference
wetlands. Similar results were obtained across emergent and open water areas.
Benthic diversity was higher in reference wetlands across wetland complexes (P =
0.046), but was similar across emergent (P = 0.102) and open water (P = 0.189) areas
106
between wetland types (Table 1). Nektonic diversity was similar between mitigation
and reference wetlands across entire wetland complexes (P = 0.626), as well as
emergent (P = 0.523) and open water (P = 0.068) areas (Table 2). Benthic (Table 1)
and nektonic (Table 2) density (P ≥ 0.348) and biomass (P ≥ 0.228) were similar
between mitigation and reference wetlands. Within open water areas, nektonic
biomass was higher (P = 0.021) in mitigation wetlands, but benthic density was
higher (P = 0.031) in reference wetlands.
The 9 most abundant benthic families (of 4 orders) included Diptera
(Chironomidae), Gastropoda (Lymnaedae, Physidae, Planorbidae, Pomatiopsidae,
Valvatidae, and Viviparidae), Pelecypoda (Sphaeriidae), and Oligochaeta (not taken
to family). The top 13 nektonic families (of 9 orders) included Amphipoda
(Talitridae), Cladocera (not taken to family), Diptera (Chironomidae), Ephemeroptera
(Baetidae and Caenidae), Gastropoda (Physidae, Planorbidae, and Viviparidae),
Hemiptera (Corixidae and Veliidae), Isopoda (Asellidae), Odonata (Coenagrionidae),
and Pelecypoda (Sphaeriidae). The 2 most abundant benthic orders sampled in both
wetland types were Gastropoda and Oligochaeta (Table 1). The 2 most abundant
nektonic orders in mitigation wetlands were Gastropoda and Hemiptera while in
reference wetlands, Isopoda and Diptera were most abundant (Table 2).
Comparisons of each order individually yielded a higher benthic Oligochaeta
density (P = 0.012) and biomass (P = 0.001) in mitigation wetlands across open water
areas (Table 1). Nektonic Gastropoda biomass was higher (P = 0.023) across wetland
complexes in mitigation wetlands (Table 2). This was attributed to higher biomass in
open water areas. Within emergent areas, Ephemeroptera nektonic density (P =
107
0.043) and Hemiptera density (P = 0.028) and biomass (P = 0.018) were higher in
mitigation wetlands (Table 2). However, nektonic Isopoda density (P = 0.015) and
biomass (P = 0.025), as well as Odonata biomass (P = 0.039) were higher in
reference sites across entire wetland complexes (Table 2). This was attributed to
higher numbers across emergent areas.
An evaluation of the 13 common nektonic families combined yielded a higher
(P = 0.021) biomass in mitigation wetlands within open water areas (Table 2).
Although benthic Planorbidae density (P = 0.020) and biomass (P = 0.024) were
higher in emergent areas of reference wetlands (Table 1), nektonic Planorbidae
density (P = 0.046) and biomass (P = 0.031) were higher across mitigation wetland
complexes (Table 2). This was attributed to higher numbers across open water areas
(density: P = 0.048; biomass: P = 0.025). Nektonic Physidae biomass was higher in
mitigation wetlands across entire wetland complexes (P = 0.015) as well as emergent
(P = 0.018) and open water (P = 0.037) areas (Table 2). Nektonic Physidae density
also was higher across mitigation wetland complexes (P = 0.021) and emergent areas
(P = 0.019), but reference wetlands contained higher (P = 0.039) nektonic Physidae
density in open water areas (Table 2). In addition, nektonic Corixidae density (P =
0.046) and biomass (P = 0.045), Coenagrionidae biomass (P = 0.041), and Caenidae
density (P = 0.029) were higher in mitigation wetland complexes (Table 2). Nektonic
Veliidae density was higher (P = 0.049) in mitigation wetland emergent areas.
Asellidae density (P = 0.015) and biomass (P = 0.025) were higher in reference
wetland complexes, but this was the only family observed within Isopoda, so results
are already reflected above within order comparisons.
108
Emergent versus open water habitats Familial richness, diversity, density, and biomass also were compared
between emergent and open water areas within mitigation wetlands (Table 3). In this
comparison, richness (benthic: P = 0.001; nektonic: P = 0.018) and diversity (benthic:
P = 0.001; nektonic: P = 0.006) were higher in emergent areas. Overall nektonic
density (P < 0.001) and biomass (P < 0.001) also were higher in emergent areas.
Similar results were obtained for the top 13 nektonic families combined.
For comparisons among emergent, open water, and scrub-shrub subtypes
within the Elder Swamp reference wetland, richness (benthic: P = 0.499; nektonic: P
= 0.253), diversity (benthic: P = 0.792; nektonic: P = 0.116), and biomass (benthic: P
= 0.865; nektonic: P = 0.111) were similar among subtypes (Table 4). Similar results
were obtained for the most common taxa. However, nektonic density for all taxa (P =
0.034) and for the top 13 families (P = 0.005) was highest in emergent areas.
Specifically, for the top 13 families, scrub-shrub invertebrate densities scored in the
middle between emergent and open water areas. While emergent and scrub-shrub
densities were similar, both densities were higher than open water densities.
DISCUSSION
Mitigation versus reference wetlands These data indicated equally abundant, diverse, and productive invertebrate
communities in mitigation wetlands relative to reference wetlands. Despite reference
wetlands supporting a higher benthic density across open water areas, mitigation
benthic density was similar to reference wetlands across entire complexes. Nektonic
109
density and biomass also were similar between wetland types across complexes, and
mitigation nektonic biomass actually exceeded reference biomass across open water
areas. Mitigation nektonic diversity also was similar to reference wetlands, both
across emergent and open water areas, and across entire complexes. Despite similar
benthic diversity across emergent and open water areas between wetland types,
reference benthic diversity exceeded mitigation diversity across wetland complexes.
An examination of specific taxa based on order and family provided further
insight into invertebrate community structure. Within these analyses emerged trends
that indicated higher abundance and productivity of invertebrates within mitigation
wetlands. These results are consistent not only across entire wetland complexes, but
within emergent and open water areas as well. While only 3 taxa were higher in
reference wetlands, 7 taxa were higher in mitigation wetlands, most of which were
nektonic specimens. Despite this trend, mitigation nektonic diversity was similar to
reference wetlands.
Of particular importance within mitigation wetlands was the abundance of
Hemiptera. Specifically, Corixidae and Veliidae were more abundant in mitigation
wetlands. These taxa are important components of the diet of dabbling ducks (Euliss
et al. 1991, Batzer et al. 1993), and actually are known to benefit from fish presence
(Zimmer et al. 2000). Although no formal surveys were conducted on fish
abundance, 10 of 11 mitigation wetlands contained fish populations. Studies, in
general, show mixed results regarding invertebrate responses to fish populations
(Wilcox 1992, Pierce and Hinrichs 1997, Batzer et al. 2000). Benthic Oligochaeta
density also was higher in mitigation wetlands, but only across open water areas. No
110
obvious natural history components of these taxa account for their higher abundance
in mitigation wetlands. Nektonic Gastropoda was generally more abundant and
productive within mitigation wetlands as well. This was reflected by such large
numbers of Physidae across complexes and subtypes, although Planorbidae was
highly productive as well, especially within open water areas. It is clear that open
water played a key role in structuring Gastropoda populations among wetlands.
Gastropoda are grazers and generally found in shallow areas with moderate amounts
of aquatic vegetation (Pennak 1989). Mitigation wetlands generally had longer
hydroperiods with a more even mixture of emergent vegetation to open water than
reference wetlands. These conditions likely favored Gastropoda colonization and
probably reflect their ubiquitous distribution throughout emergent and open water
areas of mitigation wetlands. This phenomenon is not uncommon throughout wetland
studies (Anderson and Smith 2000, Nelson et al. 2000). Despite high numbers of
nektonic Physidae and Planorbidae, benthic Planorbidae density and biomass were
higher in reference wetlands, specifically in areas with emergent vegetation. This
trend was evident because of such unproportionally high numbers of Planorbidae in
emergent areas of Altona Marsh, a natural marl wetland with alkaline conditions.
Reference wetlands also supported more Asellidae (Isopoda), and a more productive
nektonic Odonata population. Brown et al. (1997) also observed higher Asellidae
abundance in natural wetlands in New York. Asellidae generally avoid open water
and remain hidden under rocks, emergent vegetation, or debris. Hence, higher
amounts of emergent vegetation in reference wetlands (Chapter IV) likely provided
more refugia for these taxa. In fact, almost all Asellidae were sampled within
111
emergent areas of both wetland types. Despite a higher nektonic Odonata biomass,
benthic samples yielded higher Odonata densities in mitigation wetlands within
emergent areas. No trends in Odonata life history seem to account for these results.
A common taxa that is addressed throughout many invertebrate studies is
Chironomidae (Streever et al. 1995, Ashley et al. 2000, Batzer et al. 2000, Brooks
2000, Nelson et al. 2000). This taxa spends a majority of its life cycle in the aquatic
larval stage where it eventually ascends to the water surface to emerge after pupation
(Oliver 1971, Pinder 1986). Thus, it is available during different life stages to aquatic
birds with differing feeding behaviors. As such, Chironomidae are a preferred food
of young dabbling ducks (Batzer et al. 1993, King and Wrubleski 1998) and other
adult waterfowl and waterbirds (Ashley et al. 2000). They also readily colonize
newly created habitats if conditions are suitable (Danell and Sjoberg 1982) and are
important in the development of wetland physical and chemical properties (Fisher
1982). Thus, differences in Chironomidae communities of constructed and natural
wetlands have been assumed to reflect functional differences instead of poor initial
recruitment (Steever et al. 1996). The mitigation wetlands evaluated in this study
supported statistically similar Chironomidae density and biomass to reference
wetlands, despite having a density and biomass that were almost 3 and 6 times higher,
respectively in mitigation than reference wetlands. Nektonic Chironomidae samples
yielded more similar results between wetland types. Nevertheless, mitigation
wetlands in West Virginia currently contain abundant and well distributed
Chironomidae populations that should continue to serve as a valuable prey base for
avian and anuran populations.
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The rapid colonization of invertebrate communities is common in created and
restored wetlands (Streever et al. 1996, Brown et al. 1997, Fairchild et al. 1999,
Ashley et al. 2000). The proximity of mitigation wetlands to rivers, streams, and
other wetlands is known to facilitate colonization of invertebrates (Jeffries 1994,
Nelson et al. 2000). Almost all of the mitigation wetlands in this study, as well as
reference wetlands, were located near major water sources. The complex trophic
levels among invertebrate communities often dictate composition of invertebrate taxa.
Predatory taxa, for instance, depend on colonization by prey, herbivory taxa often
depend on vegetation succession, and taxa that collect fine algal and detrital particles
may depend on the development of adequate substrate conditions (Lake et al. 1989,
Fairchild et al. 2000). Because of the average 10-year development time of
mitigation wetlands included in this study, I expected temporal and spatial
development among mitigation wetlands across the state to be sufficient in supporting
diverse invertebrate taxa. In fact, representative taxa of predators, herbivores,
algivores, and detritivores all were present across mitigation wetlands.
Differences in vegetation composition and community structure between
mitigation and reference wetlands may account for some differences observed
between invertebrate taxa between wetland types. Mitigation wetlands supported
more diverse and species rich vegetation communities than reference wetlands
(Chapter II). Given the relatively higher number of invertebrates observed in
mitigation wetlands, one may conclude that, to a certain extent, the percentage of
aquatic vegetation may play less of a role in structuring invertebrate communities
than vegetation composition. This assertion is supported by results obtained by
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Brown et al. (1988), where increases in invertebrate richness and density were
observed with increasing diversity of aquatic vegetation communities. They, too,
concluded that diverse vertical structure associated with diverse vegetation
communities was more important in structuring invertebrate populations than surface
area of vegetation. Other studies have concluded similar results (Schramm et al.
1987, De Szalay and Resh 1996). The profound difference in vegetative community
composition between mitigation and reference wetlands likely plays a leading role in
structuring invertebrate populations. These differences will likely decrease through
time, however, as disturbed conditions in mitigation wetlands diminish and vegetation
competitive interactions manifest to create similar vegetation community composition
between wetland types.
Hydroperiod (length and duration of flooding) also is considered to be a major
factor structuring invertebrate communities. In addition to its effects on wildlife
communities (Chapter IV), wetland hydroperiod affects invertebrate taxon richness
(Spencer et al. 1999, Brooks 2000) as well as invertebrate density, biomass, and
production (Leeper and Taylor 1998, Anderson and Smith 2000). The general trend
in all of these studies was that invertebrate communities benefited from longer
hydroperiods. With increasing hydroperiod, concentric biotic zones can be created,
with the more ephemeral peripheral zones differing from central zones with more
permanent water (Brooks 2000). Thus, invertebrate communities can increase in
richness based entirely on life history requirements. Other benefits are associated
with longer hydroperiod, and these are discussed later. The mitigation wetlands
evaluated in this study were mostly semipermanently to permanently flooded
114
(although some were seasonally flooded) while reference wetlands varied from
seasonally flooded (Meadowville) to permanently flooded (Muddlety). Hence,
because mitigation wetlands had longer hydroperiods, I expected to observe higher
familial richness, and perhaps more significant differences in overall diversity,
density and biomass. Although this was not the case, mitigation wetlands did support
more abundant and productive nektonic taxa than reference wetlands.
While abundant research exists pertaining to invertebrate use of wetlands, few
studies have evaluated invertebrate community structure in mitigation wetlands
relative to naturally functioning reference wetlands (Rossiter and Crawford 1981,
Kreil 1986, Streever et al. 1996, Brown et al. 1997, Fairchild et al. 2000, Zimmer et
al. 2000). Within these studies, no real trend has emerged regarding the success of
mitigation wetlands in supporting abundant and productive invertebrate populations.
Brown et al. (1997) and Zimmer et al. (2000) found overall similar invertebrate
abundances between restored and natural wetlands. Likewise, Fairchild et al. (2000)
observed similar Coleopteran richness and Streever et al. (1996) observed similar
Dipteran densities between constructed and natural wetlands in Pennsylvania.
Results of these studies are consistent with those obtained in my study. However,
Rossiter and Crawford (1981) and Kreil (1986) found higher invertebrate density and
diversity in natural wetlands. Nelson et al. (2000) also observed higher invertebrate
richness and abundance in natural wetlands, but only 2 constructed wetlands were
evaluated. Although some of these studies stratified invertebrate sampling by
vegetation communities or by vegetated and open water habitats, for statistical
purposes, samples were pooled across habitats. Hence, statistics analyzing
115
invertebrates individually within these habitats were not performed. My study
compared mitigation and reference wetlands, not only within wetland subtypes
(vegetated and unvegetated), but across entire wetland complexes as well. For
instance, upon pooling samples taken from wetland subtypes, no statistical
differences emerged for either benthic or nektonic specimens, both for all taxa and for
the most common taxa. However, overall differences did emerge upon comparing
benthic and nektonic samples across wetland subtypes. Specifically, benthic density
was higher in reference wetlands across open water habitats, but nektonic biomass
was higher in mitigation wetlands. Hence, these data reveal the importance of open
water habitats in distinguishing invertebrate community structure between mitigation
and reference wetlands. Indeed, this discovery would have been ignored upon
comparing invertebrate communities across entire wetland complexes. Comparisons
of individual taxa also reflect the importance of these analyses. These data definitely
provide a clearer picture of the spatial variation in invertebrate community structure
in wetlands.
The complex interactions between vegetation and invertebrate communities
discussed above have important implications in shaping wildlife communities in
mitigation wetlands. As aforementioned, invertebrates are a primary food source for
anuran and avian populations. Thus, invertebrates, in addition to those factors
outlined in Chapter IV, likely affect wildlife abundance and distribution. As
mentioned in Chapter IV, waterbird and anuran abundance were higher in mitigation
wetlands. This may be attributable to a higher overall nektonic biomass observed
within mitigation wetlands. Granted, reference wetlands contained a higher overall
116
benthic density in open water areas, benthic invertebrates may be more difficult to
access than nektons, especially for anurans. Although benthic invertebrates are
readily accessible to dabbling ducks, the relatively more diverse nektonic taxa of
invertebrates offered in mitigation wetlands may contribute more to the prey base for
these and other waterbirds dependent on invertebrates for food. Cox et al. (1998)
found a direct correlation between survival and growth of mallard (Anas
platyrhynchos) and abundance of aquatic invertebrates, and Anderson et al. (2000)
found a positive correlation between feather molt intensity of green wing teal (Anas
crecca) and aquatic invertebrate consumption. Ashley et al. (2000) observed similar
correlations between invertebrate densities and aquatic bird abundance. Invertebrates
are not only an important food resource for waterbirds, they are important for
terrestrial passerine species that are more peripherally associated with wetland habitat
(Euliss et al. 1999). These data indicate that higher invertebrate production in
mitigation wetlands may directly affect productivity of wildlife species that depend
on them for food, and thus, provide further insight into the ecological value of
constructed wetlands in West Virginia. Hence, these data indirectly suggest the
effectiveness of mitigation efforts in replacing aquatic avian and anuran habitat lost
due to development.
The absence of consistent differences between invertebrate populations of
mitigation and reference wetlands should not be interpreted as functional similarities
between wetland types. Wetlands are complex ecosystems with variable functions
that take decades to form. Wilson and Mitsch (1996) recommended giving
freshwater wetlands 15-20 years before judging their success, and Frenkel and
117
Morlan (1991) recommended waiting at least 50 years for certain forested and coastal
wetlands. Two wetlands included in this study were about 20 years old and an
additional 3 sites were ≥ 10 years old. Although my sites do not meet recommended
criteria for constructed wetland development time, nearly half are at least 10 years
old, and I think relatively conservative inferences can still be made regarding their
success in supporting invertebrate communities.
Emergent versus open water habitats
The variation in invertebrate distribution throughout wetlands was
exemplified by significant differences in community structure between emergent and
open water areas. It was not surprising that invertebrate abundance, diversity, and
production was so much higher in emergent areas. Numerous studies have observed a
direct relation between invertebrate production and aquatic vegetation (Wilcox 1992,
Streever et al. 1995, Zimmer et al. 2000). Specifically, Streever et al. (1995) sampled
invertebrate populations between vegetated and non-vegetated areas in a constructed
wetland in Florida and found higher abundances in emergent areas. These data, as
well as results from my study, support the need to stratify wetlands by structure to
account for spatial variation in invertebrate populations. Emergent areas likely
support more invertebrates because they enjoy decreased risk of predation, increased
vertical and spatial structure, and higher food resources, especially from submerged
aquatic vegetation (Crowder and Cooper 1982, Carpenter and Lodge 1986, Severson
1987). As well, emergent vegetation may increase survival of some invertebrate taxa
by increasing egg viability or diapausing individuals (Wiggins et al. 1980, Rehfisch
1994).
118
However, too much emergent vegetation may decrease dissolved oxygen
levels by shading oxygen producing submergent vegetation, thus inhibiting
invertebrate productivity, especially Dipteran larvae (Streever et al. 1996, Nelson et
al. 2000). In this study, reference wetlands contained higher percentages of emergent
aquatic vegetation than mitigation wetlands (Chapter IV), yet invertebrate production
was relatively low. This may be attributable to lower dissolved oxygen levels from
decreased amounts of open water. While emergent vegetation does provide important
food and cover to invertebrates, the importance of open water cannot be
underestimated. Indeed, studies have shown that dissolved oxygen has a strong
influence on invertebrate community structure (Nelson et al. 2000), and that open
water habitats provide higher dissolved oxygen levels necessary for subsistence of
productive invertebrate populations. In turn, this will benefit ducklings that tend to
forage on invertebrates in open water habitats (King and Wrubleski 1998). It is
important to note, however, that duckweed (Lemna spp. L.) or algal mat
developments in open water habitats may curtail light penetration, reducing
oxygenation via photosynthesis by submerged aquatic vegetation, thus harming
invertebrate populations, and subsequently, wildlife populations (Nelson et al. 2000).
One particular study actually found a direct correlation between invertebrate diversity
and submerged aquatic vegetation (Schwartz and Gruendling 1985). This further
stresses the importance of establishing submerged aquatic vegetation in mitigation
wetlands (Chapter II). Sartoris and Thullen (1998) suggested that even proportions of
emergent vegetation and open water habitats (i.e., hemimarsh) create optimal habitat
for invertebrates. They pointed out that hemimarsh conditions, in addition to
119
providing a mosaic of habitats for wildlife, create alternating aerobic and anoxic
environments for invertebrates and allow for nitrogen treatment and degradation of
organic matter. These habitat conditions are further asserted in Chapter IV and are
presumed to be responsible for higher abundances of anurans and waterbirds in
mitigation wetlands.
An evaluation of invertebrate populations among habitat subtypes within the
Elder Swamp reference wetland also was conducted. The objective of this analysis
was to assess the value of scrub-shrub areas to invertebrates relative to open water
and emergent areas. According to this analysis, scrub-shrub areas supported similar
overall invertebrate richness, diversity, density, and biomass to emergent and open
water habitats. Due to small sample sizes, the other 3 reference wetlands were not
included in this analysis. Hence, this analysis lacks sufficient replication to make
accurate inferences about the contribution of scrub-shrub areas to invertebrate
community structure. Nevertheless, scrub-shrub areas add valuable vertical and
horizontal structure to wetland complexes, and should be incorporated into mitigation
projects.
Future considerations
The identification of variables that influence abundance and distribution of
aquatic invertebrate communities is crucial to adequately managing wetlands, not
only for wildlife, but for numerous other important functions valuable to ecosystem
integrity. Other factors not considered in this study that are known to affect
invertebrate community structure include water chemistry (Lancaster and Scudder
1987, Euliss et al. 1991, Foster 1995), turbidity (Threlkfeld and Soballe 1988,
120
Zimmer et al. 2000), nutrient enrichment (Pettigrew et al. 1998), organic content
(Craft 2000), surrounding land management activities (De Szalay and Resh 1996),
and climate change (Eyre et al. 1993). Future studies on mitigation wetlands in West
Virginia should consider these abiotic factors that contribute to spatial and temporal
variation in invertebrate community structure, while not ignoring additional effects of
stochastic events on invertebrate populations. Such studies might include evaluations
of pH, substrate composition, dissolved oxygen, conductivity, or temperature to name
a few. Bioaccumulation of trace elements (silver, aluminum, mercury, selenium) also
should be monitored if wetlands are created adjacent to agricultural fields. Dodson
(2001), for instance, observed lower invertebrate taxon richness in wetlands near
agricultural use watersheds. In particular, agricultural practices are known to
decrease egg hatching (Dillon and Gibson 1985) and feeding success in invertebrates
by increasing turbidity and contamination by fertilizer and pesticide runoff (Dodson
2001). However, this factor was minimal in our study because only 1 mitigation site
was constructed adjacent to agricultural fields.
Furthermore, because congeneric species may have different tolerances to
environmental conditions, species-level identification should be considered in future
studies that focus in invertebrate populations in mitigation wetlands. Other studies
could address the effects of wetland construction techniques including soil
transplantation, dredging, or dike development. Brown et al. (1997), for instance,
found that transplantation of remnant wetland soil significantly increased invertebrate
abundance. Although this appears to speed initial colonization by invertebrates (and
plants), it may be unnecessary given the evidence supporting the rapid development
121
of hydrophytic vegetation in the absence of soil and plant transplantations. This is
evident, for instance, at Walnut Bottom, which is one of the youngest wetlands
evaluated in this study, and this site contained the highest abundance of invertebrates
of all wetlands evaluated.
It is encouraging that mitigation wetlands supported such abundant and
productive invertebrate populations. However, strong temporal variation can exist in
invertebrate populations (Scatolini and Zeddler 1996, Fairchild et al. 2000).
Although mitigation wetlands appear to support invertebrate populations comparable
to reference wetlands, this conclusion precludes analysis of rarer taxa within the
region, as well as describing discrepancies (if any exist) among frequencies of
differing trophic levels due to time lag. These points illustrate the need for extensive
sampling over long periods of time, not only to establish regional reference standards,
but to accurately describe invertebrate populations within mitigation wetlands.
Management options
Indeed, the differences in invertebrate communities between mitigation and
reference wetlands observed in this study stress the importance of maintaining
specific habitat characteristics that promote invertebrate production. Perhaps the
most important recommendation centers on maintaining diverse vegetation
communities intermixed with equal amounts of open water, while maintaining a
hydroperiod of 4 months with seasonal drying. A recommended technique to achieve
such goals is moist soil management. This management tool optimizes wetland
vegetative vertical and spatial structure. As well, it creates spatial and temporal
variations in wetland habitat that maximize vegetation and invertebrate communities,
122
and hence, wildlife distribution and abundance. Numerous studies have shown that
longer hydroperiod increases invertebrate diversity (Batzer and Resh 1992, Anderson
and Smith 2000, Brooks 2000). Anderson and Smith (2000) found that invertebrates
were most abundant and diverse in moist-soil managed wetlands with longer
hydroperiods, followed by moist-soil managed wetlands with shorter hydroperiods,
unmanaged wetlands with longer hydroperiods, and unmanaged wetlands with shorter
hydroperiods. These differences were due to differences in soil moisture and
subsequent vegetation growth. Moist-soil managed wetlands are known to contain
more abundant and diverse vegetation communities (Anderson 1997), which, as
previously mentioned, provide more food, cover, and reproductive habitat for
invertebrates. The species composition also is different in moist-soil managed
wetlands, with annual seed producing plants being favored that decompose more
readily over more robust perennial emergents that occur in nonmanaged wetlands.
And a longer hydroperiod (4 vs. 2 months; Anderson and Smith 2000) would
facilitate this decomposition (Anderson and Smith 2002), thus creating more detritus
through fragmentation (Murkin and Kadlec 1986, Nelson et al. 1990). In addition,
longer hydroperiod increases invertebrate abundance by facilitating colonization
(Rosenzweig 1996). However, other studies have shown that as hydroperiod
becomes too long (i.e., > 6 mo.), abundance and diversity of invertebrates will decline
in permanently (Reid 1983) to semipermanently (Neckles et al. 1990) flooded
wetlands. This is caused by decreases in emergent vegetation, lowered
decomposition rates (Anderson and Smith 2000, 2002) which leads to less detritus,
and increased predation and competition among other invertebrates and fish (Reid
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1983, Neckles et al. 1990, Skelly 1997, Zimmer et al. 2000). Invertebrates are not the
only taxa that benefit from moist-soil managment. Waterbirds, too, benefit, not only
from increased abundance and production of invertebrates, but from more abundant
seed availability for foraging. Indeed, Anderson and Smith (2000) found that the
combination of moist-soil management with longer hydroperiod was the superior
management tool for increasing invertebrate populations. Moist-soil conditions
caused by water draw-downs should be created in early spring to promote plant seed
germination and invertebrate concentrations (Helmers 1992), followed by fall
flooding. Spring draw-down also coincides with peak shorebird migration for most
species (Helmers 1992). It is important to note that spring draw-downs would
negatively affect anuran breeding by creating less open water for egg mass
placement. I recommend either maintaining enough open water to facilitate anuran
breeding in large isolated wetland complexes where draw-downs occur, or
implementing a mitigation banking system where numerous wetlands in a landscape
are maintained under different management schemes to create a mosaic of habitat
suitable to support both waterbirds and anurans. Although it may not be feasible to
install water control structures and implement moist-soil management in some of the
mitigation sites evaluated in this study, moist-soil management should definitely be
considered in future mitigation projects in the state.
In addition to maintaining the appropriate hydroperiod to enhance invertebrate
habitat, future mitigation projects should consider water depth design specifications
(Chapter II). Zimmer et al. (2000), for instance, observed a negative correlation
between water depth and invertebrate abundance. Although no specific water depths
124
were provided, they found that shallow water depths were associated with higher
invertebrate abundance. Consistent with recommendations from Chapter IV, it is
recommended that wetlands include shallow (1-10 cm) and deep (11-30 cm) areas to
facilitate colonization by an array of invertebrate and wildlife taxa.
I also recommended that native aquatic vegetation be planted at newly
constructed wetlands (Chapter II). Not only will this benefit overall vegetation
diversity by decreasing the competitive advantage of less desirable species such as
broad-leaved cattail (Typha latifolia L.), it should provide refuge for invertebrates
while jump starting decomposition rates thereby creating more detritus for
invertebrate consumption.
To further increase the amount of detritus available to invertebrates, the
addition of organic amendments to wetlands (Cummings 1999) should be considered
in future mitigation projects. Crop residues, manures, or mulches (Plaster 1997)
should provide increased organic matter to newly created substrates thereby
increasing invertebrate abundance via detrital accumulation (Craft 2000).
In addition to habitat quality achieved at single wetlands, construction efforts
should focus on spatial relationships on a landscape level that facilitate colonization
and regional persistence of certain invertebrate taxa. This can be achieved by
constructing wetlands adjacent to other major water sources and away from
disturbances (i.e., agricultural fields and roads). The ecological importance of aquatic
invertebrates should not be ignored in replacing lost wetland habitat. Fortunately,
management recommendations outlined in Chapter IV are compatible with habitat
characteristics that maximize invertebrate production.
125
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137
CHAPTER III
TABLES
138
Table 1. Benthic invertebrate richness (no. families/wetland), diversity, density (no./m2) and biomass (g/m2) between mitigation (n =11) and reference (n =
4) wetlands across emergent areas, open water areas, and entire wetland complexes, 2001-2002 with comparisons of all invertebrate taxa and the 9 most
common taxa (i.e., >100 individuals).
Emergent Open water Total Mitigation Reference Mitigation Reference Mitigation Reference Invertebrate taxa Mean SE Mean SE F1,10 P Mean SE Mean SE F1,10 P Mean SE Mean SE F1,10 P Total invertebrates Density 54.7 18.4 160.6 147.5 1.49 0.250 37.1 11.5 139.5 132.1 6.34 0.031 45.9 14.0 157.8 145.3 0.97 0.348 Mass 2.190 1.480 16.423 16.390 1.30 0.280 0.645 0.343 5.092 5.069 3.29 0.100 1.417 0.895 10.787 10.757 1.65 0.228 Diversity 1.590 0.060 1.740 0.080 1.71 0.220 1.120 0.100 1.200 0.420 0.01 0.945 1.36 0.080 1.470 0.220 Common 9 taxa Density 66.6 18.6 164.0 144.8 1.82 0.207 52.9 11.6 154.6 140.6 3.13 0.108 62.6 13.3 174.3 149.7 0.68 0.430 Mass 2.603 1.652 16.419 16.390 1.85 0.204 0.857 0.403 5.393 5.331 3.09 0.109 1.741 0.942 11.297 11.232 1.67 0.225 Diptera Density 14.6 1.4 14.1 3.0 0.17 0.686 14.8 2.5 8.4 3.6 3.74 0.082 19.6 2.0 18.7 2.1 0.00 0.995 Mass 0.011 0.003 0.013 0.007 0.62 0.448 0.017 0.008 0.004 0.003 3.70 0.083 0.019 0.006 0.015 0.006 0.27 0.617 Chironomidae Density 10.1 1.8 8.0 3.1 0.01 0.913 14.5 2.6 6.0 3.1 3.06 0.111 16.8 1.8 11.3 3.1 1.42 0.261 Mass 0.004 0.001 0.003 0.001 0.02 0.879 0.018 0.008 0.003 0.003 2.88 0.120 0.017 0.008 0.005 0.002 0.86 0.375 Gastropoda Density 47.6 18.2 126.1 123.0 4.30 0.065 26.2 10.8 131.4 124.2 1.72 0.220 63.1 26.5 238.7 229.2 2.66 0.134 Mass 3.373 2.000 14.791 14.775 3.26 0.101 0.549 0.330 4.853 4.771 1.07 0.324 3.244 1.957 18.85 18.750 1.51 0.248 Lymnaedae Density 3.2 1.8 13.6 13.6 0.50 0.494 0.7 0.7 13.6 13.6 0.30 0.595 3.6 1.8 17.6 17.6 0.57 0.468 Mass 0.122 0.079 1.006 1.006 0.51 0.491 0.005 0.005 0.565 0.565 0.31 0.591 0.126 0.079 1.159 1.159 0.59 0.462 Physidae Density 17.8 9.5 40.2 40.2 2.39 0.153 8.3 4.4 11.4 11.4 0.95 0.353 18.8 8.9 46.6 46.6 2.18 0.171 Mass 2.120 1.902 11.102 11.102 1.94 0.194 0.182 0.153 0.129 0.129 1.17 0.306 1.439 1.194 11.136 11.136 2.01 0.187 Planorbidae Density 33.1 11.7 55.0 55.0 7.65 0.020 22.7 8.7 64.8 57.7 1.73 0.218 44.6 16.3 91.3 84.2 3.40 0.095 Mass 2.084 1.396 2.815 2.815 7.10 0.024 0.467 0.240 2.465 2.384 1.12 0.315 1.942 1.111 3.947 3.866 2.17 0.172 Pomatiopsidae Density 1.4 1.4 38.1 38.1 0.67 0.431 1.1 1.1 34.4 34.4 1.99 0.188 1.4 1.4 58.6 58.6 3.28 0.100 Mass 0.003 0.003 1.872 1.872 0.66 0.435 0.003 0.003 0.420 0.420 2.23 0.166 0.003 0.003 1.846 1.846 2.43 0.150 Valvatidae Density 0.6 0.4 4.0 4.0 0.18 0.679 0.0 0.0 25.3 25.3 2.18 0.171 0.6 0.4 26.1 26.1 2.25 0.164 Mass 0.004 0.004 0.046 0.046 0.14 0.713 0.000 0.000 0.255 0.255 2.26 0.164 0.004 0.004 0.265 0.265 2.10 0.178 Viviparidae Density 8.1 3.6 14.2 11.1 0.01 0.911 3.0 1.9 40.1 39.1 0.15 0.705 8.4 3.6 44.1 40.6 0.01 0.913 Mass 0.077 0.045 0.364 0.346 0.01 0.920 0.010 0.009 2.172 2.171 0.20 0.663 0.076 0.046 2.235 2.220 0.03 0.858 Oligochaeta Density 30.2 8.4 15.4 4.3 1.07 0.326 34.8 10.7 11.9 5.2 9.34 0.012 45.9 8.7 22.9 3.7 2.95 0.116
139
Emergent Open water Total Mitigation Reference Mitigation Reference Mitigation Reference Invertebrate taxa Mean SE Mean SE F1,10 P Mean SE Mean SE F1,10 P Mean SE Mean SE F1,10 P Mass 0.153 0.099 0.023 0.088 0.35 0.567 0.462 0.356 0.067 0.055 10.19 0.001 0.470 0.266 0.057 0.027 1.93 0.195 Pelecypoda Density 10.8 3.6 50.2 42.1 0.38 0.552 11.6 5.2 26.2 24.1 0.02 0.900 16.1 5.4 64.5 55.3 0.28 0.608 Mass 0.056 0.027 2.885 2.873 0.33 0.581 0.107 0.061 0.631 0.629 0.02 0.899 0.115 0.053 2.935 2.925 0.11 0.752 Sphaeriidae Density 10.8 3.6 49.4 41.3 0.38 0.554 11.6 5.2 21.2 19.1 0.02 0.890 16.1 5.4 59.5 50.2 0.08 0.786 Mass 0.057 0.027 2.885 2.873 0.29 0.601 0.107 0.061 0.627 0.626 0.02 0.896 0.116 0.053 2.932 2.922 0.27 0.617 a Bold numbering indicates a significant difference (P < 0.05).
Table 1.Continued.
140
Table 2. Nektonic invertebrate richness (no. families/wetland), diversity, density (no./L) and biomass (g/L) between mitigation (n = 11) and
reference (n = 4) wetlands across emergent areas, open water areas, and entire wetland complexes, West Virginia, 2001-2002 with comparisons
of all invertebrate taxa and the 13 most common taxa (i.e., >100 individuals).
Emergent Open water Total Order Mitigation Reference Mitigation Reference Mitigation Reference
Family x SE x SE F1,10 P x SE x SE F1,10 P x SE x SE F1,10 P Total invertebrates Richness 2.5a 0.1 2.1a 0.3 2.71 0.131 1.9a 0.3 1.1a 0.5 4.37 0.063 2.4a 0.1 1.9a 0.3 3.26 0.101 Diversity 2.46 0.11 2.33 0.04 0.44 0.523 1.95 0.18 1.16 0.43 4.20 0.068 2.52 0.10 2.45 0.05 0.25 0.626 Density 14.8 3.1 12.6 2.7 0.30 0.594 2.4 1.1 1.8 1.0 1.59 0.236 8.6 1.9 8.3 2.1 0.03 0.862 Mass 0.2586 0.1816 0.0551 0.0219 0.90 0.366 0.0226 0.0185 0.0051 0.0039 7.56 0.021 0.1407 0.1000 0.0359 0.0131 0.90 0.364 Common 13 taxa Density 16.5 4.0 13.0 2.6 1.49 0.250 3.1 1.1 3.9 2.1 2.22 0.167 12.1 3.2 10.9 2.0 0.29 0.603 Mass 0.3365 0.2248 0.0512 0.0313 3.64 0.086 0.0318 0.0216 0.0139 0.0125 7.44 0.021 0.1923 0.1110 0.0415 0.0268 4.22 0.067 Amphipoda Density 0.8 0.6 0.9 0.7 0.28 0.607 1.9 1.9 1.6 1.6 1.54 0.243 1.8 1.6 2.3 2.1 0.21 0.658 Mass 0.0003 0.0002 0.0005 0.0003 0.30 0.597 0.0145 0.0150 0.0058 0.0060 1.65 0.227 0.0103 0.0102 0.0063 0.0059 0.32 0.581 Talitridae Density 0.6 0.6 0.4 0.3 0.48 0.505 1.9 1.9 2.0 2.0 1.51 0.247 1.6 1.6 2.5 2.3 0.00 0.992 Mass 0.0002 0.0002 0.0004 0.0003 0.49 0.450 0.0148 0.0150 0.0076 0.0080 1.58 0.238 0.0102 0.0102 0.0082 0.0078 0.01 0.931 Cladocera Density 6.2 3.0 1.5 0.7 0.71 0.418 1.4 0.9 0.0 0.0 2.61 0.137 5.3 1.7 1.6 0.6 1.68 0.225 Mass 0.0057 0.0040 0.0002 0.0001 0.73 0.412 0.0007 0.0006 0.0000 0.0000 2.59 0.139 0.0040 0.0021 0.0002 0.0001 1.86 0.203 Diptera Density 6.3 1.4 5.9 0.9 0.21 0.658 0.8 0.3 0.7 0.4 0.06 0.804 5.4 1.2 6.3 1.1 0.43 0.528 Mass 0.0048 0.0016 0.0100 0.0074 0.02 0.879 0.0013 0.0010 0.0002 0.0010 0.53 0.485 0.0043 0.0014 0.0099 0.0075 0.01 0.913 Chironomidae Density 4.7 1.2 3.2 1.4 1.20 0.230 0.7 0.3 0.6 0.4 0.18 0.683 4.3 1.1 3.2 1.4 0.65 0.438 Mass 0.0039 0.0020 0.0012 0.0009 1.41 0.263 0.0011 0.0009 0.0002 0.0001 0.33 0.579 0.0039 0.0014 0.0011 0.0008 1.78 0.212 Ephemeroptera Density 4.2 1.1 3.5 2.1 5.36 0.043 1.3 0.3 0.7 0.5 1.91 0.197 4.0 0.6 4.2 1.8 1.60 0.235 Mass 0.0043 0.0016 0.0166 0.0155 3.07 0.110 0.0016 0.0010 0.0006 0.0004 2.44 0.150 0.0046 0.0015 0.0190 0.0147 0.58 0.464 Baetidae Density 1.8 1.1 2.2 1.1 0.19 0.670 0.5 0.3 0.2 0.2 3.06 0.111 1.6 0.8 2.4 1.0 0.25 0.630 Mass 0.0012 0.0009 0.0017 0.0007 0.22 0.649 0.0005 0.0004 0.0002 0.0007 2.78 0.127 0.0009 0.0006 0.0019 0.0007 0.17 0.689 Caenidae Density 2.7 0.6 0.7 0.7 5.08 0.048 1.0 0.3 0.6 0.6 0.92 0.360 2.9 0.4 0.9 0.9 6.50 0.029 Mass 0.0019 0.0010 0.0003 0.0003 4.26 0.066 0.0012 0.0007 0.0005 0.0005 0.94 0.355 0.0024 0.0009 0.0007 0.0007 3.77 0.081
141
Emergent Open water Total Order Mitigation Reference Mitigation Reference Mitigation Reference
Family x SE x SE F1,10 P x SE x SE F1,10 P x SE x SE F1,10 P Gastropoda Density 7.6 2.5 3.5 2.3 2.61 0.138 0.9 0.3 1.1 0.7 3.99 0.074 6.6 2.2 3.7 2.4 3.67 0.084 Mass 0.4012 0.2560 0.0196 0.0142 3.84 0.079 0.0309 0.0210 0.0128 0.0116 7.25 0.023 0.3232 0.2164 0.0211 0.0163 7.20 0.023 Physidae Density 3.1 1.3 1.3 1.3 7.82 0.019 0.3 0.2 0.4 0.4 5.61 0.039 2.7 1.1 1.3 1.3 7.53 0.021 Mass 0.0579 0.0280 0.0080 0.0080 7.94 0.018 0.0040 0.0034 0.0032 0.0030 5.89 0.037 0.0494 0.0244 0.0077 0.0077 8.56 0.015 Planorbidae Density 4.7 1.7 1.8 0.8 4.48 0.061 0.8 0.2 0.3 0.3 5.08 0.048 3.4 1.0 1.4 0.8 5.20 0.046 Mass 0.5388 0.4360 0.0036 0.0020 4.18 0.068 0.0417 0.0310 0.0009 0.0009 6.92 0.025 0.3097 0.2381 0.0038 0.0024 6.32 0.031 Viviparidae Density 3.5 1.6 3.5 2.4 0.40 0.540 0.1 0.1 0.8 0.5 1.01 0.339 3.5 1.6 3.5 2.6 0.72 0.416 Mass 0.0145 0.0090 0.0247 0.0170 0.17 0.689 0.0005 0.0003 0.0019 0.0012 0.79 0.394 0.0147 0.0085 0.0237 0.0164 0.35 0.567 Hemiptera Density 7.2 3.0 3.5 1.6 6.56 0.028 0.8 0.3 1.1 0.6 1.57 0.239 6.1 2.3 4.3 1.4 0.52 0.486 Mass 0.0380 0.0343 0.0004 0.0001 8.05 0.018 0.0011 0.0006 0.0008 0.0006 2.53 0.143 0.0300 0.0256 0.0012 0.0005 3.37 0.096 Corixidae Density 4.3 3.6 0.0 0.0 2.23 0.167 0.2 0.1 0.3 0.3 4.08 0.071 3.3 2.6 0.3 0.3 5.18 0.046 Mass 0.0480 0.0430 0.0000 0.0000 2.10 0.178 0.0001 0.0001 0.0006 0.0006 4.65 0.056 0.0349 0.0302 0.0006 0.0006 5.22 0.045 Veliidae Density 2.2 0.7 1.0 0.6 5.02 0.049 0.4 0.3 0.6 0.6 0.17 0.686 2.2 0.8 1.3 0.8 4.09 0.071 Mass 0.0002 0.0001 0.0001 0.0001 4.87 0.052 0.0001 0.0001 0.0002 0.0002 0.18 0.683 0.0003 0.0001 0.0002 0.0002 3.77 0.081 Isopoda Density 1.1 0.6 6.6 2.3 7.59 0.020 0.0 0.0 0.2 0.2 1.91 0.197 1.1 0.6 6.6 2.3 8.58 0.015 Mass 0.0012 0.0008 0.0144 0.0074 6.84 0.026 0.0000 0.0000 0.0001 0.0001 1.91 0.197 0.0012 0.0008 0.0144 0.0074 6.99 0.025 Asellidae Density 1.1 0.6 6.6 2.3 8.58 0.015 0.0 0.0 0.2 0.2 1.91 0.197 1.1 0.6 6.6 2.3 8.58 0.015 Mass 0.0012 0.0008 0.0144 0.0070 6.84 0.026 0.0000 0.0000 0.0001 0.0001 1.91 0.197 0.0012 0.0009 0.0144 0.0074 6.99 0.025 Odonata Density 3.9 0.6 2.1 0.8 5.56 0.040 0.7 0.2 0.4 0.4 1.05 0.331 3.1 0.5 2.0 0.7 2.63 0.136 Mass 0.0087 0.0023 0.0131 0.0101 5.27 0.045 0.0010 0.0004 0.0003 0.0003 1.76 0.214 0.0078 0.0022 0.0128 0.0102 5.65 0.039 Coenagrionidae Density 2.6 0.6 1.7 0.7 2.14 0.175 0.6 0.3 0.3 0.3 2.18 0.170 2.3 0.5 1.6 0.7 3.39 0.095 Mass 0.0029 0.0010 0.0018 0.0010 2.43 0.150 0.0009 0.0005 0.0001 0.0001 2.49 0.146 0.0030 0.0009 0.0018 0.0010 5.52 0.041 Pelecypoda Density 2.5 1.0 6.1 3.4 0.32 0.581 0.3 0.1 0.3 0.3 1.82 0.207 2.3 0.8 5.8 3.4 0.18 0.684 Mass 0.0224 0.0110 0.0750 0.0534 0.17 0.691 0.0041 0.0030 0.0011 0.0011 1.72 0.219 0.0195 0.0094 0.0702 0.0526 0.05 0.825 Sphaeriidae Density 2.3 1.0 6.1 3.4 0.61 0.452 0.3 0.1 0.3 0.3 1.82 0.207 2.1 0.8 6.0 3.3 0.52 0.486 Mass 0.0223 0.0110 0.0750 0.0530 0.31 0.588 0.0041 0.0030 0.0011 0.0011 1.74 0.217 0.0194 0.0094 0.0738 0.0523 0.13 0.728 a Bold numbering indicates a significant difference (P < 0.05).
Table 2. Continued.
142
Table 3. Benthic and nektonic invertebrate familial richness (no. families/wetland), diversity, density (benthic: no./m2;
nektonic: no./L) and biomass (benthic g/m2; nektonic: g/L) between emergent and open water areas of mitigation wetlands
(n = 11) in West Virginia, 2001-2002 with comparisons of all taxa and for the 9 most common (abundant) benthic and 13
most common nektonic taxa (i.e., >100 individuals).
Benthica Nektonica Emergent Open water Emergent Open water x SE x SE F1,10 P x SE x SE F1,10 P Total invertebrates Richness 2.1a 0.2 1.5b 0.1 22.89 0.001 2.5a 0.1 1.9b 0.3 8.01 0.018 Diversity 1.60a 0.19 1.12b 0.34 20.02 0.001 2.46a 0.36 1.95b 0.59 11.91 0.006 Density 54.7a 18.4 37.1a 11.5 1.51 0.247 14.8a 3.1 2.4b 1.1 72.70 < 0.0001 Mass 2.190a 1.484 0.645a 0.343 0.78 0.399 0.2586a 0.1816 0.0226b 0.0185 30.41 0.0003 Common taxa Density 66.6a 18.6 52.9a 11.6 0.89 0.368 16.5a 4.0 3.1b 1.1 37.64 0.0001 Mass 2.603a 1.652 0.857a 0.403 0.18 0.678 0.3365a 0.2248 0.0318b 0.0216 14.66 0.003 a The same letter following means indicates no difference between wetland types (P > 0.05).
143
Table 4. Benthic and nektonic invertebrate familial richness (no. families/wetland), diversity,
density (no./L), and biomass (g/L) among emergent, open water, and scrub-shrub areas of the
Elder Swamp reference wetland (n = 1), West Virginia, 2001-2002 with density and mass
comparisons of all taxa and for the 9 most common (abundant) benthic taxa and 13 most
common nektonic taxa (i.e., >100 individuals).
Total invertebrates Common taxa Diversity Richness Density Mass Density Mass Benthic x SE x SE x SE x SE x SE x SE Emergent 0.0a 0.0 1.3a 0.3 1.6a 0.3 0.0015a 0.0010 6.4a 3.7 0.0035a 0.0031Open water 0.49a 0.10 0.8a 0.3 3.5a 1.7 0.0025a 0.0022 12.5a 4.5 0.0092a 0.0071Scrub-shrub 0.48a 0.11 1.3a 0.3 9.6a 4.5 0.0039a 0.0027 20.7a 8.0 0.0086a 0.0061F 0.08 0.78 0.15 1.11 0.45 P 0.792 0.499 0.865 0.386 0.655 Nektonic Emergent 0.93 0.22 1.7a 0.4 5.1a 1.7 0.0063a 0.0045 6.2a 0.7 0.0026a 0.0013Open water 0.35 0.0 1.0a 0.0 0.2b 0.04 0.0001a 0.0001 1.1b 0.4 0.0003a 0.0002Scrub-shrub 1.14 0.09 1.4a 0.3 1.9ab 0.6 0.0021a 0.0015 4.9ac 1.3 0.0079a 0.0071F 2.85 1.64 5.31 2.94 12.56 1.66 P 0.116 0.253 0.034 0.111 0.005 0.258 a The same letter following means indicates no difference between wetland types (P >
0.05).
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CHAPTER IV
WILDLIFE HABITAT USE IN MITIGATION AND NATURAL
WETLANDS OF WEST VIRGINIA
COLLINS K. BALCOMBE balcster@hotmail.com
West Virginia University Division of Forestry
PO Box 6125 Morgantown, WV 26505-6125
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ABSTRACT
Most studies evaluating mitigation success have focused on hydrology, soils,
and vegetation with the premise that these functions dictate wildlife distribution and
abundance. While some monitoring of mitigation wetlands has occurred in West
Virginia, no comprehensive survey of wildlife usage has been conducted. I evaluated
avian and anuran communities, as well as habitat suitability for 8 wetland-dependent
wildlife species, in 11 mitigation and 4 natural wetlands throughout West Virginia.
All avian measurements are expressed as means per 50 m radius plot (0.78 ha).
Avian species richness (P = 0.711), diversity (P = 0.314), and abundance (P = 0.856)
were similar between mitigation (richness: x = 8.79, SE = 0.31; diversity: x = 2.41,
SE = 0.41; abundance: x = 21.1, SE = 1.7) and natural (richness: x = 8.77, SE = 0.48;
diversity: x = 2.15, SE = 0.37; abundance: x = 22.2, SE = 3.9) wetlands. Mean
abundance for the 20 most common avian species sampled was similar (P = 0.963)
between mitigation ( x = 10.4, SE = 1.2) and natural wetlands ( x = 10.4, SE = 1.6).
Out of these common species, wood duck (Aix sponsa; P = 0.037) and American
goldfinch (Carduelis tristis; P = 0.013) were higher in mitigation (wood duck: x =
0.87, SE = 0.36; American goldfinch: x = 0.54, SE = 0.11) than natural (wood duck:
x = 0.0, SE = 0.0; American goldfinch: x = 0.34, SE = 0.15) wetlands, whereas song
sparrow (Melospiza melodia; P = 0.035) was higher in natural ( x = 2.43, SE = 0.22)
than mitigation ( x = 1.25, SE = 0.11) wetlands. Waterbird (P = 0.013) and
waterfowl (P = 0.013) abundance were higher in mitigation (waterbird: x = 3.97, SE
= 1.1; waterfowl: x = 3.46, SE = 1.1) than natural (waterbird: x =0.34, SE = 0.18;
This chapter was written in the style of The Journal of Wildlife Management.
146
waterfowl: x = 0.19, SE = 0.16) wetlands. Playback surveys for inconspicuous
waterbirds yielded 2 rail species at 2 mitigation wetlands. Anuran species richness (P
= 0.023), Wisconsin index (WI) value (P < 0.001), and abundance (P < 0.001) were
higher in mitigation (richness: x = 2.01, SE = 0.09; WI: x = 0.52, SE = 0.03;
abundance: x = 4.75, SE = 0.66) than natural (richness: x = 1.47, SE = 0.14; WI: x =
0.40, SE = 0.17; abundance: x = 4.69, SE = 1.18) wetlands. For individual species
observed, American bullfrog (Rana catesbeiana; WI: P = 0.033; A: P = 0.038), green
frog (R. clamitans; WI: P = 0.012; A: P = 0.018), and pickerel frog (R. palustris; WI:
P = 0.003; A: P = 0.005) were higher in mitigation wetlands, whereas spring peeper
(Pseudacris crucifer), gray treefrog (Hyla chrysoscelis), wood frog (R. sylvatica), and
American toad (Bufo americanus) were similar between wetland types (P > 0.05).
Habitat Suitability Index (HSI) scores for all 8 species combined were similar (F =
0.57, P = 0.489) between mitigation and natural wetlands. Red-winged blackbird
(Agelaius phoeniceus; P = 0.001) and beaver (Castor canadensis; P = 0.037) HSI
values were higher in natural (blackbird: x = 0.15, SE = 0.05; beaver: x = 1.0, SE =
0.0) than mitigation (blackbird: x = 0.03, SE = 0.01; beaver: x = 0.74, SE = 0.06)
wetlands, whereas muskrat (Ondatra zibethicus), great blue heron (Ardea herodias),
wood duck (Aix sponsa), mink (Mustela vison), snapping turtle (Chelydra
serpentina), and red-spotted newt (Notophthalmus viridescens) were similar between
wetland types (P > 0.05). Differences in vegetation and invertebrate community
composition and structure likely contribute to differences in wildlife populations
between wetland types.
JOURNAL OF WILDLIFE MANAGEMENT 00(0):000-000
147
Key Words: mitigation, mitigation wetland, habitat use, birds, frogs, habitat
suitability index, wetland-dependent species, mitigation success
Wetlands are important ecosystems that provide valuable habitat for wildlife.
The destruction of wetlands across the U.S., however, has undermined the survival of
some fish, shellfish, furbearing mammals, waterfowl, and amphibians that rely
exclusively on these areas for survival (Mitsch and Gosselink 2000). The Clean
Water Act of 1972 was the first major legislation that protected our nation�s wetland
resource base, but it was not until the �no net loss� policy of the late 1980s that the
government actively sought to mitigate for these losses that have devastated the status
of wetland-dependent wildlife across the country.
Under the new policy, thousands of hectares of wetlands have been
constructed to compensate for wetland destruction, but little monitoring has been
conducted on the success of these newly created wetlands, particularly in West
Virginia (National Research Council 2001). Most studies that have addressed
mitigation success have focused on wetland function with respect to hydrology, soils,
and vegetation (Cummings 1999, Moore et al. 1999, Zedler and Callaway 1999, Stolt
et al. 2000, Campbell et al. 2002). These parameters are excellent indicators of
wetland function, but they yield limited insight into a wetland�s direct ability to
support wildlife populations. Indeed, it is assumed that adequate vegetation,
hydrology, and location will precipitate wildlife colonization of newly created
wetlands (Erwin 1990, Hammer 1992). But information regarding the ability of
mitigation wetlands to replace lost wildlife habitat is lacking (National Research
Council 2001). Of particular concern is the replacement of waterbird and anuran
148
habitat in the face of continued declines as a result of wetland destruction (Dahl 1990,
Bortner et al. 1991, Semlitch 2002). For reasons listed below, these taxa are
extremely important in the functioning of wetland ecosystems. Information
pertaining to the ability of compensatory wetlands to support specific wetland-
dependent wildlife species including some furbearers (i.e., beaver, muskrat, mink)
also is lacking. By creating a repeatable and credible methodology that can be used
to quantify wetland-dependent wildlife habitat, comparisons of wildlife habitat can be
made between created and natural wetlands that allow an assessment of wildlife
habitat replaced through compensatory mitigation. This knowledge, in turn, could
contribute to wetland design and monitoring techniques that address wildlife needs.
Numerous bird species require wetlands as their primary habitat. Eighty
percent of breeding birds in North America, and more than 50% of the 800 protected
migratory birds rely on wetlands (Wharton et al. 1982). Perhaps due to an increased
habitat diversity provided by the water surface (Ferguson et al. 1975, Weller 1999),
wetlands support higher avian species diversity (MacArthur 1964, Mensing et al.
1998) and densities (Udevitz and Michael 1982, Mensing et al. 1998) than their
upland counterparts. Wetland birds are good indicators of function because, as a
group, they exhibit a wide range of habitat requirements, and have adapted to the
variety of vegetative cover types and water regimes wetlands provide (Anderson et al.
1996, Davis and Smith 1998, Melvin and Webb 1998, Anderson and Smith 1999,
Weller 1999, Naugle et al. 2000). Wetland birds have unique diets as well. Many are
herbivorous or omnivorous and eat a variety of foods including seeds, fruit,
invertebrates, amphibians, and small mammals (Gonzalez et al. 1996, De Szalay and
149
Resh 1997, Davis and Smith 1998, Anderson and Smith 1999, Weller 1999, Anderson
et al. 2000).
Like avian species, anurans are relatively easy to sample and possess unique
habitat requirements. Because wetlands provide hibernation, foraging, breeding, and
interspersion habitat for different life stages, anurans rely exclusively on wetlands for
all or part of their life-cycle (Michael and Smith 1985, Dodd and Cade 1998,
Lehtinen et al. 1999, Semlitsch 2002). Hence, anuran populations can provide insight
into water quality and temporal variations in hydrology (Beattie and Tyler-Jones
1992, Anderson et al. 1999a, Semlitsch 2002). They feed on numerous invertebrate
species (Anderson et al. 1999b, Lima and Magnusson 2000), and are an important
food source for invertebrates and vertebrates alike (Bridges 1999, Lardner 2000).
This makes them a valuable link between invertebrate populations and higher
vertebrates in a complex food web (Weller 1999). In addition, physiological
attributes such as their permeable skin and ectothermic metabolism make them
particularly vulnerable to habitat alterations, and thus excellent indicators of
environmental health (Hall 1980, Heyer et al. 1994, Semlitsch 2002). Indeed, these
taxa are of particular importance when assessing wetland health because they are
intricately involved in complex wetland functions. They are relatively easy to
sample, are conspicuous by sight and sound, and simple to recognize in the field.
Hence, these species supply consistent and reliable data sets that are compatible with
field research.
A direct evaluation of wildlife numbers is only one way to assess the success
of mitigation wetlands in supporting wildlife populations. Another way is to evaluate
150
wildlife habitat. Numerous wildlife habitat models have been developed in recent
years that quantify habitat for either entire wildlife taxa or specific species. The
development of models is important because researchers must often assign relative
values to habitat to support objectives for mitigation. Some such models, to name a
few, include the Wetland Evaluation Technique (Adamus 1983, Adamus and
Stockwell 1983), Habitat Assessment Technique (Cable et al. 1989), and the Avian
Richness Evaluation Model (Adamus 1993). A species-specific model commonly
used today is the Habitat Suitability Index (HSI) model developed by the U.S. Fish
and Wildlife Service (1981). Based on natural history requirements for a particular
species, this model uses habitat parameters considered pertinent to a species survival
to calculate an index ranging from 0 to 1 (a 1 represents optimal habitat). Depending
on the HSI model, the habitat parameters evaluated may have significant implications
for other wildlife taxa as well, which can provide further insight into overall habitat
quality for wildlife for a given area.
There is a need to evaluate the success of mitigation wetlands in supporting
wildlife taxa that are considered good indicators of wetland health. This success can
be determined through surveys of wildlife populations and through the evaluation of
wildlife habitat (Adamus 1993, Wilson and Mitsch 1996, VanRees-Siewert and
Dinsmore 1996, Stevens et al. 2002). Natural wetlands are often used as standards of
comparison because these areas are considered relatively stable and undisturbed
(Brinson 1993, Brinson and Rheinardt 1996, Wilson and Mitsch 1996). The goal of
this study was to evaluate the success of mitigation wetlands in West Virginia in
supporting healthy wildlife communities. This functional attribute was determined by
151
comparing avian and anuran populations between mitigation and natural wetlands,
and by evaluating habitat quality of 8 wetland-dependent wildlife species using HSI
models. As such, I tested the null hypotheses that anuran and avian richness,
diversity, and abundance were similar between mitigation and natural wetlands. The
equality of HSI scores also was tested, both for each individual species, and for all 8
species combined.
STUDY AREA
I evaluated 11 constructed and partially restored mitigation wetlands (Walnut
Bottom, VEPCO, Buffalo Coal, Elk Run, Leading Creek, Sugar Creek, Sand Run,
Triangle, Trus Joist MacMillan, Enoch Branch, and Bear Run) and 4 natural wetlands
(Altona Marsh, Elder Swamp, Meadowville, and Muddlety) in northern West
Virginia. I condensed these sites into 4 areas representing 3 geomorphic settings
within the state. These settings are indicated by 3 physiographic regions described by
Fenneman (1938): Western Hills, Appalachian Plateau, and Ridge and Valley, but for
statistical purposes, all mitigation wetlands were compared to all natural wetlands. I
chose 4 natural wetlands based on limited disturbance and their similarity in location,
elevation, vegetative structure, and hydrology to mitigation sites. Because the natural
wetlands were considerably larger than mitigation sites, I only used areas within
natural wetlands that were compatible in size to mitigation sites.
Mitigation study sites were created as compensation for human activities
including facility construction, road construction, or mining. Almost every wetland
was located near some form of human disturbance, with some lying adjacent to roads
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with moderate to heavy traffic (Chapter I). Many are extensively used for
recreational use, adding to the level of disturbance. Mitigation sites ranged from 5-21
years old ( x = 10.0, SE = 1.7). All mitigation sites were ≥5 years old and ranged in
size from 3.0-9.5 ha ( x = 5.8, SE = 0.8). Elevation ranged from 265-1,036 m ( x =
586, SE = 75.9). All mitigation wetlands were classified as palustrine emergent or
palustrine unconsolidated bottom wetlands (Cowardin et al. 1979).
Natural wetlands chosen for study were located near mitigation sites within
each area, usually within the same watershed. All had established stable emergent,
scrub-shrub, and forested wetland communities. The portions of each wetland that
were evaluated ranged from 6.5 to 28.0 ha ( x = 15.1, SE = 4.7) in size and ranged
from 170-1,000 m ( x = 582, SE = 169.5) in elevation. All natural wetlands were
classified as palustrine emergent or palustrine scrub-shrub wetlands (Cowardin et al.
1979). Detailed study site descriptions are provided in Chapter I.
METHODS
Avian Communities
I evaluated avian communities by sampling breeding bird populations using
point count surveys (Ralph et al. 1995). I visited wetlands twice between 5 May and
27 June, 2001-2002, when breeding birds were most active. I conducted 10-min point
counts that occurred between 30 min before sunrise and 1000 hours, under acceptable
weather conditions (Ralph et al. 1995). I established a minimum of 1 ( x = 2.4, SE =
0.31) 0.78 ha point count station (50 m radius) at each wetland, which was spaced ≥
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250 m for independent bird surveys (Ralph et al. 1993). At each wetland, I
determined a sufficient number of sampling stations to cover the entire wetland area.
I conducted playback surveys for some waterbirds that are generally missed
with traditional bird count methodologies. Immediately following point counts, I
conducted call-response surveys for Virginia rail (Rallus limicola), king rail (R.
elegans), and sora (Porzana carolina) at the same stations used for point counts to
determine rail presence/absence and relative abundance. Surveys also were
conducted for American bittern (Botaurus lentiginosus), least bittern (Ixobrychus
exilis), and pied-billed grebe (Podilymbus podiceps). I conducted surveys according
to protocol outlined by Gibbs and Melvin (1993). I played species-specific calls
using a portable cassette player located 0.75 m above ground or water for 50 sec per
call, followed by 10 sec of silence. Calls were played with a maximum sound
pressure of 80 dB 1 m from the recorder. I played each species� call in a random
order 1 time/station. I used the American Ornithologists Union (2002) checklist for
common and scientific names of birds.
Anuran Communities
I evaluated anuran communities using nocturnal call count surveys. Surveys
followed standardized protocols developed by the U.S. Fish and Wildlife Service
(Casey and Record, unpublished report) to evaluate species presence or absence and
relative abundance. I visited wetlands 5-24 April, 7-30 May, and 5-18 June, 2001-
2002 to account for temporal breeding differences among species. These dates were
selected based on recommended temperature ranges for different survey periods (i.e.,
period 1: >5°C; period 2: >10°C; period 3: >12.8°C; Casey and Record, unpublished
154
report). I collected data for 3 min at each sampling point following a 1-2 min settling
period. I identified frogs to species and evaluated relative abundances by assigning a
Wisconsin Index value of intensity to each species� call (Mossman 1994). I assigned
a ranking of 1 to species with nonoverlapping calls and when an exact count of
individuals could be made, a ranking of 2 to species whose calls overlapped and only
estimations of numbers could be made, and a 3 to species that were calling in full
chorus. If a WI value of 3 was assigned to a species, I used a mandatory abundance
estimate of 50. I conducted surveys between 30 min after sunset and midnight. I
used The Society for the Study of Amphibians and Reptiles (2000) for common and
scientific names of frogs.
Habitat Quality
I chose HSI models that had broad taxonomic coverage and included 1 reptile
(snapping turtle, Graves and Anderson 1987), 1 amphibian (red-spotted newt, Sousa
1985), 3 mammals (beaver, Allen 1983; muskrat, Allen and Hoffman 1984; mink,
Allen 1984), and 3 bird species: 1 wading bird (great blue heron, Short and Cooper
1985), 1 waterfowl species (wood duck, Sousa and Farmer 1983), and 1 passerine
(red-winged blackbird, Short 1985). All species had wide distributions throughout
West Virginia, and possessed life-history components (i.e., foraging, reproduction,
and interspersion) that were compatible with habitat features present in the wetlands
selected for this study.
I measured a combined total of 38 habitat variables for all 8 HSI models
during summer, 2001 (Table 1). I obtained estimates of percent coverage (i.e., tree
canopy, shrub cover, emergent and submergent vegetation, broad-leafed monocots,
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percent wood duck brood and winter cover) for all HSI models using the line-
intercept method (Hays et al. 1981) and aerial photography. Percent trees with a
diameter at breast height (DBH) between 2.5 and 15.2 cm, average height of shrub
canopy, and species composition of woody vegetation ≤ 200 m of the water�s edge
were evaluated for the beaver model accordingly. From the edge of the wetland
basin, I randomly placed 200 m long transects that extended out of the wetland and
into the nearest forested cover type, if one existed. For statistical purposes, a
minimum of 30 DBH samples and shrub height samples were collected. I measured
these variables according to protocols by Robel et al. (1993). Beginning 10 m from
the edge of the wetland basin and at each 20 m point on the transect thereafter, I
measured DBH of the nearest tree to the nearest 0.1 cm. This was done along the
entire length of the 200 m line or to the end of the woody cover, whichever came
first. A minimum of 3 transect lines were established to fulfill the need for 30 tree
DBH samples. The proportion of these measurements in the 2.5 to 15.2 cm DBH size
class was calculated. At the same 20 m increment points, height and species of the
nearest shrub also was measured.
For the snapping turtle model, I measured mean water temperature at mid-
depth to the nearest 0.1ºC in August using a thermometer. Temperature was taken
every 5.0 m along the transect lines established for line-intercept measurements. I
obtained percent silt in the substrate using a 5.0 cm core sampler (15 cm deep) at 10
random points each within emergent and open water subtypes. Substrate samples
were oven dried to a constant mass at 55 ºC for ≥48 hr and sieved through a 63-
micron sieve (Graves and Anderson 1987). The mass of the silt (g) passing through
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the sieve was divided by the total mass of the collected sample. I measured mean
current velocity (cm/sec) at mid-depth by calculating the speed of a neutrally buoyant
object at mid-stream (Graves and Anderson 1987). Specifically, the time it takes for
a 3.8 cm diameter bobber to move between 2 fixed points, 3 m apart was measured
(Hays et al. 1981) at 5 random locations within each wetland subtype. A maximum
of 1 min was allowed for the bobber to move between the 2 points (Graves and
Anderson 1987). Velocity was calculated as distance divided by time.
For the red-winged black bird model, I determined carp (Cyprinus carpio)
presence using visual encounter surveys. I determined presence of dragonflies
(Odonata) using data collected during macroinvertebrate sampling (Chapter III).
All distance estimates (i.e., to forested cover type, small streams, permanent
water, between potential great blue heron nest sites (grove of trees ≥ 5 m tall; ≥ 0.4
ha in size) and foraging areas, between potential great blue heron nest sites and actual
and/or previous great blue heron nest sites) were made using a tape measure, aerial
photography, or by using data obtained by the West Virginia Division of Natural
Resources (Hays et al. 1981). I assessed disturbance-free zones (i.e., 100, 150, and
250 m) for the great blue heron model using aerial photos. Likewise, I used visual
observations to evaluate the presence of adequate great blue heron foraging areas
(i.e., clear water with a suitable prey population of small fish ≤25 cm and a firm
substrate). A 0.5 was assigned to this variable if fish were not present. For the
beaver, muskrat, mink, snapping turtle, and red-winged blackbird HSI models, I used
visual observations to evaluate fluctuations in water regime for each wetland.
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For the wood duck HSI model, I measured the number of potentially suitable
nesting tree cavities/0.4 ha (minimum entry openings of 7.6 × 10.0 cm) using 6
randomly placed 0.05 ha quadrats within the nearest forest ≤500 m of the edge of the
wetland basin. A total count of the number of artificial nest boxes (predator proofed
and maintained) was conducted at each wetland. The total area of the wetland was
used to extrapolate the number of artificial nests/0.4 ha, as necessary by the wood
duck HSI model. For all species evaluated, a minimum SI value of 0.75 was used to
conclude adequate habitat suitability for specific species, and values less than 0.25
were indicative of poor habitat quality. Optimal SI values for all variables measured
are included in Table 1.
Statistical Analyses
Mitigation and natural wetlands were compared using SAS (1988). For all
avian analyses, I included only those birds sampled within the 50 m radius (0.78 ha)
plots. I used a split-plot analysis of variance design (ANOVA) to test for differences
in avian richness (no. species/0.78 ha plot), abundance (no. birds/0.78 ha plot), and
diversity (per 0.78 ha plot) between mitigation and natural wetlands. Avian diversity
was calculated using the Shannon-Weiner Index (Shannon and Weaver 1949). Avian
species included in the waterbird analysis were Canada goose, mallard (Anas
platyrhynchos), wood duck, black duck (A. rubripes), green heron (Butorides
virescens), great blue heron, belted kingfisher (Ceryle alcyon) spotted sandpiper
(Actitis macularia), Virginia rail, and sora. Canada goose, mallard, wood duck, and
black duck were included in the waterfowl analysis.
158
I used a 2-way ANOVA with a repeated measures design to compare anuran
richness because 3 survey periods were repeated both years. For avian and anuran
analyses, the independent variables tested were year, type (mitigation vs. reference),
and year × type interactions with the dependent variables varying depending on
which taxa was being analyzed. I used individual wetlands as experimental units.
Because Wisconsin Index (WI) and anuran abundance metrics were categorical
variables, I used logistic regression to compare mitigation and natural wetlands.
Abundance estimates were obtained using SAS and grouped into intervals (i.e., 2-5,
6-15, 16-25, 26-35, and 50), which allowed them to be treated as categorical
variables. Only the mid-point of each interval was used for analyses. Logistic
regression also was needed because of unequal variances associated with WI and
abundance variables. I used an area × year × sampling period combination as a
blocking factor for logisic regression. For all other avian and anuran analyses,
geographic area was a blocking factor.
For HSI value comparisons, I used a 1-way ANOVA with geographic area as
a blocking factor to test the wetland type effect. Because HSI variables were
collected for only 1 year, no year effect was tested. Assumptions of normality were
tested with the univariate procedure in SAS, and Levene�s Test was used for
homogeneity of variances. Rank, square-root, and quarter-root transformations were
used to convert dependent variables that did not meet the aforementioned
assumptions (Dowdy and Wearden 1991). Specifically, square-root transformations
were incorporated in anuran WI comparisons, and rank transformations were used to
analyze avian communities.
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RESULTS
Avian Communities
I observed a total of 91 species of birds in mitigation and natural wetlands
(Appendix 37). In mitigation sites, 2,074 individuals from 86 species were sampled
(Appendix 38), and in natural sites, 771 individuals from 62 species were sampled
(Appendix 39). For all species sampled, mean species richness (F1,10 = 0.15, P =
0.711), diversity (F1,10 = 1.1, P = 0.314) , and abundance (F1,10 = 0.03, P = 0.856)
were similar between mitigation and natural wetlands (Table 2). Mean abundance for
the 20 most common avian species sampled was similar (F1,10 = 0.07, P = 0.800)
between mitigation and natural wetlands (Table 2). Out of these common species,
wood duck (F1,10 = 5.80, P = 0.037) and American goldfinch (F1,10 = 9.24, P = 0.013)
were more abundant in mitigation wetlands, whereas song sparrow (F1,10 = 5.94, P =
0.035) was more abundant in natural wetlands (Table 2). Great blue heron abundance
was similar (F1,10 = 0.28, P = 0.610) between wetland types. All other common
species also were similar (F1,10 ≤ 4.57, P ≥ 0.058) between wetland types. Passerine
abundance (72 species combined) was similar (F1,10 = 0.41, P = 0.537) between
mitigation and natural wetlands. However, waterbird (F1,10 = 9.08, P = 0.013) and
waterfowl (F1,10 = 9.23, P = 0.013) abundance were higher in mitigation wetlands
than natural wetlands.
Two rail species were sampled at 2 mitigation wetlands. Three sora were
sampled at Buffalo Coal during the first surveys of both years. Similarly, 3 sora were
sampled at Walnut Bottom during the first survey of year 2. Five and 2 Virginia rail
were sampled at Buffalo Coal during the second surveys of years 1 and 2,
160
respectively. No rail species were sampled at natural wetlands, and no bittern or
pied-billed grebe were sampled at any wetland.
Anuran Communities
Seven species of anurans were heard, all of which occurred in both mitigation
(Appendix 40) and natural (Appendix 41) wetlands. These included spring peeper,
gray treefrog, American bullfrog, wood frog, green frog, American toad, and pickerel
frog. Mean species richness was higher in mitigation ( x = 2.01 species/point, SE =
0.09) than natural ( x = 1.47, SE = 0.14) wetlands (F1,10 = 7.18, P = 0.023). In
addition, Wisconsin Index (WI) values (Χ2 = 14.51, P < 0.001) and abundance (Χ2 =
11.35, P < 0.001) were higher in mitigation than natural wetlands (Table 3).
Wisconsin Index and abundance (A) comparisons also were made for each species
detected (Table 3). For these indices, American bullfrog (WI: Χ2 = 4.56, P = 0.033;
A: Χ2 = 4.30, P = 0.038), green frog (WI: Χ2 = 6.36, P = 0.012; A: Χ2 = 5.64, P =
0.018), and pickerel frog (WI: Χ2 = 8.73, P = 0.003; A: Χ2 = 8.08, P = 0.005) were
higher in mitigation than natural wetlands, whereas spring peeper (WI: Χ2 = 0.61, P =
0.434; A: Χ2 = 1.46, P = 0.228), gray treefrog (WI: Χ2 = 0.88, P = 0.348; A: Χ2 =
0.60, P = 0.440), wood frog (WI: Χ2 = 2.87, P = 0.090; A: Χ2 = 2.76, P = 0.097), and
American toad (WI: Χ2 = 3.66, P = 0.056; A: Χ2 = 3.58, P = 0.059) were similar
between wetland types (Table 3).
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Habitat Quality Habitat Suitability Index scores for all 8 species combined were similar (F =
0.57, P = 0.469) between mitigation and natural wetlands (Table 4). Red-winged
blackbird (F1,10 = 21.3, P = 0.001) and beaver (F1,10 = 5.77, P = 0.037) Suitability
Index (SI) values were higher in natural wetlands, whereas muskrat (F1,10 = 3.13, P =
0.107), mink (F1,10 = 1.58, P = 0.238), great blue heron (F1,10 = 0.56, P = 0.472),
wood duck (F1,10 = 0.76, P = 0.403), snapping turtle (F1,10 = 3.66, P = 0.085), and red-
spotted newt (F1,10 = 2.17, P = 0.172) SI values were similar between wetland types
(Table 4). Complete statistical results of all applicable HSI variables (i.e., actual
mean values) between mitigation and natural wetlands are provided in Appendix 42.
Comparisons of mean SI values per variable between wetland types are provided in
Appendix 43. Results for all variables measured for each HSI model by wetland
study site are included in Appendices 44-51.
Red-winged Blackbird.-- The red-winged blackbird model considered blackbird food and reproduction
requirements. According to the model, mitigation and natural wetlands contained
poor quality habitat. While mitigation wetlands contained optimal surface water
(variable 2) and food availability (variable 3), percent emergent vegetation (variable
5) was moderate (Table 3). Three variables limited mitigation wetland performance
in this model. These included percent emergent vegetation (variable 5), percent
broad-leaved monocots (variable 1), and presence of carp (variable 3).
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Beaver.--
The beaver HSI model considered the availability of water and winter food.
Although mitigation wetlands scored a lower beaver SI score than natural wetlands,
they still contained suitable beaver habitat. The amount of tree (variable 1) and shrub
(variable 4) cover within 100 m and 200 m of mitigation sites was within adequate
range of beaver requirements (Table 1). Likewise, the species composition of woody
vegetation (variable 5) within mitigation sites consisted primarily of brookside alder
(Alnus serrulata) and speckled alder (A. incana), which increased the SI value of this
variable. Two variables, however, limited mitigation wetland performance in the
beaver HSI model. These included the percentage of trees with a DBH between 2.5
and 15.2 cm (variable 2) and the percentage of shrub crown cover (variable 3).
Muskrat.--
The muskrat HSI model was divided into 2 components: food and cover.
While mitigation wetlands contained adequate water surface (variable 2) and
emergent vegetation (variable 1) to satisfy muskrat cover requirements, they lacked
the composition of vegetation (variable 3) most desirable as food to muskrat (Table
3).
Mink.--
Similar to the muskrat HSI model, the mink model assessed the suitability of
wetlands to sustain adequate mink food and cover. Both wetland types contained
suitable mink habitat. Specifically, they contained adequate surface water (variable
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1), persistent emergent vegetation (variable 2), and percent tree/shrub cover within
100 m of the water�s edge (variable 3; Table 1).
Great Blue Heron.--
The great blue heron HSI model consisted of 2 major components: food and
reproduction. According to the model, mitigation wetlands contained adequate heron
foraging habitat. Both wetland types contained potential nesting sites within a
reasonable distance of foraging locations (variable 1), and both possessed
environmental conditions suitable to support prey populations (variable 2) while
allowing disturbance-free foraging (variable 3; Table 1). Mitigation sites scored low
reproduction SI values. While all sites contained forests ≥0.4 ha within 250 m of the
wetland edge (variable 4), and while most nesting sites met disturbance-free criteria
(variable 5), the distance between potential nesting sites and actual or previous
nesting sites (variable 6) exceeded optimal criteria for all study sites. I found that the
closest heronries on record to most sites were located in Doddridge, Calhoun, and
Randolph Counties, which were ≥32.0 km from these study sites (West Virginia
Division of Natural Resources, unpublished report).
Wood Duck.--
The wood duck HSI model was subdivided into breeding and wintering
models. According to the wood duck model, mitigation wetlands contained suitable
year-round wood duck habitat. This was attributable to the suitability of mitigation
wetlands in supporting adequate breeding and wintering habitat. While mitigation
sites appeared to support moderate wood duck breeding habitat based on the breeding
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model SI value, this was attributable to low SI values for only a few wetlands. The
main factor limiting the breeding habitat quality was the density of potential nesting
sites, both natural and artificial (variable 3; Table 1). While all but 1 mitigation site
(Walnut Bottom) contained at least some potential natural cavities either within or
around the wetlands, only 5 of 11 mitigation sites (VEPCO, Buffalo Coal, Triangle,
Sugar Creek, and Sand Run) contained artificial nest boxes. Despite relatively low
nest site densities, the percentage of potential brood cover (variable 4) in mitigation
sites was high. In turn, these factors led to variable SI values for the percentage of
wetland areas containing optimal nesting (variable 5) and brood rearing (variable 6)
habitat. Because of the limiting factor approach to model output calculation, mean
breeding SI values were low. Like the breeding model, the winter model scored
variable SI values across mitigation wetlands. Because final model SI values were
determined based on the higher values between breeding and wintering models,
overall wood duck SI values were relatively high in mitigation wetlands.
Red-spotted Newt.--
The red-spotted newt HSI model considered the suitability of habitat for cover
and reproduction. According to the model, suitable red-spotted newt habitat existed
within mitigation wetlands. Similar to natural wetlands, mitigation wetlands were
always <2 m in depth (variable 1), contained an adequate percentage of aquatic
vegetative cover (variable 2), including submerged aquatic vegetation, and were
located within a reasonable distance of forested cover types (variable 3; Table 1).
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Snapping Turtle.--
The snapping turtle HSI model was divided into 4 components for evaluation:
food, winter cover, reproduction, and interspersion. Snapping turtles scored a low
overall SI value in both mitigation and natural wetlands. Because snapping turtles are
opportunistic feeders, the model considered water temperature (variable 1), water
velocity (variable 2), and percent aquatic vegetation (variable 3) as important factors
associated with turtle feeding. Mean water temperature and velocity were within the
optimal range of snapping turtle preferences in mitigation wetlands, while percent
aquatic vegetation scored an above average rating (Table 1). Similarly, both wetland
types were situated near small streams (variable 6), thus increasing the reproductive
SI value, and all wetlands contained permanent water in at least some portion of the
complex (variable 7). This increased the interspersion SI value. The main limiting
factor in this model occurred within the winter cover component. While mitigation
and natural sites were deep enough to prevent complete freezing (variable 4), both
wetland types contained relatively low percentages of silt in the substrate (variable 5).
DISCUSSION
Avian Communities
Almost every avian metric I measured in mitigation wetlands was equal to or
greater than natural wetlands. No differences emerged in total species richness,
diversity, and abundance probably because of similarities in landscape position. Both
wetland types were generally located near forested stands, so wetland, edge, and
forest-interior species had an equal chance of being sampled between wetland types.
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Similarly, both wetland types were either adjacent or connected to other wetlands,
streams or large rivers. Although some studies have found human disturbance to
negatively affect wildlife numbers (Wilson and Mitsch 1996), the proximity of
mitigation and natural sites to human disturbances (i.e., major roads) appeared to
have minimal effects on avian numbers. Although it is known that wetland size
affects avian richness (MacArthur and Wilson 1967, Tyser 1983, Delphey and
Dinsmore 1993), the fact that natural wetlands were about 3 times larger than
mitigation wetlands had little effect on avian metrics relative to mitigation wetlands.
Mitigation wetlands, however, supported higher waterbird and waterfowl
abundance than natural wetlands. Because mitigation sites are so young (5-20 years
of age), they differed significantly in their vegetation community structure than
natural sites (Chapter II). Not only did mitigation sites contain more open water and
support less emergent aquatic vegetation than natural wetlands, they contained higher
plant species richness and diversity than natural wetlands. In fact, mitigation
wetlands contained 40.8% open water, whereas natural wetlands contained only
11.6% open water. This has been found to be true of most natural wetlands in the
Appalachian Region (Cole and Brooks 2000).
An evaluation of waterbird abundance within mitigation sites supports the
assertion that open water affects waterbird abundance. The lowest waterbird
abundances occurred in 2 mitigation wetlands with the lowest percentages of open
water (Chapter V). These sites also contained relatively low amounts of submerged
aquatic vegetation. VanRees-Siewert and Dinsmore (1996) showed that, although
total bird richness increased with increasing emergent vegetation, waterfowl and
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shorebirds preferred younger restored wetlands with more open water and mud flats.
Overall, mitigation wetlands in this study were closer to hemimarsh conditions where
an equal percentage of open water to emergent vegetation exists. Hemimarsh
conditions provide the best combination of food and cover for waterbirds (Kaminski
and Price 1981, Bookhout et al. 1989, Murkin et al. 1997). Based on these and other
studies, many have concluded that �wetter is better� in terms of constructing
wetlands. As a result, mitigation wetlands are often structurally dissimilar to the
natural wetlands they are designed to mimic, thus indicating an inability to
functionally replace those wetlands that were destroyed (Cole and Brooks 2000).
This stresses the importance of not having too much open water in mitigation
wetlands.
Waterbird abundance also may be affected by higher vegetative richness and
diversity indices observed in mitigation wetlands over natural wetlands (Chapter II).
These differences may result in an increase in the type, quantity, and quality of plant
foods while at the same time maximizing the distribution, density, and structure of
cover available for waterbirds in mitigation wetlands (De Szalay and Resh 1997,
Brown 1999). Differences in vegetation community structure may have created
favorable water chemistry and hydroperiod conditions in mitigation sites as well
(Goslee et al.1997, Castelli et al. 2000).
Similarly, I observed a higher overall nektonic macroinvertebrate biomass
within open water areas of mitigation wetlands (Chapter IV). Within both emergent
and open water areas, we observed more nektonic Planorbidae (orb snails) and
Physidae (physids), Corixidae (water boatman), Coenagrionidae (damselflies), and
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Caenidae (mayflies) in mitigation wetlands. Within open water areas, benthic
Oligochaetes (aquatic worms) also were higher in mitigation wetlands. This is
particularly important because studies have shown that these taxa are important
components in waterbird diets (Euliss et al. 1991, Anderson et al. 2000). These
differences in macroinvertebrate populations may account for differences in waterbird
abundance observed between mitigation and natural wetlands.
Other studies comparing waterbirds between mitigation and natural wetlands
have shown conflicting results. Similar to my study, Havens et al. (1995) observed
similar overall species diversity between mitigation and natural wetlands in Virginia,
but higher wading bird abundances occurred in constructed marshes. However,
Confer and Niering (1992) included waterbirds in their assessment of wildlife in
constructed and natural wetlands in Connecticut, and they observed higher wildlife
activity (overall species richness) in natural wetlands. They attributed low wildlife
indices in constructed wetlands to their isolation and relative small size. While other
studies also have shown higher avian richness and diversity in natural wetlands
(Delphey and Dinsmore, 1993, Melvin and Webb 1998), others have yielded similar
avian indices between wetland types (Perry et al. 1996, Brown and Smith 1998). It is
likely that, given the similarities in landscape position between wetland types, the
increased richness and diversity of vegetation offered in our mitigation sites was
balanced by the increased percentage of emergent vegetation in natural wetlands, thus
resulting in similar overall avian community structure between wetland types.
Great blue heron and wood duck were of particular interest because the
quality of habitat for these species was evaluated using HSI models. Although
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densities of great blue heron were higher in mitigation sites, no statistical difference
emerged. These similarities are reflected by similarities in HSI values between
wetland types. Details explaining these similarities are outlined below in the habitat
quality section of this chapter. Similar to waterbirds, differences in percent emergent
vegetation and vegetation community structure probably account for higher wood
duck abundance observed in mitigation wetlands. In fact, no wood duck were
sampled in any natural wetlands. Further speculations regarding wood duck
abundance are explained below in the habitat quality section of this chapter.
Little is known about the abundance and distribution of rails, bitterns, and
pied-billed grebes in West Virginia. While other studies have found colonization by
rail and bittern species into constructed and restored wetlands (Delphey and
Dinsmore 1993, Dick 1993, Zedler 1993, Vanrees-Siewert and Dinsmore 1996, White
and Bayley 1999), use of mitigation wetlands in West Virginia was unknown prior to
this study. While all of these species may breed throughout the state (Buckelew and
Hall 1994), they have been confirmed as breeding only in Tucker and Jefferson
Counties (Buckelew and Hall 1994). Hence, my results were somewhat expected,
especially given the amount of seemingly suitable habitat present in mitigation
wetlands in those areas (Kaufman, 1996, Linz et al. 1997). Both Buffalo Coal
(Tucker County) and Walnut Bottom (Hardy County) contained an even mixture of
open water to shallow emergent areas dominated by broad-leaved cattail (Typha
latifolia) and common rush (Juncus effusus). I expected to encounter breeding rails,
bitterns, or grebes in at least 1 of the natural wetlands located in either Tucker (Elder
Swamp) or Jefferson (Altona Marsh) Counties, although Altona Marsh may have
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lacked sufficient open water to support pied-billed grebe. Elder Swamp was located
in Tucker County 12.0 km from Buffalo Coal. It is possible that this Sphagnum
dominated bog lacked the shallow emergent areas necessary for breeding and
protection to sustain these species. The other natural wetlands either contained too
many shrubs or emergent vegetation, or were too deep. Future monitoring of these
elusive species may confirm their breeding in these and other wetlands throughout the
state.
These data indicate that mitigation wetlands in West Virginia, despite their
proximity to human disturbances, are supporting healthy avian communities,
particularly waterbirds. High avian numbers in mitigation wetlands are likely due to
wetland size and landscape position, as well as vegetative structure and diversity and
invertebrate community structure. Future studies should correlate changes in
vegetation and invertebrate communities to avian community structure.
Anuran Communities
It is not surprising that anurans have colonized mitigation wetlands so rapidly.
In fact, spring peepers, American bullfrogs, American toads, and gray treefrogs may
colonize created wetlands ≤2 years after construction (Perry et al. 1996, Mierzwa
2000, Pechmann et al. 2001). Colonization rates are generally affected by distance to
other ponds, dispersal habitat, dispersal capabilities, site fidelity of a particular
species, and size of source populations (Laan and Verboom 1990). The proximity of
my study sites to streams, rivers, and other wetlands along with the relatively large
size of mitigation sites likely contributed to rapid dispersal and colonization
(Wolfenbarger 1949, Lacki et al. 1992, Gibbs 1993, Stevens et al. 2002).
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I expected to encounter Fowler�s toad (Bufo fowleri) and mountain chorus
frog (Pseudacris brachyphona) as these species are well distributed throughout the
state. Likewise, I expected to encounter upland chorus frog (Pseudacris triseriata
feriarum) within wetlands located along the eastern panhandle (Green and Pauley
1987). Because cricket frogs (Acris crepitans) also are known to breed along the
eastern panhandle, I expected to observe them within 1 natural (Altona Marsh) or 1
mitigation (Walnut Bottom) wetland located in this area. In fact, 1 cricket frog was
observed at Altona Marsh, but it was not detected during anuran surveys. It is
possible that spadefoot toads (Scaphiopus holbrookii) use at least some mitigation or
natural wetlands within the state, but their explosive short-term breeding cycle,
fossorial lifestyle, and overall scarcity in the state make this species difficult to detect
(Green and Pauley 1987).
Mitigation wetlands in West Virginia contained higher anuran mean richness,
Wisconsin Index, and abundance values than natural wetlands. Similar to my study,
Stevens et al. (2002) observed a higher overall mean richness as well as green frog
abundance in restored than natural wetlands. Although they observed a positive
correlation between green frog abundance and percentage of cattail in restored
wetlands, my results suggest cattail may have a relatively minimal effect on green
frog abundance. Because mitigation wetlands (13.6%) contained less cattail than
natural wetlands (42.8%), yet they sustained more green frog, I think open water may
play a larger role in determining abundance of green frog, as well as American
bullfrog and pickerel frog. Lacki et al. (1992) also observed more green frogs in a
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constructed wetland in Ohio, and Pechmann et al. (2001) observed more American
bullfrogs in constructed than natural wetlands in South Carolina.
Because American toads, spring peepers, and wood frogs are less dependent
on permanent water sources (Gilhen 1984, Cook 1984), I expected these species to be
relatively more abundant than other anuran species in natural wetlands. Consistent
with this speculation, relative abundance of these species were similar between
mitigation and natural wetlands.
Many important factors may account for anuran community differences
observed between mitigation and natural wetlands. Primarily, studies have shown
that open water is positively correlated with amphibian abundance (Lacki et al. 1992,
Stevens et al. 2002). As aforementioned, mitigation wetlands more closely resembled
hemimarsh conditions by containing more open water than natural wetlands. Like
avian communities, anuran communities benefit from these conditions (Stumpel and
Van Der Voet 1998). Although hydrologic data are incomplete for our study sites,
these data may indicate an extended hydroperiod in mitigation wetlands, which may
prevent drying and subsequent tadpole mortality prior to metamorphosis. Thus,
species with longer larval periods such as American bullfrog, green frog, and pickerel
frog may have been excluded from natural wetlands with shorter hydroperiods
(Babbit and Tanner 2000, Semlitsch 2002). This may not necessarily be a limiting
factor because pond drying is a natural process that eliminates or reduces predation
on and competition among larval amphibians (Semlitsch 2000). On the contrary,
maintaining wetlands with extremely long hydroperiods may be harmful to anuran
populations because it may facilitate colonization of aquatic invertebrate and fish
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predators (Semlitsch 2002). Water depth also plays an important role in amphibian
colonization (Stevens et al. 2002). Deeper water prevents complete freezing, which
provides winter hibernacula for anurans (Cook 1984, Cunjak 1986). I found that both
mitigation and natural wetlands contained areas with sufficient hibernacula, but based
on water depth estimations, mitigation wetlands contained deeper water with more
potential wintering habitat. Furthermore, shorter distance to forests and higher
percentage of shrub cover increases anuran richness by providing cover and dispersal
corridors for post-breeding or newly metamorphosed individuals (Stevens et al.
2002). This may be of particular importance to wood frogs, which disperse long
distances via forested cover types to other wetlands (Berven and Grudzien 1990,
DeMaynadier and Hunter 1999). As well, forested perimeters may buffer wetlands
from agricultural activities, which have been linked to larval death and limb
deformities in amphibians (Berrill et al. 1997, Ouellet et al. 1997). They also may
buffer against negative impacts associated with cattle grazing. Wood frog and chorus
frog populations, in particular, are known to be sensitive to this disturbance (Ambrose
and Paskowski 1998). As mentioned in the avian discussion, mitigation and natural
wetlands shared similar landscape positions adjacent to forests. While all natural
sites were bordered immediately by forests, mitigation wetlands averaged only 14.5
m to the nearest forest. Thus, anurans in both wetland types likely benefit from
forested perimeters. Although natural wetlands contained a higher percentage of
shrub cover (27.8 vs. 7.5 in mitigation sites), lack of open water is likely limiting
anuran numbers. Shrub communities had successfully been established at 9 of 11
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mitigation wetlands, and percent coverage should increase as these wetlands mature
(Chapter II). This will be valuable in maintaining future diverse anuran habitat.
Similar to waterbird communities, differences in anuran communities may be
attributed to differences in invertebrate (Chapter IV) and vegetation (Chapter II)
communities between mitigation and natural sites. Because frogs depend on
invertebrates for their diet (Anderson et al. 1999b, Lima and Magnusson 2000), it is
expected that anuran abundance and distribution could reflect higher invertebrate
nektonic biomass densities across open water areas of mitigation wetlands. Similarly,
higher vegetative species richness and diversity may provide more diverse
microhabitats for oviposition, foraging, growth, and refuge (Stratman 2000).
Few anuran species (i.e., cricket frog, American bullfrog, green frog) can
coexist with predatory fish species (Semlitsch 2002), but studies offer conflicting
evidence as to the effect of predatory fish on anuran populations (Hecnar and
M�Closkey 1997, Lehtinen et al. 1999, Pechmann et al. 2001, Semlitsch 2002).
Despite fish populations in 9 of 11 (Vepco and Buffalo Coal did not contain fish)
mitigation wetlands and 3 of 4 (Meadowville did not contain fish) natural wetlands,
these sites continue to support healthy anuran populations. In fact, some of the
highest frog index values were obtained in wetlands that contained fish. It is
important to note that some mitigation sites consisted of numerous open water cells,
some of which did not contain fish. These areas may be used as a refuge for breeding
frogs, thus minimizing potential negative impacts caused by fish populations.
Furthermore, high anuran populations in wetlands that contain fish may be attributed
to an increase in the macroinvertebrate prey base, which can result indirectly from
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increases in predatory fish populations (Batzer et al. 2000). A more detailed study
would be needed to accurately assess the impact of fish populations on anuran
communities among mitigation wetlands in West Virginia. Even if data were to show
a negative impact of fish populations on anurans, it would be difficult to prevent the
invasion of fish into wetlands mitigation adjacent to streams or rivers.
Numerous mitigation sites were built on-site as mitigation for the construction
of a major highway in West Virginia. However, the proximity of mitigation wetlands
to major roads did not seem to adversely affect current anuran abundance. In fact, 2
sites (Sand Run and Triangle) scored among the highest richness and WI values,
respectively, of all mitigation sites. However, studies have correlated low amphibian,
as well as reptile numbers to road density (Fahrig et al. 1995, Lehtinen et al. 1999,
Haxton 2000, Trombulak and Frissel 2000). The limiting factor, however, is not
necessarily the traffic, although amphibian mortality due to vehicular collisions is not
uncommon (Fahrig et al. 1995). Roads, acting as barriers to dispersal, may have
long-term effects on metapopulation dynamics by deteriorating the genetic integrity
of localized populations (Trombulak and Frissell 2000). In addition, roads potentially
change soil density, temperature and water content, surface waters, patterns of run-
off, and sedimentation, as well as adding heavy metals to roadside environments
(Trombulak and Frissell 2000, Bridges and Semlitsch 2002). Problems associated
with dispersal may not manifest themselves within anuran populations located at my
study sites because of their proximity to streams, rivers, and other wetlands.
However, research should monitor road-related stresses to the environment and their
potential effect on anuran populations within mitigation wetlands. Although wetland
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construction near roads can potentially have long-term negative impacts, there are
numerous logistical benefits associated with on-site design and construction. As well,
on-site mitigation sites can facilitate colonization by philopatric anuran species.
Despite my confidence in the incorporation of a sampling scheme that
accurately encompassed temporal variation in anuran breeding for this study, future
survey schedules should incorporate local water-temperature and humidity
measurements, as studies have indicated their influence on anuran breeding variation
(Green 1997, Lepage et al. 1997). Furthermore, without information on reproductive
success, I cannot adequately assess the long-term success of mitigation wetlands in
supporting anuran populations. On a metapopulation scale, some sites could be
acting as sinks (Pulliam 1988). Additional survey techniques including pitfall traps,
dip nets, or egg mass searches could accompany call-count surveys in future studies.
This would provide researchers with information on dispersal and recruitment in
addition to distribution and abundance. As well, future studies should address
surrounding land-use of mitigation sites. Surrounding uplands have a large influence
on anuran breeding distribution, particularly for those that have an adult terrestrial
phase. Nevertheless, recent concern over declining amphibian populations has drawn
attention to the need to compensate for loss of amphibian habitat. My data provide,
both an assessment of the success of mitigation wetlands in West Virginia in
supporting anuran communities, and a sound framework for future research that
monitors anuran community responses to structural changes in these wetlands through
time.
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Habitat Quality
Habitat Suitability Index (HSI) models offer a simple and repeatable method
of comparing the relative habitat quality of specific species between mitigation and
natural wetlands. The HSI models chosen for this study represent a variety of
wetland�dependent taxonomic groups that are considered good indicators of wetland
function.
It was not surprising that model outputs for all species combined were similar
between mitigation and natural wetlands. Because the target species possessed a
broad range of habitat requirements, I expected certain species to score higher in
mitigation wetlands while others would score higher values in natural wetlands.
Indeed, this was the case, but statistical differences were only detected for red-winged
blackbird and beaver.
Red-winged Blackbird.--
According to the red-winged blackbird HSI model, mitigation and natural
wetlands contained poor blackbird habitat, but with natural wetlands containing
higher quality habitat than mitigation wetlands. First, natural wetlands contained
more than twice the percentage of broad-leaved monocots than mitigation wetlands.
This can primarily be attributed to higher amounts of cattail in natural wetlands. Red-
winged blackbirds generally nest in emergent wetlands with tall, dense herbaceous
vegetation, preferably cattail (Short 1985, Stanislav and Picman 1997). Cattail also is
important to other species. Although cattail can form monotypic stands that exclude
desirable diverse native species (Boutin and Keddy 1993), it can provide cover for
wintering waterfowl and amphibians. In addition, carp were absent from every
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natural wetland, whereas they were present in 1 mitigation site (Trus Joist
MacMillan). Carp can disturb submerged aquatic vegetation (McKnight and Hepp
1995), which may decrease habitat for emergent aquatic insects that blackbirds prefer
to forage.
Although mitigation and natural wetlands scored low SI values, breeding bird
surveys confirmed healthy red-winged blackbird populations in both wetland types.
In fact, blackbird abundance was similar between natural and mitigation wetlands
(Chapter V). This may indicate poor calibration during the development phase of this
model. In its current state, this model weighs each variable equally, and too little
weight may be given to surface water and Odonate variables. It is tempting, based on
red-winged blackbird abundances observed at these sites, to conclude that high
quality habitat exists, thus questioning the validity of the model. However, a much
larger study would be needed to adequately test this assumption. Although the
objective of this study was not to validate the red-winged blackbird HSI model, I still
conclude that mitigation and natural wetlands both contain suitable blackbird habitat.
Beaver.--
The beaver HSI model also yielded a higher mean SI value in natural
wetlands. Specifically, the percentage of trees with a DBH between 2.5 and 15.2 cm
DBH was higher in natural wetlands within 100 and 200 m of the wetland basin.
Similarly, the percentage of shrubs was higher in natural wetlands, both within the
wetland basin, and within 100 and 200 m of the water�s edge. Beavers forage on
trees and shrubs throughout the year, but more so during the winter when herbaceous
vegetation may be limiting (Allen 1983, Barnes and Mallik 2001). Although
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mitigation wetlands contained fewer trees within the desired DBH scale, they
contained similar percentages of overall upland tree canopy coverage. Beavers are
not the only species that can benefit from increased tree and shrub cover. A higher
percentage of canopy coverage in and around the wetland should attract diverse
guilds of songbirds while at the same time offering protection to some game species
that may use these wetlands. Mitigation wetlands should develop shrub thickets
through time, thus progressing towards the replacement of additional lost wetland
functions by offering continued wildlife benefits associated with these communities.
Unlike the red-winged blackbird HSI model, the beaver model resulted in a
more expected, and perhaps, more realistic SI value. Beavers were confirmed at 6
mitigation sites (Elk Run, Sand Run, Triangle, Trus Joist MacMillan, Enoch Branch,
and Bear Run) and at 3 of 4 natural sites (Altona Marsh, Elder Swamp, and
Muddlety), so model outputs appear to reflect beaver habitat use of mitigation and
natural wetlands. This outcome may be positive or negative, depending on one�s
view of beaver-wetland ecosystem interactions.
Muskrat.--
The muskrat HSI model yielded similar SI values between mitigation and
natural wetlands. Both wetland types contained adequate cover for muskrat, because
similar to waterfowl and anuran requirements, hemimarsh conditions provided
optimal foraging and cover habitat for muskrats (Allen and Hoffman 1984).
Mitigation and natural wetlands also contained at least some surface water year
round. The main limiting factor for the muskrat model was the food component.
Specifically, the percentage of emergent vegetation consisting of cattail, common 3-
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square (Scirpus americanus), or olney bulrush (S. olneyi) was low in both wetland
types. These species have frequently been documented as a highly preferred food and
cover source for muskrats (Bellrose 1950, Sather 1958, Campbell and MacArthur
1994, 1998). The low output by this variable is arguable, however, because muskrat
sign was observed at many sites. Too much emphasis may have been placed on
vegetation composition during model development. Although cattail, common 3-
square, and olney bulrush are the preferred food items of muskrat, they will forage on
other aquatic emergent species as well as some terrestrial species (Perry 1982). Virgl
and Messier (1997) concluded that food was not a key factor limiting distribution of
muskrat. Yet, the model scores this variable only a 0.1 when preferred vegetation
species are limiting. I recommend a minimum baseline value of 0.5 instead of 0.1
when evaluating this variable. This would better reflect the diverse food preferences
of muskrat in the face of variable limiting food resources, and hence, more accurately
reflect muskrat habitat use of mitigation wetlands.
Mink.--
The mink HSI model also yielded SI values similar between mitigation and
natural wetlands. Both wetland types contained surface water year round, and both
contained similar amounts of persistent emergent vegetation within the wetland basin,
as well as similar percentages of tree and shrub crown cover within 100 m of the
wetland. It is assumed by the model that the amount of persistent emergent
vegetation was sufficient to support an adequate prey base while at the same time
offering protective cover. Similarly, the amount of forest and shrub cover ≤100 m
from the wetland edge provided sufficient terrestrial food base during the fall and
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winter (Melquist et al. 1981, Allen 1984). This also may provide important vertical
and spatial structure for songbirds, amphibians, and other mammals. Mink diet is
diverse and includes aquatic (fish, crayfish, amphibians), semiaquatic (waterfowl,
muskrat), and terrestrial (rabbits, rodents) prey species (Allen 1984, Jedrzejewska et
al. 2001, Sidorovich et al. 2001). They also adapt well to variable environments,
especially prey availability, and are known to be highly mobile (Allen 1984). In
addition, mink are nocturnal, so they are difficult to detect. Thus, they were
confirmed at only 2 mitigation sites (Walnut Bottom, Leading Creek), and at no
natural sites. Nevertheless, mitigation wetlands appear to contain quality mink
habitat.
Great Blue Heron.--
In addition, the great blue heron HSI model output was similar between
mitigation and natural wetlands. Within the foraging component of the model,
mitigation and natural wetlands contained similar mean distances between potential
nesting and foraging areas of 36.7 and 37.5 m, respectively. These values reflect the
close proximity of forests to my study sites. This may benefit other wildlife species
by providing nearby escape cover while at the same time providing cover for
predators. The foraging component of the heron model also incorporates water depth
and color, substrate type, and presence of fish into variable 2. For this variable, the
researcher is left with an �all or none� approach that precludes any continuum that
may exist within these criteria. Some wetlands, for instance, contained suitable water
and substrate conditions but no fish. And even though a wetland may not currently
contain fish, there still is potential to support fish in the future due to transplantations
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or flooding. Add this to the fact that heron will forage on prey other than fish such as
amphibians or reptiles (Kushlan 1978, Szelistowski and Meylan 1996), I decided to
score this variable a 0.5, even if fish were not present. Indeed, the shallow, clear
water within these mitigation wetlands is ideal foraging habitat not just for great blue
heron. Other waterbirds, including mallards, wood ducks, green herons, belted
kingfishers, rails, or migrating shorebirds benefit from these conditions.
Additionally, continued growth of submerged aquatic vegetation is favored, which
also is a valuable food source for these and other waterbirds. Finally, while roads
with moderate traffic were <100 m from mitigation wetland edges, suitable heron
foraging areas existed within the interior of these sites, and thus, met disturbance-free
criteria at all mitigation sites.
Although mitigation and natural wetlands contained sufficient great blue
heron foraging habitat, they scored low reproduction component SI values. As
aforementioned, the distance between potential nesting sites to actual or previous
nesting sites was too great to provide optimal heron nesting habitat. Great blue
herons rarely travel far to establish new rookeries once an old one is vacated (Custer
et al. 1980, Kelsall and Simpson 1980), and they rarely travel distances >16 km to
forage. I suspect closer heronries exist near our study sites than those obtained from
the West Virginia Division of Natural Resources, and thus conclude that this variable
may underrepresent actual heron habitat suitability within both wetland types. Since
accurate rookery information is probably lacking for West Virginia, I cannot fault
model development for this inconsistency.
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Field observations confirmed the suitability of mitigation wetlands in
supporting great blue herons. Herons were observed (but not sampled) at 2 mitigation
sites (Bear Run and Triangle) and 1 natural site (Altona Marsh), and were actually
sampled at 7 mitigation sites (Walnut Bottom, Buffalo Coal, Elk Run, Leading
Creek, Sand Run, Trus Joist MacMillan, and Enoch Branch) and 1 natural site
(Muddlety). In most cases, herons were observed foraging or flying nearby.
Therefore, it appears that required disturbance-free zones surrounding foraging areas
accurately predicted heron foraging tolerance. However, no rookeries or nests were
observed at any of the study sites. Even though mitigation wetlands generally met
nesting disturbance-free zone criteria, it appears that herons are not using these
wetlands to breed. The heron HSI model does not provide any past research to
support its arbitrary selection of 150 and 250 m disturbance-free zones. I suspect
larger buffer zones may be needed to adequately support heronries, perhaps as much
as 800 m (Skagen et al. 2001). This assertion could be incorporated into future great
blue heron HSI model evaluations, thereby more accurately predicting heron nesting
tolerances. More studies are needed to confirm heron nesting tolerance to human
disturbance. I conclude that although the great blue heron HSI model possibly
deflates reproductive suitability as it pertains to this study due to lack of actual or
previous rookery locations, and although the model probably inflated reproduction
suitability via liberal disturbance-free zones, this model appeared to accurately reflect
heron habitat use of mitigation wetlands in West Virginia.
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Wood Duck.--
The wood duck HSI model was calculated based on breeding and wintering
habitat suitability. It was not surprising, specifically due to the amount of brood
cover, that mitigation wetlands scored such high SI values relative to natural
wetlands. Model variables stressed the importance of natural and artificial nest
cavities as well as creating structural variability within wetlands to promote adequate
wood duck breeding habitat. Because the density of potential nesting cavities was
relatively low in both wetland types, the percentage of wetland area containing
potential nesting habitat was low. However, according to the wood duck model,
optimal nesting habitat is achieved when the percentage of potential nesting habitat
reaches only 20%. Mitigation wetlands generally met this criterion, and as such
contained suitable wood duck nesting habitat. Nonetheless, numerous studies have
shown the importance of artificial nest boxes to wood duck breeding success
(Stephens 1998, Heusmann 2000, Zicus 2000), which stresses the importance of not
only installing wood duck nesting boxes in mitigation wetlands, but in situating
wetlands near forested cover types where wood duck can have easy access to nesting
locations.
The wood duck model considered potential wood duck brood cover to consist
of a combination of emergent vegetation, shrub cover, overhanging tree crowns, and
woody downfall. The amount of emergent vegetation and shrub cover in natural
wetlands was too dense to be considered optimal brood cover. According to the
wood duck model, optimal brood coverage exists where percentages of cover are
between 50 and 75%. Mitigation wetlands generally met this criterion, whereas
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natural wetlands did not, although the criterion was met through emergent vegetation
coverage, not shrub coverage. Harper et al. (1998) stressed the importance of live,
woody shrub cover in constructed wetlands to wood duck roosting. This further
asserts the need to establish shrub communities in newly created wetlands. The lower
end of brood coverage requirement (50%) for optimal brood coverage is consistent
with optimal habitat conditions for numerous taxa aforementioned. It is important to
note, however, that mitigation wetlands contained suitable brood coverage because of
emergent vegetation and shrub coverage, not because of overhanging tree crowns and
woody downfall. While 4 of 11 mitigation wetlands did contain some woody
downfall, the amount of cover was minimal and sporadic. Two of the 4 natural
wetlands contained at least some woody downfall. Studies show that structural
diversity within and around a wetland not only provides brood cover for wood duck,
it increases overall wildlife production by providing breeding and hibernation habitat,
and food and cover for mammals, birds, amphibians, and invertebrates (Wilcox and
Meeker 1992, France 1997, Babbitt and Tanner 1998, Froneman et al. 2001). This
stresses the importance of establishing woody downfall and other debris in newly
created wetlands.
According to the wood duck HSI model, mitigation wetlands also contained
suitable wood duck wintering habitat. Wintering habitat was described as similar to
brood habitat, but only persistent emergent vegetation was considered, in addition to
shrub cover, overhanging tree crowns, and woody downfall. Again, natural wetlands
were limited by the relatively dense coverage of emergent vegetation and shrub
cover. However, unlike the breeding model, the winter model did not consider the
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percentage of wetland area containing potential winter cover. Assuming similar
suitability graphs would exist in brood and winter coverages, both wetland types
would have scored higher winter SI values if this variable had been incorporated into
the model. As such, this model may underestimate the amount of winter cover
available to wood ducks across all wetlands evaluated.
Field observations confirmed the suitability of wood duck breeding habitat in
mitigation wetlands. Surveys were not conducted in the winter, so wintering habitat
suitability could not be �confirmed�. Wood duck adults were confirmed in breeding
bird surveys at 8 of 11 mitigation sites (Walnut Bottom, Buffalo Coal, Leading Creek,
Sugar Creek, Triangle, Trus Joist MacMillan, Enoch Branch, and Bear Run), and
broods were observed at 2 sites (Walnut Bottom and Leading Creek). Wood ducks
were confirmed nesting in artificial nest boxes at 1 mitigation site (Sugar Creek), and
all boxes were used by at least some bird species. As aforementioned, mitigation
sites contained significantly higher wood duck abundances than natural wetlands.
This appears consistent with the higher total SI values observed in mitigation
wetlands, although differences between SI values were not significant. However,
differences in total model SI values were attributable to differences in wintering
habitat suitability, not breeding suitability. Despite natural wetlands having similar
breeding habitat suitability to mitigation wetlands, no wood ducks were sampled in
natural wetlands. This may indicate either that the wood duck model is
overestimating breeding suitability, or that wood ducks were simply missed during
breeding bird surveys at natural sites. The latter seems less likely considering the fact
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that no wood duck were observed at natural sites, even during visits outside of
breeding surveys.
Vegetative composition may be affecting wood ducks distribution and
abundance as well, and they likely are benefiting from the establishment of diverse
vegetation (Chapter II) and invertebrate communities (Chapter IV) in mitigation
wetlands. In fact, studies have shown the importance of vegetation and invertebrates
to wood duck diet (Drobney and Fredrickson 1979, Harper et al. 1998), especially in
the absence of hard and soft mast. Considering the success of mitigation wetlands in
supporting vegetation and invertebrate communities relative to natural wetlands, I
suspect that mitigation wetlands in West Virginia will continue to provide quality
wood duck habitat.
Red-spotted Newt.--
Results from the red-spotted newt HSI model indicate that mitigation wetlands
contain suitable habitat for this species. Red-spotted newts are most abundant in
shallow wetlands with permanent water that contain dense aquatic vegetation (Sousa
1985). Aquatic vegetation is important not only for cover, but for reproduction as
well. Populations of newts with a terrestrial eft stage will migrate to nearby upland
areas, where they will remain for ≤7 years while seasonally returning to wetland
habitat to breed (Healy 1974, Waldick et al. 1999). This further emphasizes the
importance of establishing emergent and submerged aquatic vegetation in mitigation
wetlands, as well as the need to situate mitigation wetlands near healthy forest
ecosystems. It is important to note that the newt model did not directly evaluate red-
spotted newt food preferences (i.e., invertebrate abundance). It was assumed that
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adequate water and vegetation conditions would facilitate colonization by
invertebrates. Indeed, this was probably the case, as mitigation wetlands were found
to support healthy invertebrate populations (Chapter IV). Specifically, mitigation
sites contained a diverse array of taxa including flies (Diptera), springtails
(Collembola), beetles (Coleoptera), and snails (Gastropoda), all of which are
preferred food items of this opportunistic feeder (Sousa 1985, Kessler and Munns
1991). Despite mitigation sites scoring high newt SI values, breeding newts were
confirmed at only 2 mitigation sites (Sugar Creek and Walnut Bottom) and no natural
sites. Presence of fish, proximity to roads, or wetland size may be limiting newt
abundance and distribution (Gibbs 1998, Hager 1998, Smith et al. 1999), but these
factors were not considered as major influences on newt habitat use for this model. I
think that my lack of red-spotted newt observations in mitigation wetlands likely does
not reflect poor model performance by yielding inflated SI values. Instead, newts
probably use more mitigation wetlands than were observed. More detailed surveys
should confirm widespread use of mitigation wetlands throughout the state.
Snapping Turtle.--
The snapping turtle HSI model also yielded similar SI values between
mitigation and natural wetlands, and both wetland types, according to the model,
contained low quality snapping turtle habitat. This can be attributed to low
percentages of silt in the substrate. The variables evaluated in this model provide
important information, not only about snapping turtle, but about other wildlife species
as well. Mitigation wetlands contained a mean water temperature (27.7 °C) that was
within optimal range of snapping turtle, which is about 25-30 °C (Graves and
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Anderson 1987). This temperature range could potentially be suitable for other
aquatic turtles including painted turtles (Chrysemys picta), red-eared sliders
(Trachemys scripta), wood turtles (Clemmys insculpta), map turtles (Graptemys
geographica), and spotted turtles (Clemmys guttata), whose general thermal threshold
are between 15-20 °C (Ernst et al. 1994). As well, low mean water velocities were
observed across mitigation wetlands, indicating their suitability in supporting
snapping turtles. Stationary water also is suitable for numerous snakes, frogs, and
salamanders that can maximize foraging efficiency by conserving energy that would
otherwise be expended moving against high flow rates or pursuing immobile but
current-borne food items (Graves and Anderson 1987). I also observed deep enough
water in at least some portions of mitigation wetlands to provide adequate hibernacula
for snapping turtle. This may be important for other turtles, as well as some
amphibians that may use ice-free areas for hibernation (Cook 1984, Cunjak 1986). In
addition, mitigation wetlands scored high SI values for both reproduction and
interspersion components of the snapping turtle model. Because mitigation sites were
situated in close proximity to small streams and permanent water, they provided
excellent reproduction and dispersal habitat for reptiles and amphibians in general
(Hager 1998, Kasano 1998, Finkler 2001, Semlitsch 2002). The main limiting factor
affecting the performance of this model was the lack of silt observed in the substrate
of both mitigation and natural wetlands. In fact, if this variable is at an optimal level
(100%), the overall snapping turtle SI value almost doubles. Graves and Anderson
(1987) recognized that the exact silt content required to satisfy turtle burrowing
requirements is unknown, and as such, they assumed a linear relationship between
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percent silt and hibernacula suitability. I think this variable may not be limiting
snapping turtle habitat quality due to insufficient data gathering during model
development. I, too, was unable to find current literature regarding exact silt content
requirements. My observations of snapping turtle actually using mitigation sites
further supports the assertion that this model may be deflating snapping turtle usage
of mitigation wetlands. I observed snapping turtles during the summer at 6 of 11
mitigation sites (Walnut Bottom, Elk Run, Sugar Creek, Sand Run, Triangle, and
Trus Joist MacMillan) and at 1 natural site (Muddlety). Snapping turtles may not be
using mitigation sites to hibernate, but it appears that mitigation wetlands in West
Virginia provide adequate habitat for at least some life-history requirements (i.e.,
foraging, reproduction, and interspersion).
Conclusions.--
By definition, suitable habitat is indicative only of a species� presence/absence
(Hall et al. 1997). According to this definition, mitigation wetlands, in general,
provided suitable habitat for all 8 species evaluated. I recognize the intrinsic misuse
of the term, habitat �suitability� index, and instead recommend considering the
models as a habitat �quality� index, but only as it pertains to the relative quality of
habitat between mitigation and natural wetlands. My results indicate that mitigation
wetlands provided suitable, high quality, habitat for beaver, mink, and red-spotted
newt, and I concur with these model outputs based on correlations between habitat
characteristics displayed by the mitigation wetlands and with natural-history
requirements for these species, and by direct observations. I believe, however, that
red-winged blackbird and muskrat HSI models possibly provided inaccurate
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representations of habitat suitability using similar reasoning. For these species�
models, variables addressing species composition of emergent vegetation played a
key role in limiting SI values, possibly due to improper model calibration or inherent
flaws in predicting animal behavior under stresses associated with competition or
limiting resources. I can speculate that the snapping turtle model also was inaccurate
because this species was observed using mitigation wetlands during the summer, but
this species, indeed, may not be using mitigation wetlands for hibernation. Similarly,
great blue heron, although confirmed foraging within mitigation sites, are probably
not using mitigation wetlands as breeding locations. The goal of this study was not to
validate these models, but to gauge the relative quality of habitat between mitigation
and natural wetlands. As such, I conclude that natural wetlands provided better red-
winged blackbird and beaver habitat than mitigation wetlands. The other major goal
was to evaluate trends in habitat characteristics shared by mitigation wetlands that
may be valuable in monitoring wildlife in general. It is clear that mitigation wetland
habitat characteristics evaluated for these models currently meet or exceed natural
wetland reference standards. However, it is important to note the potential flaws of
those models that yielded low SI values. Overall, the mitigation wetlands evaluated
in this study provided valuable habitat for most life-history requirements for all
species evaluated.
Despite the discrepancies involved in the validity of using HSI models,
current regulations affecting resource management decisions require wildlife habitat
assessments that are repeatable and scientifically credible. If properly developed,
applied, and tested, HSI models can provide an efficient and inexpensive method for
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satisfying these requirements. Indeed, HSI models are widely used in environmental
impact statements (Brooks 1997, Morrison et al. 1998), forest planning, (Roloff et al.
1999), and even population viability analysis (Akcakaya 1995).
About 160 HSI models have been developed, but few have been tested. The
assumptions of these models have enormous implications, and critics argue that
management decisions should not be based on untested models. Using different
validation, verification, and calibration techniques, some researchers have found
positive correlations between model predictions and actual measures of wildlife
distributions, densities, and abundance (Cook and Irwin 1985, Verner et al. 1986,
Brennan 1991, Thomasma et al. 1991), while others have found negative correlations
(Seitz et al. 1982, Clark and Lewis 1983, Bart et al. 1984, Robel et al. 1993). Some
explanations for these discrepancies have been offered, including inadequate
population sampling (Cook and Irwin 1985, Lancia and Adams 1985), sampling in a
limited range of habitat conditions (Clark and Lewis 1983), improper representation
of wildlife-habitat relationships by model equations (Bart et al. 1984, Warwick and
Cade 1988, Van Horne and Weins 1991), misinterpretation of results (Cook and Irwin
1985, Capen et al. 1986), applying models to inappropriate spatial scales (Weins
1986, Roloff 1994), or the inadequate consideration of data variability (Bender et al.
1996).
Roloff and Kernohan (1999) used specific criteria to evaluate HSI validation
studies conducted between 1982 and 1995. These included the evaluation of model
components, input data variability, use of statistical power, spatial scale, range of
HSIs incorporated, type of population index used, and duration of population data
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collection. They found that the weakest component of all HSI validation studies was
inadequate consideration of input data variability and how this variability affects final
HSI interpretation. Specifically, most studies, in assessing model parameters (habitat
variables), failed to account for variability in sample means. In doing so, they failed
to provide confidence intervals to HSI scores, statistical tests on differences between
scores, or a quantifiable description of how differences in HSI scores may be related
to sampling deficiencies. Roloff and Kernohan (1999) attribute some of these
deficiencies to small sample sizes and the lack of defined replicates used to
effectively cover the complete range of habitat conditions.
My study incorporated defined replicates (wetlands) that encompassed a wide
range of habitat variation throughout West Virginia. This enabled statistical
differences in HSI scores to be evaluated, thus providing justification for inferences
to be made regarding the reflection of HSI scores on differences in habitat quality.
Although I noted the presence of any target species within study sites, I did not seek
to validate the models. Instead, the goal was to compare relative habitat quality
between wetland types, and to discuss trends in habitat variables that most influence
model output. At the very least, the multitude of habitat variables that are quantified
during model application can be applied to multivariate techniques that correlate
wildlife indices to environmental data. These data are extremely important in the
continued monitoring of these valuable ecosystems.
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CONCLUSIONS
Numerous studies have written about our inability to successfully mitigate for
wetland destruction (Race 1985, Erwin 1990, Reinartz and Warne 1993, Wilson and
Wilson 1996). Although the definition of success varies depending upon project
objectives, most agree that compensatory wetlands should replace functions lost
during wetland destruction. These data indicate that mitigation wetlands in West
Virginia currently support avian and anuran populations, as well as diverse habitat
characteristics indicative of increased habitat quality for a variety of wildlife species.
Indeed, mitigation sites contained some higher wildlife indices than natural sites, and
this could reflect actual differences in wildlife populations resulting from wetland
age, design, or location within the landscape. It is likely that wildlife distribution and
abundance reflect differences in vegetation and invertebrate community structure
between mitigation and natural wetlands, and future monitoring should focus on
monitoring the interactions between wildlife populations and these biotic factors. The
monitoring of the effects of beaver activity on vegetation structure is of particular
importance in evaluating future wildlife communities.
I should caution that it is premature to assess the full outcome of mitigation
efforts within the state. First, these data represent a short-term trend resulting from
only 2 years of data collection. Thus, these data do not encompass the temporal
variation in avian and anuran community structure. Pechmann et al. (2001)
recommended several years of census data on amphibians before meaningful
comparisons between mitigation and natural sites can be made. Similarly, D�Avanzo
(1990) and Zedler (1993) suggested a monitoring duration of 20 years for mitigation
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wetlands. Unfortunately, financial or logistical restraints often preclude long-term
monitoring capabilities.
Second, created wetlands often take at least a decade before they function
compatible to natural wetlands. Wilson and Mitsch (1996) recommend giving
freshwater wetlands 15-20 years before judging their success, and Frenkel and
Morlan (1991) recommend waiting ≥50 years for certain forested and coastal
wetlands. Two wetlands included in this study were about 20 years old and an
additional 3 sites were ≥10 years old. Although my sites do not meet recommended
criteria for mitigation wetland development time, nearly half are ≥10 years old, and I
think relatively conservative inferences can still be made regarding their success.
Finally, the variation in structure among mitigation and natural wetlands adds
to the difficulty in assessing mitigation success. This is particularly important in the
establishment of reference standards (Smith et al. 1995, Brinson and Rheindhardt
1996). Natural short-term processes such as seasonal cycles of precipitation and
temperature, coupled with long-term processes including population dynamics,
erosion and depositional processes, succession, or drought/wet cycles can cause
variation in the functional capacity of natural wetlands (Smith et al. 1995). This type
of variability is common in many wetland ecosystems including coastal marshes
(Oviatt et al. 1977), cypress swamps (Ewel and Odum 1984), prairie potholes
(Kantrud et al. 1989), and playa wetlands (Haukos and Smith 1992). Another factor
researchers must consider in establishing reference standards concerns anthropogenic
disturbance (Smith et al. 1995). Because most wetlands have been exposed to
hundreds of years of continued disturbance, their functions have been fundamentally
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changed, so it may be difficult to construct wetlands based on undisturbed standards.
Although some misuses of using natural wetlands as reference standards are possible,
reference wetlands can guide mitigation, both during and after the process by making
explicit the goals of mitigation and by evaluating the progress of mitigation wetlands
through proper monitoring (Brinson and Rheinhardt 1996). Similar variation in
wetland structure also can occur within mitigation wetlands thus providing further
evidence as to the difficulty in duplicating natural systems, especially since
alternative stable states are commonly observed in ecological communities (Drake
1990). These points illustrate the complexity in assessing mitigation success based
on reference wetlands and reiterate the need to document and compare losses of
wildlife habitat during wetland destruction to creation of wildlife habitat via
compensatory mitigation.
Indeed, temporal variation in wildlife habitat use, wetland development time,
and structural variation compound the logistics in evaluating the success of mitigation
wetlands. Nevertheless, the similarities in wildlife indices observed in this study
suggest preliminary development of mitigation sites towards reference standards. I
anticipate these data will help guide the creation of standardized protocols for the
continued monitoring of these and other mitigation wetlands, not only in West
Virginia, but also across the Appalachians.
MANAGEMENT IMPLICATIONS
Although the main goal of wetland mitigation is to construct or restore
wetlands that replace wetland functions lost to destruction, documentation of existing
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functions at impacted wetlands often does not exist. In these cases, I think it is
important to maximize wildlife habitat at compensatory wetlands, inspite of our
inability to truly mimic these systems. The implementation of different management
techniques should facilitate colonization and proliferation of diverse wildlife taxa
among current or future mitigation wetlands. I recommend constructing wetlands
≤50 m from forested cover types with a 300 m disturbance free zone that excludes
major roads. Wetlands should be ≥10 ha in size and be connected or adjacent to
streams, rivers, or other wetlands. I recommend maintaining hemimarsh conditions
with a 50/50 ratio of open water to emergent vegetation. Low water velocity and a
hydroperiod from 4 months to 1-2 years with water levels encompassing shallow (1-
10 cm) and deep (11-30 cm) areas also are recommended. This should be
accomplished under moist-soil management if water levels can be manipulated
(Chapter III). Wetland slopes of 10:1-20:1 are optimal. I also recommend enhancing
structural diversity by adding logs and rock piles in and around wetlands. Silt also
should be added to wetlands with poor hibernacula for herpetofauna. In addition,
earthen islands, Schwimmkampen, and nesting boxes should be included. Detailed
descriptions of the above management recommendations are provided below.
To further assess wetland mitigation success in terms of compensating for lost
wildlife function, it is imperative to conduct on-site wildlife surveys of the impacted
wetland that the mitigation site is designed to mitigate for. Detailed surveys of avian
and anuran communities should include documentation of lost habitat for specific
species with a particular focus on rare or inconspicuous species. This would better
enable researchers to assess a mitigation wetland�s ability to replace specific wildlife
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habitat while taking into account the status of those species being affected. An
assessment of overall species richness, diversity, and abundance can be a useful tool
in gauging relative success of mitigation wetlands in supporting wildlife, but these
indices can overshadow specific losses to wetland-dependent wildlife species. For
instance, relatively high anuran richness values observed at mitigation sites does not
reflect their ability to provide adequate habitat for wood frog. In fact, along with
American bullfrog, wood frog scored the lowest Wisconsin Index value of all species
observed. Because wood frogs are more terrestrial than many �true� frogs, they tend
to inhabit forested wetlands within West Virginia (Green and Pauley 1987). Thus, a
short-term net loss of wood frog habitat may result if inadequate compensation exists
for these important wetland types. Robb (2002) observed a 71% failure rate in
created palustrine forested wetlands in Indiana. Although little data exists on forested
wetland success within West Virginia, this trend should raise awareness as to the
difficulty in replacing lost habitat for specific wildlife species. Similar arguments
could be made concerning inconspicuous rail species. Although individuals were
observed within 2 mitigation sites, we know little about the habitat use by rails of
those wetlands that were destroyed. We are then left with bittersweet observations
that reflect the success among mitigation sites in providing adequate rail habitat, but
provide little insight into compensatory success.
This also is reflected in evaluating habitat models. Granted, habitat models
can be effective tools in assessing the relative habitat quality for specific species
between mitigation and natural wetlands, but this provides little insight into the actual
replacement of habitat for those specific species. I recommend an evaluation of
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habitat suitability index models for as many species that resources allow, both on the
wetland being impacted and on the replacement wetland. Although it is difficult to
assess the adequacy of mitigation wetland ecosystems in West Virginia in replacing
impacted wetlands, I hope that self-sustaining natural processes and species
interactions will continue to persist and mimic those of natural wetlands in West
Virginia.
Seasonal differences in avian use exist between mitigation and natural
wetlands (Perry et al. 1996, Melvin and Webb 1998). I suggest the inclusion of fall
surveys to account for winter migrating waterbirds. This would provide a more
comprehensive view of the temporal variation in wetland use, hence adding more
insight into the success of mitigation wetlands in supporting avian communities. I
expect that fall surveys would provide further evidence as to the success of mitigation
wetlands in supporting waterbirds.
Numerous strategies should be implemented in future mitigation projects to
facilitate the persistence of beneficial wildlife habitat in mitigation wetlands. First,
wetland size is an important factor dictating colonization, inhabitation, and dispersal
of wildlife (MacArthur and Wilson 1967, Tyser 1983, Kreil et al. 1986, Delphey and
Dinsmore 1993). I recommend constructing wetlands ≥10 ha in size. Although
mitigation ratios may require less wetland area to be created, replacement wetland
size could reflect the combined replacement ratios of multiple projects to achieve a
desired size. This could be a modification of the current mitigation banking system
that proactively creates multiple wetlands in a landscape as mitigation for future
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development projects. Alternatively, larger wetlands could be created to proactively
mitigate for the destruction of several smaller wetlands.
Furthermore, it is important to construct wetlands adjacent or connected to
streams, rivers, or other wetlands. This proximity is particularly important not only in
providing connectivity to neighboring populations, but in offering refuge during
unfavorable climatic conditions. It also offers protection against pollution, habitat
destruction, or changes in water levels. Second, developers should strive to create
hemimarsh conditions where an approximate 50:50 ratio of open water to emergent
vegetation exists. My study clearly indicates that this type of vegetative structure is
optimal for a variety of taxa including waterbirds, amphibians (i.e., frogs, red-spotted
newt), mammals (i.e., muskrat), and invertebrates.
Maintaining an adequate hydroperiod is important as well. Although longer
hydroperiods can ensure survival of certain anuran species, it may facilitate
colonization by unwanted predatorial fish. I recommend maintaining wetlands with
an array of hydroperiods from 4 months to 1-2 years to ensure successful recruitment
of all local species with differing habitat requirements, including invertebrate species
(Chapter III, Semlitsch 2002). This, perhaps, could be accomplished under a
mitigation banking system. Moist-soil management should be implemented in areas
where water level manipulation is feasible (Chapter III). It is important to assess the
potential impact of beaver in establishing appropriate hydrology at future mitigation
sites. I observed beaver impact at almost all of the mitigation sites. This species can
dramatically alter the hydroperiod of any landscape, both pre- and post-mitigation, so
caution is warranted in assessing hydrologic success upon creating a wetland.
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Water depth also plays an important role in determining wildlife use, affecting
both waterbird species composition and anuran breeding and hibernation. I
recommend creating wetlands with varying water depths to facilitate use by a variety
of species. Shallow (1-10 cm) and deep (11-30 cm) areas should both exist.
Although even deeper areas could be created, this may prevent periodic drying, which
would inhibit diverse hydrophytic vegetation development. However, deeper areas
can provide anuran breeding habitat in wetlands when spring draw-downs render
most of the wetland moist to promote seed germination. Again, this reiterates the
need to either maintain diverse habitats within each mitigation wetland, or maintain a
series of adjacent wetlands with diverse habitat conditions under different
management schemes, perhaps under a mitigation banking system.
Wetland slope also has been shown to affect wildlife populations. Kreil et al.
(1986) recommended slopes of 10:1 to 20:1 for mitigation wetlands to create variable
gradients for diverse vegetative growth to maximize invertebrate richness. This
would benefit waterbird and anuran species by increasing forage as well as
minimizing blockage to amphibian dispersal. Gentle slopes also are compatible with
goals of moist-soil management.
In addition, wetlands should be created near forests, preferably within 50 m.
A maximum buffer of 164 m was recommended by Semlitsch (2002). First, this will
protect wetlands against negative impacts associated with agricultural run-off.
Second, I observed that wetlands with increased tree and shrub cover <100 m from
the basin edge provided better cover, foraging, and breeding habitat for numerous
wildlife species including beaver, mink, red-spotted newt, and great blue heron. This
202
also is important in establishing coarse woody debris and leaf litter, which further
enhances dispersal corridors for post-breeding or newly metamorphosed amphibians.
Diverse guilds of songbirds and game species would benefit as well, especially once
sufficient shrub cover has developed within the wetland complexes themselves.
Water velocity also should be considered in establishing adequate wetland
hydrology. My study, like many others, showed that low mean water velocity is
beneficial to numerous wildlife taxa, particularly amphibians and some turtle species
(i.e., snapping turtle). A channelized flow may be necessary in creating necessary
hydrology within the wetland basin, but gradients should be established that dissipate
water over a large enough surface area to create hydrologic gradients that promote
diverse vegetation.
Structural complexity is another important component in the functioning of
wetlands. Studies show that structural diversity within and around a wetland
increases wildlife production by providing breeding and hibernation habitat, and food
and cover for mammals, birds, amphibians, and invertebrates. Although structural
complexity was not formally evaluated in this study, it appeared that most mitigation
sites were lacking structure. As mentioned in the wood duck model section, only 4 of
11 mitigation sites contained woody downfall and coverage was minimal. I
recommend adding numerous logs and rock piles in and around wetlands to enhance
wildlife habitat.
I also recommend adding silt to wetlands that contain poor hibernacula for
reptiles and amphibians. Sensitivity analyses showed that an increase in silt
drastically improved the habitat quality for snapping turtles. Numerous other turtle
203
species, as well as anurans, would benefit from increased silt. The amount of silt
should depend on wetland landscape position and the amount of water flowing in and
out of the system.
Earthen islands should be included in future mitigation wetlands to enhance
and protect nesting and loafing areas for waterbirds. They should be situated in the
middle of large open water areas ≥9.0 m from the shore in water 0.5 to 0.75 m deep
(Hammond and Mann 1956, Jones 1975). An alternative to earthen islands is
Schwimmkampen structures (Hoeger 1988). These are commercially available
triangular shaped rafts that can be arranged to provide nesting and loafing habitat for
ducks and geese. The islands are made of corrosion-proof plastics that protect against
weathering and microorganism damage. The vegetation installed on the top of the
islands is rot-resistant plant material that can be replaced or enhanced by natural
vegetation if desired (Hoeger 1988).
Wood duck nest boxes also should be included in future mitigation wetlands.
Boxes should be constructed from wood, preferably bald cypress (Taxodium
distichum) and mounted to a wooden pole for support. I recommend using rough-cut
lumber for construction. The opening of the box (7.6 cm ×10.0 cm) should be in the
front to facilitate maintenance and should face the east. A metallic cone predator
guard should be placed about 1 m above water. Ideally, boxes should be cleaned of
nesting materials (i.e., down feathers, egg membranes and shells, and unhatched eggs)
at least once after the peak of nesting and immediately following the breeding season
(Utsey and Hepp 1997). The wood duck I model recommends a minimum of 5
successful nests/0.4 ha for optimal wood duck habitat (Sousa and Farmer 1983).
204
Considering the availability of potential nesting sites in natural cavities surrounding
the wetlands that are constructed adjacent to forest, I recommend installing ≥1 nest
box/wetland.
Depending on what wildlife species researchers want to manage for, predatory
fish may or may not want to be included in mitigation wetlands. While fish can serve
as a valuable prey source for wading birds, they can negatively impact amphibian
populations. Although my study preliminarily shows that fish have a minimal effect
on anuran populations, without recruitment data, this cannot be confirmed. Fish will
readily pioneer wetlands located adjacent to streams or rivers during flood events, so
they may be difficult to control. I recommend, however, that carp be excluded from
mitigation wetlands because they can inhibit submerged aquatic vegetation growth,
thus negatively affecting biota up the entire food chain.
Human disturbances, especially roads, can influence distribution and
abundance of wildlife. My data indicated with respect to anurans, negative effects
associated with roads may be minimal in the short-term. However, definitive results
from other studies point to long-term dispersal problems, especially if wetlands are
isolated from other water sources. This point further supports the need to maintain
connectivity of mitigation wetlands to other wetlands or waterways. Road effects can
be more immediate, however, as in the case of the great blue heron. Although
mitigation wetlands provided valuable foraging habitat, I suspected breeding habitat
was limited by human disturbance, despite a high SI value associated with this
variable. I recommend that, in the case of highway mitigation, wetlands be
constructed �off-site� with a minimum 300 m buffer around the edge of the wetland
205
basin. This should adequately encourage colony-nesting birds to breed adjacent to
mitigation wetlands while minimizing other abiotic factors such as pollution and
sedimentation. However, I understand that constructing wetlands �on site� as
mitigation for highway construction can have logistical benefits associated with
establishing hydrology and an adequate seed bank. In addition, philopatric amphibian
species that faithfully return to one particular area to breed would benefit, as well as
migratory waterfowl that repreatedly return to a specific wetland to breed, forage, or
loaf. Whether the benefits associated with constructing wetlands �off site� outweigh
�on-site� benefits, is case specific, and should be dictated by overall objectives of the
mitigation project.
Our ability to mimic natural systems is inhibited by the nature of natural
wetlands themselves. Since we can never recreate years of geomorphological
processes, the best we can do is to create wetlands with a chance of developing into
self-sustaining functioning systems. In doing so, wildlife requirements cannot be
ignored because their existence is testimony as to the success (i.e., healthiness) of the
multitude of abiotic processes that drive wetland succession. Indeed, wildlife�s
function in wetland mitigation should be embraced as a major player in contributing
to this dynamic ecosystem. Mitigation wetlands in West Virginia were created as
mitigation for an array of human activities. Despite the variation associated with
different design techniques and mitigation objectives, these wetlands shared a variety
of habitat characteristics that enabled them to support diverse wildlife populations.
The need to document wildlife use of impacted wetlands is crucial to conserving
specific wetland-dependent species whose habitat requirements are often ignored.
206
This need may only be surpassed by the need to recognize the crucial components
outlined in this chapter in maintaining wetland ecosystem integrity.
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CHAPTER IV
TABLES
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Table 1. Optimal Suitability Index (SI) scores of 38 habitat variables evaluated for
Habitat Suitability Index models on 8 wildlife species in mitigation (n = 11) and
natural (n = 4) wetlands in West Virginia, 2001-2002.
HSI model variables Optimal SI score Beaver V1: percent tree cover a. within wetland basin 40-60% b. within 100 m 40-60% c. within 200 m 40-60% V2: percent trees 2.5-15.2 cm dbh a. within wetland basin 100% b. within 100 m 100% c. within 200 m 100% V3: percent shrub cover a. within wetland basin 40-60% b. within 100 m 40-60% c. within 200 m 40-60% V4: shrub canopy height (m) a. within wetland basin 2-4 m b. within 100 m 2-4 m c. within 200 m 2-4 m V5: woody vegetation species composition a. within wetland basin >50% aspen, b. within 100 m willow, cottonwood, c. within 200 m or alder V6: mean annual water fluctuation small Muskrat V1: percent emergent vegetation 50-80% V2: percent year with water 100% V3: percent Scirpus validus, S. americanus, 80-100% Typha latifolia Mink V1: percent year with water 75-100% V2: percent persistent emergent vegetation 50-75% V3: percent tree/shrub cover <100 m 75-100% Great blue heron V1: distance between forage area/nest site <1.0 km
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HSI model variables Optimal SI score V2: presence of shallow, clear water with fish n/a V3: 100 m foraging disturbance free zone yes V4: presence of forest within 250 m yes V5: 150, 250 m nesting disturbance free zone yes V6: distance (km) between potential <1.0 km and actual/previous nest site Red-winged blackbird V1: percent broad-leaf monocots >50% V2: percent year with water >50% V3: presence of carp no V4: presence of Odonates yes V5: percent emergent vegetaion 40-60% Wood duck V1: number of potential nesting cavities/0.4 ha n/a V2: number of nest boxes/0.4 ha n/a V3: density of potential nest sites (no./0.4 ha) >5.0 V4: percent potential brood cover 50-75% V5: percent potential winter cover 50-75% V6: distance b/w cover types <0.8 km V7: percent area optimum nesting habitat >20% V8: percent area optimum brood habitat 100% Snapping turtle V1: water temperature (°C) during summer 25-35 V2: water velocity (cm/s) during summer 0.0 V3: percent vegetation in littoral zone 100% V4: water depth vs. ice depth water > ice V5: percent silt in substrate 100% V6: distance (m) to small stream 0.0 V7: distance (m) to permanent water 0.0 Red-spotted newt V1: percent water < 2m deep 100% V2: percent vegetation in littoral zone >75% V3: distance (m) to forest <50
Table 1. Continued.
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Table 2. Richness (no. species/0.78 ha), diversity (per 0.78 ha), and abundance
(no.birds/0.78 ha) comparisons for avian communities between mitigation (n = 11)
and natural (n = 4) wetlands in West Virginia, 2001-2002.
Mitigationa Naturala Species or Group x SE x SE Richness 8.79a 0.31 8.77a 0.48 Diversity 2.41a 0.41 2.15a 0.37 Abundance All birds 21.13a 1.69 22.2a 3.89 Waterbirdsb 3.97a 1.14 0.34b 0.18 Waterfowlc 3.46a 1.10 0.19b 0.16 Passerinesd 15.89a 1.18 20.84a 3.85 Top 20 species 17.32a 1.59 18.57a 3.91 Red-winged blackbird Agelaius phoeniceus 4.61a 0.73 6.24a 1.23 European starling Sturnus vulgaris 0.99a 0.39 3.16a 3.16a Song sparrow Melospiza melodia 1.25a 0.11 2.43b 0.22 Canada goose Branta canadensis 2.02a 0.02 0.16a 0.16 Common yellowthroat Geothlypis trichas 0.71a 0.10 1.06a 0.29 Tree swallow Tachycineta bicolor 1.68a 0.38 0.53a 0.21 Cedar waxwing Bombycilla cedrorum 0.50a 0.14 0.06a 0.04 American crow Corvus brachyrhynchos 0.02a 0.01 0.16a 0.11 Indigo bunting Passerina cyanea 0.50 0.11 0.63a 0.19 Wood duck Aix sponsa 0.87a 0.36 0.0b 0.00 American goldfinch Carduelis tristis 0.54a 0.11 0.34a 0.15 Red-eyed vireo Vireo olivaceus 0.40a 0.08 0.25a 0.08 Willow flycatcher Empidonax traillii 0.36a 0.09 1.02 0.23 Mallard Anas platyrhynchos 0.57a 0.16 0.03a 0.03 Yellow warbler Dendroica petechia 0.45a 0.10 0.94a 0.23 Gray catbird Dumetella carolinensis 0.33a 0.08 0.79a 0.20 Northern cardinal Cardinalis cardinalis 0.18a 0.05 0.32a 0.14 American robin Turdus migratorius 0.44a 0.11 0.21a 0.10 Barn swallow Hirundo rustica 0.68a 0.31 0.09a 0.07 Eastern towhee Pipilo erythrophthalmus 0.23a 0.06 0.16a 0.08 Great blue herone Ardea herodias 0.12a 0.06 0.03a 0.03 a The same letter following means indicates no difference between wetland types (P > 0.05). bIncludes only those birds that depend on water for all or most of their life requisites. cIncludes only birds in the family Anatidae. dIncludes only birds in the order Passeriformes. e Great blue heron was not among the top 20 species but was included in analyses because it was evaluated using a Habitat Suitability Index model.
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Table 3. Wisconsin Index value and abundance per wetland for all anuran species combined
and for each of 7 species heard at mitigation (n = 11) and natural (n = 4) wetlands, West
Virginia, 2001-2002.
Wisconsin Index Abundance Mitigationa Naturala Mitigationa Naturala Common Name Scientific Name x SE x SE x SE x SE All frogs 0.52a 0.03 0.40b 0.07 4.75a 0.66 4.69b 1.18Spring Peeper Psuedacris c. crucifer 1.83a 0.16 1.86a 0.27 22.9a 3.32 28.4a 6.95Gray Treefrog Hyla chrysoscelis 0.17a 0.06 0.16a 0.09 0.39a 0.16 0.33a 0.19Bull Frog Rana catesbeiana 0.13a 0.05 0.05b 0.03 0.21a 0.09 0.10b 0.06Wood Frog Rana sylvatica 0.13a 0.06 0.08a 0.05 0.45a 0.29 0.21a 0.14Green Frog Rana clamitans melanota 0.84a 0.12 0.50b 0.13 7.82a 2.37 3.56b 1.29American Toad Bufo a. americanus 0.18a 0.05 0.04a 0.03 0.48a 0.17 0.05a 0.04Pickerel Frog Rana palustris 0.35a 0.09 0.09b 0.03 0.82a 0.21 0.24a 0.09a The same letter following means indicates no difference between wetland types (P > 0.05).
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Table 4. Mean Suitability Index (SI) values between mitigation (n = 11) and natural
(n = 4) wetlands of Habitat Suitability Index models for 8 wildlife species, West
Virginia, 2001-2002.
Mitigationa Naturala x SE x SE
Red-winged blackbird 0.03a 0.01 0.15b 0.05 Beaver 0.74a 0.06 1.0b 0.0 Muskrat 0.35a 0.04 0.55a 0.12 Mink 0.79a 0.05 0.89a 0.04 Great-blue heron 0.26a 0.02 0.23a 0.05 Wood duck 0.82a 0.07 0.68a 0.11 Snapping turtle 0.60a 0.01 0.53a 0.04 Red-spotted newt 0.90a 0.05 0.80a 0.11 All species combined 0.56a 0.02 0.60a 0.03 a The same letter following means indicates no difference between wetland types (P >
0.05)
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CHAPTER V
VEGETATION, INVERTEBRATE, AND WILDLIFE
COMMUNITY RANKINGS AND HABITAT ANALYSIS OF
MITIGATION WETLANDS IN WEST VIRGINIA
COLLINS K. BALCOMBE balcster@hotmail.com
West Virginia University Division of Forestry
PO Box 6125 Morgantown, WV 26505-6125
235
ABSTRACT
Numerous efforts have been made in West Virginia to construct and restore
compensatory wetlands as mitigation for natural wetlands destroyed through highway
development, timbering, mining, and other human activities. Because such little
effort has been made to evaluate these wetlands, there is a need to evaluate the
success of these systems. The objective of this study was to determine if mitigation
wetlands in West Virginia were adequately supporting ecological communities
relative to naturally occurring reference wetlands and to attribute specific
characteristics in wetland habitat with trends in wildlife abundance across wetlands.
Specifically, avian and anuran communities, as well as habitat quality for 8 wetland-
dependent wildlife species were evaluated. To supplement this evaluation, vegetation
and invertebrate communities also were assessed. Wetland ranks were assigned
based on several parameters including richness, abundance, diversity, density, and
biomass, depending on which taxa was being analyzed. Mitigation wetlands
consistently scored better ranks than reference wetlands across all communities
analyzed. Canonical correspondence analysis revealed no correlations between
environmental variables and community data. However, trends relating wetland
habitat characteristics to community structure were observed. These data support
previous chapters that revealed the success of mitigation wetlands in supporting
diverse vegetation, invertebrate, and wildlife communities and reiterates the need to
maintain specific habitat characteristics that are compatible with wildlife colonization
and proliferation.
This chapter is written in the style of Wetlands Ecology and Management.
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Key words: constructed wetland, man-made wetland, mitigation wetland,
reference wetland, restored wetland, wetland mitigation, wetland management
INTRODUCTION An enormous array of wildlife depends on wetlands for all or part of their
lives. Dwindling populations of wetland-dependent wildlife populations have
resulted from years of losses in the wetland resource base across the U.S. (Mitsch and
Gosselink, 2000). In an attempt to mitigate for losses in wetland habitat, current
legislation has mandated the construction of thousands of hectares of wetlands. To
evaluate these wetlands, researchers have attempted to describe and quantify wetland
functions relative to naturally occurring reference wetlands. Such functions
commonly evaluated include soil (Stolt et al., 2000), hydrology (Ashworth, 1997),
vegetation (Campbell et al., 2002), wildlife (Delphey and Dinsmore, 1993), or
combinations of these (Brinson, 1993; Brinson and Rheinardt, 1996; Wilson and
Mitsch, 1996). Although these functions have been evaluated exclusively in
numerous studies, few studies have engaged in a comprehensive evaluation of
multiple wetland functions to assess mitigation success. The term �success� in itself,
is quite variable, and often varies by project objectives (National Research Council,
2001). This study addressed mitigation success in terms of a wetland�s ability to
support diverse vegetation, avian, anuran, and invertebrate communities at a
functional equivalency to naturally functioning reference wetlands.
Vegetation communities were evaluated not only because they directly
determine the distribution and abundance of wildlife populations by providing
essential food and cover (MacArthur and MacArthur, 1961; Evans and Wilson, 1982;
237
Anderson et al., 1999a, King et al., 2000; Naugle et al., 2000), they indirectly affect
wildlife by contributing to a variety of other wetland functions including quantity and
type of substrate for invertebrates (Murkin et al., 1992; Anderson and Smith, 1998,
1999, 2000; King et al., 2000) and water chemistry (Goslee et al., 1997; Castelli et al.,
2000). For a variety of reasons, invertebrates are extremely important in the
functioning of wetlands as well and thus, similar to vegetation communities, can be
viewed as surrogates to wetland health. They are particularly sensitive to long-term
hydrologic cycles, water quality, and habitat type (Wiggens et al., 1980; Doupe and
Horwitz, 1995; Brooks, 2000), which is often associated with vegetative structure and
composition. In turn, invertebrates contribute to other wetland functions by assisting
in litter decomposition, nutrient cycling (Cummins 1973; Merritt et al., 1984) and
plant community regulation (Weller, 1994). Thus, invertebrates aid in the transfer of
nutrients from the sediments, detritus, and water column to higher-level organisms.
They also have direct impacts on wildlife species that depend on them for food. In
particular, waterfowl and other waterbirds (De Szalay and Resh, 1996; Davis and
Smith, 1998; Anderson and Smith, 1999; Anderson et al., 2000), as well as anurans
(Anderson et al., 1999a; Lima and Magnusson, 2000), depend on invertebrates for
food. It is clear that invertebrates play a vital role in wetland function and are integral
in analyzing the health of these ecosystems.
Considering more than 50% of the 800 protected migratory birds rely on
wetlands (Wharton et al., 1982), it is clear that an avian component is necessary in the
evaluation of mitigation wetlands. Avian communities are good indicators of wetland
function because, as a group, they exhibit a wide range of habitat requirements, and
238
have adapted to the variety of vegetative cover types and water regimes wetlands
provide (Anderson et al., 1996; Davis and Smith, 1998; Melvin and Webb, 1998;
Anderson and Smith, 1999; Weller, 1999; Naugle et al., 2000). As well, they have
diverse diets with many being herbivorous or omnivorous, preferring such foods as
seeds, fruit, invertebrates, amphibians, and small mammals (Gonzalez et al., 1996;
Anderson et al., 1996; De Szalay and Resh, 1997; Davis and Smith, 1998; Anderson
and Smith, 1999; Weller, 1999).
Like many avian species, anurans rely exclusively on wetlands (Michael and
Smith, 1985; Dodd and Cade, 1998; Lehtinen et al., 1999; Semlitsch, 2002),
specifically for hibernation, foraging, breeding, and interspersion habitat for different
life stages. In turn, anuran populations provide insight into water quality and
temporal variations in hydrology (Beattie and Tyler-Jones, 1992; Anderson et al.,
1999a; Semlitsch, 2002). While anurans often feed on numerous invertebrate species
(Anderson et al., 1999b; Lima and Magnusson, 2000), they are an important food
source for numerous other invertebrates and vertebrates alike (Bridges, 1999;
Lardner, 2000), thus making them a valuable link in a complex food web (Weller,
1999).
The development of wildlife habitat models is important because researchers
must often assign relative values to habitat to support objectives for mitigation. Some
models that have been created include the Wetland Evaluation Technique (Adamus,
1983; Adamus and Stockwell, 1983), Habitat Assessment Technique (Cable et al.,
1989), and the Avian Richness Evaluation Model (Adamus, 1993). Species-specific
models commonly used today are the Habitat Suitability Index (HSI) models
239
developed by the U.S. Fish and Wildlife Service (1981). Based on natural history
requirements for a particular species, these models use habitat parameters considered
pertinent to a species survival to calculate an index ranging from 0 to 1 (a 1 represents
optimal habitat). Depending on the HSI model, the habitat parameters evaluated may
have significant implications for other wildlife taxa as well, which can provide further
insight into overall habitat quality for wildlife for a given area.
Only 2 studies have evaluated the success of mitigation wetlands in West
Virginia, and 1 of them (R.H. Fortney, West Virginia University unpublished report)
excluded an evaluation of invertebrates while the other exclusively evaluated
production of only 1 invertebrate taxa in 1 constructed wetland (Johnson et al., 2000).
As such, there is a need to evaluate the current ability of mitigation wetlands in the
mid-Appalachians, and in particular West Virginia, to support diverse vegetation and
wildlife communities. Likewise, to maintain the significant role wildlife plays in the
development of wetland ecosystems across this region, there is a need to identify
wetland habitat characteristics that are associated with wildlife distribution and
abundance. Therefore, researchers can develop adequate monitoring protocols and
construct future wetlands that are compatible with wildlife proliferation. The
objective of this study was to determine which wetlands were best and to determine
why wildlife were distributed in which wetlands. In doing so, I sought to attribute
specific characteristics in wetland habitat with trends in wildlife abundance across
wetlands. Specifically, avian and anuran communities, as well as habitat quality for 8
wetland-dependent wildlife species were evaluated. To supplement this evaluation,
vegetation and invertebrate communities also were assessed. This study was
240
designed to assist in the creation of future monitoring protocols for mitigation
wetlands in West Virginia and to guide in the development of future mitigation
projects with the highest probability of success.
METHODS
Study sites
West Virginia can be classified into 3 regions (Fenneman, 1938). The
unglaciated Western Hill section is the largest province in West Virginia, and
includes the Appalachian Plateau between the Ohio River and the mountainous area
to the east. Most of the hills in the northern and western portions of the state are
≤450 m in elevation. Southern sections of this region, however, reach elevations
≥900 m and can exceed 1000 m. The Allegheny Mountain section includes the high
mountains that lie in the Cheat River system and in the headwaters of the North
Branch of the Potomac River. This section contains the highest elevations in West
Virginia with many ridges reaching between 1,200 m and 1,375 m in elevation. This
section contains the Allegheny Mountains that extend northward from West Virginia
into western Maryland and central Pennsylvania. The Ridge and Valley region is
located east of the Allegheny Front, and is drained primarily by the Potomac River.
This region is a lowland area that, as its name implies, contains numerous
interspersed ridges that form a narrow belt along the eastern margin of the state. The
elevation of valley floors ranges from 300 to 400 m with ridges reaching ≥1,219 m in
elevation.
Eleven mitigation wetlands were evaluated in this study: Walnut Bottom,
VEPCO, Buffalo Coal, Elk Run, Leading Creek, Sugar Creek, Sand Run, Triangle,
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Trus Joist MacMillan, Enoch Branch, and Bear Run. These wetlands were created or
restored as compensation for wetland losses sustained for different human activities
including highway development, facility construction, and mining. Almost every
mitigation site was located near some form of human disturbance. In fact, many are
located adjacent to roads with moderate to heavy traffic. A minimum standardized
time of development of 5 years was chosen for all sites. Wetlands ranged in age from
5 - 21 years ( x = 10.0, SE = 1.7; Table 1) and ranged in elevation from 265 -1036 m
( x = 586, SE = 75.9). Size ranged from 3.0 - 9.5 ha ( x = 5.8, SE = 0.80). All
mitigation wetlands were classified as palustrine emergent or unconsolidated bottom
(Cowardin et al., 1979).
Four naturally occurring reference wetlands were selected for comparisons
with mitigation wetlands: Altona Marsh, Elder Swamp, Meadowville, and Muddlety.
Each reference wetland represented a geomorphic setting (as described above) within
the state and was selected relative to mitigation wetlands within that setting. Hence,
within each of 4 areas, reference wetlands were selected based on their similarity in
hydrology and structure to respective mitigation wetlands. All were located within
similar basins or watersheds of respective constructed sites. Since reference wetlands
were considerably larger than mitigation sites, only portions, when feasible,
comparable in size to constructed sites were used for study. Reference sites ranged in
elevation from 170 -1000 m ( x = 582, SE = 169.5; Table 1) and ranged in size from
6.5 - 28.0 ha ( x = 15.1, SE = 4.7. All reference wetlands were classified as
palustrine emergent or scrub-shrub wetlands (Cowardin et al., 1979). Detailed
descriptions of mitigation and reference wetlands are provided in Chapter I.
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Vegetation community sampling
I conducted vegetation sampling in June and July of 2001, and in July of
2002. Sampling was conducted according to techniques incorporated by Stephenson
and Adams (1986). Plant communities were stratified based on distinct communities
present, and representative communities were sampled using permanently marked
0.05 ha quadrats (25 × 20 m). At each wetland, at least 1 quadrat was used to sample
each distinct plant community. Within each quadrat all live stems of trees (≥ 10 cm
diameter at breast height, DBH) and small trees (2.5 to 9.9 cm DBH) were measured
at dbh and counted to species. In addition, saplings (individuals < 2.5 cm DBH but ≥
1.0 m tall) were counted. Within each 0.05 ha quadrat, 2 5.0 × 5.0 m plots were
placed evenly along the center line of the transect. Within these plots, seedlings
(individuals > 10 cm but less than < 1.0 m tall) and shrubs (including woody vines)
were counted to species. Five 1.0 × 1.0 m plots were placed along the same center
line. Within these plots, small seedlings (individuals ≤ 10 cm tall) were counted to
species. In addition, percent cover of herbaceous plants, exposed substrate, woody
debris, and bryophytes were recorded within 1.0 × 1.0 m plots. Detailed
descriptions of vegetation community sampling are provided in Chapter II.
Wetland delineation
Wetland boundaries were determined using recent aerial photos (1.0 m
resolution) taken by the West Virginia Natural Resources Analysis Center (NRAC)
during leaf off in 2001 and 2002 and by using ground truth data collected during
mapping of dominant vegetation communities. Boundaries were outlined according
to the presence and distribution of hydrophytic vegetation communities and mapped
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using Geographic Information Systems (GIS) and ArcView software (Chapter II). If
recent aerial photography was unavailable, wetland boundaries were digitized on
1996-1997 digital ortho-quarter quads (DOQQs) obtained from the West Virginia
Department of Environmental Protection (DEP). The objective of wetland boundary
determination was to compare current wetland size (ha) with sizes required by
permits issued by the U.S. Army Corps of Engineers and West Virginia Division of
Natural Resources. As well, dry areas were measured within wetland basins in order
to assess the percentage of wetland area actually existing within the basin.
Invertebrate sampling
I conducted invertebrate sampling according to Anderson and Smith (1996,
2000) during the summers of 2001 and 2002. Specifically, I collected 620 samples in
July and September of 2001 and another 620 samples were collected in April and
June of 2002. Samples were taken at different times both years to maximize
representative taxa. Wetlands were stratified based on wetland classification
(Cowardin et al., 1979), and specimens were collected at 10 random points within
open water, emergent, and scrub-shrub (if they existed) areas of each wetland. At
each point, I used a 5 cm diameter core (15 cm deep) and a 7.5 cm diameter water
column sampler (Swanson, 1983) to collect nektonic and benthic specimens,
respectively. Water column samples were sieved in the field using a 500-micron
sieve (Huener and Kadlec, 1992) and preserved in 70% ethanol. Benthic samples
were placed in bags, refrigerated, and processed within 10 days of collection
(Anderson and Smith, 2000). Biomass was obtained by oven-drying samples at 55°C
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for ≥48 hours to a constant mass and using an analytical scale. Details of
invertebrate sampling methodologies are provided in Chapter III.
Avian and anuran communities
I evaluated avian communities by sampling breeding bird populations using
point count (0.78 ha plots) surveys (Ralph et al., 1995). I visited wetlands twice
between late May and late June, 2001 and 2002, when breeding birds were most
active. I conducted 10-min point counts that occurred between 30 min before sunrise
and 1000 hours, under acceptable weather conditions (Ralph et al., 1995). I evaluated
anuran communities using nocturnal call count surveys that followed standardized
protocols developed by the U.S. Fish and Wildlife Service (Casey and Record,
unpublished data). To account for temporal breeding differences between species,
each wetland was visited once during the months of March, April, and May, 2001 and
2002. I collected data for 3 minutes at each sampling point following a 1-2 min
settling period. Frogs were identified to species and evaluated relative abundances by
assigning a Wisconsin Index value of intensity to each species� call (Mossman, 1994).
Detailed descriptions of avian and anuran sampling schemes are included in Chapter
IV.
Habitat quality
Habitat quality was assessed using species-specific Habitat Suitability Index
(HSI) models. The models chosen had broad taxonomic coverage and included 1
reptile (snapping turtle, Chelydra serpentina, Graves and Anderson, 1987), 1
amphibian (red-spotted newt, Notophthalmus virdescens, Sousa, 1985), 3 mammals
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(beaver, Castor Canadensis, Allen, 1983; muskrat, Ondatra zibethicus, Allen and
Hoffman, 1984; mink Mustela vison, Allen, 1984), and 3 bird species (1 wading bird:
great blue heron, Ardea herodias, Short and Cooper, 1985; 1 waterfowl species: wood
duck, Aix sponsa, Sousa and Farmer, 1983; 1 passerine: red-winged blackbird,
Agelaius phoeniceus, Short, 1985). All evaluated species had wide distributions
throughout West Virginia, and possessed life-history components (i.e., foraging,
reproduction, and interspersion) that were compatible with habitat features present in
the wetlands selected for this study. Numerous methodologies were incorporated in
quantifying the 38 variables encompassing the 8 models (see Chapter IV).
Statistical analyses
Vegetation metrics (species richness, diversity, and evenness were calculated
using PC-ORD software (McCune and Mefford, 1999) for each of 45 and 15 quadrats
within mitigation and reference wetlands, respectively. Metrics were calculated for
all species and for native species only. Species diversity was calculated using the
Shannon Index (Shannon and Weaver, 1949). Average cover was calculated for each
species and totaled to get a total coverage for each plot. These values were averaged
to obtain mean total coverage for each wetland. Each herbaceous species was
assigned a wetland indicator status value (WIS): Obligate = 1, Facultative Wetland =
2, Facultative = 3, Facultative Upland = 4, and Upland = 5 (U.S. Fish and Wildlife
Service, 1996). From coverage and WIS values, mean weighted averages (Carter et
al., 1988; Wentworth et al., 1988, and Atkinson et al., 1993) were calculated based on
the following formula:
WA = (y1u1 + y2u2 + ��.ymum)/100
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where y1y2 = relative basal area (trees and small trees) or relative cover estimates
(herbaceous plants) for each species, and u1u2 = the WIS for each species (Atkinson et
al., 1993).
Species richness was calculated for avians and anurans by averaging the total
number of species observed in each sampling plot per wetland. Invertebrate richness
was calculated in a similar manner, but taxa were classified only to family. Avian
abundance was calculated by averaging the total number of individuals observed in
each sampling plot per wetland. Similar to vegetation diversity, avian and
invertebrate diversity was calculated using the Shannon Index. Anuran abundance
was calculated separately both by Wisconsin Index calling intensity values of
particular species (Mossman 1994), and by actual estimations of calling individuals.
Details involving ranking classifications and abundance estimations are provided in
Chapter IV. Invertebrate density and biomass were calculated for both benthic and
nektonic samples separately.
For the purposes of this study, metric means were not compared between
mitigation and reference wetlands. A detailed account of statistical mean
comparisons between vegetation, invertebrate, and wildlife communities is provided
in Chapters II, III, and IV, respectively. Instead, metric means for each wetland were
ranked on a scale of 1 to 15 based on observed means of each wetland relative to
other mitigation and reference wetland means. A rank of 1 was given to wetlands that
scored the best or highest value for a particular metric, whereas a 15 was given to
wetlands that scored the worst or lowest value relative to other evaluated wetlands.
Wetlands with similar means were averaged and ranked the same number, so in some
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instances, scales may not extend all the way to 15. Separate ranks were calculated
individually for vegetation, invertebrate, avian, and anuran communities, as well as
for habitat quality in order to gauge the relative success of individual wetlands in
supporting a particular community. Furthermore, an overall rank representing means
across all metrics were assigned to each wetland.
Vegetation ranking was based on combining ranks for species richness,
evenness, diversity, and weighted averages (Table 2). Overall avian ranks were
calculated by averaging total species richness, diversity, and abundance ranks, as well
as abundance ranks for waterbirds, waterfowl, and passerines (Table 3). Overall
anuran ranks were based on mean rankings of total species richness, Wisconsin Index
(WI) value, and abundance, as well as WI and abundances for the 7 frog species
sampled (Table 4). These species included spring peeper (Psuedacris crucifer), gray
treefrog (Hyla chrysoscelis), American bullfrog (Rana catesbeiana), wood frog (Rana
sylvatica), green frog (Rana clamitans), American toad (Bufo americanus), and
pickerel frog (Rana palustris). Overall invertebrate ranks represented combined
rankings of familial richness, diversity, density and biomass for nektonic and benthic
samples (Table 5). Habitat Suitability Index (HSI) ranks were based on mean ranks
for all 8 species evaluated (Table 6). A completely randomized Analysis of Variance
(ANOVA) model followed by the Tukey�s (HSD) Honestly Significantly Difference
test was used to test for differences among individual wetland rank means.
Assumptions of normality were tested with the univariate procedure in SAS, and
Levene�s Test was used for homogeneity of variances. These analyses were
performed using SAS (SAS Institute, 1988).
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I used Canonical Correspondence Analysis (CCA; ter Braak, 1986), using PC-
ORD software to correlate environmental variables to avian, anuran, and invertebrate
abundance. Canonical Correspondence Analysis is a multivariate direct ordination
method that performs a least-squares linear regression of environmental variables on
site (wetland) scores determined through correspondence analysis (Gauch, 1982).
Species are ordered on axes constrained by linear combinations of environmental
factors. The eigenvalues associated with each axis indicate the relative ability of the
axis to order or separate species distributions. Intraset correlation coefficients
represent the strength of environmental variables in structuring the ordination.
Ordination diagrams (joint plots) are interpreted by viewing the distribution of
species around environmental vectors. Species are plotted based on the relative value
of weighted averages along a particular axis. Thus, the closer a species is to a
particular vector or axis, the more closely associated it is to that variable (ter Braak
1986). In addition, the length of each vector is a measure of how much species
distributions differ along that environmental variable. Hence, longer vectors
represent more important environmental variables.
I ordinated avian, waterbird, and anuran abundances across all 15 wetlands to
5 environmental variables: % emergent vegetation, % open water, vegetation
diversity, benthic invertebrate diversity, and nektonic invertebrate diversity.
Abundances also were ordinated across mitigation sites only to 7 environmental
variables: age, size, % emergent vegetation, % open water, vegetation diversity,
benthic invertebrate diversity, and nektonic invertebrate diversity. Invertebrate
abundance was ordinated across all 15 wetlands to 4 environmental variables: %
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emergent vegetation, % submergent vegetation, % open water, and vegetation
diversity. Similarly, invertebrate abundance was ordinated across mitigation sites
only to 6 environmental variables: age, size, % emergent vegetation, % submergent
vegetation, % open water, and vegetation diversity. Only species present in ≥ 10%
of wetlands were used in this analysis due to the potential negative effect of outliers
(Gauch, 1982). I used eigenvalues, percentage of variation explained in species data,
and intraset correlations of environmental variables to each axis to assess the relative
importance of environmental variables in structuring species composition. A Monte
Carlo simulation (McCune and Mefford 1999) with 1000 permutations was used to
test the null hypothesis that there was no relationship between species and
environmental matrices (P = 0.05). Although P values were reported for all 3 axes,
the significance of correlations between matrices was determined only by axis 1 P
values because this axis accounted for the most variation in all analyses (B. McCune,
Oregon State University personal communication).
RESULTS
Wetland rankings Total mean ranks combining vegetation, anuran, avian, invertebrate, and
habitat rankings were similar between all wetlands (F14,60 = 1.26, P = 0.260; Table 7).
Nonetheless, Leading Creek, Trus Joist MacMillan, Triangle, Walnut Bottom, and
Elk Run scored the lowest (best) 5 overall ranks of all wetlands (Table 7). Triangle
and Trus Joist MacMillan scored similar ranks, as did Walnut Bottom and Elk Run.
The lowest overall rank was assigned to Leading Creek whereas the fourth and fifth
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lowest were Walnut Bottom and Elk Run. On the contrary, Elder Swamp,
Meadowville, Sugar Creek, Altona Marsh and Sand scored the 5 highest (worst)
ranks, with Elder Swamp scoring the highest rank of all wetlands. Altona Marsh and
Sand Run scored similar scores. The other 3 wetlands scored ranks in the middle.
The remaining results below are presented in a similar manner as above using the
same scales.
Vegetation rankings were significantly different among the best and worst
wetlands (F14,75 = 6.66, P < 0.001; Table 7). VEPCO, Elk Run, and Trus Joist
MacMillan scored lower (better) vegetation ranks than Sugar Creek, Muddlety,
Altona Marsh, and Meadowville, which scored the highest (worst) vegetation ranks.
Enoch Branch and Sand Run also scored relatively low ranks, but these were only
statistically lower than Muddlety and Sugar Creek.
Invertebrate rankings also were different among the best and worst wetlands
(F14,105 = 5.15, P < 0.001; Table 7). Walnut Bottom, Triangle, Elk Run, and Altona
Marsh ranks were significantly lower than Elder Swamp, Enoch Branch, and VEPCO.
Bear Run also scored a low rank, which was significant only to Elder Swamp and
Enoch Branch.
Avian rankings were different among the best and worst wetlands as well
(F14,75 = 3.03, P = 0.001; Table 7). Trus Joist MacMillan, Elk Run, and Walnut
Bottom scored ranks significantly lower than the worst wetlands, Elder Swamp and
VEPCO. Although not significant, Buffalo Coal and Leading Creek scored fourth
and fifth lowest ranks while Enoch Branch and Sugar Creek scored the third and
fourth highest ranks.
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In addition, anuran ranks were different among the best and worst wetlands
(F14,240 = 5.13, P < 0.001; Table 7). The wetlands with the 2 lowest ranks, Enoch
Branch and Leading Creek, were statistically lower than the wetlands with the 2
highest ranks, Altona Marsh and Meadowville. Although results were not significant,
Walnut Bottom, Buffalo Coal, and Muddlety scored the next lowest anuran ranks of
all wetlands. Similarly, next to Altona Marsh and Meadowville, VEPCO, Elk Run,
and Bear Run scored the next highest anuran ranks of all wetlands.
Habitat Suitability Index ranks were similar among all wetlands (F14,105 =
1.76, P < 0.055; Table 7). Nonetheless, Leading Creek, Altona Marsh, Muddlety,
VEPCO, Sugar Creek, and Triangle scored the lowest ranks and Sand Run, Bear Run,
Elk Run, Meadowville, and Buffalo Coal scored the highest habitat ranks.
Canonical Correspondence Analysis The Monte Carlo simulation of all 3 axes indicated that environmental
variables predicted species all taxa abundance no better than sets of scores randomly
assigned to samples, both for all wetlands and for mitigation sites only. The
probabilities of achieving the relationships by chance for all avians, waterbirds,
anurans, benthic invertebrates, and nektonic invertebrates are provided in Tables 8-
12, respectively. Ordination diagrams of species distributions and environmental
variables (vectors) for all avians (all wetlands: Figure 1; mitigation wetlands: Figure
2), waterbirds (all wetlands: Figure 3), anurans (all wetlands: Figure 4; mitigation
wetlands: Figure 5), benthic invertebrates (all wetlands: Figure 6; mitigation
wetlands: Figure 7), and nektonic invertebrates (all wetlands: Figure 8; mitigation
wetlands: Figure 9). Species and environmental codes for all avians and waterbirds,
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anurans, benthic invertebrates, and nektonic invertebrates are provided in Tables 13-
15. Common and scientific names for avians and anurans are presented in Appendix
52.
Wetland delineation Wetland boundaries of all study sites are presented in Chapter II in conjuntion
with maps of dominant vegetation communities. Information on the sizes of wetlands
as required under permits issued for compensatory mitigation could only be obtained
for Buffalo Coal and Elk Run. According to permits, Buffalo Coal and Elk Run were
required to be 12.1 ha and 6.1 ha, respectively. The current estimated size of these
sites as determined through methods aforementioned was 9.0 ha and 3.8 ha,
respectively. Although permit requirements on wetland size were unable to be
obtained for the remaining 9 mitigation wetlands, mitigation plans indicating size
specifications for construction were obtained for VEPCO and Trus Joist MacMillan.
According to GAI Consultants Inc (1993), the intended size of VEPCO at time of
construction was 7.8 ha. Similarly, Montgomery Watson (1996) reported the
restoration of >2.4 ha of wetlands for Trus Joist MacMillan. Current estimated sizes
of VEPCO and Trus Joist MacMillan were 7.0 ha and 3.2 ha, respectively.
Seven of 11 mitigation wetlands were wet across all or most of the wetland
basin. The amount of existing dry areas within the basins were significant for only 4
mitigation wetlands: Elk Run, Leading Creek, Sugar Creek, and Trus Joist
MacMillan. These wetlands contained dry areas of 1.0, 2.0, 1.0, and 1.2 ha,
respectively. Using the estimated sizes of delineated wetlands (Chapter II), the
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percentage of the wetland basins that were actually wet was 79.2, 81.4, 87.2, and
72.7%, respectively for these wetlands.
DISCUSSION
Wetland rankings Mitigation wetlands generally scored higher overall ranks than reference
wetlands, with reference wetlands scoring ranks in the middle. These ranks reflect
the general trend of higher vegetation and wildlife metrics in mitigation than
reference wetlands observed in Chapters II-IV.
Despite moderate vegetation and invertebrate rankings, Leading Creek scored
the lowest (best) overall rank of all wetlands evaluated. Indeed, this site scored
among the best sites in avian and anuran rankings and actually scored the best HSI
rank of all sites. Leading Creek scored number 1 rankings for beaver, great blue
heron, wood duck, snapping turtle, and red-spotted newt models. Variables that
attributed to these results are provided in Chapter IV, but surrounding trees and
shrubs definitely contributed to this statistic. Leading Creek provided excellent
combinations of large size and habitat heterogeneity for avians and anurans. In
addition to artificial nest boxes, this site contained numerous artificial and natural
perching structures that likely attributed to avian diversity. As well, it contained
well-balanced percentages of open water and emergent vegetation.
Triangle and Trus Joist MacMillan scored the next best ranks of all wetlands.
Triangle provided a heterogeneous environment with varying hydrologic regimes
along complex gradients. Although Triangle contained less than optimum amounts of
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open water, it did contain moderate amounts of shrub cover and abundant submerged
aquatic vegetation. As such, it scored the second best invertebrate rank (next to
Walnut Bottom) and the fourth best habitat quality rank of all wetlands. Avian and
anuran ranks were moderate. This site should be monitored closely for potential
impacts by beaver and the adjacent major highway. Trus Joist MacMillan scored a
similar overall rank to Triangle. Despite poor anuran and habitat ratings, Trus Joist
MacMillan scored the best avian rank and the third best vegetation rank of all
wetlands. The moderate anuran rating was likely attributed to predatory fish, and
perhaps even to sampling bias caused by the loud factory nearby, which interfered
with the ability to hear some individual�s calls. A major contributing factor to such a
good avian ranking could be the number of snags present throughout the eastern,
open-water portion of the wetland. Numerous birds were observed utilizing these
snags for nesting, foraging, or perching. Indeed, many studies have revealed the
importance of snags to avians (Hudman and Chandler, 2002; Bell and Whitmore,
2000; North et al., 2000). This site also scored the best beaver and wood duck HSI
rankings of all wetlands. Numerous variables contributed to this result (Chapter IV).
Unfortunately, this wetland was used quite extensively for recreation. Tracks from
All Terrain Vehicles (ATVs) were observed on multiple occasions both in and around
the wetland. It also is moderately fished. Considering the value of this wetland to
wildlife, I recommend fencing off this wetland to prevent further structural damage.
Another potential problem for this site is beaver. A breached beaver dam on the
eastern outflow has significantly impacted the hydrology at this site, and without
proper mitigation, this site may continue to desiccate at an alarming rate.
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Walnut Bottom and Elk Run scored similar ranks above Triangle and Trus
Joist MacMillan. Walnut Bottom is not only the largest of all mitigation wetlands, it
provides a heterogeneous environment (despite one of the highest vegetation
rankings) composed of multiple open water and emergent cells of varying shape and
sizes. It also is one of the most isolated of all sites (next to Bear Run), and contains
abundant submerged aquatic vegetation, hemimarsh conditions, variable water
depths, and snags. As a result, this site scored the best invertebrate ranking, and the
third best anuran and avian rankings. Because this site contains 3 cells on a gradient
separated by culverts, it may be compatible with moist-soil management. One
negative aspect of this site is its landscape position. Because Walnut Bottom is
located in an agricultural landscape with minimal surrounding shrub and tree
coverage, this site scored a moderate HSI ranking due to lack of food and cover for
beaver and mink. This site also may suffer from negative affects associated with
agricultural run-off (Chapter IV). Elk Run, like Trus Joist MacMillan, scored a poor
anuran rank, probably due to predatory fish and low amounts of emergent vegetation
(Chapter IV). But this site also contained abundant open water with numerous snags,
and was positioned immediately adjacent to a forest. As such, it scored the second
best avian rank of all sites, along with the third best invertebrate rank. Elk Run
scored the second best vegetation rating of all wetlands, which was unexpected
considering this wetland is one of the oldest of all sites and is essentially a large pond
containing hydrophytic vegetation only along the perimeter. As such, a low mean
weighted average was expected, but considering that only 1 vegetation plot was
established on the lower cell and no sampling replicates existed for this site,
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conclusions regarding vegetation establishment should be made with caution. This
clearly shows that vegetation rankings can provide misleading conclusions regarding
the successful establishment of vegetation communities.
Environmental data
Canonical Correspondence Analysis yielded weak correlations between
species and environmental data throughout all taxa analyzed. Some factors that may
account for such weak correlations include species dominance overriding
environmental factors, factor interactions, unmeasured variables, and chance
(Kazmierczak et al., 1995). I believe that a larger sample size would have revealed
the importance of these variables. Although statistical significance did not emerge
regarding wetland habitat characteristics, it is clear that these attributes play a large
role in structuring wildlife communities (Chapters II-IV). Indeed these data indicate
that size, as well as percent emergent vegetation, submerged aquatic vegetation, open
water, and shrub cover, in addition to the presence of snags and artificial nesting and
perching structures, may play important roles in determining the habitat quality for a
variety of communities in the wetlands I evaluated. Wetland size is known to affect
overall avian richness (MacArthur and Wilson, 1967; Tyser, 1983; Delphey and
Dinsmore,1993). In addition, percent emergent vegetation is known to affect
waterbird and waterfowl distribution (Kaminski and Price, 1981; Bookhout et al.,
1989; Murkin et al., 1997), as well as anuran abundance (Stumpel and Van Der Voet,
1998). Other studies have linked invertebrate community structure to quality and
quantity of aquatic vegetation (Brown et al., 1988; Wilcox, 1992; Streever et al.,
1995; Zimmer et al., 2000), including submergent vegetation (Carpenter and Lodge,
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1986). My study, however, found no such links between wildlife distribution and
abundance and environmental factors.
A look at wildlife population trends within the wetlands themselves provides
evidence of the importance in constructing wetlands with specific habitat attributes to
enhance wildlife colonization and proliferation. For instance, Bear Run consisted of
12 semipermanently flooded to permanently flooded ponds separated by a series of
dikes, and there was a clear difference in vegetative structure between southern and
northern cells. While the northern cells were mainly open water ponds, the 3 upper
cells to the southeast were dominated by emergent vegetation consisting of cattail
(Typha latifolia) and spikerush (Eleocharis quadrangulata). It was clear that frogs
and invertebrate, particularly nektons, utilized the 3 upper cells more frequently. This
contention is supported in Chapter III by results that showed much higher invertebrate
abundances in emergent areas. However, a statistical evaluation of anurans was
unable to be conducted because of difficulty in distinguishing anuran calls from open
water and emergent areas within individual cells. Similar results were obtained at
Sand Run, where a clear border exists between a large open water area to the west
and an area dominated by emergent vegetation (i.e., Juncus effusus) to the east.
Furthermore, although no statistical significance emerged correlating
emergent vegetation to anuran abundance, a trend did appear to exist in correlating
these 2 variables. For example, with the exception of VEPCO, the wetlands with the
poorest rankings (i.e., Altona Marsh, Meadowville, Bear Run, Sugar Creek, and Elk
Run) fell at the extreme ends of the spectrum with regards to percent emergent
vegetation (i.e., ≤ 22.3 or ≥ 81.0) One variable that was not quantified was the
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amount of snags present among wetlands. Indeed, the 2 wetlands that scored the best
avian ranks (Trus Joist MacMillan and Elk Run) were the only 2 wetlands that
contained abundant snags. These data, combined with those data presented in
Chapters II-IV show trends in habitat characteristics that contribute to wildlife
colonization and proliferation. These trends are incorporated into habitat
management recommendations for future mitigation wetlands (Chapter IV).
Mitigation success The wetland rankings outlined above provide an objective view into the
success of individual mitigation sites in performing ecological functions relative to
one another. As mentioned, Leading Creek, Trus Joist MacMillan, Triangle, Walnut
Bottom, and Elk Run scored the best overall ranks of all wetlands. For the most part,
I agree with results from wetland ranks regarding the success of individual wetlands.
However, using best professional judgement in conjuntion with wetland ranks, I have
created a list of what I think are the most successful mitigation wetlands. The
following is a list of all 11 mitigation sites in order from most successful (best) to
least successful (worst): Walnut Bottom, Buffalo Coal, Leading Creek, Enoch
Branch, Triangle, Sugar Creek, Trus Joist MacMillan, Bear Run, Elk Run, VEPCO,
and Sand Run. The rationale behind this list lies mostly with specifications on size,
heterogeneity, and disturbance. For instance, larger, more heterogeneous wetlands
with fewer disturbances were more successful than smaller, more monotypic wetlands
(i.e. too much open water or emergent vegetation, or lacking diverse hydrologic
gradients). In creating this list, I also prioritized these specifications into what I
thought were most important in determining the success of mitigation wetlands. For
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example, heterogeneity is more important than size, which is more important than
disturbance. Besides Trus Joist MacMillan and Elk Run, these specifications were
fairly accurate in predicting the positions of individual wetlands along the rank
spectrum (i.e., larger, more heterogeneous wetlands scored better ranks).
The success of individual wetlands from an area perspective, as opposed to
ecological function, was not determined for most mitigation sites because issuing
permits and mitigation plans were unavailable. Both Buffalo Coal and Elk Run area
determinations fell short of size requirements outlined in permits issued by the U.S.
Army Corps of Engineers. VEPCO, too, fell short of size projections according to
mitigation plans, but only slightly. Trus Joist MacMillan was the only wetland out of
the 4 to meet area requirements, at least according to the wetland mitigation plan.
Due to lack of available information on size specifications, it is difficult, to gauge the
relative success of individual wetlands in meeting size requirements. Although this
information would be important from a regulatory standpoint, it yields little insight
into functional success of a particular wetland relative to other sites.
Conclusions
An underlying assumption with respect to evaluating the success of mitigation
wetlands based on vegetation and wildlife rankings, is that first, all ranks are
weighted equally. Of course, some components may be more important than others
and should therefore be weighted more heavily. For instance, overall avian and
anuran species abundances are weighted similar to individual or guild species
abundances. Although total species abundance could be weighted more heavily since
it represents a combination of all species observed, it would be difficult to calibrate
260
the value of metrics accurately, and thus, would lead to spurious results. Hence,
metrics were weighted equally, and despite the implicit error in this assumption,
comparisons can still be made as to the relative success of mitigation wetlands in
supporting wildlife communities.
Another assumption of these analyses is that wetlands that scored lower ranks
were �better� or �more successful� than wetlands that scored higher ranks. An
important aspect to consider is development time. These data provided insight into
the community dynamics of these mitigation wetlands at only one point in time.
Based on results obtained in Chapter II, it was clear that development time affects
vegetation community structure and composition, and these results are reflected in the
ranks assigned to individual wetlands. Specifically, 3 of 4 reference wetlands scored
among the highest vegetation ranks of all 15 wetlands, which reflects the lower
species richness and diversity values observed in reference wetlands in Chapter II.
Two of the 4 wetlands (Elder Swamp and Meadowville) scored the lowest rankings
for all metrics combined. An evaluation of these wetlands in 10 or 20 years may
yield entirely different rankings all together as autogenic and allogenic factors
influence vegetative structure and composition, and hence, wildlife distribution and
abundance. Thus, I do not think that poor rankings of reference wetlands reflects
inadequate selection of reference wetlands. I Nonetheless, these data provide
researchers with a current index of the success of mitigation wetlands in West
Virginia in supporting wildlife communities.
The strength of the overall index rankings lies in the comprehensive nature of
the ranks themselves. By combining vegetation, invertebrates, avians, and anurans,
261
researchers are provided with a comprehensive view of the ecological functions of
these wetlands. This allows researchers to document trends in wetland structure that
improve general habitat quality for wildlife, or to assess more specific trends that
contribute to improving habitat quality for one particular taxa (i.e., anurans). This
provides more latitude in creating management objectives for constructed wetlands.
Specifically, if future mitigation efforts focus on replacing anuran habitat, as opposed
to general wildlife habitat, one could look for correlations between anuran
distribution and abundance and wetland structure. The anuran rankings provided in
this study could be applicable in such a scenario.
Future research is needed to provide researchers with a clearer understanding
of the dynamics involved in creating mitigation wetlands with high quality wildlife
habitat. Based on a literature review and data presented in this study, I compiled a list
of future research needs in order of importance to assist in the construction and
evaluation of future mitigation wetlands:
1) Identify site-specific wildlife habitat lost to wetland destruction and
implement mitigation ratios that reflect habitat quantity and quality.
2) Determine the effect of dispersal corridors and constructed wetland
size on wildlife distribution and abundance.
3) Compare wildlife communities of mitigation banking systems to
those in isolated constructed wetlands.
4) Study the effects of moist soil management on vegetation and
invertebrate production in constructed wetlands.
262
5) Study the effects of agricultural and road run-off on water quality in
wetlands constructed adjacent to agricultural fields and roads,
respectively.
6) Examine the effects of native vegetation plantings on constructed
vegetation community structure.
7) Evaluate recruitment of amphibians in constructed wetlands via
larval sampling or egg mass surveys.
The mitigation wetlands created in West Virginia currently act as good
models for future wetland development. My data showed that, overall, the ecological
function these wetlands performed was at or near reference standards. I hope
researchers will incorporate management recommendations provided throughout this
thesis into future mitigation wetlands. As well, I hope future studies outlined above
will be undertaken to enhance our knowledge of wetland ecosystems, thus ensuring
the compensation of wildlife habitat lost to wetland destruction and preserving the
integrity of wetland ecosystems for years to come.
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CHAPTER V
TABLES
275
Table 1. List of 11 mitigation and 4 reference wetland study sites in West Virginia, including site name, year constructed, size
(ha), source builder, Universal Transverse Mercator (UTM) coordinates, 7.5 minute quadrangle, basin, and watershed, 2001-
2002.
Site name Year Size (ha) Source UTM Y UTM X Quad Basin Watershed
Mitigation Sites Walnut Bottom 1997 9.5 Division of Hwys 4334210 673914 Old Fields S. Branch of Potomac R. S. Branch of Potomac R. VEPCO 1995 7.0 VA Electric Power 4337900 641300 Mt. Storm Cheat River Blackwater River Buffalo Coal 1981 9.0 Davis Trucking Co. 4332100 630900 Davis Cheat River Blackwater River Elk Run 1981 3.8 Island Crk Coal Co. 4342000 636250 Davis N. Branch of Potomac R. Elk Run Leading Creek 1995 8.6 Division of Hwys 4321563 602550 Montrose Tygart Valley Leading Creek Sugar Creek 1995 6.8 Division of Hwys 4328850 591470 Belington Tygart Valley Laurel Creek Sand Run 1992 3.0 Division of Hwys 4315060 573140 Buckhannon Tygart Valley Sand Run Triangle 1992 3.1 Division of Hwys 4316950 568500 Buckhannon Tygart Valley Buckhannon River Trus Joist MacMillan 1994 3.2 TJM Timber Co. 4318340 569560 Century Tygart Valley Buckhannon River Enoch Branch 1997 3.4 Division of Hwys 4247300 514550 Widen Gauley River Muddlety Creek Bear Run 1993 6.2 WV Dept Env. Prot. 4305780 519750 Glenville Little Kanawha Little Kanawha
Reference Sites Altona Marsh N/A 15.2 N/A 4353000 768600 Middleway Shenandoah River Shenandoah River Elder Swamp N/A 28.0 N/A 4340000 642200 Mt. Storm Lake Cheat River Blackwater River Meadowville N/A 6.5 N/A 4330920 593940 Nestorville Tygart Valley Laurel Creek Muddlety N/A 10.4 N/A 4248480 516790 Widen Gauley River Muddlety Creek
276
Table 2. Actual means and ranks of vegetation richness (no.species/plot), evenness, evenness (native species only), diversity,
diversity (native species only), and weighted average, as well as total mean and scaled ranksa for 11 mitigation and 4 reference
wetlands in West Virginia, 2001-2002.
Mitigation Wetlands
Walnut Bottom VEPCO
Buffalo Coal Elk Run
Leading Creek
Sugar Creek
Sand Run Triangle
Trus JoistMacMillan
Enoch Branch
Bear Run
x SE x SE x SE x SE x SE x SE x SE x SE x SE x SE x SE Richness 8.8 2.3 15.0 1.7 9.3 1.2 16.0 4.2 14.8 3.4 13.8 4.3 11.8 4.5 16.2 3.3 19.5 4.9 10.8 3.1 8.5 0.5 Rank 11.0 4.0 10.0 3.0 5.0 6.0 7.0 2.0 1.0 9.0 13.0 Evenness 0.71 0.1 0.84 0.2 0.77 0.1 0.77 0.1 0.75 0.1 0.44 0.1 0.78 0.1 0.71 0.1 0.74 0.2 0.78 0.2 0.78 0.2 Rank 10.0 1.0 5.5 5.5 7.0 15.0 3.0 10.0 8.0 3.0 3.0 Evenness (natives) 0.69 0.2 0.83 0.2 0.76 0.06 0.75 0.2 0.74 0.2 0.44 0.1 0.78 0.2 0.70 0.2 0.73 0.2 0.78 0.2 0.78 0.2 Rank 11.0 1.0 5.0 6.0 7.0 15.0 3.0 10.0 8.0 3.0 3.0 Diversity 1.6 0.1 2.3 0.1 1.7 0.1 2.2 0.1 2.0 0.1 1.2 0.1 1.7 0.1 2.0 0.04 2.3 0.1 1.8 0.02 1.7 0.03 Rank 10.5 1.5 8.0 3.0 4.5 14.0 8.0 4.5 1.5 6.0 8.0 Diversity (natives) 1.5 0.1 2.2 0.01 1.7 0.1 2.1 0.1 2.0 0.1 1.2 0.1 1.7 0.1 1.9 0.1 2.2 0.1 1.8 0.1 1.7 0.1 Rank 11.0 1.5 8.0 3.0 4.0 14.0 8.0 5.0 1.5 6.0 8.0 Weighted average 0.73 0.1 0.46 0.1 0.42 0.1 0.40 0.1 0.75 0.1 1.5 0.1 0.41 0.1 1.1 0.2 1.1 0.1 0.45 0.1 0.29 0.1 Rank 9.0 8.0 6.0 4.0 10.0 14.5 5.0 11.5 11.5 7.0 2.0 Mean rank 10.4 0.3 2.8 1.1 7.1 0.8 4.1 0.6 6.3 0.9 13.1 1.4 5.6 0.9 7.2 1.6 5.3 1.8 5.7 0.9 6.2 1.7 Scaled rank 11.0 1.0 8.0 2.0 7.0 15.0 4.0 9.0 3.0 5.0 6.0
277
Table 2. Extended. Reference Wetlands
Altona Marsh
Elder Swamp Meadowville Muddlety
x SE x SE x SE x SE Richness 8.7 1.2 6.6 1.6 11.0 1.3 6.0 0.8 Rank 12.0 14.0 8.0 15.0 Evenness 0.68 0.2 0.71 0.1 0.62 0.1 0.47 0.1 Rank 12.0 10.0 13.0 14.0 Evenness (natives) 0.68 0.2 0.71 0.2 0.61 0.1 0.47 0.1 Rank 12.0 9.0 13.0 14.0 Diversity 1.5 0.1 1.3 0.1 1.6 0.1 0.84 0.1 Rank 12.0 13.0 10.5 15.0 Diversity (natives) 1.5 0.1 1.3 0.1 1.5 0.1 0.84 0.1 Rank 11.0 13.0 11.0 15.0 Weighted average 1.4 0.04 0.35 0.1 1.5 0.4 0.28 0.1 Rank 13.0 3.0 14.5 1.0 Mean rank 12.0 0.3 10.3 1.7 11.7 0.9 12.3 2.3 Scaled rank 13.0 10.0 12.0 14.0 aWetlands with similar mean ranks were assigned similar scaled ranks.
278
Table 3. Actual mean and ranks of benthic and nektonic invertebrate richness (no.families/wetland), diversity, density, and mass, as well
as total mean and scaled ranksa for 11 mitigation and 11 reference wetlands in West Virginia, 2001-2002.
Mitigation Wetlands
Walnut Bottom VEPCO
Buffalo Coal
Elk Run
Leading Creek
Sugar Creek Sand Run Triangle
Trus Joist MacMillan
Enoch Branch
Metric x SE x SE x SE x SE x SE x SE x SE x SE x SE x SE Benthic Richness 2.8 0.1 1.6 0.3 1.4 0.1 2.0 0.4 1.9 0.3 1.6 0.2 1.3 0.2 2.6 0.3 2.2 0.1 1.4 0.1 Rank 2.0 8.5 11.5 5.0 6.0 8.0 14.0 3.0 4.0 11.5 Diversity 1.3 0.3 1.5 0.4 1.6 0.4 1.6 0.3 1.5 0.5 1.0 0.1 1.7 0.3 1.8 0.4 1.3 0.2 1.4 0.2 Rank 13.5 10.5 7.0 7.0 10.5 15.0 4.0 3.0 13.5 12.0 Density (no./m2) 169.4 32.1 15.9 6.4 12.9 3.1 57 12.9 26.1 7.1 35.2 16.2 8 3.3 60.2 18.3 75.3 7.7 14.8 6.8 Rank 2.0 10.0 13.0 5.0 8.0 6.0 14.0 4.0 3.0 11.5 Mass (g/ m2) 10.16 4.7 0.017 0.01 0.024 0.01 2.104 0.85 0.123 0.07 0.831 0.64 0.141 0.10 0.908 0.47 0.941 0.40 0.021 0.01Rank 2.0 14.0 12.0 3.0 9.0 6.0 8.0 5.0 4.0 13.0 Nektonic Richness 2.8 0.2 1.8 0.1 3.0 0.4 2.6 0.2 2.4 0.3 1.8 0.0 2.4 0.2 3.2 0.6 2.1 0.6 1.8 0.1 Rank 3.0 12.0 2.0 5.5 7.5 12.0 7.5 1.0 9.0 12.0 Diversity 2.5 0.8 2.0 0.6 2.4 0.7 2.6 0.3 2.9 0.4 2.8 0.6 2.7 0.5 2.8 0.4 1.9 0.5 2.4 0.6 Rank 8.5 14.0 11.5 6.5 1.5 3.5 5.0 3.5 15.0 11.5 Density (no./L) 21.1 5.1 4.4 1.7 14.4 6.7 9.8 2.9 4.0 1.1 4.2 0.8 2.1 0.4 12.3 6.4 14.4 6.0 1.7 0.4 Rank 1.0 10.0 2.5 6.0 12.0 11.0 14.0 5.0 2.5 15.0 Mass (g/L) 1.135 0.98 0.005 0.0 0.021 0.01 0.106 0.06 0.025 0.01 0.051 0.04 0.009 0.01 0.026 0.01 0.1070 0.04 0.009 0.01Rank 1.0 14.0 11.0 3.0 10.0 6.0 12.0 9.0 2.0 13.0 Total mean rank 4.1 1.6 11.6 0.8 8.8 1.6 5.1 0.5 8.1 1.1 8.4 1.4 9.8 1.5 4.2 0.8 6.6 1.8 12.4 0.4 Scaled rank 1.0 13.0 10.0 3.0 8.0 9.0 12.0 2.0 6.0 14.5
279
Table 3. Extended.
Mitigation
Cont. Reference Wetlands Bear Run Altona Marsh Elder Swamp Meadowville Muddlety Metric x SE x SE x SE x SE x SE Benthic Richness 1.7 0.3 4.5 0.4 1.4 0.2 1.4 0.2 1.6 0.3 Rank 7.0 1.0 11.5 11.5 8.5 Diversity 1.6 0.5 1.9 0.6 1.6 0.5 1.6 0.5 2.0 0.7 Rank 7.0 2.0 7.0 7.0 1.0 Density (no./m2) 30.4 12.7 593.5 236.0 3.7 0.9 14.8 19.2 Rank 7.0 1.0 15.0 11.5 9.0 Mass (g/m2) 0.322 0.15 43.06 25.9 0.002 0.0 0.028 0.0 0.062 0.02Rank 7.0 1.0 15.0 11.0 10.0 Nektonic Richness 2.6 0.3 1.5 0.5 1.5 0.3 2.0 0.1 2.7 0.4 Rank 5.5 14.5 14.5 10.0 4.0 Diversity 2.9 0.5 2.4 0.6 2.5 0.6 2.4 0.5 2.6 0.6 Rank 1.5 11.5 8.5 11.5 6.5 Density (no./L) 6.6 0.6 9.5 3.4 2.4 0.7 12.6 1.8 8.7 3.2 Rank 9.0 7.0 13.0 4.0 8.0 Mass (g/L) 0.053 0.03 0.065 0.03 0.003 0.0 0.047 0.02 0.029 0.02Rank 5.0 4.0 15.0 7.0 8.0 Total mean rank 6.1 0.8 5.3 1.2 12.4 1.1 9.2 1.0 6.9 1.1 Scaled rank 5.0 4.0 14.5 11.0 7.0 aWetlands with similar mean ranks were assigned similar scaled ranks.
280
Table 4. Actual means and ranks of avian richness (no. birds/0.78 ha plot) and diversity, and abundance (no.indiv./0.78 ha plot) for all
birds, waterbirds, waterfowl, and passerines, as well as total mean and scaled ranksa of 11 mitigation and 4 reference wetlands in West
Virginia, 2001-2002.
Mitigation Wetlands
Walnut Bottom VEPCO
Buffalo Coal
Elk Run
Leading Creek
Sugar Creek
Sand Run Triangle
Trus JoistMacMillan
Enoch Branch
Bear Run
Metric x SE x SE x SE x SE x SE x SE x SE x SE x SE x SE x SE Richness 9.9 1.2 5.3 0.9 7.9 0.5 12.3 0.6 8.1 0.6 8.2 0.7 9.0 0.7 8.6 1.1 12.9 1.4 9.4 0.8 8.8 0.8 Rank 5.0 15.0 13.0 2.0 12.0 11.0 7.0 9.5 1.0 6.0 8.0 Diversity 2.1 0.2 2.33 0.3 2.18 0.1 2.45 0.3 2.75 0.5 2.7 0.5 1.93 0.1 1.91 0.1 2.48 0.4 2.64 0.5 3.08 0.3 Rank 11.0 8.0 10.0 7.0 2.0 3.0 12.5 14.0 6.0 4.5 1.0 Abundance all birds 40.3 5.0 7.4 1.3 27.3 6.3 28.0 2.4 16.5 1.1 13.0 1.5 20.8 3.3 23.5 5.4 29.9 4.4 12.6 1.3 13.3 0.8 Rank 1.0 15.0 5.0 4.0 10.0 12.0 8.0 7.0 3.0 13.0 11.0 Waterbirdsb 19.5 17.8 0.8 0.4 9.3 4.9 3.3 2.6 3.6 0.5 0.8 0.6 0.8 0.5 1.4 0.7 2.6 1.2 1.1 0.7 0.7 0.3 Rank 1.0 9.0 2.0 4.0 3.0 9.0 9.0 6.0 5.0 7.0 11.0 Waterfowlc 18.4 7.8 0.5 0.2 8.5 4.8 2.5 2.5 3.1 0.5 0.8 0.6 0.8 0.5 1.1 0.6 1.6 1.1 0.4 0.2 0.5 0.3 Rank 1.0 9.0 2.0 4.0 3.0 7.0 7.0 6.0 5.0 10.0 9.0 Passerinesd 18.6 5.7 6.4 1.0 17.5 3.2 22.5 1.5 12.5 0.7 11.2 1.3 19.3 3.5 21.4 4.7 25.1 3.7 9.3 1.0 11.2 0.6 Rank 7.0 15.0 8.0 4.0 10.0 11.5 6.0 5.0 2.0 14.0 11.5 Total mean rank 4.3 1.7 11.8 1.4 6.7 1.8 4.2 0.7 6.7 1.8 8.9 1.4 8.3 0.9 7.9 1.4 3.7 0.8 9.1 1.6 8.6 1.6 Scaled rank 3.0 14.0 4.5 2.0 4.5 12.0 8.0 7.0 1.0 13.0 9.0
281
Table 4. Extended. Reference Wetlands
Altona Marsh
Elder Swamp Meadowville Muddlety
Metric x SE x SE x SE x SE Richness 10.1 0.5 5.4 0.7 10.4 0.8 8.6 0.8Rank 4.0 14.0 3.0 9.5 Diversity 2.21 0.2 1.93 0.2 2.64 0.3 1.82 0.2Rank 9.0 12.5 4.5 15.0 Abundance all birds 26.2 2.0 10.0 2.6 16.7 0.9 35.9 12.7 Rank 6.0 14.0 9.0 2.0 waterbirds 0.6 0.6 0.3 0.1 0.1 0.1 0.4 0.4Rank 12.0 14.0 15.0 13.0 waterfowl 0.6 0.6 0.1 0.1 0.0 0.0 0.0 0.0Rank 8.0 11.0 12.0 12.0 passerines 23.9 2.4 9.8 2.5 15.2 0.4 34.5 12.9Rank 3.0 13.0 9.0 1.0 Total mean rank 7.0 1.4 13.1 0.5 8.8 1.8 8.8 2.4Scaled rank 6.0 15.0 10.5 10.5 aWetlands with similar mean ranks were assigned similar scaled ranks. bIncludes only those birds that depend on water for all or most of their life requisites. cIncludes only birds in the family Anatidae. dIncludes only birds in the order Passeriformes.
282
Table 5. Actual means and ranks of anuran richness (no.species/wetland), Wisconsin Index (WI),
and abundance for all species and for 7 individual species, as well as total mean and scaled ranksa
of 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002.
Mitigation Wetlands
Walnut Bottom VEPCO
Buffalo Coal Elk Run
Leading Creek Sugar Creek Sand Run Triangle
Trus Joist MacMillan
Index x SE x SE x SE x SE x SE x SE x SE x SE x SERichness 2.4 0.3 1.7 0.2 1.9 0.2 1.5 0.2 2.2 0.2 1.9 0.2 2.3 0.3 1.8 0.4 2.0 0.4Rank 2.0 11.5 7.0 13.0 4.0 8.0 3.0 9.0 5.0 Total WI 0.57 0.1 0.46 0.1 0.62 0.1 0.48 0.1 0.56 0.1 0.43 0.04 0.45 0.1 0.62 0.2 0.45 0.1Rank 4.0 8.0 2.5 7.0 5.5 12.0 9.5 2.5 9.5 Spring peeper 1.5 0.3 2.1 0.2 2.5 0.2 2.3 0.3 2.2 0.1 1.5 0.2 1.4 0.3 1.7 0.6 1.3 0.5Rank 10.5 6.0 2.5 4.0 5.0 10.5 13.0 8.0 14.0 Gray treefrog 0.58 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.26 0.1 0.26 0.1 0.25 0.1 0.0 0.0 0.0 0.0Rank 1.0 11.8 11.8 11.8 4.5 4.5 6.5 11.8 11.8 American bullfrog 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.04 0.02 0.33 0.1 0.0 0.0 0.17 0.2Rank 11.8 11.8 11.8 11.8 6.0 8.0 2.5 11.8 4.0 Wood frog 0.0 0.0 0.54 0.2 0.42 0.2 0.0 0.0 0.21 0.1 0.15 0.1 0.0 0.0 0.0 0.0 0.0 0.0Rank 11.5 1.0 2.0 11.5 4.0 5.0 11.5 11.5 11.5 Green frog 0.67 0.3 0.54 0.1 1.25 0.4 1.0 0.4 0.74 0.1 0.63 0.1 0.75 0.3 1.83 0.6 0.5 0.3Rank 9.0 12.0 2.0 3.0 6.0 10.0 5.0 1.0 13.0 American toad 0.5 0.2 0.04 0.04 0.17 0.1 0.0 0.0 0.07 0.04 0.11 0.1 0.17 0.2 0.33 0.3 0.33 0.2Rank 1.0 11.5 5.0 14.0 9.0 7.5 5.0 2.5 2.5 Pickerel frog 0.75 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.33 0.1 0.28 0.1 0.25 0.1 0.5 0.3 0.83 0.4Rank 2.0 13.5 13.5 13.5 5.0 7.0 8.0 4.0 1.0 Total abundance 4.01 1.1 4.54 1.0 8.1 1.9 5.6 2.1 4.91 0.8 2.98 0.5 3.06 1.0 7.21 2.5 2.19 1.2Rank 9.0 8.0 1.0 5.0 7.0 11.0 10.0 4.0 14.0 Spring peeper 13.9 5.2 26.9 4.6 37.1 5.7 31.0 8.8 29.3 3.6 17.0 2.9 15.1 5.8 21.3 9.5 11.2 7.9Rank 13.0 7.0 3.0 4.0 6.0 11.0 12.0 8.0 14.0 Gray treefrog 1.8 0.8 0.0 0.0 0.0 0.0 0.0 0.0 0.43 0.1 0.57 0.2 0.27 0.1 0.0 0.0 0.0 0.0Rank 1.0 12.0 12.0 12.0 6.5 4.5 8.0 12.0 12.0 American bullfrog 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.14 0.1 0.06 0.04 0.45 0.2 0.0 0.0 0.17 0.2Rank 12.0 12.0 12.0 12.0 7.0 8.0 3.0 12.0 6.0 Wood frog 0.0 0.0 3.2 2.1 0.83 0.5 0.0 0.0 0.55 0.3 0.2 0.1 0.0 0.0 0.0 1.0 0.0 0.9Rank 11.5 1.0 2.0 11.5 4.0 7.0 11.5 11.5 11.5 Green frog 9.3 5.5 1.6 0.6 17.9 6.9 8.2 4.1 2.9 0.7 2.2 0.4 4.1 1.8 26.3 10.7 1.8 1.2Rank 3.0 14.0 2.0 5.0 10.0 12.0 7.0 1.0 13.0 American toad 1.1 0.6 0.04 0.0 0.17 0.1 0.0 0.0 0.14 0.1 0.24 0.1 1.1 1.1 1.7 1.7 0.5 0.3Rank 2.5 11.5 7.5 14.0 9.0 6.0 2.5 1.0 4.0 Pickerel frog 2.1 0.9 0.0 0.0 0.0 0.0 0.0 0.0 0.95 0.3 0.64 0.2 0.45 0.2 1.2 0.0 1.7 0.0Rank 1.0 13.5 13.5 13.5 5.0 7.0 8.0 3.5 2.0 Total rank 6.2 0.9 9.8 1.0 6.5 1.2 9.8 1.0 6.1 0.4 8.2 0.6 7.4 0.9 6.8 1.1 8.8 1.2Scaled rank 3.0 12.5 4.0 12.5 2.0 8.0 7.0 6.0 10.0
283
Table 5. Extended. Mitigation cont. Reference Wetlands Enoch Branch Bear Run Altona Marsh Elder Swamp Meadowville Muddlety
Index x SE x SE x SE x SE x SE x SERichness 2.7 0.5 1.8 0.2 1.0 0.2 1.7 0.2 1.3 0.2 1.9 0.3Rank 1.0 10.0 15.0 11.5 14.0 6.0 Total WI 0.69 0.1 0.37 0.03 0.28 0.1 0.44 0.1 0.30 0.1 0.56 0.1Rank 1.0 13.0 15.0 11.0 14.0 5.5 Spring peeper 2.5 0.2 1.04 0.1 1.5 0.3 1.9 0.3 1.5 0.3 2.6 0.2Rank 2.5 15.0 10.5 7.0 10.5 1.0 Gray treefrog 0.33 0.2 0.2 0.1 0.0 0.0 0.0 0.0 0.25 0.1 0.39 0.1Rank 3.0 8.0 11.8 11.8 6.5 2.0 American bullfrog 0.44 0.1 0.33 0.1 0.0 0.0 0.0 0.0 0.08 0.1 0.11 0.1Rank 1.0 2.5 11.8 11.8 7.0 5.0 Wood frog 0.11 0.1 0.0 0.0 0.0 0.0 0.22 0.1 0.08 0.1 0.0 0.0Rank 6.0 11.5 11.5 3.0 7.0 8.0 Green frog 0.78 0.3 0.57 0.1 0.33 0.2 0.72 0.2 0.21 0.1 0.72 0.2Rank 4.0 11.0 14.0 7.5 15.0 7.5 American toad 0.06 0.1 0.17 0.1 0.04 0.0 0.11 0.1 0.0 0.0 0.0 0.0Rank 10.0 5.0 11.5 7.5 14.0 14.0 Pickerel frog 0.61 0.2 0.31 0.1 0.08 0.1 0.17 0.1 0.0 0.0 0.11 0.1Rank 3.0 6.0 11.0 9.0 13.5 10.0 Total abundance 7.74 1.6 1.87 0.3 2.94 0.8 4.99 1.2 2.91 0.9 7.93 1.7Rank 3.0 15.0 12.0 6.0 13.0 2.0 Spring peeper 41.9 4.4 8.3 2.0 17.4 4.5 29.7 5.6 18.8 4.9 47.5 4.5Rank 2.0 15.0 10.0 5.0 9.0 1.0 Gray treefrog 0.88 0.4 0.43 0.2 0.0 0.0 0.0 0.0 0.57 0.3 0.75 0.4Rank 2.0 6.5 12.0 12.0 4.5 3.0 American bullfrog 0.76 0.3 0.78 0.2 0.0 0.0 0.0 0.0 0.22 0.2 0.19 0.1Rank 2.0 1.0 12.0 12.0 4.0 5.0 Wood frog 0.24 0.2 0.0 0.0 0.0 0.0 0.61 0.5 0.22 0.2 0.0 0.0Rank 5.0 11.5 11.5 3.0 6.0 11.5 Green frog 9.1 4.1 2.5 0.6 3.0 2.1 4.0 1.5 0.52 0.2 6.8 1.1Rank 4.0 11.0 9.0 8.0 15.0 6.0 American toad 0.06 0.1 0.25 0.1 0.04 0.04 0.17 0.1 0.0 0.0 0.0 0.0Rank 10.0 5.0 11.5 7.5 14.0 14.0 Pickerel frog 1.2 0.5 0.78 0.2 0.21 0.1 0.44 0.2 0.0 0.0 0.31 0.1Rank 3.5 6.0 11.0 9.0 13.5 10.0 Total rank 3.7 0.7 9.0 1.1 11.8 0.4 8.4 0.7 10.6 1.0 6.6 1.0Scaled rank 1.0 11.0 15.0 9.0 14.0 5.0 a Wetlands with similar mean ranks were assigned similar scaled ranks.
284
Table 6. Actual Habitat Suitability Index (HSI) values and ranks of 8 species, as well as total and scaled ranksa of 11
mitigation and 4 reference wetlands in West Virginia, 2001-2002.
Mitigation Wetlands
Walnut Bottom VEPCO
Buffalo Coal Elk Run
Leading Creek
Sugar Creek
Sand Run Triangle
Trus Joist MacMillan
Metric x SE x SE x SE x SE x SE x SE x SE x SE x SERed-winged blackbird 0.10 0.03 0.10 0.01 0.03 0.03 0.01 0.03 0.01 Rank 4.0 8.5 4.0 13.0 8.5 8.5 13.0 8.5 13.0 Beaver 0.58 1.0 0.69 0.49 1.0 0.63 0.51 0.78 1.0 Rank 13.0 1.0 10.0 15.0 1.0 11.0 14.0 9.0 1.0 Muskrat 0.31 0.32 0.29 0.27 0.32 0.32 0.31 0.67 0.3 Rank 10.5 7.5 13.5 15.0 7.5 7.5 10.5 2.0 12.0 Mink 0.75 0.98 0.72 0.55 0.92 0.96 0.5 0.92 0.87 Rank 11.0 2.0 12.0 14.0 4.5 3.0 15.0 4.5 7.0 Great-blue heron 0.32 0.22 0.22 0.32 0.32 0.32 0.16 0.16 0.16 Rank 1.0 9.5 9.5 1.0 1.0 1.0 12.5 12.5 12.5 Wood duck 0.92 1.0 1.0 0.65 1.0 0.30 0.60 0.98 1.0 Rank 7.0 1.0 1.0 10.0 1.0 15.0 11.5 5.0 1.0 Snapping turtle 0.56 0.59 0.61 0.6 0.71 0.65 0.54 0.6 0.61 Rank 11.0 8.0 4.5 6.5 1.0 2.0 12.0 6.5 4.5 Red-spotted newt 1.0 0.93 0.54 1.0 1.0 1.0 0.89 1.0 0.69 Rank 1.0 9.0 15.0 1.0 1.0 1.0 10.0 1.0 12.0 Mean HSI value 0.57 0.10 0.63 0.20 0.52 0.10 0.49 0.10 0.66 0.10 0.53 0.10 0.44 0.10 0.64 0.10 0.58 0.10 Total mean rank 7.3 1.7 5.8 1.3 8.7 1.8 9.4 2.1 3.2 1.1 6.1 1.8 12.3 0.6 6.1 1.3 7.9 1.8 Scaled rank 8.0 3.5 11.0 13.0 1.0 5.5 15.0 5.5 10.0
285
Table 6. Extended. Mitigation Cont. Reference Wetlands
Enoch Branch
Bear Run
Altona Marsh Elder Swamp Meadowville Muddlety
Metric x SE x SE x SE x SE x SE x SE Red-winged blackbird 0.01 0.01 0.30 0.10 0.10 0.10 Rank 13.0 13.0 1.0 4.0 4.0 4.0 Beaver 0.87 0.62 1.0 1.0 1.0 1.0 Rank 8.0 12.0 1.0 1.0 1.0 1.0 Muskrat 0.29 0.48 0.87 0.62 0.39 0.32 Rank 13.5 4.0 1.0 3.0 5.0 7.5 Mink 0.8 0.68 0.82 0.86 0.89 1.0 Rank 10.0 13.0 9.0 8.0 6.0 1.0 Great-blue heron 0.32 0.32 0.32 0.32 0.11 0.16 Rank 1.0 1.0 1.0 1.0 15.0 12.5 Wood duck 0.94 0.59 0.40 0.90 0.60 0.80 Rank 6.0 13.0 14.0 8.0 11.5 9.0 Snapping turtle 0.57 0.57 0.45 0.53 0.49 0.63 Rank 9.5 9.5 15.0 13.0 14.0 3.0 Red-spotted newt 1.0 0.87 1.0 0.62 0.58 0.98 Rank 1.0 11.0 1.0 13.0 14.0 8.0 Mean HSI value 0.60 0.10 0.52 0.10 0.65 0.10 0.62 0.10 0.52 0.10 0.62 0.20Total mean rank 7.8 1.7 9.6 1.6 5.4 2.2 6.4 1.7 8.8 1.9 5.8 1.5 Scaled rank 9.0 14.0 2.0 7.0 12.0 3.5 aWetlands with similar mean ranks were assigned similar scaled ranks.
286
Table 7. Vegetation, invertebrate, avian, anuran, and Habitat Suitability Index (HSI) ranks, as well as total mean and scaled
ranksb for 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002.
Mitigation Wetlands Walnut Bottom VEPCO Buffalo Coal Elk Run Leading Creek Sugar Creek Sand Run Triangle x SE x SE x SE x SE x SE x SE x SE x SE Vegetation ranka 10.4abcd 0.3 2.8e 1.1 7.1abcde 0.8 4.1de 0.6 6.3bcde 0.9 13.1a 1.4 5.6cde 0.9 7.2abcde 1.6 Invertebrate ranka 4.1c 1.6 11.6ab 0.8 8.8abc 1.6 5.1c 0.5 8.1abc 1.1 8.4abc 1.4 9.8abc 1.5 4.2c 0.8 Avian ranka 4.3b 1.7 11.8a 1.4 6.7ab 1.8 4.2b 0.7 6.7ab 1.8 8.9ab 1.4 8.3ab 0.9 7.9ab 1.4 Anuran ranka 6.2bcd 0.9 9.8abc 1.0 6.5bcd 1.2 9.8bcd 1.0 6.1cd 0.4 8.2abc 0.6 7.4abcd 0.9 6.8bcd 1.1 HSI ranka 7.3ab 1.7 5.8ab 1.3 8.7ab 1.8 9.4ab 2.1 3.2b 1.1 6.1ab 1.8 12.3a 0.6 6.1ab 1.3 Total mean ranka 6.5a 1.2 8.4a 1.5 7.6a 0.6 6.5a 1.0 6.1a 1.1 8.9a 0.9 8.7a 0.8 6.4a 0.7 Scaled ranka 4.5 10.0 6.0 4.5 1.0 13.0 11.5 2.5
287
Table 7. Extended. Mitigation Wetlands Cont. Reference Wetlands
Trus Joist
MacMillan Enoch Branch Bear Run Altona Marsh Elder Swamp Meadowville Muddlety
x SE x SE x SE x SE x SE x SE x SEVegetation ranka 5.3de 1.8 5.7cde 0.9 6.2bcde 1.7 12.0abc 0.3 10.3abcd 1.7 11.7abc 0.9 12.3ab 2.3Invertebrate ranka 6.6abc 1.8 12.4a 0.4 6.1bc 0.8 5.3c 1.2 12.4a 1.1 9.2abc 1.0 6.9abc 1.1Avian ranka 3.7b 0.8 9.1ab 1.6 8.6ab 1.6 7.0ab 0.9 13.1ab 0.4 8.8ab 1.4 8.8ab 2 Anuran ranka 8.8abc 1.2 3.7d 0.7 9.0abc 1.1 11.8a 0.4 8.4abc 0.7 10.6ab 1.0 6.6bcd 1 HSI ranka 7.9ab 1.8 7.8ab 1.7 9.6ab 1.6 5.4ab 2.2 6.4ab 1.7 8.8ab 1.9 5.8ab 1.5Total mean ranka 6.4a 0.6 7.7a 1.5 7.9a 0.3 8.7a 1.4 10.6a 1.3 9.7a 0.7 8.3a 1.0Scaled ranka 2.5 7.0 8.0 11.5 15.0 14.0 9.0 aDifferent letters following means indicate a significant difference at P = 0.05. b Wetlands with similar mean ranks were assigned similar scaled ranks.
288
Table 8. Summary of parameters including general structure and intraset correlation coefficients for all environmental
variables in the canonical correspondence analysis of all avian species abundance within all wetlands (n = 15) and for
mitigation wetlands only (n = 11) in West Virginia, 2001-2002.
Axis 1 Axis 2 Axis 3 General structure All wetlands Mitigation only All wetlands Mitigation only All wetlandsMitigation onlyEigenvalue 0.191 0.279 0.110 0.211 0.097 0.137 Monte Carlo Test result (P valuea) 0.841 0.764 0.907 0.391 0.415 0.255 % Variance explained 12.1 21.4 6.9 16.2 6.1 10.6 Predictor variables (correlation coefficients) Size 0.800 0.651 0.303 Age 0.163 -0.317 -0.706 % Emergent vegetation -0.503 -0.091 -0.526 -0.219 -0.053 0.61 Vegetation diversity 0.367 -0.325 -0.627 -0.720 0.209 0.173 % Open water 0.689 -0.031 0.312 0.439 0.442 -0.477 Benthic invertebrate diversity -0.736 -0.149 0.032 -0.176 -0.053 -0.175 Nektonic invertebrate diversity 0.395 -0.211 -0.152 0.668 -0.413 0.074 a P = proportion of randomized runs with eigenvalue greater than or equal to the observed eigenvalue [i.e., P = (1 + no. permutations >= observed)/(1 + no. permutations)].
289
Table 9. Summary of parameters including general structure and intraset correlation
coefficients for all environmental variables in the canonical correspondence analysis
of waterbird species abundance within 11 mitigation and 4 reference wetlands in
West Virginia, 2001-2002.
General structure Axis 1 Axis 2 Axis 3 Eigenvalue 0.265 0.082 0.057 Monte Carlo Test result (P valuea) 0.570 0.622 0.170 % Variance explained 23.5 30.8 35.9 Predictor variables (correlation coefficients) % Emergent vegetation 0.629 -0.030 0.419 Vegetation diversity 0.728 0.402 -0.281 % Open water -0.307 -0.186 -0.340 Benthic invertebrate diversity 0.018 -0.178 -0.636 Nektonic invertebrate diversity 0.393 -0.888 0.147 a P = proportion of randomized runs with eigenvalue greater than or equal to the observed eigenvalue [i.e., P = (1 + no. permutations >= observed)/(1 + no. permutations)].
290
Table 10. Summary of parameters including general structure and intraset correlation coefficients for all environmental
variables in the canonical correspondence analysis of anuran species abundance within all wetlands (n = 15) and for mitigation
wetlands only (n = 11) in West Virginia, 2001-2002.
Axis 1 Axis 2 Axis 3 General structure All wetlands Mitigation only All wetlands Mitigation only All wetlands Mitigation only Eigenvalue 0.040 0.088 0.025 0.048 0.016 0.030 Monte Carlo Test result (P valuea) 0.843 0.819 0.307 0.390 0.057 0.036 % Variance explained 15.0 32.2 9.5 17.5 6.2 11.0 Predictor variables (correlation coefficients) Size 0.234 -0.167 0.339 Age -0.327 -0.374 -0.571 % Emergent vegetation -0.273 -0.003 -0.244 -0.365 0.115 0.382 Vegetation diversity 0.092 0.154 -0.564 -0.597 0.66 -0.071 % Open water 0.564 0.048 0.295 0.621 0.303 -0.229 Benthic invertebrate diversity 0.211 -0.71 -0.478 -0.282 -0.677 -0.219 Nektonic invertebrate diversity 0.814 -0.433 0.106 -0.514 -0.230 -0.253 a P = proportion of randomized runs with eigenvalue greater than or equal to the observed eigenvalue [i.e., P = (1 + no. permutations >= observed)/(1 + no. permutations)].
291
Table 11. Summary of parameters including general structure and intraset correlation coefficients for all environmental
variables in the canonical correspondence analysis of benthic invertebrate familial abundance within all wetlands (n = 15) and
for mitigation wetlands only (n = 11) in West Virginia, 2001-2002.
Axis 1 Axis 2 Axis 3 General structure All wetlands Mitigation only All wetlands Mitigation only All wetlands Mitigation only Eigenvalue 0.292 0.332 0.099 0.178 0.063 0.056 Monte Carlo Test result (P valuea) 0.413 0.116 0.131 0.035 0.032 0.547 % Variance explained 27.0 36.5 9.1 19.6 5.8 6.2 Predictor variables (correlation coefficients) Size 0.628 0.353 -0.291 Age -0.263 -0.823 -0.246 % Emergent vegetation -0.717 -0.548 -0.641 0.292 0.190 0.271 Vegetation diversity 0.544 -0.397 0.084 -0.363 0.281 -0.133 % Submergent vegetation 0.266 0.735 0.772 -0.573 -0.486 -0.095 % Open water 0.522 0.758 0.814 -0.225 -0.124 -0.091 a P = proportion of randomized runs with eigenvalue greater than or equal to the observed eigenvalue [i.e., P = (1 + no. permutations >= observed)/(1 + no. permutations)].
292
Table 12. Summary of parameters including general structure and intraset correlation coefficients for all environmental
variables in the canonical correspondence analysis of nektonic invertebrate familial abundance within all wetlands (n = 15) and
for mitigation wetlands only (n = 11) in West Virginia, 2001-2002.
Axis 1 Axis 2 Axis 3 General structure All wetlands Mitigation only All wetlands Mitigation only All wetlands Mitigation only Eigenvalue 0.350 0.458 0.200 0.247 0.106 0.185 Monte Carlo Test result (P valuea) 0.089 0.126 0.141 0.563 0.338 0.289 % Variance explained 18.2 26.8 10.3 14.5 5.5 10.8 Predictor variables (correlation coefficients) Size 0.396 0.641 -0.578 Age -0.661 -0.142 -0.537 % Emergent vegetation -0.037 -0.060 -0.494 0.116 0.730 -0.128 Vegetation diversity 0.395 -0.499 0.665 -0.008 -0.289 0.414 % Submergent vegetation -0.566 0.504 0.314 -0.515 -0.761 -0.005 % Open water -0.367 0.425 -0.282 -0.278 0.328 0.426 a P = proportion of randomized runs with eigenvalue greater than or equal to the observed eigenvalue [i.e., P = (1 + no. permutations >= observed)/(1 + no. permutations)].
293
Table 13. Species codes and common names of all avian and waterbird species
included in canonical correspondence analysis of 11 mitigation and 4 reference
wetlands in West Virginia, 2001-2002.
Code Common name Code Common name acfl Acadian flycatcher gwwa Green-winged warbler alfl Alder flycatcher howr House wren amcr American crow inbu Indigo bunting amgo American goldfinch kill Killdeer amre American redstart mall Mallard amro American robin mawa Magnolia warbler baor Baltimore oriole modo Mourning dove bars Barn swallow noca Northern cardinal bcch Black-capped chickadee nofl Northern flicker beki Belted kingfisher nomo Northern mockingbird bggn Blue-gray knatcatcher oven Ovenbird blja Blue jay piwo Pileated woodpecker brcr Brown creeper rbwo Red-bellied woodpecker brth Brown thrasher revi Red-eyed vireo bwwa Blue-winged warbler rthu Ruby-throated hummingbird cago Canada goose rwbl Red-winged blackbird cawr Carolina wren rwsw Northern rough-winged swallowcewx Cedar waxwing sasp Savannah sparrow chsp Chipping sparrow scta Scarlet tanager chsw Chimney swift sosp Song sparrow cogr Common grackle spsa Spotted sandpiper coye Common yellowthroat swsp Swamp sparrow deju Dark-eyed junco tres Tree swallow dowo Downy woodpecker tuti Tufted titmouse eaki Eastern kingbird wavi Warbling vireo eaph Eastern phoebe wbnu White-breasted nuthatch eato Eastern towhee wevi White-eyed vireo eust European starling wifl Willow flycatcher fisp Field sparrow wodu Wood duck gcfl Great crested flycatcher woth Wood thrush grca Gray catbird ytvi Yellow-throated vireo grhe Green heron ytwa Yellow-throated warbler gtbh Great blue heron ywar Yellow warbler
294
Table 14. Species codes and common names of 7 anuran species included in
canonical correspondence analysis of 11 mitigation and 4 reference wetlands in West
Virginia, 2001-2002.
Code Common name ambu American bullfrog amto American toad grat Gray treefrog grfr Green frog nspe Spring peeper pifr Pickerel frog wofr Wood frog
295
Table 15. Species codes and common names of benthic and nektonic invertebrates
included in canonical correspondence analysis of 11 mitigation and 4 reference
wetlands in West Virginia, 2001-2002.
Code Family Code Family aeshn Aeshnidae hebr Hebridae aphi Aphididae helo Helodidae arach Arachnid 2 hydra Hydracarina asell Asellidae hydro Hydrometridae baet Baetidae hydrop Hydrophilidae belo Belostomatidae isot Isotomidae brac Braconidae lest Lestidae caen Caenidae libel Libellulidae caeni Caenidae lymn Lymnaedae cerat Ceratopogonidae merm Mermithidae chao Chaobaridae meso Mesoveliidae chir Chironomidae nauc Naucoridae chryso Chrysomelidae nemat Nematoda clad Cladocera noter Noteridae coen Coenagrionidae noto Notonectidae conch Conchostraca olig Oligochaeta cordu Cordulegastridae phys Physidae cordul Corduliidae plan Planorbidae corix Corixidae podu Poduridae culic Culicidae pomat Pomatiopsidae cycl Cyclopoida proto Protoneuridae delph Delphacidae pyral Pyralidae dixi Dixidae salid Saldidae dytis Dytiscidae sciom Sciomyzidae elmi Elmidae siph Siphlonuridae empid Empididae sisur Sisuridae ephy Ephydridae sphae Sphaeriidae erpob Erpobdellidae strati Stratiomyidae gam Gammaridae taba Tabanidae gerr Gerridae taban Tabanidae glos Glossiphoniidae tal Talitridae hali Haliplidae tipul Tipulidae
296
Table 15. Continued. Code Family union Unionidae unk1 Unknown 1 unk2 Unknown 2 valv Valvatidae veli Veliidae vivi Viviparidae
297
CHAPTER V
FIGURES
298
gtbh
grhe
cago
wodu
mall
killspsa
modo
chsw
rthu
beki
rbwo
dowo
nofl
piwo
acfl
alfl
wifl
eaph
gcfl
eaki
wevi
ytvi
wavi
revi
blja
amcr
tres
rwsw
bars
bcch
tuti
brcr
wbnu
cawr
howr
bggn
woth
amro
grca
nomo
brth
eust
cewx
bwwa
gwwa ywar
mawa
ytwa
amre
oven
coye
scta
eato
chsp
fisp
sosp
sasp
swsp
deju
noca
inbu
rwbl
cogr
baor
amgo
emvegvegh
open
invertbh
invertnh
Axis 1
Axis
2
Figure 1. Canonical correspondence analysis ordination of all avian species on 11
mitigation and 4 reference wetlands in West Virginia, 2001-2002, based on 5
environmental variables: open = % open water; emveg = % emergent vegetation;
vegh = vegetation diversity; invertbh = invertebrate benthic diversity; invertnh =
invertebrate nektonic diversity. The angle of the vectors with the axes is indicative of
their correlation with the axes where vectors that are parallel with an axis are
correlated and those that are perpendicular are uncorrelated. The length of vectors is
proportional to the relationship between that variable and avian community
composition. Species codes are defined in Table 13.
299
gtbh
grhe
cago
wodu
mall
kill
spsa
modo
chsw
rthu
beki
rbwo
dowo
nofl
piwo
acfl
alfl
wifl
eaph
gcfl
eaki
wevi
ytvi
wavi
reviblja
amcr
tres
rwsw
bars
bcch
tuti
wbnu
cawr
howr
bggn
woth
amro
grca
nomo
brth
eust
cewx
bwwa
ywar
mawa
ytwa
amre
coye
scta
eato
chsp fisp
sosp
sasp
swsp
deju
noca
inbu
rwbl
cogr
baor
amgosize
vegh
open
invertnh
Axis 1
Axis
2
Figure 2. Canonical correspondence analysis ordination of all avian species on 11
mitigation wetlands in West Virginia, 2001-2002, based on 7 environmental
variables: age, size, open = % open water; emveg = % emergent vegetation; vegh =
vegetation diversity; invertbh = invertebrate benthic diversity; invertnh = invertebrate
nektonic diversity. The angle of the vectors with the axes is indicative of their
correlation with the axes where vectors that are parallel with an axis are correlated
and those that are perpendicular are uncorrelated. The length of vectors is
proportional to the relationship between that variable and avian community
composition. Species codes are defined in Table 13.
300
gtbh
grhe
cago
wodu
mall
spsa
beki
vegh
invertnh
Axis 1
Axis
2
Figure 3. Canonical correspondence analysis ordination of all waterbird species on
11 mitigation wetlands in West Virginia, 2001-2002, based on 7 environmental
variables: age, size, open = % open water; emveg = % emergent vegetation; vegh =
vegetation diversity; invertbh = invertebrate benthic diversity; invertnh = invertebrate
nektonic diversity. The angle of the vectors with the axes is indicative of their
correlation with the axes where vectors that are parallel with an axis are correlated
and those that are perpendicular are uncorrelated. The length of vectors is
proportional to the relationship between that variable and waterbird community
composition. Species codes are defined in Table 13.
301
nspe
grat
ambu
wofr
grfr
amto
pifr
vegh
open
invertbh
invertnh
Axis 1
Axis
2
Figure 4. Canonical correspondence analysis ordination of all anuran species on 11
mitigation and 4 reference wetlands in West Virginia, 2001-2002, based on 5
environmental variables: open = % open water; emveg = % emergent vegetation;
vegh = vegetation diversity; invertbh = invertebrate benthic diversity; invertnh =
invertebrate nektonic diversity. The angle of the vectors with the axes is indicative of
their correlation with the axes where vectors that are parallel with an axis are
correlated and those that are perpendicular are uncorrelated. The length of vectors is
proportional to the relationship between that variable and avian community
composition. Species codes are defined in Table 14.
302
nspe
gratambu
wofr
grfr
amto pifr
vegh
open
invertbh
invertnh
Axis 1
Axis
2
Figure 5. Canonical correspondence analysis ordination of all anuran species on 11
mitigation wetlands in West Virginia, 2001-2002, based on 7 environmental
variables: age, size, open = % open water; emveg = % emergent vegetation; vegh =
vegetation diversity; invertbh = invertebrate benthic diversity; invertnh = invertebrate
nektonic diversity. The angle of the vectors with the axes is indicative of their
correlation with the axes where vectors that are parallel with an axis are correlated
and those that are perpendicular are uncorrelated. The length of vectors is
proportional to the relationship between that variable and anuran community
composition. Species codes are defined in Table 14.
303
gamm
chryso
elmi
unk1
cerat
chironculici
empid
ephyr
strati
taban
tipul
unk2
caeni
lymn
phys
plan
pomatvalv
vivip
erpobmerm
nemat
cordul
libell
oliga
sphaeunion
emveg
opensubm
Axis 1Ax
is 2
Figure 6. Canonical correspondence analysis ordination of benthic invertebrate
families on 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002,
based on 4 environmental variables: open = % open water; emveg = % emergent
vegetation; subm = % submergent vegetation; vegh = vegetation diversity. The angle
of the vectors with the axes is indicative of their correlation with the axes where
vectors that are parallel with an axis are correlated and those that are perpendicular
are uncorrelated. The length of vectors is proportional to the relationship between
that variable and invertebrate community composition. Species codes are defined in
Table 15.
304
chryso
elmi
unk1
cerat
chiron
culici
empid
ephyr
taban
tipul
unk2
caeni
lymn
phys
plan
valv
vivip
nemat
cordul
libell
oliga
sphae
union
age
emveg
open
subm
Axis 1
Axis
2
Figure 7. Canonical correspondence analysis ordination of benthic invertebrate
families on 11 mitigation wetlands in West Virginia, 2001-2002, based on 6
environmental variables: age, size, open = % open water; emveg = % emergent
vegetation; subm = % submergent vegetation; vegh = vegetation diversity. The angle
of the vectors with the axes is indicative of their correlation with the axes where
vectors that are parallel with an axis are correlated and those that are perpendicular
are uncorrelated. The length of vectors is proportional to the relationship between
that variable and invertebrate community composition. Species codes are defined in
Table 15.
305
gam
tal
hydra
arachclad
dytis
elmi
hali
helo
hydropnoter
isot
podu
conch
cycl
cerat
chao
chirculic
dixi
ephy
sciom
taba
baet
caen
siph
lymn
phys
plan
vivi
aphi
belo
corix
delphgerr
hebr
hydro
meso
nauc
noto
salid
veliglos
brac
asell
pyral
sisur
aeshn
coen
cordu
cordul
lest
libel
proto
olig
sphae
veghopen
subm
Axis 1Ax
is 2
Figure 8. Canonical correspondence analysis ordination of nektonic invertebrate
families on 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002,
based on 4 environmental variables: open = % open water; emveg = % emergent
vegetation; subm = % submergent vegetation; vegh = vegetation diversity. The angle
of the vectors with the axes is indicative of their correlation with the axes where
vectors that are parallel with an axis are correlated and those that are perpendicular
are uncorrelated. The length of vectors is proportional to the relationship between
that variable and invertebrate community composition. Species codes are defined in
Table 15.
306
tal
hydra
arach
clad
dytis
elmihali
helo
hydrop
noter
isot
podu
conch
cycl
cerat
chao
chir
culic
dixi
sciom
taba
baet
caen
siph
lymn
phys
plan
viviaphi
belo
corix
gerr
hebr
hydro meso
nauc
noto
salid
veli
glos
brac
asell
pyral
aeshn
coen
cordu
cordul
lest
libel
proto
olig
sphae
size
age
vegh
subm
Axis 1Ax
is 2
Figure 9. Canonical correspondence analysis ordination of nektonic invertebrate
families on 11 mitigation wetlands in West Virginia, 2001-2002, based on 6
environmental variables: age, size, open = % open water; emveg = % emergent
vegetation; subm = % submergent vegetation; vegh = vegetation diversity. The angle
of the vectors with the axes is indicative of their correlation with the axes where
vectors that are parallel with an axis are correlated and those that are perpendicular
are uncorrelated. The length of vectors is proportional to the relationship between
that variable and invertebrate community composition. Species codes are defined in
Table 15.
307
APPENDICES
308
Appendix 1. Average percent cover/1.0 m2 quadrat of all herbaceous vegetation
species sampled in 11 mitigation (n = 45) and 4 reference (n = 15) wetlands in West
Virginia, 2001-2002.
Mitigation Reference Species x SE x SE Agrimonia gryposepala 0.19 0.17 0.32 0.32 Agrostis gigantea 0.40 0.15 0.00 0.00 Agrostis hyemalis 0.00 0.00 0.02 0.02 Allium cernuum var. cernuum 0.01 0.01 0.00 0.00 Ambrosia artemisifolia 0.09 0.05 0.00 0.00 Andropogon virginicus var. virginicus 0.07 0.05 0.00 0.00 Antennaria solitaria 0.01 0.01 0.00 0.00 Anthoxanthum odoratum ssp. odoratum 0.09 0.05 0.00 0.00 Apios americana 0.06 0.04 0.00 0.00 Apocynum cannabinum 0.25 0.20 0.07 0.07 Asclepias incarnata 0.06 0.03 0.00 0.00 Asclepias syriaca 0.01 0.01 0.00 0.00 Aster 1 0.01 0.01 0.00 0.00 Aster puniceus 0.00 0.00 0.02 0.02 Aster sp. 0.02 0.02 0.00 0.00 Aster umbellatus var. umbellatus 0.11 0.08 0.00 0.00 Barbarea vulgaris 0.01 0.01 0.00 0.00 Bidens frondosa 0.11 0.08 0.00 0.00 Bidens sp. 0.34 0.21 0.00 0.00 Boehmeria cylindrica 0.11 0.06 1.88 1.15 Calamagrostis canadensis var. canadensis 0.00 0.00 4.12 4.12 Caltha palustris 0.00 0.00 0.40 0.40 Cardamine rotundifolia 0.01 0.01 0.00 0.00 Carex argyrantha 0.00 0.00 0.02 0.02 Carex canescens ssp. canescens 0.03 0.03 0.57 0.57 Carex folliculata 0.01 0.01 0.27 0.27 Carex frankii 0.01 0.01 0.00 0.00 Carex gynandra 0.09 0.06 0.00 0.00 Carex intumescens 0.01 0.01 0.00 0.00 Carex lurida 0.34 0.11 0.00 0.00 Carex scoparia var. scoparia 0.56 0.18 0.35 0.30
309
Mitigation Reference Species x SE x SE Carex shortiana 0.02 0.02 0.00 0.00 Carex squarrosa 0.04 0.04 0.00 0.00 Carex stipata 0.01 0.01 0.00 0.00 Carex stricta 0.42 0.22 4.23 2.19 Carex tribuloides 0.01 0.01 0.05 0.05 Carex vulpinoidea var. vulpinoidea 0.61 0.18 0.00 0.00 Clematis virginiana 0.00 0.00 0.40 0.40 Clinopodium vulgare 0.01 0.01 0.00 0.00 Conium maculatum 0.01 0.01 0.00 0.00 Coronilla varia 0.38 0.24 0.00 0.00 Crepis capillaris 0.01 0.01 0.00 0.00 Danthonia compressa 0.03 0.03 0.17 0.12 Danthonia spicata 0.01 0.01 0.00 0.00 Daucus carota 0.02 0.02 0.00 0.00 Dichanthelium clandestinum 0.63 0.33 0.00 0.00 Dichanthelium sphaerocarpon var. sphaerocarpon 0.11 0.11 0.00 0.00 Diphasiastrum digitatum 0.01 0.01 0.00 0.00 Dipsacus fullonum ssp. sylvestris 0.39 0.39 0.00 0.00 Drosera rotundifolia var. rotundifolia 0.00 0.00 0.22 0.17 Dulichium arundinaceum 0.00 0.00 0.02 0.02 Echinochloa crus-galli var. crus-galli 0.68 0.49 0.00 0.00 Eleocharis compressa 0.01 0.01 0.00 0.00 Eleocharis obtusa 1.06 0.37 0.00 0.00 Eleocharis quadrangulata 0.27 0.27 0.00 0.00 Eleocharis tenuis var. tenuis 1.14 0.30 0.10 0.10 Epilobium coloratum 0.07 0.04 0.32 0.32 Equisetum fluviatile 0.00 0.00 0.83 0.83 Erechtites hieraciifolia var. hieraciifolia 0.04 0.03 0.00 0.00 Erigeron aureus 0.01 0.01 0.00 0.00 Eriophorum virginicum 0.00 0.00 1.03 0.80 Eupatorium coelestinum 0.01 0.01 0.00 0.00 Eupatorium fistulosum 0.08 0.07 0.00 0.00 Eupatorium maculatum var. maculatum 0.00 0.00 0.23 0.23 Eupatorium perfoliatum 0.31 0.17 0.00 0.00 Euthamia graminifolia var. graminifolia 0.41 0.19 0.00 0.00
Appendix 1. Continued.
310
Mitigation Reference Species x SE x SE Galium aparine 0.01 0.01 0.00 0.00 Galium mollugo 0.22 0.11 0.72 0.52 Galium obtusum ssp. obtusum 0.05 0.05 0.00 0.00 Galium tinctorium 0.91 0.24 0.97 0.40 Gaultheria procumbens 0.00 0.00 0.05 0.05 Geum canadense var. canadense 0.01 0.01 0.00 0.00 Geum laciniatum 0.04 0.04 0.00 0.00 Geum rivale 0.00 0.00 0.33 0.33 Glyceria grandis var. grandis 0.11 0.08 0.42 0.22 Glyceria striata 0.01 0.01 0.02 0.02 Gratiola virginiana var. virginiana 0.00 0.00 0.23 0.23 Helenium autumnale 0.04 0.04 0.00 0.00 Heteranthera reniformis 0.21 0.20 0.00 0.00 Holcus lanatus 0.01 0.01 0.00 0.00 Hypericum mutilum 0.36 0.15 0.00 0.00 Hypericum punctatum 0.01 0.01 0.00 0.00 Impatiens capensis 0.71 0.31 2.13 1.36 Impatiens pallida 0.00 0.00 3.30 2.32 Iris pseudacorus 0.10 0.10 0.00 0.00 Juncus acuminatus 0.06 0.06 0.00 0.00 Juncus balticus 0.00 0.00 1.30 1.02 Juncus brachycarpus 0.01 0.01 0.00 0.00 Juncus brevicaudatus 0.36 0.24 0.10 0.10 Juncus effusus var. effusus 4.82 0.73 0.25 0.16 Juncus secundus 0.01 0.01 0.00 0.00 Juncus subcaudatus var. subcaudatus 0.41 0.12 0.05 0.05 Juncus tenuis 0.71 0.33 0.00 0.00 Leersia oryzoides 2.64 1.03 2.85 2.08 Lemna minor 0.29 0.15 0.00 0.00 Lespedeza cuneata 0.19 0.18 0.00 0.00 Leucanthemum vulgare 0.04 0.03 0.00 0.00 Linum medium 0.01 0.01 0.00 0.00 Lonicera japonica 0.01 0.01 0.00 0.00 Ludwigia alternifolia 0.16 0.09 0.00 0.00 Ludwigia palustris 2.07 0.52 0.38 0.21 Lycopodium clavatum var. clavatum 0.00 0.00 0.13 0.13 Lycopodium obscurum 0.00 0.00 0.60 0.60 Lycopus americanus 0.02 0.01 0.00 0.00
Appendix 1. Continued.
311
Mitigation Reference Species x SE x SE Lycopus uniflorus var. uniflorus 0.33 0.13 0.00 0.00 Lycopus virginicus 0.07 0.05 0.50 0.47 Lysimachia nummularia 0.17 0.11 0.00 0.00 Lythrum salicaria 1.52 0.94 0.00 0.00 Mimulus ringens var. ringens 0.27 0.12 0.35 0.26 Myosotis scorpioides 0.23 0.16 0.00 0.00 Onoclea sensibilis 0.16 0.11 0.10 0.10 Oxalis stricta 0.08 0.04 0.02 0.02 Panicum microcarpon 0.04 0.04 0.00 0.00 Panicum rigidulum var. rigidulum 0.43 0.15 0.00 0.00 Panicum virgatum var. virgatum 0.67 0.28 0.00 0.00 Phalaris arundinacea 6.99 2.71 0.00 0.00 Plantago lanceolata 0.13 0.06 0.00 0.00 Platanthera lacera var. lacera 0.02 0.01 0.00 0.00 Poa alsodes 0.02 0.02 0.00 0.00 Polygonum amphibium 0.02 0.01 0.00 0.00 Polygonum hydropiper 0.11 0.07 0.00 0.00 Polygonum hydropiperoides 1.59 1.09 0.03 0.02 Polygonum lapathifolium 0.10 0.10 0.00 0.00 Polygonum punctatum 0.06 0.04 0.02 0.02 Polygonum sagittatum 0.27 0.13 1.68 0.95 Polygonum scandens 0.00 0.00 0.02 0.02 Polygonum tenue var. tenue 0.03 0.03 0.00 0.00 Potamogeton spirillus 0.18 0.17 0.00 0.00 Potentilla simplex 0.59 0.27 0.00 0.00 Prunella vulgaris 0.04 0.02 0.00 0.00 Pteridium aquilinium 0.03 0.03 0.77 0.53 Pycnanthemum pycnanthemoides 0.07 0.07 0.00 0.00 Rubus hispidus 0.32 0.15 3.88 1.44 Rubus sp. 0.08 0.05 0.02 0.02 Rumex acetosella 0.01 0.01 0.00 0.00 Rumex crispus 0.12 0.08 0.00 0.00 Sagittaria latifolia var. latifolia 0.03 0.02 0.47 0.43 Scirpus acutus 0.00 0.00 0.23 0.23 Scirpus americanus 0.17 0.17 0.03 0.03 Scirpus atrocinctus 0.18 0.10 0.00 0.00 Scirpus cyperinus 0.62 0.22 0.02 0.02 Scirpus expansus 0.01 0.01 0.00 0.00
Appendix 1. Continued.
312
Mitigation Reference Species x SE x SE Scutellaria galericulata 0.00 0.00 0.07 0.07 Scutellaria lateriflora var. lateriflora 0.01 0.01 0.00 0.00 Selaginella apoda 0.01 0.01 0.00 0.00 Senecio aureus 0.05 0.04 0.00 0.00 Setaria faberi 0.01 0.01 0.00 0.00 Setaria glauca 0.01 0.01 0.00 0.00 Sisyrinchium angustifolium 0.18 0.13 0.00 0.00 Solanum carolinense var. carolinense 0.11 0.06 0.00 0.00 Solidago canadensis var. canadensis 0.17 0.17 1.53 1.53 Solidago rugosa ssp. rugosa 0.07 0.03 0.00 0.00 Solidago sp. 0.03 0.03 0.12 0.12 Solidago tall 0.17 0.17 0.00 0.00 Solidago uliginosa var. uliginosa 0.21 0.12 1.00 0.67 Sparganium americanum 0.26 0.24 1.25 1.25 Spirodela polyrrhiza 0.13 0.12 0.00 0.00 Teucrium canadense var. canadense 0.02 0.02 0.00 0.00 Thelypteris palustris var. pubescens 0.00 0.00 3.97 2.98 Toxicodendron radicans ssp. radicans 0.01 0.01 0.00 0.00 Triadenum virginicum 0.11 0.05 0.05 0.05 Trifolium arvense 0.02 0.01 0.00 0.00 Trifolium campestre 0.03 0.02 0.00 0.00 Trifolium pratense 0.16 0.13 0.00 0.00 Trifolium repens 0.17 0.13 0.00 0.00 Typha augustifolia 0.08 0.08 0.00 0.00 Typha latifolia 1.27 0.70 6.82 3.84 Vaccinium oxycoccos 0.04 0.04 0.00 0.00 Verbesina alternifolia 0.17 0.12 0.12 0.12 Vernonia noveboracensis 0.14 0.08 0.00 0.00 Viola cucullata 0.01 0.01 0.12 0.08 Viola macloskeyi ssp. pallens 0.05 0.04 0.00 0.00 Viola sororia 0.14 0.11 0.00 0.00 Viola sp. 0.02 0.01 0.00 0.00 Wolffia brasiliensis 0.24 0.24 0.00 0.00
Appendix 1. Continued.
313
Appendix 2. Species list, origin (O), and average cover (AC) per 0.05 ha plot of all
herbaceous vegetation species sampled, and vegetation species that were seen but not
sampled (SBNS) per plot at the Walnut Bottom mitigation wetland, 2001-2002.
Plot Species O AC Plot Species O AC
1 Agrostis gigantea N 1.5 4 Mimulus ringens var. ringens N 0.3
1 Phalaris arundinacea N 29.5 4 Scirpus cyperinus N 0.5 1 Polygonum hydropiper N 3.0 4 Typha latifolia N 6.8 1 Scirpus atrovirens N 3.8 SBNS 2 Agrostis gigantea N 0.3 Ambrosia artemisifolia N 2 Barbarea vulgaris E 0.3 Bidens sp. 2 Bidens sp. N 8.3 Carex frankii N 2 Carex frankii N 0.3 Carex vulpinoidea N 2 Echinochloa crus-galli var. crus-galli N 5.8 Cyperus strigosus N 2 Eleocharis obtusa N 1.8 Epilobium coloratum N 2 Erigeron aureus N 0.3 Erechtites hieraciifolia N 2 Iris pseudacorus E 4.5 Erigeron annuus N 2 Juncus tenuis N 3.5 Eupatorium perfoliatum N 2 Lycopus americanus N 0.3 Juncus effusus N 2 Mimulus ringens var. ringens N 0.3 Juncus marginatus N 2 Panicum virgatum var. virgatum N 7.0 Juncus subcaudatus N 2 Polygonum hydropiper N 0.8 Ludwigia palustris N 2 Polygonum tenue var. tenue N 1.5 Lycopus americana N 2 Rumex crispus E 3.3 Panicum virgatum N 3 Artemisia annua N 0.3 Penthorum sedoides N 3 Bidens sp. N 4.8 Polygonum tenue N 3 Carex folliculata N 0.3 Rumex crispus E 3 Carex vulpinoidea var. vulpinoidea N 1.8 Scirpus atrovirens N 3 Echinochloa crus-galli var. crus-galli N 21.5 Scirpus tabernaemontani N 3 Eleocharis obtusa N 6.0 Typha latifolia N 3 Epilobium coloratum N 1.8 Verbena hastata N 3 Juncus tenuis N 0.3 Verbena urticifolia N 3 Polygonum hydropiperoides N 2.0 3 Rumex crispus E 2.0 4 Agrostis gigantea N 3.0 4 Bidens sp. N 2.0 4 Eleocharis obtusa N 4.8 4 Juncus effusus var. effusus N 1.5 4 Juncus subcaudatus var. subcaudatus N 1.8 4 Lemna minor N 14.3 4 Ludwigia palustris N 5.0
aN = species is native to West Virginia, E = exotic species not native to West Virginia (Harmon and Ford-Werntz 2002)
314
Appendix 3. Species list, origin (O), and average cover (AC) per 0.05 ha plot of all
herbaceous vegetation species sampled, and vegetation species that were seen but not
sampled (SBNS) per plot at the VEPCO mitigation wetland, 2001-2002.
Plot Species Oa AC Plot Species Oa AC
1 Aster umbellatus var. umbellatus N 0.3 3 Carex gynandra N 2.3 1 Carex lurida N 0.3 3 Carex scoparia var. scoparia N 5.0 1 Carex lurida N 0.3 3 Euthamia graminifolia var. graminifolia N 0.5 1 Carex scoparia var. scoparia N 1.0 3 Galium mollugo E 2.5 1 Dichanthelium clandestinum N 0.5 3 Hypericum mutilum N 0.3 1 Euthamia graminifolia var. graminifolia N 1.5 3 Juncus brevicaudatus N 1.5 1 Galium tinctorium N 0.3 3 Juncus effusus var. effusus N 7.5 1 Glyceria canadensis N 0.3 3 Lycopus uniflorus var. uniflorus N 0.3 1 Hypericum mutilum N 2.3 3 Rubus hispidus N 1.5 1 Impatiens capensis N 0.3 3 Solidago uliginosa var. uliginosa N 0.3 1 Juncus brevicaudatus N 3.8 3 Triadenum virginicum N 0.5 1 Juncus effusus var. effusus N 7.5 3 Vernonia noveboracensis N 1.8 1 Juncus subcaudatus var. subcaudatus N 1.8 3 Viola macloskeyi ssp. pallens N 2.0 1 Juncus tenuis N 1.8 4 Carex gynandra N 1.8 1 Leersia oryzoides N 0.3 4 Carex scoparia var. scoparia N 0.8 1 Lycopus uniflorus var. uniflorus N 3.5 4 Dichanthelium clandestinum N 0.3 1 Scirpus atrocinctus N 1.5 4 Eleocharis tenuis var. tenuis N 5.0 1 Solidago incana ssp. incana N 0.5 4 Euthamia graminifolia var. graminifolia N 0.3 1 Solidago uliginosa var. uliginosa N 0.8 4 Galium mollugo E 2.0 1 Triadenum virginicum N 1.0 4 Juncus brevicaudatus N 10.31 Viola macloskeyi ssp. pallens N 0.3 4 Juncus effusus var. effusus N 6.3 2 Agrostis gigantea N 0.3 4 Leersia oryzoides N 1.5 2 Aster umbellatus var. umbellatus N 0.5 4 Lycopus uniflorus var. uniflorus N 2.0 2 Carex gynandra N 0.3 4 Rubus hispidus N 0.5 2 Carex lurida N 0.5 4 Solidago uliginosa var. uliginosa N 2.3 2 Carex scoparia var. scoparia N 3.5 4 Vaccinium oxycoccos N 1.8 2 Eleocharis compressa N 0.3 SBNS 2 Euthamia graminifolia var. graminifolia N 5.0 Aronia melanocarpa N 2 Galium tinctorium N 0.5 Carex gynandra N 2 Hypericum mutilum N 2.0 Coronilla varia E 2 Juncus acuminatus N 2.5 Danthonia compressa N 2 Juncus effusus var. effusus N 5.0 Drosera rotundifolia N 2 Juncus subcaudatus var. subcaudatus N 2.0 Eupatorium perfoliatum N 2 Lycopus uniflorus var. uniflorus N 1.0 Eupatorium pilosum N 2 Solidago incana ssp. incana N 1.0 Glyceria grandis N 2 Solidago uliginosa var. uliginosa N 0.5 Hypericum densiflorum N 2 Triadenum virginicum N 0.8 Hypericum mutilum N
315
Appendix 3. Continued.
SBNS continued Oa
Impatiens capensis N Leucanthemum vulgare E Onoclea sensibilis N Osmunda cinnamomea N Prunella vulgaris N Rosa multiflora E Rubus hispidus N Scirpus atrocinctus N Scirpus cyperinus N Scirpus tabernaemontani N Solidago incana N Veronia noveboracensis N aN = species is native to West Virginia, E = exotic species not native to West Virginia (Harmon and
Ford-Werntz 2002)
316
Appendix 4. Species list, origin (O), and average cover (AC) per 0.05 ha plot of all
herbaceous vegetation species sampled, and vegetation species that were seen but not
sampled (SBNS) per plot at the Buffalo Coal mitigation wetland, 2001-2002.
Plot Species O AC Species O
1 Aster umbellatus var. umbellatus N 3.8 SBNS 1 Carex scoparia var. scoparia N 0.5 Acer rubrum N 1 Carex stricta N 4.5 Carex lurida N 1 Danthonia compressa N 1.5 Carex lurida N 1 Diphasiastrum digitatum N 0.3 Glyceria grandis N 1 Juncus effusus var. effusus N 12.0 Hypericum mutilum N 1 Potentilla simplex N 1.8 Juncus subcaudatus N 1 Rubus hispidus N 1.8 Lycopus uniflora N 1 Solidago uliginosa var. uliginosa N 5.0 Polygala cruciata N 2 Carex canescens ssp. canescens N 1.5 Solidago rugosa N 2 Carex scoparia var. scoparia N 0.8 Solidago uliginosa N 2 Carex stricta N 7.5 Sparganium americanum N 2 Galium mollugo E 3.8 2 Glyceria canadensis N 1.5 2 Juncus effusus var. effusus N 7.5 2 Phalaris arundinacea N 3.8 2 Scirpus atrocinctus N 0.3 2 Triadenum virginicum N 1.8 3 Carex scoparia var. scoparia N 0.5 3 Carex stricta N 3.8 3 Galium tinctorium N 0.3 3 Juncus brevicaudatus N 0.3 3 Juncus effusus var. effusus N 6.3 3 Juncus subcaudatus var. subcaudatus N 0.3 3 Phalaris arundinacea N 0.3 3 Rubus hispidus N 0.3 3 Scirpus expansus N 0.3 3 Solidago uliginosa var. uliginosa N 0.5 3 Triadenum virginicum N 0.3 3 Viola cucullata N 0.3
aN = species is native to West Virginia, E = exotic species not native to West Virginia (Harmon and
Ford-Werntz 2002)
317
Appendix 5. Species list, origin (O), and average cover (AC) per 0.05 ha plot of all
herbaceous vegetation species sampled, and vegetation species that were seen but not
sampled (SBNS) per plot at the Elk Run mitigation wetland, 2001-2002.
Plot Species Oa AC 1 Carex lurida N 0.8
1 Carex scoparia N 2.0
1 Carex vulpinoidea 0.5
1 Eleocharis tenuis N 0.5
1 Eupatorium perfoliatum N 1.8
1 Galium mollugo E 1.8
1 Galium tinctorium N 1.0
1 Glyceria grandis N 3.5
1 Juncus effusus N 0.5
1 Leersia oryzoides N 11.8
1 Lycopus uniflorus N 0.5
1 Onoclea sensibilis N 3.8
1 Polygonum sagittatum N 0.3
1 Scirpus atrocinctus N 1.8
1 Sparganium americanum N 0.3
1 Triadenum virginicum N 0.5
1 Typha latifolia N 0.3
SBNS Agrostis hyemalis N Aster sp. Epilobium coloratum N Impatiens capensis N Mimulus ringens N Scutellaria laterifolia N aN = species is native to West Virginia, E = exotic species not native to West Virginia (Harmon and
Ford-Werntz 2002)
318
Appendix 6. Species list, origin (O), and average cover (AC) per 0.05 ha plot of all
herbaceous vegetation species sampled, and vegetation species that were seen but not
sampled (SBNS) per plot at the Leading Creek mitigation wetland, 2001-2002.
Plot Species Oa AC1 Agrostis gigantea N 0.8
1 Anthoxanthum odoratum ssp. odoratum E 0.3
1 Artemisia annua N 0.5
1 Asclepias incarnata N 0.3
1 Aster umbellatus var. umbellatus N 0.5
1 Carex vulpinoidea var. vulpinoidea N 3.0
1 Coronilla varia E 1.8
1 Dichanthelium clandestinum N 3.0
1 Dichanthelium clandestinum N 0.3
1 Dichanthelium sphaerocarpon var. sphaerocarpon N 5.0
1 Eleocharis tenuis var. tenuis N 0.5
1 Impatiens capensis N 0.5
1 Juncus effusus var. effusus N 3.3
1 Juncus tenuis N 1.8
1 Lonicera japonica N 0.5
1 Panicum virgatum var. virgatum N 6.0
1 Platanthera lacera var. lacera N 0.3
1 Potentilla simplex N 6.0
1 Prunella vulgaris N 0.5
1 Rubus hispidus N 0.3
1 Senecio aureus N 1.8
1 Solidago incana ssp. incana N 0.8
1 Solidago sp. 1.5
1 Trifolium campestre E 1.0
1 Trifolium repens E 2.0
1 Vernonia noveboracensis N 1.5
1 Viola sororia N 5.0
2 Polygonum hydropiperoides N 48.8
3 Eleocharis obtusa N 9.0
3 Heteranthera reniformis N 9.0
3 Juncus subcaudatus var. subcaudatus N 2.3
3 Leersia oryzoides N 5.0
3 Ludwigia palustris N 11.3
3 Panicum virgatum var. virgatum N 0.3
3 Polygonum hydropiperoides N 4.8
3 Potamogeton spirillus A 0.5
3 Sagittaria latifolia var. latifolia N 0.5
319
Plot Species Oa AC
4 Agrostis gigantea N 0.8
4 Apios americana N 1.5
4 Boehmeria cylindrica N 0.5
4 Carex lurida N 2.3
4 Carex scoparia var. scoparia N 2.0
4 Carex stricta N 3.0
4 Carex vulpinoidea var. vulpinoidea N 1.8
4 Dichanthelium clandestinum N 1.5
4 Eleocharis tenuis var. tenuis N 2.3
4 Eupatorium perfoliatum N 5.0
4 Euthamia graminifolia var. graminifolia N 0.5
4 Galium tinctorium N 0.5
4 Hypericum mutilum N 0.3
4 Impatiens capensis N 0.8
4 Juncus effusus var. effusus N 12.3
4 Oxalis stricta N 1.0
4 Panicum rigidulum var. rigidulum N 3.5
4 Platanthera lacera var. lacera N 0.3
4 Polygonum sagittatum N 2.3
4 Potentilla simplex N 4.5
4 Rubus sp. 1.5
4 Scutellaria lateriflora var. lateriflora N 0.3
4 Sisyrinchium angustifolium N 0.3
4 Toxicodendron radicans ssp. radicans N 1.5
4 Viola sororia N 0.5
5 Bidens sp. N 0.5
5 Carex intumescens N 0.3
5 Carex scoparia var. scoparia N 0.8
5 Carex tribuloides N 0.3
5 Carex vulpinoidea var. vulpinoidea N 0.5
5 Eleocharis obtusa N 0.3
5 Eleocharis tenuis var. tenuis N 9.8
5 Eupatorium perfoliatum N 0.8
5 Galium tinctorium N 3.8
5 Juncus effusus var. effusus N 9.8
5 Juncus subcaudatus var. subcaudatus N 1.5
5 Leersia oryzoides N 5.0
5 Ludwigia palustris N 0.0
5 Lycopus uniflorus var. uniflorus N 0.3
5 Panicum microcarpon N 1.8
5 Polygonum hydropiperoides N 4.8
5 Sagittaria latifolia var. latifolia N 0.5
Appendix 6. Continued.
320
Plot Species Oa AC
5 Scirpus cyperinus N 2.3
5 Viola sororia N 0.3
6 Eleocharis obtusa N 9.8
6 Leersia oryzoides N 6.3
6 Ludwigia palustris N 4.5
7 Agrostis gigantea N 0.3
7 Carex vulpinoidea var. vulpinoidea N 1.5
7 Eleocharis tenuis var. borealis N 6.0
7 Epilobium coloratum N 0.5
7 Eupatorium perfoliatum N 0.3
7 Galium tinctorium N 2.3
7 Heteranthera reniformis N 0.3
7 Hypericum mutilum N 0.5
7 Juncus effusus var. effusus N 9.8
7 Juncus subcaudatus var. subcaudatus N 3.3
7 Juncus tenuis N 1.5
7 Leersia oryzoides N 1.0
7 Ludwigia palustris N 1.3
7 Oxalis stricta N 0.0
7 Panicum virgatum var. virgatum N 2.3
7 Polygonum hydropiperoides N 3.0
7 Scutellaria lateriflora var. lateriflora N 0.3
7 Trifolium arvense E 0.3
7 Viola cucullata N 0.3
8 Agrostis gigantea N 0.8
8 Anthoxanthum odoratum ssp. odoratum E 0.3
8 Artemisia annua N 0.5
8 Carex lurida N 3.5
8 Carex scoparia var. scoparia N 1.5
8 Carex vulpinoidea var. vulpinoidea N 4.8
8 Eleocharis tenuis var. tenuis N 5.0
8 Epilobium coloratum N 0.3
8 Erechtites hieraciifolia var. hieraciifolia N 1.5
8 Galium tinctorium N 1.8
8 Hypericum mutilum N 3.5
8 Impatiens capensis N 0.3
8 Juncus effusus var. effusus N 6.3
8 Juncus subcaudatus var. subcaudatus N 0.5
8 Leersia oryzoides N 0.5
8 Ludwigia palustris N 0.5
8 Panicum virgatum var. virgatum N 0.3
8 Plantago lanceolata E 1.8
Appendix 6. Continued.
321
Plot Species Oa AC
8 Potentilla simplex N 0.3
8 Sisyrinchium angustifolium N 0.5
8 Solanum carolinense var. carolinense N 0.3
8 Trifolium arvense E 0.5
8 Trifolium campestre E 0.3
8 Viola sp. 0.3
9 Agrostis gigantea N 3.8
9 Anthoxanthum odoratum ssp. odoratum E 2.0
9 Artemisia annua N 1.3
9 Asclepias incarnata N 0.3
9 Asclepias syriaca N 0.3 9 Carex vulpinoidea var. vulpinoidea N 4.5 9 Crepis capillaris E 0.3 9 Dichanthelium clandestinum N 0.3 9 Eupatorium fistulosum N 0.3 9 Holcus lanatus E 0.5 9 Hypericum mutilum N 0.5 9 Juncus effusus var. effusus N 0.3 9 Juncus tenuis N 2.0 9 Leucanthemum vulgare E 1.3 9 Oxalis stricta N 0.3 9 Panicum rigidulum var. rigidulum N 3.0 9 Panicum virgatum var. virgatum N 6.3 9 Plantago lanceolata E 1.3 9 Potentilla simplex N 5.3 9 Prunella vulgaris N 0.3 9 Prunella vulgaris N 0.3 9 Rumex acetosella E 0.3 9 Senecio aureus N 0.5 9 Solanum carolinense var. carolinense N 1.8 9 Solidago incana ssp. incana N 0.8 9 Trifolium pratense E 5.5 9 Trifolium repens E 4.8 9 Viola sp. 0.5
SBNS Anthoxanthum odoratum E Asclepias incarnata N Aster sp. Carex intumescens N Carex intumescens N Carex lurida N Carex scoparia N
Appendix 6. Continued.
322
Species Oa AC
Carex tribuloides N Carex vulpinoidea N Cirsium pumilum N Cornus amomum N Coronilla varia E Dichanthelium clandestinum N Dulichium arundinaceum N Eleocharis obtusa N Erigeron anuus N Eupatorium perfoliatum N Euthamia graminifolia N Galium tinctorium N Heteranthera reniformis N Holcus lanatus E Hypericum densiflorum N Hypericum mutilum N Hypericum perforatum N Impatiens capensis N Juncus effusus N Juncus subcaudatus N Juncus tenuis N Leersia oryzoides N Leucanthemum vulgare E Ludwigia alternifolia N Lycopus uniflorus N Mimulus ringens N Oxalis stricta N Polygonum sagittatum N Potamogeton spirillus A Potentilla simplex N Rosa multiflora E Rosa palustris N Rumex crispus E Sagittaria latifolia N Salix nigra N Senecio aureus N Solanum carolinense N Solidago incana N Sparghanium americana N Vernonia noveborancensis N aN = species is native to West Virginia, E = exotic species not native to West
Virginia (Harmon and Ford-Werntz 2002)
Appendix 6. Continued.
323
Appendix 7. Species list, origin (O), and average cover (AC) per 0.05 ha plot of all
herbaceous vegetation species sampled, and vegetation species that were seen but not
sampled (SBNS) per plot at the Sugar Creek mitigation wetland, 2001-2002.
Plot Species Oa AC Plot Species Oa AC
1 Agrimonia gryposepala N 0.3 2 Juncus effusus var. effusus N 1.5
1 Agrostis gigantea N 1.0 2 Phalaris arundinacea N 68.8
1 Anthoxanthum odoratum ssp. odoratum E 0.3 2 Scirpus cyperinus N 5.5
1 Apocynum cannabinum N 9.0 3 Asclepias incarnata N 0.3
1 Asclepias incarnata N 1.5 3 Boehmeria cylindrica N 0.8
1 Boehmeria cylindrica N 2.5 3 Eleocharis tenuis var. tenuis N 2.8
1 Carex lurida N 0.3 3 Galium tinctorium N 3.5
1 Carex scoparia var. scoparia N 0.3 3 Juncus effusus var. effusus N 0.3
1 Carex scoparia var. scoparia N 0.3 3 Mimulus ringens var. ringens N 0.8
1 Carex shortiana N 0.8 3 Oxalis stricta N 0.3
1 Carex vulpinoidea var. vulpinoidea N 2.3 3 Phalaris arundinacea N 50.0
1 Dichanthelium clandestinum N 10.3 3 Scirpus cyperinus N 6.8
1 Euthamia graminifolia var. graminifolia N 1.5 3 Typha latifolia N 1.5
1 Galium tinctorium N 5.8 4 Boehmeria cylindrica N 0.5
1 Hypericum mutilum N 0.3 4 Eleocharis tenuis var. tenuis N 1.8
1 Hypericum punctatum N 0.3 4 Galium tinctorium N 3.5
1 Juncus effusus var. effusus N 6.5 4 Juncus effusus var. effusus N 1.5
1 Juncus subcaudatus var. subcaudatus N 0.5 4 Juncus tenuis N 0.3
1 Juncus tenuis N 0.5 4 Ludwigia palustris N 1.8
1 Leersia oryzoides N 1.5 4 Lycopus uniflorus var. uniflorus N 0.3
1 Ludwigia palustris N 5.0 4 Mimulus ringens var. ringens N 2.0
1 Lycopus uniflorus var. uniflorus N 3.5 4 Panicum rigidulum var. rigidulum N 1.5
1 Mimulus ringens var. ringens N 3.3 4 Phalaris arundinacea N 61.8
1 Onoclea sensibilis N 0.3 4 Potentilla simplex N 0.3
1 Oxalis stricta N 1.0 4 Scirpus cyperinus N 1.8
1 Phalaris arundinacea N 26.0 4 Typha latifolia N 0.5
1 Rubus hispidus N 0.8 5 Boehmeria cylindrica N 0.3
1 Scirpus cyperinus N 3.8 5 Eleocharis tenuis var. tenuis N 0.8
1 Solanum carolinense var. carolinense N 0.3 5 Galium tinctorium N 1.5
1 Solidago tall 0.3 5 Juncus effusus var. effusus N 0.5
1 Teucrium canadense var. canadense E 0.8 5 Leersia oryzoides N 1.5
1 Viola papilionacea N 0.3 5 Ludwigia palustris N 0.3
2 Carex scoparia var. scoparia N 1.3 5 Panicum rigidulum var. rigidulum N 1.5
2 Carex stricta N 0.3 5 Phalaris arundinacea N 63.3
2 Carex vulpinoidea var. vulpinoidea N 0.5 5 Scirpus cyperinus N 2.5
2 Eleocharis tenuis var. tenuis N 3.0 SBNS 2 Galium tinctorium N 4.8 Alnus serulata N
324
SBNS continued Oa
Asclepias incarnata N Asclepias incarnata N Barbarea vulgaris E Carex intumescens N Clinopodium vulgare N Cornus amomum N Drosera rotundifolia N Hypericum perforatum N Impatiens capensis N Ludwigia alternifolia N Ludwigia palustris N Lycopus uniflora N Mimulus ringens N Panicum rigidulum N Salix nigra N Sambucus canadensis N Sisrinchium angustifolium N Typha latifolia N Verbena hastata N Verbena urticifolia N Veronia noveboracensis N aN = species is native to West Virginia, E = exotic species not native to West Virginia (Harmon and
Ford-Werntz 2002)
Appendix 7. Continued.
325
Appendix 8. Species list, origin (O), and average cover (AC) per 0.05 ha plot of all
herbaceous vegetation species sampled, and vegetation species that were seen but not
sampled (SBNS) per plot at the Sand Run mitigation wetland, 2001-2002.
Plot Species Oa AC Plot Species Oa AC1 Juncus effusus var. effusus N 12.75 4 Juncus secundus N 0.25
1 Leersia oryzoides N 1.00 4 Juncus subcaudatus var. subcaudatus N 0.75
1 Lemna minor N 1.00 4 Juncus tenuis N 0.501 Ludwigia palustris N 8.00 4 Leersia oryzoides N 2.251 Lycopus uniflorus var. uniflorus N 0.25 4 Ludwigia alternifolia N 1.501 Lysimachia nummularia E 0.50 4 Ludwigia palustris N 0.252 Juncus effusus var. effusus N 7.50 4 Lythrum salicaria E 3.002 Lemna minor N 2.25 4 Mimulus ringens var. ringens N 0.252 Ludwigia palustris N 7.25 4 Panicum rigidulum var. rigidulum N 0.253 Andropogon virginicus var. virginicus N 1.75 4 Phalaris arundinacea N 0.503 Apios americana N 0.50 4 Polygonum hydropiper N 0.253 Apocynum cannabinum N 0.25 SBNS 3 Carex lurida N 0.50 Acer saccharinum N 3 Carex scoparia var. scoparia N 0.25 Alnus serrulata N 3 Carex vulpinoidea var. vulpinoidea N 0.75 Apocynum cannabinum N 3 Eleocharis tenuis var. tenuis N 4.50 Asclepias incarnata N 3 Hypericum mutilum N 0.50 Brasenia schreberi A 3 Impatiens capensis N 1.75 Carex baileyi N 3 Juncus effusus var. effusus N 3.75 Carex lurida N 3 Juncus tenuis N 1.00 Cephalanthus occidentalis N 3 Ludwigia alternifolia N 3.25 Chelone glabra N 3 Mimulus ringens var. ringens N 2.00 Coronilla varia E 3 Panicum rigidulum var. rigidulum N 2.25 Cyperus strigosus N 3 Platanthera lacera var. lacera N 0.25 Dichanthelium clandestinum N 3 Polygonum hydropiper N 0.25 Eleocharis tenuis N 3 Potentilla simplex N 0.25 Erigeron annuus N 3 Pteridium aquilinium N 1.50 Fraxinus americana N 3 Rubus hispidus N 6.25 Galium tinctorium N 4 Apios americana N 0.50 Helenium flexuosa N 4 Carex lurida N 2.25 Hypericum densiflorum N 4 Carex vulpinoidea var. vulpinoidea N 0.50 Lemna minor N 4 Eleocharis tenuis var. tenuis N 0.25 Linum medium N 4 Eupatorium perfoliatum N 0.25 Ludwigia alternifolia N 4 Galium tinctorium N 0.50 Lycopus uniflora N 4 Impatiens capensis N 0.25 Lysimachia nummularia E 4 Juncus brachycarpus N 0.25 Lythrum salicaria E 4 Juncus effusus var. effusus N 8.25 Onoclea sensibilis N Osmunda cinnamomea N Penstemon digitalis N Phalaris arundinacea N Quercus rubra N Rumex crispus E
Sambucus canadensis N Scirpus tabernaemontani N Scutellaria laterifolia N
326
Appendix 8. Continued.
SBNS cont. Species O Sparganium americana N Thelypteris noveboracensis N Typha latifolia N aN = species is native to West Virginia,
E = exotic species not native to West Virginia
(Harmon and Ford-Werntz 2002)
327
Appendix 9. Species list, origin (O), and average cover (AC) per 0.05 ha plot of all
herbaceous vegetation species sampled, and vegetation species that were seen but not
sampled (SBNS) per plot at the Triangle mitigation wetland, 2001-2002.
Plot Species Oa AC Plot Species Oa AC
1 Asclepias incarnata N 0.3 3 Ludwigia alternifolia N 0.8 1 Carex lurida N 2.0 3 Ludwigia palustris N 10.01 Carex scoparia var. scoparia N 0.3 3 Lycopus virginicus N 0.3 1 Carex tribuloides N 0.3 3 Lythrum salicaria E 3.8 1 Carex vulpinoidea var. vulpinoidea N 0.8 3 Myosotis scorpioides E 0.3 1 Eleocharis obtusa N 0.3 3 Phalaris arundinacea N 1.5 1 Eleocharis tenuis var. tenuis N 2.3 3 Polygonum amphibium N 0.5 1 Galium tinctorium N 1.5 3 Sagittaria latifolia var. latifolia N 0.3 1 Impatiens capensis N 10.8 3 Scirpus cyperinus N 0.3 1 Juncus effusus var. effusus N 15.8 3 Typha latifolia N 28.81 Juncus tenuis N 0.3 4 Agrostis gigantea N 4.3 1 Leersia oryzoides N 0.3 4 Apocynum cannabinum N 2.0 1 Ludwigia palustris N 4.5 4 Carex lurida N 0.3 1 Lycopus virginicus N 2.3 4 Carex scoparia var. scoparia N 1.5 1 Lysimachia nummularia E 3.8 4 Carex vulpinoidea var. vulpinoidea N 0.5 1 Lythrum salicaria E 38.3 4 Clinopodium vulgare N 0.3 1 Myosotis scorpioides E 6.8 4 Coronilla varia E 6.0 1 Polygonum sagittatum N 0.3 4 Dipsacus fullonum ssp. sylvestris E 17.51 Scirpus americanus N 7.8 4 Eleocharis tenuis var. tenuis N 1.5 1 Scirpus atrocinctus N 0.8 4 Euthamia graminifolia var. graminifolia N 1.8 1 Typha latifolia N 1.3 4 Galium tinctorium N 0.3 1 Vernonia noveboracensis N 0.3 4 Geum laciniatum N 2.0 2 Agrimonia gryposepala N 0.3 4 Impatiens capensis N 5.3 2 Bidens frondosa N 0.3 4 Juncus effusus var. effusus N 1.5 2 Eupatorium coelestinum N 0.3 4 Juncus tenuis N 2.8 2 Eupatorium fistulosum N 3.3 4 Ludwigia alternifolia N 0.5 2 Eupatorium perfoliatum N 5.5 4 Lycopus virginicus N 0.8 2 Helenium autumnale N 1.8 4 Lythrum salicaria E 4.5 2 Juncus effusus N 9.3 4 Myosotis scorpioides E 3.3 2 Polygonum amphibium N 0.3 4 Oxalis stricta N 0.3 2 Setaria glauca E 0.5 4 Panicum rigidulum var. rigidulum N 0.3 2 Solidago canadensis N 7.5 4 Phalaris arundinacea N 9.5 3 Boehmeria cylindrica N 0.3 4 Poa alsodes N 0.8 3 Cardamine rotundifolia N 0.3 4 Polygonum hydropiper N 0.5 3 Carex lurida N 0.3 4 Polygonum punctatum N 0.5 3 Carex scoparia var. scoparia N 0.3 4 Pycnanthemum pycnanthemoides N 3.0 3 Juncus effusus var. effusus N 3.3
328
Plot Species Oa AC
4 Solanum carolinense var. carolinense N 2.3 4 Verbesina alternifolia N 3.0 SBNS Agrimonia gryposepala N Allium ceruum N Apocynum cannabinum N Barbarea vulgaris E Carex gynandra N Carex projecta N Cephalanthus occidentalis N Cornus amomum N Coronilla varia E Dipsacus fullonum E Erigeron annuus N Eupatorium fistulosum N Eupatorium perfoliatum N Euthamia graminifolia N Gentian andrewsii N Juncus subcaudatus N Leucanthemum vulgare E Mentha piperita E Onoclea sensibilis N Phalaris arundinacea N Polygonum amphibium N Pycnanthemum pycnanthemoides N Sagittaria latifolia N Sambucus canadensis N Scirpus americanus N Senecio aurea N Solanum carolinense N Spiraea alba N Verbena hastata N Verbena urticifolia N Veronia noveboracensis N
aN = species is native to West Virginia, E = exotic species not native to West Virginia
(Harmon and Ford-Werntz 2002)
Appendix 9. Continued.
329
Appendix 10. Species list, origin (O), and average cover (AC) per 0.05 ha plot of all
herbaceous vegetation species sampled, and vegetation species that were seen but not
sampled (SBNS) per plot at the Trus Joist MacMillan mitigation wetland, 2001-2002.
Plot Species Oa AC Plot Species Oa AC
1 Agrimonia gryposepala N 0.3 2 Eleocharis obtusa N 6.0
1 Allium cernuum var. cernuum N 0.3 2 Eleocharis tenuis var. tenuis N 0.5
1 Andropogon virginicus var. virginicus N 1.5 2 Galium tinctorium N 0.8
1 Anthoxanthum odoratum ssp. odoratum E 1.3 2 Hypericum mutilum N 0.5
1 Aster sp.1 0.3 2 Impatiens capensis N 0.0
1 Carex lurida N 0.3 4 Polygonum hydropiperoides N 3.0
1 Carex scoparia var. scoparia N 0.3 4 Polygonum lapathifolium N 4.5
1 Carex shortiana N 0.3 4 Polygonum sagittatum N 3.3
1 Carex stipata N 0.3 4 Rumex crispus E 0.3
1 Carex vulpinoidea var. vulpinoidea N 0.5 2 Juncus effusus var. effusus N 21.5
1 Clinopodium vulgare N 0.3 2 Leersia oryzoides N 7.0
1 Conium maculatum N 0.3 2 Ludwigia palustris N 7.5
1 Danthonia spicata N 0.5 2 Lycopus americanus N 0.5
1 Daucus carota E 0.8 2 Lythrum salicaria E 0.3
1 Dichanthelium clandestinum N 10.8 2 Polygonum hydropiperoides N 5.0
1 Galium aparine N 0.5 2 Polygonum sagittatum N 0.5
1 Galium tinctorium N 0.8 2 Scirpus cyperinus N 1.5
1 Hypericum punctatum N 0.3 2 Sparganium americanum N 0.3
1 Juncus effusus var. effusus N 0.5 3 Agrimonia gryposepala N 7.5
1 Juncus tenuis N 1.0 3 Bidens frondosa N 1.5
1 Lespedeza cuneata E 0.5 3 Carex lurida N 0.3
1 Leucanthemum vulgare E 0.8 3 Carex squarrosa N 1.8
1 Linum medium N 0.3 3 Carex vulpinoidea var. vulpinoidea N 3.3
1 Lycopus uniflorus var. uniflorus N 0.5 3 Dichanthelium clandestinum N 1.5
1 Panicum rigidulum var. rigidulum N 3.5 3 Eupatorium perfoliatum var. perfoliatum N 0.3
1 Plantago lanceolata E 1.5 3 Euthamia graminifolia var. graminifolia N 6.8
1 Potentilla simplex N 8.5 3 Galium tinctorium N 1.8
1 Prunella vulgaris ssp. vulgaris N 0.8 3 Geum canadense var. canadense N 0.5
1 Rubus sp. 2.0 3 Hypericum mutilum N 0.8
1 Setaria faberi E 0.3 3 Impatiens capensis N 7.5
1 Solanum carolinense var. carolinense N 0.3 3 Juncus effusus var. effusus N 0.5
1 Solidago gramminifolia N 0.8 3 Leersia oryzoides N 2.0
1 Solidago tall 7.5 3 Lysimachia nummularia E 3.3
1 Trifolium pratense E 1.8 3 Mimulus ringens var. ringens N 0.3
2 Bidens frondosa N 3.3 3 Oxalis stricta N 0.3
2 Boehmeria cylindrica N 0.3 3 Panicum rigidulum var. rigidulum N 3.5
2 Echinochloa crus-galli var. crus-galli N 3.0 3 Polygonum hydropiperoides N 0.5
330
Plot Species Oa AC SBNS Oa
3 Polygonum punctatum N 0.5 Achillea millefolium E 3 Polygonum sagittatum N 4.8 Agrostis gigantea N 3 Rubus sp. 1.5 Apocynum cannabinum N 3 Scirpus cyperinus N 3.0 Asclepias incarnata N 3 Typha latifolia N 3.0 Carex intumescens N 3 Vernonia noveboracensis N 3.0 Carex scoparia N
4 Echinochloa crus-galli var. crus-galli N 0.3 Cornus amomum N
4 Erechtites hieraciifolia var. hieraciifolia N 0.3 Erechtites hieraciifolia N
4 Galium tinctorium N 0.3 Erigeron annuus N 4 Impatiens capensis N 1.5 Eupatorium fistulosum N 4 Juncus effusus var. effusus N 7.5 Heteranthera reniformis N 4 Leersia oryzoides N 40.3 Juncus acuminatis N 4 Ludwigia palustris N 3.3 Juncus nodosus N 4 Lycopus uniflorus var. uniflorus N 3.0 Juncus subcaudatus N Juncus tenuis N Lespedeza cuneata E Leucanthemum vulgare E Lycopus uniflora N Lythrum salicaria E Mimulus ringens N Penthorum sedoides N Rosa palustris N Scirpus tabernaemontani N Teuchrium canadense E Typha latifolia N Verbena hastata N Verbena urticifolia N Veronia noveboracensis N
aN = species is native to West Virginia, E = exotic species not native to West Virginia (Harmon and
Ford-Werntz 2002)
Appendix 10. Continued.
331
Appendix 11. Species list, origin (O), and average cover (AC) per 0.05 ha plot of all
herbaceous vegetation species sampled, and vegetation species that were seen but not
sampled (SBNS) per plot at the Enoch Branch mitigation wetland, 2001-2002.
Plot Species Oa AC Plot Species Oa AC
1 Aster sp. 0.3 3 Sisyrinchium angustifolium N 5.5
1 Coronilla varia E 9.3 3 Solanum carolinense var. carolinense N 0.3
1 Eleocharis tenuis var. tenuis N 0.3 3 Verbesina alternifolia N 4.5
1 Epilobium coloratum N 0.5 4 Eleocharis obtusa N 6.3
1 Juncus effusus var. effusus N 1.8 4 Eleocharis tenuis var. tenuis N 1.5
1 Juncus tenuis N 0.5 4 Juncus effusus var. effusus N 3.8
1 Lespedeza cuneata E 8.3 4 Juncus subcaudatus var. subcaudatus N 0.3
1 Ludwigia palustris N 0.3 4 Leersia oryzoides N 0.3
1 Panicum rigidulum var. rigidulum N 0.3 4 Ludwigia palustris N 2.5
1 Panicum virgatum var. virgatum N 6.3 4 Sparganium americanum N 10.8
1 Plantago lanceolata E 1.5 SBNS 1 Rubus hispidus N 0.8 Acer rubrum N 1 Sisyrinchium angustifolium N 2.0 Apios americana N 1 Viola sororia N 0.3 Apocynum cannabinum N 2 Eleocharis obtusa N 1.8 Asclepias incarnata N 2 Eleocharis tenuis var. tenuis N 1.8 Boehmeria cylindrica N 2 Juncus effusus var. effusus N 5.5 Carex intumescens N 2 Juncus subcaudatus var. subcaudatus N 2.0 Carex scoparia N 2 Leersia oryzoides N 0.8 Carex vulpinoidea N 2 Ludwigia palustris N 0.0 Eleocharis tenuis N 2 Sparganium americanum N 0.3 Galium tinctorium N 3 Agrimonia gryposepala N 0.3 Hypericum mutilum N 3 Antennaria solitaria N 0.3 Juncus effusus N 3 Apios americana N 0.3 Leucanthemum vulgare E 3 Aster sp. 0.8 Ludwigia alternifolia N 3 Carex lurida N 0.3 Ludwigia palustris N 3 Galium tinctorium N 6.0 Mimulus ringens N 3 Hypericum mutilum N 5.0 Onoclea sensibilis N 3 Juncus brevicaudatus N 0.3 Panicum rigidulum N 3 Juncus effusus var. effusus N 4.8 Potamogeton diversifolius N 3 Mimulus ringens var. ringens N 3.3 Rosa multiflora E 3 Onoclea sensibilis N 3.3 Sagittaria latifolia N 3 Oxalis stricta N 0.8 Scirpus tabernaemontani N 3 Panicum virgatum var. virgatum N 1.8 Solanum carolinense N 3 Rubus hispidus N 0.8 3 Scirpus cyperinus N 0.3 3 Selaginella apoda N 0.3 aN = species is native to West Virginia, E = exotic
species not native to West Virginia (Harmon and Ford-
332
Appendix 12. Species list, origin (O), and average cover (AC) per 0.05 ha plot of all
herbaceous vegetation species sampled, and vegetation species that were seen but not
sampled (SBNS) per plot at the Bear Run mitigation wetland, 2001-2002.
Plot Species Oa AC
1 Eleocharis obtusa N 0.3
1 Eleocharis quadrangulata N 12.0
1 Juncus subcaudatus var. subcaudatus N 1.5
1 Lemna minor N 3.8
1 Ludwigia palustris N 1.8
1 Potamogeton spirillus A 7.5
1 Spirodela polyrrhiza N 0.3
1 Typha latifolia N 0.3
2 Eleocharis obtusa N 1.5
2 Heteranthera reniformis N 0.3
2 Leersia oryzoides N 0.5
2 Lemna minor N 5.3
2 Ludwigia palustris N 12.5
2 Spirodela polyrrhiza N 5.5
2 Typha angustifolia N 3.8
2 Typha latifolia N 2.0
2 Wolffia brasiliensis N 10.8
SBNS
Carex lurida N
Carex tribuloides N
Cyperus strigosus N
Galium tinctorium N
Mimulus ringens N
Sagittaria graminea N aN = species is native to West Virginia, E = exotic species not native to West Virginia (Harmon and
Ford-Werntz 2002)
333
Appendix 13. Species list, origin (O), and average cover (AC) per 0.05 ha plot of all
herbaceous vegetation species sampled, and vegetation species that were seen but not
sampled (SBNS) per plot at the Altona Marsh reference wetland, 2001-2002.
Plot Species Oa AC 1 Boehmeria cylindrica N 15 1 Galium tinctorium N 1.5 1 Juncus balticus var. littoralis N 15 1 Leersia oryzoides N 0.5 1 Lycopus virginicus N 0.5 1 Scirpus acutus N 3.5 1 Thelypteris palustris var. pubescens N 42.5 2 Boehmeria cylindrica N 10 2 Galium tinctorium N 5 2 Impatiens pallida N 12.5 2 Juncus balticus var. littoralis N 4.5 2 Ludwigia palustris N 2 2 Lycopus virginicus N 7 2 Mimulus ringens var. ringens N 0.5 2 Sagittaria latifolia var. latifolia N 6.5 2 Scirpus americanus N 0.5 2 Thelypteris palustris var. pubescens N 17 2 Typha latifolia N 37.5 3 Caltha palustris var. palustris N 6 3 Equisetum fluviatile N 12.5 3 Eupatorium maculatum var. maculatum N 3.5 3 Impatiens pallida N 33.5 3 Mimulus ringens var. ringens N 0.5 3 Sagittaria latifolia var. latifolia N 0.5 3 Scutellaria galericulata N 1 3 Typha latifolia N 1
aN = species is native to West Virginia, E = exotic species not native to West Virginia (Harmon and
Ford-Werntz 2002)
334
Appendix 14. Species list, origin (O), and average cover (AC) per 0.05 ha plot of all
herbaceous vegetation species sampled, and vegetation species that were seen but not
sampled (SBNS) per plot at the Elder Swamp reference wetland, 2001-2002.
Plot Species Oa AC Plot Species Oa AC
1 Eriophorum virginicum N 1.3 6 Juncus effusus var. effusus N 1.5
1 Rubus hispidus N 12.3 6 Juncus subcaudatus var. subcaudatus N 0.8
1 Solidago uliginosa var. uliginosa N 0.3 6 Rubus hispidus N 1.5
2 Drosera rotundifolia var. rotundifolia N 0.8 6 Triadenum virginicum N 0.8
2 Eriophorum virginicum N 12.0 6 Typha latifolia N 9.8
2 Gaultheria procumbens N 0.8 6 Viola cucullata N 0.8
2 Rubus hispidus N 7.5 7 Danthonia compressa N 1.8
3 Carex canescens ssp. canescens N 8.5 7 Lycopodium obscurum N 9.0
3 Carex trisperma var. trisperma N 0.3 7 Pteridium aquilinium N 6.8
3 Drosera rotundifolia var. rotundifolia N 2.5 7 Rubus hispidus N 16.5
3 Eriophorum virginicum N 2.3 7 Solidago uliginosa var. uliginosa N 9.8
3 Juncus brevicaudatus N 1.5 SBNS
3 Rubus hispidus N 5.0 Amelanchier laevis N
4 Agrostis hyemalis N 0.3 Aster umbellatus N
4 Aster puniceus N 0.3 Carex crinita N
4 Carex argyrantha N 0.3 Carex gynandra N
4 Carex folliculata N 1.5 Carex scoparia N
4 Carex scoparia var. scoparia N 0.3 Carex vulpinoidea N
4 Galium tinctorium N 1.3 Cypredium acaule N
4 Glyceria canadensis N 1.8 Eriophorum virginicum N
4 Glyceria striata N 0.3 Galium tinctorium N
4 Impatiens capensis N 2.3 Gentian andrewsii N
4 Leersia oryzoides N 11.5 Glyceria grandis N
4 Polygonum sagittatum N 1.8 Hypericum densiflorum N
4 Rubus hispidus N 3.5 Juncus effusus N
4 Solidago sp. 1.8 Lycopodium obscurum N
4 Solidago uliginosa var. uliginosa N 1.5 Osmunda cinnamomea N
4 Typha latifolia N 0.3 Polygonum sagittatum N
4 Viola cucullata N 1.0 Populus tremuloides N
5 Danthonia compressa N 0.8 Solidago incana N
5 Lycopodium clavatum var. clavatum N 2.0 Tradenum virginicum N
5 Pteridium aquilinum var. latiusculum N 4.8 Vaccinium oxycoccus N
5 Rubus hispidus N 12.0 Viburnum dentatum N
5 Solidago uliginosa var. uliginosa N 3.5 6 Dulichium arundinaceum N 0.3
aN = species is native to West Virginia, E = exotic species not native to West Virginia (Harmon and Ford-Werntz 2002)
335
Appendix 15. Species list, origin (O), and average cover (AC) per 0.05 ha plot of all
herbaceous vegetation species sampled, and vegetation species that were seen but not
sampled (SBNS) per plot at the Meadowville reference wetland, 2001-2002.
Plot Species Oa AC Plot Species Oa AC
1 Carex scoparia var. scoparia N 4.5 4 Clematis virginiana N 6.0
1 Carex stricta N 17.0 4 Galium mollugo E 7.3
1 Carex tribuloides N 0.8 4 Galium tinctorium N 0.5
1 Eleocharis tenuis var. tenuis N 1.5 4 Geum rivale N 5.0
1 Epilobium coloratum N 4.8 4 Impatiens capensis N 17.3
1 Galium tinctorium N 3.5 4 Oxalis stricta N 0.3
1 Glyceria canadensis N 0.3 4 Polygonum sagittatum N 13.0
1 Impatiens capensis N 12.5 4 Rubus sp. 0.3
1 Leersia oryzoides N 30.0 4 Solidago canadensis var. canadensis N 23.0
1 Ludwigia palustris N 2.3 4 Verbesina alternifolia N 1.8
1 Mimulus ringens var. ringens N 4.0 SBSN 1 Polygonum sagittatum N 3.5 Asclepias incarnata N 1 Typha latifolia N 6.3 Calamagrostis canadensis N 2 Boehmeria cylindrica N 1.8 Carex gynandra N 2 Calamagrostis canadensis var. canadensis N 61.8 Carex lurida N 2 Carex stipata N 0.5 Carex scoparia N 2 Carex stricta N 11.8 Cornus amomum N 2 Galium mollugo E 3.5 Epilobium coloratum N 2 Galium tinctorium N 2.5 Juncus effusus N 2 Glyceria canadensis N 1.8 Onoclea sensibilis N 2 Impatiens pallida N 3.5 Rosa palustris N 2 Juncus effusus var. effusus N 0.3 Sambucus canadensis N 2 Leersia oryzoides N 0.8 Scirpus cyperinus N 2 Polygonum sagittatum N 7.0 Scutellaria laterifolia N 2 Scirpus cyperinus N 0.3 3 Carex stricta N 6.0 3 Galium tinctorium N 0.3 3 Glyceria canadensis N 2.5 3 Gratiola virginiana var. virginiana N 3.5 3 Mimulus ringens var. ringens N 0.3 3 Polygonum hydropiperoides N 0.3 3 Polygonum scandens E 0.3 3 Typha latifolia N 47.5 4 Agrimonia gryposepala N 4.8 4 Apocynum cannabinum N 1.0 4 Boehmeria cylindrica N 1.5 4 Carex stricta N 28.5
aN = species is native to West Virginia, E = exotic species not native to West Virginia (Harmon and Ford-Werntz 2002)
336
Appendix 16. Species list, origin (O), and average cover (AC) per 0.05 ha plot of all
herbaceous vegetation species sampled, and vegetation species that were seen but not
sampled (SBNS) per plot at the Muddlety reference wetland, 2001-2002.
aN = species is native to West Virginia, E = exotic species not native to West Virginia (Harmon and
Ford-Werntz 2002)
Plot Species Oa AC 1 Juncus effusus var. effusus N 2.0
1 Ludwigia palustris N 1.5
1 Onoclea sensibilis N 1.5
1 Polygonum hydropiperoides N 0.3
1 Polygonum punctatum N 0.3
1 Sparganium americanum N 18.8
SBNS Boehmeria cylindrica N Carex lupulina N Polygala polygama N Rosa palustris N Scutellaria laterifolia N
337
Appendix 17. Woody and herbaceous vegetation species that were planted at 3 mitigation wetland sites, West Virginia, 2001-2002.
Species Number Planted Type Common name Scientific name Triangle Sand Run VEPCO Trees Black willow Salix nigra 45 Pin oak Quercus palustris 80 Swamp white oak Quercus bicolor Red maple Acer rubrum 250 Silver maple Acer sacharinum 225 40 Serviceberry Amelanchier laevis 204 Shrubs Buttonbush Cephalanthus occidentalis 2,275 200 Black edlerberry Sambucus canadensis 1300 300 Red chokeberry Aronia arbutifolia 270 Pipestem Spiraea alba 100 Winterberry Ilex verticllata 30 Alders (smooth/speckled) Alnus serrulata/incana 275 Highbush cranberry Viburnum trilobum 115 Gray dogwood Cornus foemina 400 Herbaceous Duck potato Sagittaria latifolia 1300 100 Common threesquare Scirpus americanus 3000 Sedge Carex lurida 350 Woolgrass Scirpus atrovirens 1250 500 Sensitive fern Onoclea sensibilis 350 Seed Switchgrass Panicum virgatum 15 Ibs/acre 15 Ibs/acre 15 Ibs/acre Redtop Agrostis alba 10 Ibs/acre 10 Ibs/acre Wild millet Echinochloa crusgalli 10 Ibs/acre 10 Ibs/acre Japanese millet Echinochloa frumentacea 1/2 bushel/acre Annual rye Lolium mutliflorum 280 Ibs/acre
338
Appendix 18-1. Bird, frog, and vegetation sampling points as well as dominant
vegetation at the Altona Marsh reference wetland, West Virginia, 2001-2002.
339
Appendix 18-2. Wetland classification (Cowardin et al. 1979) where PEM =
palustrine emergent, PF = palustrine forested, PSS = palustrine scrub-shrub, and PUB
= palustrine unconsolidated bottom, of the Altona Marsh reference wetland, West
Virginia, 2001-2002.
340
Appendix 19-1. Bird, frog, and vegetation sampling points as well as dominant
vegetation at the Walnut Bottom mitigation wetland, West Virginia, 2001-2002.
Appendix 19-2. Wetland classification (Cowardin et al. 1979) where PEM =
palustrine emergent, PSS = palustrine scrub-shrub, and PUB = palustrine
unconsolidated bottom, of the Walnut Bottom mitigation wetland, West Virginia,
2001-2002.
Maps were unable to be obtained for this site.
341
Appendix 20-1. Bird, frog, and vegetation sampling points as well as dominant
vegetation at the Elder Swamp reference wetland, West Virginia, 2001-2002.
342
Appendix 20-2. Wetland classification (Cowardin et al. 1979) where PEM =
palustrine emergent, PF = palustrine forested, PSS = palustrine scrub-shrub, and PUB
= palustrine unconsolidated bottom of the Elder Swamp reference wetland, West
Virginia, 2001-2002.
343
Appendix 21-1. Bird, frog, and vegetation sampling points as well as dominant
vegetation at the VEPCO mitigation wetland, West Virginia, 2001-2002.
344
Appendix 21-2. Wetland classification (Cowardin et al. 1979) where N/A = no
applicable classification, PEM = palustrine emergent, PSS = palustrine scrub-shrub,
and PUB = palustrine unconsolidated bottom of the VEPCO mitigation wetland, West
Virginia, 2001-2002.
345
Appendix 22-1. Bird, frog, and vegetation sampling points as well as dominant
vegetation at the Buffalo Coal mitigation wetland, West Virginia, 2001-2002.
346
Appendix 22-2. Wetland classification (Cowardin et al. 1979) where N/A = no
applicable classification, PEM = palustrine emergent, PSS = palustrine scrub-shrub,
and PUB = palustrine unconsolidated bottom of the Buffalo Coal mitigation wetland,
West Virginia, 2001-2002.
347
Appendix 23-1. Bird, frog, and vegetation sampling points as well as dominant
vegetation at the Elk Run mitigation wetland, West Virginia, 2001-2002.
348
Appendix 23-2. Wetland classification (Cowardin et al. 1979) where N/A = no
applicable classification, PEM = palustrine emergent, PSS = palustrine scrub-shrub,
and PUB = palustrine unconsolidated bottom of the Elk Run mitigation wetland,
WestVirginia, 2001-2002.
349
Appendix 24-1. Bird, frog, and vegetation sampling points as well as dominant
vegetation at the Meadowville reference wetland, West Virginia, 2001-2002.
350
Appendix 24-2. Wetland classification (Cowardin et al. 1979) where N/A = no
applicable classification, PEM = palustrine emergent, and PSS = palustrine scrub-
shrub, of the Meadowville reference wetland, West Virginia, 2001-2002.
351
Appendix 25-1. Bird, frog, and vegetation sampling points as well as dominant
vegetation at the Leading Creek mitigation wetland, West Virginia, 2001-2002.
352
Appendix 25-2. Wetland classification (Cowardin et al. 1979) where N/A = no
applicable classification, PEM = palustrine emergent, PSS = palustrine scrub-shrub,
and PUB = palustrine unconsolidated bottom of the Leading Creek mitigation
wetland, West Virginia, 2001-2002.
353
Appendix 26-1. Bird, frog, and vegetation sampling points as well as dominant
vegetation at the Sugar Creek mitigation wetland, West Virginia, 2001-2002.
354
Appendix 26-2. Wetland classification (Cowardin et al. 1979) where N/A = no
applicable classification, PEM = palustrine emergent, PSS = palustrine scrub-shrub,
and PUB = palustrine unconsolidated bottom of the Sugar Creek mitigation wetland,
West Virginia, 2001-2002.
355
Appendix 27-1. Bird, frog, and vegetation sampling points as well as dominant
vegetation at the Sand Run mitigation wetland, West Virginia, 2001-2002.
356
Appendix 27-2. Wetland classification (Cowardin et al. 1979) where N/A = no
applicable classification, PEM = palustrine emergent, PSS = palustrine scrub-shrub,
and PUB = palustrine unconsolidated bottom of the Sand Run mitigation wetland,
West Virginia, 2001-2002.
357
Appendix 28-1. Bird, frog, and vegetation sampling points as well as dominant
vegetation at the Triangle mitigation wetland, West Virginia, 2001-2002.
358
Appendix 28-2. Wetland classification (Cowardin et al. 1979) where N/A = no
applicable classification, PEM = palustrine emergent, PSS = palustrine scrub-shrub,
and PUB = palustrine unconsolidated bottom of the Triangle mitigation wetland,
West Virginia, 2001-2002.
359
Appendix 29-1. Bird, frog, and vegetation sampling points as well as dominant
vegetation at the Trus Joist MacMillan mitigation wetland, West Virginia, 2001-2002.
360
Appendix 29-2. Wetland classification (Cowardin et al. 1979) where PEM =
palustrine emergent, PSS = palustrine scrub-shrub, PUB = palustrine unconsolidated
bottom, and PUS = palustrine unconsolidated shore, of the Trus Joist MacMillan
mitigation wetland, West Virginia, 2001-2002.
361
Appendix 30-1. Bird, frog, and vegetation sampling points as well as dominant
vegetation at the Muddlety reference wetland, West Virginia, 2001-2002.
362
Appendix 30-2. Wetland classification (Cowardin et al. 1979) where PEM =
palustrine emergent, PSS = palustrine scrub-shrub, and PUB = palustrine
unconsolidated bottom of the Muddlety reference wetland, West Virginia, 2001-2002.
363
Appendix 31-1. Bird, frog, and vegetation sampling points as well as dominant
vegetation at the Enoch Branch mitigation wetland, West Virginia, 2001-2002.
364
Appendix 31-2. Wetland classification (Cowardin et al. 1979) where N/A = no
applicable classification, PEM = palustrine emergent, PSS = palustrine scrub-shrub,
and PUB = palustrine unconsolidated bottom of the Enoch Branch mitigation
wetland, West Virginia, 2001-2002.
365
Appendix 32-1. Bird, frog, and vegetation sampling points as well as dominant
vegetation at the Bear Run mitigation wetland, West Virginia, 2001-2002.
366
Appendix 32-2. Wetland classification (Cowardin et al. 1979) where N/A = no
applicable classification, PEM = palustrine emergent, and PUB = palustrine
unconsolidated bottom of the Bear Run mitigation wetland, West Virginia, 2001-
2002.
367
Appendix 33. Number of benthic individuals collected by family and wetland from emergent (E) and open water (O) areas, as well as for the entire
complex (total) for 11 mitigation wetlands in West Virginia, 2001-2002.
Walnut
Bottom Vepco Buffalo Coal Elk Run Leading Creek Sugar Creek Sand Run Triangle
Trus Joist MacMillan Enoch Branch Bear Run TOTAL
Order Family E O total E O total E O total E O total E O total E O total E O total E O total E O total E O total E O total E O total
Arachnid Hydracarina 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1
Coleoptera Chrysomelidae 0 0 0 2 0 2 0 0 0 0 0 0 0 0 0 3 0 3 0 0 0 0 0 0 0 0 0 4 0 4 1 0 1 10 0 10
Coleoptera Curculionidae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1
Coleoptera Dytiscidae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 0 0 0 0 0 0 0 0 0 2 0 2 Coleoptera Elmidae 0 1 1 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 2 Coleoptera Hydrophilidae 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Coleoptera UNKNOWN 0 0 0 0 0 0 0 0 0 0 3 3 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 3 4 Diptera Ceratopogonidae 1 1 2 5 0 5 1 1 2 1 0 1 2 0 2 0 5 5 3 0 3 9 1 10 3 1 4 4 1 5 0 3 3 29 13 42 Diptera Chaobridae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 1 Diptera Chironomidae 1 11 12 13 27 40 9 10 19 15 9 24 8 2 10 3 1 4 2 1 3 1 4 5 3 5 8 11 13 24 2 4 6 68 87 155 Diptera Culicidae 0 0 0 0 0 0 1 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 Diptera Empididae 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 2 0 2 0 0 0 0 1 1 1 0 1 0 0 0 0 1 1 4 2 6 Diptera Ephydridae 0 0 0 2 0 2 0 2 2 10 1 11 3 0 3 12 0 12 1 0 1 4 3 7 3 0 3 2 0 2 4 0 4 41 6 47 Diptera Psychodidae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 1 1 Diptera Sciomyzidae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 1 0 1 Diptera Tabanidae 1 0 1 1 0 1 1 0 1 1 0 1 4 0 4 2 2 4 1 0 1 0 0 0 2 0 2 0 0 0 0 0 0 13 2 15 Diptera Tipulidae 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 2 0 2 Diptera UNKNOWN 1 0 1 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 3 0 3 Ephemeroptera Caenidae 0 1 1 0 0 0 0 2 2 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 4 Ephemeroptera Ephemerillidae 0 0 0 0 1 1 0 0 0 1 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 3 Gastropoda Lymnaedae 12 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 5 2 0 2 0 0 0 2 0 2 17 4 21 Gastropoda Physidae 199 94 293 0 0 0 0 0 0 4 1 5 1 0 1 2 0 2 5 5 10 50 27 77 55 0 55 0 0 0 8 2 10 324 129 453 Gastropoda Planorbidae 278 285 563 9 1 10 1 3 4 132 18 150 17 7 24 6 9 15 17 5 22 19 22 41 48 2 50 0 2 2 28 80 108 555 434 989 Gastropoda Pomatiopsidae 10 8 18 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 8 18 Gastropoda Valvatidae 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 2 0 2 Gastropoda Viviparidae 63 8 71 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 13 7 20 34 0 34 0 0 0 19 0 19 129 16 145 Gastropoda UNKNOWN 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 1
368
Walnut Bottom Vepco Buffalo Coal Elk Run
Leading Creek Sugar Creek Sand Run Triangle
Trus Joist MacMillan Enoch Branch Bear Run TOTAL
Order Family E O total E O total E O total E O total E O total E O total E O total E O total E O total E O total E O total E O total
Hemiptera Notonectidae 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Hirudinodea Erpobdellidae 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 Hirudinodea Glossiphoniidae 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Lepidoptera Pyralidae 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Nematoda Mermithidae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 2 0 0 0 1 1 2 Nematoda Nematoda 0 0 0 0 0 0 0 0 0 2 1 3 2 0 2 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 5 1 6 Odanata Coenagrionidae 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Odanata Corduliidae 0 0 0 0 0 0 0 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 3 1 4 5 Odanata Libellulidae 0 1 1 0 0 0 0 0 0 0 1 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 3 Oligochaeta Oligochaeta 65 19 84 24 12 36 3 36 39 20 28 48 69 20 89 25 144 169 3 4 7 28 79 107 253 48 301 25 25 50 15 9 24 530 424 954 Pelecypoda Sphaeriidae 0 2 2 0 0 0 1 7 8 48 55 103 17 7 24 4 0 4 0 0 0 41 58 99 10 0 10 0 0 0 4 2 6 125 131 256 Pelecypoda Unionidae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 2 0 2 2 1 3 Trichoptera Leptoceridae 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Trichoptera Phryganeidae 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 UNKNOWN UNKNOWN 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 3 0 0 0 0 3 3 TOTALS 633 431 1064 59 41 100 18 63 81 241 117 358 128 36 164 59 162 221 34 16 50 171 207 378 416 57 473 48 45 93 86 104 190 1893 1279 3172
Appendix 33. Continued.
369
Appendix 34. Number of nektonic individuals collected by family and wetland from emergent (E), open water (O), and scrub-shrub
(SS) areas, as well as for the entire complex (total) for 4 reference wetlands in West Virginia, 2001-2002.
Altona Marsh Elder Swamp Meadowville Muddlety TOTAL Order Family E O total E O SS total E O total E O SS total E O SS total Amphipoda Gammaridae 1 0 1 0 0 1 1 0 0 0 0 0 0 0 1 0 1 2 Amphipoda Talitridae 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 Coleoptera Chrysomelidae 0 0 0 0 0 0 0 0 0 0 4 0 0 4 4 0 0 4 Coleoptera Elmidae 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 Decapoda Astracidae 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 1 Diptera Ceratopogonidae 0 1 1 1 0 3 4 1 0 1 3 2 0 5 5 3 3 11 Diptera Chironomidae 3 1 4 1 5 1 7 9 0 9 7 13 1 21 20 19 2 41 Diptera Ephydridae 3 0 3 1 0 0 1 12 0 12 4 1 0 5 20 1 0 21 Diptera Scatophagidae 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 Diptera Stratiomyidae 0 1 1 0 0 0 0 1 0 1 0 0 0 0 1 1 0 2 Diptera Tabanidae 1 1 2 0 0 0 0 2 0 2 2 0 0 2 5 1 0 6 Diptera UNKNOWN 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 Ephemeroptera Caenidae 0 0 0 0 0 0 0 0 0 0 0 2 0 2 0 2 0 2 Gastropoda Lymnaedae 130 55 185 0 0 0 0 0 0 0 0 0 0 0 130 55 0 185 Gastropoda Physidae 435 73 508 0 0 0 0 0 0 0 0 0 0 0 435 73 0 508 Gastropoda Planorbidae 450 597 1047 0 2 0 2 0 0 0 0 11 4 15 450 610 4 1064Gastropoda Pomatiopsidae 319 264 583 0 0 0 0 0 0 0 0 0 0 0 319 264 0 583 Gastropoda Valvatidae 5 122 127 0 0 0 0 0 0 0 0 0 0 0 5 122 0 127 Gastropoda Viviparidae 105 327 432 0 0 0 0 2 0 2 2 2 0 4 109 329 0 438 Hirudinodea Erpobdellidae 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 1 Isopoda Asellidae 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 1 Megaloptera Sialidae 0 0 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 1 Nematoda Nematoda 0 0 0 0 0 0 0 1 0 1 1 7 0 8 2 7 0 9 Oligochaeta Oligocheata 11 17 28 1 3 10 14 28 0 28 23 20 4 47 63 40 14 117 Pelecypoda Sphaeriidae 419 180 599 0 1 0 1 5 0 5 8 1 6 15 432 182 6 620 Pelecypoda Unionidae 7 36 43 0 0 0 0 0 0 0 0 0 0 0 7 36 0 43
370
Altona Marsh Elder Swamp Meadowville Muddlety TOTAL Order Family E O total E O SS total E O total E O SS total E O SS total UNKNOWN UNKNOWN 0 0 0 0 0 0 0 1 0 1 0 0 0 0 1 0 0 1 TOTALS 1893 1675 3568 5 11 15 31 62 0 62 57 59 15 131 2017 1745 30 3792
Appendix 34. Continued.
371
Appendix 35. Number of nektonic individuals collected by family and wetland from emergent (E) and open water (O) areas, as well as for the
entire complex (total) for 11 mitigation wetlands in West Virginia, 2001-2002.
Walnut Bottom Vepco Buffalo Coal Elk Run Leading Creek Sugar Creek Sand Run Triangle
Trus Joist MacMillan Enoch Branch Bear Run TOTAL
Order Family E O total E O total E O total E O total E O total E O total E O total E O total E O total E O total E O total E O total Amphipoda Gammaridae 0 0 0 0 0 0 3 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 3 Amphipoda Talitridae 2 159 161 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 159 162 Arachnid Hydracarina 0 0 0 0 0 0 21 6 27 1 8 9 0 0 0 0 0 0 1 0 1 5 11 16 0 0 0 1 0 1 1 3 4 30 28 58 Arachnid Arachnid 0 1 1 4 1 5 2 0 2 0 0 0 1 0 1 5 0 5 1 0 1 5 1 6 1 0 1 0 0 0 2 0 2 21 3 24 Arguloida Argulidae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Cladocera NA 2 83 3 2 5 7 102 27 129 17 7 24 1 0 1 9 0 9 2 0 2 5 32 37 45 0 45 0 0 0 2 0 2 187 154 341 Coleoptera Carabidae 1 3 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 4 Coleoptera Chrysomelidae 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 Coleoptera Dytiscidae 6 3 9 2 1 3 15 1 16 7 0 7 14 0 14 0 1 1 0 0 0 5 0 5 2 0 2 0 0 0 3 0 3 54 6 60 Coleoptera Elmidae 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 1 0 0 0 2 0 2 4 1 5 Coleoptera Gyrinidae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 1 Coleoptera Haliplidae 0 27 27 0 0 0 2 2 4 3 0 3 3 0 3 0 0 0 5 2 7 6 11 17 1 0 1 0 0 0 5 10 15 25 52 77 Coleoptera Helodidae 1 0 1 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 Coleoptera Hydrophilidae 4 0 4 1 0 1 0 1 1 0 0 0 1 0 1 1 1 2 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 8 2 10 Coleoptera Noteridae 0 0 0 0 0 0 6 1 7 1 0 1 0 2 2 1 0 1 0 0 0 4 0 4 0 0 0 0 0 0 2 0 2 14 3 17 Coleoptera UNKNOWN 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 1 0 0 0 0 0 0 0 0 0 2 0 2 Collembola Isotomidae 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 2 2 0 0 0 0 0 0 0 0 0 0 0 0 1 2 3 Collembola Poduridae 0 0 0 0 0 0 7 3 10 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 4 11 Conchostraca Conchostraca 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 4 4 0 0 0 0 0 0 0 1 1 1 5 6 Copepoda Cyclopoida 2 10 12 2 5 7 12 2 14 3 5 8 1 1 2 2 0 2 1 0 1 2 0 2 2 0 2 0 0 0 6 2 8 33 25 58 Diptera Athericidae 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Diptera Ceratopogonidae 0 0 0 0 0 0 6 2 8 6 3 9 0 0 0 1 0 1 1 0 1 1 1 2 0 0 0 0 0 0 1 0 1 16 6 22 Diptera Chaobaridae 0 0 0 0 0 0 0 0 0 2 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 4 8 6 4 10 Diptera Chironomidae 10 16 26 48 19 67 148 20 168 10 12 22 6 1 7 6 0 6 14 2 16 6 52 58 7 0 7 15 0 15 6 8 14 276 130 406 Diptera Culicidae 6 4 10 3 0 3 22 1 23 1 1 2 13 1 14 4 0 4 0 0 0 1 2 3 1 0 1 1 0 1 2 0 2 54 9 63 Diptera Dixidae 0 0 0 0 0 0 0 0 0 2 0 2 0 0 0 0 0 0 2 0 2 0 0 0 0 0 0 0 0 0 0 0 0 4 0 4 Diptera Ephydridae 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Diptera Sciomyzidae 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2
372
Walnut Bottom Vepco Buffalo Coal Elk Run
Leading Creek Sugar Creek Sand Run Triangle
Trus Joist MacMillan Enoch Branch Bear Run TOTAL
Order Family E O total E O total E O total E O total E O total E O total E O total E O total E O total E O total E O total E O total Diptera Stratiomyidae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 1 Diptera Tabanidae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1 0 1 1 0 1 2 1 3 Diptera Tipulidae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 1 Diptera UNKNOWN 1 0 1 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 2 1 3 Ephemeroptera Baetidae 13 72 85 0 0 0 0 0 0 0 1 1 0 0 0 0 1 1 1 1 2 1 5 6 3 0 3 0 0 0 7 12 19 25 92 117 Ephemeroptera Caenidae 1 0 1 1 3 4 6 47 53 36 15 51 0 6 6 3 4 7 16 19 35 4 56 60 1 0 1 8 1 9 14 10 24 90 161 251 Ephemeroptera Siphlonuridae 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 3 Ephemeroptera UNKNOWN 0 0 0 1 0 1 0 0 0 0 0 0 3 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 4 Gastropoda Lymnaedae 2 2 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 3 2 5 Gastropoda Physidae 28 41 69 0 0 0 0 0 0 0 0 0 3 0 3 7 1 8 9 2 11 10 1 11 14 1 15 0 0 0 6 10 16 77 56 133
Gastropoda Planorbidae 25 46 71 0 0 0 0 2 2 58 9 67 19 2 21 14 13 27 18 6 24 5 13 18 2 0 2 4 17 21 44 22 66 189 130 319 Gastropoda Viviparidae 32 8 40 0 0 0 0 2 2 3 0 3 1 1 2 1 0 1 5 0 5 9 3 12 15 0 15 0 0 0 3 0 3 69 14 83 Hemiptera Aphididae 0 0 0 0 0 0 3 0 3 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 4 Hemiptera Belostomatidae 1 0 1 0 0 0 0 0 0 0 0 0 0 2 2 1 0 1 0 0 0 1 0 1 0 0 0 1 0 1 1 0 1 5 2 7 Hemiptera Corixidae 1 6 7 1 3 4 13 1 14 2 2 4 0 2 2 0 2 2 0 0 0 0 0 0 82 4 86 0 0 0 0 0 0 99 20 119 Hemiptera Delphacidae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 1 Hemiptera Gerridae 0 2 2 0 0 0 4 1 5 3 1 4 2 0 2 2 0 2 3 0 3 0 0 0 0 0 0 8 0 8 0 0 0 22 4 26 Hemiptera Hebridae 1 3 4 0 0 0 2 0 2 4 1 5 0 0 0 4 0 4 5 1 6 2 0 2 0 0 0 3 0 3 8 2 10 29 7 36 Hemiptera Hydrometridae 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 1 1 0 1 2 0 2 0 0 0 1 0 1 0 0 0 6 0 6 Hemiptera Mesoveliidae 2 0 2 0 0 0 0 0 0 0 1 1 0 0 0 3 0 3 4 0 4 1 3 4 1 1 2 5 0 5 7 1 8 23 6 29 Hemiptera Naucoridae 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 1 2 Hemiptera Nepidae 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 Hemiptera Notonectidae 0 2 2 0 0 0 2 0 2 2 0 2 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 7 2 9 Hemiptera Saldidae 0 0 0 0 0 0 2 1 3 2 0 2 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 1 1 0 0 0 5 2 7 Hemiptera Veliidae 1 0 1 0 0 0 3 0 3 5 1 6 2 1 3 4 0 4 20 0 20 33 43 76 0 0 0 14 0 14 15 10 25 97 55 152 Hemiptera UNKNOWN 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 4 0 4 4 1 5 Hirudinea Glossiphoniidae 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 3 0 0 0 0 0 0 0 0 0 1 3 4 Hymenoptera Braconidae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 1 2 0 2 Hymenoptera Formicidae 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Hymenoptera Mymaridae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 1 Isopoda Asellidae 1 0 1 0 0 0 0 0 0 0 0 0 16 0 16 36 0 36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 53 0 53 Lepidoptera Pyralidae 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 1 0 0 0 3 0 3
Appendix 35. Continued.
373
Walnut Bottom Vepco Buffalo Coal Elk Run
Leading Creek Sugar Creek Sand Run Triangle
Trus Joist MacMillan Enoch Branch Bear Run TOTAL
Order Family E O total E O total E O total E O total E O total E O total E O total E O total E O total E O total E O total E O total Neuroptera Sisuridae 0 0 0 4 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 4 Odonata Aeshnidae 0 0 0 4 0 4 0 0 0 0 0 0 1 0 1 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 6 0 6 Odonata Coenagrionidae 3 37 40 2 9 11 10 10 20 17 2 19 5 2 7 5 2 7 4 2 6 1 12 13 5 0 5 3 2 5 15 0 15 70 78 148 Odonata Cordulegastridae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 2 1 3 0 0 0 0 0 0 0 0 0 3 1 4 Odonata Corduliidae 0 1 1 0 0 0 0 1 1 3 0 3 0 0 0 0 0 0 1 0 1 2 6 8 1 0 1 0 0 0 4 0 4 11 8 19 Odonata Lestidae 0 2 2 0 1 1 0 0 0 1 0 1 1 0 1 1 2 3 0 0 0 0 0 0 1 0 1 2 0 2 0 0 0 6 5 11 Odonata Libellulidae 4 0 4 2 0 2 3 1 4 4 1 5 2 0 2 3 1 4 5 1 6 16 8 24 2 0 2 0 0 0 13 1 14 54 13 67 Odonata Protoneuridae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 2 Odonata UNKNOWN 0 0 0 1 0 1 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 3 0 3 Oligochaeta Oligochaeta 0 1 1 0 0 0 27 2 29 4 0 4 0 1 1 2 2 4 2 0 2 2 2 4 0 0 0 0 0 0 6 0 6 43 8 51 Ostracoda Ostracoda 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 Pelecypoda Sphaeriidae 0 0 0 0 0 0 1 6 7 38 20 58 7 1 8 1 3 4 0 0 0 23 2 25 1 0 1 0 0 0 2 4 6 73 36 109 Pelecypoda Unionidae 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Plecoptera Chloroperlidae 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Plecoptera UNKNOWN 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 1 Trichoptera Phryganeidae 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 UNKNOWN UNKNOWN 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 2 0 2 TOTALS 153 531 602 83 48 131 428 140 568 236 91 327 108 23 131 119 36 155 127 38 165 162 275 437 190 6 196 71 22 93 190 100 290 1867 1310 3177
Appendix 35. Continued.
374
Appendix 36. Number of individuals collected by family and wetland from emergent (E), open water (O), and scrub-shrub (SS) areas,
as well as for the entire complex (total) for 4 reference wetlands in West Virginia, 2001-2002.
Altona Marsh Elder Swamp Meadowville Muddlety TOTAL Order Family E O total E O SS total E O total E O SS total E O SS totalAmphipoda Gammaridae 3 0 3 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 Amphipoda Talitridae 3 35 38 0 0 0 0 0 0 0 6 0 0 6 9 35 0 44 Amphipoda UNKNOWN 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Arachnid Hydracarina 0 0 0 3 0 0 3 0 0 0 0 1 0 1 3 1 0 4 Arachnid Arachnid 0 0 0 1 0 0 1 0 0 0 2 0 0 2 3 0 0 3 Cladocera N/A 0 0 0 4 0 0 4 1 0 1 1 1 0 2 6 1 0 7 Coleoptera Dytiscidae 3 0 3 1 1 1 3 2 0 2 8 1 0 9 14 2 1 17 Coleoptera Elmidae 1 0 1 1 0 0 1 0 0 0 1 0 0 1 3 0 0 3 Coleoptera Haliplidae 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1 1 Coleoptera Helodidae 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 Coleoptera Hydrophilidae 1 0 1 1 0 0 1 0 0 0 0 1 0 1 2 1 0 3 Coleoptera Staphylinidae 0 0 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 1 Collembola Isotomidae 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 Collembola Poduridae 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1 1 Copepoda Cyclopoida 2 0 2 1 0 4 5 0 0 0 4 0 0 4 7 0 4 11 Diptera Ceratopogonidae 1 0 1 3 0 0 3 1 0 1 0 0 0 0 5 0 0 5 Diptera Chironomidae 0 0 0 13 4 5 22 1 0 1 41 10 6 57 55 14 11 80 Diptera Culicidae 2 0 2 14 2 2 18 1 0 1 2 0 1 3 19 2 3 24 Diptera Dixidae 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 1 Diptera Ephydridae 0 0 0 0 0 0 0 1 0 1 0 0 0 0 1 0 0 1
375
Altona Marsh Elder Swamp Meadowville Muddlety TOTAL Order Family E O total E O SS total E O total E O SS total E O SS totalDiptera Ptychopteridae 0 0 0 0 0 0 0 6 0 6 0 0 0 0 6 0 0 6 Diptera Tabanidae 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 1 Diptera UNKNOWN 0 0 0 1 0 1 2 1 0 1 0 0 0 0 2 0 1 3 Ephemeroptera Baetidae 1 1 2 0 0 6 6 4 0 4 9 2 1 12 14 3 7 24 Ephemeroptera Caenidae 0 0 0 0 0 0 0 0 0 0 7 37 1 45 7 37 1 45 Ephemeroptera Siphlonuridae 0 0 0 0 0 0 0 9 0 9 0 1 0 1 9 1 0 10 Ephemeroptera UNKNOWN 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 1 0 1 Gastropoda Lymnaedae 4 2 6 0 0 0 0 0 0 0 0 0 0 0 4 2 0 6 Gastropoda Physidae 10 2 12 0 0 0 0 0 0 0 0 0 0 0 10 2 0 12 Gastropoda Planorbidae 5 0 5 0 0 1 1 0 0 0 16 4 1 21 21 4 2 27 Gastropoda Pomatiopsidae 3 0 3 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 Gastropoda Viviparidae 17 4 21 0 0 0 0 0 0 0 11 4 0 15 28 8 0 36 Hemiptera Corixidae 0 2 2 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 Hemiptera Delphacidae 0 0 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 1 Hemiptera Gerridae 0 1 1 0 0 0 0 0 0 0 3 1 0 4 3 2 0 5 Hemiptera Hebridae 0 0 0 0 0 0 0 1 0 1 2 0 0 2 3 0 0 3 Hemiptera Hydrometridae 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 1 Hemiptera Mesoveliidae 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 1 Hemiptera Notonectidae 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 Hemiptera Veliidae 0 0 0 0 0 1 1 1 0 1 8 29 0 37 9 29 1 39 Isopoda Asellidae 25 1 26 0 0 0 0 15 0 15 74 0 0 74 114 1 0 115Neuroptera Sisuridae 0 0 0 0 0 0 0 1 0 1 0 0 0 0 1 0 0 1 Odanata Coenagrionidae 3 0 3 1 0 0 1 0 0 0 11 8 0 19 15 8 0 23 Odanata Cordulegastridae 0 0 0 0 0 0 0 0 0 0 2 0 0 2 2 0 0 2
Appendix 36. Continued.
376
Altona Marsh Elder Swamp Meadowville Muddlety TOTAL Order Family E O total E O SS total E O total E O SS total E O SS totalOdanata Corduliidae 0 0 0 0 1 0 1 0 0 0 0 12 0 12 0 13 0 13 Odanata Libellulidae 0 0 0 1 0 0 1 0 0 0 3 2 0 5 4 2 0 6 Odanata Protoneuridae 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 1 0 1 Oligochaeta Oligochaeta 0 0 0 3 0 0 3 3 0 3 0 0 0 0 6 0 0 6 Ostracoda Podocopa 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 1 Pelecypoda Sphaeriidae 39 2 41 1 0 0 1 2 0 2 16 0 1 17 58 2 1 61 Plecoptera Nemouridae 0 0 0 0 0 0 0 1 0 1 0 0 0 0 1 0 0 1 Plecoptera Perlodidae 0 0 0 0 0 0 0 2 0 2 0 0 0 0 2 0 0 2 Trichoptera Hydrophilidae 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 UNKNOWN UNKNOWN 0 0 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 1
TOTALS 126 52 178 52 8 23 83 53 0 53 232 116 11 359 463 176 34 673
Appendix 36. Continued.
377
Appendix 37. Species list of all birds sampled inside and outside 50 m radius plots
(number of birds per point count) in 11 mitigation and 4 natural wetlands in West
Virginia, 2001-2002.
Mitigation Natural Common Name Scientific Name x SE x SE Great Blue Heron Ardea herodias 1.7 0.7 0.3 0.0 Green Heron Butorides virescens 2.1 0.3 1.0 0.0 Turkey Vulture Cathartes aura 2.0 4.3 3.0 1.1 Canada Goose Branta canadensis 20.3 14.8 10.8 10.3 Muscovy Duck Cairina moschata 0.3 0.0 0 0 Green-winged Teal Anas crecca 0.1 0.0 0 0 Black Duck Anas rubripes 0.1 0.0 0 0 Wood Duck Aix sponsa 9.0 4.9 0 0 Mallard Anas platyrhynchos 7.7 3.2 1 0.3 Red-shouldered Hawk Buteo lineatus 0.0 0.0 0.25 0 Red-tailed Hawk Buteo jamaicensis 0.1 0.0 0 0 Ruffed Grouse Bonasa umbellus 0.1 0.0 0 0 Wild Turkey Meleagris gallopavo 0.3 0.2 0.5 0 Northern Bobwhite Colinus virginianus 0.0 0.0 0.25 0 Virginia Rail Rallus limicola 0.1 0.0 0 0 Sora Porzana carolina 0.5 0.0 0 0 Killdeer Charadrius vociferus 1.5 0.8 0.75 0.4 Spotted Sandpiper Actitis macularia 0.5 0.3 0.25 0 American Woodcock Scolopax minor 0.0 0.0 0.5 0 Mourning Dove Zenaida macroura 2.4 1.7 4.5 0 Yellow-billed Cuckoo Coccyzus americanus 1.8 0.5 0.75 0 Chimney Swift Chaetura pelagica 0.5 0.2 2.25 1 Ruby-throated Hummingbird Archilochus colubris 0.3 0.0 0 0 Belted Kingfisher Ceryle alcyon 1.4 0.3 0.25 0 Red-bellied Woodpecker Melanerpes carolinus 1.3 0.5 3 3.5 Red-headed Woodpecker Melanerpes erythrocephalus 0.0 0.0 0.25 0 Downy Woodpecker Picoides pubescens 1.5 0.6 0 0 Northern Flicker Colaptes auratus 2.1 0.7 1.25 0.4 Pileated Woodpecker Dryocopus pileatus 1.9 0.7 1 0.3 Eastern Wood-Pewee Contopus virens 1.5 0.7 1 0.3 Acadian Flycatcher Empidonax virescens 1.6 1.4 1.5 1.4 Alder Flycatcher Empidonax alnorum 0.8 0.3 3.75 1.7
378
Mitigation Natural Common Name Scientific Name x SE x SE Willow Flycatcher Empidonax traillii 4.3 1.8 10.5 2.9 Least Flycatcher Empidonax minimus 0.3 0.0 0 0 Eastern Phoebe Sayornis phoebe 0.4 0.0 0 0 Great Crested Flycatcher Myiarchus crinitus 1.2 1.5 0.5 0 Olive-sided Flycatcher Contopus borealis 0.0 0.0 0.25 0 Eastern Kingbird Tyrannus tyrannus 1.5 0.6 1.75 0.4 White-eyed Vireo Vireo griseus 0.5 0.3 2 0.0 Yellow-throated Vireo Vireo flavifrons 0.6 0.1 0.5 0.0 Warbling Vireo Vireo gilvus 0.3 0.0 0.25 0.0 Red-eyed Vireo Vireo olivaceus 7.3 2.7 4 1.6 Blue Jay Cyanocitta cristata 2.5 0.9 3 1.2 American Crow Corvus brachyrhynchos 7.1 1.0 8 1.8 Common Raven Corvus corax 0.0 0.0 1.25 0.0 Tree Swallow Tachycineta bicolor 11.4 2.3 4.5 2.3 Northern Rough-winged Swallow Stelgidopteryx serripennis 1.5 0.7 0 0 Barn Swallow Hirundo rustica 5.7 3.7 3.5 1.3 Black-capped Chickadee Poecile atricapillus 0.8 0.6 0.25 0 Carolina Chhickadee Parus carolinensis 0.3 0.0 0 0 Tufted Titmouse Baeolophus bicolor 3.4 1.0 2 1.0 Brown Creeper Certhia americana 0.1 0.0 0.25 0.0 Red-breasted Nuthatch Sitta canadensis 0.1 0.0 0 0 White-breasted Nuthatch Sitta carolinensis 0.8 0.4 0.25 0 Carolina Wren Thryothorus ludovicianus 0.9 0.4 0.75 0.4 House Wren Troglodytes aedon 0.3 0.2 1.5 0.0 Blue-gray Gnatcatcher Polioptila caerulea 1.7 0.9 2.25 1.8 Eastern Bluebird Sialia sialis 0.4 0.0 0 0 Veery Catharus fuscescens 0.1 0.0 0 0 Hermit Thrush Catharus guttatus 0.0 0.0 0.25 0 Swainson's Thrush Catharus ustulatus 0.0 0.0 0.5 0 Wood Thrush Hylocichla mustelina 3.5 1.6 1.25 1.1 American Robin Turdus migratorius 5.8 1.7 3.25 1.9 Gray Catbird Dumetella carolinensis 4.3 1.1 8.5 2.5 Northern Mockingbird Mimus polyglottos 1.2 0.6 2.5 1.4 Brown Thrasher Toxostoma rufum 0.7 0.2 0.75 0.4 European Starling Sturnus vulgaris 18.3 9.9 25.75 35.0Cedar Waxwing Bombycilla cedrorum 11.0 3.1 2 1.0 Blue-winged Warbler Vermivora pinus 1.0 0.7 1.5 0.0
Appendix 37. Continued.
379
Mitigation Natural Common Name Scientific Name x SE x SE Golden-winged Warbler Vermivora chrysoptera 0.1 0.0 0.75 0.0 Northern Parula Parula americana 0.2 0.0 0 0 Yellow Warbler Dendroica petechia 4.2 1.0 9.25 3.1 Magnolia Warbler Dendroica magnolia 1.2 1.2 0.25 0.0 Black-throated Green Warbler Dendroica virens 0.1 0.0 0.25 0.0 Yellow-throated Warbler Dendroica dominica 1.1 1.3 0 0.0 Black-and-white Warbler Mniotilta varia 0.3 0.2 0.75 0.0 Prairie Warbler Dendroica discolor 0.2 0.0 0 0 Cerulean Warbler Dendroica cerulea 0.5 0.0 0 0 Prothonotary Warbler Protonotaria citrea 0.1 0.0 0 0 American Redstart Setophaga ruticilla 0.5 0.6 0 0 Worm-eating Warbler Helmitheros vermivorus 1.6 1.3 0.25 0 Ovenbird Seiurus aurocapillus 0.7 0.6 1.25 0.4 Kentucky Warbler Oporornis formosus 0.1 0.0 0 0.0 Common Yellowthroat Geothlypis trichas 10.0 2.3 13.5 2.9 Scarlet Tanager Piranga olivacea 2.3 1.2 1 0.7 Eastern Towhee Pipilo erythrophthalmus 4.7 1.4 3.75 1.3 Chipping Sparrow Spizella passerina 2.2 2.1 1 0.0 Field Sparrow Spizella pusilla 3.4 1.0 1.75 1.8 Grasshopper Sparrow Ammodramus bairdii 0.1 0.0 0 0 Song Sparrow Melospiza melodia 17.3 4.2 24.75 3.7 Savannah Sparrow Passerculus sandwichensis 0.5 0.3 1.25 0.0 Swamp Sparrow Melospiza georgiana 1.7 2.3 7.5 9.9 Vesper Sparrow Pooecetes gramineus 0.1 0.0 0 0 Dark-eyed Junco Junco hyemalis 0.5 0.3 0 0 Northern Cardinal Cardinalis cardinalis 5.1 1.8 6 4.8 Rose-breasted Grosbeak Pheucticus ludovicianus 0.1 0.0 0.25 0 Indigo Bunting Passerina cyanea 7.7 2.7 5.75 3.5 Red-winged Blackbird Agelaius phoeniceus 52.4 12.1 73 27.9Boat-tailed Grackle Quiscalus major 0.0 0.0 0.25 0.0 Common Grackle Quiscalus quiscula 2.3 0.9 0 0 Brown-headed Cowbird Molothrus ater 0.2 0.0 0 0 Baltimore Oriole Icterus galbula 0.9 0.2 0.75 0 Orchard Oriole Icterus spurius 0.1 0.0 0 0 American Goldfinch Carduelis tristis 7.0 1.3 6 3.7 House Sparrow Passer domesticus 0.3 0.0 0 0
Appendix 37. Continued.
380
Appendix 38. Number of birds sampled inside 50 m radius plots (I), outside plots (O) and totals for 11 mitigation wetlands in West
Virginia, 2001-2002.
Walnut Bottom Vepco
Buffalo Coal Elk Run
Leading Creek
Sugar Creek Sand Run Triangle
Trus Joist MacMillan
Enoch Branch Bear Run TOTAL
Common Name Scientific Name I O total I O total I O total I O total I O total I O total I O total I O total I O total I O total I O total I O total Great Blue Heron Ardea herodias 5 0 5 0 0 0 0 1 1 0 1 1 6 1 7 0 0 0 0 1 1 0 0 0 3 0 3 0 1 1 0 0 0 14 5 19 Green Heron Butorides virescens 0 2 2 0 0 0 1 1 2 2 0 2 2 1 3 0 0 0 0 0 0 1 3 4 0 3 3 4 1 5 2 0 2 10 11 21 Turkey Vulture Cathartes aura 0 21 21 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 22 22 Canada Goose Branta canadensis 89 0 89 0 0 0 57 61 118 10 0 10 2 0 2 7 0 7 3 0 3 0 0 0 0 0 0 0 0 0 0 1 1 0 62 230 Muscovy Duck Cairina moschata 3 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 3 Green-winged Teal Anas crecca 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 1 Black Duck Anas rubripes 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Wood Duck Aix sponsa 38 1 39 0 0 0 1 0 1 0 0 0 37 0 37 1 0 1 0 0 0 6 0 6 10 0 10 3 1 4 8 1 1 95 3 98 Mallard Anas platyrhynchos 20 8 28 4 1 5 10 7 17 0 0 0 24 0 24 0 2 2 0 0 0 3 1 4 3 1 4 0 0 0 1 0 1 65 20 85 Red-tailed Hawk Buteo jamaicensis 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 1 Ruffed Grouse Bonasa umbellus 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 1 Wild Turkey Meleagris gallopavo 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 3 Virginia Rail Rallus limicola 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Sora Porzana carolina 0 0 0 0 0 0 4 2 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 2 6 Killdeer Charadrius vociferus 1 0 1 1 0 1 2 2 4 0 0 0 2 1 3 0 0 0 0 0 0 0 0 0 3 4 7 0 0 0 0 0 0 9 7 16 Spotted Sandpiper Actitis macularia 0 0 0 2 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 3 0 0 0 1 0 1 7 0 7 Mourning Dove Zenaida macroura 1 1 2 0 0 0 0 1 1 0 0 0 0 6 6 0 0 0 0 0 0 1 0 1 7 8 15 0 0 0 0 1 1 9 17 26 Yellow-billed Cuckoo Coccyzus americanus 0 4 4 0 0 0 0 0 0 0 2 2 0 0 0 0 3 3 0 0 0 0 0 0 1 1 2 0 3 3 0 6 6 1 19 20 Chimney Swift Chaetura pelagica 0 0 0 0 0 0 2 0 2 0 0 0 1 0 1 0 0 0 0 0 0 0 2 2 0 0 0 0 0 0 0 0 0 3 2 5 Ruby-throated Hummingbird Archilochus colubris 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 1 0 1 3 0 3 Belted Kingfisher Ceryle alcyon 4 0 4 0 2 2 0 0 0 1 0 1 0 0 0 0 1 1 0 0 0 1 0 1 2 0 2 2 0 2 2 0 2 12 3 15 Red-bellied Woodpecker Melanerpes carolinus 1 0 1 0 1 1 0 0 0 0 0 0 0 2 2 0 1 1 0 1 1 0 0 0 0 0 0 1 2 3 0 5 5 2 12 14 Downy Woodpecker Picoides pubescens 0 0 0 0 0 0 0 0 0 4 0 4 0 1 1 2 4 6 0 0 0 0 0 0 0 0 0 2 0 2 2 1 3 10 6 16 Northern Flicker Colaptes auratus 0 1 1 1 2 2 0 0 0 2 1 3 0 0 0 3 5 8 2 0 2 3 0 3 1 0 1 0 2 2 1 0 1 13 10 23 Pileated Woodpecker Dryocopus pileatus 0 1 1 0 0 0 0 0 0 0 3 3 0 1 1 1 4 5 0 0 0 0 0 0 0 0 0 1 4 5 1 5 6 3 18 21 Eastern Wood-Pewee Contopus virens 0 0 0 0 0 0 0 0 0 0 2 2 0 1 1 0 4 4 0 0 0 0 0 0 0 0 0 0 2 2 2 5 7 2 14 16 Acadian Flycatcher Empidonax virescens 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 2 0 2 2 2 4 0 0 0 0 0 0 0 0 0 5 6 11 10 8 18
381
Walnut Bottom Vepco
Buffalo Coal Elk Run
Leading Creek
Sugar Creek Sand Run Triangle
Trus Joist MacMillan
Enoch Branch Bear Run TOTAL
Common Name Scientific Name I O total I O total I O total I O total I O total I O total I O total I O total I O total I O total I O total I O total Alder Flycatcher Empidonax alnorum 0 0 0 1 1 2 0 3 3 4 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 4 9 Willow Flycatcher Empidonax traillii 0 0 0 0 1 1 7 1 8 0 1 1 11 5 16 5 3 8 0 0 0 0 0 0 11 2 13 0 0 0 0 0 0 34 13 47 Least Flycatcher Empidonax minimus 0 0 0 0 0 0 0 0 0 0 3 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 3 Eastern Phoebe Sayornis phoebe 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 0 0 0 2 0 2 4 0 4 Great Crested Flycatcher Myiarchus crinitus 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 0 0 0 0 0 0 0 0 0 1 0 1 7 3 10 10 3 13 Eastern Kingbird Tyrannus tyrannus 1 1 2 0 0 0 0 0 0 6 0 6 0 1 1 0 1 1 1 1 2 1 0 1 4 0 4 0 0 0 0 0 0 13 4 17 White-eyed Vireo Vireo griseus 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 2 0 0 0 0 0 0 0 0 0 2 1 3 1 0 1 4 2 6 Yellow-throated Vireo Vireo flavifrons 0 0 0 0 1 1 0 0 0 0 1 1 1 0 1 0 0 0 1 0 1 0 0 0 0 0 0 0 1 1 2 0 2 4 3 7 Warbling Vireo Vireo gilvus 1 0 1 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 3 0 3 Red-eyed Vireo Vireo olivaceus 1 0 1 3 6 9 1 0 1 0 1 1 13 1 14 7 5 12 4 1 5 1 2 3 1 1 2 2 0 2 21 9 30 54 26 80 Blue Jay Cyanocitta cristata 0 0 0 0 1 1 0 0 0 0 0 0 0 2 2 1 5 6 0 1 1 1 1 2 0 1 1 1 5 6 2 6 8 5 22 27 American Crow Corvus brachyrhynchos 0 9 9 0 5 5 1 6 7 0 3 3 0 12 12 0 8 8 0 4 4 0 5 5 0 5 5 0 7 7 1 12 13 2 76 78 Tree Swallow Tachycineta bicolor 15 2 17 5 1 6 17 4 21 23 0 23 4 4 8 13 0 13 21 0 21 2 0 2 9 2 11 0 0 0 3 0 3 112 13 125 Northern Rough-winged Swallow Stelgidopteryx serripennis 6 1 7 0 0 0 0 0 0 0 0 0 2 0 2 0 0 0 1 0 1 2 0 2 2 0 2 0 0 0 2 0 2 15 1 16 Barn Swallow Hirundo rustica 35 0 35 0 0 0 7 0 7 0 0 0 9 0 9 0 0 0 2 0 2 0 0 0 4 0 4 6 0 6 0 0 0 63 0 63 Black-capped Chickadee Poecile atricapillus 0 0 0 0 0 0 0 0 0 0 1 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 2 3 5 0 2 2 3 6 9 Carolina Chhickadee Parus carolinensis 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 3 2 1 3 Tufted Titmouse Baeolophus bicolor 0 1 1 0 0 0 0 1 1 0 1 1 1 5 6 1 5 6 0 1 1 0 2 2 0 1 1 2 6 8 7 3 10 11 26 37 Brown Creeper Certhia americana 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 1 Red-breasted Nuthatch Sitta canadensis 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 White-breasted Nuthatch Sitta carolinensis 0 0 0 0 0 0 0 0 0 1 1 2 0 0 0 0 4 4 0 0 0 0 0 0 1 0 1 0 0 0 2 0 2 4 5 9 Carolina Wren Thryothorus ludovicianus 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 2 0 2 1 1 2 1 0 1 3 1 4 8 2 10 House Wren Troglodytes aedon 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 2 0 2 0 0 0 0 0 0 3 0 3 Blue-gray Gnatcatcher Polioptila caerulea 0 0 0 0 0 0 0 0 0 0 0 0 4 1 5 0 1 1 1 0 1 1 0 1 0 0 0 2 1 3 7 1 8 15 4 19 Eastern Bluebird Sialia sialis 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 4 4 0 4 Veery Catharus fuscescens 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 Wood Thrush Hylocichla mustelina 0 0 0 0 2 2 0 0 0 0 1 1 0 0 0 1 7 8 1 0 1 0 2 2 2 0 2 1 5 6 5 11 16 10 28 38 American Robin Turdus migratorius 0 0 0 3 2 5 0 1 1 8 7 15 8 8 16 1 0 1 0 1 1 8 1 9 7 3 10 1 2 3 0 3 3 36 28 64 Gray Catbird Dumetella carolinensis 0 0 0 0 0 0 1 0 1 3 1 4 11 2 13 0 4 4 0 0 0 4 0 4 7 0 7 5 2 7 4 3 7 35 12 47 Northern Mockingbird Mimus polyglottos 1 2 3 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 1 2 5 1 6 0 0 0 1 0 1 9 4 13 Brown Thrasher Toxostoma rufum 0 0 0 0 0 0 0 1 1 0 0 0 1 0 1 1 0 1 0 0 0 0 0 0 0 1 1 3 0 3 0 1 1 5 3 8 European Starling Sturnus vulgaris 2 1 3 1 2 3 5 0 5 1 1 2 0 21 21 0 3 3 3 0 3 28 37 65 43 52 95 0 1 1 0 0 0 83 118 201 Cedar Waxwing Bombycilla cedrorum 0 0 0 2 0 2 6 0 6 5 0 5 20 10 30 4 3 7 3 19 22 5 16 21 3 0 3 0 4 4 3 18 21 51 70 121 Blue-winged Warbler Vermivora pinus 0 0 0 0 0 0 0 0 0 0 1 1 0 1 1 3 3 6 0 0 0 0 0 0 0 0 0 1 0 1 2 0 2 6 5 11
Appendix 38. Continued.
382
Walnut Bottom Vepco
Buffalo Coal Elk Run
Leading Creek
Sugar Creek Sand Run Triangle
Trus Joist MacMillan
Enoch Branch Bear Run TOTAL
Common Name Scientific Name I O total I O total I O total I O total I O total I O total I O total I O total I O total I O total I O total I O total Golden-winged Warbler Vermivora chrysoptera 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Northern Parula Parula americana 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 1 0 1 0 0 0 1 1 2 Yellow Warbler Dendroica petechia 3 2 5 0 0 0 2 1 3 7 0 7 10 0 10 6 2 8 3 1 4 0 1 1 5 1 6 1 0 1 1 0 1 38 8 46 Magnolia Warbler Dendroica magnolia 0 0 0 2 7 9 0 0 0 1 1 2 0 0 0 0 0 0 1 0 1 0 1 1 0 0 0 0 0 0 0 0 0 4 9 13 Black-throated Green Warbler Dendroica virens 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 Yellow-throated Warbler Dendroica dominica 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1 1 2 0 0 0 0 0 0 7 2 9 8 4 12 Prairie Warbler Dendroica discolor 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 1 2 Cerulean Warbler Dendroica cerulea 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 3 6 3 3 6 Prothonotary Warbler Protonotaria citrea 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Black-and-white Warbler Mniotilta varia 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 1 0 1 3 0 3 American Redstart Setophaga ruticilla 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 3 1 4 4 1 5 Worm-eating Warbler Helmitheros vermivorus 0 0 0 0 1 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 6 4 6 10 4 14 18 Ovenbird Seiurus aurocapillus 0 0 0 1 4 5 0 0 0 0 0 0 0 0 0 0 2 2 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1 7 8 Kentucky Warbler Oporornis formosus 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 1 Common Yellowthroat Geothlypis trichas 0 1 1 4 5 9 3 2 5 6 2 8 20 8 28 15 2 17 0 0 0 9 0 9 8 0 8 4 6 10 12 3 15 81 29 110 Scarlet Tanager Piranga olivacea 0 0 0 0 1 1 0 0 0 0 0 0 1 2 3 2 2 4 1 0 1 0 0 0 0 0 0 1 3 4 5 7 12 10 15 25 Eastern Towhee Pipilo erythrophthalmus 0 1 1 0 3 3 0 0 0 0 1 1 4 2 6 4 2 6 0 2 2 1 2 3 2 2 4 9 2 11 9 6 15 29 23 52 Chipping Sparrow Spizella passerina 0 0 0 1 0 1 1 0 1 2 1 3 0 0 0 0 0 0 0 0 0 1 1 2 0 0 0 0 0 0 5 12 17 10 14 24 Field Sparrow Spizella pusilla 1 4 5 0 5 5 2 7 9 0 0 0 0 5 5 1 9 10 0 0 0 0 1 1 0 0 0 1 1 2 0 0 0 5 32 37 Grasshopper Sparrow Ammodramus bairdii 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Song Sparrow Melospiza melodia 8 3 11 12 3 15 11 1 12 2 3 5 34 16 50 22 8 30 2 1 3 9 0 9 14 0 14 10 1 11 24 6 30 148 42 190 Savannah Sparrow Passerculus sandwichensis 0 0 0 3 0 3 0 1 1 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 1 5 Swamp Sparrow Melospiza georgiana 0 0 0 4 0 4 10 5 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 5 19 Vesper Sparrow Pooecetes gramineus 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Dark-eyed Junco Junco hyemalis 1 0 1 0 0 0 0 0 0 0 0 0 2 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 3 6 0 6 Northern Cardinal Cardinalis cardinalis 0 1 1 0 0 0 0 0 0 0 0 0 6 6 12 3 5 8 1 1 2 3 3 6 4 1 5 0 3 3 7 12 19 24 32 56 Rose-breasted Grosbeak Pheucticus ludovicianus 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 Indigo Bunting Passerina cyanea 1 1 2 0 1 1 0 0 0 3 1 4 7 2 9 15 1 16 1 1 2 2 2 4 2 0 2 11 8 19 19 7 26 61 24 85 Red-winged Blackbird Agelaius phoeniceus 54 14 68 7 1 8 64 74 138 14 1 15 63 20 83 22 4 26 26 8 34 76 13 89 60 4 64 10 2 12 38 1 39 434 142 576 Common Grackle Quiscalus quiscula 10 0 10 0 0 0 0 0 0 2 2 4 0 5 5 0 0 0 0 0 0 0 0 0 3 0 3 1 2 3 0 0 0 16 9 25 Brown-headed Cowbird Molothrus ater 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 2 0 2 Baltimore Oriole Icterus galbula 0 0 0 0 0 0 0 0 0 1 0 1 3 0 3 1 0 1 2 0 2 2 0 2 0 0 0 0 0 0 1 0 1 10 0 10 Orchard Oriole Icterus spurius 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 American Goldfinch Carduelis tristis 12 0 12 1 2 3 0 4 4 2 0 2 12 3 15 6 2 8 1 0 1 5 2 7 3 4 7 7 0 7 11 0 11 60 17 77 House Sparrow Passer domesticus 0 0 0 0 0 0 0 0 0 0 0 0 3 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 3
Appendix 38. Continued.
383
Appendix 39. Number of birds sampled inside 50 m radius plots (I), outside plots (O) and totals for 4 natural wetlands in West
Virginia, 2001-2002.
Altona Marsh
Elder Swamp Meadowville Muddlety TOTAL
Common Name Scientific Name I O total I O total I O total I O total I O totalGreat Blue Heron Ardea herodias 0 0 0 0 0 0 0 0 0 1 0 1 1 0 1 Green Heron Butorides virescens 0 0 0 0 0 0 0 2 2 2 0 2 2 2 4 Turkey Vulture Cathartes aura 0 2 2 0 6 6 0 1 1 0 3 3 0 12 12Canada Goose Branta canadensis 5 31 36 0 0 0 0 7 7 0 0 0 5 38 43Wood Duck Aix sponsa 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Mallard Anas platyrhynchos 0 1 1 1 1 2 0 0 0 0 1 1 1 3 4 Red-shouldered Hawk Buteo lineatus 0 0 0 0 0 0 0 0 0 1 0 1 1 0 1 Wild Turkey Meleagris gallopavo 0 0 0 0 0 0 0 2 2 0 0 0 0 2 2 Northern Bobwhite Colinus virginianus 0 1 1 0 0 0 0 0 0 0 0 0 0 1 1 Killdeer Charadrius vociferus 0 1 1 0 2 2 0 0 0 0 0 0 0 3 3 Spotted Sandpiper Actitis macularia 0 0 0 1 0 1 0 0 0 0 0 0 1 0 1 American Woodcock Scolopax minor 0 0 0 0 0 0 2 0 2 0 0 0 2 0 2 Mourning Dove Zenaida macroura 3 15 18 0 0 0 0 0 0 0 0 0 3 15 18Yellow-billed Cuckoo Coccyzus americanus 0 1 1 0 0 0 0 1 1 0 1 1 0 3 3 Chimney Swift Chaetura pelagica 0 6 6 0 0 0 3 0 3 0 0 0 3 6 9 Belted Kingfisher Ceryle alcyon 0 0 0 0 0 0 1 0 1 0 0 0 1 0 1 Red-bellied Woodpecker Melanerpes carolinus 6 5 11 0 0 0 0 1 1 0 0 0 6 6 12Red-headed Woodpecker Melanerpes erythrocephalus 1 0 1 0 0 0 0 0 0 0 0 0 1 0 1
384
Altona Marsh
Elder Swamp Meadowville Muddlety TOTAL
Common Name Scientific Name I O total I O total I O total I O total I O totalDowny Woodpecker Picoides pubescens 1 0 1 0 0 0 0 0 0 1 0 1 2 0 2 Northern Flicker Colaptes auratus 1 2 3 0 0 0 0 2 2 0 0 0 1 4 5 Pileated Woodpecker Dryocopus pileatus 1 0 1 0 2 2 0 1 1 0 0 0 1 3 4 Eastern Wood-Pewee Contopus virens 0 2 2 0 0 0 0 1 1 0 1 1 0 4 4 Acadian Flycatcher Empidonax virescens 1 0 1 0 0 0 3 2 5 0 0 0 4 2 6 Alder Flycatcher Empidonax alnorum 0 1 1 1 6 7 0 0 0 6 1 7 7 8 15Willow Flycatcher Empidonax traillii 15 2 17 1 2 3 10 1 11 10 1 11 36 6 42Great Crested Flycatcher Myiarchus crinitus 1 0 1 0 0 0 1 0 1 0 0 0 2 0 2 Olive-sided Flycatcher Contopus borealis 0 0 0 0 1 1 0 0 0 0 0 0 0 1 1 Eastern Kingbird Tyrannus tyrannus 3 0 3 0 0 0 0 0 0 1 3 4 4 3 7 White-eyed Vireo Vireo griseus 0 0 0 0 0 0 3 1 4 3 1 4 6 2 8 Yellow-throated Vireo Vireo flavifrons 0 0 0 0 0 0 2 0 2 0 0 0 2 0 2 Warbling Vireo Vireo gilvus 0 0 0 0 1 1 0 0 0 0 0 0 0 1 1 Red-eyed Vireo Vireo olivaceus 1 1 2 3 2 5 5 3 8 0 1 1 9 7 16Blue Jay Cyanocitta cristata 0 5 5 0 1 1 1 0 1 3 2 5 4 8 12American Crow Corvus brachyrhynchos 0 6 6 0 4 4 2 8 10 3 9 12 5 27 32Common Raven Corvus corax 0 0 0 0 5 5 0 0 0 0 0 0 0 5 5 Tree Swallow Tachycineta bicolor 10 1 11 2 0 2 1 0 1 4 0 4 17 1 18Barn Swallow Hirundo rustica 0 2 2 0 0 0 0 7 7 3 2 5 3 11 14Black-capped Chickadee Poecile atricapillus 0 0 0 1 0 1 0 0 0 0 0 0 1 0 1 Tufted Titmouse Baeolophus bicolor 2 0 2 0 0 0 0 1 1 1 4 5 3 5 8
Appendix 39. Continued.
385
Altona Marsh
Elder Swamp Meadowville Muddlety TOTAL
Common Name Scientific Name I O total I O total I O total I O total I O totalBrown Creeper Certhia americana 0 0 0 1 0 1 0 0 0 0 0 0 1 0 1 White-breasted Nuthatch Sitta carolinensis 0 0 0 0 0 0 0 1 1 0 0 0 0 1 1 Carolina Wren Thryothorus ludovicianus 1 1 2 0 0 0 0 0 0 0 1 1 1 2 3 House Wren Troglodytes aedon 4 2 6 0 0 0 0 0 0 0 0 0 4 2 6 Blue-gray Gnatcatcher Polioptila caerulea 0 0 0 0 0 0 7 0 7 1 1 2 8 1 9 Hermit Thrush Catharus guttatus 0 0 0 0 1 1 0 0 0 0 0 0 0 1 1 Swainson's Thrush Catharus ustulatus 0 0 0 0 2 2 0 0 0 0 0 0 0 2 2 Wood Thrush Hylocichla mustelina 0 0 0 0 0 0 1 3 4 0 1 1 1 4 5 American Robin Turdus migratorius 8 1 9 0 2 2 1 0 1 0 1 1 9 4 13Gray Catbird Dumetella carolinensis 10 2 12 0 1 1 9 2 11 9 1 10 28 6 34Northern Mockingbird Mimus polyglottos 2 5 7 0 0 0 2 1 3 0 0 0 4 6 10Brown Thrasher Toxostoma rufum 0 0 0 0 0 0 1 0 1 1 1 2 2 1 3 European Starling Sturnus vulgaris 0 2 2 0 0 0 0 0 0 101 0 101 101 2 103Cedar Waxwing Bombycilla cedrorum 0 5 5 1 0 1 1 0 1 0 1 1 2 6 8 Blue-winged Warbler Vermivora pinus 0 0 0 0 0 0 3 0 3 2 1 3 5 1 6 Golden-winged Warbler Vermivora chrysoptera 0 0 0 0 0 0 3 0 3 0 0 0 3 0 3 Yellow Warbler Dendroica petechia 9 1 10 1 1 2 8 0 8 15 2 17 33 4 37Magnolia Warbler Dendroica magnolia 0 0 0 0 0 0 1 0 1 0 0 0 1 0 1 Black-throated Green Warbler Dendroica virens 0 1 1 0 0 0 0 0 0 0 0 0 0 1 1 Yellow-throated Warbler Dendroica dominica 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Black-and-white Warbler Mniotilta varia 0 0 0 0 0 0 0 0 0 1 2 3 1 2 3
Appendix 39. Continued.
386
Altona Marsh
Elder Swamp Meadowville Muddlety TOTAL
Common Name Scientific Name I O total I O total I O total I O total I O totalWorm-eating Warbler Helmitheros vermivorus 0 0 0 0 1 1 0 0 0 0 0 0 0 1 1 Ovenbird Seiurus aurocapillus 0 0 0 0 0 0 1 2 3 0 2 2 1 4 5 Common Yellowthroat Geothlypis trichas 18 3 21 4 9 13 13 0 13 4 3 7 39 15 54Scarlet Tanager Piranga olivacea 0 0 0 0 0 0 1 0 1 3 0 3 4 0 4 Eastern Towhee Pipilo erythrophthalmus 1 0 1 0 2 2 3 3 6 1 5 6 5 10 15Chipping Sparrow Spizella passerina 0 0 0 3 1 4 0 0 0 0 0 0 3 1 4 Field Sparrow Spizella pusilla 0 0 0 1 5 6 0 0 0 0 1 1 1 6 7 Song Sparrow Melospiza melodia 27 3 30 12 3 15 19 4 23 27 4 31 85 14 99Savannah Sparrow Passerculus sandwichensis 0 0 0 5 0 5 0 0 0 0 0 0 5 0 5 Swamp Sparrow Melospiza georgiana 1 0 1 19 10 29 0 0 0 0 0 0 20 10 30Northern Cardinal Cardinalis cardinalis 10 9 19 0 0 0 3 1 4 0 1 1 13 11 24Rose-breasted Grosbeak Pheucticus ludovicianus 1 0 1 0 0 0 0 0 0 0 0 0 1 0 1 Indigo Bunting Passerina cyanea 1 0 1 0 0 0 15 0 15 6 1 7 22 1 23Red-winged Blackbird Agelaius phoeniceus 101 44 145 23 8 31 21 6 27 74 15 89 219 73 292Boat-tailed Grackle Quiscalus major 0 1 1 0 0 0 0 0 0 0 0 0 0 1 1 Common Grackle Quiscalus quiscula 0 2 2 0 0 0 0 2 2 1 18 19 1 22 23Baltimore Oriole Icterus galbula 1 0 1 0 0 0 1 0 1 0 1 1 2 1 3 American Goldfinch Carduelis tristis 9 8 17 0 1 1 2 1 3 2 1 3 13 11 24
Appendix 39. Continued.
387
Appendix 40. Species lista of all frogs sampled by survey period in 11 mitigation wetlands in West Virginia (WB = Walnut Bottom,
VO = Vepco, BC = Buffalo Coal, ER = Elk Run, LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus
Joist MacMillan, EB = Enoch Branch, and BR = Bear Run), 2001-2002.
a * represents the observation of a particular species
Year 1 WB VO BC ER LC SC SR T TJM EB BR Common Name Scientific Name 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3Spring Peeper Psuedacris c. crucifer * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *Gray Treefrog Hyla chrysoscelis * * * * * * * *American Bullfrog Rana catesbeiana * * * * * * * * * * *Wood Frog Rana sylvatica * * * *Green Frog Rana clamitans melanota * * * * * * * * * * * * * * * * * * * * *American Toad Bufo a. americanus * * * * * * * * *Pickerel Frog Rana palustris * * * * * * * * * * * * * * * * Year 2 WB VO BC ER LC SC SR T TJM EB BR Common Name Scientific Name 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3Spring Peeper Psuedacris c. crucifer * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *Gray Treefrog Hyla chrysoscelis * * * * * * * * *American Bullfrog Rana catesbeiana * * * * *Wood Frog Rana sylvatica * * * * * * * *Green Frog Rana clamitans melanota * * * * * * * * * * * * * * *American Toad Bufo a. americanus * * * * * * * * *Pickerel Frog Rana palustris * * * * * * * * * * * *
388
Appendix 41. Species lista of all frogs sampled by survey period in 4 natural
wetlands in West Virginia (AM = Altona Marsh, ES = Elder Swamp, MV =
Meadowville, and MY = Muddlety), 2001-2002.
a * represents the observation of a particular species
Year 1 AM ES MV MY Common Name Scientific Name 1 2 3 1 2 3 1 2 3 1 2 3Spring Peeper Psuedacris c. crucifer * * * * * * * * * * * *Gray Treefrog Hyla chrysoscelis * *Bull Frog Rana catesbeiana * *Wood Frog Rana sylvatica * Green Frog Rana clamitans melanota * * * * * * *American Toad Bufo a. americanus * Pickerel Frog Rana palustris * * Year 2 AM ES MV MY Common Name Scientific Name 1 2 3 1 2 3 1 2 3 1 2 3Spring Peeper Psuedacris c. crucifer * * * * * * * * * * *Gray Treefrog Hyla chrysoscelis * * * *Bull Frog Rana catesbeiana *Wood Frog Rana sylvatica * * Green Frog Rana clamitans melanota * * * * *American Toad Bufo a. americanus * * Pickerel Frog Rana palustris * * *
389
Appendix 42. A comparison of actual mean values of all variables measured within the beaver,
muskrat, mink, great blue heron, red-winged blackbird, wood duck, snapping turtle, and red-
spotted newt Habitat Suitability Index models between mitigation (n = 11) and natural (n = 4)
wetlands in West Virginia, 2001-2002.
Mitigationa Naturala
HSI model variables x SE x SE F1,13 P Beaver V1: percent tree cover a. within wetland basin 0.07 0.1 2.3 1.1 4.97 0.044b. within 100 m 39.9 6.8 20.4 9.7 0.00 0.986c. within 200 m 45.1 8.0 43.2 7.3 0.02 0.904V2: percent trees 2.5-15.2 cm dbh a. within wetland basin 0.0 0.0 0.0 0.0 N/A N/A b. within 100 m 3.4 2.9 36.7 9.4 9.05 0.010c. within 200 m 11.5 4.7 21.7 7.9 0.88 0.367V3: percent shrub cover a. within wetland basin 7.5 2.0 27.8 6.3 9.06 0.010b. within 100 m 11.6 3.0 28.8 8.1 3.54 0.082c. within 200 m 12.6 2.8 22.7 6.2 1.80 0.203V4: shrub canopy height (m) a. within wetland basin 1.5 0.2 1.6 0.1 0.12 0.921b. within 100 m 2.1 0.1 1.4 0.1 8.49 0.012c. within 200 m 2.0 0.1 1.5 0.1 8.52 0.012V5: woody vegetation species compositionb a. within wetland basin A: 4; B: 7 N/A All Bs N/A N/A N/A b. within 100 m All Bs N/A All Bs N/A N/A N/A c. within 200 m All Bs N/A All Bs N/A N/A N/A V6: mean annual water fluctuationc All As N/A All As N/A N/A N/A Muskrat V1: percent emergent vegetation 48.0 6.2 59.4 10.2 0.90 0.361V2: percent year with water 100 0.0 100 0.0 N/A N/A V3: percent Scirpus validus, S. americanus 13.6 3.9 42.8 14.1 8.10 0.014Typha latifolia Mink V1: percent year with water 100 0.0 100 0.0 N/A N/A V2: percent persistent emergent vegetation 46.9 6.0 59 10.1 1.11 0.310
390
Mitigation Natural HSI model variables x SE x SE F1,13 P V3: percent tree/shrub cover <100 m 48.2 6.0 62.1 11.8 1.40 0.258Great blue heron V1: distance between forage area 36.8 21.8 37.5 23.9 0.00 0.986 and potential nest site V2: presence of shallow, clear water with fish yes: 9; no; 2 N/A yes: 3; no: 1 N/A N/A N/A V3: 100 m foraging disturbance free zone all yes N/A all yes N/A N/A N/A V4: presence of forest within 250 m all yes N/A all yes N/A N/A N/A V5: 150, 250 m nesting disturbance free zone yes: 8; no: 3 N/A yes: 2; no: 2 N/A N/A N/A V6: distance (km) between potential 50.8 4.2 82.4 28.5 3.26 0.094 and actual/previous nest site Red-winged blackbird V1: percent broad-leaf monocots 17.2 4.4 39.9 9.9 6.02 0.029V2: percent year with water 100 0.0 100 0.0 N/A N/A V3: presence of carp 10 of 11 N/A 0 of 4 N/A N/A N/A V4: presence of Odonates yes N/A yes N/A N/A N/A V5: percent emergent vegetaion 48.0 6.2 59.4 10.2 0.90 0.361Wood duck V1: number of potential nesting cavities/0.4 ha 6.4 1.3 10 3.4 1.53 0.237V2: number of nest boxes/0.4 ha 0.1 0.1 0.0 0.0 1.41 0.257V3: density of potential nest sites (no./0.4 ha) 1.3 0.3 1.8 0.6 1.08 0.318V4: percent potential brood cover 58.5 0.8 83.2 6.4 4.64 0.051V5: percent potential winter cover 47.5 0.8 86.8 7.8 7.00 0.020V6: distance b/w cover types 0.0 0.0 0.0 0.0 N/A N/A V7: percent area optimum nesting habitat 25.0 0.8 36.3 12.5 1.14 0.315V8: percent area optimum brood habitat 82.7 0.8 61.5 20.8 1.51 0.240Snapping turtle V1: water temperature (°C) during summer 27.7 0.9 23.8 2.5 3.52 0.083V2: water velocity (cm/s) during summer 0.003 0.0 0.0 0.0 0.99 0.339V3: percent vegetation in littoral zone 72.9 4.5 62.8 11.0 1.06 0.323V4: water depth vs. ice depth all yes N/A all yes N/A N/A N/A V5: percent silt in substrate 24.3 2.1 18.9 3.3 1.79 0.204V6: distance (m) to small stream 12.3 4.9 0.0 0.0 2.19 0.162V7: distance (m) to permanent water 0.0 0.0 0.0 0.0 N/A N/A Red-spotted newt V1: percent water < 2m deep 100 0.0 100 0.0 N/A N/A V2: percent vegetation in littoral zone 72.9 4.5 62.8 11.0 1.06 0.323V3: distance (m) to forest 14.5 6.8 0.0 0.0 1.59 0.229
Appendix 42. Continued.
391
Appendix 42. Continued. a The same letter following means indicates no difference between wetland types (P > 0.05). bA = woody vegetation dominated by aspen (Populus spp.), willow (Salix spp.), cottonwood (Populus spp.), or alder (Alnus spp.) B = woody vegetation dominated by other deciduous species C = woody vegetation dominated by coniferous species cA = small fluctuations with no effect on burrow/lodge entrances B = moderate fluctuations with some effect on burrow/lodge entrances C = extreme fluctuations or water absent for part of year
392
Appendix 43. Actual and Suitability index (SI) mean values for variables measured within the beaver, muskrat, mink, great blue
heron, red-winged blackbird, wood duck, snapping turtle, and red-spotted newt Habitat Suitability Index models between mitigation (n
= 11) and natural (n = 4) wetlands in West Virginia, 2001-2002.
Mitigationa Naturala HSI model variables Actual x SE SI SE Actual x SE SI SETotal SI value: all species combined 0.56a 0.02 0.60a 0.03Beaver Total SI value 0.74a 0.1 1.0b 0.0V1: percent tree cover a. within wetland basin 0.07 0.1 0.01 0.0 2.3 1.1 0.05 0.0b. within 100 m 39.9 6.8 0.75 0.1 20.4 9.7 0.63 0.1c. within 200 m 45.1 8.0 0.72 0.1 43.2 7.3 0.78 0.1V2: percent trees 2.5-15.2 cm dbh a. within wetland basin 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0b. within 100 m 3.4 2.9 0.15 0.1 36.7 9.4 0.49 0.1c. within 200 m 11.5 4.7 0.22 0.1 21.7 7.9 0.27 0.1V3: percent shrub cover a. within wetland basin 7.5 2.0 0.16 0.0 27.8 6.3 0.55 0.1b. within 100 m 11.6 3.0 0.29 0.1 28.8 8.1 0.56 0.1c. within 200 m 12.6 2.8 0.30 0.1 22.7 6.2 0.51 0.1V4: shrub canopy height (m) a. within wetland basin 1.5 0.2 0.69 0.1 1.6 0.1 0.81 0.1
393
Mitigationa Naturala HSI model variables Actual x SE SI SE Actual x SE SI SEb. within 100 m 2.1 0.1 0.95 0.0 1.4 0.1 0.73 0.1c. within 200 m 2.0 0.1 0.95 0.0 1.5 0.1 0.74 0.0V5: woody vegetation species compositionb a. within wetland basin A: 4; B: 7 N/A 0.75 0.1 All Bs N/A 0.60 0.0b. within 100 m All Bs N/A 0.60 0.0 All Bs N/A 0.60 0.0c. within 200 m All Bs N/A 0.60 0.0 All Bs N/A 0.60 0.0V6: mean annual water fluctuationc All As N/A 1.0 0.0 All As N/A 1.0 0.0Muskrat Total SI value 0.35a 0.04 0.55a 0.1V1: percent emergent vegetation 48.0 6.2 0.81 0.1 59.4 10.2 0.92 0.03V2: percent year with water 100.0 0.0 1.0 0.0 100.0 0.0 1.0 0.0V3: percent Scirpus validus, S. americanus, Typha latifolia 13.6 3.9 0.18 0.04 42.8 14.1 0.38 0.2Mink Total SI value 0.79a 0.1 0.89a 0.04V1: percent year with water 100.0 0.0 1.0 0.0 100.0 0.0 1.0 0.0V2: percent persistent emergent vegetation 46.9 6.0 0.82 0.1 59.0 10.1 0.91 0.03V3: percent tree/shrub cover <100 m 48.2 6.0 0.66 0.1 62.1 11.8 0.82 0.1Great blue heron Total SI value 0.26a 0.02 0.23a 0.1V1: distance between forage area 36.8 21.8 1.0 0.0 37.5 23.9 1.0 and potential nest site V2: presence of shallow, clear water with fish yes: 9; no; 2 N/A 0.91 0.1 yes: 3; no: 1 N/A 0.88 0.0
Appendix 43. Continued.
394
Mitigationa Naturala Habitat model variables Actual x SE SI SE Actual x SE SI SEV3: 100 m foraging disturbance free zone all yes N/A 1.0 0.0 all yes N/A 1.0 0.1V4: presence of forest within 250 m all yes N/A 1.0 0.0 all yes N/A 1.0 0.0V5: 150, 250 m nesting disturbance free zone yes: 8; no: 3 N/A 0.80 0.2 yes: 2; no: 2 N/A 0.63 0.0V6: distance (km) between potential 50.8 4.2 0.10 1.3 82.4 28.5 0.10 0.2 and actual/previous nest site Red-winged blackbird Total SI value 0.03a 0.01 0.15b 0.1V1: percent broad-leaf monocots 17.2 4.4 0.10 0.0 39.9 9.9 0.55 0.3V2: percent year with water 100.0 0.0 1.0 0.0 100.0 0.0 1.0 0.0V3: presence of carp 10 of 11 N/A 0.92 0.1 0 of 4 N/A 1.0 0.0V4: presence of Odonates yes N/A 1.0 0.0 yes N/A 1.0 0.0V5: percent emergent vegetaion 48.0 6.2 0.42 0.1 59.4 10.2 0.60 0.2Wood duck Total SI value 0.82a 0.1 0.68a 0.1V1: number of potential nesting cavities/0.4 ha 6.4 1.3 N/A N/A 10.0 3.4 N/A N/AV2: number of nest boxes/0.4 ha 0.1 0.1 N/A N/A 0.0 0.0 N/A N/AV3: density of potential nest sites (no./0.4 ha) 1.3 0.3 0.25 0.1 1.8 0.6 0.36 0.1V4: percent potential brood cover 58.5 0.8 0.80 0.1 83.2 6.4 0.62 0.2V5: percent potential winter cover 47.5 0.8 0.80 0.1 86.8 7.8 0.47 0.3V6: distance b/w cover types 0.0 0.0 N/A N/A 0.0 0.0 N/A N/AV7: percent area optimum nesting habitat 25.0 0.8 0.81 0.1 36.3 12.5 0.98 0.03V8: percent area optimum brood habitat 82.7 0.8 0.83 0.1 61.5 20.8 0.71 0.1
Appendix 43. Continued.
395
Mitigationa Naturala Habitat model variables Actual x SE SI SE Actual x SE SI SESnapping turtle Total SI value 0.60a 0.01 0.53a 0.04V1: water temperature (°C) during summer 27.7 0.9 0.98 0.02 23.8 2.5 0.80 0.1V2: water velocity (cm/s) during summer 0.003 0.0 1.0 0.0 0.0 0.0 1.0 0.0V3: percent vegetation in littoral zone 72.9 4.5 0.73 0.1 62.8 11.0 0.63 0.1V4: water depth vs. ice depth all yes N/A 1.0 0.0 all yes N/A 1.0 0.0V5: percent silt in substrate 24.3 2.1 0.24 0.02 18.9 3.3 0.19 0.04V6: distance (m) to small stream 12.3 4.9 1.0 0.0 0.0 0.0 1.0 0.0V7: distance (m) to permanent water 0.0 0.0 1.0 0.0 0.0 0.0 1.0 0.0Red-spotted newt Total SI value 0.90a 0.1 0.80a 0.11V1: percent water < 2m deep 100.0 0.0 1.0 0.0 100.0 0.0 1.0 0.0V2: percent vegetation in littoral zone 72.9 4.5 0.92 0.1 62.8 11.0 0.80 0.1V3: distance (m) to forest 14.5 6.8 0.98 0.04 0.0 0.0 1.00 0.0a The same letter following means indicates no difference between wetland types (P > 0.05). bA = woody vegetation dominated by aspen (Populus spp.), willow (Salix spp.), cottonwood (Populus spp.), or alder (Alnus spp.) B = woody vegetation dominated by other deciduous species C = woody vegetation dominated by coniferous species cA = small fluctuations with no effect on burrow/lodge entrances B = moderate fluctuations with some effect on burrow/lodge entrances C = extreme fluctuations or water absent for part of year
Appendix 43. Continued.
396
Appendix 44. Variable measurements and Suitability Index (SI) values for the red-
winged blackbird Habitat Suitability Index model for mitigation (n = 11) and natural
(n = 4) wetlands in West Virginia (mitigation sites: WB = Walnut Bottom, VO =
Vepco, BC = Buffalo Coal, ER = Elk Run, LC = Leading Creek, SC = Sugar Creek,
SR = Sand Run, T = Triangle, TJM = Trus Joist MacMillan, EB = Enoch Branch, and
BR = Bear Run; natural sites: AM = Altona Marsh, ES = Elder Swamp, MV =
Meadowville, and MY = Muddlety), 2001-2002.
V1 V2 V3 V4 V5 HSI formula % of year carp % emergent % broad- with surface absent vegetation leaved water from Odanates (persistent and (V1*V2*V3 Mitigation monocots present wetland? present? nonpersistent) *V4*V5) WB Actual 12.7 100.0 yes yes 44.6 SI 0.10 1.0 1.0 1.0 1.0 0.10 VO Actual 3.8 100.0 yes yes 66.9 SI 0.10 1.0 1.0 1.0 0.30 0.03 BC Actual 2.8 100.0 yes yes 41.5 SI 0.10 1.0 1.0 1.0 1.0 0.10 ER Actual 14.8 100.0 yes yes 22.3 SI 0.10 1.0 1.0 1.0 0.10 0.01 LC Actual 3.6 100.0 yes yes 68.8 SI 0.10 1.0 1.0 1.0 0.30 0.03 SC Actual 10.8 100.0 yes yes 81.0 SI 0.10 1.0 1.0 1.0 0.30 0.03 SR Actual 17.1 100.0 yes yes 22.4 SI 0.10 1.0 1.0 1.0 0.10 0.01 T Actual 37.6 100.0 yes yes 68.0 SI 0.10 1.0 1.0 1.0 0.30 0.03 TJM Actual 10.4 100.0 no yes 47.2 SI 0.10 1.0 0.1 1.0 1.0 0.01 EB Actual 30.4 100.0 yes yes 38.9 SI 0.10 1.0 1.0 1.0 0.1 0.01
397
V1 V2 V3 V4 V5 HSI formula % of year carp % emergent % broad- with surface absent vegetation leaved water from Odanates (persistent and (V1*V2*V3 Mitigation cont. monocots present wetland? present? nonpersistent) *V4*V5) BR Actual 45.6 100.0 yes yes 26.7 SI 0.10 1.0 1.0 1.0 0.1 0.01 Mean actual 17.2 100.0 n/a n/a 48.0 Mean SI 0.10 1.0 0.92 1.0 0.42 0.03 Natural AM Actual 59.6 100.0 yes yes 87.3 SI 1.0 1.0 1.0 1.0 0.30 0.30 ES Actual 34.6 100.0 yes yes 44.3 SI 0.1 1.0 1.0 1.0 1.0 0.10 MV Actual 14.6 100.0 yes yes 43.8 SI 0.1 1.0 1.0 1.0 1.0 0.10 MY Actual 50.9 100.0 yes yes 62.0 SI 1.0 1.0 1.0 1.0 0.1 0.10 Mean Actual 39.9 100.0 n/a n/a 59.4 Mean SI 0.55 1.0 1.0 1.0 0.60 0.15
Appendix 44. Continued.
398
Appendix 45. Variable measurements and Suitability Index (SI) values for the beaver Habitat Suitability Index model for mitigation
(n = 11) and natural (n = 4) wetlands in West Virginia (mitigation sites: WB = Walnut Bottom, VO = Vepco, BC = Buffalo Coal, ER
= Elk Run, LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus Joist MacMillan, EB = Enoch Branch,
and BR = Bear Run; natural sites: AM = Altona Marsh, ES = Elder Swamp, MV = Meadowville, and MY = Muddlety), 2001-2002.
V5 HSI formulac
V1 V2 V3 V4 Species composition V6 a/b = [(V1*V2)1/2 * V5]1/2 +
% tree cover % trees 2.5 to 15.2 cm dbh % shrub cover shrub canopy height (m) of woody vegetation a mean [(V3*V4)1/2 *V5]1/2
w/in w/in w/in w/in w/in annual c = .5[(V1*V2)1/2 * V5]1/2 +
wetland wetland wetland wetland wetland water [(V3*V4)1/2 *V5]1/2
Mitigation basin < 100 m < 200 m basin < 100 m < 200 m basin < 100 < 200 basin < 100 m < 200 m basin < 100 m < 200 m Fluctuationb a+b+c/2.5 WB Actual 0.0 26.7 22.5 0.0 26.7 53.3 0.0 0.0 0.0 n/a 2.0 1.6 B B B A SI 0.0 0.73 0.61 0.0 0.42 0.62 0.0 0.0 0.0 0.0 1.0 0.80 0.60 0.60 0.60 1 0.58 VO Actual 0.0 66.7 72.7 0.0 20.0 13.3 4.5 3.3 10.8 0.60 1.8 1.6 B B B A SI 0.0 0.92 0.85 0.0 0.4 0.30 0.01 0.08 0.26 0.30 0.92 0.80 0.60 0.60 0.60 1 1.0 BC Actual 0.0 0.0 0.0 0.0 6.7 20.0 22.1 18.3 19.2 0.60 1.4 1.7 B B B A SI 0.0 0.0 0.0 0.0 0.25 0.4 0.50 0.47 0.51 0.30 0.65 0.90 0.60 0.60 0.60 1 0.69 ER Actual 0.0 53.3 50.8 0.0 0.0 13.3 10.7 3.3 2.5 1.8 1.9 2.0 B B B A SI 0.0 1.0 1.0 0.0 0.0 0.3 0.23 0.08 0.02 0.92 0.98 1.0 0.60 0.60 0.60 1 0.49 LC Actual 0.0 25.0 30.5 0.0 13.6 6.7 2.8 20.0 22.5 1.1 1.9 1.8 A B B A SI 0.0 0.66 0.71 0.0 0.31 0.25 0.02 0.50 0.55 0.60 0.98 0.92 1.0 0.60 0.60 1 1.0 SC Actual 0.0 60.0 65.5 0.0 0.0 6.7 11.0 8.0 11.0 1.9 1.9 2.0 B B B A SI 0.0 1.0 0.91 0.0 0.0 0.25 0.25 0.22 0.26 0.98 0.98 1.0 0.60 0.60 0.60 1 0.63 SR Actual 0.50 32.5 59.4 0.0 0.0 0.0 4.9 3.8 3.8 1.8 2.4 2.3 B B B A SI 0.0 0.85 1.0 0.0 0.0 0.0 0.1 0.09 0.04 0.92 1.0 1.0 0.60 0.60 0.60 1 0.51 T Actual 0.0 33.8 27.5 0.0 0.0 0.0 8.0 20 15 1.9 1.9 1.9 B B B A SI 0.0 0.83 0.78 0.0 0.0 0.0 0.20 0.50 0.38 0.98 0.98 0.98 0.60 0.60 0.60 1 0.78 TJM Actual 0.0 18.8 17.5 0.0 6.7 13.3 14.1 10.0 13.8 1.7 2.5 2.4 A B B A SI 0.0 0.51 0.43 0.0 0.25 0.30 0.30 0.25 0.33 0.90 1.0 1.0 1.0 0.60 0.60 1 1.0
399
Appendix V5 HSI formulac
V1 V2 V3 V4 Species composition V6 a/b = [(V1*V2)1/2 * V5]1/2 +
% tree cover % trees 2.5 to 15.2 cm dbh % shrub cover shrub canopy height (m) of woody vegetation a mean [(V3*V4)1/2 *V5]1/2
w/in w/in w/in w/in w/in annual c = .5[(V1*V2)1/2 * V5]1/2 +
wetland wetland wetland wetland wetland water [(V3*V4)1/2 *V5]1/2 Mitigation cont. basin < 100 m < 200 m basin < 100 m < 200 m basin < 100 < 200 basin < 100 m < 200 m basin < 100 m < 200 m fluctuationb a+b+c/2.5 EB Actual 0 48.8 69.8 0 0 0 3.8 32.5 31.7 1.7 2.6 2.3 A B B A SI 0 1.0 0.88 0 0 0 0.06 0.77 0.80 0.90 1.0 1.0 1.0 0.60 0.60 1.0 0.87 BR Actual 0.30 73.8 79.8 0 0 0 0.70 8.8 8.8 1.5 2.4 2.5 A B B A SI 0 0.8 0.77 0 0 0 0.01 0.20 0.20 0.75 1.0 1.0 1.0 0.60 0.60 1.0 0.62 Mean actual 0.07 39.9 45.1 0 3.4 11.5 7.5 11.6 12.6 1.5 2.1 2.0 n/a n/a n/a n/a Mean SI 0.01 0.75 0.72 0 0.15 0.22 0.16 0.29 0.3 0.69 0.95 0.95 0.75 0.60 0.60 1.0 0.74 Natural AM Actual 7.4 25.0 23.3 0 60.0 33.3 12.3 5.0 2.5 1.9 1.7 1.6 B B B A SI 0.16 0.66 0.62 0 0.67 0.46 0.28 0.1 0.02 0.98 0.9 0.8 0.60 0.60 0.60 1.0 1.0 ES Actual 1.7 3.3 22.5 0 66.7 53.3 23 63.3 48.3 1.2 0.9 1.2 B B B A SI 0.05 0.03 0.61 0 0.75 0.62 0.52 1.0 1.0 0.6 0.48 0.6 0.60 0.60 0.60 1.0 1.0 MV Actual 0 57.5 56.3 0 13.3 0 58.4 10.0 10.6 1.4 1.8 1.8 B B B A SI 0 1.0 1.0 0 0.3 0 1.0 0.25 0.26 0.65 0.92 0.92 0.60 0.60 0.60 1.0 1.0 MY Actual 0 75.0 70.8 0 6.7 0 17.6 36.7 29.2 2.0 1.3 1.3 B B B A SI 0 0.83 0.87 0 0.25 0 0.41 0.9 0.75 1.0 0.62 0.62 0.60 0.60 0.60 1.0 1.0 Mean Actual 2.3 20.4 43.2 0 36.7 21.7 27.8 28.8 22.7 1.6 1.4 1.5 n/a B B A Mean SI 0.05 0.63 0.78 0 0.49 0.27 0.55 0.56 0.51 0.81 0.73 0.74 0.60 0.60 0.60 1.0 1.0
a A = woody vegetation dominated (>50%) by aspen, willow, cottonwood, or alder B = woody vegetation dominated by other deciduous species C = woody vegetation dominated by confiers b A = small fluctuations B = moderate fluctuations C = extreme fluctuations c Total HSI score is equal to the lesser value of V6 and a+b+c/2.5
Appendix 45. Continued.
400
Appendix 46. Variable measurements and Suitability Index (SI) values for the muskrat Habitat Suitability Index model for mitigation
(n = 11) and natural (n = 4) wetlands in West Virginia (mitigation sites: WB = Walnut Bottom, VO = Vepco, BC = Buffalo Coal, ER
= Elk Run, LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus Joist MacMillan, EB = Enoch Branch,
and BR = Bear Run; natural sites: AM = Altona Marsh, ES = Elder Swamp, MV = Meadowville, and MY = Muddlety), 2001-2002.
Food/Cover Cover Component Component Food Component
V3 V1 V2 % of emergent % emergent vegetation consisting vegetation % of year of Olney bulrush, HSI formula a (persistent and with surface common threesquare, SI Cover = SI Food = Mitigation nonpersistent) water present or cattail (V1 * V2)1/2 (V1 * V3)1/2 WB Actual 44.6 100 12.7 SI 0.89 1.0 0.11 0.94 0.31 VO Actual 66.9 100 2.9 SI 1.0 1.0 0.10 1.00 0.32 BC Actual 41.5 100 2.8 SI 0.84 1.0 0.10 0.92 0.29 ER Actual 22.3 100 14.8 SI 0.48 1.0 0.15 0.69 0.27 LC Actual 68.8 100 3.1 SI 1.0 1.0 0.10 1.0 0.32
401
Food/Cover Cover Component Component Food Component V1 V2 V3 % of emergent % emergent vegetation consisting vegetation % of year of Olney bulrush, HSI formula a (persistent and with surface common threesquare, SI Cover = SI Food = Mitigation cont. nonpersistent) water present or cattail (V1 * V2)1/2 (V1 * V3)1/2 SC Actual 81.0 100 10.3 SI 1.0 1.0 0.10 1.0 0.32 SR Actual 22.4 100 19.5 SI 0.49 1.0 0.19 0.70 0.31 T Actual 68 100 37.6 SI 1.0 1.0 0.45 1.0 0.67 TJM Actual 47.2 100 10.4 SI 0.91 1.0 0.10 0.95 0.30 EB Actual 38.9 100 0.0 SI 0.82 1.0 0.10 0.91 0.29 BR Actual 26.7 100 35.4 SI 0.53 1.0 0.44 0.73 0.48 Mean actual 48.0 100 13.6 Mean SI 0.81 1.0 0.18 0.89 0.35
Appendix 46. Continued.
402
Food/Cover Cover Component Component Food Component V1 V2 V3 % of emergent % emergent vegetation consisting vegetation % of year of Olney bulrush, HSI formula a (persistent and with surface common threesquare, SI Cover = SI Food = Natural nonpersistent) water present or cattail (V1 * V2)1/2 (V1 * V3)1/2 MY Actual 87.3 100 62.9 SI 0.95 1.0 0.8 0.97 0.87 ES Actual 44.3 100 35.6 SI 0.87 1.0 0.44 0.93 0.62 MV Actual 43.8 100 66.7 SI 0.86 1.0 0.18 0.93 0.39 MY Actual 62.0 100 6.0 SI 1.0 1.0 0.1 1.0 0.32 Mean Actual 59.4 100 42.8 Mean SI 0.92 1.0 0.38 0.96 0.55 a Total HSI score is equal to the lesser value of SI Cover and SI Food
Appendix 46. Continued.
403
Appendix 47. Variable measurements and Suitability Index (SI) values for the mink Habitat
Suitability Index model for mitigation (n = 11) and natural (n = 4) wetlands in West Virginia
(mitigation sites: WB = Walnut Bottom, VO = Vepco, BC = Buffalo Coal, ER = Elk Run,
LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus Joist
MacMillan, EB = Enoch Branch, and BR = Bear Run; natural sites: AM = Altona Marsh,
ES = Elder Swamp, MV = Meadowville, and MY = Muddlety), 2001-2002.
V1 V2 V3 HSI formula % tree and/or % of year % persistent shrub cover with surface emergent w/in 100 m Mitigation water present vegetation of water's edge V1((4V2 + V3)/5)WB Actual 100 42.4 36.3 SI 1.0 0.83 0.43 0.75 VO Actual 100 61.8 68.4 SI 1.0 1.0 0.91 0.98 BC Actual 100 40.3 18.3 SI 1.0 0.82 0.30 0.72 ER Actual 100 22.3 55.0 SI 1.0 0.50 0.73 0.55 LC Actual 100 63.8 41.3 SI 1.0 1.0 0.60 0.92 SC Actual 100 81.0 64.0 SI 1.0 0.98 0.88 0.96 SR Actual 100 22.4 36.3 SI 1.0 0.50 0.52 0.50 T Actual 100 68.0 41.3 SI 1.0 1.0 0.61 0.92 TJM Actual 100 47.2 26.3 SI 1.0 0.98 0.43 0.87 EB Actual 100 38.9 65.0 SI 1.0 0.78 0.89 0.80 BR Actual 100 26.7 77.6 SI 1.0 0.60 1.0 0.68
404
V1 V2 V3 HSI formula % tree and/or % of year % persistent shrub cover with surface emergent w/in 100 m Mitigation cont. water present vegetation of water's edge V1((4V2 + V3)/5)Mean actual 100 46.9 48.2 Mean SI 1.0 0.82 0.66 0.79 Natural AM Actual 100 86.3 30.0 SI 1.0 0.90 0.48 0.82 ES Actual 100 43.8 66.6 SI 1.0 0.85 0.90 0.86 MV Actual 100 43.8 65.0 SI 1.0 0.90 0.89 0.89 MY Actual 100 62.0 86.7 SI 1.0 1.0 1.0 1.0 Mean Actual 100 59 62.1 Mean SI 1.0 0.91 0.82 0.89
Appendix 47. Continued.
405
Appendix 48. Variable measurements and Suitability Index (SI) values for the great-blue heron Habitat Suitability Index model for
mitigation (n = 11) and natural (n = 4) wetlands in West Virginia (mitigation sites: WB = Walnut Bottom, VO = Vepco, BC = Buffalo
Coal, ER = Elk Run, LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus Joist MacMillan, EB =
Enoch Branch, and BR = Bear Run; natural sites: AM = Altona Marsh, ES = Elder Swamp, MV = Meadowville, and MY =
Muddlety), 2001-2002.
Foraging Component Reproduction Component V1 V2 V3 V4 V5 V6 HSI formula distance (m) disturbance free distance (km) of b/w foraging presence of disturbance presence of (250 m for land and potential nest area and shallow, clear free up to forest w/in 150 m for water) site to actual (V1*V2* potential water with 100 m around 250 m of around potential or previous V3*V4*
Mitigation nest site fish (<25 cm) foraging area? wetland? nesting sites? nest site V5*V6)1/2 WB Actual 10.0 yes/yes yes yes yes 83.4 SI 1.0 1.0 1.0 1.0 1.0 0.10 0.32 VO Actual 20.0 yes/no yes yes yes 55.8 SI 1.0 0.50 1.0 1.0 1.0 0.10 0.22 BC Actual 250.0 yes/no yes yes yes 52.3 SI 1.0 0.50 1.0 1.0 1.0 0.10 0.22 ER Actual 0.0 yes/yes yes yes yes 49.6 SI 1.0 1.0 1.0 1.0 1.0 0.10 0.32 LC Actual 50.0 yes/yes yes yes yes 37.9 SI 1.0 1.0 1.0 1.0 1.0 0.10 0.32
406
Foraging Component Reproduction Component V1 V2 V3 V4 V5 V6 HSI formula distance (m) disturbance free distance (km) of b/w foraging presence of disturbance presence of (250 m for land and potential nest area and shallow, clear free up to forest w/in 150 m for water) site to actual (V1*V2* potential water with 100 m around 250 m of around potential or previous V3*V4*
Mitigation cont. nest site fish (<25 cm) foraging area? wetland? nesting sites? nest site V5*V6)1/2 SC Actual 20.0 yes/yes yes yes yes 42.4 SI 1.0 1.0 1.0 1.0 1.0 0.10 0.32 SR Actual 0.0 yes/yes yes yes no 43.2 SI 1.0 1.0 1.0 1.0 0.25 0.10 0.16 T Actual 20.0 yes/yes yes yes no 47.6 SI 1.0 1.0 1.0 1.0 0.25 0.10 0.16 TJM Actual 25.0 yes/yes yes yes no 48.1 SI 1.0 1.0 1.0 1.0 0.25 0.10 0.16 EB Actual 5.0 yes/yes yes yes yes 65.4 SI 1.0 1.0 1.0 1.0 1.0 0.10 0.32 BR Actual 5.0 yes/yes yes yes yes 32.9 SI 1.0 1.0 1.0 1.0 1.0 0.10 0.32 Mean actual 36.8 n/a n/a n/a n/a 50.8 Mean SI 1.0 0.91 1.0 1.0 0.8 0.10 0.26
Appendix 48. Continued.
407
Foraging Component Reproduction Component V1 V2 V3 V4 V5 V6 HSI formula distance (m) disturbance free distance (km) of b/w foraging presence of disturbance presence of (250 m for land and potential nest area and shallow, clear free up to forest w/in 150 m for water) site to actual (V1*V2* potential water with 100 m around 250 m of around potential or previous V3*V4*
Natural nest site fish (<25 cm) foraging area? wetland? nesting sites? nest site V5*V6)1/2 AM Actual 50.0 yes/yes yes yes yes 166.4 SI 1.0 1.0 1.0 1.0 1.0 0.10 0.32 ES Actual 100.0 yes/yes yes yes yes 56.2 SI 1.0 1.0 1.0 1.0 1.0 0.10 0.32 MV Actual 0.0 yes/no yes yes no 40.6 SI 1.0 0.5 1.0 1.0 0.25 0.10 0.11 MY Actual 0.0 yes/yes yes yes no 66.4 SI 1.0 1.0 1.0 1.0 0.25 0.10 0.16 Mean Actual 37.5 n/a n/a n/a n/a 82.4 Mean SI 1.0 0.88 1.0 1.0 0.63 0.10 0.23
Appendix 48. Continued.
408
Appendix 49. Variable measurements and Suitability Index (SI) values for the wood duck Habitat Suitability Index model for
mitigation (n = 11) and natural (n = 4) wetlands in West Virginia (mitigation sites: WB = Walnut Bottom, VO = Vepco, BC = Buffalo
Coal, ER = Elk Run, LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus Joist MacMillan, EB =
Enoch Branch, and BR = Bear Run; natural sites: AM = Altona Marsh, ES = Elder Swamp, MV = Meadowville, and MY =
Muddlety), 2001-2002.
Breeding Model Winter model Total HSI V1 V2 V3 V4 V7 V8 SI formula V5 # of tree density of % area % area % potential equals higher cavities/0.4 ha potential nest w/ optimum w/ optimum Total breeding winter cover SI between with 7.6 X 10 cm # of nest # of nest sites/0.4ha: % potential nesting brood-rearing SI = lower value (equals breeding SI Mitigation entrance boxes boxes/0.4 ha (.18*V1) + (.95*V2) brood cover habitat (= nesting SI) habitat (= brood SI) of V7 and V8 total winter SI) and winter SI WB Actual 4.0 0.0 0.0 .72 49.1 14.0 98.0 46.9 SI .14 0.98 .70 0.98 0.70 0.92 0.92 VO Actual 1.3 2.0 0.11 0.34 71.4 7.0 100 66.3 SI 0.07 1.0 0.28 1.0 0.28 1.0 1.0 BC Actual 0.0 1.0 0.04 0.04 63.6 1.0 100 62.4 SI 0.01 1.0 0.02 1.0 0.02 1.0 1.0 ER Actual 8.0 0.0 0.0 1.4 33 28.0 65.0 33.0 SI 0.28 0.65 1.0 0.65 0.65 0.62 0.65 LC Actual 9.3 0.0 0.0 1.4 71.6 34.0 100 66.6 SI 0.34 1.0 1.0 1.0 1.0 1.0 1.0 SC Actual 6.7 10.0 0.59 1.7 92 34.0 30.0 92.0 SI 0.34 0.3 1.0 0.3 0.30 0.29 0.30 SR Actual 8.0 3.0 0.4 1.8 28.9 32.0 60.0 28.9 SI 0.32 0.6 1.0 0.6 0.60 0.57 0.60 T Actual 5.3 5.0 0.65 1.6 76 24.0 98.0 76.0 SI 0.24 0.98 1.0 0.98 0.98 0.98 0.98
409
Breeding Model Winter model Total HSI V1 V2 V3 V4 V7 V8 SI formula V5 # of tree density of % area % area % potential equals higher cavities/0.4 ha potential nest w/ optimum w/ optimum Total breeding winter cover SI between with 7.6 X 10 cm # of nest # of nest sites/0.4ha: % potential nesting brood-rearing SI = lower value (equals breeding SI Mitigation cont. entrance boxes boxes/0.4 ha (.18*V1) + (.95*V2) brood cover habitat (= nesting SI) habitat (= brood SI) of V7 and V8 total winter SI) and winter SI TJM Actual 6.7 0.0 0.0 1.2 70.5 24.0 100 70.5 SI 0.24 1.0 1.0 1.0 1.0 1.0 1.0 EB Actual 5.3 0.0 0.0 0.95 60 19.0 100 45.8 SI 0.19 1.0 0.94 1.0 0.94 0.90 0.94 BR Actual 16.0 0.0 0.0 2.9 27.7 58.0 59.0 27.4 SI 0.58 0.59 1.0 0.59 0.59 0.56 0.59 Mean actual 6.4 0.20 1.3 58.5 26 82.7 47.5 Mean SI 0.25 0.80 0.81 0.83 0.64 0.82 0.82 Natural AM Actual 18.7 0.0 0.0 3.4 99.6 68.0 4.0 99.5 SI 0.68 0.04 1.0 0.4 0.40 0.01 0.40 ES Actual 4 0.0 0.0 0.72 68.6 14.0 100 68.1 SI 0.14 1.0 0.9 1.0 0.90 1.0 0.90 MV Actual 12 0.0 0.0 2.2 85 44 60.0 100 SI 0.44 0.6 1.0 0.6 0.60 0.0 0.60 MY Actual 5.3 0.0 0.0 0.95 79.6 19.0 82.0 79.6 SI 0.19 0.82 1.0 0.82 0.80 0.86 0.80 Mean Actual 10 0.0 0.0 1.8 83.2 36.3 61.5 86.8 Mean SI 0.36 0.62 0.98 0.71 0.68 0.47 0.68
Appendix 49. Continued.
410
Appendix 50. Variable measurements and Suitability Index (SI) values for the snapping turtle Habitat Suitability Index model for mitigation (n =
11) and natural (n = 4) wetlands in West Virginia (mitigation sites: WB = Walnut Bottom, VO = Vepco, BC = Buffalo Coal, ER = Elk Run, LC =
Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus Joist MacMillan, EB = Enoch Branch, and BR = Bear Run; natural
sites: AM = Altona Marsh, ES = Elder Swamp, MV = Meadowville, and MY = Muddlety), 2001-2002.
Winter Cover Reproduction Interspersion Food Component (SIF) Component (SIWC) Component (SIR) Component (SII) V1 V2 V3 V4 V5 V6 V7 HSI formula mean water mean water temp (°C) at mid velocity (cm/s) % aquatic winter water distance (m)
depth during at mid depth vegetation in depth > max. % silt in distance (m) to permanent (SIF*SIWC*SIR)1/3 Site summer during summer littoral zone ice depth? substrate to small stream water * SII WB Actual 26.2 0.0 84.7 yes 18.5 0.0 0.0 SI 1.0 1.0 0.84 1.0 0.19 1.0 1.0 0.56 VO Actual 22.2 0.014 66.9 yes 25.1 50.0 0.0 SI 0.82 1.0 0.67 1.0 0.25 1.0 1.0 0.59 BC Actual 27.4 0.0 52.4 yes 29.1 35.0 0.0 SI 1.0 1.0 0.52 1.0 0.29 1.0 1.0 0.61 ER Actual 26.6 0.0 87.6 yes 23.4 0.0 0.0 SI 1.0 1.0 0.88 1.0 0.23 1.0 1.0 0.6 LC Actual 26.4 0.0 75.2 yes 39.3 10.0 0.0 SI 1.0 1.0 0.75 1.0 0.39 1.0 1.0 0.71 SC Actual 30.9 0.0 87.8 yes 29.1 0.0 0.0 SI 1.0 1.0 0.88 1.0 0.29 1.0 1.0 0.65 SR Actual 26.4 0.0 63.4 yes 18.4 10.0 0.0
411
Winter Cover Reproduction Interspersion Food Component (SIF) Component (SIWC) Component (SIR) Component (SII) V1 V2 V3 V4 V5 V6 V7 HSI formula mean water mean water temp (°C) at mid velocity (cm/s) % aquatic winter water distance (m)
depth during at mid depth vegetation in depth > max. % silt in distance (m) to permanent (SIF*SIWC*SIR)1/3 Site summer during summer littoral zone ice depth? substrate to small stream water * SII SI 1.0 1.0 0.63 1.0 0.18 1.0 1.0 0.54 T Actual 28.8 0.002 89.6 yes 21.5 15.0 0.0 SI 1.0 1.0 0.90 1.0 0.22 1.0 1.0 0.60 TJM Actual 27.0 0.011 47.9 yes 28.8 10.0 0.0 SI 1.0 1.0 0.48 1.0 0.29 1.0 1.0 0.61 EB Actual 29.2 0.001 82.9 yes 13.6 5.0 0.0 SI 1.0 1.0 0.83 1.0 0.14 1.0 1.0 0.51 BR Actual 33.9 0.0 63.2 yes 20.8 0.0 0.0 SI 1.0 1.0 0.63 1.0 0.21 1.0 1.0 0.57 Mean actual 27.7 0.003 72.9 n/a 24.3 12.3 0.0 Mean SI 0.98 1.0 0.73 1.0 0.24 1.0 1.0 0.60 Natural AM Actual 20.1 0.0 87.8 yes 11.0 0.0 0.0 SI 0.65 1.0 0.88 1.0 0.11 1.0 1.0 0.45 ES Actual 23.4 0.0 44.7 yes 19.5 0.0 0.0 SI 0.90 1.0 0.45 1.0 0.20 1.0 1.0 0.53 MV Actual 20.6 0.0 43.8 yes 17.9 0.0 0.0 SI 0.64 1.0 0.44 1.0 0.18 1.0 1.0 0.49 MY Actual 31.1 0.0 74.8 yes 27.2 0.0 0.0 SI 1.0 1.0 0.75 1.0 0.28 1.0 1.0 0.63
Appendix 50. Continued.
412
Winter Cover Reproduction Interspersion Food Component (SIF) Component (SIWC) Component (SIR) Component (SII) V1 V2 V3 V4 V5 V6 V7 HSI formula mean water mean water temp (°C) at mid velocity (cm/s) % aquatic winter water distance (m)
depth during at mid depth vegetation in depth > max. % silt in distance (m) to permanent (SIF*SIWC*SIR)1/3 Site summer during summer littoral zone ice depth? substrate to small stream water * SII Mean Actual 23.8 0.0 62.8 n/a 18.9 0.0 0.0 Mean SI 0.80 1.0 0.63 1.0 0.19 1.0 1.0 0.53
Appendix 50. Continued.
413
Appendix 51. Variable measurements and Suitability Index (SI) values for the red-spotted
newt Habitat Suitability Index model for mitigation (n = 11) and natural (n = 4) wetlands in
West Virginia (mitigation sites: WB = Walnut Bottom, VO = Vepco, BC = Buffalo Coal,
ER = Elk Run, LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle,
TJM = Trus Joist MacMillan, EB = Enoch Branch, and BR = Bear Run; natural sites: AM
= Altona Marsh, ES = Elder Swamp, MV = Meadowville, and MY = Muddlety), 2001-
2002.
V1 V2 V3 HSI formula % aquatic vegetation distance (m) % water in littoral to forested Mitigation < 2 m deep zone cover type V1 * V2 * V3 WB Actual 100 84.7 10.0 SI 1.0 1.0 1.0 1.0 VO Actual 100 66.9 25.0 SI 1.0 0.93 1.0 0.93 BC Actual 100 52.4 75.0 SI 1.0 0.72 0.75 0.54 ER Actual 100 87.6 0.0 SI 1.0 1.0 1.0 1.0 LC Actual 100 75.2 0.0 SI 1.0 1.0 1.0 1.0 SC Actual 100 87.8 20.0 SI 1.0 1.0 1.0 1.0 SR Actual 100 63.4 0.0 SI 1.0 0.89 1.0 0.89 T Actual 100 89.6 0.0 SI 1.0 1.0 1.0 1.0 TJM Actual 100 47.9 25.0 SI 1.0 0.69 1.0 0.69 EB Actual 100 82.9 5.0 SI 1.0 1.0 1.0 1.0 BR Actual 100 63.2 0.0 SI 1.0 0.87 1.0 0.87
414
V1 V2 V3 HSI formula % aquatic vegetation distance (m) % water in littoral to forested Mitigation cont. < 2 m deep zone cover type V1 * V2 * V3 Mean actual 100 72.9 14.5 Mean SI 1.0 0.92 0.98 0.90 Natural AM Actual 100 87.8 0.0 SI 1.0 1.0 1.0 1.0 ES Actual 100 44.7 0.0 SI 1.0 0.62 1.0 0.62 MV Actual 100 43.8 0.0 SI 1.0 0.58 1.0 0.58 MY Actual 100 74.8 0.0 SI 1.0 0.98 1.0 0.98 Mean Actual 100 62.8 0.0 Mean SI 1.0 0.80 1.0 0.80
Appendix 51. Continued.
415
Appendix 52. Common and scientific names of all birds included in Analysis of
Variance models used to calculate metrics for wetland rankings and in Canonical
Correspondence Analyses (CCA) on 11 mitigation and 4 reference wetlands, West
Virginia, 2001-2002.
Common Name Scientific Name Great Blue Heron Ardea herodias Green Heron Butorides virescens Turkey Vulture Cathartes aura Canada Goose Branta canadensis Muscovy Duck Cairina moschata Green-winged Teal Anas crecca Black Duck Anas rubripes Wood Duck Aix sponsa Mallard Anas platyrhynchos Red-shouldered Hawk Buteo lineatus Red-tailed Hawk Buteo jamaicensis Ruffed Grouse Bonasa umbellus Wild Turkey Meleagris gallopavo Northern Bobwhite Colinus virginianus Virginia Rail Rallus limicola Sora Porzana carolina Killdeer Charadrius vociferus Spotted Sandpiper Actitis macularia American Woodcock Scolopax minor Mourning Dove Zenaida macroura Yellow-billed Cuckoo Coccyzus americanus Chimney Swift Chaetura pelagica Ruby-throated Hummingbird Archilochus colubris Belted Kingfisher Ceryle alcyon Red-bellied Woodpecker Melanerpes carolinus Red-headed Woodpecker Melanerpes erythrocephalus Downy Woodpecker Picoides pubescens Northern Flicker Colaptes auratus Pileated Woodpecker Dryocopus pileatus Eastern Wood-Pewee Contopus virens Acadian Flycatcher Empidonax virescens
416
Common Name Scientific Name Alder Flycatcher Empidonax alnorum Willow Flycatcher Empidonax traillii Least Flycatcher Empidonax minimus Eastern Phoebe Sayornis phoebe Great Crested Flycatcher Myiarchus crinitus Olive-sided Flycatcher Contopus borealis Eastern Kingbird Tyrannus tyrannus White-eyed Vireo Vireo griseus Yellow-throated Vireo Vireo flavifrons Warbling Vireo Vireo gilvus Red-eyed Vireo Vireo olivaceus Blue Jay Cyanocitta cristata American Crow Corvus brachyrhynchos Common Raven Corvus corax Tree Swallow Tachycineta bicolor Northern Rough-winged Swallow Stelgidopteryx serripennis Barn Swallow Hirundo rustica Black-capped Chickadee Poecile atricapillus Carolina Chhickadee Parus carolinensis Tufted Titmouse Baeolophus bicolor Brown Creeper Certhia americana Red-breasted Nuthatch Sitta canadensis White-breasted Nuthatch Sitta carolinensis Carolina Wren Thryothorus ludovicianus House Wren Troglodytes aedon Blue-gray Gnatcatcher Polioptila caerulea Eastern Bluebird Sialia sialis Veery Catharus fuscescens Hermit Thrush Catharus guttatus Swainson's Thrush Catharus ustulatus Wood Thrush Hylocichla mustelina American Robin Turdus migratorius Gray Catbird Dumetella carolinensis Northern Mockingbird Mimus polyglottos Brown Thrasher Toxostoma rufum European Starling Sturnus vulgaris Cedar Waxwing Bombycilla cedrorum
Appendix 52. Continued
417
Common Name Scientific Name Blue-winged Warbler Vermivora pinus Golden-winged Warbler Vermivora chrysoptera Northern Parula Parula americana Yellow Warbler Dendroica petechia Magnolia Warbler Dendroica magnolia Black-throated Green Warbler Dendroica virens Yellow-throated Warbler Dendroica dominica Black-and-white Warbler Mniotilta varia Prairie Warbler Dendroica discolor Cerulean Warbler Dendroica cerulea Prothonotary Warbler Protonotaria citrea American Redstart Setophaga ruticilla Worm-eating Warbler Helmitheros vermivorus Ovenbird Seiurus aurocapillus Kentucky Warbler Oporornis formosus Common Yellowthroat Geothlypis trichas Scarlet Tanager Piranga olivacea Eastern Towhee Pipilo erythrophthalmus Chipping Sparrow Spizella passerina Field Sparrow Spizella pusilla Grasshopper Sparrow Ammodramus bairdii Song Sparrow Melospiza melodia Savannah Sparrow Passerculus sandwichensis Swamp Sparrow Melospiza georgiana Vesper Sparrow Pooecetes gramineus Dark-eyed Junco Junco hyemalis Northern Cardinal Cardinalis cardinalis Rose-breasted Grosbeak Pheucticus ludovicianus Indigo Bunting Passerina cyanea Red-winged Blackbird Agelaius phoeniceus Boat-tailed Grackle Quiscalus major Common Grackle Quiscalus quiscula Brown-headed Cowbird Molothrus ater Baltimore Oriole Icterus galbula Orchard Oriole Icterus spurius American Goldfinch Carduelis tristis House Sparrow Passer domesticus
Appendix 52. Continued.