ECOLOGY OF SYMPATRIC MULE DEER AND
WHITE-TAILED DEER IN WEST-CENTRAL TEXAS
by
KRISTINA JOHANNSEN BRUNJES, B.S., M.S.
A DISSERTATION
IN
WILDLIFE
Submitted to the Graduate Faculty of Texas Tech University in
Partial Fulfillment of the Requirements for
the Degree of
DOCTOR OF PHILOSOPHY
Approved
Chairperson of the Committee
Accepted
Dean of the Graduate School
December, 2004
ACKNOWLEDGMENTS
I wish to thank my major advisor, Dr. Warren Ballard, for allowing me to work on
this study. I am also grateful to my committee members, Drs. Clyde Jones, Paul
Krausman, Nancy Mclntyre, and Mark Wallace for their advice and support.
This project would not have been possible without the efforts of TPWD biologists
Mary Humphrey and Fielding Harwell. I am indebted to you both for all your hard work
and support. Several technicians provided much-appreciated assistance during this
project - Simon Pederson, Rick Hanson, Shane Dempsey, and Charles Anderson.
This project was funded by Texas Tech University, Texas Parks and Wildlife
Department, and the Rob and Bessie Welder Wildlife Foundation. Additional support
was provided by the Houston and West Texas Chapters of Safari Club International. I am
grateful for the willingness of the landowners of the ranches in Crockett County to
provide me with housing and access to the properties. I especially appreciate the
friendship of Larry and Grace Clark, who made me part of their family.
My mother and stepfather, Bronwyn and Bob Gillette, have been so supportive of
me and they provided much encouragement and love during this scholastic journey. My
in-laws, Kitty and John Henry Brunjes, and my husband's grandmother, Abbey Anger,
have also been wonderful and I am blessed to be part of their family. But the greated
thanks goes to my husband, John Brunjes. Without his love, encouragement, and staunch
support I would never have completed this project.
TABLE OF CONTENTS
ACKNOWLEDGMENTS ii
ABSTRACT v
LIST OF TABLES vii
LIST OF FIGURES ix
CHAPTER
I. INTRODUCTION 1
Literature Cited 3
II. HOME RANGE SIZE AND SURVIVAL OF MALE SYMPATRIC MULE AND WHITE-TAILED DEER IN TEXAS 5
Abstract 5
Introduction 5
Study Area 7
Methods 8
Results 11
Discussion 14
Literature Cited 20
III. HOME RANGE SIZE AND SURVIVAL OF FEMALE SYMPATRIC MULE AND WHITE-TAILED DEER IN TEXAS 28
Abstract 28
111
IV.
Introduction
Study Area
Methods
Results
Discussion
Literature Cited
HABITAT SELECTION BY SYMPATRIC MULE AND
WHITE-TAILED DEER IN TEXAS
Abstract
Introduction
Study Area
Methods
Habitat Classification
Data Analysis
Results
Females
Males
Discussion
Management Implications
Literature Cited
29
30
32
35
38
45
57
57
58
61
62
64
65
65
66
67
68
69
71
IV
ABSTRACT
Fluctuations in populations of sympatric mule deer (Odocoileus hemionus) and
white-tailed deer (O. virginianus), as well as the potential for interspecific competition
have fostered a need for information about the ecology of these unique populations to aid
the development of management strategies. I estimated home range sizes, core area sizes,
overlap, and survival of sympatric desert mule deer and white-tailed deer in west-central
Texas. I captured 50 female mule deer, 53 female white-tailed deer, and 18 males of
each species, fitted them with radiocoUars, and monitored them for mortality from 2000
through 2003.
I calculated home ranges for 7 males of each species in 2001 and 2002. Home
range sizes of male deer (mule deer, 8.8 km ; white-tailed deer, 7.4 km^) were similar.
Interspecific home range overlap was less common than intraspecific overlap. Mean
annual survival was 0.76 ± 0.04 (mean + SE) for mule deer and 0.80 ± 0.06 for white-
tailed deer.
I estimated home range (95% kernel) and core area (50% kernel) sizes and
overlap and survival of female deer. Average (+ SE) spring home range size of mule
deer was 3.9 + 0.32 km" and white-tailed deer was 4.32 + 0.77 km ; summer home range
sizes were 2.82 + 0.32 km^ and 2.08 + 0.23 km , respectively. Interspecific seasonal
home range overlap indices were similar to intraspecific overlap. Core area overlap also
was similar within and between species during summer, but interspecific core area
overlap was less common during spring. Mean (+ SE) annual survival of mule deer (0.91
+ 0.08) was greater than survival of white-tailed deer ( 0.64 ± 0.10). Starvation and
disease were the most commonly identified causes of death for males and females,
suggesting improved quality and abundance of forage may be warranted to buffer
environmental vagaries. However, significant spatial overlap indicated that tailoring
management efforts to benefit just 1 species will require attention to the scale of intended
activities.
I evaluated the role of vegetation community structure and topography on the
habitat use of sjmipatric deer in west-central Texas using information obtained from
radiocollared deer and a geographic information system (GIS). Both species used habitat
in a non-random fashion and exhibited species- and sex-specific preferences. Mule deer
used habitats with less vegetation cover and more topographic diversity, while white-
tailed deer avoided landscapes at higher elevations. Males of both species avoided areas
with greatest vegetation cover including those areas containing permanent water sources,
but females tended to use such areas, particularly during summer fawning. Differences
observed in the smaller core area scale were not always detected at the larger home range
level, indicating that decisions about habitat use were made at different spatial scales.
VI
LIST OF TABLES
2.1 Comparison of mean 95% and 50% (core area) kernel home range estimates of sympatric adult male mule and white-tailed deer in west-central Texas, January through August, 2001-2002, using analysis of variance. 25
2.2 Mean overlap indices for 95% kernel home ranges and 50% kernel core areas of sympatric adult male mule and white-tailed deer in west-central Texas, January through August, 2001-2002. 26
3.1 Seasonal minimum convex polygon home range sizes (km^) for sympatric adult female mule deer and white-tailed deer in west-central Texas, 2000-2002. 50
3.2 Seasonal 50% core area sizes (km^) for sympatric adult female mule deer and white-tailed deer in west-central Texas, 2000-2002. 51
3.3 Seasonal 95% kernel home range sizes (km^) for sympatric adult female mule deer and white-tailed deer in west-central Texas, 2000-2002. 52
3.4 Within-year seasonal fidelity (mean overlap indices) of 50% core areas and 95% home ranges sympatric adult female mule deer and white-tailed deer in west-central Texas, 2000-2002. 53
3.5 Mean overlap indices of individual spring and summer 50% core areas and 95% home ranges across years for sympatric adult female mule deer and white-tailed deer in west-central Texas, 2000-2002. 54
3.6 Mean overlap indices of 50% core areas and 95% home ranges with other individuals of either species for sympatric adult female mule deer and white-tailed deer in west-central Texas, 2000-2002. 55
4.1. Percentage of study area covered by each of 11 delineated vegetation classes with corresponding elevation classes and descriptions of the vegetation species or type most prevalent in that class for 5 ranches in west-central Texas, 2000-2002. 74
4.2. Multiple analysis of variance results for contrasts of 95% home range habitat compositions of radiomarked sympatric adult female mule deer and white-tailed deer in west-central Texas during spring and summer of 2000-2002. 75
Vll
4.3. Home range composition and preference rankings by year and species for sympatric adult female deer in west-central Texas during spring and summer of 2000 - 2002. 76
4.4. Multiple analysis of variance results for contrasts of 50% core area habitat compositions of radio-marked sympatric adult female mule deer and white-tailed deer in west-central Texas during spring and summer of 2000-2002. 78
4.5. Core area composition and preference rankings by year and species for sympatric adult female deer in west-central Texas during spring and summer of 2000 - 2002. 79
4.6. Multiple analysis of variance results for contrasts of 95% home range and core area habitat composition of radiomarked sympatric adult male mule deer and white-tailed deer in west-central Texas during spring and summer of 2000-2002. 81
4.7. Home range (95% kernel) and core area (50% kernel) composition and preference rankings by year and species for sympatric adult male deer in west-central Texas during spring and summer of 2000 - 2002. 82
Vlll
LIST OF FIGURES
2.1 Survival curves for sympatric adult male white-tailed deer and mule deer (n = 18 of each species) in west-central Texas, 31 January 2000 through 31 January 2003. 27
3.3 Survival curves for sympatric adult female white-tailed deer and mule deer (n = 18 of each species) in west-central Texas, 31 January 2000 through 31 January 2003. 55
IX
CHAPTER I
INTRODUCTION
White-tailed deer (Odocoileus virginianus) and mule deer (O. hemionus) occur
sympatrically in 12 western states. In west Texas, the ranges of desert mule deer and
white-tailed deer overlap in portions of the Trans-Pecos region, along the western edge of
the Edwards Plateau, and in the Panhandle (Smith, 1987). In some areas, white-tailed
deer have become more abundant in areas traditionally considered mule deer habitat
(Harwell and Gore, 1981), probably due to changes in vegetation communities resulting
from livestock production (Baker, 1984). Simultaneously, mule deer have decreased or
disappeared entirely from some areas (Wiggers and Beasom, 1986).
Similarities exist in behavior pattems of mule and white-tailed deer, but the
species may differ in behavior where they are sympatric (Geist, 1981). The coexistence
of white-tailed deer and mule deer is likely dependent on habitat differences and
preferences that vary according to geographic location (Martinka, 1968; Kramer, 1973;
Henry and Sowls, 1980; Krausman and Abies, 1981; Swenson et al., 1983; Wiggers,
1983; Whittaker, 1995). Spatial and temporal segregation based on topography, woody
cover, resource competition, social dominance, and interference competition might
explain species coexistence (Anthony and Smith, 1977; Kramer, 1973; Krausman, 1978;
Krausman and Abies, 1981; Wiggers and Beasom, 1986; Avey et al., 2003).
The habitat requirements of both species are poorly understood in west Texas,
particularly in sympatric areas. In 1998, Texas Parks and Wildlife Department (TPWD)
biologists initiated a pilot study to investigate differences in habitat use by mule deer and
white-tailed deer in Crockett County, Texas. Slope, amount of forbs, and amount of
grass explained only a portion of the differences in microhabitat use by deer (Avey et al.,
2003), indicating a need for further research. My study was designed to explore further
the differences in habitat use by mule and white-tailed deer, identify causes of mortality
for adult deer, and investigate the spatial and temporal relationships between these
sympatric deer species. Chapters II through IV consist of 3 manuscripts intended for
submission to peer-reviewed journals. Each chapter is written in a different format, as
they are destined for different journals; thus they may differ in subheading and reference
styles. Chapter II describes the home range sizes and overlap and survival of male deer.
Chapter III describes the home range sizes and overlap and survival of female deer. This
information is presented in 2 chapters due to differences in data collection and analyses
required. Chapter IV focuses on the habitat availability and use by each species using a
geographic information system (GIS). Each chapter has several co-authors: Chapters II
and III: Kristina J. Brunjes, Warren B. Ballard, Paul R. Krausman, Mary H. Humphrey,
and Fielding Harwell; Chapter IV: Kristina J. Brunjes, Warren B. Ballard, Paul R.
Krausman, Mary H. Humphrey, Fielding Harwell, Nancy E. Mclntyre, and Mark C.
Wallace.
Literature Cited
Anthony, R. G., and N. S. Smith. 1977. Ecological relationships between mule deer and white-tailed deer in southeastern Arizona. Ecological Monographs 47:255-277.
Avey, J. T., W. B. Ballard, M. C. Wallace, M. H. Humphrey, P. R. Krausman, F. Harwell, and E. B. Fish. 2003. Habitat relationships between sympatric mule and white-tailed deer in Texas. The Southwestern Naturalist 48:644-653.
Baker, R. H. 1984. Origin, classification and distribution. Pages 1-18 in L. K. Halls, editor. White-tailed deer: ecology and management. Stackpole Books, Harrisburg, Pennsylvania.
Geist, V. 1981. Behavior: adaptive strategies. Pages 157-224 in O. C. Wallmo, editor. Mule and black-tailed deer of North America. University of Nebraska Press, Lincoln, Nebraska, USA.
Harwell, W. F., and H. G. Gore. 1981. White-tailed deer population trends. Job Performance Report. Federal Aid Project Number W-109-R-4. Job Number 1. Texas Parks and Wildlife Department, Austin, Texas, USA.
Henry, R. S., and L. K. Sowls. 1980. White-tailed deer of the organ pipe cactus national monument, Arizona. Arizona Cooperative Wildlife Research Unit, University of Arizona, Tucson. Technical Report No. 6.
Kramer, A. 1973. Interspecific behavior and dispersion of two sympatric deer species. Journal of Wildlife Management. 37:288-300.
Krausman, P. R. 1978. Forage relationships between two deer species in Big Bend National Park, Texas. Journal of Wildlife Management 42:101-107.
Krausman, P. R., and E. D. Abies. 1981. Ecology of the Carmen Mountains white-tailed deer. Scientific Monograph Series No. 15. U.S. Department of Interior, National Park Service, Washington, D.C, USA.
Martinka, C. J. 1968. Habitat relationships of white-tailed and mule deer in northern Montana. Journal of Wildlife Management 32:558-565.
Smith, W. P. 1987. Dispersion and habitat use by sympatric Columbian white-tailed deer and Columbian black-tailed deer. Journal of Mammalogy 68:337-347.
Swenson, J. E., S. J. Knapp, and H. J. Wentiand. 1983. Winter distribution and habitat use by mule deer and white-tailed deer in southeastern Montana. Prairie Naturalist 15:97-112.
Whittaker, D. G. 1995. Patterns of coexistence for sympatric mule and white-tailed deer on Rocky Mountain Arsenal, Colorado. Doctoral Dissertation, University of Wyoming, Laramie, Wyoming, USA.
Wiggers, E.P. 1983. Characterization of adjacent desert mule and white-tailed deer habitats in west Texas. Dissertation, Texas Tech University, Lubbock, Texas, USA.
Wiggers, E.P., and S. L. Beasom. 1986. Characterization of sympatric or adjacent habitats of two deer species in west Texas. Journal of Wildlife Management 50:129-134.
CHAPTER II
HOME RANGE SIZE AND SURVIVAL OF SYMPATRIC MALE DEER IN TEXAS
Abstract
Information about the ecology of sympatric male deer is limited, hindering
development of management strategies for sympatric herds. We estimated home range
and core area sizes and overlap and survival of sympatric male desert mule deer
(Odocoileus hemionus) and white-tailed deer (O. virginianus) in west-central Texas. We
captured 18 males of each species, fitted them with radiocoUars, and monitored their
locations and survival from 2000 through 2003. We calculated home ranges for 7 males
of each species in 2001 and 2002. Home range sizes of mule deer (8.8 km^) and white-
tailed deer (7.4 km^) were not statistically different. Interspecific home range overlap
was less common than intraspecific overlap. Mean annual survival was 0.76 + 0.04
(mean + SE) for mule deer and 0.80 + 0.06 for white-tailed deer. Large predators such as
coyotes (Canis latrans), black bear (Ursus americanus), wolves (C. lupus) and mountain
lions (Puma concolor) were absent from the study area yet survival rates were generally
similar to those reported for deer herds subject to adult mortality from predation.
Introduction
In Texas, the distributions of desert mule deer and white-tailed deer overlap in
portions of the Trans-Pecos region, the western edge of the Edwards Plateau, and in the
Panhandle region (Smith, 1987). Landowners and wildlife managers have become
concerned in recent decades as white-tailed deer have become more abundant in areas
previously considered desert mule deer habitat (Harwell and Gore, 1981), and mule deer
have decreased or disappeared entirely from some areas now inhabited by white-tailed
deer (Wiggers and Beasom, 1986). The amount of area used by male deer and their
survival is of interest to private landowners and managers due to the significant economic
contribution of hunting in Texas (Harveson et al., 2000). Income generated by hunting
leases or other wildlife recreation can supplement or even exceed that from traditional
livestock operations (Butler and Workman 1993). Because of higher bag limits and
longer seasons to hunt white-tailed deer, managers may wish to revise management
activities to increase white-tailed deer populations, whereas others may prefer to reverse
the increase of white-tailed deer in the area and favor mule deer.
Our objectives were to determine whether home range sizes differed between the
species, determine the degree of overlap of home ranges and core areas between the
species, identify causes of mortality, and estimate seasonal and annual survival rates.
Because allopatric male white-tailed deer in semi-arid and arid environments have
smaller home ranges (Michael, 1965; Gallina et al., 1997) than do allopatric male mule
deer in arid environs (Dickinson and Garner, 1979; Relyea et al., 2000), we predicted that
mule deer would have larger home ranges than white-tailed deer. However, we expected
to find overlapping home ranges between the species, as they are not territorial and have
similar diets (Anthony, 1972; Krausman, 1978). We suspected that white-tailed deer
would have lower overall survival because desert mule deer have evolved in arid
environments (Anthony, 1972), while white-tailed deer have only recently expanded the
periphery of their distributional range into our study area (Wiggers and Beasom, 1986).
In addition to the practical management considerations presented by sympatric
distribution of deer, this herd also presents a unique opportunity to examine the ecology
of both species in an area generally free of large mammalian predators. Previous studies
of sympatric mule deer and white-tailed deer in other areas of the western U.S. have been
conducted in areas occupied by large predators, particularly mountain lions. Given that
predation is a major source of adult mortality and that predation is thought to be additive
in highly variable systems (Bleich and Taylor, 1998; see review in Ballard et al., 2001),
the absence of large mammalian predators on the study area should be reflected in high
adult survival for both species.
Study Area
We conducted the study on 5 contiguous ranches (approximately 323 km^ total) in
the northwest corner of Crockett County, Texas. Livestock production, oil production,
and hunting were the primary land use activities in the region. Permanent water from
windmills was available in all pastures on all ranches year-round. Large predators such
as coyote, black bear, wolves and mountain lions were absent from the study area (Cook
1984), however bobcats (Felis rufus) were present during the study period. Population
density was unknown, but 54 bobcats were removed on a portion of the study area (165.9
km^) during December through February of 2001 (L. Clark, ranch foreman, personal
communication).
The site was located in a fransitional area on the western edge of the Edwards
Plateau and eastern Trans-Pecos region. Lower elevations were dominated by mesquite
(Prosopis sp.), creosote (Larrea tridentata), tarbush (Flourensis cernua) and prickly pear
(Opuntia sp.). Juniper (Juniperus sp.) was the dominant woody species on slopes and
mesa tops. Dense thickets of hackberry trees (Celtis occidentalis) and littie walnut frees
(Juglans microcarpa) occurred along washes. The more xeric slopes supported arid-land
plants such as yuccas (Yucca sp.) and ocotillo (Fouquieria splendens) (Correll and
Johnston, 1970).
Broad, level plateaus, rolling hills, and steep canyon walls characterized the
topography. Elevation ranged from 700 to 915 m. Mean annual precipitation for 2000
through 2002 was 25 cm; the average for 1963 through 1997 was 43 cm. Most rainfall
occurred from May to September, with highest amounts usually falling in September.
The average annual low temperature was 10°C; the average annual high was 26°C. In
winter temperatures ranged from a minimum daily low of-l°C to a maximum daily high
of 16°C and in summer ranged from 16 to 32°C (National Oceanic and Atmospheric
Administration, 2000; 2001; 2002).
Methods
We estimated deer densities from helicopter surveys of the study area in February,
2001. The pilot and one observer surveyed the study area by flying adjacent belt
transects approximately 200 m wide at an altitude of approximately 30 m. A Garmin
Geographic Positioning System unit (Garmin Ltd., Olathe, Kansas) was used to plot
transects and maintain parallel flight lines. Surveys began at 0800 hrs and ended at 1700
hrs; the entire study area was surveyed over 5 days. We counted deer on both sides of the
helicopter and used group composition, antier characteristics, and location to determine if
deer had been counted previously (DeYoung, 1985). We classified deer to species, sex,
and age (juvenile or adult). We calculated the number of deer per unit area and ratio of
males to females and juveniles to adult females for each ranch.
On 2-3 February 2000 and 30 January 2001, personnel from Holt Helicopters
(Uvalde, Texas) captured deer with a net gun fired from a helicopter (Krausman et al.,
1985). We recorded sex and condition of each animal and estimated the age of deer by
the tooth-wear and replacement method (Severinghaus, 1949; Robinette et al., 1957). We
fitted each male deer with a numbered plastic eartag and a 500 g radiocollar with a
mortality sensor (MOD-500NH; Telonics, Mesa, Arizona, USA).
We used a truck-mounted null-peak system consisting of two 4-eIement Yagi
antennas mounted on a rotating, telescoping boom to track telemetered deer. To estimate
telemetry system error, we followed methods outlined in White and Garrott (1990). All
personnel were required to triangulate radio-collars hung on poles or trees 1 m above
ground at random locations in the general vicinity of collared deer home ranges.
Bearings were obtained for 8-10 collars placed in different locations once per month,
using the same methodology used to triangulate study animals. Triangulated bearings
were compared to actual bearings calculated using the exact location of telemetry stations
and collars as determined with a Garmon'""' Global Positioning System (GPS). We used
the software program LOAS (Ecological Software Solutions, Sacramento, California) to
calculate test collar and deer locations. We located collared males >2 times per month
during January through August 2000 to 2002 to estimate home ranges. Individual deer
locations were not friangulated during September through mid-January because
landowners resfricted our access to the property during deer-hunting season, however we
were permitted to check for mortalities 1 weekend each month. We rotated the timing of
relocations sequentially through 3 time blocks (0500-1059,1100-1659,1700-2400). We
used the Animal Movement extension for ArcView (Hooge and Eichenlaub, 2000) to
calculate 95% and 50% fixed kernel home ranges and minimum convex polygons (MCP)
to facilitate comparison to previous studies. We calculated 50% kernel home ranges as
an approximation of each animal's core area (Loveridge and Macdonald, 2003).
We used ArcView software to identify the polygon created when the home ranges
of 2 individuals overlapped. Each overlap polygon was assigned to 1 of 3 dyads: mule
deer:mule deer (MM), mule deer:white-tailed deer (MW), or white-tailed deer:white-
tailed deer (WW) for comparisons. If >_1 location of either animal occurred within that
overlap polygon, we calculated an overlap index using the following ratio:
[(ni + n2)/(Ni + N2)] X 100
where U] and n2 refer to respective number of locations for each deer within the overlap
polygon, and Ni and N2 refer to the respective total number of locations recorded for each
deer used to calculate the home range (Chamberlain and Leopold, 2002). We used the
same procedure to calculate overlap indices for core areas.
We used Levene's test to check for homogeneity of variance for all comparisons
and examined residuals for normality (Zar, 1999; Bryce et al., 2002). We used analysis
10
of variance (ANOVA; a = 0.05) to compare mean home range sizes between years and
ages within species and between species and to test for interactions among years, seasons,
and species (White and Garrott, 1990). Because of unequal sample sizes, Fisher's LSD
test was used for means separation in overiap comparisons.
We monitored all animals for mortality at least weekly during the field season
(January - August), and monthly September through December during 2000 through
2002. When a mortality signal was detected, animals were located as quickly as possible
to determine cause of death. Cause of death was determined by field necropsy and by
searching for evidence of predation (Lawrence, 1995). We used the Mayfield method to
estimate seasonal and annual survival rates (Millspaugh and Marzluff, 2001) using the
software package MICROMORT (Heisey and Fuller, 1985). We used Wilcoxon
statistics to determine if overall survival functions differed between species (Allison,
1995). We used chi-square tests to test for differences in seasonal and annual survival
between species (Sauer and Williams, 1989) and adjusted a using a Bonferroni correction
factor (a/number of comparisons) to control experiment-wise error rate (Zar, 1999).
Results
Estimated deer densities (both sexes) during the study were 2.4 mule deer/km^
and 1.6 white-tailed deer/km^. We captured and fitted 10 males of each species with
radiocoUars in January 2000. In January 2001, we captured and collared an additional 8
males of each species. Mean age at capture of mule deer was 3.5 years (range = 3.5 to
4.5) and that of white-tailed deer was 4.5 years (range = 3.5 to 6.5). Home ranges and
11
core areas were calculated for 7 deer of each species having > 30 locations per year
(range: 30-51 locations/deer/year) in 2001 and 2002 (Millspaugh and Marzluff, 2001).
We did not have any deer with >30 locations during 2000 to calculate home range.
Average bearing error was ±7° based on friangulated locations of collars in known
locations. Levene's test for homogeneity of variance was not significant for any
comparison at or = 0.05 and examination of residuals indicated that data were normally
distributed. Of the 7 mule deer and 7 white-tailed deer for which >30 locations per year
were available (5 and 3, respectively), these were tracked in both years and we averaged
their calculated home range size for later analyses. Within each species, neither home
range size nor core area size differed among years or age classes, nor were there any
interactions (Table 2.1), so we pooled data for each species. Home range size and core
area size did not differ between species (Table 2.1). Mean home range size for mule deer
was 8.8 km ±1.6 (SE) and mean core area size was 1.0 km ± 0.2; mean home range size
for white-tailed deer was 7.4 km^ ± 1.3 and mean core area size was 1.1 km^ ± 0.2.
Minimum convex polygon size for mule deer home range was 8.3 km ±2.1 and for
white-tailed deer 4.8 km^ ± 0.8. The home range calculated for 2002 overlapped the
home range calculated for 2001 for 4 mule deer and 3 white-tailed deer. Only 1 mule
deer had no overlap of home ranges between years. The mean percentage of the 2001
home range that overlapped the 2002 home range was 0.4 ± 0.2 for mule deer and 0.5 ±
0.1 for white-tailed deer. The amount of overlap between years was not different
between species (Fi = 0.15, P = 0.71).
12
During both years, the home range of every study animal overiapped the home
range of > 1 other study animal. Each study animal's home range also overlapped the
home range of > 1 collared individual of the other species, except 1 white-tailed deer
whose home range did not overlap the home range of any collared mule deer.
Overlapping core areas between collared animals were less common than overlapping
home ranges (Table 2.2). Home range and core area overlap indices did not differ
between years within dyads (home range: Fi = 0.29, P = 0.59; core area: Fj = 0.14, P =
0.7), nor did we detect a year by dyad interaction (home range: F2 = 2.41, P = 0.10; core
area: Fj = 1.60, P = 0.29). Home range overlap indices did not differ between the MM
and WW dyads, but MW overlap indices were less than those of either intraspecific dyad
(F2 = 7.17, P = 0.002). We observed only 1 instance in which the calculated core areas
overlapped for a mule deer and a white-tailed deer, but no locations of either species
occurred within the overlap polygon. Core area overlap indices did not differ between
MM and WW dyads (Fi = 1.25, P = 0.35).
Eighteen male deer of each species were monitored for mortality from 31 January
2000 through 1 February 2003. Six mule deer and 4 white-tailed deer died during the
study. No radiocollared animals died of apparent capture myopathy and there were no
confirmed predation losses. Causes of mortality included fence entanglement (1 mule
deer), legal harvest (2 mule deer, 1 white-tailed deer), poaching (1 white-tailed deer),
starvation and/or disease (2 mule deer, 1 white-tailed deer), and undetermined causes (1
mule deer and 1 white-tailed deer).
13
Survival curves for males were not different between the species (X^ = 0.0004, P
= 0.98). Seasonal survival was not different between species (X i = 0.08, P = 0.99;
Figure 3) or years (X 2 = 0.46, P = 0.97) but tended to be lower during autumn and winter
(October 1 through January 31) for both species (Figure 2.1). Annual survival was not
different between years within species (X 2 = L33, F = 0.51 for mule deer; X^ = 0.54, P
= 0.76 for white-tailed deer), nor between species (X i =0.12, P = 0.94).
Discussion
According to competition theory, 2 species with similar life history traits should
partition resources when sympatric (Hardin, 1960). Diet does not appear to drive habitat
partitioning between these species (Hill and Harris, 1943; Allen, 1968; Martinka, 1968;
Krausman, 1978), suggesting some other resource (e.g., space) was driving resource
partitioning. Equivalent home range sizes may be a direct result of sympatry as both
species exist on the same forage resource. Although the larger body mass of mule deer
suggests they should require larger home ranges, factors such as forage quality and
availability (Relyea et al., 2000) and deer population density impact home range size
(Bertrand et al. 1996, Kilpatrick et al. 2001). The observed occurrence of interspecific
home range overlap in this study suggests either that only partial avoidance is necessary
to permit coexistence, or that habitat partitioning occurred on a temporal scale or at a
finer spatial scale than can be detected by home range-level analyses.
Both species appeared to maintain their home ranges within the same general area
during both years. Only 1 male, a 4.5 year-old mule deer, exhibited no overiap between
14
its home ranges in 2001 and 2002. This fidelity, coupled with the occurrence of
interspecific home range overiap, suggested that neither species was actively driving the
other out of the area during the study period. Core area overlap indicated a greater
potential for competition than home range overiap (Wauters and Dhondt, 1985), yet
interspecific core area overiap occurred only once. This avoidance could be an artifact of
our diurnal/crepuscular data collection, if deer spend more time bedded down versus
foraging and other activities during these periods. Thus, the smaller degree of overlap
between the species core areas could be due in part to differences in preferred bedding
sites, as mule deer prefer bed sites with less cover and steeper slopes (Avey et al., 2003).
Avoidance of the other species' core areas may be sufficient partitioning to permit
coexistence.
Because we were unable to track deer during September through December, our
home range estimates were probably underestimates, as male deer tend to increase
movement outside of their home range during the breeding season (Dickinson and
Garner, 1979; Rodgers et al., 1978; Gallina et al., 1997; Relyea and Demarais, 1994).
Mule deer on the Elephant Mountain Wildlife Management Area in the Trans-Pecos,
Texas, tracked during all seasons had harmonic mean estimator home ranges of 13.9 km^
in year 1 and 13.6 km^ in year 2. These estimates may be larger than the estimates for
this study (8.8 km^ for mule deer and 7.4 km^ for white-tailed deer) due to the inclusion
of breeding season, but seasonal home ranges were not reported (Relyea et al., 2000).
The Elephant Mountain herd was subject to mountain lion predation (Lawrence et al.,
2004) but the effect of predation on home range size was not explored. Home range
15
estimates for mule deer males in this study were smaller than those reported for allopatric
male mule deer during winter (28.2 km^), summer (19.4 km^), and fall (17.1 km^) in the
Texas Panhandle (Koerth, 1981), and considerably smaller than those reported for Rocky
Mountain mule deer (O. h. hemionus) sympatric with white-tailed deer (26.3 km^ for
mule deer males) in Colorado (Whittaker, 1995). Our MCP estimates were similar to
those of 2 adult desert mule deer during spring and summer in southern Arizona (6.2 km^
and 4.7 km ; Rodgers et al., 1978). Seasonal MCP home ranges calculated for mule deer
in the mountains of western Arizona were much larger, ranging from a mean of 37.5 km^
± 10.0 during April through June to a mean of 91.9 km^ ± 27.2 during January through
March (Krausman and Etchberger, 1995). White-tailed deer inhabiting the desert of
•y
northeastern Mexico also had larger annual MCP home range estimates (20.5 km ± 1.4).
This did not appear to be due only to the increased movement of males during the rut, as
the smallest seasonal home range average was 16.0 km^ during July through October
(Gallina et al., 1997). The effects of predation on home range size are difficult to assess
from the literature, as studies may not specify the presence or absence of predators if
survival or mortality factors are not specific objectives of the research.
Increased brush cover across the region has resulted in improved habitat
suitability for white-tailed deer (Wiggers and Beasom, 1986) and may suppress or negate
any advantage mule deer may have from longer occupancy of the area (Anthony, 1972).
Drought in desert areas can decrease survival and productivity of sympatric deer
(Anthony, 1976), reducing apparent competition by suppressing both populations.
Rainfall during our study was 18 cm below average; drought may have narrowed species-
16
specific differences in survival as well as home range size. Male deer tend to suffer
higher overall mortality rates than females (Gavin et al., 1984; Dusek et al., 1989;
Bartman et al., 1992; Van Deelen et al., 1997). Susceptibility to hunting mortality tends
to be greater for males (McCuIlough, 1979; Coe et al., 1980; Dusek et al., 1989), due to
dispersal (Roseberry and Klimsfra, 1974) and disproportionate harvest of male deer by
hunters (Van Deelen et al., 1997). Harvest by hunters (>30% of mortalities in this study)
did not appear to affect either species disproportionally. In the Trans-Pecos region of
west Texas, legal harvest was the most important cause of mortality for adult male mule
deer (Lawrence et al., 2004). Survival in our study was lowest during autumn and winter,
which coincided with the rut and post-rut periods, for which decreased survival rates have
been reported in other studies of each species (Nelson and Mech, 1986; Dusek et al.,
1989; Van Deelen et al., 1997; Lawrence et al. 2004). Lower fall and winter survival
rates resulted from increased mortality due to harvest and drought-related malnutrition,
rather than effects of winter.
Competition may be suppressed in sympatric populations of prey species subject
to predation (Hastings, 1978). Predation mortality may be additive or compensatory
depending on a myriad of environmental and population-specific factors (Ballard et al.,
2001). Variation in and unknown interactions between habitat carrying capacity, weather
and climate, and competition with other species make it difficult to ascertain the limiting
or regulating effect of predators within a study population; attempting to compare results
among studies conducted under differing circumstances must be done with caution
(Ballard et al., 2001). Annual survival rates of adult male mule deer in the Trans-Pecos
17
subject to mountain lion predation ranged from 0.54 to 0.80 (Lawrence et al., 2004). The
annual survival rate of male and female mule deer (0.72) was lower than that of white-
tailed deer (0.81) in a sympatric deer herd in south-central British Columbia where deer
were subject to predation by mountain lions (Robinson et al., 2001). Annual survivorship
of adult mule deer subject to mountain lion predation in the Great Basin ranged from 0.64
to 0.88 (Bleich and Taylor, 1998). Survival of adult male white-tailed deer in south
Texas subject to coyote predation ranged from 0.65 to 0.74 (DeYoung, 1989). Estimated
survival of male mule deer in this study was 0.76, similar to that of white-tailed deer
(0.80), but we observed no instances of predation on male deer of either species.
Survival of male mule deer over the course of the study was greater than means reported
for adult male mule deer (0.60) in Colorado (White and Bartmann, 1983) and in
Washington (0.50; McCorquodale, 1999) where deer herds were migratory and subject to
natural predators. Overall survival rate of white-tailed deer males in this study was
higher than that reported for adult male white-tailed deer in Minnesota (0.47; Nelson and
Mech, 1986) and in northern and southern New Brunswick (0.57 and 0.38 respectively;
Whitlaw et al., 1998), areas with harsh winter weather and natural predators. Seasonal
survival rates for white-tailed males in our study appeared similar to rates reported for
white-tailed males during summer (1.0) and winter and spring (0.78) in Michigan (Van
Deelen et al., 1997). The relatively high survival rates during spring and summer during
our study may be the result of the nonmigratory nature of deer in this area, a lack of
predators, and mild winters. That no mortalities were confirmed as predator losses was
expected, given historical (Cook, 1984) and continued intensive predator control to
18
protect livestock, particulariy sheep. Of the predators known to prey on deer, only
bobcats were continually present on the study area during our 3 years of study. A pair of
coyotes with 3 pups appeared on one ranch during June 2002, but were killed within 2
weeks of their discovery. Neither bobcats nor coyotes are considered important predators
on adult deer (Ballard et al., 2001). The lack of predation losses indicated that additional
efforts at predator control or removal would likely have little impact on adult male
survival, although potential effects of control on fawn survival are unknown (Ballard et
al., 2001). Survival rates for mule deer in the Southwestern U.S. are variable, both in the
presence and absence of predators, and in most cases, our estimates were near or slightiy
greater than the higher values reported. This was consistent with Bleich and Taylor's
(1998) supposition that predation can have significant impacts on deer herds in highly
variable environments.
19
Literature Cited
Allen, E. O. 1968. Range use, foods, condition, and productivity of white-tailed deer in Montana. Journal of Wildlife Management 32:130-141.
Allison, P. D. 1995. Survival analysis using SAS: a practical guide. SAS Institute, Inc., Gary, North Carolina.
Anthony, R. G. 1972. Ecological relationships between mule deer and white-tailed deer in southeastern Arizona. Doctoral dissertation. University of Arizona, Tucson.
Anthony, R. G. 1976. Influence of drought on diets and numbers of desert deer. Journal of Wildlife Management 40:140-144.
Avey, J. T., W. B. Ballard, M. C. Wallace, M. H. Humphrey, P. K. Krausman, F. Harwell, and E. B. Fish. 2003. Habitat relationships between sympatric mule deer and white-tailed deer in Texas. Southwestern Naturalist 48:644-653.
Ballard, W. B., D. Lutz, T. W. Keegan, L. H. Carpenter, and J. C. deVos, Jr. 2001. Deer-predator relationships: a review of recent North American studies with emphasis on mule and black-tailed deer. Wildlife Society Bulletin 29:99-115.
Bartmann, R. M., G. C. White, and L. H. Carpenter. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monographs 121.
Berfrand, M. R., A. J. DeNicoIa, S. R. Beissinger, and R. K. Swihart. 1996. Effects of parturition on home ranges and social affiliations of female white-tailed deer. Journal of Wildlife Management 60:899-909.
Bleich, V. C, and T. J. Taylor. 1998. Survivorship and cause-specific mortality in five populations of mule deer. Great Basin Naturalist 58:265-272.
Bryce, J., P. J. Johnson, and D. W. Macdonald. 2002. Can niche use in red and grey squirrels offer clues for their apparent coexistence? Journal of Applied Ecology 39:875-887.
Butier, L. D.. and J. P. Workman. 1993. Fee hunting in the Texas Trans Pecos area: a descriptive and economic analysis. Journal of Range Management 46:38-42.
Chamberlain, M. J. and B. D. Leopold. 2002. Spatio-temporal relationships among adult raccoons (Procyon lotor) in central Mississippi. American Midland Naturalist 148:297-308.
20
Coe, R. J., R. L. Downing, and B. S. McGinnes. 1980. Sex and age bias in hunter-killed white-tailed deer. Journal of Wildlife Management 44:245-249
Cook, R. L. 1984. Texas. Pages 457-474 in L. K. Halls, editor. White-tailed deer: ecology and management. Stackpole Books, Harrisburg, Pennsylvania, USA.
Correll, D. S. and M. C. Johnston. 1970. Manual of the vascular plants of Texas. Texas Research Foundation, Renner, Texas, USA.
DeYoung, C. A. 1985. Accuracy of helicopter surveys of deer in south Texas. Wildlife Society Bulletin 13:146-149.
DeYoung, C. A. 1989. Mortality of adult male white-tailed deer in south Texas. Journal of Wildlife Management 53:513-523
Dickinson, T. G., and G. W. Garner. 1979. Home range use and movements of desert mule deer in southwestern Texas. Proceedings of the Annual Conference of Southeastern Fish and Wildlife Agencies 33:267-278.
Dusek, G. L., R. J. Mackie, J. J. Herriges, Jr., and B. B. Compton. 1989. Population ecology of white-tailed deer along the Lower Yellowstone River. Wildlife Monographs 104.
Gallina, S., S. Mandujano, J. Bello, and C. Delfin 1997. Home-range size of white-tailed deer in northeastern Mexico. Pages 47-50 in J. DeVos, Jr., editor. Proceedings of the Deer/Elk Workshop. Rio Rico, Arizona.
Gavin, T. A., L. H. Suring, P. A. Vohs, Jr., and E. C. Meslow. 1984. Population characteristics, spatial organization, and natural mortality in the Columbian white-tailed deer. Wildlife Monographs 91.
Hardin, G. 1960. The competitive exclusion principle. Science 131:1292-1297.
Harveson, L. A., M. E. Tewes, N. J. Silvy, and J. Rutiedge. 2000. Prey use by mountain lions in southern Texas. Southwestern Naturalist 45:472-476
Harwell, W. F., and H. G. Gore. 1981. White-tailed deer population trends. Job Performance Report. Federal Aid Project Number W-109-R-4. Job Number 1. Texas Parks and Wildlife Department, Austin, Texas, USA.
Hastings, A. 1978. Spatial heterogeneity and the stability of predator-prey systems: Predator-mediated coexistence. Theoretical Population Biology 14:380-395.
21
Heisey, D. M., and T. K. Fuller. 1985. Evaluation of survival and cause-specific mortality rates using telemetry data. Journal of Wildlife Management 49:668-674.
Hill, R. R., and D. Harris. 1943. Food preferences of Black Hills deer. Journal of Wildlife Management 7:233-235.
Hooge P. N. and B. Eichenlaub. 2000. Animal movement extension to ArcView. Ver. 2.0. Alaska Science Center - Biological Science Office, U.S. Geological Survey, Anchorage, Alaska, USA.
Kilpatrick, H. J., S. M. Spohr, and K. K. Lima. 2001. Effects of population reduction on home ranges of female white-tailed deer at high densities. Canadian Journal of Zoology 79:949-954.
Koerth, B.H. 1981. Habitat use, herd ecology, and seasonal movements of mule deer in the Texas Panhandle. Master's Thesis, Texas Tech University, Lubbock, USA.
Krausman, P. R. 1978. Forage relationship between two deer species in Big Bend National Park, Texas. Journal of Wildlife Management 42:101-107.
Krausman, P. R., and R. C. Etchberger. 1995. Response of desert ungulates to a water project in Arizona. Journal of Wildlife Management 59:292-300.
Krausman, P. R., J. J. Hervert, and L. L. Ordway. 1985. Capturing deer and mountain sheep with a net-gun. Wildlife Society Bulletin 13:71-73.
Lawrence, R. K. 1995. Population dynamics and habitat use of desert mule deer in the Trans-Pecos Region of Texas. Unpublished Ph.D. dissertation, Texas Tech University, Lubbock.
Lawrence, R. K., S. Demarais, R. A. Relyea, S. P. Haskell, W. B. Ballard, and T. L. Clark. 2004. Desert mule deer survival in southwest Texas. Journal of Wildlife Management 68:561-569.
Loveridge, A. J., and D. W. Macdonald. 2003. Niche separation in sympatric jackals (Canis mesomelas and Canis adustus). Journal of Zoology 259:143-153.
Martinka, C. J. 1968. Habitat relationships of white-tailed and mule deer in northern Montana. Journal of Wildlife Management 32:558-565.
McCorquodale, S. M. 1999. Movements, survival, and mortality of black-tailed deer in the Klickitat Basin of Washington. Journal of Wildlife Management 63:861-871.
22
McCuIlough, D. R. 1979. The George Reserve deer herd: population ecology of a K-selected species. University of Michigan Press, Ann Arbor, Michigan, USA.
Michael, E. D. 1965. Movements of white-tailed deer on the Welder Wildlife Refuge. Journal of Wildlife Management 29:44-52.
Millspaugh, J. J., and J. M. Marzluff. 2001. Radio tracking and animal populations. Academic Press, San Diego, California.
National Oceanic and Atmospheric Adminisfration. 2000. Annual climatological summary; Big Lake 2, Texas.
National Oceanic and Atmospheric Administration. 2001. Annual climatological summary; Big Lake 2, Texas.
National Oceanic and Atmospheric Administration. 2002. Annual climatological summary; Big Lake 2, Texas.
Nelson, M. E., and L. D. Mech. 1986. Mortality of white-tailed deer in northeastern Minnesota. Journal of Wildlife Management 50:691-698.
Relyea, R. A., and S. Demarais. 1994. Activity of desert mule deer during the breeding season. Journal of Mammalogy 75:940-949.
Relyea, R. A., R. K. Lawrence, and S. Demarais. 2000. Home range of desert mule deer: testing the body-size and habitat-productivity hypotheses. Journal of Wildlife Management 64:146-153.
Robinette, W. L., D. A. Jones, G. Rogers, and J. S. Gashwiler. 1957. Notes on tooth development and wear for Rocky Mountain mule deer. Journal of Wildlife Management 21:134-153.
Robinson, H. S., R. B. Wielgus, and J. C. Gwilliam. 2001. Cougar predation and population growth of sympatric mule deer and white-tailed deer. Canadian Journal of Zoology 80:556-568
Rodgers, K. J., P. F. Ffolliott, and D. R. Patton. 1978. Home range and movement of five mule deer in a semidesert grass-shrub community. United States Department of Agriculture Forest Service Research Note RM-355.
Roseberry, J. L., and W. D. Klimstra. 1974. Differential vulnerability during a controlled deer harvest. Journal of Wildlife Management 38:499-507.
23
Sauer, J. R., and B. K. Williams. 1989. Generalized procedures for testing hypotheses about survival or recovery rates. Journal of Wildlife Management 53:137-142.
Severinghaus, C. A. 1949. Tooth development and wear as criteria of age in white-tailed deer. Journal of Wildlife Management 13:195-216.
Smith, W. P. 1987. Dispersion and habitat use by sympatric Columbian white-tailed deer and Columbian black-tailed deer. Journal of Mammalogy 68:337-347.
Van Deelen, T. R., H. Campa III, J. B. Haufler, and P. D. Thompson. 1997. Mortality patterns of white-tailed deer in Michigan's upper peninsula. Journal of Wildlife Management 61:903-910.
Wauters, L. A., and A. A. Dhondt. 1985. Population dynamics and social behaviour of red squirrel populations in different habitats. Proceedings of the International Congress of Game Biologists 17:311-318.
White, G. C, and R. M. Bartmann. 1983. Estimation of survival rates from band recoveries of mule deer in Colorado. Journal of Wildlife Management 47:506-511.
White, G. C, and R. A. Garrott. 1990. Analysis of wildlife radio-tracking data. Academic Press, San Diego, California, USA.
Whitiaw, H. A., W. B. Ballard, D. L. Sabine, S. J. Young, R. A. Jenkins and G. J. Forbes. 1998. Survival and cause-specific mortality rates of adult white-tailed deer in New Brunswick. Journal of Wildlife Management 62:1335-1341.
Whittaker, D.G. 1995. Patterns of coexistence for sympatric mule and white-tailed deer on Rocky Mountain Arsenal, Colorado. Doctoral Dissertation, University of Wyoming, Laramie, USA.
Wiggers, E.P., and S. L. Beasom. 1986. Characterization of sympatric or adjacent habitats of two deer species in west Texas. Journal of Wildlife Management 50:129-134.
Zar, J. H. 1999. Biostatistical Analysis. 4'" edition. Prentice-Hall, Inc. Upper Saddle River, New Jersey, USA.
24
Table 2.1. Comparison of mean 95% and 50% (core area) kernel home range estimates of sympatric adult male mule and white-tailed deer in west-cenfral Texas, January through August, 2001-2002, using analysis of variance.
Estimate
95%
Kernel
50%
kernel
Species
Mule deer
n = 7
White-tailed deer
n = 7
Combined n = 14
Mule deer
n = 7
White-tailed deer
n = 7
Combined n = 14
Variable
Age
Year
Age X Year
Age
Year
Age X Year
Species x Year
Species
Age
Year
Age X Year
Age
Year
Age X Year
Species x Year
Species
Degrees of freedom
2
1
3
4
1
6
3
1
2
1
3
4
1
6
3
1
F statistic
0.22
1.00
10.9
1.47
0.06
1.43
0.87
0.46
0.15
1.80
1.45
1.20
0.34
0.71
0.74
0.15
P-value 0.81
0.34
0.41
0.34
0.81
0.41
0.47
0.51
0.87
0.21
0.93
0.41
0.57
0.69
0.54
0.71
25
Table 2.2. Mean overlap indices for 95% kernel home ranges and 50% kernel core areas of sympatric adult male mule and white-tailed deer in west-central Texas, January through August, 2001-2002. Indices for home range and core area were tested between species using analysis of variance (ANOVA). Fisher's LSD was used for means separation when ANOVA was significant. Means followed by the same letter within a year were not different at a = 0.05.
Dyad n x overlap SE
Home ranges MM 17 29.32a 6 25
WW 15 44.32a 10.08
MW 10 8.57b 3.24
Core areas MM 3 39.10 19.75
WW 5 48.36 10.84
26
Mule deer
>
3 VI
<^ Cv'fe
-sS^ .<i^ rxV
-. ^ ^ ^ • • ^ ^ ^ < ^
> cCV -S5 a- . ^
h^^ J^ 4^ ^-^ .^^
White-tailed deer
Season and year
- ^ .c, - ^ - ?> ^^ ^ ^^
<5 y ^ ,4i ^ cs: .o* ,4 ^ c,<
^ ^ ^ ^ V ^
Season and year
Figure 2.1. Survival curves for sympatric adult male white-tailed deer and mule deer (n 18 of each species) in west-central Texas, 31 January 2000 through 31 January 2003.
27
CHAPTER III
HOME RANGE SIZE AND SURVIVAL OF SYMPATRIC FEMALE DEER IN
TEXAS
Abstract
Sympatry can create special dynamics between species' populations, impacting
the creation of effective management sfrategies. We estimated home range (95% kernel)
and core area (50% kernel) sizes and overlap and survival of sympatric female desert
mule deer (Odocoileus hemionius) and white-tailed deer (O. virginianus) in west-central
Texas. We captured 50 mule deer and 53 white-tailed deer, fitted them with radiocoUars,
and monitored them during 2000 through 2003. Average (+ SE) spring home range size
of mule deer was 3.9 + 0.32 km^ while that of white-tailed deer was 4.32 ± 0.77 km ;
summer home range sizes were 2.82 + 0.32 km^ and 2.08 + 0.23 km , respectively.
Interspecific seasonal home range overlap indices were similar to intraspecific overlap.
Core area overlap also was similar within and between species during summer, but
interspecific core area overlap was less common during spring. Small home range size
may indicate that deer densities are relatively high on this study area. Mean annual
survival of mule deer (0.91 + 0.08) was greater than survival of white-tailed deer ( 0.64 +
0.10). Starvation and disease were the most commonly identified cause of death,
suggesting management to improve the quality and abundance of forage may be
warranted. In addition, the lack of predation on adults may be contributing to the long-
28
term persistence of mule deer on the study area despite encroachment of white-tailed deer
populations.
Introduction
The distributions of desert mule deer (Odocoileus hemionus) and white-tailed deer
(O. virginianus) in Texas overiap in portions of the Trans-Pecos region, the western edge
of the Edwards Plateau, and in the Panhandle (Smith, 1987). In recent decades white-
tailed deer have become more abundant in areas previously considered desert mule deer
habitat (Harwell and Gore, 1981), while mule deer have decreased or disappeared entirely
from some areas (Wiggers and Beasom, 1986). Our objectives were to investigate home
range sizes differences between the 2 species, examine the degree of overlap of home
ranges and core areas, identify causes of mortality, and estimate survival rates. Because
allopatric female white-tailed deer in semi-arid and arid regions tend to have smaller
home ranges (Gallina et al., 1997) than allopatric female mule deer in similar
environments (Dickinson and Garner, 1979; Hayes and Krausman, 1993; Relyea et al.,
2000), we predicted that desert mule deer would have larger home ranges than white-
tailed deer in west-central Texas. Furthermore, intraspecific and interspecific
competition tend to compress home range size in ungulates (Courtois et al., 1998).
However, because the species are not territorial and have similar diets (Anthony, 1972;
Krausman, 1978) we predicted that there would be overlap in home ranges. Other studies
of sympatric deer have found that the species maintain separate distributions, but these
studies occurred in the prairies of Montana (Wood et al. 1989) and in rolling grasslands
29
of Colorado (Whittaker 1995), where deer herds are subject to harsh winter conditions
and are at least partially migratory. Other studies have concluded that while white-tailed
deer have higher productivity, mule deer have greater survival rates (Wood et al.,1989;
Whittaker and Lindzey, 2001). Population estimates for both species in west-central
Texas have remained stable over the past decade (Texas Parks and Wildlife Department,
unpublished reports), suggesting that survival rates and productivity are similar between
the species, or there is a tradeoff between productivity and fawn or adult survival similar
to that seen in sympatric herds in Montana (Wood et al.,1989) and Colorado (Whittaker
and Lindzey, 2001). We suspected that white-tailed deer would have higher overall
survival because while desert mule deer have been present historically in this region,
white-tailed deer have successfully expanded the periphery of their distributional range
into the study area (Wiggers and Beasom, 1986). Furthermore, studies which examined
sympatric deer in Montana and in Washington found that as white-tailed deer populations
expanded into traditional allopatric mule deer ranges, mule deer populations suffered
declines (Wood et al. 1989, Weilgus et al. 2000).
Study area
The study areas encompassed 5 contiguous ranches (approximately 323 km^) on
the western edge of the Edwards Plateau in the northwest corner of Crockett County,
Texas. Because all ranches were managed for livestock and/or hunting leases, water was
available from windmills in all pastures year-round. Large predators such as coyote
(Canis latrans), black bear (Ursus americanus), wolves (C. lupus) and mountain lions
30
(Puma concolor) were absent from the study area as a result of long-term predator control
efforts (Cook, 1984). Bobcats (Felis rufus) were present during the study period.
Population density was unknown, but 54 bobcats were removed on a portion of the study
area (165.9 km^) during December through February of 2001 (L. Clark, ranch foreman,
personal communication).
Mesquite (Prosopis sp.), creosote (Larrea tridentata), tarbush (Flourensis cernua)
and prickly pear (Opuntia sp.) were dominate vegetation in lower elevation areas.
Juniper (Juniperus sp.) was the dominant woody species on mesas. Washes supported
dense thickets of hackberry trees (Celtis occidentalis) and littie walnut trees (Juglans
microcarpa). Slopes supported xeriphytic plants including yuccas (Yucca sp.) and
ocotillo (Fouquieria splendens) (Correll and Johnston, 1970). Livestock grazing, oil
production, and hunting were either ongoing or had ceased within the previous 5 years on
all ranches.
Topography consisted of broad, level plateaus, rolling hills, and steep canyons.
Elevation ranged from 700 m to 915 m. Mean annual precipitation for 2000 through
2002 was 25 cm (the average for 1963 through 1997 was 43 cm). Most rainfall occurred
during May through September; greatest amounts usually occurred during September.
The average annual low temperature was 10°C and the average annual high was 26°C. In
winter temperatures ranged from a minimum daily low of-l°C to a maximum daily high
of 16°C and in summer ranged from 16 to 32°C (National Oceanic and Atmospheric
Administration, 2000; 2001; 2002).
31
Methods
We estimated deer densities from helicopter surveys conducted in February 2001.
The pilot and one observer surveyed the study area by flying adjacent belt transects
approximately 200 m wide at an altitude of approximately 30 m. A Garmin Geographic
Positioning System unit (Garmin Ltd., Olathe, Kansas) was used to plot fransects and
maintain parallel flight lines. Surveys began at 0800 hrs and ended at 1700 hrs; the entire
study area was surveyed over 5 days. We counted deer on both sides of the helicopter
and used group composition, antler characteristics, and location to detennine if deer had
been counted previously (DeYoung, 1985). We classified deer to species, sex, and age
(juvenile or adult). We calculated the number of deer per unit area and ratio of males to
females and juveniles to adult females for each ranch.
On 2-3 February 2000 and 30 January 2001, personnel from Holt Helicopters
(Uvalde, Texas) captured deer with a net gun fired from a helicopter following the
protocol outiined by Krausman et al. (1985). We recorded sex and condition of each
animal and estimated the age of deer by tooth-wear and replacement (Severinghaus,
1949; Robinette et al., 1957). We fitted each deer with a numbered plastic eartag and a
500 g radiocollar equipped with a motion-sensitive mortality switch (Telonics, Mesa,
Arizona, USA).
We conducted radio-tracking with a truck-mounted null-peak system consisting of
2 4-element Yagi antennas mounted on a rotating, telescoping boom in the truck-bed. To
estimate telemetry system error, we followed methods outlined in White and Garrott
(1990). AU personnel were required to triangulate radio-collars hung on poles or trees 1
32
m above ground at random locations in the general vicinity of collared deer home ranges.
Bearings were obtained for 8-10 collars placed in different locations once per month,
using the same methodology used to triangulate study animals. Triangulated bearings
were compared to actual bearings calculated using the exact location of telemetry stations
and collars as determined with a Garmon^M Global Positioning System (GPS). We used
the software program LOAS (Ecological Software Solutions, Sacramento, California) to
determine deer locations. We located collared females >4 times per month during
January through August 2000 to 2002 to estimate home ranges. Deer were not located
during hunting season (September through mid-January) in compliance with landowners'
wishes. We rotated the timing of relocations sequentially through 3 time blocks (0500-
1059, 1100-1659, 1700-2400). We used the Animal Movement extension for ArcView
(Hooge and Eichenlaub, 2000) to calculate 95% and 50% fixed kernel home ranges and
minimum convex polygons (MCP). We calculated MCP home range estimates for 13-17
mule deer and 14-19 white-tailed deer per season and year for comparison to previously
published studies, but used only home ranges generated with kernel estimators for further
analysis. We used 50% kernel home ranges as an approximation of each animal's core
area (Loveridge and Macdonald, 2003). Home ranges were calculated for winter-spring,
which encompassed the gestation period (January - April) and summer, the fawning
season (May - August). Seasonal home ranges and core areas were calculated each year
for individuals having >30 locations in that season.
We used ArcView software to identify the polygon created when core areas
(CA's) or home ranges (HR's) overiapped (Figs. 1, 2). Each overiap polygon was
33
assigned to 1 of 3 dyads: mule deer:mule deer (MM), mule deer:white-tailed deer (MW),
or white-tailed deer:white-tailed deer (WW). If at least 1 location of either animal
occurred within that overlap polygon, we calculated an overlap index using the following
ratio:
[(ni + n2)/(Ni + N2)] X 100
where ni and n2 refer to respective number of locations for each deer within the
overlap polygon, and Ni and N2 refer to the respective total number of locations recorded
for each deer used to calculate the home range (Chamberiain and Leopold, 2002). We
used this same procedure to calculate overlap indices for core areas. We also calculated
overlap indices for spring and summer home ranges of individual deer to quantify
seasonal differences. We did not calculate interspecific overlap indices for 2000 because
only 3 instances of interspecific home range overlap were detected. This was likely due
to the fact that in 2000 we endeavored to spread our capture effort throughout the entire
study area. During the 2001 capture, we concentrated our efforts in the center of the
study area, resulting in increased detection of overlapping core areas and home ranges
among collared animals.
We used Levene's test to check for homogeneity of variance for all comparisons
and examined residuals for normality (Zar, 1999; Bryce et al., 2002). If Levene's test
was insignificant and data were normally distributed, we used analysis of variance
(ANOVA; a = 0.05) to compare mean home range sizes between years and ages within
species and between species, and to test for interactions (White and Garrott, 1990).
When Levene's test was significant, indicating inequality of variances, we used Kruskal-
34
Wallis for one-way comparisons, and Friedman's test for 2-way comparisons (Zar, 1999).
Because of unequal sample sizes, Fisher's LSD test was used for means separation in
overlap comparisons.
We monitored all animals for mortality at least weekly during the field season
(January - August), and monthly September through December during 2000 through
2002. When a mortality signal was detected, animals were located as quickly as possible
to determine cause of death. Cause of death was determined by field necropsy and by
searching for evidence of predation (Lawrence et al., 2004). We used the staggered entry
design of the Kaplan-Meier product limit estimator to estunate seasonal and annual
survival and the log-rank test for homogeneity between groups (Kaplan and Meier, 1958;
Pollock et al., 1989). We adjusted a using a Bonferroni correction factor (a/number of
comparisons) to control experiment-wise error rate (Zar, 1999).
Results
Estimated deer densities during the study were 2.4 mule deer/km^ and 1.6 white-
tailed deer/km^. The number of males:females in 1999, prior to study initiation, was 1:3
for mule deer and 1:7 for white-tailed deer; the ratio in 2001 was 1:3 for both species.
The number of fawns per female in 1999 was 0.5:1 for mule deer and 0.4:1 for white-
taUed deer; in 2001, the ratio was 0.2:1 for both species.
We captured and fitted 40 females of each species with radiocoUars in January
2000. In January 2001, we captured and collared an additional 13 white-tailed deer and
10 mule deer. Mean age at capture was 4.5 years for both species (mule deer range = 2.5
35
to 6.5; white-taUed deer range = 1.5 to 7.5). Average bearing error was ±7° based on
triangulated locations of collars in known locations. Mean MCP home range sizes were
similar between species in both seasons (Table 3.1).
Mean 50% kernel core area size did not differ among seasons across years for
either species (mule deer: F5 = 1.28, P = 0.28; white-tailed deer: F5 = 1.05, P = 0.39).
Seasonal core area sizes were averaged across years within species to compare spring and
summer core area sizes (Table 3.2). Mean spring 50% core area size was greater than
summer core area size for white-taUed deer (Fi = 5.18, P = 0.03) but not for mule deer
(Fj = 0.79, P = 0.38). Mean 50% core area size was not different between mule deer and
white-tailed deer for either spring (Fj = 0.08, P = 0.78) or summer (Fi = 3.59, P = 0.06).
Mean 95% kernel home range size did not differ among seasons across years for
either species (mule deer: F5 = 0.70, P = 0.62; white-taUed deer: F5 = 1.74, P = 0.13;
Table 3.3). Mean spring 95% HR size was greater than summer HR size for white-tailed
deer (Fi = 8.50, P = 0.004) but not for mule deer (Fj = 1.56, P = 0.21). Within seasons,
mean 95% HR size was not different between mule deer and white-tailed deer for either
spring (Fl = 1.25, P = 0.27) or summer (Fi = 3.57, P = 0.06).
Within species, summer core area at least partially overlapped spring core area for
all individual deer during all years (Table 3.4). Overiap indices were not different among
years (Fj = 1.01, P = 0.37) or between species (F2 = 0.01, P = 0.92), nor was there a
species by year interaction (F2 = 0.97, P = 0.38). Home range overiap indices also were
not different among years (Fi = 0.85, P = 0.43) or between species (F2 = 0.18, P = 0.67),
nor was there a species by year interaction (F2 = 0.91, P = 0.41).
36
Seasonal core areas and home ranges of individual animals also overiapped across
years within seasons (Table 3.5). The overlap index for spring-to-spring core areas was
greater for mule deer than for white-tailed deer (Fi = 4.29, P = 0.04). Sunmier-to-
summer core area overiap was also greater for mule deer (Fi = 9.60, P = 0.003).
However, spring and summer home ranges were not different across years (Fi = 2.57, P =
0.12 and Fi = 3.25, P = 0.08, respectively).
We observed instances of interspecific and intraspecific overlap of home ranges
and core areas; however, differences among dyads occurred only in core areas (Table
3.6). In spring 2002, intraspecific overlap was greater than interspecific overlap for both
species (X^2 = 10.35, P = 0.006). With the exception of summer 2001, interspecific
overlap was less than intraspecific overlap during both seasons. The degree of
interspecific overlap did not differ among season/years for either species (F2 = 0.48, P =
0.69), but they were different among dyads (F2 = 3.03, P = 0.04). There was no dyad by
season and year interaction (F^ = 1.67, P = 0.13). Overlap of 95% kernel home ranges
was similar among all dyads across all seasons. There were no differences in overlap
indices for home ranges among seasons (F2 = 0.51, P = 0.68) or dyads (F2 = 0.74, P =
0.48), nor was there a dyad by season and year interaction (Fg = 0.64, F = 0.70).
Mule deer survival was greater than white-tailed deer survival throughout the
study (Figure 3.1). Mean annual survival was greater for mule deer (0.91 + 0.08; range
0.76 - 1.0) than for white-taUed deer (0.64 ± 0.10; range 0.48 - 0.83; X^i = 4.83, F =
0.05). Seasonal survival was also greater for mule deer during all seasons and years (X 1
= 4.58, F = 0.05). Eighteen radiocollared white-taUed deer and 9 mule deer died during
37
the study; 3 white-tailed deer and 6 mule deer were censored because they left the study
area or the collars failed. Female mule deer were not hunted and no collared female
white-taUed deer were harvested during the study period. Causes of mortality included
auto collision (1 white-taUed deer), poaching (2 white-tailed deer), predators (1 white-
tailed deer), and starvation or disease (2 mule deer, 3 white-tailed deer). Cause of
mortality could not be determined for 7 mule deer and 11 white-taUed deer.
Discussion
Differences in forage use and preference do not appear to be a universal
mechanism facUitating coexistence of these species (HiU and Harris, 1943; Allen, 1968;
Martinka, 1968; Krausman, 1978). According to competition theory, species with similar
life history traits should partition resources when they are sympatric if coexistence is to
occur (Hardin, 1960). Resource partitioning may be occurring based on some other
resource (e.g., space) or other ecological mechanisms (e.g., predation, density-dependent
factors) may facilitate coexistence (Saether, 1997). Home ranges tend to be larger as
habitats become more xeric (Wood et al., 1989); however, female mule deer in this study
had smaller home ranges than mule deer in other semi-arid and arid regions. Because of
their larger body mass, mule deer should require larger home range sizes than sympatric
white-tailed deer, but habitat productivity appears to have a greater impact on actual
home range sizes of ungulates (Relyea et al., 2000). Deer home range size tends to be
largest during the breeding season (Gallina et al., 1997) and we therefore may have
underestimated annual home range size for both species. In a sympatric area of Montana,
38
average polygon home range size of non-migratory female mule deer was 6.30 ± 0.61
km^ and that of white-taUed deer was 33.5 ± 6.22 km^ (Wood et al., 1989). Home ranges
for our sympatric herd also were smaller than those reported for female desert mule deer
in western Arizona (daytime MCP mean = 32.3 km , night = 25.5 km ; Hayes and
Krausman, 1993) and southwestern Arizona (121 km ; Rautenstrauch and Krausman,
1989). However, annual MCP estimates from this study (2.3 km^) were comparable to
those from a sympatric area of southwestern Texas where mountain lion predation occurs
(3.8 km ; Dickinson and Garner, 1979). Home range size of white-tailed deer in our
study was simUar to MCP estimates for white-tailed deer in northeastern Mexico (2.06 ±
•y
0.13 km ; GaUina et al., 1997) but was smaller than those of white-tailed deer in a
sympatric area of Montana (33.48 + 6.22 km ; Wood et al., 1989). Small home range
size may be indicative of relatively high deer densities on this study area; high ungulate
densities have been negatively correlated with home range size in ungulates (Marshall
and Whittington, 1969). These high densities are likely a result of the lack of predators
and low hunting pressure on the study area. Intraspecific and interspecific competition, if
occurring on the study area, would also compress home range size (Courtois et al., 1998),
but experimental manipulation of the herd would be required to determine if competition
was occurring.
The interspecific home range overlap we observed may indicate that habitat
partitioning occurred on a finer temporal or spatial scale than can be detected by home
range-level analyses. Interspecific overlap during summer was greater during 2001 when
spring rainfall was below normal, and decreased in 2002 when spring rainfall and
39
subsequent forage production were average. That interspecific home range overiap was
less than intraspecific overiap in spring suggests the species segregate to a greater extent
when forage resources were more abundant. Forage preferences of both species became
more divergent during droughts in Arizona, which may permit greater spatial overlap by
these species during drought (Anthony, 1976). It is possible that competition for forage
forced both species to forgo normal spatial avoidance during dry periods, however
temporal avoidance may still occur. Alternatively, possibly the amount of non-
overlapping home range area was sufficient to permit coexistence. Confirmation of
coexistence will require long-term monitoring to account for effects of environmental
variation (Bleich and Taylor, 1998).
Core area overlap provides a greater potential for competition between species
and conspecifics, assuming individuals spend more time within their core area relative to
their entire annual home range (Wauters and Dhondt, 1985). Areas of interspecific
overlap were smaller and occurred less frequently than intraspecific overlap, which may
indicate greater influence by interspecific competition on spatial distribution of individual
deer. Both species appeared to maintain their home ranges within the same general area
during both years, suggesting coexistence was occurring and neither species actively
drove the other out of the area during the study period. Sympatric deer in Colorado also
appeared to coexist via localized individual avoidance rather than complete exclusion of
one species from the area (Whittaker, 1995). However, white-tailed deer in our study
exhibited less overlap among their own seasonal home ranges across years, simUar to
sympatric female white-tailed deer in Montana, which also frequentiy shifted home
40
ranges in consecutive years (Wood et al., 1989). Competition from both mule deer and
conspecifics may be the cause of decreased individual philopatry, as adult deer shift core
areas in search of increased resources or to avoid competitors (Lesage et al., 2000).
Changes in female white-tailed deer home ranges may also have resulted from forage
availability differences related to annual precipitation rather than as a direct response to
the presence of mule deer.
Drought in desert areas may decrease survival and productivity of sympafric deer
(Anthony, 1976), reducing apparent competition by suppressing both populations.
However, independent of rainfall, survival may not reflect differences in population
dynamics possibly driven by competition. Survival was not different between sympatric
mule deer and white-tailed deer in Colorado and adult survival was not considered
significant factor driving observed differences in population dynamics of the 2 species
nor in population models constructed for that deer herd (Whittaker and Lindzey, 2001).
Unlike northern populations subjected to severe winter weather, lower fall and winter
survival rates in the herd in our study likely resulted from increased mortality due to
drought-related malnutrition, rather than winter weather-related stress. Survival of
female deer in our study was generally higher than survival rates reported from deer
herds subject to predation and/or severe winter weather. Mean annual survival for adult
female mule deer in Colorado, Idaho, and Montana was 0.85; variation across the
geographic area was low. Herds in all 3 states were thought to be regulated by similar
processes, particularly winter weather, however predation effects on adult deer were not
examined (Unsworth et al., 1999). Survival rates of mule deer (male and female
41
combined) were lower than rates for sympatric white-tailed deer (0.72 and 0.81
respectively) in south-central British Columbia, where deer must cope with harsh winters
and mountain lion predation (Robinson et al., 2002). Annual survival for adult female
black-tailed deer (O. h. columbianus) averaged 0.82, although survival feU to 0.71 during
a severe winter and deer were migratory (McCorquodale, 1999). Annual survival of
adult mule deer in the Great Basin area of California and Nevada ranged from 0.64
0.88; the primary source of mortality was mountain lion predation (Bleich and Taylor,
1998). Annual survival of females in a declining white-taUed deer herd in western South
Dakota ranged from 0.50 - 0.62, similar to annual rates for this study, however deer were
subject to coyote predation and were migratory (DePemo et al., 2000). Western South
Dakota is within the range of mule deer, however the authors did not mention the
presence or absence of mule deer in the area.
The coexistence of prey species that are potential competitors can be facilitated by
predation if it reduces apparent competition for resources (Hastings, 1978). Although
predation has been determined to be a primary limiting factor for many wild ungulates,
few studies have documented population level effects of predation on deer herds (Ballard
et al., 2001). The presence of large predators, particularly mountain lions, could result in
a mule deer decline, if increasing alternate prey (i.e., white-tailed deer) facilitated
increased predator populations, as has occurred in other western mule deer herds (Bleich
and Taylor, 1998; Crete and Daigle, 1999; Wielgus et al., 2000). In areas where either
species occurs with large predators, particularly mountain lions or wolves (Canis lupus),
predation is a significant source of mortality for adult deer (Ballard et al., 2001). Because
42
predation could be ruled out for most mortalities classified as unknown, the primary
causes of adult mortality in this deer herd were starvation, disease, and senescence.
Possibly, the lack of predation on adults was contributing to the long-term persistence of
mule deer on our study area. Annual survival of female mule deer in our study was
greater than that of female mule deer farther west in the Trans-Pecos region (0.59 to
0.88), where mountain lions accounted for 100% of predation losses of adult females
(Lawrence et al., 2004). Mountain lions in south Texas preferred white-tailed deer to
other wild prey available (Harveson et al., 2000). Of other predators known to prey on
deer, only bobcats (Lynx rufus) occurred on the study area during our 3 years of study.
Fifty-four bobcats were removed on a portion of the study area (165.9 km^) during
December through February of 2001 (L. Clark, ranch foreman, personal communication),
however population density was unknown. A pair of coyotes (Canis latrans) with 3 pups
appeared on 1 ranch during June 2002 but were killed within 2 weeks of their discovery.
Although a bobcat did kill 1 study animal (adult female white-tailed deer), neither
bobcats nor coyotes are considered important predators on adult deer (Ballard et al.,
2001). Absence of coyotes on our study area may contribute to continued sympatry.
Coyote predation on fawns in Colorado was believed to hinder white-tailed deer
recruitment, keeping population growth of white-tailed deer similar to that of mule deer
(Whittaker, 1995). Efforts at predator control or removal would likely have littie impact
on adult female survival given the current low-to-nonexistent level of predation.
Predation was demonstrated to be compensatory in a Colorado mule deer population
(Bartmann et al., 1992) and despite mountain lion predation on adult female mule deer in
43
the Trans-Pecos region, losses resulting from environmental stress continued, particularly
during drought (Lawrence et al., 2004). However, potential effects on fawn survival
were unknown (Ballard et al., 2001), and further research into the mechanisms of
coexistence in this sympatric herd should include study of fawn survival and mortality.
44
Literature Cited
Allen, E. O. 1968. Range use, foods, condition, and productivity of white-taUed deer in Montana. Journal of WUdlife Management 32:130-141.
Anthony, R. G. 1972. Ecological relationships between mule deer and white-tailed deer in southeastern Arizona. Doctoral dissertation. University of Arizona, Tucson.
Anthony, R. G. 1976. Influence of drought on diets and numbers of desert deer. Journal of WUdlife Management 40:140-144.
BaUard, W. B., D. Lutz, T. W. Keegan, L. H. Carpenter, and J. C. deVos, Jr. 2001. Deer-predator relationships: a review of recent North American studies with emphasis on mule and black-taUed deer. WUdlife Society Bulletin 29:99-115.
Bartmann, R. M., G. C. White, and L. H. Carpenter. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monographs 121.
Bleich, V. C, and T. J. Taylor. 1998. Survivorship and cause-specific mortality in five populations of mule deer. Great Basin Naturalist 58: 265-272.
Bryce, J., P. J. Johnson, and D. W. Macdonald. 2002. Can niche use in red and grey squirrels offer clues for their apparent coexistence? Journal of Applied Ecology 39:875-887.
Chamberiain, M. J., and B. D. Leopold. 2002. Spatio-temporal relationships among adult raccoons (Procyon lotor) in central Mississippi. American Midland Naturalist 148:297-308.
CorreU, D. S., and M. C. Johnston. 1970. Manual of the vascular plants of Texas. Texas Research Foundation, Renner, Texas.
Courtois, R., J. Labonte, and J. P. Ouellet. 1998. Movements and location of home range of Moose, Alces alces, in eastern Quebec. Canadian Field-Naturalist 112:602-610.
Crete, M., and C. Daigle. 1999. Management of indigenous North American deer at the end of the 20"' century in relation to large predators and primary production. Acta Veterinaria Hungarica. 47:1-16.
DePerno, C. S., J. A. Jenks, S. L. Griffin, and L. A. Rice. 2000. Female survival rates in a declining white-taUed deer population. WUdlife Society BuUetin 28:1030-1037.
45
DeYoung, C. A. 1985. Accuracy of helicopter surveys of deer in south Texas. Wildlife Society Bulletin 13:146-149.
Dickinson, T. G., and G. W. Garner. 1979. Home range use and movements of desert mule deer in southwestern Texas. Proceedings of the Annual Conference of Southeastern Fish and Wildlife Agencies 33:267-278.
Gallina, S., S. Mandujano, J. BeUo, and C. Delfin 1997. Home-range size of white-taUed deer in northeastern Mexico. Pages 47-50 in J. DeVos, Jr., editor. Proceedings of the Deer/Elk Workshop. Rio Rico, Arizona.
Hardin, G. 1960. The competitive exclusion principle. Science 131:1292-1297.
Harveson, L. A., M. E. Tewes, N. J. Silvy, and J. RuUedge. 2000. Prey use by mountain lions in southern Texas. Southwestern Naturalist 45:472-476
HarweU, W. F., and H. G. Gore. 1981. White-taUed deer population trends. Job Performance Report. Federal Aid Project Number W-109-R-4. Job Number 1. Texas Parks and Wildlife Department, Austin, Texas, USA.
Hayes, C.L., and P.R. Krausman. 1993. Nocturnal activity of female desert mule deer. Journal of WUdlife Management 57:897-904.
Hastings, A. 1978. Spatial heterogeneUy and the stabUity of predator-prey systems: Predator-mediated coexistence. Theoretical Population Biology 14:380-395.
HiU, R. R., and D. Harris. 1943. Food preferences of Black HiUs deer. Journal of WUdlife Management 7:233-235.
Hooge P. N., and B. Eichenlaub. 2000. Animal movement extension to ArcView. Ver. 2.0. Alaska Science Center - Biological Science Office, U.S. Geological Survey, Anchorage, Alaska.
Kaplan, E.L., and P. Meier. 1958. Nonparametric estimation from incomplete observation. Journal of the American Statistical Association 53:457-481.
Krausman, P. R. 1978. Forage relationship between two deer species in Big Bend National Park, Texas. Journal of WUdlife Management 42:101-107.
Krausman, P. R., J. J. Hervert, and L. L. Ordway. 1985. Capturing deer and mountain sheep with a net-gun. WUdlife Society Bulletin 13:71-73.
46
Lawrence, R. K., S. Demarais, R. A. Relyea, S. P. HaskeU, W. B. Ballard, and T. L. Clark. 2004. Desert mule deer survival in southwest Texas. Journal of WUdlife Management 68:561-569.
Lesage, L., M. Crete, Huot, J., Dumont, A., and Ouellet, J. 2000. Seasonal home range size and philopatry in two northern white-tailed deer populations. Canadian Journal of Zoology 78:1930-1940.
Loveridge, A. J., and D. W. Macdonald. 2003. Niche separation in sympatric jackals (Canis mesomelas and Canis adustus). Journal of Zoology 259:143-153.
MarshaU, A.D., and R. W. Whittington. 1969. A telemetric study of deer home ranges and behavior of deer during managed hunts. Proceedings of the Annual Conference of Southeastern Fish and Wildlife Agencies 20:30-46.
Martinka, C. J. 1968. Habitat relationships of white-tailed and mule deer in northern Montana. Journal of WUdlife Management 32:558-565.
McCorquodale, S. M. 1999. Movements, survival, and mortality of black-taUed deer in the Klickitat Basin of Washington. Journal of Wildlife Management 63:861-871.
National Oceanic and Atmospheric Administration. 2000. Annual climatological summary; Big Lake 2, Texas.
National Oceanic and Atmospheric Administration. 2001. Aimual climatological summary; Big Lake 2, Texas.
National Oceanic and Atmospheric Administration. 2002. Annual climatological summary; Big Lake 2, Texas.
Pollock, K. H., S. R. Winterstein, C. M. Bunck, and P. D. Curtis. 1989. Survival analysis in telemetry studies: the staggered entry design. Journal of Wildlife Management 53:7-15.
Rautenstrauch, K. R., and P. R. Krausman. 1989. Influence of water avaUabUity on movements of desert mule deer. Journal of Mammalogy 70:197-201.
Relyea, R. A., and S. Demarais. 1994. Activity of desert mule deer during the breeding season. Journal of Mammalogy 75:940-949.
Relyea, R. A., R. K. Lawrence, and S. Demarais. 2000. Home range of desert mule deer: testing the body-size and habitat-productivity hypotheses. Journal of Wildlife Management 64:146-153.
47
Robinette, W. L., D. A. Jones, G. Rogers, and J. S. GashwUer. 1957. Notes on tooth development and wear for Rocky Mountain mule deer. Journal of Wildlife Management 21:134-153.
Robinson, H. S., R. B. Wielgus, and J. C. GwiUiam. 2001. Cougar predation and population growth of sympatric mule deer and white-tailed deer. Canadian Journal of Zoology 80:556-568
Saether, B. E. 1997. Environmental stochasticity and population dynamics of large herbivores. Trends in Ecology and Evolution 12:143-149.
Severinghaus, C. A. 1949. Tooth development and wear as criteria of age in white-taUed deer. Journal of WUdlife Management 13:195-216.
Smith, W. P. 1987. Dispersion and habitat use by sympatric Columbian white-tailed deer and Columbian black-taUed deer. Journal of Mammalogy 68:337-347.
Unsworth, J. W., D. F. Pac, G. C. White, and R. M. Bartmann. 1999. Mule deer survival in Colorado, Idaho, and Montana. Journal of WUdlife Management 63:315-326.
Wauters, L. A., and A. A. Dhondt. 1985. Population dynamics and social behaviour of red squirrel populations in different habitats. Proceedings of the International Congress of Game Biologists 17:311-318.
White, G. C, and R. A. Garrott. 1990. Analysis of wildlife radio-tracking data. Academic Press, San Diego, California, USA.
Whittaker, D.G. 1995. Patterns of coexistence for sympatric mule and white-tailed deer on Rocky Mountain Arsenal, Colorado. Doctoral Dissertation, University of Wyoming, Laramie, USA.
Whittaker, D.G., and F. G. Lindzey. 2001. Population characteristics of sympatric mule and white-taUed deer on Rocky Mountain Arsenal, Colorado. Journal of WUdlife Management 65:946-952.
Wielgus, R., L. Shipley, W. Myers, C. Robbins. 2000. Effects of cougar predation and nutrition on mule deer population declines in the Intermountain Province of the Columbia Basin. Annual Report to Bonneville Power Administration.
Wiggers, E.P., and S. L. Beasom. 1986. Characterization of sympatric or adjacent habitats of two deer species in west Texas. Journal of Wildlife Management 50:129-134.
48
Wood, A.K., R.J. Mackie, and K. L. Hamlin. 1989. Ecology of sympatric populations of mule deer and white-taUed deer in a prairie environment. Montana Department of Fish, WUdlife, and Parks, WUdlife Division, Helena, USA.
Zar, J. H. 1999. Biostatistical Analysis. 4"* edition. Prentice-HaU, Inc. Upper Saddle River, New Jersey, USA.
49
Table 3.1. Seasonal minimum convex polygon home range sizes (km^) for sympatric adult female mule deer and white-taUed deer in west-cenfral Texas, 2000-2002.
Species
Mule deer
White-tailed deer
Year
2000
2001
2002
Seasonal x
Annual x
2000
2001
2002
Seasonal x
Annual x
Season
Spring
Summer
Spring
Summer
Spring
Summer
Spring
Summer
Spring
Summer
Spring
Summer
Spring
Summer
Spring
Summer
n
13
14
15
15
17
15
17
15
15
14
19
15
14
16
17
16
19
16
x
1.68
1.88
1.26
1.28
1.76
1.30
1.28
1.16
2.30
1.46
1.53
1.45
1.20
2.37
1.12
1.47
0.92
2.25
SE
0.17
0.20
0.21
0.21
0.24
0.16
0.14
0.11
0.19
0.11
0.08
0.20
0.25
0.30
0.21
0.17
0.11
0.21
50
Table 3.2. Seasonal 50% core area sizes (km^) for sympatric adult female mule deer and white-tailed deer in west-central Texas, 2000-2002. Means followed by different letters were different at a = 0.05.
Species Year Season n SE
Mule deer 2000
2001
2002
Seasonal x
Annual x
White-taUed deer 2000
2001
2002
Seasonal x
Annual x
Spring
Summer
Spring
Summer
Spring
Summer
Spring
Summer
Spring
Summer
Spring
Summer
Spring
Summer
Spring
Summer
13
14
15
15
17
15
17
15
15
14
19
15
14
16
17
16
19
16
0.88
0.84
0.80
0.58
0.55
0.42
0.73
0.61
0.51
0.86
0.42
0.77
0.44
0.72
0.41
0.78a
0.42b
0.42
0.25
0.24
0.17
0.23
0.11
0.03
0.10
0.09
0.08
0.47
0.08
0.16
0.07
0.10
0.09
0.16
0.05
0.06
51
Table 3.3. Seasonal 95% kernel home range sizes (km^) for sympatric adult female mule deer and white-tailed deer in west-central Texas, 2000-2002. Means followed by different letters were different at a = 0.05.
Species
Mule deer
White-taUed deer
Year
2000
2001
2002
Seasonal x
Annual x
2000
2001
2002
Seasonal x
Annual x
Season
Spring
Summer
Spring
Summer
Spring
Summer
Spring
Summer
Spring
Summer
Spring
Summer
Spring
Summer
Spring
Summer
n
13
14
15
15
17
15
17
15
15
14
19
15
14
16
17
16
19
16
X
3.52
3.37
3.29
2.87
3.38
2.26
3.9
2.82
2.47
3.94
1.89
4.30
2.52
4.67
1.94
4.32a
2.08b
1.77
SE
0.63
0.90
0.60
0.39
0.48
0.23
0.32
0.32
0.29
2.24
0.34
0.88
0.49
0.60
0.40
0.77
0.23
0.26
52
Table 3.4. Within-year seasonal fidelity (mean overlap indices) of 50% core areas and 95% home ranges of sympatric adult female mule deer and white-taUed deer in west-cenfral Texas, 2000-2002.
Home range type
50% core areas
95% home ranges
Year
2000
2001
2002
2000-2002
2000
2001
2002
2000-2002
Mule deer
x
30.80
30.44
19.59
25.99
69.36
70.38
66.06
68.38
SE
9.98
6.51
5.09
3.82
6.34
6.14
4.24
3.15
N
7
14
15
36
7
14
15
36
White-taUed deer
X
15.38
31.61
25.54
25.38
58.76
72.03
69.62
68.02
SE
9.58
7.06
6.38
4.25
6.71
3.37
3.81
2.57
n
9
14
17
40
9
14
17
40
53
Table 3.5. Mean overlap indices of individual spring and summer 50% core areas and 95% home ranges across years for sympatric adult female mule deer and white-tailed deer in west-central Texas, 2000-2002. Means followed by different letters across rows were different at a = 0.05.
Home range Seasonal overlap Mule deer White-taUed deer type
SE n X SE n
Core areas Spring - spring 32.19a 5.51 19 16.60b 5.05 25
Summer - summer 26.81a 4.72 19 9.53b 3.29 25
Home ranges Spring - spring 58.45 6.63 19 42.87 6.81 25
Summer - summer 59.75 7.03 19 41.44 7.06 25
54
Table 3.6. Mean overiap indices of 50% core areas and 95% home ranges with other individuals of either species for sympatric adult female mule deer (M) and white-tailed deer (W) in west-central Texas, 2000-2002. Means followed by different capital letters across rows, and different lower-case letters within columns, were different at a = 0.05.
Home range type
MM WW MW
Season SE n SE n SE n
Core area
2001 Spring
Summer
2002 Spring
Summer
Combined Spring
Summer
Home range
2001 Spring
Summer
2002 Spring
Summer
Combined Spring
Summer
10.52 3.81 19 16.00 5.77 22 5.54ab 1.91 35
6.11 3.40 14 6.22 3.03 26 10.44a 3.52 26
14.89A 5.53 21 14.86A 4.47 30 0.77bB 0.54 31
10.01 4.80 14 15.96 6.43 14 8.82a 3.88 12
12.81A 3.40 40 15.34A 3.52 52 3.30B 1.08 66
8.06 2.9 28 9.63 3.03 40 9.93 2.68 38
36.33 5.21 19 34.76 7.03 22 30.96 4.01 35
34.70 8.37 14 28.73 5.36 26 33.51 5.73 26
34.04 4.75 21 38.52 5.11 30 27.51 3.61 31
34.35 6.36 14 45.24 5.94 14 36.08 7.74 12
35.12 3.47 40 36.93 4.15 52 29.34 2.71 66
34.52 5.16 28 34.51 4.20 40 34.32 4.56 38
55
~4 1
^O
\
• ^ ^
^«
^O
X \
\ %
U
• ^
' ^
\ <5>
«J?
\
='<?
*»
> .
tr
—I ^ 1 \ \ 1 1 1 r
o o e o o o o o o %
O
II
c 0 )
T3 C
u CJ
-a -o <)> n)
^—» OJ
Si ^ a 03
s <1l
d du
l
CT?
O Ui
• 4 — >
CO U.
a IZl
for
<u > l - l
p o ^ Si
> > ) - i
3 CO
1-H
m OJ
5 UH
m o o (N >-. t - i 03 3
OS
^ H C* J3 MO 3 O ,^ o o o (N
>-, kH (B 3 C 03
1—i
^ H C )
(/3 03 X ii
H "3 c 0 ) CJ
leAiAjn^
56
CHAPTER IV
HABITAT SELECTION BY SYMPATRIC DEER IN WEST-CENTRAL TEXAS
Abstract
White-tailed deer (Odocoileus virginianus) and mule deer (O. hemionus) occur
sympatrically across much of the cenfral and western United States, including portions of
west Texas. Fluctuations in populations of both species and the potential for interspecific
competition have fostered a need for information that would aid in management of
sympatric populations. We evaluated the role of vegetation community structure and
topography on the habitat use of sympatric deer in west-central Texas using deer
locations obtained via radiotelemetry and a geographic information system (GIS). Both
species used habitat in a non-random fashion and exhibited species- and sex-specific
preferences. Mule deer selected habitats with less vegetation cover and more topographic
diversity, whereas white-tailed deer avoided vegetation associations at higher elevations.
Males of both species avoided areas with greatest vegetation cover including those areas
containing permanent water sources, but females used such areas, particularly during
summer fawning. Differences observed on the smaller core area (50% kernel home
range) scale were not always detected at the larger home range level, indicating that
decisions about habitat use were made at different spatial scales. Given the differential
importance of various vegetation associations to the establishment of core areas of each
sex and species, maintenance of a mosaic of vegetation, particularly in lower elevation
areas and in proximity to food and water sources is necessary if managers wish to
57
perpetuate coexistence of both species. Habitat conditions of overiap areas should be
targeted for determination of potential limiting factors for both species as competition is
mostiy likely to occur in these areas.
Introduction
White-taUed deer and mule deer occur sympatrically across much of the central
and western United States. In west Texas, the ranges of desert mule deer and white-tailed
deer overiap in portions of the Trans-Pecos region, along the western edge of the
Edwards Plateau, and in the Panhandle (Smith 1987). In some of these areas, white-
tailed deer have become more abundant in areas traditionally considered desert mule deer
habitat (Harwell and Gore 1981), possibly due to changes in vegetation resulting from
livestock production (Baker 1984). Simultaneously, mule deer have decreased or
disappeared entirely from some areas experiencing white-tailed deer expansion (Wiggers
and Beasom 1986). Conversely, in southeastern Arizona, environmental changes caused
by livestock have created conditions that favor mule deer expansion into areas once
inhabited only by white-taUed deer (Anthony and Smith 1977). Potential resource
competition has been reported for other sympatric herds (Martinka 1968, Anthony and
Smith 1977, Krausman 1978, Wood et al. 1989).
The habitat requirements of both species have received relatively littie study in
sympatric areas of west Texas. White-taUed deer preferred areas with greater woody
cover in areas of the Trans Pecos having high densities (>20 deer/km^) of both species
(Wiggers and Beasom 1986). However, no differences in vegetation parameters were
58
detected between locations of each species in areas of low deer density (<20 deer/km^).
In south Texas, heavily used portions of the home ranges of allopafric adult male white-
tailed deer had greater woody canopy cover and horizontal screening cover than unused
portions (Pollock et al. 1994). Also in south Texas, white-taUed deer densities averaged
<3.5 deer/km^ when total brush cover was <43%, whereas highest densities (18.5
deer/km^) occurred when brush cover exceeded >60% (Steuter and Wright 1980).
Traditional management strategies advocating habitat manipulations for mature males
have recommended creation or maintenance of areas with dense woody canopy cover, a
high number of woody species, and dense horizontal screening cover.
Topography has also been suggested as a landscape feature that causes habitat
partitioning by sympatric deer (Kramer 1973, Krausman 1978, Wiggers and Beasom
1986). Research previously conducted on the western edge of the Edwards Plateau found
bedding sites of the 2 species could be differentiated to some extent by 3 parameters
(slope, amount of forbs, and amount of grass) but significant unexplained variation
remained (Avey et al., 2003). In southeastern Arizona, Coues' white-tailed deer (O. v.
couesi) were found primarily at higher elevations with more mesic vegetation and desert
mule deer in lower-elevational xeric habitats (Anthony and Smith, 1977). The same
pattern was true of Carmen Mountains white-tailed deer (O. v. carminis) in Big Bend
National Park, Texas (Krausman and Abies 1981). The relative distribution of desert
mule deer and white-tailed deer in the southwest suggested mule deer were better adapted
to arid conditions than were white-taUed deer (Brown 1984). White-taUed deer tended to
be associated with more mesic habitats where the species co-occur (Anthony and Smith
59
1977, Krausman and Abies 1981). Although water availability can be a primary factor in
determining deer disfribution and habitat use in arid regions, in areas where water
disfribution was adequate and constant, deer distributions were more likely determined by
other factors (Boroski and Mossman 1996). Studies in such areas are especiaUy valuable
for enhancing our understanding of factors influencing habitat selection by deer (Bello et
al. 2001).
In theory, the presence of a competitor should refine habitat use in both
competitors if long-term coexistence is to occur (Rosenzweig 1991). In 1998, Texas
Parks and Wildlife Department (TPWD) biologists initiated a pilot study to investigate
differences in habitat use by mule deer and white-tailed deer in Crockett County, Texas.
Slope, amount of forbs, and amount of grass explained only a small portion of the
differences in microhabitat use by deer (Avey 2001), indicating a need for further
research. Our study was designed to explore further the differences in habitat use by mule
and white-tailed deer at different scales. Specifically, we evaluated the combined role of
vegetation community structure and topography in habitat use by each species. We
predicted that the physical structure of the terrain would be less important than vegetation
associations in the distribution of each species on the study area because topographic
differences were not as pronounced as those in previous studies in other regions. In arid
regions, white-tailed deer were tied to mesic habitats, whereas mule deer were less
dependent upon the heavy cover of lowlands and draws. In areas of sympatry, white-
tailed deer tended to be associated with areas of greater woody shrub cover, regardless of
terrain, than mule deer (Geist 1998).
60
Study area
Our study area consisted of 5 contiguous ranches totaling approxmiately 323 km^
in the northwestern corner of Crockett County, Texas, on the western edge of the
Edwards Plateau where it begins fransition to the topography and desert vegetation of the
Trans-Pecos region. Human activities and land uses on the study area included various
levels of livestock grazing, oil production, and hunting during the past 5 years. Because
all ranches were managed for livestock and/or hunting leases, water was available from
windmills in all pastures year-round. Long-term predator eradication programs have
extirpated large predators such as coyote (Canis latrans), black bear (Ursus americanus),
wolves (C. lupus) and mountain lions (Puma concolor) from the study (Cook, 1984). .
Population densities of bobcats (Felis rufus) present during the study period were
unknown, but 54 bobcats were removed from a portion of the study area (165.9 km^)
during December through February of 2001 (L. Clark, ranch foreman, personal
communication).
Lower elevations were dominated by mesquite trees (Prosopis sp.), shrubs < 2 m
in height such as catclaw acacia (Acacia greggi), creosote bush (Larrea tridentata), and
tarbush (Flourensis cernua), prickly pear cactuses (Opuntia sp.) and tree cholla (O.
embricata). Juniper (Juniperus sp.) was the dominant tree species on slopes and mesa
tops. Draws supported a dense grassy understory and thickets of hackberry (Celtis
occidentalis) and little walnut trees (Juglans microcarpa). Xeric mesa slopes supported
small woody shrubs, yuccas (Yucca sp.) and ocotillo (Fouquieria splendens) (Correll and
Johnston 1970).
61
Topography consisted of broad, level plateaus, roUing hiUs, and steep canyons.
Elevation ranged from 700 m to 900 m. Mean annual precipitation for 2000 through
2002 was 25 cm; the average for 1963 through 1997 was 43 cm. Most rainfall occurred
from May to September, with highest amounts usually occurring in September. The
average annual low temperature was 10°C; the average annual high was 26''C. In winter
temperatures ranged from a minimum daily low of-l°C to a maximum daily high of
16°C, and in summer ranged from 16 to 32°C (National Oceanic and Atmospheric
Adminisfration 2000, 2001, 2002).
Methods
We conducted a helicopter survey in February 2001 to estimate deer density and
herd composition. The pilot and one observer flew adjacent belt transects approximately
200 m wide at an altitude of approximately 30 m. The pilot used a Garmin Geographic
Positioning System unit to plot transects and maintain parallel flight lines. Surveys began
at 0800 and ended at 1700; the entire study area was surveyed over 5 days. The pilot and
observer counted deer on both sides of the helicopter and used group composition, antler
characteristics, and location to decide whether deer had been counted previously
(DeYoung 1985). Observers recorded species, sex, and age class (juvenUe or adult) for
each deer counted. For each ranch, we calculated the number of deer per unit area and
ratio of males to females and juveniles to adult females.
Personnel from Holt Helicopters (Uvalde, Texas) captured deer with a net gun
fired from a helicopter (Krausman et al., 1985) on 2-3 February 2000 and 30 January
2001. We recorded sex and condition of each collared animal and estimated the age of
62
deer by tooth-wear and replacement (Severinghaus 1949, Robinette et al. 1957). We
fitted each deer with a numbered plastic eartag and a 500 g radiocollar equipped with a
mortality sensor (Telonics, Mesa, Arizona).
We conducted radio-fracking with a truck-mounted null-peak system consisting of
2 4-element Yagi antennas mounted on a rotating, telescoping boom in the truck-bed. To
estimate telemefry system error, we followed methods outlined in White and Garrott
(1990). All personnel were required to triangulate radio-collars hung on poles or trees 1
m above ground at random locations in the general vicinity of collared deer home ranges.
Bearings were obtained for 8-10 collars placed in different locations once per month,
using the same methodology used to triangulate study animals. Triangulated bearings
were compared to actual bearings calculated using the exact location of telemetry stations
and collars as determined with a Garmon^M Global Positioning System (GPS). We used
the software program LOAS (Ecological Software Solutions, Sacramento, California) to
calculate deer locations. Average bearing error was ±7° based on triangulated locations
of collars in known locations. We located collared deer >4 times per month during
January through August 2000 to 2002 to estimate home ranges. Deer were not located
during hunting season (September through mid-January) in compliance with landowners'
wishes, although we did check for mortalities monthly. We rotated the timing of
relocations sequentiaUy through 3 time blocks (0500-1059,1100-1659,1700-2400). We
used the Animal Movement extension for ArcView (Hooge and Eichenlaub 2000) to
calculate 95% and 50% fixed kernel home ranges. We designated 50% kernel home
ranges as each animal's core area (Loveridge and Macdonald 2003). Home ranges of
63
female deer were calculated for winter-spring which encompassed the pregnancy period
(January -April) and summer, which included fawning periods of both species (May -
August). We calculated only annual home ranges for male deer because of sample size
limitations.
Habitat classification
We developed a geographic infonnation system (GIS) of the study area using
United States Geological Survey Digital Orthophoto Quadrangles (1-m resolution)
obtained from Texas Natural Resources Information Service. We created a coverage
depicting vegetation associations by manually delineating area boundaries visible on
aerial photographs in ERDAS (Leica Geosystems GIS & Mapping, LLC, Atlanta,
Georgia). We assigned each vegetation association polygon to 1 of 11 classes and 1 of 3
general elevation classes (Table 4.1). We used ground surveys to ensure that boundaries
determined from examination of digitized aerial photographs were correctly delineated
and that each polygon was assigned to the correct vegetation class. We then used home
range polygons to clip the vegetation coverage using ARC/INFO (Environmental
Systems Research Institute, Redlands, California), to produce the coverages used to
calculate the proportional area of different vegetation classes present in each home range
or core area.
64
Data analvsis
We used multivariate analysis of variance (MANOVA) to test for differences and
interactions in habitat composition of home ranges and core areas among years, seasons,
and species for each sex. We then used compositional analysis (Aebischer et al. 1993) to
further investigate in which classes habitat use differed for males and females within
years. Direct comparisons between males and females were not reliable due to large
differences in sample sizes.
For both sexes, we first compared home-range composition to the composition of
the study area. The study area was defined as a minimum convex polygon of all animal
locations for all years, as areas not used by any study animal were not considered
"available." We then compared core area composition to home-range composition.
These 2 spatial scales (home range and core area) were used to reflect Johnson's (1980)
second and third order selection, respectively.
Results
Estimated deer densities during the study were 2.4 mule deer/km^ and 1.6 white-
tailed deer/km^. The number of females per male in 1999, prior to study initiation, was
1:3 for mule deer and 1:7 for white-taUed deer; the ratio in 2001 was 1:3 for both species.
The number of fawns per female in 1999 was 0.5:1 for mule deer and 0.4:1 for white-
tailed deer; in 2001 the ratio was 0.2:1 for both species.
65
Females
We captured and fitted 40 adult (> 1 year) females of each species with
radiocoUars in January 2000. In January 2001, we captured and collared an additional 13
white-tailed deer and 10 mule deer. Mean age at capture was 4.5 years for both species
(mule deer range = 2.5 to 6.5; white-tailed deer range = 1.5 to 7.5). Seasonal home
ranges and core areas were calculated each year for individuals having >30 locations in
that season.
The 95% kernel home ranges of female deer were different in composition among
years and between species, but we detected no differences among seasons and no
interactions (Table 4.2). For both species during each year, the composition of home
ranges was different from the overall composition of the study area (Table 4.3). Core
area (50% kernel home range) composition differed among years, seasons, and between
the species (Table 4.4) and differed from the overall composition of the study area (Table
4.5), but core areas were not different from the overall composition of the 95% home
ranges within either species (A = 0.95, F = 1.60, df = 11, F = 0.10).
Classes located in lower elevation were ranked higher for white-tailed deer home
ranges compared to female mule deer. The Mill class was ranked highest for all female
home ranges, presumably because all permanent water sources (natural and artificial)
were located within patches assigned to the Mill class as these areas contained large trees
such as mature hackberry and thicker ground cover relative to the overall study area.
White-tailed deer females apparently favored lower elevation classes and those
dominated by mesquite, while juniper -dominated and higher elevation classes were
66
ranked lowest. Conversely, Mesa tops and juniper-dominated areas ranked high for mule
deer, but Draw areas ranked low, indicating possible avoidance by mule deer females.
Core area class rankings were similar to home range for both species. Mesquite-
dominated classes and Draw ranked low for mule deer. High elevation classes (Steep and
Mesa) and juniper-dominated classes ranked low for white-tailed deer.
Males
We captured and fitted 10 males of each species with radiocoUars in January
2000. In January 2001, we captured and collared an additional 8 males of each species.
Mean age at capture of mule deer was 3.5 years (range = 3.5 to 4.5) and that of white-
tailed deer was 4.5 years (range = 3.5 to 6.5). Home ranges and core areas were
calculated for 7 deer of each species for 2001 and 2002, using a minimum of 30 locations
(Millspaugh and Marzluff 2001). We did not have any deer with >30 locations during
2000 to calculate home range.
The classes Dense and Mill did not appear in the core areas of male deer. In
addition. Steep and Mill ranked last and next-to-last for both species' home ranges, and
Steep was a component of only one individual's home range for each species. Therefore,
for males, polygons categorized in these 3 classes were reclassified into the surrounding
polygon(s) for analyses.
We detected no differences or interactions in composition of home ranges or core
areas between years for males of either species (Table 4.6), so we pooled data across
years within species for compositional analysis. There was a species effect on
composition of deer home ranges, but core areas within these were not different.
67
Composition of mule deer core areas was different from that of their home ranges (X =
0.01, F = 30.57, df = 7, F = 0.009); however, the core areas of white-tailed deer did not
differ from home ranges (A = 0.12, F = 3.24, df = 7, F = 0.18). Core areas of both
species and home ranges of white-tailed deer differed from overall study area
composition but composition of mule deer home ranges was not different from available
in the study area (Table 4.7). Adult male mule deer selected areas in Mesa and juniper-
mix (JNmx) while white-tailed deer males selected juniper-tarbush (JNTB) and Draw
areas. However, class ranking patterns for core areas were different from those of the
home ranges (Table 4.7). Mesa ranked first for mule deer home ranges, was third for
core area, but was last for white-tailed deer core area. Similariy, Draw ranked first for
white-tailed deer home range, third for white-tailed deer core area, but was last for mule
deer core area.
Discussion
Local elevation and topography have been cited as factors affecting differences in
the distributions of sympatric deer (Kramer 1973, Krausman 1978, Swenson et al. 1983,
Wiggers and Beasom 1986). Our vegetation classes inherentiy included differences in
elevation as each vegetation class occurred within only 1 of 3 distinct elevation classes.
For example, the Mesa top vegetation class was a distinct association dominated by
scattered juniper bushes and grasses. Most classes were very uniform in terms of terrain
ruggedness with 2 exceptions; steep mesa sides and draws tended to include rougher
patches of terrain created by rimrock formations and erosion, respectively. Earlier
68
research conducted on our study site suggested that vegetation structure impacted
selection by deer to a greater extent than did differences in elevation (Avey et al. 2003).
However, mule deer showed a distinct preference for mesa areas which white-tailed deer
appeared to avoid. The difference in our results versus those of Avey et al. (2003) may
be the result of the scale at which selection was examined in each study. Avey et al.
(2003) investigated habitat use at the individual deer location level; however, others have
suggested that mule deer make selection decisions based on factors detected at a scale
larger than their home ranges (Kie et al. 2002). We delineated our vegetation classes at a
greater resolution in order to examine habitat use pattems on both a home range level
scale and on a core area scale. The lack of home range and core areas including Dense
and Mill classes indicated that male deer did not choose to spend much time in densely
vegetated areas or in areas in proximity to water sources. Male mule deer used steeper
and higher elevation areas than did white-tailed deer, which may be attributable to
differences in predator-escape mechanisms between the species (Geist 1998, Lingle and
Wilson 2001).
Management implications
Whittaker (1995), Avey et al. (2003), and this study examined spatial scales
ranging from individual animal locations up to the landscape level and to some extent the
seasonal temporal scale. Although interspecific differences in habitat use were detected,
considerable overlap did occur. This overlap, combined with anecdotal evidence from
previous studies (Kramer 1973) that suggested the 2 species avoid being in exactiy the
69
same place at the same time, indicated partitioning may occur on 2 separate scales.
Specifically, these would be either 1) a very fine temporal-spatial scale such as when an
individual animal encounters an individual of the other species at a resource such as a
water trough or feeder or 2) an intermediate scale such as that quantified by our core area
measurements. Management actions such as providing abundant food and water sources
across a variety of terrain and vegetation associations should minimize any potential
impacts of increased interactions at the 1 ' scale that might result from increased survival
or other population increases. Given the importance of open and well concealed areas to
the establishment of core areas of mule deer and white-taUed deer, respectively,
maintenance of a mosaic of open and dense cover, particularly in close proximity to food
and water sources, is necessary if managers wish to perpetuate coexistence of both
species.
70
Literature cited
Aebisher, N. J., P. A. Robertson, and R. E. Kenward. 1993. Compositional analysis of habitat use from animal radio-tracking data. Ecology 74:1313-1325.
Anthony, R. G., and N. S. Smith. 1977. Ecological relationships between mule deer and white-taUed deer in southeastern Arizona. Ecological Monographs 47:255-277.
Avey, J. T. 2001. Habitat relationships between sympatric mule and white-tailed deer in south-cenfral Texas. Thesis, Texas Tech University, Lubbock, Texas, USA.
Avey, J. T., W. B. BaUard, M. C. Wallace, M. H. Humphrey, P. R. Krausman, F. Harwell, and E. B. Fish. 2003. Habitat relationships between a sympafric mule and white-tailed deer Texas. The Southwestern Naturalist 48:644-653.
Baker, R. H. 1984. Origin, classification and distribution. Pages 1-18 in L. K. Halls, editor. White-tailed deer: ecology and management. Stackpole Books, Harrisburg, Pennsylvania, USA.
Bello, J., S. Gallina, and M. Equihua. 2001. Characterization and habitat preferences by white-taUed deer in Mexico. Journal of Range Management 54:537-545.
Boroski, B. B., and A. R. Mossman. 1996. Distribution of mule deer in relation to water sources in northern California. Journal of WUdlife Management 60:770-776.
Brown, D. E. 1984. The effects of drought on white-tailed deer recruitment in the arid southwest. Pages 7-12 in P. R. Krausman and N. S. Smith, editors. Deer in the southwest: a workshop. School of Renewable Natural Resources, University of Arizona, Tucson, USA.
Correll, D. S., and M. C. Johnston. 1970. Manual of the vascular plants of Texas. Texas Research Foundation, Renner, Texas, USA.
DeYoung, C. A. 1985. Accuracy of helicopter surveys of deer in south Texas. Wildlife Society Bulletin 13:146-149.
Geist, V. 1998. Deer of the world: their evolution, behavior, and ecology. Stackpole Books, Mechanicsburg, Pennsylvania, USA.
Harwell, W. F., and H. G. Gore. 1981. White-tailed deer population trends. Job Performance Report. Federal Aid Project Number W-109-R-4. Job Number 1. Texas Parks and Wildlife Department, Austin, Texas, USA.
71
Hooge P. N., and B. Eichenlaub. 2000. Animal movement extension to ArcView. Ver. 2.0. Alaska Science Center - Biological Science Office, U.S. Geological Survey, Anchorage, Alaska, USA.
Johnson, D. H. 1980. The comparison of usage and avaUability measurements for evaluating resource preference. Ecology 61:65-71.
Kie, J. G., R. T. Bowyer, M. C. Nicholson, B. B. Boroski, and E. R. Loft. 2002. Landscape heterogeneity at differing scales: effects on spatial distribution of mule deer. Ecology 83:530-544.
Kramer, A. 1973. Interspecific behavior and dispersion of two sympatric deer species. Journal of WUdlife Management. 37:288-300.
Krausman, P. R. 1978. Forage relationships between two deer species in Big Bend National Park, Texas. Journal of Wildlife Management 42:101-107.
Krausman, P. R., and E. D. Abies. 1981. Ecology of the Carmen Mountains white-taUed deer. Scientific Monograph Series No. 15. U.S. Department of Interior, National Park Service, Washington, D.C.
Krausman, P. R., J. J. Hervert, and L. L. Ordway. 1985. Capturing deer and mountain sheep with a net-gun. WUdlife Society BuUetin 13:71-73.
Lingle, S., and W. F. Wilson. 2001. Detection and avoidance of predators in white-tailed deer (Odocoileus virginianus) and mule deer (O. hemionus). Ethology 107:125-147.
Loveridge, A. J., and D. W. Macdonald. 2003. Niche separation in sympatric jackals (Canis mesomelas and Canis adustus). Journal of Zoology 259:143-153.
Martinka, C. J. 1968. Habitat relationships of white-tailed and mule deer in northern Montana. Journal of WUdlife Management 32:558-565.
Millspaugh, J. J., and J. M. Marzluff. 2001. Radio tracking and animal populations. Academic Press, San Diego, California, USA.
National Oceanic and Atmospheric Administration. 2000. Annual climatological summary; Big Lake 2, Texas, USA.
National Oceanic and Atmospheric Administration.. 2001. Annual climatological summary; Big Lake 2, Texas, USA.
72
National Oceanic and Atmospheric Administration.. 2002. Annual climatological summary; Big Lake 2, Texas, USA.
PoUock, M. T., D. G. Whittaker, S. Demarais, and R. E. Zaiglin. 1994. Vegetation characteristics influencing site selection by male white-tailed deer in Texas. Journal of Range Management 47:235-239.
Robinette, W. L., D. A. Jones, G. Rogers, and J. S. Gashwiler. 1957. Notes on tooth development and wear for Rocky Mountain mule deer. Journal of Wildlife Management 21:134-153.
Rosenzweig, M. L. 1991. Habitat selection and population interactions: the search for mechanism. American Naturalist 137:S5-S28.
Severinghaus, C. A. 1949. Tooth development and wear as criteria of age in white-tailed deer. Journal of WUdlife Management 13:195-216.
Smith, W. P. 1987. Dispersion and habitat use by sympatric Columbian white-tailed deer and Columbian black-tailed deer. Journal of Mammalogy 68:337-347.
Steuter, A. A., and J. A. Wright. 1980. White-tailed deer densities and brush cover on the Rio Grande Plain. Journal of Range Management 33:328-331.
Swenson, J. E., S. J. Knapp, and H. J. Wentiand. 1983. Winter distribution and habitat use by mule deer and white-tailed deer in southeastern Montana. Prairie Naturalist 15:97-112.
Whittaker, D. G. 1995. Patterns of coexistence for sympatric mule and white-tailed deer on Rocky Mountain Arsenal, Colorado. Doctoral Dissertation, University of Wyoming, Laramie, USA.
Whittaker, D. G., and F. G. Lindzey. In press. Habitat use of sympatric deer species on Rocky Mountain Arsenal, Colorado. Wildlife Society Bulletin.
Wiggers, E.P., and S. L. Beasom. 1986. Characterization of sympatric or adjacent habitats of two deer species in west Texas. Journal of WUdlife Management 50:129-134.
Wood, A.K., R.J. Mackie, and K. L. Hamlin. 1989. Ecology of sympatric populations of mule deer and white-tailed deer in a prairie environment. Montana Department of Fish, Wildlife, and Parks, Wildlife Division, Helena, USA.
73
Table 4,1, Percentage of study area covered by each of 11 delineated vegetation classes with corresponding elevation classes (high >870 m, middle 840 -870 m, low < 840 m) and descriptions of the vegetation species and type most prevalent in that class for 5 ranches in west-central Texas, 2000-2002,
Class Elevation % of class^ study
area
MQmx (mesquite-mixed shrubs)
Description
JNmx middle 0,21 Brushland of juniper trees (Juniperus sp,) and (Juniper-mixed mixed shrubs <2 m in height associated with mesa shrubs) slopes and hills
low 0,19 Brushland of mesquite trees {Prosopis sp.) and mixed shrubs <2 m
TBMQ (tarbush-mequite)
middle 0,17 Tarbush {Flourensis cernua) shrubs and mesquite trees <2 m
JNTB low (juniper-tarbush)
Mesa high (mesa tops)
JNMQ low (juniper-mesquite)
Draw low (draws/washes)
CRmx low (creosote- mixed shrubs) Steep high (steep mesa slopes)
Mill low (thickets associated with windmills)
0,12 Juniper trees and tarbush shrubs
0,07 Flat mesa tops, juniper brushland with grasses and shrubs
0,07 Brushland of juniper and mesquite trees
0,07 Dry creekbeds and floodplains with dense grasses and shrubs
0,05 Shrubland of creosote bush {Larrea tridentata) and tarbush
0.02 Steep rocky mesa sides and rimrock areas
<0,01 Thickets around windmills or temporary pools not in draws
" Areas <2400 m above mean sea level were classified as "low", 2400m - 2800m as "middle", and >2800 m as "high".
74
Table 4.2. Multiple analysis of variance results for contrasts of 95% home range habitat compositions of radiomarked sympatric adult female mule deer and white-tailed deer in west-cenfral Texas during spring and summer of 2000-2002.
Contrasts
Year
Season
Year * season
Species
Year * species
Season * species
Year * season * species
Wilks' A
0.7348
0.9006
0.9333
0.4963
0.8336
0.9581
0.9343
F
2.45
1.63
0.52
14.94
1.40
0.64
0.51
df
22
11
22
11
22
11
22
P
0.0004
0.0959
0.9667
<0.0001
0.1094
0.7901
0.9696
75
3
in -J
• a
c rt ^
> > i
X)
v: CO
O C
•a •3 0 ) Uf l
O u V I k-o
-a o c
_-; lU
- • ^
Q
CQ
Z X
s OS u o z •—1
X 6 O o oa
X E U & Q O
Z
CQ H Z i—»
O
E Z X E
OS U
D .
X E a: U
o
o o CQ
E OS U
o
E Z
oa
u
Q .
D. 1A rj
"a '.J
CO
u r i ^ ^ (N
1
M O
E ,;— tn SO
kin
c ca ;-1> CJ
c o
O O CNI
"3 ^ '.J
E E 3
^ c ca M
CQ
z o CQ
O
c/5 X E Z
r-o o o
Q O
CQ H X E O
o o
o
CQ
z
X E Z
o o o
ON
ri
E O
O
03
d
5 "O o o o
O C3
1) a, 1/5
ca
3
> o
-a
T3 T3
IE
• a
• * » > - -u — ca ^
f 2 | ^
ca o o o CN
c
76
o U
Xi ca
U
<
%
a, VL
>
X E
OS U
ca
O
O
CQ
O
z
oa z X E Z
O o o
O
CQ H Z
E Z
OS U X E O
ca
Q
O
CQ
o o
tn
o
0) •a
CM O o CN
• o c ca
(3
r«u,
«u o
.!o
en5
* o k^ .c
bus
k. ra " C/} . f —
BM
Q
H bs
,
3 JZ tf)
• o
mix
-o c ca
sp.)
to
'1 >!
{Pro
<U
'3 a" <D
E cn
• - ^
X
MQ
m
hrub
s,
t/L
-a u X
and
mi
d. cn
rus
>jj •S-c 2 ^
unip
e
" — 1
. XU
I
Z "-
^ Q
^ 3
- D U •p;
v5
•J C/5
X
E U Jj
• a u x; ^ o Qj ^ o >.
^ ca
Q CJ
3
a-X CJ
E
c ca ^ o D .
'S 3
o 5 z -» cn^ O . O
ca cn u
E
cs cn OJ
JZ cn 3
X ca
• o c ca
<u .& 'E 3
_cn
oa z •—) o '
*3 cr !/3
E
cd • o OJ CJ
'c3
lyJ^
CJ
^
^ 3 ^
O 'o
^
0)
o
cn
CJ
* - l
i J . • ^
3
cn CJ
E _cn
cn c u
Q = cn"
ca
tj ca
M o o .E
T3 C ca cn u
IH * ca cn U E
. D .
^ xT cn 3
ca
c ca
y ^
a 2
^ 1
cn
ca ;--o c
O c cn
O
>, ca 1 -o
^ O cn
1 •a c
• ^
T3 C 3 O
^ ca
CJ
^CJ
IE
" 'cn c Q U
1 -a c ca
E~ o o
X
d. cn
•b
s f~(^
77
Table 4.4. Multiple analysis of variance results for contrasts of 50% core area habitat compositions of radio-marked sympatric adult female mule deer and white-tailed deer in west-central Texas during spring and summer of 2000-2002.
Contrasts
Year
Season
Year * season
Species
Year * species
Season * species
Year * season * species
Wilks' A
0.7335
0.8722
0.9365
0.4425
0.8288
0.9032
0.9323
F
2.42
2.12
0.48
18.21
1.42
1.55
0.52
df
22
11
22
11
22
11
22
F
0.0005
0.0219
0.9781
<0.0001
0.1006
0.1189
0.9670
78
- CJ
-5 -^ -a >> ca x ) ti
*C la Cl.
E >-, tn
0 c ^ cn OJ
'5 0) 0 . cn
-0
ca u.
yea
>% X )
cn ca u
0
c 0
tat
c to tn OJ
rep
ona
' k-0 0 , 0
!,>
u 0 c qj
;— 0
D . C
u. OJ
C4-(
•3 "0 c
; a
•3 aj
0 u cn i— to
-a c 3 OJ E ca cn
a> .c
to V-ca
x : cn
• 3
cn
cn cn ca
0 CN
0. 0 4 — 1
tn
ca OJ t .
0 CN
0 0
aoo c CN
u
o z
Q CQ
Z X
E O
X
E OS u ft 1>
Vi
O
CQ
c to
Q
X
E Z
o o o CO V
CQ
X
E Z X
E C«5 U
O % Z
n OJ
Q
O
oa
X
E o
CO o o o
X
E OS U
Q
O % Z
o CQ
Q oa H z X E a
X
E Z
o o o cz> V
E 05 U
D oa
Z
E Z
E O
o
oa
o o
(50 C
nki
ca u. OJ
enc
,0J
^ 0 . - a c ca c
^ 0
*cn 0
& E 0 CJ ca OJ w. ca u k-0
0
4.5,
_u
3 ea
E 3 cn
•a c ca
^ a. cn ao
^c ' w 3
T3 cn ca X OJ
H ca
'c to CJ
cn <u
^ c
• ^
OJ i/^ fO 0
• ° CO
"S ^ E S
H <a "c5
u
o >-
CN
O
o C3
o o o CN
CO CN CO I3N
O
o
OJ
-o
CN CO CO 0 0
o o CO
3
s o o (N
ro CN
O CN O
OJ OJ
T3 -O
x:
79
u
o U
OJ ft VI
X E oi U
o CQ H O
X
E O
cn oa H
z
OJ
X
E z
o o o CO V
CN 0 0
CO
CO
CN CN o o o
oa
X
E Z *—, o z 1—1
X E
OS u X E O
Q
ca t -
Q O
s CQ
o o o CO
V
0 0
ON
o o CO
OJ CD
(N O o CN
C3 1) u.
-a i.. a c < -a ca Q OJ
2 - ^ "ca
g « S ^ X vT ^ OJ t ;
• 2 o - ^ Co 55 CJ j j OJ • £
! ^ S " '^ , 2 cn : ~
h(f
m
xi
rbus
, C
R
ccid
ca cn o * " - a CO cn OJ --.i
• - o - i i
BM
Q
cree
k y{
Ce
H >. fc „ 1- D cn "O JD
X3 cn , ^ 3 - S CJ * - ^ ca
w ca „ - a ^ « OJ W flj
mix
ji
te,
hick
"2 a- tt C cn OJ ca OJ , ' t i
^^ g 3
.2 =« E § - s , -CO ft -
Pro
ju
ni
nse'
" ^ cn «
a - Q •3 0 = cr 5 cn
cn ^ ca OJ Z OJ
2 ^„ « cn cn^ >^
• " • D H o X o o
di.i ^ . , c
hrub
s is
fla
t d
esai
=" ca ' S
• s . s S
and
mix
rb
ush,
M
stee
p m
e:
-—~ ca
ft- .S2
^ 5 OJ 3 =^ i j V t . * j ^ OJ 1/3
. R . ft „
S 'S -s 3 = 3
^ ^ cn " t : 1- - ^ ca
unip
e N
TB
an
d t
• ;—, - . -. ,22 oj" S
•• JN
mx
mes
quit
tr
iden
t a
tn
ca •a
c
o c cn
"o o ft > 1 k . ca
mpo
r
OJ
^ o
mil
ls
• o c '?• •a c 3 O
)-ca
icke
ts
j :
tso
ft
_cn 'tn C O
'Mil
l" c
•a
tom
, an
o X
p,)
rive
r
cn
.y
dman
i~^
80
" c: ^
tat
c OJ
ca ft E o CJ . ^ J
o
o
•A n
ca CJ
sb E 1—
— cn
c
nki
ca ;_ -o
enc
.'O
to
;_ ft
• a
c ca c
." tn
ft E c CJ
^ S r )
O
OJ
E E 3 tn
• o c ca
ing
ft cn
bO C
^ 3 • a
tn ca X OJ
H 'rt k-
"c OJ
S?5 r^. i V ,
rt u
• " "
o •D
-a a> c E k-
E •-
- o ca
ca .;:i C L
^ - E OJ g_ ca C ft in
^ .O S 2i In '"3 OJ • - C
M H • -r— ^ ^
« P- — OJ ^ 3 E 5 ^ o " ^
OJ CJ • ; ^ OJ
OS
ft c/5
CQ f-Z
X
E O S ca
Q X
E OS U O S oa H O
z "- X
UI
Z
n3 cn
^
s
XU
Ii
O
s X
E OS u
X
E z o s CQ E-ffl
JNT
1 * ^
z
Q
E o5 U X
E O 2 O
s Z
BM
Q J
H XJ
CJ
S oa z X
E
E Z - X
UI
O
s X
E o: u
JNM
Q
^ ca
a o S oa 20 i~
00 r i CJN —
r ) o o q d CO
T3
— •
v:
CO
z o
3 !D-
E
• o c
esa
T3 y^
i/.
O c ! / • .
o
CL.
« "? £
-)C
^ ^ ^ JC
3 J 2
17! t«
CL
0) C/)
3 ^ «
T3
C
2 2
lis
'E •a c
i • o c 3 o C3
o
_ .y IH
"o
O ' •--^ X -J
u
^ JC ^
' O -^ i ^ " t Z S .§--'.5 ^ w '_>
82
Top Related