Murdoch Dissertation (c)2007

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A FUNCTIONAL GROUP APPROACH FOR PREDICTING THE COMPOSITION OF HARD CORAL ASSEMBLAGES IN FLORIDA AND BERMUDA A Dissertation Submitted to the Graduate Faculty of the University of South Alabama in partial fulfillment of the requirements for the degree of Doctor of Philosophy in The Department of Marine Science by Thaddeus J. T. Murdoch i

description

A FUNCTIONAL GROUP APPROACH FOR PREDICTING THE COMPOSITION OF HARD CORAL ASSEMBLAGES IN FLORIDA AND BERMUDAA Dissertation Submitted to the Graduate Faculty of the University of South Alabama in partial fulfillment of the requirements for the degree of Doctor of Philosophy in The Department of Marine Science byThaddeus J. T. MurdochB.Sc., Dalhousie University, 1988B.A. Honours, Dalhousie University, 1991M.S., University of South Alabama, 1998Copyright c 2007 Thaddeus J. T. MurdochAll rights reserved

Transcript of Murdoch Dissertation (c)2007

Page 1: Murdoch Dissertation (c)2007

A FUNCTIONAL GROUP APPROACH FORPREDICTING THE COMPOSITION OF

HARD CORAL ASSEMBLAGESIN FLORIDA AND BERMUDA

A Dissertation

Submitted to the Graduate Faculty of theUniversity of South Alabama

in partial fulfillment of therequirements for the degree of

Doctor of Philosophy

in

The Department of Marine Science

byThaddeus J. T. Murdoch

B.Sc., Dalhousie University, 1988B.A. Honours, Dalhousie University, 1991M.S., University of South Alabama, 1998

Copyright c 2007 Thaddeus J. T. MurdochAll rights reserved

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ACKNOWLEDGEMENTS

The Keyswide Coral Reef Expedition was funded by NOAA’s National Undersea

Research Center at the University of North Carolina, Wilmington; NOAA’s Sanctuaries

and Reserves Division; The U.S. National Park Service, Biscayne National Park; The

Munson Foundation; The Florida Institute of Oceanography; and the Harbour Branch

Oceanographic Institution. The Expedition was carried out under permits from the

Florida Keys National Marine Sanctuary, the U.S. National Park Service, and the State of

Florida.

The Bermuda Project was supported by a fellowship from the University of South

Alabama; a PADI Aware grant; and a Bermuda Programme award from the Bermuda

Institute of Ocean Sciences. Additional support was provided by the Bermuda

Biodiversity Project, Bermuda Zoological Society, the Ernest E. Stempel Foundation, and

the Department of Conservation Services, Bermuda Government.

The research in this dissertation could not have been done without the help of many

people. I am grateful to John Ogden and Steven Miller for organizing the Keyswide Coral

Reef Expedition, and to Ken Johns and Otto Rutten for running the program of

continuous nitrox diving during the cruises. They, Dennis Hanisak and Laura Seimon

participated in the field work that formed the basis of the Florida section of this

dissertation. Dione Swanson provided valuable assistance in both the field and

laboratory. I am grateful to my committee members, and the professors and students of

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the Dauphin Island Sea Lab and the Bermuda Institute of Ocean Sciences for their

assistance, interest and support of this project.

Field work in Bermuda would not have been possible without the lively assistance of

the members of Robbie Smith’s Benthic Ecology Research Lab during 2000 – 2003 and

the BREAM team at BZS from 2004 – 2006. I am also thankful to Annie Glasspool and

Jack Ward for supporting me while I wrote up the dissertation. Jon Martin, Julie Prerost,

Toby Bolton, Jeannette Loram, Alexander Venn , Philippe Rouja, Mike Colella, Gerardo

Toro Farmer, and Matt Ajemian provided invaluable scientific and moral support. I am

deeply indebted to my family for unwavering encouragement.

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TABLE OF CONTENTS

LIST OF TABLES..............................................................................................................ix

LIST OF FIGURES...........................................................................................................xii

ABSTRACT.......................................................................................................................xx

CHAPTER 1: THE NEED FOR A FUNCTIONAL GROUP APPROACH TO

DESCRIBE THE STRUCTURE OF CARIBBEAN HARD CORAL

ASSEMBLAGES.........................................................................................1

Introduction..................................................................................................1

Functional traits and functional groups in reef corals..................................4

Assigning species to functional groups using the Adaptive

Strategies Theory..........................................................................................6

Characteristics of each Adaptive Strategy..................................................12

The graphic model of the Adaptive Strategies Theory...............................15

Assigning Caribbean reef corals to functional groups and

defining the critical tests............................................................................21

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Characteristics of each functional group of coral.......................................27

Sources of environmental stress and disturbance on coral reefs................32

Testing the applicability of the functional group approach

for reef corals..............................................................................................35

Similarities in distribution of species between and among FG......35

Rank abundance by species and functional groups........................39

Percent cover of all corals..............................................................40

Percent cover per functional group................................................41

Total species richness....................................................................45

Functional group richness..............................................................47

Species richness within functional groups.....................................52

Testing the adaptive strategies theory on Caribbean coral reefs................54

CHAPTER 2: THE RESPONSES OF FUNCTIONAL GROUPS OF CORALS TO

DIRECT AND INDIRECT GRADIENTS ON THE FLORIDA REEF

TRACT.......................................................................................................56

Introduction................................................................................................56

Objectives...................................................................................................61

Similarities in distribution of species between and among FG......62

Rank abundance by species and functional groups........................63

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Percent cover and abundance per functional group.......................64

Species richness of all corals.........................................................66

Functional group richness..............................................................66

Species richness per functional group............................................67

Methodology...............................................................................................68

Geographic setting.........................................................................68

Data collection and analysis...........................................................69

Statistical Analysis.........................................................................73

Results ........................................................................................................75

Similarities in distribution of species between and among FG......75

Rank abundance by species...........................................................82

Rank abundance per functional group...........................................88

Percent cover of each functional group vs. W................................92

Percent cover of each functional group vs. total coral cover.........94

Total species richness vs. W...........................................................98

Total species richness vs. total coral cover....................................99

Functional group richness vs. W..................................................101

Functional group richness vs. total coral cover...........................105

Species richness within functional groups vs. W.........................109

Species richness within functional groups vs. total coral cover. .112

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Discussion.................................................................................................118

Dominance by species and functional groups..............................118

Percent cover per functional group..............................................121

Total species richness..................................................................123

Functional group richness............................................................124

Species richness within functional groups...................................125

Conclusions..............................................................................................128

CHAPTER 3: THE GEOGRAPHY AND ENVIRONMENTAL

CHARACTERISTICS OF THE NORTH LAGOON OF

BERMUDA..............................................................................................133

Introduction...............................................................................................133

Previous research into the distribution of corals across the North

Lagoon......................................................................................................141

Predominant environmental factors in operation across the study

area 143

Suspended particulate matter.......................................................143

Water temperature........................................................................146

Solar radiation..............................................................................147

The effect of depth and turbidity.....................................147

The effect of aspect..........................................................148

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Wave energy and currents............................................................150

Project 1: Mapping of the lagoonal reefs.................................................151

Introduction and Methodology....................................................151

Results and Discussion................................................................154

Project 2: Assessing the three dimensional light field over a range

of depths.........................................................................................................

157

Introduction and Methodology....................................................156

Results and Discussion................................................................157

Project 3: Cross-platform differences in downwelling light

availability................................................................................................162

Introduction and Methodology....................................................162

Results and Discussion................................................................164

Discussion.................................................................................................169

CHAPTER 4: THE DISTRIBUTION OF CORAL SPECIES AND FUNCTIONAL

GROUPS OVER PHYSICAL GRADIENTS ACROSS THE NORTH

LAGOON OF BERMUDA......................................................................173

Introduction..............................................................................................173

Objectives.................................................................................................175

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Similarities in the distribution of species and functional groups.175

Similarities among sites in species assemblages.........................178

Percent cover and abundance per functional group.....................178

Species distributions across sites.................................................179

Species richness of all corals.......................................................180

Functional group richness............................................................180

Methodology.............................................................................................181

Data collection.............................................................................181

Data analysis................................................................................186

Statistical analysis........................................................................190

Results ......................................................................................................192

Depths per reefs...........................................................................192

Similarity in species distributions across sites on each reef........195

Similarity among sites in species assemblages............................199

Distribution patterns of coral species...........................................215

Frequency of occurrence........................................................215

Standard measures for coral reefs................................................242

Section 1: Tops of reefs only.................................................242

A. Average percent coral cover.......................................243

B. Species richness...........................................................243

C. Functional group richness...........................................243

D. Percent cover of the branched viviparous FG.............244

E. Percent cover of the massive viviparous FG...............244

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F. Percent cover of the massive oviparous FG................245

Section 2: Tops and south sides of reefs................................249

A. Average percent coral cover.......................................249

B. Species richness...........................................................249

C. Functional group richness...........................................250

D. Percent cover of the branched viviparous FG.............250

E. Percent cover of the massive viviparous FG...............252

F. Percent cover of the massive oviparous FG................252

G. Percent cover of the folious and plating

viviparous FG..............................................................253

Discussion.................................................................................................262

Species and functional group distribution across sites................262

Percent cover per functional group..............................................264

Management issues......................................................................265

CHAPTER 5: SUMMARY, CONCLUSIONS AND RECOMMENDATIONS............269

REFERENCES................................................................................................................283

APPENDICES.................................................................................................................306

Appendix A Digital video image capture methodology...........................308

Appendix B: Applescript computer program to place dots on frames.....313

Appendix C: A list of coral species observed in Bermuda.......................317

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Appendix D: Bermuda climatology..........................................................318

Appendix E: Logistic regression of rank abundances; Florida data.........319

BIOGRAPHICAL SKETCH...........................................................................................325

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LIST OF TABLES

Table Page

1.01 The characteristic differences in biological attributes between

competitive, stress-tolerant and ruderal plant species (modified from

Grime 1979).....................................................................................................10

1.02 Life history characteristics of massive scleractinian corals as defined in

Table 3 in Soong (1993)..................................................................................23

1.03 The ranking of each proposed functional group in ten critical traits, and

the adaptive strategy to which they most closely represent.............................26

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2.01 Results of one-way analysis of similarity of the Bray-Curtis similarities

of the abundance data of the most abundant 11 species observed across

20 reef sites located on the Florida Reef Tract................................................79

2.02 Results of one-way analysis of similarity of the Bray-Curtis similarities

of the abundance data of all species observed across 20 reef sites

located on the Florida Reef Tract.....................................................................81

2.03 A table of the number of occurrences with which each the 36 most

abundant species ranked from 1 to 20 across all 200 transects........................85

2.04 A table of the observed number of times each functional group ranked

from 1 to 4 across the 200 transects surveyed.................................................90

2.05 Results of two-way t-test of the linear correlation between coral cover

of each functional group and W on 10 reef sites along the Florida Reef

Tract, testing whether the slopes are zero........................................................94

2.06 Results of orthogonal contrasts on whether the linear regressions of

percent coral cover for each functional group versus total coral cover at

each reef site were significantly different from zero.......................................97

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2.07 Results of two-way t-tests on whether the second-order coefficients for

polynomial regressions of FG cover versus total coral cover were

significantly different from zero......................................................................97

2.08 Results of orthogonal contrasts on the linear regressions of functional

group richness for each level of constraint versus W.....................................102

2.09 Results of orthogonal contrasts on the second-order coefficients for

polynomial regressions of functional group richness for each level of

constraint versus W........................................................................................102

2.10 Presence or absence matrices of the presence or absence of functional

groups across the ten reefs of the environmental gradient W. The rules

for inclusion of functional groups are as in Figure 2.18, above....................104

2.11 Results of orthogonal contrasts on the linear regressions of functional

group richness for each level of constraint versus W.....................................107

2.12 Results of orthogonal contrasts on the second-order coefficients for

polynomial regressions of functional group richness for each level of

constraint versus W........................................................................................107

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2.13 Results of analyses of variance of the linear regression of species

richness versus W for each functional group.................................................110

2.14 Results of two-way t-tests on whether the second-order coefficients for

polynomial regressions for species richness of each functional group

versus W were significantly different from zero............................................110

2.15 Results of two-way t-tests of the linear regression of species richness

for each functional group versus total coral cover for each functional

group..............................................................................................................114

2.16 Results of two-way t-tests on whether the second-order coefficients for

polynomial regressions of FG species richness versus total coral

assemblage cover were significantly different from zero..............................114

2.17 Sorted matrices of species presence or absence for each functional

group across 20 transects at each of the 20 sites of the Keyswide Coral

Reef Expedition.............................................................................................116

3.01 Characteristics of each zone of the survey area across the Bermuda

Lagoon, and the patch reefs contained therein...............................................155

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3.02 Two-way analysis of variance of the effects of depth and aspect on the

proportion of surface light reaching a hemispherical sensor.........................161

3.03 ANOVA table of the differences in light intensity across the five

locations from the data illustrated in Figure 2.13..........................................168

3.04 Results of a Tukey’s post hoc analysis of the significance in the

differences in the amount of luminance at 8-m depth over the hours of

11 am to 1 pm between the five locations across the reef platform...............168

4.01 Details of the 18 surveyed reefs surveyed across the North Lagoon.............185

4.02 Results of an ANOSIM analysis of distinctness in clustering of each

functional group.............................................................................................198

4.03 ANOSIM table for the factor Aspect across all sites, including the

results of pairwise post-hoc tests...................................................................203

4.04 Significance levels of separate ANOSIM tests comparing similarities

between reef sites located on the south versus north sides of reefs in

each zone and at different depths...................................................................204

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4.05 ANOSIM table for the factor Depth, calculated from data at each depth

from across all sites........................................................................................207

4.06 Significance levels of pair-wise tests comparing similarities between

reef sites located on different depths.............................................................207

4.07 ANOSIM table for the factor Zone across all sites........................................210

4.08 SIMPER analysis of the dominant species that differ between zones

across the Bermuda Platform.........................................................................211

4.09 Results of the 2-way ANOVAs of the six parameters across the 18 reef

sites located on the tops of patch reefs located in three replicate “legs”

across six zones located across the north lagoon in Bermuda.......................248

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LIST OF FIGURES

Figure Page

1.01 Percent cover for each of the 38 species recorded on the 20 reefs surveyed on the Keyswide Coral Reef Expedition............................................3

1.02 A modified diagram of Grime’s (1979) Adaptive Strategy Theory for

classifying habitats according to levels of stress and disturbance...................11

1.03 The Adaptive Strategies Theory graphic model, also known as the CSR

model, depicted as a ternary diagram..............................................................16

1.04 Generalized model of community dominants by Steneck and Dethier

(1994) that refines to Grime’s (1977) AST model (shaded in light gray).......18

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1.05 A modified version of Grime’s (1977) and Steneck and Dethier’s (1994)

generalized two-dimensional model of FG dominance within habitat

types.................................................................................................................20

1.06 Representation of how varying levels of the four most important

environmental factors act to promote growth, or act as a stressor or

disturbance agent to corals..............................................................................34

1.07 An illustration of different hypothetical distributions of species and

functional groups across an environmental gradient (A to D), and how

they appear when graphed as (i) abundances, (ii) tabulated in a matrix

of presence vs. absence, and (iii) graphed using a multivariate

ordination technique, such as Multidimensional Scaling (MDS)....................37

1.08 An illustration of how total assemblage biomass is predicted to vary

across habitat types characterized by different levels of resource

availability and disturbance.............................................................................41

1.09 Diagrams depicting the differing ways in which the abundances of

competitive (C), stress-tolerant (S) and ruderal (R) functional groups of

corals are predicted to vary across habitats located across the range of

stress and disturbance gradients encompassed by the AST mode...................43

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1.10 The distribution of species richness predicted to occur across habitats by

Grime’s (1977) Adaptive Strategies model.....................................................46

1.11 A diagram illustrating the range of strategies encompasses by (a) annual

herbs, (b) biennial herbs, (c) perennial herbs and ferns, (d) trees and

shrubs, (e) lichens and (f) bryophytes.............................................................48

1.12 A three dimensional model of the levels of biomass predicted for set of

functional groups of species across habitat types characterized by

varying levels of disturbance potential and productivity potential..................49

1.13 A diagram illustrating how functional groups are predicted to be

dispersed across patches located with habitats defined by varying rates

of resource gain and loss.................................................................................52

2.01 The elongated oval within this square diagram of state space represents

the hypothetical range within the AST (CSR) model that was occupied by

the sites of the Florida Reef Tract that are the focus of this chapter...................58

2.02 Relationship between total percent cover of the entire coral assemblage

and the measure of environmental disturbance due to island passes, W.........60

2.03 Map of South Florida and the Florida Keys.....................................................69

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2.04 A dendrogram showing the similarities in response patterns among the

eleven most abundant species assessed in Florida...........................................77

2.05 MDS showing the similarities in response patterns among the eleven

most abundant species assessed in Florida in two-dimensional state

space................................................................................................................78

2.06 MDS showing the similarities in response patterns among all 36 species

assessed in Florida in two-dimensional state space.........................................80

2.07 The log percent relative abundance of the species observed at the 200

transects assessed.............................................................................................83

2.08 The distribution of the proportion of ranks over the 200 sites that the

most dominant species, Montastrea faveolata, displayed...............................87

2.09 The proportion of ranks displayed by each functional group across the

200 transects surveyed.....................................................................................89

2.10 The relationship between rank per functional group and total abundance

per transect for the 200 transects surveyed......................................................90

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2.11 Relationship between percent coral cover of each functional group and

environmental influence of island passes, (W)................................................93

2.12 Orthogonal relationship between average percent coral cover for each

functional group and the total coral cover for the 20 reef sites surveyed

on the Keyswide Coral Reef Expedition.........................................................95

2.13 The same graphs illustrating the relationship between average percent

coral cover for each functional group and the total coral cover for the 20

reef sites surveyed as in Figure 2.12, but with different scales on the y-

axes..................................................................................................................96

2.14 Relationship between species richness of all corals and environmental

influence of island passes, W, at each reef site................................................98

2.15 Relationship between species richness and total coral cover across the

20 reef sites....................................................................................................100

2.16 Relationships between functional group richness under the four levels

of membership constraint and the environmental gradient of W across

reef sites.........................................................................................................103

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2.17 Regression of functional group richness versus total coral cover for each

site..................................................................................................................106

2.18 Relationship between species richness of each functional group and

environmental influence of island passes, W, at each reef site......................109

2.19 Regressions of species richness for each functional group on total coral

cover for each site..........................................................................................113

2.20 Percent cover for each of the 38 species recorded on the 20 reefs

surveyed on the Keyswide Coral Reef Expedition........................................129

2.21 Functional group cover for each of the four predominant functional

groups recorded on the 20 reefs surveyed on the Keyswide Coral Reef

Expedition......................................................................................................130

3.01 A photomosaic map of the Bermuda Islands and surrounding reef

platform.........................................................................................................134

3.02 An illustrated map of the islands and surrounding lagoonal patch reefs

of Bermuda, with important geographic features labeled (produced by

the author as part of the Bermuda Zoological Society).................................137

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3.03 A graph charting the number of passages by ships traveling through the

southern shipping channel in 2004................................................................145

3.04 An aerial photograph of a cruise ship traversing the south shipping

channel of Bermuda in a westerly direction, and leaving a plume of

sediment in its wake......................................................................................146

3.05 Temperature record for 2 subsurface temperature data loggers located

either near North Shore (Inshore) or on the forereef at 30 ft depth

(Offshore) for a three year period from 1998 – 2000 (modified from de

Putron 2003)..................................................................................................147

3.06 A graph of the hourly positions and paths the sun appears to take as it

crosses the sky in Bermuda over the course of a day during the summer

and winter solstices, and either equinox........................................................149

3.07 Zonal boundaries, locations of the north and south shipping channels,

and location of patch reefs distributed across the study area

encompassing the North Lagoon...................................................................153

3.08 A diagram illustrating the modified Li-Cor scalar PAR sensor.....................159

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3.09 Mean proportion of surface light (± standard error) originating from

four directions at five depths, as measured by the hemispherical sensor......160

3.10 Map of the five reef sites, indicated by the light-bulb symbol......................163

3.11 Light intensity readings taken over five days from sensors positioned at

8-m depth at 5 reef sites located at different distances from shore across

the area of study.............................................................................................166

3.12 Average light intensity (Lumens ±SE) measured from 11 am to 1 pm

local standard time over the first of the five days of deployment, by

light sensors located at 8-m depth at five reef sites positioned at

increasing distances from the North Shore of Bermuda................................167

3.13 Representation of how varying levels of the four most important

environmental factors act to promote growth, or act as a stressor or

disturbance agent to corals............................................................................171

4.01 A modified version of Grime’s (1977) and Steneck and Dethier’s (1994)

generalized two-dimensional AST model of FG dominance within

habitat types, incorporating the concession that biota can only survive

in habitats within which the rate or amount of resource acquisition

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(resource abundance) is greater than the rate or amount of resource loss

(or disturbance)..............................................................................................177

4.02 General design of the study, in which survey sites (circles) were

surveyed at a range of depths on the north, south and top sides of

replicate patch reefs within each of six zones located at increasing

distances from shore......................................................................................183

4.03 A map of the lagoonal reefs located within and around the research area

and the 18 patch reef sites surveyed in the videographic analyses................184

4.04 Diagram illustrating the average depths of each site on patch reefs

located on different sides (aspects) and at varying distances from shore......194

4.05 Dendrogram of Bray-Curtis similarities of species and functional groups

clustered according by group-averaging........................................................196

4.06 Multidimensional scaling diagram (MDS) of square-root transformed

relative abundance data for coral species averaged across sites located

on replicate reefs and over different aspects, depths and distances from

shore...............................................................................................................197

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4.07 MDS of square-root transformed relative abundance data of species for

all sites...........................................................................................................202

4.08 MDS of square-root transformed relative abundance data of species for

all sites depths on all reefs.............................................................................206

4.09 MDS of square-root transformed relative abundance data of species for

all sites...........................................................................................................209

4.10 The sites surveyed across the Bermuda platform cluster into three

groups with different coral species composition, which also match three

different environmental conditions................................................................214

4.11 MDS of square-root transformed frequency of occurrence data of all

coral species for all sites, as in the three figures abov...................................216

4.12 The average proportion of frames with any coral present across all sites,

illustrated as a line graph per site per reef (A) and as a bubble graph per

depth and zone (B).........................................................................................217

4.13 Four MDS graphs of square-root transformed frequency of occurrence

data of Branched Viviparous species as a group, and for M. decactis, M.

mirabilis and P. porites corals separately for all sites...................................219

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4.14 The average proportion of frames with corals of the Viviparous

Branching (VB) functional group present across all sites, illustrated as a

line graph per site per reef (top) and as a bubble graph per depth and

zone (bottom).................................................................................................220

4.15 The average proportion of frames with corals of the species Madracis

decactis present across all sites, illustrated as a line graph per site per

reef (top) and as a bubble graph per depth and zone (bottom)......................221

4.16 The average proportion of frames with corals of the species Madracis

mirabilis present across all sites, illustrated as a line graph per site per

reef (top) and as a bubble graph per depth and zone (bottom)......................222

4.17 The average proportion of frames with corals of the species Porites

porites present across all sites, illustrated as a line graph per site per

reef (top) and as a bubble graph per depth and zone (bottom)......................223

4.18 MDS graph of square-root transformed frequency of occurrence data of

the coral species Agaricia fragilis, the only member of the Foliose and

Plating Viviparous (FP) functional group observed in the North lagoon

in Bermuda in this study................................................................................225

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4.19 The average occurrence frequency of the species Agaricia fragilis

across all sites, illustrated as a line graph per site and reef (top) and as a

bubble graph per depth and zone (bottom.....................................................226

4.20 Four MDS graphs of square-root transformed data of occurrence

frequency by Massive Viviparous species as a group, and for F. fragum,

P. astreoides and S. radians corals separately, for all sites...........................228

4.21 The average proportion of occupied frames per transect with corals

belonging to the Massive Viviparous functional group present across all

sites, illustrated as a line graph per site per reef (top) and as a bubble

graph per depth and zone (bottom)................................................................229

4.22 The average proportion of frames with corals of the species Favia

fragum present across all sites, illustrated as a line graph per site per

reef (top) and as a bubble graph per depth and zone (bottom)......................230

4.23 The average proportion of frames with corals of the species Favia

fragum present across all sites, illustrated as a line graph per site per

reef (top) and as a bubble graph per depth and zone (bottom)......................231

4.24 The average proportion of frames with corals of the species

Siderasterea radians present across all sites, illustrated as a line graph

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per site per reef (top) and as a bubble graph per depth and zone

(bottom).........................................................................................................232

4.25 Seven MDS graphs of square-root transformed relative abundance data

of (a) Massive Oviparous species as a group, and for (b) M. cavernosa,

(c) M. faveolata, (d) M. frankesi, (e) D. labyrinthiformis, (f) D. stigosa

and (g) S. intersepta separately for all sites...................................................234

4.26 The average proportion of frames with corals of the Massive Oviparous

(MO) functional group present across all sites, illustrated as a line graph

per site per reef (top) and as a bubble graph per depth and zone

(bottom).........................................................................................................235

4.27 The average proportion of frames with corals of the species

Montastraea cavernosa present across all sites, illustrated as a line

graph per site per reef (top) and as a bubble graph per depth and zone

(bottom).........................................................................................................236

4.28 The average proportion of frames with corals of the species

Montastraea faveolata present across all sites, illustrated as a line graph

per site per reef (top) and as a bubble graph per depth and zone

(bottom).........................................................................................................237

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4.29 The average proportion of frames with corals of the species

Montastraea franksi present across all sites, illustrated as a line graph

per site per reef (top) and as a bubble graph per depth and zone

(bottom).........................................................................................................238

4.30 The average proportion of frames with corals of the species Diploria

labyrithiformis present across all sites, illustrated as a line graph per site

per reef (top) and as a bubble graph per depth and zone (bottom)................239

4.31 The average proportion of frames with corals of the species Diploria

strigosa present across all sites, illustrated as a line graph per site per

reef (top) and as a bubble graph per depth and zone (bottom)......................240

4.32 The average proportion of frames with corals of the species

Stephanocoenia intersepta present across all sites, illustrated as a line

graph per site per reef (top) and as a bubble graph per depth and zone

(bottom).........................................................................................................241

4.33 Average percent coral cover for (A), (B) species richness, (C) functional

group richness as well as (D – F) the average percent cover for each

functional group on the tops of each of three replicate reef sites in each

of the six zones..............................................................................................246

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4.34 Percent cover, species richness and functional group richness of corals

surveyed on sites located on the tops and southern flanks of patch reef.......254

4.35 Percent cover of the Branched Viviparous, Massive Viviparous and

Massive Oviparous functional groups of corals surveyed on sites

located on the tops and southern flanks of patch reefs..................................254

4.36 Percent cover of the three species of Branched Viviparous functional

group..............................................................................................................257

4.37 Percent cover of Agaricia fragilis, the one species of the Foliose and

Plating functional group found within the lagoonal sites surveyed...............258

4.38 Percent cover of the three species of Massive Viviparous functional

group..............................................................................................................259

4.39 Percent cover of the two of the five species of Massive Oviparous

functional group.............................................................................................260

4.40 Percent cover of the three other species of Massive Oviparous

functional group.............................................................................................261

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5.01 Diagrams depicting the differing ways in which the abundances of

competitive (C), stress-tolerant (S) and ruderal (R) functional groups of

corals are predicted to vary across habitats located across the range of

stress and disturbance gradients encompassed by the AST model, and

depending on the degree of niche overlap exhibited by each functional

group..............................................................................................................272

5.02 A diagram illustrating how the Zero Net Growth Intercepts (ZNGI) of

each of the predominant functional groups of Caribbean coral found in

Florida and Bermuda are dispersed across the Adaptive Strategies

Theory model.................................................................................................273

5.03 The bounded area laid over the modified Adaptive Strategies Theory

shown in Figure 5.02 represents the range of habitat types surveyed in

Florida............................................................................................................274

5.04 The bounded area laid over the modified Adaptive Strategies Theory

shown in Figure 5.02 represents the range of habitat types surveyed in

Bermuda.........................................................................................................275

5.05 A network of interacting corals on the Bermuda fore reef............................278

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ABSTRACT

Murdoch, Thaddeus James Thomas, Ph.D., University of South Alabama, December 2007. A Functional Group Approach for Predicting the Composition of Hard Coral Assemblages in Florida and Bermuda. Chair of Committee: Dr. Richard B. Aronson

In Florida the functional-group approach provided new insights into the manner in

which varying levels of disturbance affected species richness across sites. Despite the

chaotic patterns in biomass displayed by each assemblage of coral species when

separately plotted across reefs, each functional group of corals responded to direct and

indirect gradients of disturbance in a orderly and group-specific manner. Functional

groups displayed a nested distributional pattern, indicating that negative interactions

between functional groups are probably weak

Terrestrial and marine ecologists have found that a functional group approach can

accurately predict how organisms will respond to changes in environment conditions. A

functional group approach categorizes organisms, regardless of phylogeny, according to

similarities and differences in life history and other ecologically relevant traits. One such

model, the "CSR plant strategy theory" developed by Phillip Grime in 1973 for

terrestrial plants, predicts the assemblage structure of biota over gradients of stress and

disturbance. To test the CSR model, coral assemblages on reefs from Florida and

Bermuda were assessed at the hierarchical levels of species and functional groups. The

data were used to address the question of whether the functional-level approach provides

information about community structure that species-level analysis fails to provide.

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Additionally, the predictions of the CSR model were tested regarding how coral cover,

species diversity and assemblage structure should vary in habitats characterized by

differing levels of disturbance and resource-limitation.

In Bermuda, functional groups of corals also displayed a nested pattern across sites

located over a range of depths and reef zones. When species were aggregated according

to shared habitat, species from the same genus co-occurred in almost every case. This

implies that these closely related species also share many functional traits and yet still

coexist in many habitats

The Adaptive Strategies Theory provides a series of simple, testable hypotheses that

can be used to guide ecological research in an iterative and informative manner. The

Adaptive Strategies Theory is a powerful theoretical framework, which can be modified

to give it great heuristic value for guiding ecological research.

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CHAPTER 1: THE NEED FOR A FUNCTIONAL GROUP APPROACH TO DESCRIBE THE STRUCTURE OF CARIBBEAN HARD CORAL ASSEMBLAGES

Introduction

Coral reefs are in decline around the globe (Aronson and Precht 2001, Knowlton

2001, Gardner et al 2003, Wilkinson 2004). Concerns that assemblages of reef corals may

have lost their ability to resist disturbance are mounting (Jackson et al 2001; Nyström and

Folke 2001; McClannahan et al 2002; Bellwood et al 2004; Hughes et al 2005; Aronson

and Precht 2006; Nyström 2006), as exhibited by dramatic changes in the community

structure of coral reefs, from a state of high coral biomass and low algal biomass to an

alternate condition of high algal biomass and low coral biomass Gardner et al. 2003.

In the Caribbean, the most obvious change is the loss of the three dominant species of

coral (Acropora cervicornis, A. palmata and Montastraea annularis species complex),

and the clear zonation patterns these species once produced (Done 1983; Graus and

Macintyre 1989; Jackson 1991; Hughes 1994). Nonetheless, on many of the same reefs,

it appears that subordinate coral species have not decreased to the same extent (e.g. Bak

and Engel 1979; Aronson and Precht 1999). While it is well known that corals differ in

their sensitivities to a range of environmental and biological factors, coral ecology as a

science does not yet provide the means for predicting which species will be affected by

specific changes in their environment nor in the manner in which changes will manifest

themselves.

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If we are to effectively manage coral reef communities and prevent further declines of

corals, we must improve our understanding of how all species of coral respond to

changes in physical and biological processes. We need to be able to determine whether

predictable patterns in the abundance, co-occurrence and diversity of corals occur across

habitats that vary in environment or in disturbance history. We also must ascertain the

role that all species of corals play in providing function to reef ecosystems, including reef

growth, nutrient cycling, the inhibition of invasive species, and the enhancement of

biodiversity. With the exception of what historically were some of the more abundant

coral species, such as Acropora cervicornis, Montastraea annularis and Porites

astreoides, there has been very little advancement in these areas.

Expanding our focus to all of the corals that live on a coral reef will require

developing techniques for simplifying the complicated data that accompany such an

increase in perceptional scope. The degree of complexity inherent in multi-species data

from a large-scale ecological assessment can be seen in the following example. During

the Keyswide Coral Reef Expedition of 1995 (Murdoch and Aronson 1999), 19,055

individual corals, representing 38 species, were recorded from 200 video transects filmed

on twenty reefs located across the entire 350-km long Florida Reef Tract. When the

percent cover data for each species on each reef surveyed was plotted (Figure 1.01), the

resulting graph appears to have little structure. Instead the graph may best be

described as a chaotic tangle of species varying in occurrence across reefs in an

idiosyncratic manner. The lack of pattern found in data from Florida is typical for

monitoring projects that cover large regions (e.g. Goreau 1959; Done 1982), and

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illustrates the need for techniques with which to organize and simplify species-level data

so that they can be interpreted in an ecologically meaningful way.

Figure 1.01. Percent cover for each of the 38 species recorded on the 20 reefs surveyed on the Keyswide Coral Reef Expedition. Letters represent individual sites on reefs separated by ~ 10 km. Data from each reef are plotted from western-most to eastern-most location.

Recently it has been suggested that a revived focus on the biological traits of

organisms and the manner in which they vary across environmental gradients will

promote the development of better ways of measuring and interpreting ecological

information (McGill et al. 2006). Biological traits are specific, quantifiable characteristics

of an organism that can be compared across individuals both within and among species.

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Gradient analysis can include either indirect gradients, such as differences in depth down

a fore reef, or direct gradients of a particular physical or chemical parameter, such as

light intensity or oxygen concentration. A trait-based approach uses the properties of

environmental gradients to tease apart the relative form that functionally important traits

take in an assemblage of organisms located across the gradients, in much the same

manner that glass prisms can be used to split a beam of white light into its component

colors (Keddy 1992).

Functional Traits and Functional Groups in Reef Corals

Corals are affected by and react to environmental and biological factors through their

physiological, morphological and behavioral traits. Within a geographic region, the

members of the species pool that are found within a particular habitat are presumed to

possess the traits that allow their recruitment and continued presence, whereas the species

that are absent are assumed to lack these same critical characteristics (Bradbury and Loya

1978; Sorokin 1993; Sullivan and Chiappone 1993; Edinger and Risk 1995; Hughes et al.

1999). Many researchers have attempted to detect theoretically meaningful correlations

between the traits that different coral species possess and the species’ abundance within a

habitat. For instance, Lang (1973) looked for patterns in competitive dominance

hierarchies of corals by ranking species according to their aggressive abilities. Porter

(1976) and Green et al. (1987) grouped species by polyp size in order to ascertain

whether species with similar polyps shared trophic position and thus depth zones on

forereefs. Szmant (1986), Edinger and Risk (1995), Hughes et al. (1999), Knowlton

(2001) and others have grouped corals by reproductive mode. Corals that brood planula

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larvae were compared with corals that broadcast spawn, and predictions regarding their

relative abundance or distribution were made based on the differences in energy

allocation, dispersal method and dispersal range between brooders and spawners. Barnes

(1973), Jackson (1979), Bellwood et al. (2004), and others grouped corals and other reef

biota according to morphology. They theorized that, since morphology is related to the

rates of light collection, sediment shedding and fragmentation, morphology could be used

to predict which coral species would dominate a particular habitat. However, all of these

attempts at using single kinds of traits to predict the presence or abundance of corals in a

particular habitat have been unsuccessful. This is because a single-trait approach cannot

define differences between all species, not can it encompass the broad range of energetic,

physical, chemical and biological factors and processes that affect corals on reefs. A

more powerful technique is to examine how sets of different kinds of co-occurring traits

are correlated with, or induced in response to, differences among habitats located along

environmental and biological gradients (Keddy 1992; Körner 1993)).

The manner in which species share groups of traits may be analyzed in two ways:

(1) Functional trait analysis

(2) Functional group analysis

Functional trait analysis looks at the form each trait takes separately at the hierarchical

level below the level of the species. Direct analysis of traits has been shown to be a

powerful technique for interpreting the causes of the spatial distributions of terrestrial

plants (e.g. Weiher et al. 1998; Mayfield et al. 2006), but it also further increases the

complexity and amount of information needed. Alternatively, in functional group

analysis, species that share life history or adaptive strategy are sorted into functional

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groups, a hierarchical level above species. Functional group analysis has been shown to

be useful for interpreting terrestrial plant data, but it provides the added benefit of

simplifying species-level information, not making it more complex (Fagerstromm 1988;

Körner 1993).

Assigning Species to Functional Groups using the Adaptive Strategies Theory

Ecologists use functional classification schemes for two separate reasons (Gitay and

Noble 1997). When investigating the effects of organisms on ecosystem processes,

species are categorized into functional effects groups (e.g. Walker et al. 1999).

Alternatively, when the goal is to determine the manner in which organism will react to

environmental change, species are categorized into functional response groups (e.g.

Lavorel et al. 1997). The research described in this manuscript focuses on the patterns

manifested by functional response groups at locations that vary in environmental

condition.

There are as many ways to assign species to functional response groups as there are

ecological factors of interest (Körner 1993). However, I propose that one particularly

constructive way of classifying modular, sessile organisms such as plants, and perhaps

corals, into functional groups is by using a modified version of Grime’s (1979) Adaptive

Strategies Theory (AST; Keddy 1992; Andersen 1995; Steneck and Dethier 1996; Airoldi

1998). Grime (1979) used first principles to categorize all habitats into four primary kinds

(Figure1.02), which I will refer to as habitat types, according to the relative measure

within each habitat of two fundamental environmental factors. These two

environmental conditions are (1) the availability or supply rate of resources (i.e. nutrients,

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energy) employable for biomass maintenance and growth, and (2) the likelihood or rate

that biota within a habitat will sustain damage or the loss of resources, biomass or

physiological function (which is defined as disturbance). Following Grime’s (1979)

scheme, the reciprocal of resource availability is defined as “stress”, and is considered to

be different from disturbance. Accordingly, stress is defined as a lack of resources

available for use by an organism, and disturbance is defined as a loss of the resources

already acquired by the organism under consideration (Grime 1979), . Other terrestrial

(Wilson and Keddy 1986; Chapin 1991) and marine (Kautsky and Kautsky 1989; Steneck

and Dethier 1996) ecologists utilize the same convention, although the distinction

between stress and disturbance is not usually made by coral ecologists (e.g. Dollar 1981;

Grigg 1995; Hughes and Connell 1999)

The specific suite of environmental conditions in which an organism finds itself

affects the relative benefits and costs of allocating resources to different biological

functions. Additionally, since the organism often finds itself in an environment with

limiting resources, it must balance, or tradeoff, the amount of resources allocated to each

function, based on the current adaptive value of that function, and relative to the adaptive

value of the other functional structures and behaviors in which it could also invest. The

organism must also minimize the risks inherent in allocating resources to a functional

structure that has a high probability of being damaged or made redundant.

All organisms must allocate resources to the following biological functions and

behaviors:

Resource acquisition

Maintenance and repair of body function

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Resource and energy storage

Defense: The development of biochemical, structural or behavioral characteristics

that prevent or inhibit other organisms from taking part of its body structure or resources.

Aggression: The development of biochemical, structural or behavioral

characteristics that which facilitate competitive superiority for space, or other kinds of

resource, over other organisms.

Growth

Sexual reproduction

Recycling of damaged or obsolete body structures and organelles.

Additionally, clonal organisms such as corals can allocate resources to asexual

reproduction in any of three ways. First, they can reproduce asexually via fragmentation

of viable parts of the colony, the rate of which dependent on the rate of growth and

growth form of the species (Highsmith 1987). Second, some corals, such as Porites

astreoides, are also capable of asexual reproduction by self-fertilization (Brazeau et al.

1998). Third, some corals, such as Pocillopora, may produce planulae asexually

(Stoddart 1983; Sherman et al. 2006).

Of the ten ways to allocate resources described above, three in particular play a key

role in determining the life-history and functional characteristics of an organism and its

survival abilities in different environmental conditions (Table 1; Grime 1973). These

three primary processes to which an organisms must allocate resources in order to persist

within a habitat are:

(1) Growth,

(2) Defense and Resource Storage, and

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(3) Sexual Reproduction.

Within habitats characterized by high levels of available resource, and a low risk of

disturbance (Figure 1.02), ecologically successful organisms will be those that primarily

allocate resources to growth. Similar rates of growth could not be supported in habitats

with low levels of resource availability, even with low levels of disturbance, and survival

in such an environment would instead require resource allocation primarily to storage and

defensive structures and behaviors. Alternatively, organisms are likely to lose stored or

growth-directed biomass in habitats characterized by high levels of resource, but high

rates or intensity of disturbance. In these heavily disturbed environments, resources

should primarily be allocated to reproduction, so that offspring may escape to less-

disturbed habitats. Following the logic of Grime (1973), no strategy exists that permits

the survival of an organism under the concurrent conditions of intense disturbance and

negligible resources for repair or reproduction.

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Table 1.01. The characteristic differences in biological attributes between competitive,

stress-tolerant and ruderal plant species (modified from Grime 1979).

Adaptive Strategy

Attribute Competitive Stress-tolerant Ruderal

Maximum Size Large Small Small

Longevity Long or short Very long Very short

Reproductive Maturity Late Late Early

Reproductive Effort Small Small Large

Reproductive Method Both Clonal Sexual

Growth Rate Rapid Slow Rapid

Stress response Rapid Slow Reproduces

Palatability Variable Low High

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Figure 1.02. A modified diagram of Grime’s (1979) Adaptive Strategy Theory for classifying habitats according to levels of stress and disturbance. The diagram also illustrates the optimal strategy predicted to be exhibited by the biota found within each habitat type, based on the optimal use of resources and the likelihood of incurring damage.

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Characteristics of each Adaptive Strategy

Competitive dominant species

Organisms that primarily utilize a strategy in which growth is favored are termed

“competitive dominants” by Grime (1979; Figure 1.02). Allocation of resources to

growth is an optimal strategy when resources are abundant and levels of disturbance are

low, because growth promotes further resource capture and allows even more growth.

This positive feedback loop allows competitive species to reach large sizes, when in

benign habitats, relative to species employing other strategies. High rates of growth also

permit competitive species to expand (laterally and vertically) more quickly than less

competitive species, and thereby dominate previously unoccupied space. Occupied space

can also be actively acquired using growth, via either the over-topping or shading-out of

slower growing organisms. In benign habitats the storage of resources is disadvantageous

for competitively-superior species, since stored resources cost resources and energy to

store and also tie-up resources that would be better used in the acquisition of more space

and more resources.

Asexual reproduction via fragmentation or similar mechanisms, which Grime (1977)

refers to as vegetative reproduction, is expected to be enhanced in competitive species,

since high growth rates, coupled with of partial mortality, will result in the generation of

disconnected clones of relatively large size. Alternatively, the proportion of resources

used for sexual reproduction in competitive species is expected to be relatively small,

since the release of gametes represents a risky loss of resources that could also be used

for additional growth and acquisition of space (Williams 1975; Bazzazz et al. 1987; Hall

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and Hughes 1996; Heino and Kaitala 1999). As disturbances occur in all habitats,

however, some level of reproduction is necessary for survival by species using all

strategies. Reproductive onset in competitive species is predicted to be delayed until the

organisms have grown to a large size. When initiated, reproduction is expected to occur

after the season of maximal potential productivity or during the season of highest

likelihood of disturbance. When exposed to either periods of stress or of disturbance,

competitive species are expected to further reduce the allocation of resources to

reproduction or storage, in favor of continued growth or tissue repair (Grime 1979).

Ruderal Species

Organisms that allocate most resources to reproduction are defined by Grime as

“ruderal” or weedy species. Ruderal species are those that are capable of surviving in

habitats characterized by high levels of disturbance, but only when abundant resources

are also available. Ruderals are predicted to have life history strategies that differ

substantially from those of competitive species, except that they share in the ability to

rapidly capture resources. Since the likelihood or intensity of disturbance is high for

ruderal organisms, they are likely to experience high rates of partial or total mortality and

rarely reach large sizes. Species that allocate resources to the development of structures

or physiological attributes that reduce the effects of disturbance would be more likely to

persist in disturbed environments, but at a cost in the amount of resources available for

the development of other tissues or for reproduction. Initial growth rates may be high in

ruderal species, but since the relative cost of reproduction outweighs the risk that

reproduction will reduce survivorship in highly disturbed environments, ruderal species

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are predicted to initiate reproductive effort at a small size. Resource storage would be

disadvantageous in ruderal species since lifespan is likely to be short. Fragmentation rates

are predicted to be high in ruderal species. However, since fragment size is likely to be

smaller than in competitive species, the fragments of ruderal species may have a lower

likelihood of survival. Under periods of stress, ruderals are expected to increase resource

allocation to reproduction, since the likelihood of continued survival within the habitat is

reduced.

Stress-tolerant species

Species that allocate resources predominantly to storage and defense are termed

“stress-tolerant species” by Grime (1979). Since the rate or probability of acquisition of

resources is low, stress-tolerant organisms should possess structures that maximize

resource capture and storage when resources are present. Allocation of resources for

biochemical, structural or behavioral modifications that reduce the loss of biomass by

predation or competition would also be maximally advantageous under stressed

conditions. Low rates of resource capture will limit growth and reproductive output and

delay the initiation of reproduction in these organisms to “mast” years when resources are

particularly high. However, despite slow rates of growth the eventual attainment of a

large size would be possible if the organisms were located within a habitat experiencing

very low levels of disturbance. Additionally, the slow rates of growth and low density of

biomass in stressed habitats slow the rates of competition, allowing a high number of

species to coexist (Huston 1994).

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The Graphic Model of the Adaptive Strategy Theory

In this section I describe in detail the graphic model of Grime’s (1979) Adaptive

Strategy Theory. I then explain how it has been refined by various investigators since it

was first proposed. I also offer my own modifications to the graphic model, with which I

hope to improve both the model’s clarity and the way it logically corresponds with

reality.

As shown in Figure 1.02, above, the initial graphic model of the adaptive strategy

theory was a square subdivided into four boxes, each representing an extreme in

environmental condition possible within a habitat (Grime 1979). However, since the high

stress and disturbance environment was defined as uninhabitable by all biota, Grime

rearranged the square habitat model as a triangle, or ternary diagram. In this new

configuration, competitive ability, intensity of disturbance and intensity of stress are

represented by three axes (Figure 1.03). The C, S and R axes of the ternary graph are the

source for a second name for the Adaptive Strategies Theory, which is the “CSR model”.

Secondary and tertiary strategies, which represent compromises in adaptive traits

between the three primary strategies, such as “Competitive-Ruderal”, are hypothesized to

exist in habitats characterized by intermediate levels of stress or disturbance (Grime

1979).

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Figure 1.03. The Adaptive Strategies Theory graphic model, also known as the CSR model, depicted as a ternary diagram. Primary functional strategies are represented as follows: C = competitively dominant, S = stress-tolerant, R = Ruderal. Secondary and tertiary strategies represent a compromise between two or three of the primary strategies, and are represented in the model by combinations of these three letters.

Grime (1977) added the variable “Competition” and modified the graphic model into

a ternary diagram so that the trade-offs between the adaptive strategies that confer

advantage under each of the three strategies could be represented illustratively in a simple

and intuitive manner. However, one problem with the ternary version of the model is that

it represents three variables constrained within two dimensions. To be more accurately

represented, the three variables should be considered to be independent of each other, and

thus each should have their own axes on a three-dimensional model (Loehle 1988). This

error in the graphic model means that the relative overall cost of response to each species

is constrained to the same level of cost as all other species under study. Such a graphic

constraint is consistent with the role of trade-offs between the three adaptive strategies

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that Grime intended. However, it is more likely that some species will be better or worse

than others at acquiring resources or at balancing the trade-off between the intensity of

interspecific competition, resource availability and disturbance level, or that the trade-

offs are not linear. Therefore, Loehle (1988) contended, to more accurately depict nature,

each species should be located on points within a relatively bigger or smaller triangles in

the CSR ternary model. Of course Grime’s intent was to produce a relatively simple

model of all possible adaptive strategies, which Loehle’s proposed three-dimensional

model would not be. More importantly, however, it could be argued that adding

competition to the square graphic model to make it a ternary model mixes the two

independent variables, representing the environmental condition of the habitats, with the

dependent competitive response that the organisms within the habitats are predicted to

make (Steneck and Dethier 1994; Wilson and Lee 2000).

In order to avoid the problems associated with combining the dependent variable of

competition and the two independent variables in the graphic AST model, Steneck and

Dethier (1994) restructured the CSR ternary diagram of Grime (1977) back into a two

dimensional graphic (Figure 1.04). This reconfiguration restores resource availability

and disturbance to their capacity as independent variables, and C, S and R as dependent

response variables within the environmental state space.

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Figure 1.04. Generalized model of community dominants by Steneck and Dethier (1994) that refines to Grime’s (1977) AST model (shaded in light gray). Primary strategies are in accordance with the AST with the addition of disturbance-adapted biota in the upper right corner of the model, which Grime later refuted (Grime 1995). Secondary strategies are indicated by letter designations.

However, I contend that Steneck and Dethier (1994) made a different error in their

graphic model (Figure 1.04). In their restructured model, Steneck and Dethier (1994)

included as inhabitable, areas under the graph in which resources are at very low levels

but in which disturbances are moderately high. If one assumes: (1) that the disturbance

gradient represents a range of rates of resource loss, (2) the gradient of stress on the y

axis represents a range of rates of resource gain, (3) that similar positions on the two axes

are intended to represent comparable levels of resource flux (albeit opposing directions of

flux), and (4) that habitat types in which rates of resource loss are greater than resource

gain cannot support organisms, then logically one should conclude that locations on the

graph representing a loss-gain ratio greater than 1 should be empty of functional groups.

To encompass these assumptions and conclusion, I suggest that the graphic model should

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be redrawn as in Figure 1.05. In this further revision of the AST/CSR graphic model,

viable biological strategies are only shown to exist in the areas of state-space in which the

rate of resource gain is greater than the rate of resource loss. The line defining the

boundary between viable and intolerable environmental conditions represents the zero net

growth intercept (ZNGI) of the entire assemblage under investigation, in a manner

similar to that used by Tilman (1982; 1989), Chase and Leibold (2003) and others. With

the revised graphic model one can better represent how changes across habitats in the

environmental factors of resource availability and disturbance affect the characteristics of

coral assemblages. In Chapter 2 I delineate how the AST predicts each functional group

of corals will exhibit different levels of abundance, species richness and functional

ecology on reefs located across natural or anthropogenic gradients of stress and

disturbance.

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Figure 1.05. A modified version of Grime’s (1977) and Steneck and Dethier’s (1994) generalized two-dimensional model of FG dominance within habitat types. This modified version incorporates the concession that biota can only survive in habitats within which the rate or amount of resource acquisition is greater than the rate or amount of resource loss. The boundary between the white and grey areas is the ZNGI of the assemblage as a whole. Letter designations for adaptive strategies are as in Figure 2.

Assigning Caribbean Reef Corals to Functional Groups and

Defining the Critical Tests

Functional classification schemes such as the AST have been most typically applied

to the study of terrestrial and marine plants (e.g. Grime 1979; Steneck and Dethier 1994;

reviewed in Solbrig 1994). Some animals, such as ants, also possess many of the same

characteristics that allow plants to be grouped according to functional response, such as

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modularity, a dispersive reproductive phase and a sessile adult phase, and competition for

space, and for this reason have also been investigated under various functional

classification schemes (Andersen 1995). Reef corals equipped with zooxanthellae also

share many of the characteristics that plant ecologists use to differentiate functional

groups in plants (Furla et al. 2005), and for this reason may also be meaningfully

classified into functional groups using the sorting strategies developed by plant

ecologists.

Like plants, reef corals possess a modular structure and can be composed of an

indeterminate number of repeating multicellular units. Corals adopt many of the same

basic morphological shapes as plants, and these shapes typically share terminology, such

as foliose, palmate or bushy. It is not important that corals do not produce the exact same

morphologies as plant, just that corals and plants are both capable of utilizing their

modular character to produce a wide range of morphologies that differ in functional

effect and response to the environment and to competition. Corals and plants have

comparable life histories, with a dispersive reproductive phase followed by a sessile adult

phase. Both kinds of organisms also generally rely on light-driven photosynthesis and the

acquisition of water-dissolved nutrients for the resources and energy needed for growth

and other life-sustaining processes. Some corals and some plants are “ecosystem

engineers” (Jones et al. 1994), which produce topographic complexity that provides

habitat for other organisms, thereby enhancing the biological diversity of the habitats

they occupy. Additionally, both corals and plants maintain their spatial position through

interference competition with neighboring sessile organisms.

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I contend that Caribbean reef coral species and the potential functional groups can be

assigned to positions within Grime’s Adaptive Strategies model, through reference to the

same kinds of attributes and characteristics in corals as Grime utilized for plants. Reef

corals appear to possess sets of traits that are indicative of adaptive strategies similar to

those defined for plants by Grime (1977). For example, Soong (1993) observed that

different species of massive (in this case, meaning hemispherical or mound-shaped,

following Budd et al. 2006) reef corals that shared maximum size (large or small) also

exhibited similar rates of growth and recruitment, reproductive mode, reproductive

season, and the size at which each species reached sexual maturity (Table 2).

Specifically, large massive corals appeared to exhibit a more K-selected strategy, with a

spawning reproductive mode, relatively high rates of colony growth as adults, delayed

puberty and low reproductive investment. Conversely, small massive species of corals

exhibited a more ruderal strategy, with a brooding reproductive mode, slower growth as

adults, and higher investment in reproduction and recruitment. The same ranges of and

trade-offs in trait values can be seen in Grime’s competitive and ruderal adaptive

strategies for plants. These similarities between Soong’s (1993) data for corals and

Grime’s (1979) plant groups imply that:

1) corals are also constrained in the manner in which they allocate resources to

critical ecological functions and

2) additional functional groups of corals, defined according to other morphological

and reproductive life history strategies, may match Grime’s other adaptive

strategies.

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Table 1.02. Life history characteristics of massive scleractinian corals as defined in Table 3 in Soong (1993).

Character Large Species Small Species References* Reproductive Broadcasting Brooding 2, 11, 12Mode

Reproductive Once, Many Times, 11, 12Season Annual Cycle Lunar Cycle

Puberty Size Large Small 13

Recruitment Low? (sic) High? (sic) 3, 5, 6, 7, 8,10, 11, 12

Growth Rate High Low 1, 4, 9 _____ 1: Vaughan (1915); 2: Stimpson (1978); 3: Bak and Engel (1979);4: Highsmith (1979); 5: Rylaarsdam (1980); 6: Rogers et al. (1984); 7: Fitzhardinge (1985); 8:Hughes and Jackson (1985); 9: Hudson (1985);10: Wallace (1985); 11: Szmant (1986); 12: Soong (1991); 13: Soong 1993.

Johnson et al. (1995), in their investigation into the extinction selectivity of corals

with different ecological and life history traits, also found that sets of traits covaried in

Caribbean corals. In both extinct and extant corals, they found that branching species

were significantly more likely to have small corallites and small colonies than other

morphologies; massive corals were significantly more likely to have large corallites, large

colonies, and be oviparous; and that plating corals were more likely to have intermediate

sizes of corallites and be viviparous. Also oviparous corals were more likely to be

gonochoric, while viviparous corals were more likely to be hermaphroditic; a relationship

which was independently described by Carlon (1999).

Hughes and Tanner (2000) noted similar characteristic differences between large and

small, massive coral species as did Soong (1993). They found that Montastrea annularis,

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a large massive spawning coral, displayed slower growth, was longer lived, and exhibited

sporadic (seasonal) recruitment; all life history strategies of K-selected organisms.

Conversely, Agaricia agaricites, a small brooding coral, has a shorter lifespan and more

consistent recruitment, under even marginal conditions; both of which were recognized as

ruderal strategies (Knowlton 2001).

Edinger and Risk (1999) proposed the use of a reef classification scheme for

Indonesian corals derived from Grime’s AST model. Their classification scheme

primarily used coral morphology as a means of categorizing Indonesian corals into one of

three adaptive strategies. In their scheme, conservation status of corals, equivalent to

functional groups, were as follows:

Competitive: Non-Acropora and foliose corals

Ruderal: Acropora species

Stress-tolerant: Massive and submassive corals

Edinger and Risk (2000) demonstrated that the conservation status could be predicted

for Indonesian reefs by classifying them according to the relative dominance of these

conservation classes. However, Edinger and Risk (2000) emphasized that their grouping

strategy and conservation classes were designed explicitly for Indonesian coral reefs and

that in other regions the categories should be changed to match regionally appropriate

coral species and conservation goals.

Attributes used for Classification

The scheme I propose, morphology and reproductive mode are the primary traits used

to define functional groups of coral species (Appendix 1). As indicated in Table 3,

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reproductive mode and morphology are the combined traits that indicate a broad suite of

other functional characteristics of reef corals. The functional groups proposed are:

Competitive dominant: Branched oviparous corals,

Competitive-Ruderal: Branched, viviparous corals

Ruderal: Massive, viviparous corals

Competitive – Stress-Tolerant: Massive, oviparous corals,

Stress-Tolerant: Plating, foliose and solitary corals, (only viviparous in the

Caribbean).

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Table 1.03. The ranking of each proposed functional group in ten critical traits, and the adaptive strategy to which they most closely represent. Smaller numbers represent higher rank and greater levels of each attribute. The morphological categories are: B: Branched; M: Massive; P: Plating and Solitary. The reproductive categories are: O:Oviparous; V: Viviparous. The reproductive methods are; F: Fragmentation; X: sexual reproduction. The adaptive strategies are: C: Competitive; CR: Competitive – Ruderal; CS: Competitive – Stress-tolerant: R: Ruderal; S: Stress-tolerant.

Trait BO BV MO MV PV Review Reference

Maximum Size (Genet) 1 3 2 5 4 Johnson et al. 1995

Longevity (Ramet) 3 4 2 5 1 Hughes 1984

Longevity (Genet) 1 2 3 5 4 Highsmith 1987

Reproductive Maturity 5 2 4 1 3 Richmond 1998

Reproductive Effort 4 2 3 1 5 Richmond 1998

Reproductive Method F>X F:X F>X F<X F<X Highsmith 1987

Growth Rate 1 2 3 4 5 Huston 1985b

Stress Response 3 4 2 5 1 Bak and Meesters 1998

Aggression 3 4 5 2 1 Lang 1973

Palatability 3 2 4 1 5 Rotjan and Lewis 2005

Adaptive Strategy C CR CS R S

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Characteristics of Each Functional Group of Coral

Competitive dominant: Branched oviparous corals

In the Caribbean, branched, oviparous corals are represented by Acropora and

Oculina species (Appendix 1; Fadlallah 1983; Harrison et al. 1984; Richmond and

Hunter 1990; Brooke and Young 2003). Corals of these two genera have high growth

rates (Huston 1985b), indeterminate growth (Highsmith 1987) and typically dominate the

surface of most coral reefs (Richmond and Hunter 1990; Brooke and Young 2003).

Sexual reproduction occurs in late summer, the period when both resource availability

and the risk of damage due to hurricanes are most likely, and thus when the risk of

wasting resources via reproduction is offset the most (Woodley et al. 1981). Recruitment

rates are typically very low (Bak and Engel 1979, Rogers et al. 1984, Harrison and

Wallace 1990; Smith 1992, Richmond 1997), which confirms their status as competitive

dominants which allocate resources to growth versus reproduction. These branched

corals fragment easily and can apparently utilize this form of asexual reproduction to

successfully disperse over small distances (Highsmith 1987, Lirman 2000). Their

branched structure allows survival under high sediment loads, although episodic

occurrences of high turbidity may inhibit rapid growth fueled by photosynthesis. Rapid

growth and a tall, branched structure allows these corals to overgrow all other corals

under benign environmental conditions. They are moderately aggressive in direct

interactions with other corals (Lang 1973). While their skeletal structure provides

moderate protection from predation by parrotfish, Acroporids are prone to corallivory by

polychaetes (Woodley et al. 1981) and snails (Baums et al. 2003). The corals of this

functional group should demonstrate low spatial variability among sites at one depth

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within a reef, but high variability across areas of varying water quality (e.g. Lidz and

Shinn 1991 ). Also, sections of the reef tract that receive more frequent or very intense

disturbances, such as areas exposed to the open ocean, should have lower cover of

branched spawning corals compared to less frequently disturbed areas (e.g. Geister 1977;

De Meyer 1998; Parker and Oxenforn 1998).

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Competitive-Ruderal: Branched, viviparous corals

Branched corals of the genera Porites and Madracis, as well as the species Agaricia

tenuifolia utilize a viviparous reproductive strategy (Appendix 1; Morse et al. 1988;

Johnson et al. 1995; Richmond 1998). These corals typically have a digitate, branched, or

morphologically plastic form (Smith 1984; Bruno and Edmunds 1996; Veron 2000) and

can dominate large areas (Lewis and Snelgrove 1990; Chornesky 1991; Aronson et al.

1998). While the colonies can be very large, living tissue often does not connect

neighboring branches (Smith1984; Lewis and Snelgrove 1990; Veron 2000), implying

that branch longevity is much shorter than colony longevity. Branched viviparous corals

release planulae over an extended period of time (Richmond 1997), resulting in relatively

high rates of recruitment (Bak and Engel 1979; Smith 1992). Since they can also disperse

through fragmentation (Highsmith 1987; Bruno and Edmunds 1997), corals of this

functional group are able to take advantage of both asexual and sexual reproduction as a

means of escaping disturbances and spreading across a reef (Bruno and Edmunds 1997).

Branched viviparous corals exhibit weak aggression towards other coral species (Lang

1973). Additionally they are not structurally defended from corallivory, and can suffer

high levels of predation by parrot fish (Murdoch, Looney and Aronson unpublished

document; Grottoli-Everett and Wellington 1997, Miller and Hay 1998). The enhanced

tolerance to disturbance and mix of reproductive strategies should allow branched

viviparous corals to show moderate to high cover and low variability across reefs in

marginal habitats (Aronson et al. 2005) , and low cover in areas where parrotfish or

competitively dominant species are abundant.

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Ruderal: Massive, viviparous corals

Massive (mound-shaped), viviparous corals are found within a broad range of genera,

including Agaricia, Favia, Manicinia and Porites (Appendix 1). Corals of these genera

have smaller colony sizes (than massive, oviparous corals), determinate growth, a short

lifespan, and high reproductive output (Soong and Lang 1992; Soong 1993). These corals

tolerate greater extremes in disturbance than mound-shaped spawners (Sammarco 1985;

Connell 1997), but are not good competitors for space (Lang 1973), and reproduce at a

young age (Richmond 1990). Additionally many massive oviparous corals are capable of

self-fertilization (Brazeau et al. 1998). As they reproduce continually over the year, less

energy is available for growth (Hall and Hughes 1998). These factors indicate a ruderal

lifestyle that is maximally adapted to frequent settlement and rapid growth within patches

of marginal quality generated by disturbance. These corals are likely to be the first to

settle in newly disturbed areas, and indeed may be the only corals present if conditions

are extreme. Like viviparous branched corals, massive viviparous corals also are not well

defended and are subject to high levels of corallivory by parrotfish (Rotjan and Lewis

2005). The corals of this functional group should demonstrate low variability among sites

within reefs, as they have a wide range of environmental tolerance and high recruitment

rates. Mound-like brooding corals should also show low variability from reef to reef, for

the same reasons. As they are neither good competitors nor aggressive, ruderal corals

should be less abundant than competitively dominant species on most reefs.

Competitive – Stress tolerant: Massive oviparous corals

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Massive oviparous corals include species from the genera Montastrea, Diploria,

Colpophylia, as well as additional genera (Appendix 1). Corals that are mound-like and

that spawn gametes generally possess moderate to high growth rates as adult colonies,

indeterminate growth and can reach very large sizes (Soong 1993). As they only

reproduce during part of the year, and generate gametes which need to be fertilized in the

water column, they have moderate to low recruitment success (Smith 1992). Partial

mortality may create large fragments with high survivorship. Massive oviparous corals

are generally sensitive to sedimentation (Nugues and Roberts 2003), although this

weakness may be offset by the corals’ ability to grow rapidly (Logan et al. 1994).

However, their shape and size may aid in the survival of intense disturbances such as

storms and hurricanes (Woodley et al. 1981, Liddell and Olhorst 1987). Massive

oviparous corals have moderately large and plocoid corallites, which protect polyp tissue

from predation by fish such as parrotfish. The corals of the massive oviparous group

probably demonstrate high spatial variability in coral cover from reef to reef, depending

on the water quality of each reef. Reefs in clear oligotrophic ocean water should have a

high cover of large massive oviparous corals, with a large proportion of the population

composed of competitively superior genets. Reefs in turbid or nutrient-rich water should

have a lower cover of these corals, and the ones present should be smaller and more

fragmented. The within-reef variability of this group of corals could be high or low,

depending on the levels and history of disturbance, and age of the reef in question.

Stress Tolerant: Plating, foliose, and solitary corals

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Plating, foliose, and solitary corals, such as species within the genera Agaricia,

Mycetophyllia and Scolymia, have slow growth rates and generally a moderate to small

colony size (Johnson et al. 1995, Veron 2000). They tend to have thick tissue relative to

skeletal thickness (Budd et al. 2006), and thus fragment rarely. However, since they

produce brooded planulae (Johnson et al. 1995; Richmond 1998) which may be capable

of settlement soon after release from the parent, recruits may tend to cluster in

environments for which they have an adaptive advantage. The corals in this group

generally rank high in Lang’s (1973) aggression scale, and often have complex skeletal

structures, such as coarse septal dentition, (Budd et al. 2006) which may prevent

complete tissue loss to polyps by either competition or predation. Stress-tolerant corals

should be very patchily distributed on all scales, since they recruit near to the parent

colony and are susceptible to disturbance and interference competition by most other

types of coral.

Sources of Environmental Stress and Disturbance on Coral Reefs

The four environmental factors that most strongly play a role in determining the

characteristics of a coral assemblage at a reef site are temperature (Weber and White

1974; Glynn and Stewart 1973; Walker et al. 1982)), light (including UV light)

(reviewed in Falkowski et al. 1990), current speed (Geister 1977), and suspended

sediment load (Dodge and Vaisnys 1977; Acevedo et al. 1989; Anthony 1999). All four

of these factors may be considered a source of enhanced growth or as a source of

disturbance to corals, depending on the intensity or rate at which the coral is exposed to

each factor.

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Corals are adapted to a specific range of temperatures, and are negatively affected if

exposed to temperatures that are only 2° above or below this range (Figure 1.06A;

Walker et al. 1982; Glynn 1988). Cold temperature can be viewed as a stress, in that

physiological processes are restricted by low temperatures. Conversely, high

temperatures act as a disturbance by damaging the tissue of the coral host and also

causing the expulsion of the symbiotic zooxanthellae in the process of coral bleaching

(reviewed by Browne 1997).

Corals are also adapted to a specific range of light conditions (Figure 1.06B), with

excessive light causing damage to the both the coral host and also damage or the

expulsion of their symbiotic zooxanthallae (Falkowski et al. 1990; Browne 1997). Since

light is required by zooxanthallae for photosynthesis of carbohydrates, which are made

available to the coral host, low levels of light result in a loss of resources to the coral

colony.

Suspended sediments (Figure 1.06C) negatively affect coral increasing the turbidity of

the water column and there by blocking light transmission (McCarthy et al. 1974),

smothering the coral polyps (Hubbard and Pocock 1972; Rogers 1990), or by abrading

coral tissue (Rogers 1990). Alternatively, suspended sediments may provide nutrition to

corals that are not otherwise available in oligotrophic waters (Anthony 1999; Mills et al.

2004) and corals may be nutrient stressed when both dissolved and particulate sources of

nitrogen are in low concentration.

Waves and other forms of water motion generate currents which affect corals in

different ways depending on their strength (Figure 1.06D). Water motion is required to

carry dissolved and particulate nutrients to the coral (Anthony 1999; Mills et al. 2004)

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and low current speeds result in less nutrient resources being available to the coral colony

due to the development of a boundary current. On the other hand, currents with a high

rate of flow can break corals (Geister 1977; Tunnicliffe 1981) or suspend sediment and

thereby abrade coral tissue (Rogers 1990).

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Figure 1.06. Representation of how varying levels of the four most important environmental factors act to promote growth, or act as a stressor or disturbance agent to corals.

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Testing the Applicability of the Functional Group Approach for Reef Corals

In this dissertation, I test several hypotheses regarding how each different functional

group of reef corals varies across environmental gradients of stress and disturbance. The

specific predictions are as follows:

Similarities in Distribution of Species Between and Among FG

Species within functional groups are hypothesized to be redundant in terms of their

functional responses to the environment. If this is so then species belonging to the same

functional group should differ little in their distributions across sites, due to the shared

responses to environmental and biological conditions (Steneck and Dethier 1994; Gitay

and Noble 1997; Hooper et al. 2002). Conversely, the distribution patterns of species

belonging to the functional groups should be substantially different due to disparate

environmental tolerances. Under the above paradigm, species within environmental

functional groups are hypothesized to be redundant in terms of their functional responses

to the environment. If this is so then species belonging to the same functional group

should differ little in their distributions across sites, due to the shared responses to

environmental and biological conditions (i.e. Figure 1.07C).

If, however, the traits used to distinguish species into functional groups are those

primarily utilized for resource acquisition, and not environmental tolerance, then species

within functional groups should be too similar to be able to persist within the same

habitats (following Gause 1934). Under this scenario species that belong to the same

resource-based functional groups (also termed “guilds”) should tend to occur in different

habitats (reviewed in Fox 1999). Also species from different guilds should be able to

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coexist to a greater degree than species from the same guild. Patterns of species

distributions when grouped into guilds should match the pattern in Figure 1.07D, below.

Conversely, if functional groups do not exist, or if the species within functional

groups do not respond in unison to changes in environmental condition, then a serial

(Figure 1.07A) or nested pattern (Figure 1.07B) of species turnover may occur across

sites. Analysis of species abundance data, species presence-absence across sites, or the

ordination of multidimensional species data for sites can be used to determine which of

the above patterns are exhibits by corals in sites located across environmental gradients.

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Figure 1.07. An illustration of different hypothetical distributions of species and functional groups across an environmental gradient (A to D), and how they appear when graphed as (i) abundances, (ii) tabulated in a matrix of presence vs. absence, and (iii) graphed using a multivariate ordination technique, such as Multidimensional Scaling (MDS). In the second column of figures, columns in the matrix represent sites and rows represent species and functional groups. Filled cells in a row represent the presence of a species and empty cells represent its absence. Each row represents a different hypothetical distribution, as follows:

(A) The pattern of species presence when species and functional groups are replaced in series across an environmental gradient.

(B) An alternate pattern, in which the range of sites inhabited by organisms with lower tolerances are nested within the range of sites occupied by more tolerant species and functional groups.

(C) The distribution pattern in which functional groups exhibit turnover in response to the environmental gradient but species within functional groups coexist and have the same distributions (i.e. FG underdispersion).

(D) A different pattern in which species only compete strongly within functional groups but not between functional groups. Under this scenario species of different functional groups are predicted to co-occur while species within functional groups distribute themselves with turnover across the environmental gradient (i.e. FG overdispersion)

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Rank Abundance by Species and Functional Groups

According to the AST (Grime 1979), species and functional groups should differ in

dominance depending upon the levels of stress and disturbance of the habitat they are in.

Alternately, the unified neutral theory (UNT) suggests (Hubbell 2001) that all coral

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species are functionally equivalent, and the ranking of any species will be random from

site to site, regardless of the environmental conditions of the reef in which it is found. If

the paradigm of UNT is in operation, no species is expected to exhibit greater dominance

when examined across a large number of sites. Conversely, it may be that species differ

in dominance, but that no within-functional group similarities in dominance patterns

exist. This would indicate that each species is different from all other species but that

they do not share functional group affiliation as I previously designated them above. If,

however, species from the same functional group tend to have similar dominance patterns

across transects, this would indicate that functional groups exist and that species within

functional groups tend to be fairly equivocal. In other words the UNT may apply within

FG but not between FG. In Under this model, the pattern of dominance of species would

conform with both the AST and a version of the UNT (Hubbell 2005).

If the predictions of the AST are true, then the corals of the MO (massive oviparous)

functional group should dominate on reefs with high colony density. This is because they

are predicted to use growth to dominate when resources are abundant and levels of

disturbance low. However, since low total colony abundance was shown above to be

highly correlated with W, which I showed above is a proxy for disturbance, and the MO

functional group is predicted to have low growth rates and survivorship when levels of

disturbance or stress are high, it is predicted to not dominate on reefs with low total

colony abundance. Conversely, species of the stress-tolerant and the ruderal functional

groups, which are the foliose and plating functional group and the massive viviparous

functional groups, are predicted to dominate reefs with low total colony density. The

rank abundance of the species from each group will drive the rank abundance of each

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functional group as a whole, and if this is the case then the MO functional group is

predicted to dominate most reefs with the other functional groups occupying a

subordinate position.

Percent Cover of All Corals

The first line in Grime’s (1977) classic paper defines stress and disturbance as

“external factors limiting (plant) biomass”. In this scenario, the level of stress represents

the relative rate of resource availability to organisms within a habitat, and disturbance the

relative rate of resource removal or loss to organisms within a habitat. Habitats

characterized by the presence of more resources (i.e. a high rate of resource gain), and

fewer disturbances (i.e. a lower rate of resource loss), should exhibit more organisms,

higher amounts of biomass or a higher percentage of cover by corals than habitats

exposed to higher levels of disturbance or stress (Figure 1.08).

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Figure 1.08. An illustration of how total assemblage biomass is predicted to vary across habitat types characterized by different levels of resource availability and disturbance.

Percent Cover per Functional Group

According to the AST, each functional group is adapted to survive only within a

specific range of disturbance, stress and competition, representing that functional groups’

environmental and biological niche. If functional groups are affected by the environment

in this manner, each primary functional group (C, ST or R) will dominate one of the three

environmental extremes (see Figure 1.09A below), and also will decline in abundance

rapidly in habitats characterized by other environmental conditions. Also each

intermediate strategy (such as C-R, S-R or C-S) should peak in abundance at a midpoint

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between environmental extremes. The abundance of each functional group is also

expected to display little overlap from HT to HT according to this model.

More recent theoretical and empirical evidence (O’Neill et al. 1988; O’Neill 1989;

Peterson et al 1998; Bolker and Pacala 1999) indicates that the pattern in which each

functional group heavily dominates one area within the AST model may not apply.

Instead all functional groups may be capable of coexistence in almost all habitat types

except the three extreme environments. If the functional groups that are not competitively

dominant utilize either (1) recently cleared patches of high resource availability via

source-sink dynamics (ruderals), or (2) patches of low resource quality (i.e. heavily

shaded; stress-tolerant species), then they could persist in habitats exposed to low

disturbance and high stress, despite the spatial dominance of the competitive group

(Bolker and Pacala 1999). If these adaptive strategies are in effect, then ruderal and

stress-tolerant species may also reach maximum cover in habitats with highest resource

availability, and the overlap between functional groups will be high (Figure 1.09B and C

below).

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Figure 1.09. Diagrams depicting the differing ways in which the abundances of competitive (C), stress-tolerant (S) and ruderal (R) functional groups of corals are predicted to vary across habitats located across the range of stress and disturbance gradients encompassed by the AST model. Each model illustrates a different degree of niche overlap that may plausibly be exhibited by each functional group. In all graphs X and Y represent graphs of abundance relative to levels of disturbance (X) or stress (Y). Z represents the modified CSR square diagram, with the zero net growth intercept (ZNGI) illustrated for each functional group. Graph A matches Grime’s original predictions in which functional groups are limited to specific regions of adaptive niche phase space with no overlap in niche boundaries. Graphs B and C represent alternate models in which competitive species do not negatively interact with stress-tolerant or ruderal species. In graph B the functional groups exhibit minimal overlap in niche boundary, whereas in graph C the functional groups exhibit maximal overlap in niche boundary. In all models C, S an R functional groups maintain dominance under differing environmental conditions.

Regardless of whether the niche model or the competitive hierarchy model is the more

accurate description of reality, and irrespective of the level of overlap between species,

the following predictions can be made:

The competitive group will exhibit it’s highest level of cover at the least disturbed

and least stressed site.

The competitive group will exhibit higher cover than all other groups at the least

disturbed and least stressed site.

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Other functional groups may peak in cover at some moderate level of disturbance

or stress.

All functional groups should display lowest cover at the most disturbed or stress

site.

The C, CS, and S groups should decline in cover more rapidly than R groups

across gradients of disturbance. The S group should decline to minimal levels before the

C group across a disturbance gradient.

C, CR and R groups should decline in cover more rapidly than S groups across

gradients of stress.

Total Species Richness

As previously stated in the Intermediate Disturbance Hypothesis (Grime 1973;

Connell 1978; Sousa 1979; Aronson and Precht 1995; Dial and Roughgarden 1998 and

many more), the number of species found within certain kinds of habitat will be limited

by both environmental conditions and biological interactions. High levels of stress or

disturbance should restrict species richness by limiting the rates of growth or by depleting

populations faster than they can recover (Figure 1.10). Under low levels of stress or

disturbance, species with the best ability to acquire resources and procure territory from

other species will inevitably maintain a competitive advantage. The monopolization of

space by these competitive species will obstruct the settlement and growth of subordinate

species within patches, thus limiting the number of species within habitats that have low

levels of stress and disturbance. For these reasons, in Grime’s Adaptive Strategies model

(1977) a peak in species richness is expected to appear at the location within the model

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where rates of population growth and rates of recovery from disturbance are both at

moderate levels (Figure 1.10).

Figure 1.10. The distribution of species richness predicted to occur across habitats by Grime’s (1977) Adaptive Strategies model. High represents a peak in species richness at the midpoint between resource loss and gain. Low represents areas of reduced species richness due to environmental or biological factors. Circles enclose areas of equal species diversity.

Functional group richness

Functional group richness represents the number of functional groups found within a

particular habitat. While Grime (1977) does not make any explicit predictions about how

functional group richness or diversity varies across his ternary model, he does plot the

general location of different plant groups, such as trees, shrubs and herbs, within the

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ternary diagram (Figure 1.11). In his illustration, the greatest number of plant functional

types occurs at the midpoints of the two axes of resource flux, with fewer plant types

found towards the edges. Unfortunately, Grime (1977) does not provide a theoretical

reason for the pattern he predicts to occur.

Alternatively, Steneck and Dethier (1994) predict that the number of functional

groups will peak across habitat types in the same manner as does total biomass of the

assemblage across the adaptive strategies model (Figure 1.12). Their pattern is based on

the empirical results of their research into the distribution of marine plant functional

groups across tropical and temperate sub-tidal habitats. In their graphical model the most

stress- and disturbance-tolerant species are grouped into one inclusive category, and are

located across all survivable habitat types. Additional functional groups then appear

towards the corner of the square in which resources are not limited and disturbance levels

are low. This pattern directly contradicts the general predictions of the Adaptive

Strategies Model (Grime 1979), where ruderal species are defined as intolerant to stress,

and stress-tolerant species are defined as incapable of persisting under heightened

disturbance. Another problem with the Steneck and Dethier (1994) model is that no

theoretical explanation for their predicted (nested) pattern is provided either.

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Figure 1.11. A diagram illustrating the range of strategies encompasses by (a) annual herbs, (b) biennial herbs, (c) perennial herbs and ferns, (d) trees and shrubs, (e) lichens and (f) bryophytes. For the distribution of strategies within the model see Figure 4. Modified from Grime (1977).

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Figure1.12. A three dimensional model of the levels of biomass predicted for set of functional groups of species across habitat types characterized by varying levels of disturbance potential and productivity potential. Modified from Steneck and Dethier (1996).

As stated above, there are considerable shortcomings with both of the above models.

The prediction of Steneck and Dethier (1994) of a peak in the Competition section of the

ternary model is counter that of Grime (1977), who states that the peak in functional

diversity should occur in habitats experiencing the lowest levels of competition. Neither

theory incorporates a prediction of how the richness or diversity of species within each

functional group will vary across habitat types. Finally, both models lack a theoretical

underpinning. In order to address these issues, in the next paragraph I put forward a

theoretical explanation for how the components of (1) functional group diversity, and (2)

the diversity of species within each functional group will vary across habitats of varying

resource flux, as illustrated in the Adaptive Strategies Model.

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In the restructured model I propose, I define positions within the graphical Adaptive

Strategies Model as habitats, in which each habitat is composed of a patchwork of habitat

types that differ slightly in environmental condition (Figure 1.13; Connell and Keough

1985). Each position within the model defines the upper limit in the rate or amount of

resource flux (gain or loss) within each habitat. In this manner, highly stressed habitats

should only contain a small range of resource availability due to a low rate of resource

gain, disturbed habitats should contain a small range of resource availability due to high

rates of resource loss outpacing resource gain, while benign habitats should possess

patches exhibiting a wide range of resource availability, due to resource gain outpacing

resource loss.. Following this reasoning, stressed or disturbed habitats should be limited

in the range of species and functional groups they can harbor, while benign habitat types

should exhibit the full complement of functional groups. More functional groups are

predicted to survive within benign habitat types despite the dominance of space by

competitive dominants because some patches are likely to exist that possess lower levels

of resource availability or higher levels of disturbance which the competitors cannot

tolerate. Accordingly, functional diversity should peak in the upper left corner of the

model, as it does in the model of Steneck and Dethier (1994), and not as predicted by

Grime (1977). However, in the proposed model, unlike that of Steneck and Dethier

(1994), ruderal functional groups are not predicted to occur within stressed habitats, and

stress-tolerant functional groups are predicted to be absent from habitats subject to high

levels of disturbance. Such a pattern is in accordance with the original Adaptive Strategy

Theory (Grime 1977).

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Figure 1.13. A diagram illustrating how functional groups are predicted to be dispersed across patches located with habitats defined by varying rates of resource gain and loss. Larger squares represent habitats. The smaller nested squares represent patches within habitats. Letters represent the functional group occupying each patch. C represents the competitive functional group. S represents the stress-tolerant group and R represents ruderals. Grey squares represent empty patches. The black field on the lower right side of the diagram represents the range of habitats in which high relative rates of resource loss limit biomass.

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Species richness within functional groups

The differences in life history strategy of each functional group should affect how the

species within each group interact across gradients of stress or disturbance. Competitively

dominant organisms are predicted to compete heavily under benign environmental

conditions, but it may be that competition is only directed towards other members of the

competitive functional group and not members of the other functional groups. Ruderal

species are typically the poorest competitors for space, in both direct contact and

overgrowth competition. Stress-tolerant species are characterized as the strongest

defenders of space, but also recruit to patches that possess low levels of resource that

could potentially reduce their rates of competition substantially. If it is true that

competitive dominant species only compete with each other, then the species richness of

the competitive group should be reduced in habitats where resources are more abundant

and where disturbance levels are low. Under this scenario, the stress-tolerant and ruderal

species would be expected to display highest levels of species richness in low stress and

disturbance patches. Alternately if the species within the competitive functional group

does compete against all other species regardless of life-history, or if species within each

functional group compete strongly with other members of the same group, than all FG

will display a reduction in species as resources increase and disturbance levels decline.

Regardless of the potential differences in competitive interaction between functional

groups, all functional groups are predicted to display a reduction in species richness in

habitats characterized by low resource levels or high disturbance. The species richness of

the competitive dominant and stress-tolerant functional groups should decline faster than

the ruderal group’s species richness as disturbance levels increase, and the species

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richness of the competitive dominant and ruderal functional groups should decline faster

than stress-tolerant functional group’s species richness as resources levels decline across

sites.

Testing the adaptive strategies theory on Caribbean coral reefs

In the chapters to follow, I will examine the ability of the proposed functional group

approach to predict the structure of coral assemblages at sites on reefs located across the

environmental and biological gradients found across the Florida Keys reef tract and the

Bermuda reef platform. In Chapter 2, I test the predictions of the adaptive strategies

model with coral data from reefs in Florida. The Florida data are from deep fore reef

sites located at 13 to 19 m depth. These reefs are characterized by a spur-and-groove

geomorphology and separated by deeper, sandy areas. An earlier investigation

determined that the Florida Reef tract displays distinctive scales of variability in total

coral cover and abundance. Chapters 3 and 4 describe how I collected data from sites

located at multiple aspects (i.e. compass bearing) and depths from patch reefs located at

intervals across the lagoon that is found north of the island of Bermuda. By selecting sites

that vary in depth and distance from shore, the responses of species and functional groups

of coral to two distinct environmental gradients can be examined. In Chapter 5 I

summarize the conclusions of the previous chapters and discuss their implications.

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CHAPTER 2: THE RESPONSES OF FUNCTIONAL GROUPS OF CORALS TO

DIRECT AND INDIRECT GRADIENTS ON THE FLORIDA REEF TRACT

Introduction

In this chapter I examine how functional groups of corals are distributed across a

gradient of disturbance (i.e., along the C-R axis of the AST model; Figure 2.01), over

which the range of the resource (stress) gradient is at a minimum. This was done by

comparing coral assemblages located at a single depth across reef sites known to vary in

water quality. Standardizing the environmental conditions in this way allowed the

examination of the hypothesized competition-colonization trade-off displayed between

competitive and ruderal corals, while limiting the expected range of responses by the

stress-tolerant functional groups.

The 1995 Keyswide Coral Reef Expedition was a multidisciplinary survey of coral reef

habitats located along the entire Florida Reef Tract. The results and mapping these coral

assemblages showed that coral cover, colony abundance and diversity varied among reefs

on deeper forereef habitats (13-19 m depth) (Aronson and Murdoch 1996; Murdoch 1998;

Murdoch and Aronson 1999). Each biological measure (i.e. cover, abundance, diversity)

showed little variability across sites separated by 1 km within reefs, demonstrated high

variability among adjacent reefs separated by less than 10 km, and showed little variability

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across regions sampled at the 50-km scale. Furthermore, focused analysis in the Middle and

Lower Keys regions determined that exposure to inimical water from Florida Bay reaching

the reefs through passes between the keys was a likely source of the high variability in

community structure observed from reef to reef (Murdoch 1998). Florida Bay water does

not flow into the other regions of the Florida Keys where reefs were assessed by Murdoch

(1998), and so only reefs within the Middle and Lower Keys were including in the focused

analysis.

Florida Bay water possesses several characteristics that can limit coral growth or

survival. These characteristics include extreme variability in temperature and salinity,

and high nutrient and sediment loads (Shinn et al. 1989, Szmant and Forrester 1996). To

test the hypothesis that Florida Bay water negatively affected the coral assemblages on

spur-and-groove reefs in the Middle and Lower Keys, the average coral cover, as

surveyed in the Keyswide Coral Reef Expedition (Murdoch and Aronson 1999), was

compared with a dependent variable (W) by Murdoch (1998). The variable W was

derived from (A) the average flow rate of Florida Bay water traveling through individual

passes, which was measured by Smith (1994), divided by (B) the linear distance to the

nearest up-current pass in km, as determined by maritime charts:

W = flow rate (m sec-1) / linear distance from pass to reef (km) (1)

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Figure 2.01. The elongated oval within this square diagram of state space represents the hypothetical range within the AST (CSR) model that was occupied by the sites of the Florida Reef Tract that are the focus of this chapter.

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Visual inspection of the graph and regression analysis of average coral cover at each

site with W (Figure 2.02) indicated that coral cover declined in a linear fashion with an

increase in W (i.e., an increase in flow rates or a decrease in the distance to the nearest

pass). The least squares regression analysis of data describing the change in coral cover

with change in W produced the equation:

Coral cover = 17.381 - 0.2367(W) (2)

The independent variable W (flow rate/distance to pass) explained much of the

variance in coral cover. A t-test determined that the slope of the best-fit line differed

highly significantly from zero [r2 = 0.8318, df = 9; t-ratio = -6.29, p = 0.0002].

The existence of a significant linear relationship between the variable W and coral

cover on the reefs of the Middle and Lower Keys provides support for the conclusion that

there exists a steep gradient of environmental factors in operation across these habitats

(Murdoch 1998), and that these factors vary with the factor W. Direct gradient analysis

can be done to determine how the coral assemblage varies relative to the factor W. As

stated above, investigating the manner in which functional traits and groups of corals

vary in relation to direct (environmental) gradients is most likely to produce powerful

models when done along obvious physical gradients such as the one observed in the

Florida Keys (Hutchinson 1957; Whittaker 1975; McGill et al 2006).

All 20 sites of the Keyswide Coral Reef expedition also varied in percent cover of the

total coral assemblage (hereafter referred to as “total coral cover”; Aronson and Murdoch

1996; Murdoch 1998), ranging from ~1% to ~20%. While the environmental causes of

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Figure 2.02. Relationship between total percent cover of the entire coral assemblage and the measure of environmental disturbance due to island passes, W.

the variability of all 20 reefs is unknown, indirect gradient analysis may be used to test

the hypotheses detailed in Chapter 1 regarding whether the attributes of functional groups

of corals vary changes relative to total coral cover. Since total coral cover represents the

most commonly-used metric for determining the ecological condition of coral reefs, and

because the manner in which the attributes of functional groups of corals vary relative to

total coral cover are as yet unstudied, an investigation of the manner in which functional

traits and groups of corals vary in relation to the indirect (biological) gradient is also

important to determine.

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OBJECTIVESFocusing on the functional groups of corals described in Ch 1, I examined how the

coral composition of 10 separate reefs located within the Middle and Lower Keys regions

changed in relation to the direct environmental gradient defined by the variable W. Only

these 10 reefs were surveyed relative to W as they are the only reefs within proximity to

the passes connecting the reef tract to Florida Bay. In particular, I examined how the (1)

rank-abundance (dominance) of species and functional groups (2) percent cover and

abundance of each functional group, (3) species richness of the total coral assemblage,

(4) functional group richness, and (5) species richness within each separate functional

groups varied across the Middle and Lower Keys reef sites previously shown to vary in

total coral cover in a linear manner relative to the distance from passes and the strength of

the currents flowing through each pass (Murdoch 1998).

I also investigated the relationship between the same five variables and the indirect

gradient of total coral cover on all 20 of the coral reefs surveyed in the Keyswide Coral

Reef Expedition, using model 2 (orthogonal) regression for functional group cover and

model 1 (least squares estimate) regression for all other comparisons. While the

environmental causes of the differences in total assemblage cover for the ten reefs not

included in the analysis of the direct gradient were not experimentally determined, all

twenty reefs were assessed for a couple of reasons. These reasons are: (1) percent cover

data represent a common means of evaluating the ecological condition of coral reefs

(Rogers 1994), and (2) gradient analysis of the 20 sites encompassing the entire Florida

Keys region may uncover patterns in the five independent factors that are not apparent in

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the smaller dataset from the 10 sites in the Middle and Lower Keys sectors. The 20 sites

surveyed were not compared using

Based on the theoretical postulates stated earlier, I predict the following patterns in

the coral assemblage structure of these Floridian reefs:

Similarities in distribution of species between and among FG

Species within functional groups are hypothesized to be redundant in terms of their

functional responses to the environment. If this is so then species belonging to the same

functional group should differ little in their distributions across sites, due to the shared

responses to environmental and biological conditions (Steneck and Dethier 1994; Gitay

and Noble 1997; Hooper et al. 2002). Conversely, the distribution patterns of species

belonging to separate functional groups should be substantially different due to disparate

environmental tolerances. Under the above paradigm, species belonging to the same

functional group should differ little in their distributions across sites, due to the shared

responses to environmental and biological conditions (i.e. Figure 2.03C).

If, however, the traits used to distinguish species into functional groups are those

primarily utilized for resource acquisition, and not environmental tolerance, then species

within functional groups should be too similar in resource requirements to be able to

persist within the same habitats (following Gause 1934). Under this scenario, species that

belong to the same resource-based functional groups (also termed “guilds”) should tend

to occur in different habitats (reviewed in Fox 1999). Also species from different guilds

should be able to coexist to a greater degree than species from the same guild. Patterns of

species distributions of guilds should match the pattern in Figure 2.03D, below.

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Rank abundance by species and functional groups

Examination of the rank-abundance patterns of species and functional groups was

done to test whether species and functional groups differ in dominance, as predicted by

the AST, or alternately, whether all coral species are functionally equivalent, as the

unified neutral theory (UNT) suggests(Hubbell 2001). If the UNT is correct then all

species will appear equally likely to be the most abundance on a transect, regardless of

the environmental conditions of the reef in which it is found, and no species will exhibit

greater dominance.

Alternately, it may be that species differ in dominance, but that no within-functional

group similarities in dominance patterns exist. This would indicate that each species is

different from all other species, but that they do not share functional group affiliation as I

previously designated them in Chapter 1. If, however, species from the same functional

group tend to have similar dominance patterns across transects, this would indicate that

functional groups exist and that species within functional groups tend to be fairly

equivocal. In other words the UNT would apply within FG but not between FG, which is

a pattern which conforms with both the AST and a version of the UNT (Hubbell 2005).

If the predictions of the AST are true, then the corals of the MO (massive oviparous)

functional group should dominate on reefs with high colony density. This is because they

are predicted to use growth to dominate when resources are abundant and levels of

disturbance low. However, since low total colony abundance was shown above to be

highly correlated with W, which I showed above is a proxy for disturbance, and the MO

functional group is predicted to have low growth rates and survivorship when levels of

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disturbance or stress are high, it is predicted to not dominate on reefs with low total

colony abundance. Conversely, species of the stress-tolerant and the ruderal functional

groups, which are the foliose and plating functional group and the massive viviparous

functional groups, are predicted to dominate reefs with low total colony density, although

they should do so under different environmental conditions. The rank abundance of the

species from each group will drive the rank abundance of each functional group as a

whole, and if this is the case then the MO functional group is predicted to dominate most

reefs with the other functional groups occupying a subordinate position.

To test the null hypothesis that no species or functional group ranks higher than the

rest, the counts for each possible rank was tabulated for each species, and separately for

each functional group, across all 200 transects of the 20 sites. Chi-square analysis was

used to determine whether the resultant table possesses a non-random distribution of

ranks across sites for species and for functional groups. Logistic regression was also done

to determine whether the ranks of each functional group varied in a non-random manner

relative to the average coral cover of the 200 sites.

Percent cover and abundance per functional group

The percent cover for the species that make up the most competitive functional group

is predicted to peak on reefs far from passes, where sources of disturbance are most likely

to be low and light levels likely to be highest, or on reefs with maximum levels of total

coral cover. If different functional groups compete with each other then the cover of

stress-tolerant and disturbance-tolerant species is predicted to peak on reefs at moderate

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distances from passes where levels of stress and disturbance are at moderately high levels

and where competitively dominant species are in relatively low abundance (Figs. 1.08A).

Alternatively, if functional groups do not compete with each other to a significant

degree, then the cover of all functional groups should peak in habitats within which

resources are highest and sources of disturbance are low (Figs. 1.08B,C). Under this

scenario, the competitive-dominant group is still predicted to have higher biomass on the

reefs farthest from passes than all other functional groups. The competitive and stress-

tolerant functional groups of coral (i.e., MO and FP) are also predicted to have a more

limited range of distribution across the disturbance gradient (W) than the disturbance-

tolerant functional groups of coral (i.e., Branched, Viviparous [BV] and Massive,

Viviparous [MV] corals). Additionally, if the AST model is correct, the competitive

dominant functional group should exhibit significantly higher percent cover on reefs with

low disturbance and stress than the other groups, while the stress-tolerant and

disturbance-tolerant functional groups should exhibit significantly lower percent cover,

regardless of which habitats they dominate. If the predictions of the unified neutral

theory (UNT) are correct all functional groups will be equivocal and will show no

significant differences in distribution or in abundance or biomass proxy (i.e., percent

cover) within or across reef sites.

These predictions, as well as those following, were tested using both linear and

second-order polynomial regressions. Linear regression were done to determine whether

functional groups increased or decreased in percent across the gradients. Second-order

polynomial regressions were done to determine whether the percent cover of each

functional group peaked at a midpoint along the gradient.

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Species richness of all corals

Since depth was held constant among sites but turbidity most likely varied with

distance from passes, the amount of resources available as light and as suspended

particulate matter reaching each reef surface, as well as the level of sedimentation stress,

likely varied with distance from passes as well (Shinn et al. 1989). The relative levels of

stress and disturbance therefore probably vary with site location. According to the

predictions of the productivity-diversity hypothesis, which lead to CSR theory (Grime

1973; 1979), and which is also known as the intermediate disturbance hypothesis

(Connell 1978; Aronson and Precht 1994; Huston 1994; and many more), the habitat

types with intermediate levels of stress and disturbance should display greater species

richness than either the habitats with low levels of stress or disturbance and the habitats

with high levels of stress or disturbance.

Functional group richness

Grime (1977) predicts that the richness of functional groups will be low across sites,

as each functional group is replaced by another due to the combined effects of

environmental filtering and competitive exclusion between functional groups (Figure

1.08). Alternatively, if competition does not operate between FG, then all functional

groups are predicted to occur on reefs characterized by the lowest values of W (or highest

total cover), and functional group richness will decline as disturbance levels increase

(Figure 1.08), with the distribution of less-tolerant functional groups nested within more-

tolerant functional groups. If the UNT is correct, then functional groups do not exist and

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the all species have an equal chance of being found at any site regardless of position

across the direct or indirect gradients.

Species richness per functional group

If the predictions of Grime (1977) are correct, then the number of competitive species

(i.e., those in the MO functional group) should peak on reefs in Florida that are

characterized by low levels of W or high levels of total coral cover, and decline steeply as

W increases or total coral cover increases. The number of ruderal and stress-tolerant

species should peak at moderate levels of disturbance, due to both environmental and

biological constraints. Accordingly there should be a turnover between functional groups

across the direct and indirect gradients (Figure 1.08).

If competition only operates between species within functional groups, however, then

the species richness of all functional groups should peak at moderate levels of W or total

coral cover, with the less tolerant functional group nested within the distribution of the

more tolerant functional groups. This unimodal pattern would occur within FG because

of the effects of competitive exclusion due to limiting similarities occurring between the

functionally similar species within FG at low levels of disturbance, and environmental

constraints limiting species membership within FG at high levels of disturbance (Figure

1.08).

METHODOLOGY

Geographic setting

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The Florida Reef Tract lies at the southern tip of Florida and seaward of the Florida

Keys and is the third largest barrier reef in the world. The reefs and surrounding

mangroves, seagrass meadows and forested islands form a large, interconnected

ecosystem that sustains abundant wildlife, both above and below the sea surface (Florida

Keys National Marine Sanctuary Management Plan 1995). The ecological condition of

the Florida Reef Tract has been an issue of heightened national focus as coral cover and

diversity have declined substantially in recent decades (Jaap et al. 1988; Murdoch and

Aronson 1999; Miller et al. 2002; Aronson et al 2003; Wheaton et al. 2003).

The Florida Reef Tract is 350 km long and extends from Biscayne Bay at its

northeastern most end to the Dry Tortugas islands at its western most end (Figure 2.03).

A regional feature with a strong influence on the corals of the Florida reef tract is Florida

Bay. Florida Bay is a large, shallow body of water with limited circulation that lies to the

north and west of the Florida Keys. The water enclosed within Florida Bay is subject to

extremes of temperature, salinity, turbidity, and nutrient content (Vaughan 1918, Shinn et

al. 1989, Szmant & Forrester 1996). This water is forced by tides and winds onto the

Florida reef tract through the tidal passes in the Middle Keys (Wang et al. 1994, Smith

1994, 1997). Reef development is poor near the passes, probably because of the effects

of the water from Florida Bay on corals and other reef organisms (Shinn et al. 1989,

Ginsburg and Shinn 1994).

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Figure 2.03. Map of South Florida and the Florida Keys. The reef tract is seaward of

Hawk Channel and forms a linear barrier reef roughly 350-km in length.

The ten reef sites included in the direct gradient analysis are lettered E

through N. All 20 of the reef sites are included in the indirect gradient

analysis.

Data collection and analysis

Videographic and species presence-absence data were collected during three research

cruises conducted over 26 days during August, September and October, 1995. The reef

tract was surveyed at twenty deeper habitats (13–19 m depth), which were chosen a

priori and located from Biscayne Bay to the Dry Tortugas. Subsequent to in situ

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assessments, sixteen of the reef sites were defined as spur-and-groove habitats and four

sites as hard-ground communities. Almost all of the sites were positioned along the reef

slopes of named, emergent reefs The names of these reefs were retained as designations

for the survey sites (Figure 2.03).

Reef ridges are frequently present offshore of the emergent reefs along the Florida

Reef Tract (Lidz et al. 1991a, 1991b, 1997). These “outlier” reefs may protect the reefs

that are landward of them from storm-driven waves and other oceanographic influences.

The rule of the Keyswide research team was to sample the seaward-most section of reef

that was at the correct depth, not necessarily corresponding to the area directly downslope

from the emergent reef. For this reason, some of the reefs sampled were downslope

outlier reefs.

Transects were videographed and analyzed following the methodology described in

Aronson et al. (1994). One or two divers stretched 25-m long waterproof tape measures

down the middle of ten haphazardly selected spurs. Transects were generally 3–10 m

apart and the area videographically surveyed encompassed approximately 25m x 100m of

reef. Care was taken to avoid placing the transect lines over sand or off the ends of spurs.

Once each transect line was in place, another diver slowly swam down its length,

videotaping a 0.4 m wide x 25 m long swath of the reef. Videography was accomplished

with a Hi-8 video camera that was enclosed in a underwater housing and equipped with a

wide-angle lens and two 50 W waterproof lights. A 40 cm stainless steel rod projected

forward from the camera housing. This rod was used as a guide so the diver could

maintain a set distance of 40 cm between the camera lens and the reef surface. On the

end of this rod, a 15-cm wide gray plastic bar was mounted such that it appeared in the

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field of view of the camera. The plastic bar served as a scale in the videotaped images.

During filming the underwater video camera was held perpendicular to the overall slope

of the reef, with the end of the stainless-steel rod suspended less than 2 cm from the reef

surface. This camera position ensured that the videographed images were of the reef in

plan view.

In order to accurately assess biological richness data on Caribbean coral reefs such as

those in the current study, Aronson et al. (1994) determined (using species saturation

curves) that more transects are required in comparison to the number of transects needed

to obtain accurate percent cover data. These additional transects are needed in order to

account for rare, widely dispersed species. Coral species presence data, for use in the

determination of species and functional group richness per reef site, were collected in the

present study from the 10 videographed transects as well as an additional 10 transects

surveyed visually, following the procedure in Aronson et al. (1994). The visually

assessed transects were placed in the same manner as the videographic transects, and

continued over an area of roughly equal size. The richness data therefore was collected

over twice the area of reef as the coral cover data.

The video transects were analyzed in the laboratory with a Hi-8 videocassette recorder

(VCR) attached to a high-resolution color monitor. Each transect was divided into 50

regularly spaced, non-overlapping frames, displayed by pausing the VCR. One of ten

clear plastic sheets, marked with ten random points, was laid over the monitor screen and

the sessile organism or substrate type present under each point identified and recorded

manually. The video was then advanced to the next frame and a new sheet of dots

haphazardly selected. This method is the more primitive predecessor of the computer-

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automated method described in Chapter 4, but which results in identical data. By

following this protocol, each transect yielded 500 data points. Estimated percent cover of

coral species, other biological groups such as sponges and gorgonians, and of different

types of substrate was calculated from the point count data from the ten transects for each

reef site. The abundance of colonies for each species was also assessed from the video

data. Counts of colonies were made for each species on each transect, and the results

from the ten transects per site used to calculate the average abundance per species per

site.

The total species or functional group richness at each site was determined by

summing all species present within both the ten videographic transects and ten additional

transects of equal dimension that were assessed visually while diving the survey site,

following the standard protocol (Aronson et al. 1994). Functional group richness was

calculated using four increasingly-stringent procedures. (i) The least-stringent method

allowed a functional group to be recorded as present at a site if only one colony of any

member species was observed on all 20 transects. Three increasingly stringent conditions

for the indication of presence of a functional group on a reef were calculated by recording

member species of functional groups as present at a site when recorded over more than

(ii) 5, (iii) 10, and (iv) 15 transects. Increasing the number of transects that the member

species had to occur before the functional group was counted had the effect of

increasingly filtering out the less ubiquitous or transient species that were present at a

site.

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Statistical analysis

Similarities in distribution of species between and among FG

Species that are grouped according to shared environmental tolerances should tend to

co-occur in habitats, while species that share resource requirements should tend displace

others from habitats. In order to examine the degree of similarity in the distribution of

species species within and between functional groups, I calculated an Analysis of

Similarity (ANOSIM; Table 2.01) on the raw colony count data of the 11 most abundant

species across the 200 transects. Bray Curtis similarities between square-root

transformed abundance data for all species were calculated and similarity trees and non-

metric multidimensional-scaled diagrams produced for visually comparison against the

hypothetical patterns illustrated in Figure 1.08.

To test the null hypothesis that no species or functional group ranks higher than the

rest, the counts for each possible rank was tabulated for each species, and separately for

each functional group, across all 200 transects of the 20 sites. Chi-square analysis was

used to determine whether the resultant table possesses a non-random distribution of

ranks across sites for species and for functional groups. Logistic regression was used to

determine whether the rank of each functional group changed in a non-random manner

relative to the total percent coral cover of each site.

The predictions of the remaining hypotheses described in Chapter 1 and above were

tested using regression analysis. For the tests of (1) percent cover of each functional

group, (2) total species richness, (3) functional group richness and (4) species richness

within functional groups against the predicted responses to both the environmental

gradient W and the biological gradient in total coral cover, the correlative relationships

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between the variables were examined by computing linear and second-order polynomial

regressions. Orthogonal (Model 2) regression was used for comparing functional group

cover with total coral cover, since both variables were derived from the same data, and

thus had error variances of similar extent (Sokal and Rohlf 1995). Least squares

estimates (Model 1) regression was done for all other variables. All second-order

relationships were predicted to be concave-downward, in accordance with the hypotheses

of the intermediate disturbance hypothesis (Grime 1973; Connell 1978; Huston 1994).

Departures of linear regression coefficients from zero, and determinations of whether

second-order coefficients for polynomial regressions were significantly different from

zero, were done using one-tailed t-tests.

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RESULTS

Similarity in distribution of species within and between functional groups.

Species within functional groups were hypothesized to be redundant in terms of their

functional responses to the environment (Grime 1979; Steneck and Dethier 1994). In

order to examine the degree of similarity in the functional responses of species within and

between functional groups, I calculated an Analysis of Similarity ANOSIM; Table 2.03)

on the raw colony count data of the 11 most abundant species across the 200 transects.

Bray Curtis similarities between each square-root transformed abundance data for species

were calculated and similarity trees and non-metric multidimensional-scaled diagrams

produced for visually comparison. (Figs. 2.04, 2.05).

The five of the six species of the MV functional group were more similar to each

other in multidimensional distributional space than they were to corals from the other

functional groups (Figure 2.05). The one exception was Stephanocoenia intercepta,

which was also the least abundant member of the MO functional group. The species of

the MV functional group also were more similar to each other in the patterns of

abundance they exhibited across the 200 reefs than to species of the other two functional

groups, with the exception of the one MO coral described above. The species of the BV

functional group were dissimilar to each other and to all 9 other species in the

comparison.

ANOSIM analysis (Table 2..01) determined that the MV and BV functional groups

were both significantly different from the MO in the manner in which the abundances

were distributed across the 200 survey sites. The MV and BV functional groups were not

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found to differ significantly in their distribution pattern, although the failure to detect

significant differences may have been due to a type II error caused by the small number

of possible permutations that could be run with the data.

Bray-Curtis similarities were also calculated for all 36 species evaluated in the rank-

abundance comparisons. The many rare species appeared to display neutral patterns of

distribution across sites. Visual assessment of the MDS diagram (Fig. 2.06) confirms that

the rare species did not display any coherent patterns of similarity between each other. In

particular, the member species of the FP group were found to have low similarity values

among each other (i.e., less than 20 out of 100). The other species that displayed neutral

rank-abundances across the Florida reef sites also were not similar in distribution to

neither the rare nor the abundant species.

ANOSIM of the entire suite of species determined that the overall pattern of

abundance exhibited by the FP group was highly significantly different from that of the

MO functional group (p = 0.007; Table 2.02). All other comparisons were not

significant, except for the statistical comparison between the very abundant MO

functional group and the very scarce BV functional group.

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Figure 2.04. A dendrogram showing the similarities in response patterns among the

eleven most abundant species assessed in Florida. Bray Curtis distances

were calculated based on square-root transformed coral colony counts.

Species were clustered using the group-linkage method..

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Figure 2.05. MDS showing the similarities in response patterns among the eleven most

abundant species assessed in Florida in two-dimensional state space.

Species that are closer together and bound within similarity isoclines are

more alike than species farther apart or outside isoclines. Bray Curtis

distances were calculated based on square-root transformed coral colony

counts. Species were clustered using the group-linkage method.

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Table 2.01 Results of one-way analysis of similarity of the Bray-Curtis similarities of the

abundance data of the most abundant 11 species observed across 20 reef sites

located on the Florida Reef Tract.

ANOSIM

Analysis of Similarities

Global Test

Sample statistic (Global R): 0.734

Significance level of sample statistic: 0.1%

Number of permutations: 999 (Random sample from 4620)

Number of permuted statistics greater than or equal to Global R: 0

Pairwise Tests

R Significance Possible Actual Number >=

Groups Statistic Level % Permutations Permutations Observed

MV, MO 0.66 2.4 84 84 2MV, BV 0.5 10.0 10 10 1MO, BV 0.875 3.6 28 28 1

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Figure 2.06. MDS showing the similarities in response patterns among all 36 species

assessed in Florida in two-dimensional state space. Species that are closer

together and bound within similarity isoclines are distributed across sites in

a more similar manner than species farther apart or outside isoclines. Bray

Curtis distances were calculated based on square-root transformed coral

colony counts. Species were clustered using the group-linkage method.

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Table 2.02. Results of one-way analysis of similarity of the Bray-Curtis similarities of

the abundance data of all species observed across 20 reef sites located on the

Florida Reef Tract

ANOSIM

Analysis of Similarities

Global Test

Sample statistic (Global R): 0.073

Significance level of sample statistic: 13.5%

Number of permutations: 999 (Random sample from a large number)

Number of permuted statistics greater than or equal to Global R: 134

Pairwise Tests

R Significance Possible Actual Number >=

Groups Statistic Level % Permutations Permutations Observed

BO, MV 0.563 7.1 28 28 2

BO, FP 0.141 21.8 55 55 12

BO, MO 0.646 3.0 66 66 2

BO, BV -0.010 60.7 28 28 17

BO, X -1.000 100.0 3 3 3

MV, FP -0.033 60.7 5005 999 606

MV, MO 0.066 22.8 8008 999 227

MV, BV 0.022 37.9 462 462 175

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MV, X -0.333 71.4 7 7 5

FP, MO 0.178 0.7 92378 999 6

FP, BV -0.078 78.4 5005 999 783

FP, X -0.525 100.0 10 10 10

MO, BV 0.096 17.3 8008 999 172

MO, X -0.178 45.5 11 11 5

BV, X -0.556 100.0 7 7 7

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Rank Abundance per Species

The six most abundant coral species out of the 34 species analyzed belonged to the

massive oviparous functional group (Figure 2.07; Table 2.03). Out of the 8097 coral

colonies that were counted across the 200 transects, 6330 colonies were accounted for by

these six species, which represents over 78% of all the colonies observed. The

probability that the six most abundant species observed would all belong to the MO

functional group (out of the four groups sampled) by chance, is highly significantly

small, at p = 3.61E-5.

The next three most abundant species were all of the massive viviparous functional

group, which were classified as ruderal corals. Represented by 831 colonies, these three

species accounted for approximately 10% of all coral colonies counted. The next two

most abundant species also members of a separate single functional group. These two

species were both branched viviparous corals (competitive-ruderal classification), and

accounted for ~4% of all colonies counted across the Florida Reef Tract, with 328

colonies total. The other 27 observed coral species accounted for less than 100 colonies

each across all transects.

The ranks of the most common eleven species across all transects examined

individually were also distributed in a highly non-random fashion (Table 2.04; Figs 2.07,

2.08). Most transects had an average of 11 total species, of these the three top-ranking

species tended to be consistently most abundant across most transects. The next three

species rarely ranked below sixth on most transects. The three massive viviparous corals,

which ranked seventh through ninth overall, were rarely in the top two ranks, but also

rarely ranked below ninth. All species of the foliose and plating functional group ranked

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equally as subordinate in rank, as were 4 out of 6 species of the branched viviparous

functional group. A chi-square test of the distribution of all species in proportional ranks

from 1 to 11 out of 34 possible rankings total was found to be very highly significantly

different from the null, at p = 7.8E-192.

Figure 2.07 (below). The log percent relative abundance of the species observed at the

200 transects assessed. Different shaped points represent the

different functional group memberships of the species.

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Table 2.03. (below) A table of the number of occurrences with which each the 36

most abundant species ranked from 1 to 20 across all 200 transects. The designations of

rank are displayed along the top row of the table. For example, the species M. faveolata

ranked first on 79 transects, second on 35 transects, and so on. Darker-shaded cells

represent a greater number of occurrences. A chi-squared test determined that the

probability of the observed distribution of rank abundances occurred at random is

exceptionally significantly small, at p = 5.22E-148.

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Figure 2.08. The distribution of the proportion of ranks over the 200 sites that the most

dominant species, Montastrea faveolata, displayed. The distribution of the

proportion of ranks if all corals shared dominance, as predicted by the UNT,

is also plotted for comparison. The null, or neutral distribution was

calculated for each rank by dividing the sum of all occurrences each species

by the number of occurrences of all species, and then multiplying the result

by the number of occurrences for the rank in question.

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Rank Abundance per Functional Group

Since the highest-ranking 11 species were found to be most similar in dominance to

other species within the same functional group, I also analyzed the rank-abundance

distribution of each functional group across the 200 transects (Figure 2.09; Table 2.04).

The massive oviparous functional group, classified as competitive-stress-tolerant, was

found to rank highest (i.e., first) in dominance in 182 of the 200 transects. The massive

viviparous functional group, classified as ruderal, ranked second compared to the other

three functional groups. The BV functional group most often ranked third, and FP

functional was most often fourth ranking in abundance across all sites.

The ranks of each functional group were plotted against their total abundance value of

each transect. This comparison was conducted to determine if the competitive - stress-

tolerant functional group (i.e., MO) was consistently dominate even on transects

regardless of low colony abundance. Colony abundance was also shown to be highly

negatively correlated with proximity to passes (Murdoch 1998) and thus is a good proxy

for stress or disturbance. I also examined whether functional groups of corals

hypothesized to be disturbance-or stress-tolerant would increase in dominance rank

within these marginal transects (Figure 2.10).

The MO functional group ranked first on reefs with more than 25 colonies. The MO

group was subordinate on 18 reefs, all with low coral abundance. Conversely, the other

three functional groups rarely or never ranked first in abundance except when total coral

abundance was less than 25 colonies. Logistic regression of the rank data compared to

total coral abundance for sites found that the patterns displayed by each functional group

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were highly significant at p values of < 0.001. The model formulae and significance

tests are presented in Appendix 2.01.

Figure 2.09. The proportion of ranks displayed by each functional group across the 200

transects surveyed. The pattern is exceptionally significantly different from

a neutral distribution, at p = 1.56E-173 (Table 2).

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Table 2.04. A table of the observed number of times each functional group ranked from

1 to 4 across the 200 transects surveyed. Also tabulated is the expected

distribution of ranks under the UNT, as well as the chi-squared test

comparing the differences between the two matrices. The observed pattern

of rank abundances was found to be exceptional significantly different from

the expected null model, at p = 1.56E-173.

Figure 2.10. (below) The relationship between rank per functional group and total

abundance per transect for the 200 transects surveyed. Logistic regression

analysis and tests of significant of the data are presented in Appendix 2.01.

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Percent coral cover of each functional group versus W

Functional groups did not appear to replace each other across the gradient of W

(Figure 2.11), and instead demonstrated a nested distribution pattern as the intensity of W

varied. All species peaked in cover at lowest values of W and declined in cover on reefs

with higher W values. Only the MS functional group displayed high levels of cover at

low levels of W, whereas all other functional groups of corals accounted for low cover

across all reefs, as predicted by the CSR theory.

The BV functional group did not vary significantly with W (Table 2.05; Figure 2.11a).

Coral cover by the branched brooding corals was very low at all sites, and ranged from

0.09% to 1.93%.

The foliose and plating, brooding functional group of corals also displayed very low

percent coral cover across all sites surveyed, with a range of 0.13% to 1.51%. Despite

the low cover overall, however, this functional group did display a highly significant

negative correlation with W (Table 2.05; Figure 2.11b).

The cover of the MV functional group of corals displayed little variation relative to W,

and ranged from 0.80% to 2.40% (Figure 2.12c). The coral cover of the MV group did

not vary significantly with W (Table 2.05; Figure 2.11c).

Percent coral cover of the MO functional group ranged from 0.76 to 12.09% (Figure

2.12d). Coral cover for the MO group was highly-significantly correlated with W and

formed a negative slope (Table 2.05; Figure 2.11d), indicating that massive corals that

spawn gametes are more abundant on reefs far from island passes.

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Figure 2.11. Relationship between percent coral cover of each functional group and

environmental influence of island passes, (W). The best fit linear (–) and

second-order polynomial (- -) relationships are written in the lower left-hand

corner of each graph.

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Table 2.05. Results of two-way t-test of the linear correlation between coral cover of

each functional group and W on 10 reef sites along the Florida Reef Tract,

testing whether the slopes are zero.

FG Estimate Standard Error

t Ratio Prob > |t|

BO 0.0014052 0.003028 0.4600 0.6550BV -0.009157 0.012911 -0.7100 0.4983FP -0.19733 0.005124 -3.8500 0.0049MV -0.018454 0.010043 -1.8400 0.1035MO -0.190742 0.025143 -7.5900 < 0.001

Percent cover per functional group versus total coral cover

When percent cover of each functional group was regressed against total cover of all

corals, only the MO functional group displayed an substantial change with cover across

sites, with a range from 0.1% to 18.7% over the 20 sites surveyed (Figs. 2.12, 2.13).

Alternatively, the BV, MV and FP functional groups each only displayed low coral cover

(between zero and less than 2.5% cover) across the same 20 sites (Figs. 2.13, 2.14).

The BV functional group displayed a significant increase in cover relative to total

coral cover (Table 2.06; Figs. 2.12a, 2.13a), while the FP, MO and MV functional groups

increased highly significantly with total coral cover across the 20 sites (Table 2.07, Figs

2.12b-d, 2.13b-d). Only the MV functional group displayed a significant second-order

polynomial regression with total coral cover, with a concave-down regression curve

(Table 2.07, Figs 2.12c, 2.13c).

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Figure 2.12. Orthogonal relationship between average percent coral cover for each

functional group and the total coral cover for the 20 reef sites surveyed on

the Keyswide Coral Reef Expedition. The orthogonal fit linear (–) and

second-order polynomial (- -) relationships are written in the lower left-

hand corner of each graph. The thick diagonal line represents the maximum

possible value of cover for each functional group relative to total coral

cover.

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Figure 2.13. The same graphs illustrating the relationship between average percent coral

cover for each functional group and the total coral cover for the 20 reef sites

surveyed as in Figure 2.12, but with different scales on the y-axes. The best

fit linear (–) and second-order polynomial (- -) relationships are written in

the lower left-hand corner of each graph. The thick diagonal line represents

the maximum possible value of cover for each functional group relative to

total coral cover.

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Table 2.06. Results of orthogonal contrasts on whether the linear regressions of percent

coral cover for each functional group versus total coral cover at each reef site

were significantly different from zero.

FG Variance

Ratio

Correlation Prob.

BV 0.0077 0.4961 <0.05

FP 0.0006 0.8478 <0.005

MV 0.0104 0.6635 < 0.005

MO 0.7803 0.9894 < 0.0001

Table 2.07. Results of two-way t-tests on whether the second-order coefficients for

polynomial regressions of FG cover versus total coral cover were

significantly different from zero.

FG Estimate Std Error t Ratio Prob>|t|

BV 0.002915 0.002915 -1.21 0.2444

FP 0.0002887 0.000496 0.58 0.5683

MV -0.006665 0.002531 -2.63 <0.0001

MO 0.0087727 0.004555 1.93 0.071

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Total species richness versus W

A second-order polynomial regression between species richness and W was concave

downward and highly significant (r2 = 0.727919, t ratio = -3.16, p = 0.016; Figure 3.14).

A linear relationship between species richness and W was negative and marginally

insignificant (r2 = 0.3404, t ratio = -2.03, p = 0.077; Figure 2.14).

Figure 2.14. Relationship between species richness of all corals and environmental

influence of island passes, W, at each reef site. The best fit linear (–) and

second-order polynomial (- -) relationships are written in the lower left-hand

corner of the graph.

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Total species richness versus total coral cover

Species richness ranged from a low of 20 species to a high of 34 species out of a total

number of 36 observed across all sites. A second-order polynomial regression between

the total number of species per site and the total coral cover per site was concave

downward and very highly significant (r2 = 0.7863, t ratio = -6.32, p < 0.001; Figure

2.15). A linear regression of the same data was also significant [r2 = 0.284602; t ratio =

2.68; p = 0.0154]. However, a plot of the residuals demonstrated that the two variables

were not well represented by a linear relationship. In the plot of residuals, all but one

point out of 12 between 4% and 15% cover were above the best fit linear line, and all

points outside the 4% to 15% range were below the best fit line, indicating the data did

not fit the assumptions of linear regression (Sokal and Rohlf 1995).

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Figure 2.15. Relationship between species richness and total coral cover across the 20

reef sites. The best fit linear (–) and second-order polynomial (- -)

relationships are written in the lower left-hand corner of each graph.

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Functional group richness versus W

Functional group richness appeared to vary depending on both the intensity of the

environmental gradient W and the degree of sparseness to which species were distributed

across sites (Tables 2.08, 2.09; Figure 2.16). When species observed across any one of

the twenty transects per site were included, the number of functional groups observed

across the 10 survey sites was 4 of 4, regardless of the value of W (Figure 2.16).

However, as the constraints regarding how many transects a species must be distributed

over before being counted (i.e., how ubiquitously distributed a species was) increased, a

consistent pattern could be seen (Table 2.10) in which first the species within the FP

functional group became increasingly sparse, then the species of the BV functional group,

and finally the species of the MO functional group , Functional groups tended to lose

ubiquitous species on reefs with high values of W , and so functional group richness

declined as W increased.

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Table 2.08. Results of orthogonal contrasts on the linear regressions of functional group

richness for each level of constraint versus W.

Term Estimate Std Error t Ratio Prob>|t|

Five -0.011 0.005 -2.14 0.065

Ten -0.007 0.010 -0.76 0.469

Fifteen -0.035 0.012 -2.91 0.020

Table 2.09. Results of orthogonal contrasts on the second-order coefficients for

polynomial regressions of functional group richness for each level of

constraint versus W.

Term Estimate Std Error t Ratio Prob>|t|

Five -0.00059 0.0001 -3.94 0.006

Ten -0.00027 0.001 -0.55 0.600

Fifteen -0.00083 0.001 -1.59 0.160

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Figure 2.16. Relationships between functional group richness under the four levels of

membership constraint and the environmental gradient of W across reef

sites. The best fit linear (–) and second-order polynomial (- -) relationships

are written in the lower left-hand corner of each graph. The rules for

inclusion of functional groups in each graph were as follows:

ALL = At least one species per FG on one transect or more.

Five = At least one species per FG on more than five transects.

Ten – At least one species per FG on more than ten transects.

Fifteen = At least one species per FG on more than fifteen transects.

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Table 2.10. Presence or absence matrices of the presence or absence of functional groups

across the ten reefs of the environmental gradient W. The rules for inclusion

of functional groups are as in Figure 2.18, above.

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Functional group richness versus total coral cover

Functional group richness declined as a function of increasing the constraints on

presence in a reef site and as when total coral cover were at the highest and lowest values

(Tables 2.11, 2.12; Figure 2.17). When the constraint of membership was relaxed,

functional group richness was four out of four across the 20 reef sites (Figure 2.17). As

the statistical constraints that filtered out sparse species within functional groups were

increased functional groups decline in presence on reefs in the order of FP, then BV, the

MO, while the MV functional group was observed on all reefs regardless of constraints

on detection.

As sparsely distributed species were filtered out of the data, FG richness took on a

unimodal distribution. At highest levels of total coral cover the FP and BV functional

groups were not present, while at the lowest levels of total coral cover the FP, BV and

MO functional groups were absent. These results indicate that the species of the FP

functional group were distributed most sparsely among transects between reefs overall,

and more so on reefs characterized by high and low coral cover. The BV functional

group displayed a similar pattern, but was less sparsely distributed across sites. The MO

functional group only displayed absences on two reefs that had low total coral cover. The

MV functional group was ubiquitous across all sites regardless of total coral cover.

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Figure 2.17. Regression of functional group richness versus total coral cover for each

site. Each graph represents a different level of membership constraint,

labeled as in Figure 2.18 above. The best fit linear (–) and second-order

polynomial (- -) relationships are written in the lower left-hand corner of the

graph.

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Table 2.11. Results of orthogonal contrasts on the linear regressions of functional group

richness for each level of constraint versus W.

Term Estimate Std Error t Ratio Prob>|t|

Five 0.0390 0.0190 2.05 0.0548

Ten 0.0586 0.0277 2.12 0.0485

Fifteen 0.0567 0.0305 1.86 0.0791

Table 2.12. Results of orthogonal contrasts on the second-order coefficients for

polynomial regressions of functional group richness for each level of

constraint versus W.

Term Estimate Std Error t Ratio Prob>|t|

Five -0.0052 0.0029 -1.79 0.0909

Ten -0.0143 0.0030 -4.75 0.0002

Fifteen -0.0145 0.0036 -3.98 0.0010

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Species richness within functional groups versus W

In contrast to percent cover for each functional group, in which one functional group

dominated in cover, all groups demonstrated high species richness across sites relative to

the strength of the environmental gradient of W (Figure 2.18). W was poorly correlated

with species richness within each functional group. The BV and FP functional groups

appeared to vary little in species richness except at the highest level of W. The MV and

MO functional groups displayed little change in species richness across the entire

environmental gradient.

The species richness of the branched, viviparous, functional group ranged from 3 to 6

species per site out of a maximum of 7 species (Figure 2.18a). Species richness for the

BV functional group was negatively correlated with W, but not significantly so (Table

2.13). A second-order polynomial regression of BV species richness on W was concave

downward but was also not significant (Table 2.14).

Species richness of FP functional group range across the 10 sites assessed, ranged

from between 5 and 10 species, out of a possible 10 species observed regionally (Figure

2.18b). A linear regression of FP species richness functional group on W was not

significant (Table 2.13), but a second-order polynomial regression between species

richness and W was significant and concave-downwards (Table 2.14; Figure 2.18b).

Neither the species richness of the MV functional group nor that of the and MO

functional group were not correlated significantly with W (Table 2.13). Additionally,

second-order polynomial regressions of species richness on W for both groups appeared

little different from the linear regression, and were also not significant (Table 2.14,

Figure 2.18c,d). The species richness of the MV functional group varied between 5 and 8

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species (Figure 2.18c), while the MO functional group displayed a range from 8 to 10

species across the sites surveyed (Figure 2.18d).

Figure 2.18 . Relationship between species richness of each functional group and

environmental influence of island passes, W, at each reef site. The best fit

linear (–) and second-order polynomial (- -) relationships are written in the

lower left-hand corner of each graph.

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Table 2.13. Results of analyses of variance of the linear regression of species richness

versus W for each functional group.

FG Estimate Std Error t Ratio Prob>|t|

BV -0.0305 0.0173 -1.77 0.1155

FP -0.0508 0.0257 -1.98 0.0836

MV 0.0080 0.0175 0.46 0.6591

MO -0.0266 0.0145 -1.84 0.1034

Table 2.14. Results of two-way t-tests on whether the second-order coefficients for

polynomial regressions for species richness of each functional group versus

W were significantly different from zero.

FG Estimate Std Error t Ratio Prob>|t|

BV -0.0014 0.0007 -1.94 0.0939

FP -0.0026 0.0008 -3.01 0.0195

MV 0.0002 0.0008 0.19 0.8515

MO -0.0003 0.0007 -0.47 0.6554

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Species richness within functional groups versus total coral cover

Of 36 species observed across all 20 sites, six were branched viviparous corals, ten

were foliose or plating, viviparous corals, ten species were assigned to the MO functional

group and nine species were characterized by a massive morphology and a viviparous

reproductive mode. Across the 20 sites surveyed (Figure 2.19), the BV functional group

displayed a minimum value of 2 species and a maximum of six species. The FP

functional group ranged from three species to ten species. The massive oviparous

functional group displayed a maximum of ten species and a minimum of seven species,

while the massive oviparous functional group ranged from five to nine species across the

20 sites surveyed.

The species richness of the branched viviparous functional group displayed a

concave-down, highly significant second-order polynomial correlation when compared

against total coral cover (Table 2.16, Figure 2.19a). A linear regression of the same data

was not significant (Table 2.15).

A second-order polynomial regression of the species richness of the FP functional

group was also highly significantly correlated with total coral cover, and also displayed a

concave-down curve (Table 2.16, Figure 2.19b). When the FP functional group data was

divided between sites with coral cover values less than 10% and values greater than 10%

in a post-hoc analysis, it was subsequently found that species richness of the FP group

was linearly negatively correlated with total coral cover at a very high significance level

(Table 2.15, Figure 2.19b). In contrast, the species richness of the FP group was not

correlated with total coral cover at sites with coral cover values great than 10% (Table

2.16, Figure 2.19b).

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In comparison with the BV and FP functional groups, the species richness of the MO

functional group remained at roughly 8 species across all sites, with no significant change

regardless of total coral cover (Table 2.15, Figure 2.19c). The species richness of the

massive viviparous functional group also remained high across all reefs and was found to

slightly increase in relation with total coral cover. However, linear regression analysis

determined that the MO functional group exhibited a marginally insignificant correlation

with total coral cover (Table 2.16, Figure 2.19d). The second-order polynomial

regression of the species richness for both the MO and MV functional groups versus total

coral cover per site was not significant (Table 2.16).

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Figure 2.19. Regressions of species richness for each functional group on total coral

cover for each site. The best fit linear (–) and second-order polynomial

(-  -) relationships are written in the lower left-hand corner of each graph.

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Table 2.15. Results of two-way t-tests of the linear regression of species richness for

each functional group versus total coral cover for each functional group.

FG Estimate Std Error t Ratio Prob>|t|

BV 0.0336813 0.052473 0.64 0.5290

FPa 0.6828664 0.111125 6.15 <.0001

FPb -0.001081 0.050731 -0.02 0.9838

MV -0.02411 0.035353 -0.68 0.5039

MO 0.0590496 0.030219 1.95 0.0664

Table 2.16. Results of two-way t-tests on whether the second-order coefficients for

polynomial regressions of FG species richness versus total coral assemblage

cover were significantly different from zero.

FG Estimate Std Error t Ratio Prob>|t|

BV -0.02798 0.005511 -5.08 <.0001

FP -0.032122 0.006295 -5.1 <.0001

MV -0.008554 0.005512 -1.55 0.1391

MO -0.001785 0.005016 -0.36 0.7263

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Analysis of the presence or absence of each species across all sites in a sorted matrix

displayed the manner in which the species of each functional group responded to the

environmental differences that occurred across the 20 reef sites (Table 2.17). All species

included in the BV functional group were present at sites possessing moderate total coral

cover, but that functional group lost species on reefs that had the highest and lowest

percent coral cover values. The species Madracis decactis and Porites furcata were

present on all sites, whereas Porites divaricata and Madracis mirabilis were absent from

reefs with both exceptionally high and exceptionally low coral cover.

The FP functional group displayed a linear decline in species richness on reefs with

less than 10% coral cover. Visual analysis of a sorted matrix of the FP functional group

data illustrates this decline. All of the 10 FP species are present on at least some of the

reefs possessing 10% cover or more, but species are lost progressively across sites with

lower cover values. Only Eusmilia fastigata was found at all 20 sites, whereas Mussa

angulosa, Mycetophylia lamarkiana, My. ferox, My. danaana were absent from virtually

all reefs with less than 5% cover.

In contrast to the BV and FP functional groups, the species of the MO functional

group are present across all sites regardless of coral cover according to visual

examination of a sorted matrix of this group. Only the shallow-water species

Montastraea annularis is rare across all sites.

Examination of a sorted data matrix of the MV functional group illustrates that the

species of this group vary little in presence or absence across all sites regardless of total

coral cover. One notable exception is Favia fragum, which is present at sites with a total

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coral cover below 10%, but not present at sites with a total coral cover above 10%.

Isophllastrea rigida and Isophyllia sinuosa are absent from almost all sites.

Table 2.17. (below) Sorted matrices of species presence or absence for each functional

group across 20 transects at each of the 20 sites of the Keyswide Coral Reef

Expedition. White cells represent absent species, grey cells represent present

species. The heavy black line running across each matrix represents the

predicted boundary between present and absent species if the perfect

nestedness of sorted species had occurred at each reef site. Species absent

below the bordered cells are expected to be present, and species present above

the bordered cells are predicted to be absent. Notice that the pattern of

bordered cells across sites in the table matches the pattern of points in the

graphs of species richness per functional group versus total coral cover

(Figure 2.19). MDP values represent the mid-point location of each species

across the gradient of reef sites, calculated by reciprocal averaging of the sites

of occurrence of each species.

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DISCUSSION

Functional groups of corals were observed to respond to direct and indirect gradients

of disturbance in a manner that substantiates the premise that each group of species

allocate different functional responses to environmental and biological conditions on a

reef. Despite the chaotic patterns in biomass displayed by each coral species when

separately plotted across reefs (Figure 1.01), each functional group of corals responded to

the direct and indirect gradients in a orderly and group-specific manner. The gradient

replacement pattern predicted by Grime (1977), in which each functional group

dominated a particular region of the gradients, was not observed. Instead, functional

groups displayed a nested distribution pattern, indicating that if negative interactions

occur between functional groups they have little impact on distribution patterns. Instead

coexistence strategies of some form may be operating between functional groups or

functional groups have such different life-history strategies that they rarely interact. The

ecological significance of each statistical test is discussed below.

Dominance by species and functional groups

Examination of patterns of rank abundance determined that on the reefs considered in

this analysis, eleven species out of a pool of at least 36 species were substantially more

abundant than the rest (Figure 2.05). These species belonged to three different functional

groups and the species members of each group both (1) sorted by rank in a similar

manner and were (2) distributed across the 200 transects surveyed in a statistically similar

way across multivariate state space (Figs 2.10, 2.11, 2.12). The rarer species, alternately,

showed rank-abundances (Figure 2.05) and multivariate distributions across transects

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(Figure 2.12) that were without apparent pattern. These results indicate that all coral

species are not equivalent in their functional responses. These results alone refute one of

the fundamental hypotheses of the UNT (Hubbell 1997, 2001) that all species of coral are

functionally identical and can be modeled accordingly. By ignoring the shape of the

rank-abundance curve, which is statistically similar to many other curves (McGill 2006),

I instead focused on manner in which each species was ranked across transects, while

taking into account its functional characteristics and the manner in which each species

and functional group was predicted to display abundance patterns across gradients of

disturbance and stress. This species-specific and functional-group specific analysis

uncovered exceptionally non-neutral distributions of rank by the 11 dominant species

within the habitat. Furthermore, species of corals that shared life-history and other

characteristics were distributed across transects in statistically similar patterns to other

members of the same functional group, confirming that functional groups are composed

of functionally (and statistically) similar species that all differ substantially in functional

responses when compared with the responses of the member species of other functional

groups.

The functional-group differences in rank-abundance were also highly non-random

(Table 2.02; Figs 2.08, 2.09). Furthermore, the relative levels of dominance by each

functional group in relationship to the total colony abundance of the set of 200 transects

fit the predictions of the AST, based on the life-history strategies that each functional

group possesses. For instance, the functional group that was predicted to be the

competitive dominate in the Florida reef habitat was the massive, oviparous functional

group, which is made up of corals with a domal morphology, generally large colony size

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and a seasonal reproductive pattern. Theoretically another functional group, the branched

oviparous corals such as Acropora cervicornis would be considered more likely to

dominate reefs in good condition in Florida, but the members of this functional group

were ecologically removed by disease and coral bleaching (Aronson and Precht 1998).

With the BV functional group no longer ecologically important on the Florida reefs the

MO functional group are the fastest growing as adults and the most capable of allocating

resources for growth and domination of benign reef environments. The MO functional

group consistently ranked highest of the four functional groups across each of the 200

transects assessed.(Figure 2.08), except when the total colony abundance of a transect

was below 25 colonies per transect (Figure 2.09). These transects with low total colony

abundance were shown in Murdoch (1998) to represent heavily disturbed areas of reef.

High levels of disturbance would lead to colony damage that would likely outpace the

ability of the MO corals to acquire new resources for repair. The more weedy or more

stress-tolerant corals of the BV, MV and FP functional groups are theoretically better

suited to habitats exposed to higher levels of stress or disturbance, and the results above

did determine that these three groups each ranked highest in dominance only on the

transects with total colony abundance below 25 colonies per transect (Figure 2.09).

Other patterns of rank abundance also matched the predictions of the AST. The FP

functional group is characterized as stress-tolerant in the functional group framework I

developed in Chapter 1. Stress-tolerant species are predicted to have slow growth rates,

low rates of reproduction and to rarely fragment. For these reasons, colony abundance of

the FP functional group was expected to be ranked lower than that of the other functional

groups, a priori. Examination of the rank-abundances of each species and of the FP

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functional group as a whole both confirmed that this functional group was consistently

lowest ranking in abundance on the vast majority of transects.

Unlike the FP functional group, the species of the MV functional group have a ruderal

life-history. These corals primarily utilize resources for reproduction and have higher

levels of recruitment than other types of corals. Although they also are poor competitors

for space, high levels of recruitment may permit the MV functional group to maintain a

secondary dominance on most reefs of high total colony abundance. On reefs with low

colony abundance the MV corals would be freed from competition with the MO

functional group, which may also allow the MV functional group to dominate these

habitats.

Percent coral cover per functional group

Grime (1977) predicted that different functional groups of sessile organisms would

dominate (in terms of biomass) specific zones of a disturbance gradient, due to: (1) their

distinct environmental tolerances limiting membership as disturbance levels increase

across sites; and (2) negative biological interactions between groups inhibiting

membership as disturbance decreases across sites (Figure 2.03a). Alternatively, if

functional groups are primarily affected by environmental conditions alone and do not

compete with each other, then an alternative pattern was hypothesized, in which the

ranges of the least environmentally-tolerant functional groups are nested within the

ranges across the environmental gradient of the more tolerant functional group. Linear

and second-order polynomial regression analysis of functional group percent cover (used

as a proxy for biomass by coral ecologists) and functional group richness across both a

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direct environmental gradient and an indirect biological gradient demonstrated that, on

the deeper spur-and groove fore reefs in the Florida Keys, coral functional groups

conform to the nested pattern with high overlap (i.e., Figure 2.03c) and not the

replacement pattern (Figure 1.03d).

The MO functional group, which is composed of large, broadcast-spawning head

corals, exhibited the highest cover at the least disturbed site in the direct gradient and

indirect gradient analysis. Additionally the MO functional group was consistently the

dominant functional group across all sites except at the individual sites where the

environmental measure of disturbance (W) was highest, or total coral cover was lowest.

Since the branched, oviparous corals are ecologically extinct from the Florida Keys

region (Precht and Aronson 2004), the massive oviparous corals represent the most

competitive coral group remaining. As such, the dominance of the MO group fits the

predictions of the AST model (Grime 1979).

Other functional groups of corals were predicted by the AST (Grime 1979) to peak in

biomass at some moderate position across the direct and indirect gradients. However,

only the MB functional group displayed a significant (p < 0.001) unimodal distribution,

which was observed in the indirect gradient analysis. The BV functional group did also

exhibit higher values in cover at moderate total coral cover and a downward facing

second-order polynomial relationship, but the polynomial section of the equation was not

significantly different from zero (Table 2.05). The best fit second-order polynomial

relationship of the FP and MO functional groups did not differ visually from the best fit

line of the linear regression for each functional groups. Additionally, while all functional

groups displayed significant linear relationships with total coral cover, only the FP and

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MO functional groups displayed a significant linear relationship with W. As such, the

distribution of the MO functional group across the direct and indirect gradients, and its

biomass dominance across reefs, fits the predictions of the AST model (Grime 1979).

The Ruderal and Competitive Ruderal functional groups of corals were predicted by

the AST (Grime 1979) to peak in biomass at some moderate position across the direct

and indirect gradients. For Caribbean corals, these adaptive strategies are represented by

the massive, viviparous corals and the branching, viviparous corals, respectively. The

MB functional group did display a significant (p < 0.001) unimodal distribution in

percent coral cover across the indirect gradient analysis. The BV functional group did

also exhibit higher values in cover at moderate total coral cover and a downward facing

second-order polynomial relationship, but the polynomial section of the equation was not

significantly different from zero (Table 2.05).

Another prediction of the AST (Grime 1979) was that all functional groups will

display lowest percent cover at highest levels of disturbance. This prediction was also

observed in the analysis of the direct gradient (Figure 2.04; Table 2.01).

Total species richness

According to both the IDH (Connell 1978; Huston 1994) and the AST (Grime 1979) a

peak in species richness is expected to appear at a location across either direct or indirect

gradients where rates of population growth and rates of recovery from disturbance are

both at moderate levels (Figure 2.16; 2.17). Total species richness was found to have a

highly significant unimodal relationship with W, and a very highly significant unimodal

relationship with total coral cover. Linear regression across the direct environmental

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gradient was not significantly different from a flat line. For species richness data

measured across a gradient of coral cover, examination of the residual plot determined

that linear regression, although significant, was not an appropriate model. It is interesting

to note that even at very low values of total coral cover, the species richness of a site was

greater than 20 species, which could be considered very high for the Florida region at this

depth, (Dustan and Halas 1987; Porter and Meier 1992; Aronson et al 1994). This high

species richness despite low coral cover is probably due to the inclusion of rare and

sparsely distributed species over the relatively large area (~200 m2) surveyed for species

at each site. It is worth noting here that the IDH as a theoretical model is specifically

intended to explain species richness and diversity at the patch scale, and that at regional

scales a linear relationship between biomass and species richness would be expected

(Chase and Leibold 2002). The results presented here demonstrate that the IDH also

applies at the meso-scale on the Florida Reef Tract.( i.e., between reefs separated by ~ 10

km across the 350-km long region), despite the large area encompassed.

Functional group richness.

Species belonging to all four functional groups were found on every reef site surveyed

in Florida, regardless of the position of reefs along either the direct or indirect gradients

of disturbance. As such, coral assemblage structure did not match neither the Gradient

Replacement pattern predicted by Grime (1977) nor the Nestedness pattern predicted by

Patterson (1987) at the level of functional groups. The lack of turnover of functional

groups across the reef sites indicates that at least one species within each functional group

is capable of surviving on all of the reefs surveyed. Sites that were not spur-and-groove

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reef were not considered in the analysis. The exclusion of marginal reef habitat no doubt

limited the degree of extreme environmental conditions encompassed by the gradient

analysis. Additional research that includes reef and non-reef habitats would be required

to examine whether environmental conditions can limit functional group presence on the

Florida Keys reefs.

Species richness within functional groups

Some species displayed a limited range of reefs across which they were present within

all functional groups. Meanwhile, other species within both functional groups were

present across all sites in both gradients. The nested pattern was most strongly displayed

by species within the FP functional group, with highest richness found in low disturbance

reefs and a linear decline in richness as total coral cover declined. The pattern exhibited

by the FP species was expected, as the FP functional group possesses a stress-tolerant

adaptive strategy that was predicted to be most affected by increased levels of

disturbance.

The species of the BV functional group also displayed a nested distribution pattern,

except in this case the peak in richness was found at a mid-point on the indirect gradient

and the same species were absent from both ends of the gradient. This pattern indicated

that some species within the BV functional group are tolerant of a wide range of

environmental conditions while others are not. Alternately it could be that environmental

conditions limited recruitment or colony survival at one end of the gradient and

competition or predation limited membership at the other end of the gradient (Menge and

Sutherland 1987). Examination of recruitment densities, partial mortality, competitive

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interactions and indicators of predation, such as fish bites, would be required to

determine the cause of the unimodal pattern exhibited by the BV functional group.

Some functional groups displayed significant changes in species richness across the

indirect gradient of total coral cover across the 20 reef sites, however. Both the BV and

FP functional groups displayed significantly fewer species on reefs characterized by low

coral cover. The foliose, plating and solitary corals of the FP functional group possess

many traits that promote the tolerance of stress, which Grime (1977) predicted would

restrict their ability to persist under conditions of high disturbance. Examination of the

sorted matrix of FP species shows that the four species most affected negatively by the

indirect gradient are Mycetophyllia lamarikiana, Mussa angulos, My. ferox and My.

danaana. These corals all possess larger polyps, thicker tissue and are the most

aggressive of the FP functional group (Budd et al. 2001; Lang 1972). The sensitivity of

the FP species, especially species from the Mycetophyllia genus, to disturbance indicates

that these K-selected and typically rare species may be most susceptible to degraded

water quality from Florida Bay.

The branched, viviparous corals that were excluded from reefs with low coral cover

include Porites divaricata, Madracis mirabilis and Madracis formosa. The same species

were also absent on reefs with the highest levels of total coral cover. These corals

possessed the smallest polyps and thinnest branches of the species within the BV

functional group (Budd et al. 2001). This pattern indicated that some species within the

BV functional group are tolerant of a wide range of environmental conditions while

others are not. Alternately it could be that environmental conditions limited recruitment

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or colony survival at one end of the gradient and competition or predation limited

membership at the other end of the gradient (Menge and Sutherland 1987). Examination

of recruitment densities, partial mortality, competitive interactions and indicators of

predation, such as fish bites, would be required to determine the cause of the unimodal

pattern exhibited by the BV functional group.

Both the MV and MO functional groups displayed very little change in species

richness across reefs, regardless of total coral cover. It was predicted that corals of the

MV functional group would be more tolerant of disturbance than species from other

functional groups, since the MV corals exhibit high levels of recruitment and a smaller

overall colony size, as described in Ch. 1, above. One or two species from the MO and

MV group did display a reduced range of sites across which they were found.

In the MV group Montastrea annularis was only found at four reef sites out of the 20

included in the analysis of the indirect gradient. M. annularis is known to dominate

shallow water habitats. It is probable that the limited distribution displayed by this

species on the deeper forereef was due to these sites being outside the range of its

environmental tolerance.

Three species were found to have a limited distribution across the indirect gradient of

20 reefs. Isophyllastrea rigida was only found at one site, while Isophylia sinuosa was

observed at six reef sites. The rarity of both species implies that the environmental

conditions of the deeper forereef sites are also outside the tolerances that they are adapted

too. The response of the MV coral Favia fragum is particularly worthy of note; it was

only found in sites with low total coral cover and not in sites with high total cover, and

had the lowest midpoint value of all corals regardless of functional group membership

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(Table 2.08). It may be that F. fragum selectively recruits to habitats characterized by

high disturbance, or that it is particularly susceptible to competitive exclusion by more

aggressive species.

The species richness of the MO functional group did decline as total coral cover

decreased, but the relationship was marginally insignificant. Perhaps the large scale at

which the surveys were taken allowed for the inclusion of less-disturbed microhabitats

which allowed for the persistence of this functional group. Alternately, the classification

of the MO functional group as Competitive–Stress-tolerant may need to be revised.

However, since coral cover of this functional group greatly exceeded that of all other

groups, it does conform to the competitive dominant strategy as proposed by Grime

(1977) in other ways.

CONCLUSIONS

In the introductory chapter I described how, when graphed, the percent cover data for

all corals surveyed (redrawn as Figure 2.20 below) on the Keyswide Coral Reef

Expedition produced a chaotic pattern in which each species appears to vary

independently. I used the confusing graph to demonstrate the need for techniques with

which to organize and simplify species-level data so that they can be interpreted in an

ecologically meaningful manner.

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Figure 2.20. Percent cover for each of the 38 species recorded on the 20 reefs surveyed

on the Keyswide Coral Reef Expedition.

The functional group framework that I developed in Chapter 1 was tested in this

chapter using data collected from the same corals as in the above example. described in

Chapter 1. As such we should now be able to re-organize the species data that produced

the chaotic graph above into functional groups, and expect to see meaningful pattern

where, in the figure above, there is none.

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Figure 2.21. Functional group cover for each of the four predominant functional groups

recorded on the 20 reefs surveyed on the Keyswide Coral Reef Expedition.

As can be seen in Figure 2.21, the functional group framework provides a means for

interpreting the species data in a more ecologically meaning way. The MO functional

group, which dominates reefs with low levels of disturbance, can be seen to peak on reefs

opposite the islands of the Florida Keys. On reefs near passes through the islands,

however, the percent cover of the MO functional group declines dramatically.

The other three functional groups are not predicted to be as abundant or to produce as

much biomass as the MO functional group, and we can see that they remain at low

overall cover even on the reefs on which the MO functional group can accumulate high

levels of biomass. Figure 2.21 also indicates that since the species of the MO functional

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group are the predominant provider of coral cover in the Florida keys, management

action should focus on protecting these species or promoting their recovery. The other

functional groups are less affected by disturbance and stress than the MO functional

group, however, and it may be advantageous to determine what life-history strategies

allow these more tolerant corals to persist in the face of stress or disturbance so that all

coral species may be better protected from environmental change.

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CHAPTER 3. THE GEOGRAPHY AND ENVIRONMENTAL CHARACTERISTICS

OF THE NORTH LAGOON OF BERMUDA

INTRODUCTION

Bermuda, a United Kingdom Overseas Territory, is located on a 5560-hectare chain of

limestone islands located in the North Atlantic near 32oN 64oW (Figure 3.01). Although

Bermuda is north of the tropics, prevailing warm oceanic conditions support a limited

number of small mangrove forests, extensive seagrass beds and well-developed coral

reefs. The Bermuda reef platform encompasses a wide range of habitat types, from

small, enclosed bays and harbors to the broad lagoon, all of which are encircled by a

well-developed rim reef and large, exposed fore-reef zones. Bermuda is host to a reduced

suite of species relative to more southern reefs of the Caribbean, with only 22 species of

shallow-water hard coral recorded (Appendix 2.01; Sterrer 1998). The relatively small

number of local species aids in the search for biota - environment linkages, by reducing

the complexity of the coral assemblage. Additionally, there exists a library of climatic

and oceanographic data on Bermuda’s marine environment that dates back many decades

(Bermuda Weather Service; Bermuda Institute of Ocean Sciences [formerly the Bermuda

Biological Station for Research, Inc.]).

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It appears that acroporid corals were not present in Bermuda over the past several

hundred thousand years (Garrett et al. 1971). Repeated transplant experiments carried out

in the early 1970s at a site on the northern rim reef confirmed that acroporid corals are

currently prevented from establishment on Bermuda reefs by cold winter temperatures

(R. N. Ginsburg and E. A. Shinn personal communication). Consequently, unlike most of

Figure 3.01. A photomosaic map of the Bermuda Islands and surrounding reef platform.

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the western Atlantic (Aronson and Precht 2001), Bermuda’s reefs were not affected

by the loss of staghorn and elkhorn corals that occurred in the 1980s to early 1990s.

Instead, in most places the reef community appears to have changed little in the past 30

years when compared to the rest of the Caribbean, despite continued perturbation from

overfishing (Butler et al. 1993), ship groundings (Smith 1992), sedimentation (Dodge and

Vaisnys 1977), land reclamation (Flood et al. 2006), coral bleaching and coral disease

(Cook et al. 1990). Coral cover in Bermuda averages 50–90% on the terrace reef (Logan

1988), 20–26% at rim reef sites (Dodge et al. 1982, CARICOMP 1997; Murdoch et al.

unpublished data), 17% (with a range of 10–45%) on patch reefs (Dodge et al. 1982,

Garrett et al. 1971; Murdoch et al. unpublished data) and 13% inside the breaker line on

the South shore (Garrett et al. 1971; Murdoch et al. unpublished data).

Study Area

The area under study is centrally located within the north lagoon, and is bounded at

the southern extent by the north shore of the main island of Bermuda (Figure 3.02).

Roughly 1-km seaward of the shore runs the South Ships Channel, which is ~100-m

wide, 10–13 m deep, and which starts seaward of the island of St. Georges, at the east

end, and continues westward to Grassy Bay, where it branches and continues to three

locations. One branch of the channel extends to connect to the Royal Naval Dockyard,

while the other branch continues through the Great Sound and there splits again, with one

secondary channel continuing on to the anchorages on either side of Morgan’s Point and

the other secondary channel turning eastward and terminating at the docks in Hamilton

Harbour.

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Platform margin (fore) reefs and lagoonal reefs have been historically classified into

several different types, with some of the nomenclature specific to Bermuda (Figure 3.02;

Appendix A; Garrett et al. 1971; Logan 1988; Logan and Thomas 1992). Within the

lagoon, pinnacle reefs are characteristically steep-sided patch reefs measuring 10–150 m

in width and 6–20 m in height, and are typically found in the outer lagoon. Ring-shaped

patch reefs that are 50-m to 500-m wide are known as “mini-atolls”. Mini-atolls typically

have a raised rim of coral and algae encircling a sediment-filled mini-lagoon containing

only scattered coral knobs. When mini-atolls extend beyond 500 m in width they are

referred to as “faro” reefs (Stoddart and Scoffin 1979; Logan 1988). In Bermuda faro

reefs generally exhibit large central areas of shallow (~4-m depth) sandy seabed peppered

with very sparse coral knobs, fringed by a ~10-m wide ridge of well-developed coral reef

and surrounded by much deeper water (10 - 20-m depth).

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Figure 3.02. (below) An illustrated map of the islands and surrounding lagoonal patch

reefs of Bermuda, with important geographic features labeled (produced by

the author). The islands of Bermuda are clustered in a fishhook-like shape

on the southeast side of the atoll. The reef platform extends 15 km to the

northwest of the island. The rim reef reaches to within 2 m of the sea

surface and encloses the north lagoon and the tens of thousands of patch and

pinnacle reefs therein. The fore reef surrounds the island and platform and

extends down to a continuous field of loose rubble rhodoliths that rings the

platform at roughly 100-m depth. Below this field, the sides of the extinct

volcano on which Bermuda rests continue down without coral growth to the

Bermuda Rise, over 4000-m deep.

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The study area is characterized by several large clusters of patch, pinnacle and faro

reefs that extend across the north lagoon (Figure 3.02). Baileys Flat (or Flats), which

form the eastern boundary of the study area, are a string of well-developed patch reefs

that runs in a roughly linear fashion for 9 km, from just offshore of Bailey’s Bay out to a

large shallow faro reef called The Crescent. A similar congregation of patch reefs, known

as Brackish Pond Flats, is found near the western edge of the study area. Brackish Pond

Flats extend in a north-south direction from Spanish Point out towards Devils Flats.

Brackish Pond Flats lies about 5 km west of Bailey’s Flats. Both of these linear reef

systems are thought to have formed on the tops of topographic highs that were once

aeolian dunes (windblown sand) formed during glacial periods, when sea levels were up

to 100-m lower than at present and the Bermuda platform was subaerially exposed

(Garrett and Scoffin 1977).

Connecting the northern end of the two reef flats is a network of faro reefs called

White Flats and The Crescent. These reefs possibly grew on top of massive wash-over

sand deposits that were created by the storm erosion of sand islands that are hypothesized

to have been in place along the northeast rim during the last rise in sea level, roughly

6000 years ago (Garrett and Scoffin 1977). Within the basin bound by Baileys Flats,

Brackish Pond Flats and White Flats are found scattered patch reefs. These patch reefs

tend to reach to very close to the surface and are generally conical in shape.

Seaward of White Flats and The Crescent lies a natural channel that is ~20-m deep,

and through which runs the North Ships Channel. Northward of the shipping channel are

located several lobe-shaped faro-reef formations, 1–2 km in length and up to 1-km in

width, and which also are hypothesized to have formed on top of wash-over deposits

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(Garrett et al, 1971). There is currently >20 m of coral accretion on top of the Pleistocene

deposits, which grew after submersion 6-8 thousand years ago (ka) (Garrett et al, 1971;

Garrett and Scoffin 1977). Many flat-topped pinnacle reefs, each roughly 50–100 m in

diameter, are scattered between the faros in this area. The faro reefs extend in a

northwesterly direction to adjoin at the landward side of a section of the rim reef locally

known as the Ledge Flats. Seaward of the rim lies the reef terrace, forereef, and then the

volcanic slope of the Bermuda seamount which continues down to the abyssal depths.

Eastward of Baileys Flat is a large expanse of flat sandy seabed at 13 m depth and

with no coral reefs, known as Murray’s Anchorage. Westward of Brackish Pond Flats is

the entrance to the Great Sound, and the western side of the North Shipping Channel, as

well as Dockyard. Further to the west continues the lagoon, across which are scattered

other reef flats and clusters of patch reefs.

All surveys were carried out within the study area extending from land out to the rim

reef across the middle of the North Lagoon. The study area was partitioned into six zones

representing different distances from shore (Figure 3.07). Sites were not surveyed on the

rim or fore reef as these areas are an ecologically and hydrographically a different kind of

habitat. The forereef habitat is exposed to oceanic water over at least half of the tidal

cycle and receives the full brunt of storm waves. In contrast, lagoonal waters are retained

on the platform for 4.2 days and have higher loads of suspended sediment, a greater range

of temperature and lower levels of nitrogen than offshore oceanic waters (see Morris et

al. 1977). In addition, lagoonal reefs are protected from the full strength of oceanic waves

emanating from the N, E and W quarters by the encircling rim reef, and from waves

originating from the S by the islands of Bermuda. Furthermore, the rim and fore-reef

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habitats are all interconnected and form one large ring-shaped reef, while the patch and

faro reefs are often separated from neighbors by expanses of relatively deep water and

sediment-covered basins.

Below I review the previously published information regarding the distributions of

marine environmental factors or reef corals across habitats in Bermuda. Subsequently I

describe three separate projects in which I quantified different aspects of the study area

for which information was lacking previously. In Project 1, I describe how the coral reefs

located within the study area was mapped into a Geographic Information System

application (Project 1). In Project 2 I describe the results of an effort to quantify light

availability across the study area. Project 3 details the results of an analysis that

determined how light varied in intensity over a range of depths and when measured

originating from different directions.

Previous research into the distribution of corals across the North Lagoon

The coral reefs of Bermuda have been the focus of interest for geologists and

biologists for over 100 years (Heilprin 1889; Agassiz 1895; Verrill 1902). Recent

research has focused on reefs within Castle Harbour (Dodge et al. 1982; Smith 1999;

Flood et al. 2006; Jones et al. 2007), along the nearshore zones off North Shore (Smith et

al. 1998; Jones et al. 2007), within the central lagoon at Three-Hill Shoals and Crescent

Reef (e.g. Logan 1988; Smith et al. 2003; Jones et al. 2007), and on the northern and

southern forereef terrace (Cook et al 1996; Jones et al. 2007). These previous surveys

found that coral cover across the study area of the current project increases with distance

from shore, with reefs near North Shore having the lowest cover (10-15 percent coral

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cover; Figure 3.02), lagoonal reefs at Crescent and Three Hill Shoals having higher cover

(25-35 percent coral cover), and forereefs in the area around North Rock having the

highest coral cover (35-45 percent coral cover; Jones et al. 2007). Nearshore sites were

hypothesized to have lower cover due to the water quality of the area limiting growth and

survivorship. Water quality was hypothesized to be poor nearshore due to the proximity

to the reefs to areas of high population density and to the southern shipping channel,

which is a source of increased sediment suspension (Jones et al. 2007).

However, prior to the research project described in this dissertation, no data existed

for the patch reefs at intermediate locations between North Shore and the Crescent and

Three-Hill Shoals area. Also, only two lagoonal patch reefs in the zone just shoreward of

the platform rim have ever been assessed. These two reefs were surveyed in the early

1970s (Garrett et al. 1971; Logan 1988), before overfishing drastically reduced the

densities of sharks and other carnivorous fish species such as rockfish (i.e. groupers) and

snappers (Butler et al. 1993). In Chapter 4, I investigate whether coral cover, coral

richness, and the relative contribution by different functional groups of corals do vary

with distance from shore in a linear fashion, as the previous research described above

indicates, or whether a different pattern really exists. I also compare sites that differ in

depth and aspect across patch reefs, which represents another level of analysis that was

not attempted by prior researchers.

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Predominant environmental factors in operation across the study area

The environmental factors generally considered to most strongly determine the

assemblage structure of reef corals in Bermuda are temperature (Cook et al. 1990; Smith

1999), light (Dodge and Vaisnys 1977; Fricke and Meischner 1985; Logan et al 1994),

wave energy (Upchurch 1970; Mills et al. 2004), and the amount of suspended sediments

in the water column (Smith 1999; Mills 2000; Mills et al. 2004). These four factors

interact over environmental gradients that occur across the area of study (Logan 1988).

Suspended Particulate Matter

High levels of suspended sediment, or particulate matter (SPM), which reduces light

transmission to depth, are generally found in nearshore areas and decrease in

concentration as one moves offshore (Upchurch 1970; Logan 1988; G. Toro Farmer

unpublished data). This gradient is most likely present because the nearshore reefs are

protected from the predominantly southwesterly winds over the year by the location of

the island along the southern side of the reef platform. The sheltering effect of land

reduces the yearly amount of wave energy, allowing the retention of finer-grained

sediments near the shore (Upchurch 1970). The nearshore waters of the north lagoon also

experience a dramatic increase in the traffic of ships through the south channel in the

summer (Figure 3.03). These ships typically re-suspend substantial amounts of sediment,

as seen in the long, wide sediment trails that remain along the entire length of the ships

channel for many hours (Figure 3.04). The southern shipping channel runs along the

north shore of the island at a distance of roughly 0.5 km from shore (Figure 3.06, below).

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The lagoonal reefs far from shore are not as well protected by the island from waves

generated by high wind, although neighboring shallow (~2-m depth) reefs probably

reduce wave energy to some degree. Also, while there is a northern shipping channel that

passes through the offshore patch reefs, during the sampling period of this project (2000–

2005) ships only rarely traversed this passage (Bermuda Government, Dept. Marine and

Ports). For these reasons the reefs offshore experience higher wave energy (Mills et al.

2004), but also lower levels of suspended sediment. As I show below (Project 3), the

lower levels of suspended sediment offshore allows more light to reach a given depth on

offshore reefs than at a comparable depth on inshore reefs.

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Figure 3.03. A graph charting the number of passages by ships traveling through the

southern shipping channel in 2004. Cruise ships carrying tourists only come

to Bermuda in the warm months of summer. Ships bringing cargo visit

Bermuda on a regular weekly schedule over the entire year. The data

presented is derived from the Bermuda 2004 Cruise Ship Schedule (Bermuda

Govt., Department of Tourism and Transport 2004).

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Figure 3.04. An aerial photograph of a cruise ship traversing the south shipping channel

of Bermuda in a westerly direction, and leaving a plume of sediment in its

wake. A portion of North Shore and Spanish Point can be seen behind the

ship. (© 2006 T.J.T.Murdoch)

Water Temperature

Temperature varies in a predictable gradient from nearshore to offshore across the

study area (CARICOMP 1997; de Putron 2003). Reefs near the rim are exposed to

oceanic waters, which exhibit a limited range in temperature relative to the seawater in

enclosed bays and harbors. For this reason the greatest range in temperature occurs in

inshore waters, which cool to below 17°C in the winter months (February-April) and

warm to 31°C in the summer months of August and September (Figure 3.05). Offshore

reefs, alternatively , reach 18 to 19°C in winter and 29°C in summer months. Outer

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lagoon reefs experience temperatures that lie between these two extremes (de Putron

2003).

Figure 3.05. Temperature record for 2 subsurface temperature data loggers located either

near North Shore (Inshore) or on the forereef at 30 ft depth (Offshore) for a

three year period from 1998 – 2000 (modified from de Putron 2003).

Solar Radiation

The Effect of Depth and Turbidity

The visible sunlight that we see is of the same general range of wavelengths as the

solar radiation that plants use for photosynthesis; technically referred to as

Photosynthetically Available Radiation (PAR; Kirk 1994). Sunlight is absorbed by water,

even when it contains little suspended sediment (Kirk 1994). Light intensity decreases

with depth in an exponential manner, the rate of which is dependant upon the turbidity of

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the water and the wave-state of the surface (Kirk 1994). Corals at deeper sites are

expected to receive less light for growth than corals at shallower sites. Sites at a particular

depth in water with higher turbidity should likewise receive less light than sites at the

same depth in clearer water.

The Effect of Aspect

The coral reefs in Bermuda represent the most northerly coral reefs in the Atlantic. As

such, the angle of the sun in the southern sky is more acute here than on reefs located

closer to the equator (Figure 3.06). For this reason, the southern side of a patch reef in

Bermuda should be exposed to substantially more sunlight over the course of the year

relative to the northern side of the same patch reef. Below I describe a study (Project 2) to

determine the differences in light flux to a sensor facing a southerly vs a northerly

direction. In Chapter 4 I compare the differences in the coral assemblages located on the

north to those on the south sides of the same patch reef at the same depth.

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Figure 3.06. A graph of the hourly positions and paths the sun appears to take as it

crosses the sky in Bermuda over the course of a day during the summer and

winter solstices, and either equinox. The numerals around the circumference

of the circle represent bearing, with 90° representing East. The numerals

within the circle represent the angle above the horizon, with 90 representing

the zenith point, directly overhead. The sun is at it’s apparent daily apogee in

Bermuda at 12.13 pm local standard time. Graph generated using the

shareware tool “Sol Path” (© C. Gronbeck 2002, 2006).

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Wave energy and currents

The island of Bermuda possesses a hilly topography with an average height of 30 m

above sea level (Morris et al. 1977), which acts to block the effects of the wind on marine

habitats located in a leeward direction. As the island is located along the south-east edge

of the lagoon, the island primarily blocks winds that originate from the east through to a

south-westerly direction from reaching lagoonal waters. The prevailing winds in

Bermuda are from a south-westerly direction throughout the summer (Appendix C,

below), which results in calmer waters being found near the northern shore and higher

waves occurring offshore. In the winter, the prevailing winds originate from the north-

westerly direction. As there are no islands to block the wind from the north-west, high

seas produced by winter storms affect all lagoonal reefs to a relatively equal degree

(Morris et al. 1977 ), and even the northern shore is subjected to large (>4-m) waves

(Thomas 1985). Additionally, wind-driven current flow declines with depth, at an

exponential rate (Ekman 1905).

Bermuda experiences a semi-diurnal tidal cycle with a range of 0.75 m on average

(Morris et al. 1977). As a result of the changing tides, strong currents occur in some areas

on the Bermuda platform, particularly at the entrances to enclosed bodies of water such

as Harrington Sound and the Great Sound (Figure 3.02; Morris et al. 1977). Strong tidal

currents can also be observed to flow over the lagoonal rim at all locations, although they

are strongest at the northeast and southwest ends of the lagoon, presumably due to the

position of the Bermuda islands. However, since the study area is located within the

central area of the Bermuda lagoon,, far from enclosed bodies of water and the NE and

SW parts of the lagoon, tidal currents have little strength.

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Project 1: Mapping of lagoonal reefs

Introduction and Methodology

When the project was first initiated there were no accurate maps available that delineated

the locations of the patch reefs found scattered within the lagoon. For this reason, many

of the sites I surveyed were selected based on the surprisingly inaccurate maps of reef

location available from the Hydrographic Office of the United Kingdom, as well as from

triangulation of terrestrial landmarks and extensive time spent out in the lagoon in boats

learning the “lay of the land”.

In order to aid in the scientific study of Bermuda’s lagoonal reefs henceforth, in

2003–2004 I produced the first accurate, geo-referenced digital map of the entire suite of

reefs visible within the study area, as part of a larger mapping effort I did as a member of

the Bermuda Zoological Society that included all lagoonal patch and pinnacle reefs. This

map was produced by referencing a mosaic set of georeferenced aerial photographs of the

islands and surrounding submerged platform that the Bermuda Zoological Society

commissioned in 1997 (Figure 3.01).

The aerial photographs of the Bermuda Islands and surrounding reef platform were

produced using a Zeiss Jena LMK photogrammetric survey camera with forward motion

compensation, which was mounted onto a small aircraft. In 2003 a composite raster

bitmap for the entire Bermuda platform was produced from the slides, with a final

resolution of 50 cm per pixel and a geo-referenced error of less than 2 m (Bermuda

Zoological Society 1997). A map of probable coral reef habitat was then created for the

entire Bermuda platform from the digital mosaic with the GIS package ESRI ArcMap 9.1

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(Figure 3.02). To create this map I manually digitized the boundaries of coral reef areas

as continuous closed polygons at a scale of 1:2500, using color (light to dark reddish-

brown) and the presence of sand halos around reefs as visual indicators of boundary edge.

Spatial referencing of the digital photographs was accurate to 2 m and, combined with a

pixel size of 50 cm, a spatial accuracy of about ±2.5 m was possible for visually mapped

reef boundaries. Over 34,000 separate reefs were mapped across the extent of the lagoon.

Once the boundaries of each reef within the lagoon was mapped to GIS, I delineated

the outer edges of the study area, as well as the margins between each of the six zones

within the electronic map. I then used the Hawth’s Analysis Tools extension for ESRI’s

ArcGIS (Beyer 2004) to generate the data which I compiled into Table 3.01, which

details the area enclosed by each zone, the number of reefs in each zone, the density of

reefs per km2, the total reef area per zone, the percentage of total zone area covered by

reefs, and the mean size of each reef.

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Figure 3.07. Zonal boundaries, locations of the north and south shipping channels, and

location of patch reefs distributed across the study area encompassing the

North Lagoon. The numbers allocated to each zone are written on the right

side of the map.

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Results and Discussion

The characteristics of the patch reefs within each of the six zones surveyed are listed

in Table 3.01. Zone 1 lies closest to shore and is bounded on the southern side by the

northern shore of the island. The northern boundary is delineated by the South Shipping

Channel which cuts across the study area. Zone 2 is located on the northern side of the

South Shipping Channel and extends 1-2 km to seaward. Zones 1 and 2 had the fewest

reefs per km2, but the mean reef size was larger than most other zones. Many of the

nearshore reefs in Zone 1 appear to be fringing reefs, which are large, linear structures

that are positioned with the long axis running parallel to shore. These reefs probably

formed on a basement of drowned shoreline and only formed in the past 4,000-6,000

years (Garrett et al. 1971; Garrett and Scoffin 1977).

The reefs in Zones 2 to 4 are mostly contained within the clusters of reefs known as

Baileys Flat and Brackish Pond Flat. These reef systems appear to have formed on

fossilized sand dunes that formed during glacial periods when the shallow platform was

subaerially exposed. Between these two large reef clusters is a deeper area of

approximately 12-m depth across which are scattered many smaller patch and pinnacle

reefs, which may contribute to the lower mean area of the reefs in the middle zones of the

platform.

The reefs in zones 5 and 6 are large faro reef complexes, formed on what are most

probably wash-over sediment deposits that formed 8000 to 6000 years ago when the

platform first flooded (Garrett et al, 1971; Garrett and Scoffin 1977). These reefs form

large clusters with large reefs surrounding a shallow inner sand-covered area speckled

with small patch reefs.

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Table 3.01. Characteristics of each zone of the survey area across the Bermuda Lagoon,

and the patch reefs contained therein.

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Project 2: Assessing the three-dimensional light field over a range of depths

Introduction and Methodology

Although light in oceanic waters can be accurately quantified as a one-dimensional

gradient of downwelling and upwelling flux, light in shallow coastal environments has a

three-dimensional character (reviewed in Kirk 1994; Ackleson 2003). Bermuda’s high

latitude further enhances the multidimensional character of the light field, in that the

angle of the sun in the sky is significantly sharper through much of the year than it is at

all other coral reef regions, which al lie further to the south.

To quantify the three-dimensional character of light in Bermudian waters, I assessed

the differences in light flux measured by a hemispherical sensor, representing a mound-

shaped coral colony, when it was positioned perpendicular to the directions North, East,

South, West, Up and Down (N, E, S, W, U, D). To do this I modified a standard scalar

Li-Cor light sensor, which is spherical and designed to measure light impinging from all

directions, by covering the bottom half of the sphere so that light could only be received

over the top half of the sphere (Figure 3.08). Light was blocked from the bottom half of

the sensor with the use of opaque adhesive tape, and the entire sensor was mounted at the

midpoint of an circular and opaque black plastic collar with a 25-cm diameter. The collar

was added to further prevent the reception of light by the sensor from sources located

below the exposed hemispherical sensor surface.

I measured light availability from the underwater light field emanating as

downwelling light, upwelling light, and light impinging from easterly, southerly, westerly

and northerly aspects. Average measurements from these six directions were recorded by

the data logger at 5-second intervals for 5 minutes each at 3-m depth intervals down to

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15-m depth. Data collection was done in clear oceanic water (Secchi disk depth >18 m) at

location 32.382°N, 64.648°W on the forereef east of Bermuda, on July 24th, 2002. A

second light sensor was placed at 9-m depth to control for the effects of clouds.

Concurrent measurements taken in air and at 9-m depth prior to the experiment were used

to convert recorded light flux to a percentage of the light hitting the surface of the ocean.

Both sensors were connected by transmission cables to a electronic data logger located on

the boat at the surface. The boat was not directly overhead of the area of data collection,

so as to avoid detection of the boat shadow. The mean light flux and standard error of

each collection period from each depth and aspect were subsequently graphed for visual

comparison. The data did not conform to the assumption of equal variances, and

transformations of the data were unable to resolve the problem. The results of ANOVA

on all forms of the transformed data produced the same significance values as did

individual Mann-Whitney U tests (a nonparametric test of differences), so the results

from the ANOVA using non-transformed data are presented.

Results and Discussion

At all depths the amount of light impacting the sensor when it faced a southerly

direction was substantially higher than when it faced a northerly direction (Figure 3.09).

Downwelling light was substantially higher than the amount of upwelling light (as

expected), and downwelling light was also significantly higher than light originating from

either a southerly direction or a northerly direction. Additionally, more downwelling light

was available in locations closer to the surface than at greater depths. The values for the

sensor placed in an easterly and westerly aspect were statistically indistinguishable from

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each other and at levels between those obtained from the northerly and southerly aspects,

which is as would be expected (T. Murdoch unpublished data). For simplicity, the data

from these two “midpoint” directions have been omitted from further analysis in this

section. Two-way ANOVA of depth and aspect for all 5 depths and four directions (N, S,

U, D) found that the interaction between the depth and the direction that the sensor faced

was highly significant at p < 0.001 (Table 2.02). Tukey HSD post hoc comparisons of the

light data determined that all measurements were significantly different for each depth

and aspect except between all measurements taken at 12-m depth and at 15-m depth, and

between the measurements taken from the northerly aspect and of upwelling light at all

depths.

These results illustrate that the location of Bermuda at a high latitude results in more

light being available to an organism living on the south-facing side of an object, such as a

coral reef, than on the north side, due to a shading effect created by the bulk of the reef

itself. The survey was done in August, when the angle of the sun is more obtuse than it is

for eight months of the year. Thus, for most of the year the relative difference in light

availability between the north and south sides of a reef is greater than that observed.

However, since less light reaches the surface of the earth as the sun angle sharpens, the

absolute difference between the northern aspect and southern aspect would be less in

winter months.

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Figure 3.08. A diagram illustrating the modified Li-Cor scalar PAR sensor. Opaque

adhesive tape, an opaque plastic jar, and a black plastic collar constrained

the light quantified by the sensor to that impacting the upper, exposed

hemisphere.

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Figure 3.09. Mean proportion of surface light (± standard error) originating from four

directions at five depths, as measured by the hemispherical sensor.

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Table 3.02. Two-way analysis of variance of the effects of depth and aspect on the

proportion of surface light reaching a hemispherical sensor.

Source SS df MS F-ratio p

Depth 5382523.974 4 1345630.993 178.307 .000

Aspect 24710913.276 3 8236971.092 1091.466 .000

Depth *

Aspect5931307.572 12 494275.631 65.496 .000

Error 2867746.630 380 7546.702

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Project 3: Cross-platform differences in downwelling light availability

Introduction and Methodology

If turbidity is higher nearshore relative to offshore, as prior research (CARICOMP

1999; Jones 2007) indicate, then the amount of downwelling light impacting a point at a

particular depth should be lower nearshore than offshore. In order to assess cross-

platform differences in the availability of downwelling light, light flux was assessed at 8-

m depth at five equally-spaced locations that were at different distances from shore

(Figure 3.10), over a week-long interval in June 2004. Downwelling light intensity was

measured using a collection of miniaturized, submersible Onset Hobo® light sensors with

self-contained data loggers, following techniques described in Kirk (1994).

Each sensor recorded light flux at 5-min intervals over the 7-day period. The

maximum light flux readings taken over the 2 hr in the middle of each daylight period

were used to calculate differences between locations in light availability. Only data from

the first five days were used, as most sensors became fouled with fine sediment or

filamentous algae after that period of time. Transformed data did not conform to the

assumptions of homogeneity of variances; the results from ANOVA of the non-

transformed data are presented but should be interpreted with caution.

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Figure 3.10. Map of the five reef sites, indicated by the light-bulb symbol. At each site

luminance readings were taken concurrently, from 26 July 26 to 1 August

2004. All sensors were placed at exactly 8-m depth, with the sensor surface

facing straight upward. The boundaries of the study area, the six zones, and

the north and south shipping channels are also illustrated

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Results and Discussion

Figure 3.11 illustrates the continuous changes in light level over 5-min intervals over

the five days across the five sites. Light levels increase over the course of a day until

12:13 pm local standard time, and then decline again as the surface of the earth rotates

away from the sun. Sharp spikes in light above the daily maximum are characteristic of

peaks in light produced by the passage of waves. A surface wave can act as a lens, and

may either focus or diffuse light reaching a point below it (termed “wave focusing”; Kirk

1994; Schubert et al. 2001). This process of wave focusing is the source for the

meandrous patterns of brighter light observed on the sandy sea floor in shallow water, or

on the bottom of a swimming pool. The magnitude of the spike during wave focusing

events is dependent on the shape of the wave and the depth of the sensor, with the highest

spikes occurring when lens shape and sensor depth match and a large amount of the sun’s

light is focused on the spot. Sudden large drops in light intensity that one can see in the

daily light data are probably due to the occlusion of the sun by clouds (Kirk 1994). Drops

in light intensity that match across all sensors, such as the event recorded near noon on

the third day surveyed, indicate the passage of very large clouds that encompassed the

entire reef platform. Another source of reduced light across large areas is the occurrence

of sustained wind events with speeds greater than 28 km/hr (15 kts), which cause the

formation of frothing waves or “white caps” that reflect light away from the seabed (Kirk

1994).

Light levels were highest at the site located in the rim reef zone, and declined at sites

progressively nearer to shore (Figs. 3.11, 3.12). ANOVA determined that the overall

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pattern was highly significant (Table 3.03). Tukey’s HSD post hoc analysis (Table 3.04)

determined that only sites C and D were not significantly different in light intensity.

These results indicate that, for a given time period at a given depth, corals nearshore

are exposed to less light than those offshore. Since light is a critical resource for

hermatypic corals which host photosynthetic zooxanthellae (Rogers 1979; Achituv and

Dubinsky 1990), and since different coral species are adapted to cope with a range of

characteristic annual light budgets (Huston 1985a; Graus and Macintyre 1989), it is

expected that different corals will be found at the same depth but at different distances

from shore across the Bermuda platform.

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Figure 3.11. Light intensity readings taken over five days from sensors positioned at 8-m

depth at 5 reef sites located at different distances from shore across the area

of study. Instantaneous light intensity readings were taken at 5-second

intervals over five days.

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Figure 3.12. Average light intensity (Lumens ±SE) measured from 11 am to 1 pm local

standard time over the first of the five days of deployment, by light sensors

located at 8-m depth at five reef sites positioned at increasing distances from

the North Shore of Bermuda. The approximate distance from shore of the

boundaries between zones (which varied along the extent of each zone) are

also indicated.

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Table 3.03. ANOVA table of the differences in light intensity across the five locations

from the data illustrated in Figure 2.13.

Source SS df MS F ratio p

Distance 193031.858 4 48257.964 216.557 0.000

Error 25626.866 115 222.842

Table 3.04. Results of a Tukey’s post hoc analysis of the significance in the differences in

the amount of luminance at 8-m depth over the hours of 11 am to 1 pm

between the five locations across the reef platform. Only sites C and D did

not differ significantly in the amount of light measured at 8-m depth.

Tukey HSD

Distance A B C D E

A

B 0.000

C 0.000 0.009

D 0.000 0.000 0.596

E 0.000 0.000 0.000 0.000

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DISCUSSION

A review of the literature regarding Bermuda’s physical oceanographic conditions, as

well as novel research, indicates that the four critical environmental factors of

temperature, light, suspended particulate matter and current flow all covary with distance

from shore and with depth. As described in Chapter 1, these four factors can each affect

corals as stressors, disturbance agents and as factors promoting growth, depending on the

levels or intensities at which they occur (Figure 3.13).

The amount of variability in temperature is higher nearshore compared with offshore,

with colder winter temperatures and hotter summer temperatures experienced by sites

near land (Morris et al. 1977; du Putron 2003). Offshore sites, which are bathed in the

waters of the surrounding Sargasso Sea, experience less change in temperature over the

year. Temperatures also vary across depths in the summer, with warmer waters occurring

at the sea surface across the lagoon (Morris et al. 1977). Low temperatures inhibit

physiological functions, and as such act to inhibit growth and tissue repair. High

temperatures, alternatively, act as a disturbance agent, by inducing coral bleaching (Cook

et al. 1990; Brown 2004), inhibiting reproduction (Fraser and Currie 1996), promoting

the growth of coral diseases (Harvell et al. 1999), and the growth of competing

organisms such as macroalgae (Johannes et al. 1983). Accordingly, nearshore reefs are

predicted to have less coral cover and species relative to offshore reefs. Additionally,

competitively-dominant corals may be expected to dominate in areas of lower

temperature range found offshore, with disturbance-tolerant or stress-tolerant corals

dominating the nearshore areas with a high range of temperatures.

Light levels in Bermuda are highest in the shallowest waters offshore, and decline

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both with depth and with proximity to shore. Wave energy follows the same pattern. Both

light and wave energy act as damaging agents at high levels, promote growth at moderate

levels and inhibit productivity at very low levels. For that reason it may be expected that

ruderal corals dominate shallow sites, particularly on reefs offshore, while competitive-

dominate coral species dominate at some mid-point across the lagoon and at moderate

depths. Deep sites, particularly nearshore, are predicted to be dominated by stress-tolerant

coral species adapted to low levels of light and low rates of dissolved nutrient flux.

Suspended particulate matter (SPM) is in highest concentration nearshore, and

decreases in concentration as the distance from shore increases (Mills et al. 2004; G.

Toro-Farmer unpublished data). SPM can act as both a disturbance agent and as a source

of nutrients. Nearshore sites are predicted to possess more corals that are capable of

removing or surviving the smothering effects of SPM. Additionally, heterotrophic corals

that are able to utilize SPM instead of light as a source of carbohydrate nutrition may be

favored in nearshore habitats relative to those offshore.

In Chapter 4 I describe how I examined the manner that species and functional groups

of coral varied across sites that differed in distance from shore and depth, which serve as

simple proxy direct gradients for the co-varying physical gradients of temperature, light,

SPM and wave energy that were described in this chapter. Coral assemblages were

surveyed across sites located at a range of depths and distances from shore on patch and

pinnacle reefs within the North Lagoon of Bermuda, and the results compared to the

patterns predicted by the modified Adaptive Strategies Theory that I presented in Chapter

1.

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Figure 3.13. Representation of how varying levels of the four most important

environmental factors act to promote growth, or act as a stressor or

disturbance agent to corals.

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CHAPTER 4: THE DISTRIBUTION OF CORAL SPECIES AND FUNCTIONAL

GROUPS OVER PHYSICAL GRADIENTS ACROSS THE NORTH

LAGOON OF BERMUDA

INTRODUCTION

According to the Adaptive Strategies Theory (AST; Grime 1979), one can predict the

characteristics of the functional group of organisms that will dominate a particular habitat

by determining the levels of stress and disturbance that are found at that location (Figure

4.01). On coral reefs, the four environmental factors that predominantly affect the

amount of stress or disturbance which corals experience are: water temperature, solar

radiation (i.e. sunlight), suspended particulate matter (SPM) and water flow. In Chapter 3

I described how these four physical factors vary as gradients across the North Lagoon of

Bermuda. In this chapter I examine whether the modified AST that I described in Chapter

1 predicts how species and functional groups of coral are distributed across sites on reefs

in Bermuda that are located over these environmental gradients of stress and disturbance.

The sites I surveyed in Bermuda can be thought of as representing the range of

environmental conditions enclosed within the nested square illustrated in the AST (CSR)

diagram below (Figure 4.01).

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The four critical environmental factors of temperature, light, suspended particulate

matter and current flow all vary with distance from shore and with depth (Chapter 3). As

described in Chapter 1, these four factors can each act on corals as either stressors,

disturbance agents and in the promotion of growth, depending on the levels or intensities

at which they occur (Figure 1.06).

Sea water temperature exhibits a wider range within the surveyed area at nearshore

sites compared with locations offshore, with colder winter temperatures and hotter

summer temperatures experienced by sites near land (Morris et al. 1977; de Putron 2003).

Since corals suffer physiological disturbance when they experience temperatures too far

outside their average range, nearshore reefs are predicted to have less coral cover and

species relative to offshore reefs. due to high disturbance levels (strong annual seasonal

temp fluctuations) restricting the growth of stress-tolerant corals and limiting the number

of species capable of surviving on these nearshore reefs. Additionally, competitively-

dominant corals may be expected to dominate in the areas of lower temperature range

found offshore.

Light levels in Bermuda are highest in the shallowest waters offshore, and decline

both with depth and with proximity to shore, due to the re-suspension of sediments. Wave

energy follows the same distribution pattern. Light and wave energy both damage corals

when at high levels . At moderate levels light and water flow both promote coral growth.

At low levels of both light and water flow corals experience limited productivity .

Accordingly, ruderal corals are predicted to dominate shallow sites, particularly on reefs

offshore, while competitive-dominate coral species are predicted to dominate at some

mid-point across the lagoon and at moderate depths. Deep sites, particularly offshore, are

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predicted to be dominated by stress-tolerant coral species adapted to low levels of light

and low rates of dissolved nutrient flux due to reduced rates of water flow. Nearshore

reefs may see high nutrient fluxes due to the presence of nitrogen-rich ground water.

Suspended particulate matter (SPM) is in highest concentration nearshore, and

decreases in concentration as the distance from shore increases (von Bodungen et al

1982; Mills et al. 2004; G. Toro-Farmer unpublished data). SPM can act as both a

disturbance agent and as a source of nutrients Nearshore sites are predicted to possess

more corals that are capable of removing or surviving the smothering effects of SPM.

Additionally, heterotrophic corals that are able to utilize SPM instead of light as a source

of carbohydrate nutrition may be favored in nearshore habitats relative to those offshore.

OBJECTIVES

With the use of direct gradient analysis I tested the following hypotheses regarding

how species and functional groups of coral varies across the sites surveyed in the

Bermuda lagoon:

Similarities in the distribution of species and functional groups

Irrespective of the manner in which stress or disturbance agents are distributed across

sites, species within functional groups are hypothesized to have similar functional

responses to the environment. If this is so, then species belonging to the same functional

group should differ little in their distributions across sites, due to the shared responses to

environmental and biological conditions (Steneck and Dethier 1994; Gitay and Noble

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1997; Hooper et al. 2002). Conversely, the distribution patterns of species belonging to

different functional groups should be substantially different from each other, due to

disparate environmental tolerances. Chapter 1 details how these differences in site fidelity

should appear when distributional data is graphed in a variety of ways.

Despite my best attempts to do otherwise, it may be that the traits I selected to use in

the categorization of species into functional groups are those indicative of functional

mechanisms by which species acquire resources, and not those which are used to cope

with differing environmental disturbances. If this is so, then species within functional

groups may overlap greatly in their nutritional needs and therefore compete strongly

amongst other members for resources Species that belong to the same resource-based

functional group (also known as “guild”) should tend to occur in different

environmentally-defined habitats (reviewed in Fox 1999). Also species that are members

of different guilds should be able to coexist within a location to a greater degree than

species from the same guild.

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Figure 4.01. A modified version of Grime’s (1977) and Steneck and Dethier’s (1994)

generalized two-dimensional AST model of FG dominance within habitat

types, incorporating the concession that biota can only survive in habitats

within which the rate or amount of resource acquisition (resource

abundance) is greater than the rate or amount of resource loss (or

disturbance). The boundary between the white and grey areas is the zero net

growth intercept (ZNGI) of the assemblage as a whole. The nested square

within the AST diagram of state space represents the hypothetical range within

the AST model that was represented by the sites surveyed within the north

lagoon of the Bermuda Reef Platform. Letter designations are:

C – Competitive Dominant;

R – Ruderal;

S – Stress tolerant.

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Similarity among sites in species assemblages

Sites were compared according to the degree to which they shared coral species. Sites

that differed in aspect, depth and distance from shore were evaluated so that the species

composition of each site could be interpreted accordingly. Sites that shared

environmental characteristics, regardless of zone or depth, were expected to cluster

together in multidimensional species-abundance space. Sites at a similar depth and

distance from shore were expected to cluster together in multidimensional state space (i.e.

have similar assemblages of corals on them) because the shared environmental conditions

of each site should filter coral species membership in the same way.

Percent cover and abundance per functional group

The percent cover for corals overall, and for the group of species that are members of

the most competitive functional group, are both predicted to peak on reefs where the

levels of disturbance and stress are lowest. In the north lagoon light and wave energy are

highest at shallow, offshore sites and lowest at nearshore, deep sites. Conversely, SPM

and temperature are most damaging to corals at nearshore locations regardless of depth,

and decline with distance from shore. Accordingly, moderate levels of all four variables

are expected to occur at mid-depth and roughly in the centre of the lagoon. Since

moderate levels of the four variables are the least limiting to corals, the average coral

cover of all species, as well as of the competitive species should peak at sites located in

the middle of the lagoon as well. Members of the Branched, Oviparous (BO) functional

group (i.e. the acroporids) are not found in Bermuda. With the BO group absent, either

the Competitive-Ruderal or Competitve - Stress-tolerant functional groups may plausibly

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occupy its environmental niche, and thus dominate habitats characterized by low levels of

stress and disturbance in Bermuda. Branched Viviparous (BV) species represent the

Competitive-Ruderal group. Species of the Massive Oviparous (MO) functional group

belong to the Competitive-Stress-tolerant group.

Massive, viviparous (MV) corals, which I classified as Ruderal according to the

modified AST, are predicted to dominate at offshore reef sites in shallow water where

disturbance levels are predicted to be the highest. Stress-tolerant corals of the Foliose and

Plating (FP) functional group are predicted to be intolerant of disturbance at all but the

lowest levels. Since temperature variability and SPM, which are both forms of

disturbance, are higher nearshore compared with offshore over all depths, stress-tolerant

corals should dominate only deep sites located in the zones furthest from shore.

Species distributions across sites

In addition to providing information regarding the percent cover and relative

abundance of each functional group across all sites, as I did in Chapter 2, I also

determined the distribution patterns of each species. This species-specific data allows one

to see the degree to which species within functional groups share distributional patterns,

if at all. I also present this data for a pragmatic reason. This project represents the most

intensive survey of reef sites across Bermuda’s north lagoon to date, and the only survey

of how coral assemblages change with depth and distance from the shore across patch

reefs across the lagoon. For this reason, species distribution data are provided in order to

aid in management and conservation of the corals, as well to guide future scientific

research.

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Species richness of all corals

According to the predictions of the productivity-diversity hypothesis, which lead to

CSR theory (Grime 1973; 1979), and the intermediate disturbance hypothesis (Connell

1978; Aronson and Precht 1994; Huston 1996), the habitat types with intermediate levels

of stress and disturbance should display greater species richness than either the habitats

with low levels of stress or disturbance and the habitats with high levels of stress or

disturbance. Sites located in the middle of the lagoon and at mid-depth are thus predicted

to possess the highest number of species, with lower numbers of species found at the

extremes of distance and depth.

Functional group richness

Grime (1977) predicts that the richness of functional groups will be low across sites,

as he predicts each functional group will be replaced by another from site to site due to

the combined effects of environmental filtering and competitive exclusion between

functional groups. Alternatively, if competition does not operate between groups, then

all functional groups are predicted to occur at mid-depths on reefs centrally located

within the lagoon, as these reefs are characterized by moderate levels of the four

environmental factors. Shallow sites offshore and all sites inshore are predicted to not

possess the stress-tolerant functional groups, and deeper sites should not possess the

ruderal nor competitive-ruderal species, according to the AST.

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METHODOLOGY

Data collection

The tops of three replicate patch reefs (designated E, C and M), and the sides of two

of the three patch reefs (E and C), separated by at least 1-km, were sampled within each

of the 6 zones (Figs. 4.02, 4.03; Table 4.01). Zones differed in distance from the North

Shore of Bermuda and were within the lagoonal area bounded by the rim reef to the

north. At each reef, transects were videotaped following the procedures described in

Aronson et al. (1994), Aronson and Swanson (1997), for fore-reef habitats, but with

modifications that were needed in order to cope with the different geomorphology of

patch reefs. Since variation in the size of reefs may have affected the composition of the

coral assemblage in unintended ways (Keough 1984), all of the reefs surveyed were of

similar area and overall shape. Each patch reef was oval in shape, roughly 60-m long,

40-m wide, and with the long-axis lying in an east-west direction. The top of each patch

reef was assessed using eight 10-m long transects, placed haphazardly and so as to

encompass as much of the top of the patch reef as possible Only eight transects were

used as no more could be surveyed without overlap. . Additionally, four 10-m long

transects were haphazardly placed horizontally along consecutive ~2- to 3-m depth

contours on the southern and northern sides of the reefs.. Only four 10-m transects were

filmed on each flank; this representing the maximum number of transects that could fit

along the ~ 50-m long flank of each patch reef at each depth, while still allowing for the

haphazard placement of the transects. Since the four transects encompassed most of the

surface of the reef at each depth it seemed probable that the sampled population

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represented most or all of the total population of corals found at each site, which is to say

that most or nearly all of the statistical universe was recorded.

All transects were videotaped along a 0.4-m wide x 10-m long swath of the reef with a

high-resolution digital video camera enclosed in an underwater housing. An aluminum

bar projecting forward from the camera housing was used to maintain a 40-cm distance

between the camera lens and the reef surface. A depth gauge mounted on the end of the

bar displayed the depth of the reef substrate on each video frame, providing a measure of

the rugosity of the reef surface when filming the tops of reefs. The depth gauge also (1)

aided the videographer in maintaining a set depth while filming transects on the steeply

sloped sites of pinnacle reefs, (2) provided scale in the videotaped images, and (3)

provided a record of the depths surveyed on each reef.

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Figure 4.02. General design of the study, in which survey sites (circles) were surveyed at

a range of depths on the north, south and top sides of replicate patch reefs

within each of six zones located at increasing distances from shore. Not

shown are the replicate reefs within each zone.

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Figure 4.03. A map of the lagoonal reefs located within and around the research area and

the 18 patch reef sites surveyed in the videographic analyses. Horizontal

lines indicate the six zone boundaries. Grey lines represent the location of

the north and south shipping channels. A portion of the island of Bermuda is

represented by the area in darker gray at the bottom of the image.

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Table 4.01. Details of the 18 surveyed reefs surveyed across the North Lagoon, also

mapped on Figure 4.03. Replicates labeled M were only videographically

sampled on the top of the reef, whereas replicates E and C were surveyed on

the tops as well as across a range of depths on the north and south sides of

each reef.

Zone Replicate Name Site Lat Long

Reef Top

Depth (m)

1 E Baileys Bay Patch E1 32.3520 -64.7250 7

1 M Shelly Bay Patch M1 32.3290 -64.7440 7

1 C Robbie’s Reef C1 32.3170 -64.7520 7

2 E Inner Baileys Flat E2 32.3530 -64.7480 5

2 M Shelly Bay Shoals M2 32.3360 -64.7570 5

2 C Finger Coral Patch C2 32.3356 -64.7765 7

3 E Martello Patch E3 32.3720 -64.7430 6

3 M Judie's Awakening M3 32.3700 -64.7620 6

3 C Gaeroid’s Reef C3 32.3550 -64.7820 7

4 E Angel Reef E4 32.3808 -64.7660 4

4 M Jeannette's Reef M4 32.3750 -64.7830 4

4 C Sascha’s Reef C4 32.3643 -64.8062 4

5 E 8A Hole Reef E5 32.4066 -64.7830 4

5 M S. Crescent 3 Patch M5 32.3870 -64.7990 3

5 C Pawlik’s Reef C5 32.3940 -64.7890 2

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6 E Pretty Bumpy Reef E6 32.4180 -64.8193 2

6 M Lisa's Reef M6 32.3961 -64.8605 2

6 C Claire's Reef C6 32.4094 -64.8410 3

Data analysis

Different hypotheses were tested using different types of data derived from the

videotaped transects. Relative Frequency of occurrence (RF) data for corals was used for

the analysis of the similarity in species distributions, the similarity of sites in species

composition, and the frequency of occurrence of each species across all reefs, as well as

species richness and functional group richness data. RF data was used for these analyses

instead of point-count data as it included rare or small species that may be missed in the

assessment of randomly placed points on transects. The RF data were collected in the

following manner. 20 non-overlapping video frames were digitally captured from each of

the 10-m long transects. Following image capture, the presence or absence of each

species in each of the 20 frames was recorded. The proportion of frames over which each

species occurred in each transect was then calculated by dividing the number of times

each species was present in each of the 20 frames.

Point-count data was assessed from each video transect following a computer-

automated version of the procedures described in Aronson et al. (1994), Aronson and

Swanson (1997) and Murdoch and Aronson (1999) that were developed by the author for

a different project (Appendix 4B). The video transects from the tops of three replicate

reefs, and the tops and southern flanks over a range of depths for two replicate reefs for

each of the six zones were assessed for the percent cover of individual coral species by

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point-counts Twenty-five random points positioned on each adjacent digital image

captured from the videographic tape. The alternate (odd-numbered) frames were captured

to provide other views of the same substrate and as an aid for visual analysis of point

count locations but were otherwise not analyzed. . The results of each analyzed frame

were summed for the entire transect, and the average of the four or eight transects was

used to calculate the average percent cover for each of the sites on a reef.

The following variables were calculated for each reef site from the videographic data:

Species coexistence among habitats

The frequency of occurrence (RF) data were used to calculate a similarity matrix for

the suite of species, based on the proportion data from each transect and separately based

on the proportion data averaged at each site. Transect-level and site-level results were

alike, so the less complicated site-level analysis is described. A Bray-Curtis similarity

metric was calculated for each species pair from square-root transformed proportional

data. Since frequency of occurrence data exhibits a smaller range of values than biomass

data, it need only be square root transformed, instead of fourth-root transformed, when

used to generate similarity matrices (Clarke and Gorley 2006). Using the Bray-Curtis

metric, species that exactly shared the same distribution pattern were assigned the highest

percent similarity (i.e. 100%), and species with distribution patterns that did not overlap

at all were assigned very low similarity values. The benefit of looking at the coexistence

of species within and among functional groups in this way is that knowledge of the actual

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environmental and biological conditions of each site was not needed, as long as sites

were sampled across a broad range of habitats.

Similarity among sites in species assemblages

Sites were also compared according to the degree to which they shared coral species

using the same frequency of occurrence data as described above. Sites that differed in

aspect, depth and distance from shore were compared so that the species composition of

each site could be interpreted accordingly. Sites that shared zone and depth were

expected to cluster together in multidimensional species-abundance space, because sites

with similar depth and distance from shore shared environmental conditions and therefore

should affect coral species membership in a similar manner.

Species distributions across sites

In order to see how member species of each functional group were distributed across

sites in the four dimensions surveyed (i.e. RF x depth x aspect x replicate reef), I graphed

the frequency of occurrence data for each species. These data were averaged for each of

the four or eight transects for each site and the results graphically presented in three

ways. An MDS diagram was generated for all sites, and the average RF of each species

and functional group plotted as a circle, with differing sized representing differences in

occurrence. Additionally average (±SE) RF was plotted as points on a line graph for each

replicated site, aspect, depth and reef. The same data were also plotted onto a bubble

diagram for each depth and reef (but not aspect). Bubble diagrams present the relative

abundance for each species across sites and depths in a two-dimensional manner that is

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analogous to the actual distribution of sites across real space. These three disparate

graphical techniques were concurrently used for the identical data so that the reader could

better comprehend the 4D manner in which each species and functional group was

distributed across sites.

Percent cover data for each species at each sites was also used to determine the

distributional patterns of each species across the tops of three replicate reefs and tops plus

south sides of two replicate reefs in each zone. The method by which these analyses were

done is described below.

Standard measures

Percent cover, species richness and functional group richness measures of the coral

assemblage were also collected across sites from video transects. This data was collected

from video transects filmed on the tops of three replicate reefs and on the tops and south

sides of two replicate reefs located in each of the six zones. The information from the

tops and south sides was collected for two reasons: (1) to test the hypotheses of the

modified AST using the kind of information usually collected by coral-reef scientists in

the habitats where research is generally focused (i.e. the tops of reefs and not the sides);

and (2) to accurately determine the manner in which coral parameters vary across the

North Lagoon. The data from the north sides were ignored so as to reduce the complexity

of the analysis by ignoring the effect of aspect.

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Statistical analyses

Codes for species and functional groups

The acronyms used in the graphs to follow for each functional group are:

BV: Branched Viviparous; FP: Foliose and Plating viviparous

MV: Massive Viviparous; MO: Massive Oviparous;

Functional group membership used in the graphs to follow, and the letter designations for

each species are as follows:

Functional Group Species Abbreviation

BV Madracis decactis MDEC

BV Madracis mirabilis MMIR

BV Porites porites PPOR

FP Agaricia fragilis AFRAG

MO Diploria labyrinthiformis DLAB

MO Diploria strigosa DSTRIG

MO Montastraea cavernosa MCAV

MO Montastraea faveolata MFAV

MO Montastraea franksi MFRANK

MO Stephanocoenia intersepta STEPH

MV Favia fragum FAV

MV Porites astreoides PAST

MV Siderastrea radians SRAD

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A Bray-Curtis similarity matrix was generated for all observed coral species, based on

their distributions across all reef sites. The results of the matrix was graphically

displayed, as both a dendrogram and a multidimensional scaling (MDS) diagram (Figs.

2.19-2.23) An analysis of similarity was calculated in order to determine whether

functional groups of species formed significantly distinct clusters.

A two-way analysis of variance was calculated for each of the standard univariate

measures assessed.

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RESULTS

Depths per reef

Figure 4.04 illustrates the number of sites per reef and the depths at which each site

was surveyed on each patch reef. The number of sites per reef was limited by the size of

the flanks (i.e. sides) of each reef, and reefs in different zones had flanks of different

heights. Reefs in Zones 1 and 2 were small and deep and therefore only one depth could

be surveyed per side. Reefs in Zones 3 and 4 were in shallower water, but reached closer

to the surface and as a result two could be surveyed per side. Reefs in the outer two

zones were in deeper water, but reached the shallowest depths as well. As a result, three

depths could be surveyed on the reefs in zone 5 and five depths surveyed down each

flank on reefs in Zone 6. The reefs in most zones were patch reefs with sloping sides.

Reefs in Zones 1 and 2 did not contain deeper central basins of sediment. Reefs in Zones

3 –5 were better developed and did contain a deeper central “mini-lagoon” containing

sediment and limited coral development, These central areas were avoided in the

transects. The reefs in Zone 6 were well-developed pinnacle reefs, with shallow, flat tops

without central mini-lagoons, and had very steep or overhanging sides reaching to 12-m

depth.

The limited height that characterizes the reefs in Zones 1 and 2 may be indicative of a

highly disturbed and stressed environment to corals. These two zones are separated by the

southern shipping channel, in which light levels are reduced and suspended sediment

loads are high due to the passage of container and passenger ships throughout the year.

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Figure 4.04 should be referred to when examining the graphs to follow, as the manner

in which sites graphically arranged on each reef are the same manner throughout. In each

matching graph, the site located at the top of each reef is within the central white band for

each zone, while south-facing sites are illustrated within the light gray band in each zone,

and the sites with a northern aspect are illustrated within the darker gray band in each

zone.

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Figure 4.04. Diagram illustrating the average depths of each site on patch reefs located

on different sides (aspects) and at varying distances from shore. Two

replicate reefs were sampled in each zone across all depths and on all sides.

The depths of the reefs in zone 1 completely overlapped. S: Southern

aspect; T: Top of reef; N: Northern aspect. C = Central replicate; E: Eastern

replicate.

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Similarity in species distributions across sites on each reef

A Bray-Curtis similarity matrix was generated for all observed coral species, based on

their distributions across all reef sites. The results of the matrix was graphically displayed

using both a dendrogram and a multidimensional scaling (MDS) diagram (Figs. 2.05,

2.06). Species that shared phylogeny and functional group membership tended to cluster

together, both when plotted in a dendrogram and in multidimensionally scaled space.

Coral species that fit this pattern included Madracis mirabilis and Madracis decactis;

Diploria strigosa and Diploria labyrinthiformis; and Montastraea franksii and

cavernosa. Species that did not fit the pattern of phylogenetic nor functional-group

clustering are Porites astreoides [MV] grouping with Montastraea faveolata [MO], and

the three species group of Favia fragum [MO], Siderastrea radians [MO] and

Stephanocoenia intercepta [MV]. The two species Agaricia fragilis and Porites porites

did not cluster with any species.

Analysis of similarity (ANOSIM; Table 2.02) determined that the BV and MO

functional groups were not significantly dissimilar in their distribution patterns in

multidimensional space, but only marginally so (p = 0.06). The clusters formed by the

MO and MV functional groups were not significantly dissimilar, at p = 0.1.

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Figure 4.05. Dendrogram of Bray-Curtis similarities of species and functional groups

clustered according by group-averaging. Similarities per pair of species were

based on square-root transformed relative abundance data averaged across

sites located on replicate reefs and over different aspects, depths and

distances from shore.

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Figure 4.06. Multidimensional scaling diagram (MDS) of square-root transformed

relative abundance data for coral species averaged across sites located on

replicate reefs and over different aspects, depths and distances from shore.

The symbol used for each species indicates its functional group membership.

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Table 4.02. Results of an ANOSIM analysis of the distinctness in clustering of each

functional group.

One-Way Analysis

Global Test

Sample statistic (Global R): 0.395

Significance level of sample statistic: 2.5%

Number of permutations: 999 (Random sample from 120120)

Number of permuted statistics greater than or equal to Global R: 24

Pairwise Tests

R Significance Possible Actual Number >=

Groups Statistic Level % Permutations Permutations Observed

MV, PV 0.111 50.0 4 4 2

MV, MO 0.290 10.7 84 84 9

MV, BV -0.222 100.0 10 10 10

PV, MO 1.000 14.3 7 7 1

PV, BV -0.333 100.0 4 4 4

MO, BV 0.420 6.0 84 84 5

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Similarity among sites in species assemblages

The 60 sites surveyed across aspects, depths and zones were grouped according to

how similar they were in terms of shared species, based on the relative abundance data.

Sites were compared in order to see whether sites that shared aspect, depth or zone also

shared species assemblage structure. The resultant matrix of Bray-Curtis site similarities,

based on square-root-transformed relative abundance data for species, was graphed into

both a dendrogram (not shown due to its complexity) and MDS. Linear boundaries of

equal similarity were produced, enclosing similar sites within the two-dimensional

graphic of multidimensional species state-space. Only the 58% iso-similarity boundary is

illustrated, for clarity and because the site clusters generated by this one iso-similarity

boundary were the most meaningful, as determined below.

In order to determine whether there were meaningful patterns in the manner that the

species relative abundance data clustered sites, three separate one-way and two-way

analyses of similarity (ANOSIM) of sites were carried out. Sites were compared

according to:

1. Aspect within depth and zone

2. Depth

3. Zone

Sites were also graphed onto the three separate MDS diagrams using symbols that

represented either aspect, depth or zone of each site. These three graphs are illustrated

below.

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1) Aspect

Figure 4.07 illustrates the MDS of sites illustrated with icons that indicate Aspect. All

of the sites located on the Tops of patch reefs (grey squares) are grouped in the upper

cluster (A), along with sites with other aspects (the two triangle icons). Conversely, only

sites that had either a Northern or Southern aspect are within the lower two clusters (B

and C). There are no apparent clusters of northern vs. southern-facing sites. A series of

Analyses of Similarity (ANOSIMs) of the factor Aspect across each depth within each

zone confirmed this visual interpretation of the data. The tops of patch reefs possessed

significantly different assemblages of coral species than either side of the same reef. The

north and south sides of each patch reef, however, were only found to differ significantly

in assemblage structure in Zone 1 and Zone 3 (Table 4.03 this table does not show the

differences existed between sides in Zone 1 and 3 Table 4.04 shows that Zones 1 2 and

3D had differences between the sides I think the lack of a consistent pattern of

differences will allow you to pool the north and south data

The finding that coral assemblages were not dissimilar on opposite sides of patch

reefs across most zones was unexpected. An analysis comparing the amount of light

reaching surfaces with a southern or northern aspect found that significantly more light

should be available to corals on the southern side of a patch reef in Bermuda than on the

northern side of the same reef. It may be that the availability of diffuse light is sufficient

to prevent the occurrence of differences between the two sides of patch reefs in most

zones. On the other hand, it may be that the lagoonal corals are obtaining the majority of

their energy via heterotrophy instead of autotrophy, and thus the coral assemblages on

each site are not structured by light availability or the zoox are sufficiently adapted (more

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pigments per cell) or more abundant (cells per mL or cm2 of coral tissue) that the coral is

not penalized for the reduced light levels. Just have to be above saturating light levels,

which may be only about 1/3- ½ incoming radiance for some zoox. Get some refs on this.

As a third alternative, perhaps the metric of relative abundance that was used resulted in

data that were not powerful enough (you needed more transects per “site”). for the

detection of differences in the assemblage structure between the north and southern

flanks of reefs. However, since tops of reefs in each zone were consistently found to

differ significantly from that of both flanks but you had 8 transects compared to 4 on

either flank, it seems likely that the relative abundance data should provide sufficient

power for the complete analysis.

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Figure 4.07. MDS of square-root transformed relative abundance data of species for all

sites. Sites are represented by one of three icons depending upon the aspect

which characterized that site. S: Southern aspect; T: Top of reef (i.e. vertical

aspect); N: Northern aspect.

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Table 4.03. ANOSIM table for the factor Aspect across all sites, including the results of

pairwise post-hoc tests.

Global Test for Aspect

Sample statistic (Global R): 0.098

Significance level of sample statistic: 0.1%

Number of permutations: 999 (Random sample from a large number)

Number of permuted statistics greater than or equal to Global R: 0

Pairwise Tests

R Significance Possible Actual Number >=

Groups Statistic Level % Permutations Permutations Observed

S, T 0.181 0.1 Very large 999 0

S, N -0.001 43.6 Very large 999 435

T, N 0.198 0.1 Very large 999 0

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Table 4.04. Significance levels of separate ANOSIM tests comparing similarities between

reef sites located on the south versus north sides of reefs in each zone and at

different depths. Sites on the sides of reefs are labeled as follows: S: Shallow;

M: Mid-depth; D: Deep.

Zone and

Depth p

1 0.009

2 0.046

3S 0.591

3D 0.008

4S 0.103

4D 0.349

5S 0.263

5D 0.288

6S 0.119

6M 0.417

6D 0.834

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2) Depth

Figure 4.08 shows the MDS of sites illustrated with icons that indicate Depth. An

obvious pattern can be seen in which sites are sorted by depth in the MDS diagram,

(which is derived solely from species abundance data). ANOSIM revealed that globally

sites clustered to a significant manner when categorized according to the factor Depth

Pairwise comparisons indicate that sites categorized by virtually all depths were

significantly clustered (Table 4.06). Only the species assemblages at depths 2 to 4 m, and

5 to 7m depths were not grouped significantly (Table 4.05). Light and wave energy both

decline with water depth, and these two physical factors are probably responsible for the

strong zonation patterns across depths in the coral species.

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Figure 4.08. MDS of square-root transformed relative abundance data of species for all

sites depths on all reefs. Sites are represented by one of ten icons that

indicate the average depth in meters of that site. Darker icons represent

deeper sites. The number in the legend next to each icon is the average depth

in meters of that site.

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Table 4.05. ANOSIM table for the factor Depth, calculated from data at each depth from

across all sites.

Global Test for Depth

Sample statistic (Global R): 0.382

Significance level of sample statistic: 0.1%

Number of permutations: 999 (Random sample from a large number)

Number of permuted statistics greater than or equal to Global R: 0

Table 4.06. Significance levels of pair-wise tests comparing similarities between reef

sites located on different depths.

Pairwise tests: Significance Level

2 3 4 5 6 7 8 9 12

2                  

3 0.002                

4 0.321 0.627              

5 0.001 0.001 0.001            

6 0.001 0.001 0.001 0.065          

7 0.001 0.001 0.001 0.171 0.003        

8 0.001 0.001 0.001 0.001 0.001 0.036      

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9 0.002 0.001 0.78 0.001 0.001 0.001 0.001    

12 0.001 0.002 0.001 0.001 0.001 0.001 0.001 0.096  

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3) Zone

There is also an obvious pattern in which sites are sorted consecutively by zone across

the field of points in the MDS diagram (Figure 4.09), which is derived solely from

species abundance data. Sites from Zones 1 and 2 are chiefly located in the lower right

cluster, sites from Zone 3 and 4 are predominantly located in the upper cluster, and sites

from Zones 5 and 6 are located in either the upper or lower left cluster. An ANOSIM of

Zone (Table 4.07), regardless of aspect or depth of each site, determined that all zones

were significantly different in terms of coral assemblage composition, except pairwise

comparisons between Zones 1 and 2, and Zones 1 and 3. Zones 2 and 3 were significantly

different, however.

Table 4.08 displays the results of a SIMPER similarity analysis for each zone.

SIMPER analysis examines the contribution of each species to the average resemblances

between zones (Clarke et al. 2006). Generally it can be seen that the two Madracis

species (which are in the Branched Viviparous functional group) dominate inshore zones,

whereas the Massive Viviparous species Porites astreoides and the Massive Oviparous

species Montastraea faveolata, Diploria strigosa and Diploria labyrinthiformis dominate

offshore zones. One adaptive mechanism by which these five massive corals can coexist

is examined in Section B, below.

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Figure 4.09. MDS of square-root transformed relative abundance data of species for all

sites. Sites are represented by one of six icons depending upon the zone that

site was located within. Darker icons represent sites further from shore. The

number in the legend next to each icon represents the zone the site was in,

with Zone 1 being closest to shore and Zone 6 furthest from shore.

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Table 4.07. ANOSIM table for the factor Zone across all sites.

Global Test

Sample statistic (Global R): 0.622

Significance level of sample statistic: 0.1%

Number of permutations: 999 (Random sample from a large number)

Number of permuted statistics greater than or equal to Global R: 0

Pairwise Tests

R Significance Possible Actual Number >=

Groups Statistic Level % Permutations Permutations Observed

1, 2 1.000 10.0 10 10 1

1, 3 1.000 6.7 15 15 1

1, 4 0.818 4.8 21 21 1

1, 5 0.929 2.8 36 36 1

1, 6 0.833 3.6 28 28 1

2, 3 0.722 2.9 35 35 1

2, 4 0.549 1.8 56 56 1

2, 5 0.895 0.8 120 120 1

2, 6 0.821 1.2 84 84 1

3, 4 0.35 4.8 126 126 6

3, 5 0.763 0.3 330 330 1

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3, 6 0.792 0.5 210 210 1

4, 5 0.589 0.1 792 792 1

4, 6 0.617 0.2 462 462 1

5, 6 0.522 0.1 1716 999 0

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Table 4.08. SIMPER analysis of the dominant species that differ between zones across

the Bermuda Platform.

Zone 1Average similarity: 71.57

Species Av.Abund Av.Sim Sim/SD Contrib% Cum.%MDEC 2.65 25.70 3.73 35.91 35.91MMIR 2.13 17.96 3.49 25.10 61.01SRAD 0.99 8.73 10.06 12.19 73.20FAV 1.12 7.07 2.59 9.88 83.08MFAV 0.78 4.61 1.02 6.43 89.52MCAV 0.66 2.13 0.80 2.98 92.49

Zone 2Average similarity: 68.78Species Av.Abund Av.Sim Sim/SD Contrib% Cum.%MMIR 3.38 20.96 2.13 30.48 30.48MDEC 2.47 17.48 2.93 25.41 55.89PAST 1.82 10.65 3.72 15.49 71.37MFAV 1.48 8.03 2.47 11.68 83.05DSTRIG 0.77 4.01 1.48 5.83 88.88MCAV 0.75 2.48 0.76 3.60 92.49

Zone 3Average similarity: 84.82Species Av.Abund Av.Sim Sim/SD Contrib% Cum.%MMIR 3.79 24.55 10.50 28.94 28.94MDEC 2.79 17.20 3.31 20.28 49.22PAST 2.91 16.80 3.30 19.80 69.02MFAV 2.30 9.98 2.72 11.76 80.78MCAV 1.27 5.74 158.50 6.77 87.55AFRAG 0.67 4.74 1.80 5.59 93.14

Zone 4Average similarity: 81.88Species Av.Abund Av.Sim Sim/SD Contrib% Cum.%MMIR 2.94 17.31 5.97 21.14 21.14PAST 2.78 14.40 3.28 17.59 38.73MDEC 2.47 12.86 2.11 15.70 54.43MFAV 2.49 12.11 3.29 14.79 69.22DSTRIG 1.65 7.92 2.75 9.68 78.90MCAV 1.23 6.43 3.17 7.85 86.75MFRANK 1.12 4.18 1.39 5.10 91.85

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Table 4.08 continued.

Zone 5Average similarity: 74.30Species Av.Abund Av.Sim Sim/SD Contrib% Cum.%PAST 2.17 13.18 1.50 17.74 17.74MFAV 2.05 13.01 7.51 17.51 35.25MDEC 2.25 12.37 1.55 16.65 51.90MCAV 1.58 6.89 1.86 9.27 61.18MFRANK 1.37 6.68 1.71 8.99 70.16DSTRIG 1.13 6.42 1.23 8.64 78.81DLAB 0.98 5.91 1.58 7.96 86.77MMIR 0.86 4.16 1.17 5.60 92.37

Zone 6Average similarity: 73.62Species Av.Abund Av.Sim Sim/SD Contrib% Cum.%PAST 2.01 14.07 3.17 19.11 19.11MDEC 1.31 11.11 6.28 15.09 34.20MCAV 1.28 10.00 1.99 13.58 47.78MFAV 1.58 9.43 2.27 12.81 60.59MFRANK 1.37 7.82 1.17 10.63 71.22DLAB 1.06 6.16 1.55 8.37 79.59DSTRIG 0.95 5.46 1.16 7.41 87.00STEPH 0.65 4.41 1.04 5.99 92.99

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Aspect, Zone and Depth

The aspect, depth and zone of a site interact to generate the cluster pattern Figs 4.07 –

4.09). The tops of sites from all zones are in the upper cluster (Figure 4.10). The sites

located on the sides of reefs in Zones 1 through 4 are located in the lower right cluster

(Figure 4.10), and sites located on the deeper sides of reefs in Zones 5 and 6 are located

in the lower left cluster (Figure 4.10). Light and wave energy is higher on the tops of the

lagoonal reefs, while deeper sites are darker and have slower current flow. Reefs

nearshore have higher sediment than reefs offshore. Thus B sites are darker but with

higher suspended sediment than A, and C sites are darker, deeper and with less suspended

sediment than both A and B.

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Figure 4.10. The sites surveyed across the Bermuda platform cluster into three groups

with different coral species composition, which also match three different

environmental conditions. The three groups are (A) Tops of all reefs, (B)

deeper sites in zones 1-4 and (C) deeper sites in zones 5-6.

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Distribution patterns of coral species

Frequency of occurrence

All corals as a group

The average frequency of occurrence (RF) of any coral at each site is plotted as dot

size onto the same MDS graph used above (Figure 4.11) The same data was also plotted

using the standard format for a line graph (Figure 4.12A) and also as a “bubble” graph

(Figure 4.12B). These three graphs allow one to examine how corals overall were

distributed across the patch reefs located over the lagoon. All three graphs illustrate that

corals occurred frequently on many shallow sites across most zones. The smaller sized

circles in the lower left cluster indicate that corals occurred less frequently at sites that

were located on the sides of patch reefs far from shore.

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Figure 4.11. MDS of square-root transformed frequency of occurrence data of all coral

species for all sites, as in the three figures above. In this and all following

MDS diagrams throughout this section, the size of each circle represents the

number of frames containing any coral, averaged across transects per site,

according to the scale in the legend.

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A,

B.

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Figure 4.12. The average proportion of frames with any coral present across all sites,

illustrated as a line graph per site per reef (A) and as a bubble graph per

depth and zone (B).

Branched Viviparous Corals

The frequency of occurrence of all branching viviparous corals as a group, and of

each species of BV coral separately, are plotted in Figs 4.13 to 4.17 below. As a group,

the BV corals occur most frequently on the sides of the reefs in zones 1 and 2, and occur

less often on reefs further from shore. The two species of Madracis each separately share

this basic distribution pattern, with a much greater likelihood of occurring in frames

sampled on the sides of patch reefs rather than on the tops, and greater numbers of

occurrences observed nearshore compared with offshore (Figs 4.13 B, 4.13C, 4.15, 4.16).

In comparison, the species Porites porites differs from the Madracis species in its

distribution, and was only observed to occur on the tops of reefs and never on the sides.

Porites porites was also much rarer than the Madracis species across all reef sites overall

(Figs. 4.13D, 4.17).

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Figure 4.13. Four MDS graphs of square-root transformed frequency of occurrence data

of Branched Viviparous species as a group, and for M. decactis, M. mirabilis

and P. porites corals separately for all sites.

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Branched Viviparous Functional Group

A.

B.

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Figure 4.14. The average proportion of frames with corals of the Viviparous Branching

(VB) functional group present across all sites, illustrated as a line graph per

site per reef (top) and as a bubble graph per depth and zone (bottom).

Madracis decactis

A.

B.

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Figure 4.15. The average proportion of frames with corals of the species Madracis

decactis present across all sites, illustrated as a line graph per site per reef

(top) and as a bubble graph per depth and zone (bottom).

Madracis mirabilis

A.

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B.

Figure 4.16. The average proportion of frames with corals of the species Madracis

mirabilis present across all sites, illustrated as a line graph per site per reef

(top) and as a bubble graph per depth and zone (bottom).

Porites porites

A.

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B.

Figure 4.17. The average proportion of frames with corals of the species Porites porites

present across all sites, illustrated as a line graph per site per reef (top) and as

a bubble graph per depth and zone (bottom).

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Foliose and Plating Viviparous Corals

The only coral in the foliose and plating (FP) functional group that was observed

within the lagoon was the species Agaricia fragilis. The distribution of A. fragilis was

found to have little similarity to the distribution of the other corals assessed using Bray-

Curtis similarity analysis (Figs 4.18, 4.19). A. fragilis was observed primarily on the

deeper flanks of patch reefs in Zones 1–3. Its predominance in low light environments

fits the prediction for A. fragilis as a stress-tolerant species adapted to areas of low

current flow, low light availability and also low total coral cover.

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Figure 4.18. MDS graph of square-root transformed frequency of occurrence data of the

coral species Agaricia fragilis, the only member of the Foliose and Plating

Viviparous (FP) functional group observed in the North lagoon in Bermuda

in this study. Circles size represents the average number of frames

containing A. fragilis per site out of 20, as in the legend on the side of each

MDS graph. Note the different scale used in this MDS for A. fragilis

compared with the other MDS diagrams in this section.

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Agaricia fragilis

A.

B.

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Figure 4.19. The average occurrence frequency of the species Agaricia fragilis across all

sites, illustrated as a line graph per site and reef (top) and as a bubble graph

per depth and zone (bottom).

Massive Viviparous corals

When the frequency of occurrence of all species of the Massive Viviparous functional

group, and each member species, Favia fragum, Porites astreoides and Siderastrea

radians, are plotted at each site across the MDS diagram (Figure 4.20) we can see that the

distribution pattern of the MV group (Figure 4.20) is primarily driven by the distribution

of P. astreoides (Figure 4.20C; 4.22). P. astreoides is most abundant in the upper cluster,

which represents the tops and shallow sides of reefs. Sites in the lower two clusters,

which are derived from reef sites located on the deeper sides of patch reefs, are

characterized by much less P. astreoides.

Favia fragum is less abundant and is also primarily found on the tops of reefs (Figs.

4.20B; 4.22). Alternatively, S. radians appears equally distributed across reef sites across

the three clusters (Figure 4.20D; 4.24), with no obvious pattern related to depth, zonation

or aspect.

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Figure 4.20. Four MDS graphs of square-root transformed data of occurrence frequency

by Massive Viviparous species as a group, and for F. fragum, P. astreoides

and S. radians corals separately, for all sites. Circle size represents the

average number of frames containing each species or functional group per

transect per site out of 20, as in the legend on the side of each MDS graph.

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Massive Viviparous functional group

A.

B.

Figure 4.21. The average proportion of occupied frames per transect with corals

belonging to the Massive Viviparous functional group present across all

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sites, illustrated as a line graph per site per reef (top) and as a bubble graph

per depth and zone (bottom).

Favia fragum

A.

B.

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Figure 4.22. The average proportion of frames with corals of the species Favia fragum

present across all sites, illustrated as a line graph per site per reef (top) and as

a bubble graph per depth and zone (bottom).

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Porites astreoides

A.

B.

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Figure 4.23. The average proportion of frames with corals of the species Favia fragum

present across all sites, illustrated as a line graph per site per reef (top) and

as a bubble graph per depth and zone (bottom).

Siderastrea radians

A.

B.

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Figure 4.24. The average proportion of frames with corals of the species Siderasterea

radians present across all sites, illustrated as a line graph per site per reef

(top) and as a bubble graph per depth and zone (bottom).

Massive Oviparous corals

As a group, massive oviparous corals were most abundant on the tops of reefs (upper

cluster) and on the sides of the reefs in Zones 5 and 6 (left cluster; Figs. 4.25A, 4.26).

Only the species M. faveolata (Figs. 4.25C, 4.27) displayed a similar distribution pattern

to the pattern displayed by the functional group overall, however. The two species M.

cavernosa and M. franksi, which were found to be similar at a 75% level using Bray-

Curtis analysis, did display obvious differences in distribution when graphed. M.

cavernosa was most abundant on the sides of nearshore reefs (right cluster) and on the

tops of reefs (top cluster; Figs. 4.25B, 4.26), while M. franksi was most abundant on the

sides of the offshore reefs (Cluster C; Figs 4.25D, 4.28).

The two Diploria species exhibit similar patterns of abundance (Figs 4.25E, 4.25F,

4.29, 4.30), with most corals occurring on the tops of reefs in the upper cluster, and few

species on the flanks in the other two habitat clusters. Some differences in distribution

between the two Diploria species are apparent, however. D. labyrinthiformis is less

abundant than D. strigosa overall, and appeared to be more common on the sides of reefs

offshore (left cluster) relative to D. strigosa.

Stephanocoenia intersepta displayed the most distinct pattern of abundance relative to

the other MO corals (Figs. 4.25G; 4.31). Its highest abundance was not on the tops of

reefs in Zones 3 and 4 like most MO coral species, but instead on the sides of reefs in

zones 5 and 6.

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Figure 4.25 . Seven MDS graphs of square-root transformed relative abundance data of

(a) Massive Oviparous species as a group, and for (b) M. cavernosa, (c) M.

faveolata, (d) M. frankesi, (e) D. labyrinthiformis, (f) D. stigosa and (g) S.

intersepta separately for all sites.

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Massive Oviparous functional group

A.

B.

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Figure 4.26. The average proportion of frames with corals of the Massive Oviparous

(MO) functional group present across all sites, illustrated as a line graph per

site per reef (top) and as a bubble graph per depth and zone (bottom).

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Montastraea cavernosa

A.

B.

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Figure 4.27. The average proportion of frames with corals of the species Montastraea

cavernosa present across all sites, illustrated as a line graph per site per reef

(top) and as a bubble graph per depth and zone (bottom).

Montastraea faveolata

A.

B.

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Figure 4.28. The average proportion of frames with corals of the species Montastraea

faveolata present across all sites, illustrated as a line graph per site per reef

(top) and as a bubble graph per depth and zone (bottom).

Montastraea franksi

A.

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B.

Figure 4.29. The average proportion of frames with corals of the species Montastraea

franksi present across all sites, illustrated as a line graph per site per reef

(top) and as a bubble graph per depth and zone (bottom).

Diploria labyrinthiformis

A.

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B.

Figure 4.30. The average proportion of frames with corals of the species Diploria

labyrithiformis present across all sites, illustrated as a line graph per site per

reef (top) and as a bubble graph per depth and zone (bottom).

Diploria strigosa

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A.

B.

Figure 4.31. The average proportion of frames with corals of the species Diploria

strigosa present across all sites, illustrated as a line graph per site per reef

(top) and as a bubble graph per depth and zone (bottom).

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Stephanocoenia intersepta

A.

B.

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Figure 4.32. The average proportion of frames with corals of the species Stephanocoenia

intersepta present across all sites, illustrated as a line graph per site per reef

(top) and as a bubble graph per depth and zone (bottom).

Standard measures for coral reefs

In the section below I examine how average percent cover of the entire coral

assemblage, and each functional group separately, as well as species richness and

functional group richness vary over the six zones. Due to time constraints only the tops of

three replicate reefs in each zone were surveyed. The data from these three surveys are

presented first. On two of the three replicate reefs, both the tops and south sides were

surveyed for the six factors. The data that includes the change in coral assemblages

across the sides of patch reefs are described in the section following the one below.

Section 1: Tops of Reefs Only

A. Average Percent Coral Cover

The average percent coral cover for all corals as a group (which I term “Total Coral

Cover” or TCC below) peaked in the middle of the north lagoon in Zone 3 (Figure

4.33A). TCC appeared substantially lower in Zone 1, nearshore. TTC also declined

progressively with distance from shore across Zones 4 to 6. Additionally there appeared

to be substantial variability in TCC among reefs within each region. Two-way ANOVA

confirmed that the interaction between zone placement and replicate reefs was highly

significant, at p < 0.001 (Table 4.09A). Since wave energy has been shown to be higher

offshore (Mills et al. 2004), and suspended sediment load higher nearshore (Toro Farmer,

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unpublished data) it may be that the central reefs have higher TCC because the corals

there are exposed to less levels of disturbance or stress than corals on reefs either

offshore or nearshore.

B. Species Richness

The number of coral species on the top of reefs peaked in Zone 2 (Figure 4.33B). The

variability in species richness between sites was highest in Zone 1 and declined on sites

further from shore. Two-way ANOVA confirmed that the interaction of zone placement

and replicate was highly significant, at p = 0.006 (Table 4.09B). This pattern, in which

nearshore sites display higher variability than offshore sites, was hypothesized by

Murdoch and Aronson (1999), and reiterated by Pandolfi (2002). Zone 2 represents an

area in close proximity to the south shipping channel, as well as near the island of

Bermuda. It may be that disturbances are more frequent in this area and that the

mechanisms of the Intermediate Disturbance Hypothesis (Grime 1977; Connell 1978) are

operating to promote coral richness there.

C. Functional Group Richness

Functional group richness (Figure 4.33C)for the three predominant functional groups

was lowest offshore, reached a plateau across sites 2–4, and then declined again in Zone

1. Two-way ANOVA confirmed that the interaction of zone placement and replicate was

highly significant, at p = 0.005 (Table 4.09C).The analysis of each species in the section

above and for percent cover of each functional group illustrates that the decline in FG

richness offshore is due to a decline in the abundance and biomass of the Branched

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Viviparous functional group. The decline in Zone 1, alternatively, is due to a decline in

the abundance and biomass of the two mound-shaped or massive functional groups.

D. Percent cover of the Branched Viviparous Functional Group

Branched viviparous corals are predicted to be both competitive and ruderal (C-R),

following the AST model of Grime (1977). As such they should be capable of tolerating

disturbance to at least a moderate degree, and also capable of dominating habitats when

released from competition (See Ch. 1). Branched viviparous corals peaked in abundance

on some of the reefs in Zone 2 in this analysis (Figure 4.33D). Sites in all other zones

exhibited substantially lower cover of the BV functional group, with virtually zero cover

in Zones 5 and 6. Two-way ANOVA (Table 4.09D) confirmed that the interaction of

zone placement and replicate was highly significant, at p < 0.001. Zone 2 is nearest the

southern shipping channel, which is a source of suspended sediment during summer

months. Others have noted that the branched corals dominate nearshore habitats off North

Shore (i.e. Logan 1988; Mills et al. 2004). It may be that the BV functional group is more

tolerant of suspended sediment than the massive corals in the other functional groups, and

that this tolerance, combined with a lack of competition with the other groups allows the

branched viviparous corals to dominate reefs in Zone 2.

E. Percent cover of the Massive Viviparous functional group

The massive viviparous corals are predicted to be the most tolerant of disturbance. As

such the cover of the MV group was expected to show little variation across sites

regardless of zone. As illustrated in Figure 4.33E, however, the average percent cover of

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this functional group peaked in Zone 4, with lower cover values in zones nearer or further

from shore. Two-way ANOVA confirmed that the interaction of zone placement and

replicate was highly significant, at p < 0.001 for the MV functional group (Table 4.09E).

F. Percent cover of the Massive Oviparous functional group

The massive oviparous corals are predicted to be relatively tolerant to stress but also

to be able to dominate reefs through competitive interactions when resources are

abundant and disturbance levels are low. The MO functional group is predicted to display

low cover on reefs exposed to higher disturbance. In the analysis of percent cover on the

three reefs across the six zones across the North Lagoon of Bermuda, the MO functional

group displayed similarly high values across reefs in zones 3 through 6, with a decline in

cover on reefs in Zones 2 and 1 (Figure 4.33F). Variability between reefs within zones

was minimal in Zone 4, with more variability evident in zones closer or further from

shore. Two-way ANOVA (Table 4.09F) confirmed that the interaction of zone placement

and replicate was highly significant, at p < 0.001.

It may be that the higher levels of turbidity and lower current flow speeds nearshore

caused a decline in survivorship for the large mound-shaped corals in the MO functional

group. Reefs offshore, however, are exposed to much lower levels of sediment, but

higher wave energy. The MO corals should be able to withstand wave energy due to their

morphology, so it is unclear why the percent cover of the MV functional group would not

be highest on reefs furthest from shore

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Figure 4.33. (next page). Average percent coral cover for (A), (B) species richness, (C)

functional group richness as well as (D – F) the average percent cover for

each functional group on the tops of each of three replicate reef sites in each

of the six zones. The data for each site was based on eight transects of 10-m

length. The tops of the reefs of each zone differed in depth, and light

availability at a given depth was reduced nearshore relative to offshore, as

described above.

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A. Total Coral Cover

B. Species Richness

C. Functional Group Richness

D. Branched Viviparous Coral Cover

E. Massive Viviparous Coral Cover

F. Massive Oviparous Coral Cover

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Table 4.09. Results of the 2-way ANOVAs of the six parameters across the 18 reef sites

located on the tops of patch reefs located in three replicate “legs” across six

zones located across the north lagoon in Bermuda.

A. Total Coral CoverSource SS df MS F-ratio p-value ZONE 1.760 5 0.352 50.501 0.000LEG 0.023 2 0.012 1.670 0.192ZONE*LEG 0.612 10 0.061 8.779 0.000Error 0.878 126 0.007

B. Species RichnessSource SS df MS F-ratio p-value ZONE 109.285 5 21.857 15.839 0.000LEG 29.056 2 14.528 10.528 0.000ZONE*LEG 36.111 10 3.611 2.617 0.006Error 173.875 126 1.380

C. FG richnessSource SS df MS F-ratio p-value ZONE 19.951 5 3.990 18.535 0.000 LEG 0.722 2 0.361 1.677 0.191ZONE*LEG 5.861 10 0.586 2.723 0.005Error 27.125 126 0.215

D. Branched Viviparous Coral CoverSource SS df MS F-ratio p-value ZONE 1.518 5 0.304 59.148 0.000LEG 0.065 2 0.032 6.320 0.002ZONE*LEG 0.640 10 0.064 12.466 0.000Error 0.647 126 0.005

E. Massive Viviparous CoverSource SS df MS F-ratio p-value ZONE 0.788 5 0.158 58.255 0.000LEG 0.003 2 0.001 0.553 0.576ZONE*LEG 0.240 10 0.024 8.860 0.000Error 0.341 126 0.003

F. Massive Oviparous CoverSource SS df MS F-ratio p-value ZONE 1.249 5 0.250 29.632 0.000LEG 0.197 2 0.098 11.663 0.000ZONE*LEG 0.544 10 0.054 6.451 0.000Error 1.062 126 0.008

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Standard measures for coral reefs

Section 2: Tops and South Sides of Reefs

A. Average Percent Coral Cover

As in the section above, the average percent cover of the entire coral assemblage (i.e.

TCC; Figure 4.34A) can be seen to vary substantially both across zones and across

replicates within zones. Depth also clearly plays a factor in the total coral cover at a site,

and appears to interact in a complex manner with distance from shore. Coral reefs

nearshore in Zones 1 to 3 display higher cover on the sides of reefs than on the tops of

reefs, while reefs in the zones further from shore display higher cover on the tops of reefs

than on the sides. TCC is highest on the flank of one of the 2 reefs samples in Zone 2.

TCC was found to be lowest on the top of reefs in Zone 1, and at the deepest sites on the

reefs in Zone 6.

Historically researchers in Bermuda have only surveyed the tops of patch reefs found

in the lagoon. As can be seen by comparing Figs. 4.34 and 4.35 to Figure 4.33 from the

last section, surveying only the tops of reefs fails to account for a substantial proportion

of the average percent cover that occurs on these lagoonal reefs. Instead, to truly

represent the condition of Bermuda’s lagoonal reefs, surveys should encompass the full

range of depths that occur across each reef, and over the entire extent of the lagoon.

B. Species Richness

On the reefs surveyed in this project, species richness (Figure 4.34B) can be seen to

vary with depth as well as zone and across replicates within zones in a complicated

manner. Species richness appeared to peak in Zone 3, was found to be lowest on the

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deepest sites in Zone 6. Surveys that only encompass the tops of reefs, as in Section 2

above, fail to uncover these complexities in species richness that occur across the flanks

of lagoonal reefs in Bermuda.

C. Functional Group Richness

The number of functional groups within a site also appears (Figure 4.34C) to be due

to factors that interact across zones, replicates and depths. Functional group richness

appears higher on deeper sites on reefs nearshore than on the tops of reefs. Alternatively,

functional group richness is lower on the tops of reefs offshore than it is on the sides of

the same reefs. Functional group richness peaks in Zones 3 and 4, and is lowest on the

deepest sites in Zone 6. Again, ecologically important patterns in functional group

richness are apparent on the sides of these lagoonal patch reefs that standard survey

techniques would have missed.

D. Percent cover of the Branched Viviparous functional group

The percent cover of the coral species belonging to the Branched Viviparous

functional group was found to peak in Zone 2 (Figure 4.35A). Moreover, percent cover of

this group was consistently higher on the deeper sites than on the tops of reefs in Zone 1

through to Zone 4. The BV functional group displayed low percent cover in Zones 5 and

6 across all depths. Since the BV corals were consistently higher on the sides of patch

reefs than on the tops, it is apparent that standard surveys which only consider the tops of

patch reefs will misrepresent the contribution of the BV coral species to the assemblage

structure of lagoonal corals.

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When the percent cover of each of the member species of the BV functional group are

presented separately (Figure 4.36), it is apparent that the species Madracis mirabilis

contributed the greatest percentage of biomass and thus was responsible for the general

pattern in percent cover that characterized the functional group as a whole. Madracis

mirabilis peaked in Zones 2 with a decline in cover both closer and further from shore. It

also displayed higher cover on the flanks of patch reefs versus on the tops. The sibling

species to Madracis mirabilis, Madracis decactis, displayed a similar distribution and

pattern of biomass, but with lower values overall (Figure 4.36B). Conversely the third

BV coral, Porites porites (Figure 4.36C), displayed a completely different pattern in

terms of percent coral cover. It was found to exhibit the highest percent cover values on

the tops of reefs instead of the flanks like the other BV species. P. porites also displayed

very low values in percent cover, generally being represented by only one point per site.

The species-specific patterns apparent in the percent cover data of these BV coral species

match the patterns displayed by the same species in the MDS analysis described above,

which were based on measures of relative abundance data instead.

E. Percent cover of the Massive Viviparous functional group

The coral species of the Massive Viviparous functional group consistently peaked in

cover on the tops of reefs and was lower on the flanks of the same reefs, regardless of

zone (Figure 4.35). The percent cover of the MV functional group peaked in Zone 3, and

was found to be lower on reefs closer to shore and further from shore. Surveying the tops

of reefs for this functional group would provide meaningful estimates of its functional

role across the lagoon.

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Comparison of the component species of the MV functional group (Figure 4.38)

illustrates that the species P. astreoides is responsible for the general pattern in percent

cover across the lagoon that characterizes the group. P. astreoides peaks in abundance in

Zones 3 and 4, and exhibits higher percent cover on the tops of reefs versus on the deeper

flanks. Favia fragum and Siderastrea radians, alternatively, present very low percent

cover values of 1 or 2 points per site, and appear to occur across depths and zones. These

patterns concur with the patterns apparent in the MDS analysis based on relative

abundance data described in Section 1 above.

F. Percent cover of the Massive Viviparous functional group

The corals that comprise the Massive Viviparous functional group were found to peak

in percent cover on the tops of reefs in Zones 3 to 6, with lower values apparent in Zones

1 and 2, nearer to shore (Figure 4.35). The cover of the MV functional group generally

declined with depth across all zones, but with an alternate pattern occurring on one of the

two replicate reefs in some zones.

The two Diploria species peaked in percent cover on the tops of patch reefs and

displayed lower cover on the sides, across all zones (Figure 4.38). The species Diploria

strigosa exhibited higher cover than D. labyrinthiformis, although both species peaked at

roughly 5% cover on the lagoonal reefs. These co-occurrence patterns of these two

species were found to be very similar, based on relative abundance data (section 1

above), and the percent cover data appears to confirm that these two sister species also

share habitats when biomass is used as a measure.

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The percent cover data for the two species Montastraea frankesi and M. faveolata was

grouped into one variable after it was decided that the discrimination between the two

species in the point count analysis may have been compromised. The M. annularis spp.

category displayed the highest percent cover across reefs, with high variability in cover

apparent across depths, replicate reefs and zones. The congener M. cavernosa was found

to contribute lower percent cover across the region overall. It peaked in cover on the sides

of patch reefs in the middle of the lagoon, with lower values on reefs in Zones 1, 2 and 6.

The species Stephanocoenia intersepta was rarely sampled by point count analysis.

The species was absent from the two sampled reefs in Zone 4, and it peaked in cover in

Zones 1 and 6. It also tended to display higher percent cover on deeper sites on a reef

than on the tops of reefs. The pattern of cover presented by the species Stephanocoenia

intercepta appears substantially different to that of the other species of the MO functional

group. The patterns generated by the percent cover data for all species in the MO

functional group matches the patterns determined by relative abundance data as described

in Section 1 above.

G. Percent cover of the Foliose and Plating Viviparous functional group

The one species of the FP functional group that was sampled across the lagoon was

the plating species Agaricia fragilis (Figure 4.35). It was only represented in the percent

cover data by a few points or less per site, and always on the deeper sites on inshore reefs

located in Zones 1 to 3. Observations while diving found that, while not represented by

point count data, the species A. fragilis was only observed on the tops of patch reefs in

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Zones 1 and 2, and elsewhere generally within caves and in the shadows of overhanging

ledges.

Figure 4.34. (Below) Percent cover, species richness and functional group richness of

corals surveyed on sites located on the tops and southern flanks of patch

reefs. Two replicate reefs were sampled across six zones. T: Tops; S: Sides.

Numbers represent depths in feet [and will be converted to meters and make

larger!].

Figure 4.35. (Below) Percent cover of the Branched Viviparous, Massive Viviparous and

Massive Oviparous functional groups of corals surveyed on sites located on

the tops and southern flanks of patch reefs. Two replicate reefs were

sampled across six zones. T: Tops; S: Sides. Numbers represent depths in

feet [and will be converted to meters].

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Figure 4.36. Percent cover of the three species of Branched Viviparous functional group.

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Figure 4.37. Percent cover of Agaricia fragilis, the one species of the Foliose and Plating

functional group found within the lagoonal sites surveyed.

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Figure 4.38. Percent cover of the three species of Massive Viviparous functional group.

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Figure 4.39 A-B Percent cover of the two of the five species of Massive Oviparous

functional group.

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Figure 4.39 C-E. Percent cover of the three other species of Massive Oviparous

functional group.

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DISCUSSION

Species and functional group distributions across sites

In the investigation regarding whether species that were members of the same

functional groups shared distribution patterns in terms of occurrence, the MDS of coral

species based on relative abundances across sites fit a pattern indicating nested functional

groups across habitat types, (Figure 1.07). This mixed pattern was generated because

some, but not all, species within each functional groups shared similar distribution

patterns across sites. In each functional groups there was a group of species that shared

habitats, with a small number of species displaying low coverage, relative abundance and

no clear preference or occurrence within particular habitats. For instance, the BV coral

Porites porites differed from the other species of Branched Viviparous corals in both

habitat and biomass. In a similar manner, the MO corals Favia fragum and Siderastrea

radians were most similar to the MV coral Stephanocoenia intersepta, in that all three

species were relatively rare, exhibited low coverage , and did not show a clear preference

for either the tops of reefs nor the deeper sites. Nor did these three species show a

preference for reefs inshore nor offshore.

Of the species within functional groups that did share distribution patterns, and thus

high levels of Bray-Curtis similarity, most pairs were composed of congeneric species.

This pattern in which species that share phylogenetic heritage also share habitats implies

that the environmental tolerances of the sibling species act to control their distribution to

a greater degree than intergeneric competition. One mechanism by which sister species

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could co-occur within habitats include a priority effect in which each species has an equal

likelihood of occurring within a small patch and each can prevent its congener from

removing it (Brown et al. 2002) . Alternatively it may be that, since coral cover on many

of the sites surveyed is less than 50%, competitive interactions are rare and the effects of

competition weak across the lagoon and that environmental conditions limit the longevity

of all colonies. If so then continual recruitment by all species would allow persistence

across the lagoon despite short life spans among individuals of each species. Statistical

tests that can check for the pattern in which species share habitats at a larger scale, while

rarely sharing patches within habitats could be used to determine whether intergeneric

competition operates in the species that showed shared distributions in the Bermuda

lagoon.

The occurrence of species within functional groups that possessed disparate

distribution patterns represents a result that is contrary to the predictions of the AST

(Grime 1979). Within all three functional groups there were some inter-group

distributional differences between species that indicate that the AST theory has some

limitations in its ability to predict species distributions. Within the MO functional group,

the two Diploria species appeared to dominate the tops of reefs, while Montastraea

species were abundant on both the tops and sides of reefs. Conversely Stephanocoenia

intersepta was primarily found at the deepest parts of offshore reefs. Similarly the BV

coral P. porites was located on the tops of reefs while the two Madracis species were

found on the flanks of patch reefs. Porites astreoides also dominated the tops of reef

while S. radians, another MV coral, typically occurred at the base of reefs. In all three

functional groups it appears as if each functional group has member species that fulfill

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their functional role within a particular depth, with different species representing each

functional group at a different depth. Such a distribution pattern may be indicative of the

role of inter-group competition in limiting the membership of species within a functional

group to the same depth habitat, while shared physiological traits concurrently result in

shared life-history traits and functional responses across depths by members of the same

functional group.

Percent coral cover per functional group

In the North Lagoon of Bermuda, different functional groups of corals varied in

relative abundance, percent cover and in occurrence across a range of habitats in a

manner that supports some of the hypotheses of the modifies AST presented in Chapter 1.

The Massive Oviparous (MO) and Branched Viviparous (BV) functional groups were

characterized in Ch. 1 as stress-tolerant–competitive and ruderal–competitive,

respectively. As such both groups were predicted to dominate particular habitats in the

absence of the BO functional group, which is predicted to be the most competitive, but

which is not found in Bermuda. Alternatively, the Massive Viviaparous (MV) and FP

(Foliose and Plating) functional groups were predicted to be ruderal and stress-tolerant,

respectively. Both of these groups are predicted to not dominate habitats in terms of

abundance or biomass, although for different functional reasons. The MV functional

group is predicted to allocate resources to reproduction over biomass accumulation as a

means of surviving the effects of competition and disturbance. Conversely the FP

functional group is predicted to occur in habitats characterized by low levels of light

where disturbances and competitive interactions are rare.

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Management issues

Previous research on cross-lagoonal patterns of coral species distributions has been

limited to only four locales: the nearshore patch reefs, the outer lagoonal reefs at Crescent

and Three Hill Shoals, the rim reefs around North Rock and the 30-ft forereef (Logan

1988; Smith et al. 2003; Jones 2007). The previous interpretations of the data from these

locations paint the picture that coral cover and diversity increases in a fairly linear

manner from nearshore to offshore. This simple gradient in biomass and diversity is

hypothesized to be due to the negative influence of factors created by the island, such as

sediment or temperature extremes. However, the previously surveyed areas are separated

by large expanses of reef that have never been assessed scientifically. As such, the

precision of this historical research is rather coarse, and more complex patterns of

abundance, biomass and diversity may in fact exist across the North Lagoon. Since I

surveyed replicate reefs over six consecutive zones across the lagoon, the intensive

sampling represented by the current study should provide a more accurate depiction of

the condition of the coral assemblages in question.

In terms of functional effects, both the MO and BV functional groups provide the

most coral cover across the Bermuda lagoon, although in different zones. All functional

groups of corals possess a range of different characteristics, and management actions that

promote the survivorship of one functional group may inhibit the survival of species

belonging to other groups. In the same manner that botanists farm or garden trees in a

different way than they tend grasses or herbs, coral reef managers and scientists need to

consider the functional responses of each functional type of coral, and not treat all corals

as functionally equivalent in response or effect.

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While the species of the MV functional group does not provide much coral cover, its

component species are highly fecund and are the most likely to recruit to newly created

habitat, if water quality and other conditions are appropriate. The BV and MO corals

recruit more rarely but may rely on similar cues as the MV functional group. As such the

MV functional group may be a useful species for indicating the relative intensity of

disturbance within a habitat, and also the relative suitability of the area for recruitment by

species belonging to all functional groups of coral.

The highest percent cover, diversity and relative abundance of corals was observed to

be within Zones 3 and 4, which have been neglected by previous researchers. These reefs

are located with the North Coral Reef Preserve and so are legally protected,. The reefs are

also in close proximity to the south shipping channel, however, and as such are at a

greater risk to environmental impact compared with most reefs in Bermuda.

This project also determined that the coral assemblages found on the flanks of the

lagoonal patch reefs possess higher coral cover and diversity than the tops of the reefs.

Most coral research focuses on the tops of patch reefs, due to the historical focus on

forereef sites in which flanks do not exist. Research and management of the lagoonal

reefs in Bermuda, and presumably elsewhere, may be driven by erroneous data unless the

sides of the reefs are considered.

The deeper reef sites in Zone 6 were characterized by low coral abundance and

percent cover, despite the proximity to the open ocean, the higher availability to light

compared to sites at the same depth nearshore, and a lower range of temperature

variability. The cause for the low biomass and species richness in this habitat is not

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obvious, and may have been due to some form of disease or anthropogenic disturbance

heretofore unrecorded.

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CHAPTER 5: SUMMARY, CONCLUSIONS AND RECOMMENDATIONS

In this dissertation I modified the Adaptive Strategies Theory, originally developed by

Grime (1977) for terrestrial plants, by removing confounding variables from the visual

model. The original Adaptive Strategies Theory relied strongly on a ternary model

showing the range of habitat characteristics across which species could adapt. However,

this ternary model confounded the independent variables of resource availability and

disturbance with the dependent variable of competition. I restructured the model as a two-

dimensional box across which only the two independent variables of resource availability

and disturbance were plotted. By modifying the model in this way, I was better able to

consider the varying levels of resource gain and loss, and thus use resource economics

theory to predict adaptive strategies. I then illustrated how the necessary trade-offs

required to cope with differing rates of resource gain and loss determine the range of

physiological and behavioral responses exhibited by an organism across habitat types.

I applied the refined theory to Caribbean reef corals. Corals were sorted into

functional groups based on their morphologies and reproductive modes. These two

functional attributes are indicative of the following adaptive strategies:

Branched oviparous corals [BO]: Competitive dominant,

Branched, viviparous corals [BV]: Competitive-Ruderal,

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Massive, viviparous corals [MV]: Ruderal,

Massive, oviparous corals [MO]: Competitive – Stress-Tolerant,

Plating, foliose & solitary corals [FP], (which are only viviparous in the

Caribbean): Stress-Tolerant

In both Florida and Bermuda, these functional groups of corals responded to gradients of

disturbance and stress in predictably different ways.

In Florida, despite the chaotic patterns in biomass displayed by each assemblage of

coral species when separately plotted across reefs, each functional group of corals

responded to direct and indirect gradients of disturbance in a orderly and group-specific

manner. The replacement pattern predicted by Grime (1977), in which each functional

group dominated a particular region of the gradient, was not observed (Figure 5.01A).

Instead, functional groups displayed a nested distributional pattern (Figs. 5.01B; 5.02;

5.03), indicating that negative interactions between functional groups are probably weak .

In Bermuda as well, functional groups displayed a nested pattern across sites located

over a range of depths and geomorphological reef zones (Figs 5.01B; 5.03). As predicted

by the modified Adaptive Strategies theory for nested functional groups (Figs. 5.03;

5.04), branched viviparous corals dominating mid-depth sites inshore which were

characterized by low disturbance by waves and high resource availability from light and

suspended particulate matter. The massive viviparous corals, which were predicted to be

ruderal and thus limited to high resource habitats regardless of disturbance level,

primarily occurring in shallow sites from mid-shelf to offshore. The massive oviparous

corals, which were predicted to be more stress-tolerant and thus occur across a greater

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depth gradient, but a more limited disturbance gradient, dominating both shallow and

deep sites from mid-shelf to offshore.

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Figure 5.01. Diagrams depicting the differing ways in which the abundances of

competitive (C), stress-tolerant (S) and ruderal (R) functional groups of

corals are predicted to vary across habitats located across the range of stress

and disturbance gradients encompassed by the AST model, and depending

on the degree of niche overlap exhibited by each functional group. In all

graphs X and Y represent graphs of abundance relative to levels of

disturbance (X) or stress (Y). Z represents the modified CSR square

diagram, with the zero net growth intercept (ZNGI) illustrated for each

functional group. Graph A matches Grime’s original predictions in which

functional groups are limited to specific regions of adaptive niche phase

space with no overlap in niche boundaries. Graph B represents an alternate

model in which competitive species do not negatively interact with stress-

tolerant or ruderal species. In graph B the functional groups exhibit maximal

overlap in niche boundary. In all models C, S an R functional groups

maintain dominance under differing environmental conditions.

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Figure 5.02. A diagram illustrating how the Zero Net Growth Intercepts (ZNGI) of each

of the predominant functional groups of Caribbean coral found in Florida

and Bermuda are dispersed across the Adaptive Strategies Theory model.

For clarity, the inset shows the distribution for each functional group

separately. The functional groups are distributed in a nested pattern across

habitat types defined by varying rates of resource gain and loss. Letters

represent the functional group occupying each patch as described in the text

above. The dark gray field on the lower right side of the diagram represents

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the range of habitats in which high relative rates of resource loss limit

biomass.

Figure 5.03. The bounded area laid over the modified Adaptive Strategies Theory shown

in Figure 5.02 represents the range of habitat types surveyed in Florida.

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Figure 5.04. The bounded area laid over the modified Adaptive Strategies Theory shown

in Figure 5.02 represents the range of habitat types surveyed in Bermuda.

Numbers represent zones, with 2 closer to shore and 6 furthest offshore.

Letters represent relative depths, as follows: S: Shallow; D: Deep.

In Florida the functional-group approach provided new insights into the manner in

which varying levels of disturbance affected species richness across sites. Massive

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oviparous corals represented approximately 85% of the percent coverage of all corals on

a reef regardless of overall coral cover at a site, whereas other kinds of coral represented

a much smaller proportion of overall coral cover. Despite the small proportions in overall

cover, there were dramatic changes in species presence patterns across sites by the

subordinate functional groups. By categorizing species into functional groups, and then

tabulating the presence or absence of species across reefs ranked according to water

quality or overall coral cover, it was apparent that only the branched viviparous (BV) and

the Foliose and Plating (FP) functional groups lost species across the gradient. The BV

functional group lost species at both high and low total coral cover, whereas the FP

functional group had progressively fewer species as coral cover declined across reefs.

The loss of stress-tolerant species such as those in the FP group was predicted by the

modified Adaptive Strategies Theory.

When species were aggregated according to shared habitat in Bermuda, species from

the same genus co-occurred in almost every case. This implies that these closely related

species also share many functional traits and yet still coexist in many habitats. There are a

number of strategies by which these closely related species may coexist, including:

1. The related species may have either evolved means of avoiding competition,

are ruderal, or are stress tolerant and therefore are probably located within a (neutral;

Hubbell 2001) habitat where competition is so slow as to be negligible.

2. The species compete heavily at the colony scale but are able to mitigate

competition on a smaller or larger scale.

3. The species are so similar that at the population level there is competitive

equilibrium.

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4. The species have slight differences in the location of source and sink

populations across the reef platform.

Each of the above points is a testable hypothesis worthy of further inquiry.

Coral cover on the lagoonal reefs in Bermuda and on the fore-reefs in the Florida

Keys (which were all offshore reefs) did not exceed 30%, and therefore the level of

interaction between coral colonies may have been fairly low. Percolation theory predicts

that randomly distributed, equally-shaped objects will contact a large network of

neighbors as the overall percent cover of the area approaches 60% (With et al. 1997).

This implies that corals in habitats with greater than 60% coral cover should have at least

one contacting neighbor (Figure 5.05), and probably more. Fore-reef sites at 15-m depth

in Bermuda generally have over 75% coral cover (Murdoch unpublished data), and

although the experiments have yet to be done, it may be that competitive exclusion

structures coral assemblages in these high-density coral habitats.

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Figure 5.05. A network of interacting corals on the Bermuda fore reef.

A functional-group approach also provided insight into the manner in which species

were either dominant, subordinate or rare (e.g. Grime et al. 2001) across sites. The fact

that species from one functional group dominate reefs under particular environmental

conditions is contrary to the predictions of the unified neutral theory of Hubbell (2001),

which predicts that all corals are equally likely to dominate any patch. The unified neutral

theory was formulated for plant species within single functional groups and located

within uniform habitats, such as species of hardwood trees within a flat area of tropical

forest, and not for all of the plants that could coexist in the same forest. A key assumption

of this dissertation is that corals as a group are like plants as a group, and furthermore that

the functional groups of corals can be thought of as different “kinds” of corals the same

way we think of trees, shrubs and weeds as different kinds of plants. If branched

oviparous corals are functionally different from branched viviparous corals or any other

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284

coral group, then it is inappropriate to assume that all corals will act in the same manner

under the same conditions, just as we would not expect species of trees and grasses to

share functional responses to the same environmental conditions.

As originally proposed by Grime (1977) the Adaptive Strategies Theory focuses

attention to the corners of the a triangular state-space model where each point of the

triangle represents an extreme habitat and corresponding adapted functional group. IN

this triangular model, intermediate habitats are predicted to be occupied by intermediate

functional groups. If this is the case then functional groups will replace each other from

habitat type to habitat type and the functional diversity across habitats will either be one

(1) or none (0). Contrary to prediction, functional groups of corals showed a nested

pattern of distribution, in which more than one functional group tended to exist within a

habitat. It seems, based on this information, that the C, S and R strategies are

complementary, not exclusionary. Species within the “Competitive Dominant” functional

group may compete heavily with each other, but the effect of competition between

functional groups appears to be reduced by trade-offs in the relative degree to which each

functional group displays the three primary traits of growth, reproduction and defense. If

so, the “Competitive Dominant” functional group appears to be badly named, and should

instead be called the “Growth” functional group.

A bigger problem with the Adaptive Strategies Theory is in defining the degree of

resource availability and disturbance that a habitat possesses without tautologically

referencing the biota about which one is attempting to make predictions. Also, the

assumption that all sources of disturbance or resources can be delimited to one axis is

probably false. In Bermuda each kind of disturbance affected each functional group

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285

differently: the kinds of corals that can tolerate wave damage are different from those that

can tolerate high levels of suspended sediment. Despite this problem, however, the

Adaptive Strategy Theory does accurately predict that a ruderal strategy is required to

persist under both kinds of disturbance, and also that the functional group with a

competitive-dominant strategy would not be able to persist under either form of

disturbance.

The Adaptive Strategy Theory is typically used to predict the assemblage structure of

only one upper-level taxon of organisms, such as plants, macroalgae or reef corals,

ignoring all the other sessile organisms. It seems likely that species from multiple phyla,

or even different kingdoms (i.e. sponges, soft corals, algae, hard corals etc), share

membership in the same environmental functional group. Organisms adapted to the same

habitat type should share functional traits. These larger taxonomic groupings may have

had a long evolutionary history of interphyletic interaction, and, therefore such should be

considered together.

In the end, the weakness of the Adaptive Strategies Theory is that in simplifying

complex ecological data, it also reduces the accuracy of the resulting information. This is

of course also its strength. The Adaptive Strategies Theory provides a series of simple,

testable hypotheses that can be used to guide ecological research in an iterative and

informative manner. To fully test all of the predictions of Adaptive Strategies Theory,

one would have to measure a very large number of traits in many species, as well as a

broad range of physical, chemical, geological and biological characteristics across many

habitats. The Adaptive Strategies Theory is not so much an accurate model of reality as it

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286

is a powerful theoretical framework, which can be modified to give it great heuristic

value for guiding ecological research.

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APPENDICES

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APPENDIX A: Digital Video Image Capture Methodology

•Introduction

The following methodologies allow image capture, image manipulation and data analysis

transects of spur-and-groove reef habitats that were filmed with a digital video camera in

an underwater housing. While the methods were developed using Macintosh computers

and associated hardware and software, the same or similar products exist for the PC, and

most of the methods in this document can be accomplished with either platform.

• Hardware RequiredSony DCR-VX1000 Digital Video Camera

Amphibico VX1000 U/W Housing

Macintosh Power Mac G3/266 Desktop Computer

Radius Digital Video Card With Firewire Port

• Software Required

Microsoft Excel 98

Adobe Photoshop 5.0

Radius PhotoDV plugin for Photoshop

Applescript Script Editor 1.1.2.

IMPORTANT: Macros such as Applescript are programs that automate applications including the “Finder” application. As such it is possible to create, alter or delete files stored on any hard drive or unlocked disk attached to the computer while running a Macro. The manner in which Applescript macros work,

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and the function of the macrosprovided should be understood before running them. The authors assume no responsibility for any type of loss, or any other damages, including, but not limited to special, incidental, consequential, or other damages.• Make Folder of Random Dot Files (Excel and Photoshop)

Turn on computer.

Make new folder named “NewDots” on the startup HD.

This is to hold the 99 random-dot image files.

Open Excel File named: random dot maker98

Open Adobe Photoshop 5.0

Open Applescript program: Random-dot Image Generator

Run Applescript program: Random-dot Image Generator

Once this program has run – there should be 99 image files of random dot images with 10

random dots – lettered – in the folder named “NewDots” on your startup HD.

• Capture DV reef frames

If the digital video camera or cassette recorder is not attached to the computer – then shut

down the Mac and connect the digital video cassette player to the Radius digital video

card that is inside the Mac Power PC G3 via the Firewire ports.

Turn on the Mac and the DV cassette player.

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If the digital cassette recorder is attached to the computer – quit Applescript and open the

applications Adobe Photoshop 5.0 with the Radius plugin, and Microsoft Excel

Locate the correct video tape and place it in the digital video cassette player.

In Photoshop, open the Radius digital video plugin via the following path -

File: Import: Radius PhotoDV…

In the Radius control window play the videotape and record the start and stop times for

each transect in the Excel spreadsheet named: Tape Gap Calculator

Rewind the tape and cue it to the first frame of the first transect.

Select the following options (see below) while still in the Radius Plugin:

Capture Mode: Autocapture

Every [XXX} frames

i.e. Number of frames per time-gap between frame grabs – as prescribed by the

Tape Gap Calculator

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Until [52] are captured (give or take a couple)

Capture as[Yr-Si-D-Tr-Qu} - 2 digit yr, 2-5 letter site designation, 1 letter depth designation, 2 digit transect, 2 digit frame – starting at “00”

i.e. 98-Pel-D-04-00 = Year 1998, Pelican Reef, Deep Site, 4th Transect, 1st frame

Capture size: [720x480 (raw)]

De-interlace: [None]

Format:: [NTSC 4:3]

Once this is all in order – press start and wait for the 53 frames to be captured.

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• Clean up video frames

Once the 53 frames have been captured – they can all be adjusted to the correct size,

color adjusted and saved by running the Photoshop action “DO PING 52 TIMES” ***

*** NB – it is important to re-record the sub-action “SAVE” within this action so that the

files are saved to the correct folder.

The entire process of capturing and cleaning up the frames can then be repeated for the

other 9 transects on the 3 digital video tapes per site.

Be sure to save all of the files from each transect in a unique folder nested within another

folder holding all of the transects of a site– so that all of the files can be batch processed

in the next step. Folders should be named in the following manner –

HARD DRIVE: SITE FOLDER:

containing:

HARD DRIVE: SITE FOLDER: TRANSECT FOLDER

i.e. MyHardDrive: 98-Pel-D 01-10 containing 98 Pel D 01 : 98 Pel D 10

• Paste dots to images

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Once all of the frames are captured, cleaned up and saved into folders corresponding to

site and transect – run the Applescript “Paste Random Dots” to paste the dots from

randomly selected images to each of the 500+ frames of each site. This program will

lead you through the selection of the folder containing the random-dot files, as well

through to the selection of the first image file in the first of the 10 folders within the

folder corresponding to the site currently under analysis.

• Analyze Video Frames

Data can be either entered directly into an Excel spreadsheet on the computer – or entered

onto a paper spreadsheet. The user records the sessile biota or substrate underneath the

center point of the hollow square dots located on each image. The user also needs to

record the depth of each frame.

If a randomly positioned dot falls on the depth gauge present in the image – the user can

rotate the layer containing the dots 180° - this usually moves the dots to a position over

the substrate.

Several Photoshop actions are included that facilitate in the analysis of the video images.

The quick-keys corresponding to these actions are:

F1 – Select Background Layer

F2 – Select Layer 1

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F3 – Toggle Brightness/Contrast manipulation control

�-F4 – Flatten layers down to background

F5 – Rotate currently selected layer 180°

F15 – “PING” – a suite of actions that manipulate the raw video image so it is

the correct size and of improved resolution and color balance.

�-L - Levels control – a very useful tool for color-adjusting underwater images

-L - Auto Levels adjust

Once all the images have been analyzed all of the images in each folder nested in the

folder for each site can be flattened using the Batch command and the “flatten” action in

Photoshop:

The menu commands are as follows:

File: Automate: Batch…

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• Burn to CD

(E) Once an entire reef site has been analyzed, the digital video frames and the Excel spreadsheets and other statistical data can be stored in a folder and subsequently copied onto a CD using CD recording software such as Adaptec Toast 3.5.3

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APPENDIX B: Applescript computer program for using Microsoft Excel® and

Adobe Photoshop® software to place dots on frames

-- the list of file types which will be processed

-- eg: {"PICT", "JPEG", "TIFF", "GIF"}

property type_list : {"8BPS", "PICT", "JPEG", "TIFF", "GIF"}

-- since file types are optional in Mac OS X,

-- check the name extension if there is no file type

-- NOTE: do not use periods (.) with the items in the name extensions list

-- eg: {"txt", "text", "jpg", "jpeg"}, NOT: {".txt", ".text", ".jpg", ".jpeg"}

property extension_list : {}

property timerRoutine : ""

-- This droplet processes both files or folders of files dropped onto the applet

on open these_items

----the below checks to ensure needed Excel files and Photoshop Actions are in

place

tell application "Finder"

activate

set ButtonChoice to display dialog " ••••WARNING••••

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This program will modify

ALL Photoshop files contained

within the files or folders dragged

over its icon.

Do you wish to continue?" buttons ¬

{"STOP!", "OK"} default button "STOP!" with icon caution

set button_name to button returned of ButtonChoice

if button_name is "STOP!" then

return

end if

set ButtonChoice to display dialog "This program requires that you have

the included Microsoft Excel file random dot maker (25) open, and

the included Photoshop Action file

placed in the Photoshop Extensions Folder on your HD.

Have you done this?" buttons ¬

{"NO! Quit so I can do it", "OK"} default button "OK" with icon note

end tell

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set button_name to button returned of ButtonChoice

if button_name is "NO! Quit so I can do it" then

return

end if

repeat with i from 1 to the count of these_items

set this_item to (item i of these_items)

set the item_info to info for this_item

if folder of the item_info is true then

process_folder(this_item)

else if (alias of the item_info is false) and ¬

(the file type of the item_info is in the type_list) then

process_item(this_item)

else

tell application "Finder"

activate

display dialog "The files or folders did not contain Photoshop

files." buttons {"Quit"} ¬

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default button "Quit" with icon stop

end tell

return

end if

end repeat

tell application "Finder"

activate

display dialog "The session has finished." buttons {"Quit"} ¬

default button "Quit" with icon stop

end tell

end open

-- this sub-routine processes folders

on process_folder(this_folder)

set these_items to list folder this_folder without invisibles

repeat with i from 1 to the count of these_items

set this_item to alias ((this_folder as text) & (item i of these_items))

set the item_info to info for this_item

if folder of the item_info is true then

process_folder(this_item)

else if (alias of the item_info is false) and ¬

(the file type of the item_info is in the type_list) then -- or ¬

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--the name extension of the item_info is in the extension_list) then

process_item(this_item)

end if

end repeat

end process_folder

-- this sub-routine processes files

on process_item(this_item)

-- NOTE that the variable this_item is a file reference in alias format

-- FILE PROCESSING STATEMENTS GOES HERE

tell application "Microsoft Excel"

Activate

(*set Visible of ActiveWindow to false*)

Activate Window "random dot maker FGB (25)"

Select Range "R1C1"

CopyObject Selection

Paste

Activate ChartObject "Chart 13" of ActiveSheet

Select ChartArea of ActiveChart

set CutCopyMode to false

CopyObject ChartArea of ActiveChart

end tell

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(* this part is not needed

tell application "Adobe® Photoshop® 6.0.1"

activate

do script "Dot Grabber" -- an Adobe Photoshop 6.0 action - see attached

end tell *)

-- this selects the next photoshop file

tell application "Finder"

activate

select file (this_item)

open selection

end tell

-- this pastes the NewDots onto a new layer on the video frame, saves the file and

closes it

tell application "Adobe® Photoshop® 6.0.1"

activate

do script "Dot Paster"

end tell

end process_item

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Appendix C: A list of coral species observed in Bermuda

The following is a list of the species of scleractinian hard corals that have been observed

in Bermuda by the author. Just list the ones seen at your sites

Branched Oviparous

1. Oculina diffusa

2. Oculina robusta ???

Branched Viviparous

1. Madracis decactis

2. Madracis formosa (New possible record: S. R. Smith)

3. Madracis mirabilis

4. Porites furcata (New record: T.J.T. Murdoch: unpublished confirmation)

5. Porites porites

Massive Viviparous

1. Agaricia agaricites (T.J.T. Murdoch, A. Venn: possible sighting)

2. Dichocoenia stokesii

3. Favia fragum

4. Isophyllia sinuosa

5. Meandrina meandrites

6. Porites astreoides

7. Siderastrea radians

Massive Oviparous

1. Diploria labyrinthiformis

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2. Diploria strigosa

3. Montastraea cavernosa

4. Montastraea faveolata

5. Montastraea franksi

6. Montastraea species A (The majority of M. annularis spp. appear to be a hybrid

between M. faveolata and M. franksi in BDA)

7. Siderastrea siderea (T.J.T. Murdoch, S. du Putron: possibly regionally extinct?)

8. Stephanocoenia intersepta

Foliose, Plating and Solitary

1. Agaricia fragilis

2. Scolymia cubensis (W. Sterrer: potentially more than one species)

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Appendix D: Bermuda climatology

Climatology of Bermuda from 1949-1999, as published online by the Bermuda Weather

Service (http://www.weather.bm/data/climatology.html)

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Appendix E: Logistic regression of rank abundances; Florida data

Logistic regression of rank abundances versus total abundance per transect for each

functional group

Logistic Fit of BV By TCA

BV

0.00

0.25

0.50

0.75

1.00

-10 0 10 20 30 40 50 60 70 80 90 100 110 120 130

SUM

1

2

3

4

5

Whole Model Test

Model -LogLikelihood DF ChiSquare Prob>ChiSq

Difference 6.34659 1 12.69318 0.0004

Full 238.99612

Reduced 245.34271

RSquare (U) 0.0259

Observations (or Sum 200

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Wgts)

Converged by Objective

Parameter Estimates

Term Estimate Std Error ChiSquare Prob>ChiSq

Intercept -2.4993419 0.3709632 45.39 <.0001

Intercept -0.1303332 0.2248103 0.34 0.5621

Intercept 2.07864736 0.2772554 56.21 <.0001

Intercept 4.94687655 0.6259174 62.46 <.0001

TCA -0.0150532 0.0042367 12.62 0.0004

Logistic Fit of FP By TCA

FP

0.00

0.25

0.50

0.75

1.00

-10 0 10 20 30 40 50 60 70 80 90 100 110 120 130

SUM

12

3

4

5

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Whole Model Test

Model -LogLikelihood DF ChiSquare Prob>ChiSq

Difference 7.21570 1 14.4314 0.0001

Full 217.89041

Reduced 225.10611

RSquare (U) 0.0321

Observations (or Sum

Wgts)

200

Converged by Objective

Parameter Estimates

Term Estimate Std Error ChiSquare Prob>ChiSq

Intercept -3.3128101 0.5286694 39.27 <.0001

Intercept -1.3570022 0.2650898 26.20 <.0001

Intercept 1.05681986 0.2432521 18.88 <.0001

Intercept 4.49707184 0.5152874 76.17 <.0001

TCA -0.0164569 0.0043939 14.03 0.0002

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Logistic Fit of MV By TCA

MV

0.00

0.25

0.50

0.75

1.00

-10 0 10 20 30 40 50 60 70 80 90 100 110 120 130

SUM

1

2

3

45

Whole Model Test

Model -LogLikelihood DF ChiSquare Prob>ChiSq

Difference 10.41441 1 20.82881 <.0001

Full 166.38296

Reduced 176.79736

RSquare (U) 0.0589

Observations (or Sum

Wgts)

200

Converged by Gradient

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Parameter Estimates

Term Estimate Std Error ChiSquare Prob>ChiSq

Intercept -1.254137 0.2738426 20.97 <.0001

Intercept 2.70655809 0.3465647 60.99 <.0001

Intercept 4.91549566 0.5580352 77.59 <.0001

Intercept 5.85518535 0.7797963 56.38 <.0001

TCA -0.0227229 0.0050557 20.20 <.0001

Logistic Fit of MO By TCA

MO

0.00

0.25

0.50

0.75

1.00

-10 0 10 20 30 40 50 60 70 80 90 100 110 120 130

SUM

1

234

Whole Model Test

Model -LogLikelihood DF ChiSquare Prob>ChiSq

Difference 21.677679 1 43.35536 <.0001

Full 55.428898

Reduced 77.106577

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RSquare (U) 0.2811

Observations (or Sum

Wgts)

200

Converged by Objective

Parameter Estimates

Term Estimate Std Error ChiSquare Prob>ChiSq

Intercept -0.251108 0.4552401 0.30 0.5812

Intercept 1.39009666 0.5633292 6.09 0.0136

Intercept 2.36232842 0.7768345 9.25 0.0024

TCA 0.12926131 0.0333187 15.05 0.0001

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BIOGRAPHICAL SKETCH

Name of Author: Thaddeus James Thomas Murdoch

Place of Birth: Somerset Village, Sandy’s Parish, BERMUDA

Date of Birth: April 18, 1966

Graduate and Undergraduate Schools Attended:

University of South Alabama, Mobile, Alabama, USA

Dalhousie University, Halifax, Nova Scotia, CANADA

Degrees Awarded:

1995 – 1998 Master of Science in Marine Science,University of South Alabama, Mobile, Alabama, USAand the Dauphin Island Sea Lab, Dauphin Island, Alabama, USA.

1988 - 1991 Bachelor of Arts, Honors in Psychology (Neuroendocrinology), Dalhousie University, Halifax, N.S. CND

1984 - 1988 Bachelor of Science in Biology, Dalhousie University, Halifax, N.S. CND

Awards and Honors:

Bermuda Biological Station for Research, Inc. - Grant in Aid: 2003

PADI Foundation: 2000

Ph.D. Fellowship, Marine Science Dept., U. South Alabama: 1999 to 2002

Nelson Award for Outstanding Masters Student, U. South Alabama: 1998

Marine Science Dept. Student Assistantship, U. South Alabama: 1995 to 1998