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Emergence Dynamics of American Alligators (Alligator mississippiensis) in Arthur R. Marshall Loxahatchee National Wildli...

Permanent Link: http://ufdc.ufl.edu/UFE0021270/00001

Material Information

Title: Emergence Dynamics of American Alligators (Alligator mississippiensis) in Arthur R. Marshall Loxahatchee National Wildlife Refuge Life History and Application to Statewide Alligator Surveys
Physical Description: 1 online resource (115 p.)
Language: english
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2008

Subjects

Subjects / Keywords: alligators, detectability, emergence, surveys, thermoregulation
Interdisciplinary Ecology -- Dissertations, Academic -- UF
Genre: Interdisciplinary Ecology thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: The purpose of this study was to extend knowledge of the behavioral ecology of alligators in the seasonally fluctuating south Florida environment and then apply this knowledge to develop estimates of alligator detectability for management purposes. I first modeled alligator thermoregulatory response to environmental conditions by investigating emergence rates and using them as an index of heat seeking or heat avoidance. All models indicated a higher probability of emergence in the spring compared to that of the fall. Springtime solar radiation had a positive affect on emergence probabilities. Larger alligators showed a higher degree of heat avoidance in the summer and spent less time emerged than smaller individuals in this study. Body condition also had an effect on emergence rates as alligators with higher body condition scores had higher rates of emergence. I also investigated alligator emergence behavior and how it relates to a variety of environmental variables known to have an effect on crocodilian behavior including season, air and water temperature, moon phase, rain, and wind. Data were analyzed using the GENMOD procedure in the Statistical Analysis System. An Akaike Information Criterion (AIC) for model selection was calculated for each model, and model averaging was performed to come up with a final model that best describes and predicts alligator emergence. Compared to spring and fall, alligators were less likely to be emerged at any given time during summer. Compared to summer months, alligators in autumn are only slightly more likely to be emerged. Alligators are less likely emerged in low moonlight compared to half moon or full moon cycles. In addition, alligators are slightly more likely to be emerged during half moons compared to full moons. During nighttime hours, higher water depths decreased the emergence rates of alligators. Higher water temperatures result in decreased emergence rates, while higher air temperature results in increased emergence rates. I found that the best time for conducting surveys is in low wind, in half or full moon phases, and on clear, cloud-free nights with relatively high air and water temperatures and relatively lower water depths. Regardless of conditions, an equation was developed that south Florida alligator researchers can use to adjust their survey results in an appropriate manner to correct for the influence of varying environmental conditions on alligator detectability. Although the equation successfully predicted alligator emergence rates in the summer and fall, it lost much of its predictive ability in the spring. I suggest that some other variable or variables that were not measured in this study were effectively overriding the expected influence of the surrounding environment. This research can be used by alligator managers to reduce the amount of time needed to detect significant changes in alligator populations as they respond to restoration actions. Eventually, as this type of research advances, alligator managers will be able to incorporate actual population levels and not indices into their monitoring programs.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Thesis: Thesis (M.S.)--University of Florida, 2008.
Local: Adviser: Mazzotti, Frank J.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2008
System ID: UFE0021270:00001

Permanent Link: http://ufdc.ufl.edu/UFE0021270/00001

Material Information

Title: Emergence Dynamics of American Alligators (Alligator mississippiensis) in Arthur R. Marshall Loxahatchee National Wildlife Refuge Life History and Application to Statewide Alligator Surveys
Physical Description: 1 online resource (115 p.)
Language: english
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2008

Subjects

Subjects / Keywords: alligators, detectability, emergence, surveys, thermoregulation
Interdisciplinary Ecology -- Dissertations, Academic -- UF
Genre: Interdisciplinary Ecology thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: The purpose of this study was to extend knowledge of the behavioral ecology of alligators in the seasonally fluctuating south Florida environment and then apply this knowledge to develop estimates of alligator detectability for management purposes. I first modeled alligator thermoregulatory response to environmental conditions by investigating emergence rates and using them as an index of heat seeking or heat avoidance. All models indicated a higher probability of emergence in the spring compared to that of the fall. Springtime solar radiation had a positive affect on emergence probabilities. Larger alligators showed a higher degree of heat avoidance in the summer and spent less time emerged than smaller individuals in this study. Body condition also had an effect on emergence rates as alligators with higher body condition scores had higher rates of emergence. I also investigated alligator emergence behavior and how it relates to a variety of environmental variables known to have an effect on crocodilian behavior including season, air and water temperature, moon phase, rain, and wind. Data were analyzed using the GENMOD procedure in the Statistical Analysis System. An Akaike Information Criterion (AIC) for model selection was calculated for each model, and model averaging was performed to come up with a final model that best describes and predicts alligator emergence. Compared to spring and fall, alligators were less likely to be emerged at any given time during summer. Compared to summer months, alligators in autumn are only slightly more likely to be emerged. Alligators are less likely emerged in low moonlight compared to half moon or full moon cycles. In addition, alligators are slightly more likely to be emerged during half moons compared to full moons. During nighttime hours, higher water depths decreased the emergence rates of alligators. Higher water temperatures result in decreased emergence rates, while higher air temperature results in increased emergence rates. I found that the best time for conducting surveys is in low wind, in half or full moon phases, and on clear, cloud-free nights with relatively high air and water temperatures and relatively lower water depths. Regardless of conditions, an equation was developed that south Florida alligator researchers can use to adjust their survey results in an appropriate manner to correct for the influence of varying environmental conditions on alligator detectability. Although the equation successfully predicted alligator emergence rates in the summer and fall, it lost much of its predictive ability in the spring. I suggest that some other variable or variables that were not measured in this study were effectively overriding the expected influence of the surrounding environment. This research can be used by alligator managers to reduce the amount of time needed to detect significant changes in alligator populations as they respond to restoration actions. Eventually, as this type of research advances, alligator managers will be able to incorporate actual population levels and not indices into their monitoring programs.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Thesis: Thesis (M.S.)--University of Florida, 2008.
Local: Adviser: Mazzotti, Frank J.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2008
System ID: UFE0021270:00001


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EMERGENCE DYNAMICS OF AMERICAN ALLIGATORS (Alligator mississippiensis) IN
ARTHIUR R. MARSHALL LOXAHATCHEE NATIONAL WILDLIFE REFUGE: LIFE
HISTORY AND APPLICATION TO STATEWIDE ALLIGATOR SURVEYS




















By

CHRISTOPHER DAVID BUGBEE


A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE

UNIVERSITY OF FLORIDA

2008
































O 2008 Christopher David Bugbee



































To my family: Thank you for lending your guidance and support through the years, and for the
opportunity to chase my dream .. and grab it by the tail.

To Aletris: Thank you for your encouragement, inspiration, advice, support, and patience.
I love you.









ACKNOWLEDGMENTS

I thank Ken Rice, Frank Mazzotti, and Franklin Percival for the opportunity to conduct this

study and for their guidance along the way. I thank the researchers and technicians who assisted

with this proj ect; they include, Justin Davis, Joe Kern, Wellington Guzman, Mike Rochford,

Eliza Gilbert, Aletris Neils, Mike Cherkiss, Hardin Waddle, Brian Jeffery, Mark Parry, and

Cameron Carter. I thank Dr. Darryl Heard for his advice in developing the surgical protocol. I

would also like to thank Laura Brandt for all of her contributions to the proj ect, and Mark Miller,

Ikuko Fujisaki, and Meghan Brennan for their statistical guidance.












TABLE OF CONTENTS


page

ACKNOWLEDGMENT S .............. ...............4.....


LI ST OF T ABLE S ............ ...... ._._ ...............7....


LI ST OF FIGURE S .............. ...............9.....


AB S TRAC T ............._. .......... ..............._ 10...


CHAPTER


1 INTRODUCTION ................. ...............12.......... ......


The American Alligator ................. ...............12........... ....
Alligators and the Everglades ................. ...............13................
Everglades Alligator Thermal Ecology .............. ...............14....
Alligator Surveys ................ ...............17.................

2 AMERICAN ALLIGATOR (Alligator mississippiensis) AMPHIBIOUS BEHAVIOR
AND THERMAL ECOLOGY INT RESPONSE TO ENVIRONMENTAL
FLUCTUATIONS ................. ...............19.......... .....


Introducti on .................. ............. ...............19 .....

Alligator Amphibious Behavior ................. ......... ...............19......
A Harsh Environment ................. ...............21........... ....
Thermoregulation .............. ...............22....
M material s/M ethod s .............. ...............26....

Study Area ................. ...............26......... ......
T el em etry ................. ...............26......... ......
Nest S earches............... ...............2
Data Protocol s/Management .............. ...............27....
Data Analysis............... ...............28
M odeling............... ........ ............2
Environmental variable analysis .............. ...............29....
Size, condition, and sex variable analysis s ...._.._.._ ..... .._._. ... .._..... .......3
Re sults........._........ .. ... ...._.... ... ..... ...... .............3
Environmental Variable Analysis............... ...............30
Size, Condition, and Sex Variable Analysis............... ...............31
Discussion ........._....... ......... ...............32......
Seasonal Activities .............. ...............32....
Solar Radiation ........._.._... ...............33.._.._.. ......
Circadian Rhythms .............. ...............36....
W ater Depths ........._..._... ...............37.._.._.. ......
Alligator Size............... ...............38..
Alligator Condition............... ...............3












A lligator Sex............... .......... .............4
Implications and Future Work............... ...............41..


3 EMERGENCE DYNAMICS OF AMERICAN ALLIGATORS (Alligator
mississippiensis) IN ARTHUR R. MARSHALL LOXAHATCHEE NATIONAL
WILDLIFE REFUGE AND THEIR APPLICATION TO ALLIGATOR
MONITORING ................. ...............55.......... ......


Introducti on ................. ........... ...............55.......

Everglades Restoration ................. ...............55.................
Everglades Alligator Surveys ................ ...............56........... ....
Alligator Detectability ................. ...............56.......... .....
Hypotheses .............. ...............57....
M aterials/M ethods .............. ...............58....

Study Area ................. ...............58.................
T el em etry ................. ...............59.......... ......
Nest S earches............... ...............5
Data Protocol s/Management .............. ...............60....
Data Analy sis............... ...............60
Modeling............... ...............61
Re sults........._..... ..._ ... ...............63.....

Equation Accuracy .............. ...............65....
Discussion ........._..... ...._... ...............66.....

Equation Accuracy .............. ...............66....
Seasonal Activities .............. ...............67....
Time of Night .............. ...............67....
Moon Phases............... ...............68.
W ater Depths .........___ _........ ._ ._ ...............69....
Water and Air Temperatures .............. ...............70....
Rain ........._.. ..... ._ ...............72.....
W ind .............. .. ....... .. .......... ........7

Implications and Future Work............... ...............73..

4 CONCLUSIONS .............. ...............85....


APPENDIX


A METHODOLOGY .............. ...............91....


B DATA PROTOCOLS AND MANAGEMENT .............. ...............103....


C PERM IT S .............. ...............105....


LI ST OF REFERENCE S ....._.._................. ........_.._.........10


BIOGRAPHY ................. ...............115..............










LIST OF TABLES


Table page

2-1 Environmental variables of all models used to describe the emergence dynamics of
alligators in Arthur R. Marshall Loxahatchee National Wildlife Refuge. .........................45

2-2 The AICC, a AICC, and Akaike weights of 20 models used to describe the
emergence dynamics of alligators in Arthur R. Marshall Loxahatchee National
W wildlife Refuge ................. ...............46.................

2-3 Regression coefficients (p-values) and associated confidence intervals of the
averaged model used to describe the emergence dynamics of Arthur R. Marshall
Loxahatchee National Wildlife Refuge alligators ................. .............. ......... .....47

2-4 Regression coefficients of a model used to describe the emergence dynamics of
alligators in Arthur R. Marshall Loxahatchee National Wildlife Refuge based on
size, body condition, and sex. ............. ...............48.....

2-5 Average body condition scores of 1999-2005 south Florida alligators and 2005-2006
Arthur R. Marshall Loxahatchee National Wildlife Refuge alligators. .............................49

2-6 Analysis of variance for average body condition of 2005-2006 Arthur R. Marshall
Loxahatchee National Wildlife Refuge alligators and 1999-2005 south Florida
alligators ................. ...............50........._.....

2-7 Analysis of variance for average body condition of spring 2006 Arthur R. Marshall
Loxahatchee National Wildlife Refuge alligators and 1999-2005 south Florida
alligators ................. ...............51........._.....

2-8 Analysis of variance for average body condition of fall 2005 Arthur R. Marshall
Loxahatchee National Wildlife Refuge alligators and 1999-2005 south Florida
alligators ................. ...............52......__ .....

2-9 Comparison of average body condition of spring 2006 and spring 1999-2005 Arthur
R. Marshall Loxahatchee National Wildlife Refuge alligators ................. ................ ...53

2-10 Analysis of variance for average body condition of spring 2006 and spring 1999-
2005 Arthur R. Marshall Loxahatchee National Wildlife Refuge alligators. ....................54

3-1 The a AICC and Akaike weights of models used to describe the emergence
dynamics of Arthur R. Marshall Loxahatchee National Wildlife Refuge alligators .........75

3-2 Regression coefficients (p-values) and associated confidence intervals of the
averaged model used to describe the emergence dynamics of Arthur R. Marshall
Loxahatchee National Wildlife Refuge alligators ................. .............. ......... .....76










3-3 Summary of the differences between equation-predicted proportion (P) and actual
observed proportion (0) of alligators emerged at Arthur R. Marshall Loxahatchee
National Wildlife Refuge in 2005-2006. ............. ...............77.....

3-4 Results of a paired two-sample t-test for spring predicted vs. observed proportion of
alligators emerged at Arthur R. Marshall Loxahatchee National Wildlife Refuge in
2005-2006. ............. ...............78.....

3-5 Results of a paired two-sample t-test for summer predicted vs. observed proportion
of alligators emerged at Arthur R. Marshall Loxahatchee National Wildlife Refuge in
2005-2006. ............. ...............79.....

3-6 Results of a paired two-sample t-test for autumn predicted vs. observed proportion of
alligators emerged at Arthur R. Marshall Loxahatchee National Wildlife Refuge in
2005-2006. ............. ...............8 0....

A-1 Results of epoxy experiment for transmitter attachment. ................. .................9

A-2 Summary of transmitter application and recovery ................. ..........._. ......... ....99










LIST OF FIGURES


Figure page

2-1 Study site at Arthur R. Marshall Loxahatchee National Wildlife Refuge. ........................44

3-1 Relationships between observed and predicted proportions of alligators emerged at
Arthur R. Marshall Loxahatchee National Wildlife Refuge, 2005-2006...........................81

3-2 Relationships between water temperature (oC) and proportion of alligators emerged
at Arthur R. Marshall Loxahatchee National Wildlife Refuge, 2005-2006.......................82

3-3 Relationships between rainfall (cm/hr) and proportion of alligators emerged at
Arthur R. Marshall Loxahatchee National Wildlife Refuge, 2005-2006...........................83

3-4 Relationships between wind speed (km/hr) and proportion of alligators emerged at
Arthur R. Marshall Loxahatchee National Wildlife Refuge, 2005-2006...........................84

A-1 Parietal/squamosal wiring ................. ...............100................

A-2 Transmitter attachment. ............. ...............101....

A-3 One recaptured alligator with the transmitter firmly in place ................. ................ ...102









Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Science

EMERGENCE DYNAMICS OF AMERICAN ALLIGATORS (Alligator mississippiensis) IN
ARTHIUR R. MARSHALL LOXAHATCHEE NATIONAL WILDLIFE REFUGE: LIFE
HISTORY AND APPLICATION TO STATEWIDE ALLIGATOR SURVEYS

By

Christopher David Bugbee

May 2008

Chair: Frank Mazzotti
Major: Interdisciplinary Ecology

The purpose of this study was to extend knowledge of the behavioral ecology of alligators

in the seasonally fluctuating south Florida environment and then apply this knowledge to

develop estimates of alligator detectability for management purposes. I first modeled alligator

thermoregulatory response to environmental conditions by investigating emergence rates and

using them as an index of heat seeking or heat avoidance. All models indicated a higher

probability of emergence in the spring compared to that of the fall. Springtime solar radiation

had a positive affect on emergence probabilities. Larger alligators showed a higher degree of

heat avoidance in the summer and spent less time emerged than smaller individuals in this study.

Body condition also had an effect on emergence rates as alligators with higher body condition

scores had higher rates of emergence.

I also investigated alligator emergence behavior and how it relates to a variety of

environmental variables known to have an effect on crocodilian behavior including season, air

and water temperature, moon phase, rain, and wind. Data were analyzed using the GENMOD

procedure in the Statistical Analysis System. An Akaike Information Criterion (AIC) for model

selection was calculated for each model, and model averaging was performed to come up with a









final model that best describes and predicts alligator emergence. Compared to spring and fall,

alligators were less likely to be emerged at any given time during summer. Compared to summer

months, alligators in autumn are only slightly more likely to be emerged. Alligators are less

likely emerged in low moonlight compared to half moon or full moon cycles. In addition,

alligators are slightly more likely to be emerged during half moons compared to full moons.

During nighttime hours, higher water depths decreased the emergence rates of alligators. Higher

water temperatures result in decreased emergence rates, while higher air temperature results in

increased emergence rates. I found that the best time for conducting surveys is in low wind, in

half or full moon phases, and on clear, cloud-free nights with relatively high air and water

temperatures and relatively lower water depths. Regardless of conditions, an equation was

developed that south Florida alligator researchers can use to adjust their survey results in an

appropriate manner to correct for the influence of varying environmental conditions on alligator

detectability. Although the equation successfully predicted alligator emergence rates in the

summer and fall, it lost much of its predictive ability in the spring. I suggest that some other

variable or variables that were not measured in this study were effectively overriding the

expected influence of the surrounding environment. This research can be used by alligator

managers to reduce the amount of time needed to detect significant changes in alligator

populations as they respond to restoration actions. Eventually, as this type of research advances,

alligator managers will be able to incorporate actual population levels and not indices into their

monitoring programs.









CHAPTER 1
INTTRODUCTION

The American Alligator

The American alligator (Alligator mississippiensis) is considered a keystone species and

top predator in the Greater Everglades Ecosystem (Mazzotti and Brandt 1994). Through

construction of holes, caves, and trails, alligators create resources for a wide variety of biota

including aquatic plants, fish, amphibians, and reptiles including other alligators (Beard 1938;

Kushlan 1974; Mazzotti and Brandt 1994; Rice et al. 2005). As a reptilian top predator, the

American alligator consumes a wide variety of prey species as it grows from a hatchling to an

adult. Hatchlings consume small prey such as insects and fish and also serve as prey to a variety

of other species including their own (Deitz 1979; Barr 1997). Large juveniles function

ecologically as Everglades mesopredators, consuming larger prey but still serving as potential

prey for adults. Considering these dynamics, alligators play a significant role in shaping the

faunal community of the Everglades ecosystem (Rice et al. 2004; 2005).

The alligator is also a prominent example of an ecosystem engineer in the Everglades.

Alligators create holes in the marsh that provide refugia for a variety of plants and animals,

particularly in the dry season (Kushlan 1974; Loftus and Eklund 1994; Palmer 2000). These

holes influence the community structure of aquatic fauna and vegetation, both concentrating

aquatic life for predators and creating conditions that favor certain plant species over others

(Craighead 1968; Palmer 2000). Additionally, alligator nests create suitable habitat for

vegetation sensitive to elevation (Palmer 2000) and provide nesting habitat for other reptiles

(Craighead 1968; Kushlan and Kushlan 1980; Enge et al. 2000). First and foremost alligator

holes serve to benefit alligators. Alligators of all size classes use holes as refugia, from

hatchlings to large adults (Campbell 1999). Reproductive females use associated habitats for









nesting, and both males and females require alligator holes to court and mate with one another

(Garrick and Lang 1975). Of 29 alligator holes surveyed by Campbell (1999), all showed signs

of recent alligator activity. Consequently, alligators help to shape the community structure of

both plants and animals in the Everglades ecosystem.

Alligators and the Everglades

Within the last 100 years, the original Everglades ecosystem has been spatially reduced,

drained, and irreversibly lost as a result of extensive landscape alterations for development and

flood control (Light and Dineen 1994). Once natural hydrologic fluctuations are now

anthropogenically controlled (Lord 1993; Davis and Ogden 1994). Wildlife populations have

been affected following development and drainage of the Everglades ecosystem, and this is

especially true of alligators (Mazzotti and Brandt 1994). Specifically, alligator population

densities are lower in over-drained marshes and swamps. Reproductive output is known to be

lower in areas characterized by prolonged high water depths due to nest flooding. Alligator body

condition may also be consistently lower in these areas due to prolonged dispersion of aquatic

prey (Mazzotti and Brandt 1994; Dalrymple 1996; Barr 1997). Additionally, although many

alligators use manmade canals as habitat, canals may be population sinks as both reproductive

and survival rates are lowered due to increased nest flooding and cannibalism of smaller

individuals (Mazzotti and Brandt 1994; Chopp 2002; Rice et al. 2005).

The South Florida Restoration Initiative began in 1992. The Comprehensive Everglades

Restoration Plan (CERP) was signed into law in 2000 and represents the primary means of

achieving Everglades restoration. Restoration efforts include proj ects to remove canals and

increase the extent and quality of natural areas. Wildlife studies in the Everglades ecosystem

often focus on the effects of fluctuating water depths on the ecology of the study organisms.

Population trends of some organisms can be viewed as indications of ecosystem change, and









ecological modeling is a vital tool used in the adaptive assessment of restoration (Gunderson et

al. 1994; Gentile et al. 2001).

Several aspects of alligator ecology have been shown to be dependent on water levels.

These include courtship (Garrick and Lang 1987; Vliet 1987), nesting (Kushlan and Jacobsen

1990), growth and survival (Hines et al. 1968), and body condition (Zweig 2002). Alligators are

sensitive to fluctuating water levels both spatially and temporally, and the success of many other

species is linked to the natural presence of alligators. For these reasons, alligators represent an

ideal performance measure of restoration progress and are an integral part of the Adaptive

Assessment Process component of CERP (CERP Monitoring and Assessment Plan 2003, section

3.1.3.15). Although alligators have received much scientific attention and are a well-studied

species, there are still many aspects of its behavioral ecology that remain unknown.

Everglades Alligator Thermal Ecology

The American alligator has evolved to inhabit warm-temperate rather than tropical

environments (Brisbin and Standora 1982; Mazzotti 1989). Among the living crocodilians,

alligators (both Alligator mississippiensis and Alligator sinensis) are the only species that have

evolved to inhabit environments that experience sub-freezing temperatures (Brisbin and Standora

1982). South Florida however is subtropical and represents the southern extent of the natural

range of the American alligator (Mazzotti 1989; Conant and Collins 1991). South Florida is

characterized by consistent high temperatures and a distinct wet and dry season that together

present a unique set of challenges for alligators that inhabit this region (Dalrymple 1996; Barr

1997; Howarter 1999; Kushlan and Jacobsen 1990). Alligator habitat south of Lake Okeechobee

represents an environment with a high cost: benefit ratio for alligators for a significant part of the

year (Dalrymple 1996; Kushlan and Jacobsen 1990). This is especially true during summer and

fall due to high levels of virtually inescapable heat (high cost) combined with relatively low









availability of food due to higher water depths and the resulting dispersal of aquatic prey (low

benefit). In spring, south Florida can be described as an environment with a comparatively low

cost: benefit ratio, or one in which temperatures are less extreme (lower cost) and food is more

concentrated (higher benefit).

In theory, crocodilians and other reptiles invest more energy into active thermoregulation

in environments that are characterized by low cost: benefit ratios (Spotila et al. 1972; Heatwole

1976; Huey and Slatkin 1976; Lang 1980; Lang 1987; Shine and Madson 1996). In thermally

variable or productive environments, there are usually many avenues of heat exchange and

adequate energetic resources to invest energy into active thermoregulation (Heatwole 1976; Lang

1987; Slip and Shine 1988; Shine and Madson 1996). In the spring for example, Everglades

alligators respond by actively engaging in behaviors such as basking and orienting their bodies in

relation to the sun's rays to optimize solar absorption (Spotila et al. 1972; Lang 1987; Mazzotti

1989). This active heat-seeking behavior is reflected in the trend that alligator body temperature

is most variable and often greater than ambient temperatures in the spring (Howarter 1999).

Alternatively, reptiles that inhabit thermally-equable environments, or environments

characterized by high cost: benefit ratios generally adopt a more thermal generalist strategy and

thermoconform to their surrounding environment (Heatwole 1976; Lang 1980; Lang 1987; Shine

and Madson 1996). The advantage of this strategy is to conserve energy stores. By becoming less

active and thermoconforming, metabolic rates are reduced and energy is conserved for other

processes such as growth or reproduction (Lang 1987).

There is some evidence that south Florida alligators adopt more of a thermoconformer

strategy in the hotter summer and fall months (Lang 1977, Abercrombie 2002). Alligator body

temperatures are higher, more stable, and better correlate with environmental temperatures









during fall compared to spring in south Florida (Abercrombie 2002). During summer and fall,

alligators also appear to shift their behavior by remaining submerged to keep cool (Howarter

1999, Abercrombie 2002). Alligators appear to be more nocturnal in summer (Woodward and

Marion 1979), and the dominant strategy may be to remain submerged for most of the daylight

hours. In climates with high ambient temperatures, crocodilians often leave the water altogether

at night to release excess heat (Lang 1980; Mazzotti 1989). The shift to a primarily nocturnal

lifestyle during the hotter portion of the year is typical of reptiles found in tropical environments

(Heatwole 1976; Lang 1980; Lang 1987; Luiselli and Akani 2002). Alligator thermoregulatory

behavior may closely reflect a seasonal shift in the cost: benefit ratios of the south Florida

environment.

The first obj ective of this study was to investigate patterns of thermoregulatory behavior

by comparing alligator emergence behavior and circadian rhythms to patterns of solar radiation,

water level, and seasonal change in the south Florida environment. I expected that if south

Florida represents an environment that undergoes a seasonal shift in cost: benefit ratios for

alligators, then alligator thermoregulatory behavior will reflect this by showing some kind of

transition. I expected to see behavior that reflected an environment with a low cost: benefit ratio

during the relatively cooler portions of the year (i.e. lower heat levels and higher food

concentrations) and behavior that suggested an environment with a high cost: benefit during

summer and fall (i.e. higher heat levels and lower food concentrations). Specifically, I expected

alligators to actively engage in heat-seeking thermoregulation during the spring and to transition

to thermoconformity during the hotter portion of the year stop when the costs of active

thermoregulation outweigh the benefits.









Everglades alligators likely have a built-in response system that governs their behavior in

an thermally optimal way when confronted by seasonal change. Lang (1976) suggested that

photoperiod, not necessarily ambient temperatures, may be the driving force behind alligator

amphibious behavior. If this is the case, then anthropogenically managed water regimes in the

Everglades should approximate natural ones. If natural conditions and water cycles are not

maintained in the Everglades, alligators may not optimally thermoregulate. For example, if water

levels are too high in the spring, and spring shifts to a low cost low benefit environment, how

would alligators respond? Similarly, if water levels are too low in the summer and fall, and the

environment becomes one of high costs and high benefits, would alligators effectively miss the

opportunity to feed and restore energy stores? The end result could have negative effects on the

fitness of individual animals, and ultimately have negative impacts at the population level.

Alligator Surveys

Successful restoration of the Everglades will be assessed through monitoring of

performance measures concerning indicator species (Rice et al. 2005). The alligator has been

chosen as one of these indicators and performance measures including abundance and

distribution, nesting, body condition, and alligator hole occupancy are currently being monitored

(Rice et al. 2005). Spotlight surveys (or night counts) are a common approach to monitoring

crocodilian abundance and distribution (Magnussun 1982; Bayliss 1987; O'Brien 1990; Wood et

al. 1985; Hutton and Woolhouse 1989; Woodward and Moore 1990). In south Florida, spotlight

surveys are used to describe alligator encounter rates (alligators/km). Due to a variety of

confounding variables (detectability, habitat use, habitat characteristics, survey speed), encounter

rates do not directly translate into estimates of alligator density (alligators/km2) Or abundance

(the number of alligators in a defined area). Instead, spotlight surveys serve as a relative index of

abundance. Over time, trends in encounter rate data can provide information about alligator









population traj ectory in response to management actions. This index becomes more robust when

factors such as detection or detectability are considered (Cassey and McCardle 1999; Thompson

and Seber 1994; Thompson 2002).

Estimating wildlife abundance requires replicated scientific and statistical methodology

(Steinhorst and Samuel 1989). It is impossible to assess the true number of alligators in a

population, but models can be established that describe correlations between survey results and

population size. Understanding detectability is essential for the accuracy of such models

(Steinhorst and Samuel 1989; Cassey and McCardle 1999; Thompson and Seber 1994;

Thompson 2002). This research attempts to describe alligator detectability during encounter rate

surveys to account for individuals present in the population that were not recorded by the

observer due to several reasons: alligators may have been present but simply missed by the

observer, they may have been present but in a low visibility habitat, or they may have been

submerged and effectively not present for the researcher to observe (Woodward and Marion

1979). Specifically, I investigated alligator emergence behavior and how it related to a variety of

environmental variables known to effect crocodilian behavior (Woodward and Marion 1979;

Pacheco 1996; Sarkis-Goncalves et al. 2004). The ultimate goal was to develop relationships

between alligator detectability and various environmental factors that alligator managers can use

to reduce bias in survey results. This research is critical for alligator management in south

Florida as it will reduce the amount of time needed to statistically detect changes in alligator

populations as they respond to different restoration actions, thus allowing managers information

needed to adaptively manage Everglades restoration.









CHAPTER 2
AMERICAN ALLIGATOR (Alligator mississippiensis) AMPHIBIOUS BEHAVIOR AND
THERMAL ECOLOGY INT RESPONSE TO ENVIRONMENTAL FLUCTUATIONS

Introduction

The Everglades ecosystem is characterized by seasonally fluctuating hydrological

conditions due to naturally occurring patterns of precipitation (Mazzotti and Brandt 1994). The

American alligator has received scientific attention in the Everglades for its ability to indicate the

overall health of this ecosystem (Rice et al. 1994). Several aspects of alligator biology including

courtship, nesting, growth and survival have all been examined in some detail in relation to water

depths (Hines et al. 1968; Kushlan and Jacobsen 1990; Vliet 1987). However, alligator

amphibious behavior and its role in thermoregulation in a fluctuating environment has not been

examined.

Alligator Amphibious Behavior

For crocodilians, different behavioral activities (foraging, resting, thermoregulation, etc.)

can occur under water, at the water surface, or on land. For example, in all crocodilians, some

social interactions and foraging behavior occur underwater (Webb et al. 1982; Fish and Cosgrove

1987; Vliet 2001). However, it remains unclear as to what extent alligators vary their amphibious

behavior depending on seasonal fluctuations and environmental conditions. Alligators may

allocate more time and energy towards certain behaviors (i.e. foraging, socializing,

thermoregulating) in response to water depths and other environmental fluctuations associated

with seasonal change (Lang 1979; Howarter et al. 2000).

Alligators primarily thermoregulate behaviorally and use various thermal microhabitats in

the environment as resources (Lang 1979; Lang 1987; Mazzotti and Brandt 1994). Alligators

exposed to different environmental conditions are known to use thermal resources differently

(Lang 1976; Lang 1979; Lang 1987; Abercrombie et al. 2002). In a seasonally fluctuating









environment like the Everglades, alligators likely have an optimal behavioral response when

confronted by seasonal change (Lang 1976). If this response is triggered by some natural cue

such as photoperiod or ambient temperature (Lang 1976), then other natural conditions such as

water depth should be in harmony. A prolonged divergence from natural conditions in the

Everglades, particularly water cycles, may interfere with alligator thermal behavior. For

example, if water depths are consistently too high in spring, or consistently too low in summer

and fall, alligators may not be able to allocate their energetic resources toward appropriate

activities including thermoregulation. This may have negative effects on survival and fitness of

individual animals, and ultimately have negative impacts at the population level.

Furthermore, Mazzotti and Brandt (1994) suggested that alligators of different sizes and

sexes use wetland habitats distinctly on varying spatial and temporal scales and in response to

changing water depths. Campbell and Mazzotti (2001) suggest further that in the Everglades,

alligator holes associated with tree islands more often contain an adult female alligator and

hatchlings, while relatively smaller satellite holes in marl substrates typically contain juveniles

and sub-adults. But with lower spring water depths in the Everglades, these satellite holes tend to

dry up faster, and alligators become concentrated in remaining alligator holes and trails

(Mazzotti 1989; Kushlan and Jacobsen 1990; Mazzotti and Brandt 1994; Rice et al. 2005). Adult

male alligators have been observed to travel between remaining alligator holes during spring dry

downs (Campbell and Mazzotti 2001). Everglades alligators of all sizes are thus forced to share

the same space in the spring which may result in higher rates of cannibalism (Mazzotti and

Brandt 1994; Campbell and Mazzotti 2001). Also, alligators in crowded conditions may not be

able to thermoregulate optimally as their natural behaviors are known be affected as a response

to overcrowding (Seebacher and Grigg 1997; Asa et al. 1998).









An investigation into the amphibious behavior of alligators will allow managers to more

completely understand the full range of behavioral adaptations Everglades alligators use to deal

with the fluctuations that characterize the Everglades.

A Harsh Environment

The severity of anthropogenic alteration of the Everglades ecosystem has taken a toll on

natural alligator population levels, dynamics, and distributions (Mazzotti and Brandt 1994; Rice

et al. 2005). Alterations have intensified the negative effects of natural droughts (Jacobsen and

Kushlan 1984), reduced and altered the amount of available habitat (Kushlan 1974; Kushlan

1990; Gunderson and Loftus 1993), and negatively affected nesting efforts and reproduction

(Kushlan and Jacobsen 1990). South Florida poses a unique set of challenges for alligators as it

represents the southern extent of their natural range. The Everglades is subtropical whereas most

alligator populations occur in a warm-temperate zone (Brisbin and Standora 1982; Conant and

Collins 1991; Mazzotti 1989). A general ecological trend is that organisms that inhabit the

peripheries of their natural range are often faced by a unique set of challenges and may be

physically stressed (Heatwole 1976; Pulliam 1988; Dias 1996). South Florida alligators

physically reflect their environment as they are generally smaller, thinner, and take longer to

grow and mature when compared to alligators from north Florida or Louisiana (Kushlan and

Jacobsen 1990; Dalrymple 1996; Barr 1997). This may be due to several reasons including

climate and food availability (Jacobsen and Kushlan 1989; Dalrymple 1996; Barr 1997). The

American alligator is a crocodilian that has evolved to inhabit temperate rather than tropical

environments (Brisbin and Standora 1982; Mazzotti 1989). South Florida essentially represents

an intermediate between the two, and is characterized by consistently high and equable

temperatures compared to other parts of alligator' s range. This relatively warmer climate may

result in high metabolic costs for alligators that inhabit this part of their range (Howarter 1999;









Percival et al. 2000). On the same note, although south Florida winters are relatively mild, winter

temperatures still reduce alligator body temperature to levels that inhibit activity (Howarter

1999). Therefore, south Florida alligators are inactive for a greater portion of the year than are

their northern counterparts.

Thermoregulation

It has been traditionally argued that active behavioral thermoregulation is less important

for tropical ectotherms than it is for their temperate counterparts (Heatwole 1976; Peterson et al.

1993; Shine and Madson 1996). Specifically, because of physiologically compatible thermal

conditions characteristic of the tropics, tropical ectotherms allocate relatively less energy towards

behavioral thermoregulation. In theory, reptiles invest more in active thermoregulation when the

benefits outweigh the costs and there are relatively few physical or energetic constraints (Spotila

et al. 1972; Heatwole 1976; Huey and Slatkin 1976). This may occur in a thermally variable

environment where there are many thermal choices and many avenues of heat exchange for an

ectothermic animal (Heatwole 1976; Lang 1979; Lang 1987; Slip and Shine 1988; Shine and

Madson 1996). Given the opportunity, a thermal strategy tends to evolve in which an animal

invests more into remaining, by means of active behavior, within a narrow range of temperatures

(Huey and Slatkin 1976). In other words, reptiles will thermoregulate when it is necessary and

when there are opportunities to do so. In the spring throughout their natural range, alligators

respond by actively engaging in behaviors such as basking and orienting their bodies in relation

to the sun's rays to optimize solar absorption (Spotila et al. 1972; Fish and Cosgrove 1987;

Mazzotti 1989). In the Everglades, this active heat-seeking behavior is reflected in the fact that

alligator body temperature is most variable in the spring and often higher than that of the

surrounding environment (Abercrombie et al. 2002).









Alternatively, reptiles in thermally equable environments (where thermal choices are

limited) or in environments with high cost: benefit ratios generally adopt a more thermal

generalist strategy and thermally conform to their surrounding environment (Heatwole 1976;

Huey and Slatkin 1976; Lang 1987; Shine and Madson 1996). In other words, reptiles will not

thermoregulate when it is physiologically unnecessary or there are no opportunities to do so.

Behavioral thermoregulation has its associated costs and if these costs are great thermoregulation

becomes disadvantageous. Behavioral thermoregulation can only be beneficial when its costs are

relatively low, and thermal specialists will engage in thermoregulation more than thermal

generalists unless costs are high (Heuy and Slatkin 1976). The advantage of this strategy is

simply to conserve energy stores. By becoming less active, metabolic rates are reduced and

energy is conserved for other processes such as growth or reproduction (Lang 1987). For

example, during the hotter portions of the year, many tropical reptile species also become more

nocturnally active and thus avoid the intense heat of the day (Heatwole 1976; Huey and Slatkin

1976; Shine and Madson 1996; Luiselli and Akani 2002).

Spring in south Florida may be considered an environment with a lower cost: benefit ratio

to alligators due to less extreme ambient temperatures, more variable thermal environments, and

more concentrated, available food resources that result from annual dry downs. During this time,

alligators could theoretically afford to invest more in behavioral thermoregulation and would

behave as thermal specialists. In summer and possibly fall, south Florida becomes an

environment with a high cost: benefit ratio for alligators due to consistently high temperatures

coupled with low food resources due to increasing water depths and prey dispersal (Barr 1997;

Dalrymple 1996; Kushlan and Jacobsen 1990). During this time, south Florida alligators may be

unable to invest as much into behavioral thermoregulation and the strategy may shift from that of









a typical thermal specialist species to that more of a typical thermal conformer, as strategies of

thermoregulation and thermal conformity likely occur on some continuum (C. O. Da C.

Diefenbach 1975).

The purpose of this study was to extend knowledge of the behavioral ecology of alligators

in the seasonally fluctuating and anthropogenically controlled south Florida environment. I

investigated alligator behavioral response to environmental conditions by investigating

emergence behavior. I viewed emergence rates (proportion of time spent at the water' s surface or

on land) as an index of heat seeking or heat avoidance behavior, as alligators are known to

behaviorally thermoregulate both on land and at the water surface by assuming various postural

positions or by varying the proportion of the body that is exposed (Fish and Cosgrove 1987;

Lang 1987). Specifically, I investigated effects of season, solar radiation, nocturnal behavior, and

water depths on emergence activity. I hypothesized that Everglades alligators would show lower

emergence rates in summer, followed by fall and then spring due to a general avoidance of

intense heat and decreasing thermoregulation with increasing heat. Unfortunately I was unable to

test emergence rates in winter; however Everglades alligators are thought to be highly inactive

during the colder winter months, usually resting in shallow water with only their nostrils exposed

(Morea 2000). I also hypothesized that higher water depth would reflect higher summer

temperatures and result in lower emergence rates. Alligators depend on water for effective

cooling during summer, and water depths are highest in the summer. I expected solar radiation to

positively influence emergence rates in the spring, but to negatively influence emergence rates in

summer and fall when heat is avoided by alligators. I also hypothesized that alligators would be

more nocturnally active in summer and fall like many temperate and tropical ectotherms,

including other crocodilians (Mazzotti 1989; Luiselli and Akani 2002). Essentially, I expected to









see behavior that reflects low cost: benefit ratios during the relatively cooler portions of the year

and behavior that suggests a high cost: benefit ratio during summer and fall.

I also examined effects of size, sex, and body condition on alligator emergence rates.

While large and small individuals within a species generally hold the same body temperatures,

they accomplish this by different means (Mazzotti 1989). For example, all crocodilians depend

on solar radiation and conduction in water to alter their internal temperatures, but as size

decreases, the importance of the convective environment (ambient air temperatures) becomes

more important (Lang 1987; Mazzotti 1989). Larger crocodilians also lose heat at a slower rate

compared to smaller crocodilians and have comparatively more stable body temperatures than

smaller individuals (Wright 1987). I hypothesized that since the body temperatures of relatively

smaller alligators are more quickly adjusted by the thermal environment, these individuals will

more often exploit the full spectrum of thermal options and as a result may be more active in

patterns of emergence and submergence. On the other hand, I hypothesized that larger

crocodilians, once having achieved optimal body temperatures in the morning (Lang 1987;

Mazzotti 1989) might be expected to spend most of their time submerged in the aqueous portion

of their habitat, especially in the hotter months, and would invariably would spend less time

emerged than smaller individuals. Larger crocodilians are also expected to have potential for

longer dives due to their mass-dependent rates of oxygen consumption (Wright 1987).

Additionally, metabolic heat production may be significant for larger alligators (Lang 1987;

Mazzotti 1989) and this would result in larger individuals having to spend even less time seeking

radiation at the water surface.

I included the role of body condition to account for the likely variability in physical

condition that may influence the effect of alligator size on emergence rates, as measured by









mass/length relationships. Also, the relative physical condition of an individual Everglades

alligator, as revealed by body condition score (Zweig 2002), may have an effect on its ability to

tolerate environmental stressors. I hypothesized that alligators with higher body condition scores

will show higher emergence rates during the hotter parts of the year compared to alligators with

low scores.

Some authors report a male-biased sex ratio in alligator captures (Chabreck 1965;

Woodward and Marion 1979; Woodward and Linda 1993). Male alligators are also know to have

larger home ranges and higher levels of movement compared to females (Chabreck 1965;

Howarter 1999). Female alligators may be more sedentary and secretive in nature. For this

reason, I expected to see a higher rate of male emergence over female emergence.

Materials/Methods

Study Area

This study was conducted within the Arthur R. Marshall Loxahatchee National Wildlife

Refuge (LOX) located in western Palm Beach County, Florida (Fig. 2-1). LOX is an

approximately 57,324 hectare refuge that represents the northernmost extent of the Greater

Everglades Ecosystem. LOX is characterized by having a deep layer of peat and organic soil

(Richardson et al. 1990; Davis et al. 1994) atop bottom bedrock with large areas of open sloughs,

wet prairies, and sawgrass strands (Richardson et al. 1990). My study site is within the south-

central portion of LOX, an area defined by a relatively stable, year-round hydroperiod,

comparatively dense vegetation, and a relatively high alligator density (L. Brandt, pers. comm.).

Telemetry

I used radio transmitters attached to the parietal bones of twenty-eight alligators to

investigate emergence rates in this study. Custom VHF transmitters were equipped with

conductivity switches that doubled the pulses per minute of the broadcasted signal when the









transmitter was under water. Transmitters were also designed to digitally broadcast the

proportion of time the transmitter was underwater during the last hour. A fixed antenna and radio

receiver were installed at the study site (UTM 17R 0573247, 2926401) and were used to detect

and record the status of all deployed transmitters. The receiver was programmed to cycle

continuously through all deployed transmitters so that each frequency was searched and its status

recorded once per hour. In addition to the antenna/receiver, a weather station was installed at the

study site to record solar radiation. Weather data were correlated with emergence data recorded

by the fixed receiver to determine potential relationships between alligator behavior and solar

radiation. Transmitters remained attached for roughly four months, and the study consisted of a

2005 (wet season, July-November, 10 alligators) and 2006 (dry season to onset of wet season,

April-August, eighteen alligators) field season (See Appendix A for full details of telemetry

methodol ogy).

Nest Searches

Nest searches were also conducted for every female used in this study. These searches

consisted of driving the airboat in parallel transects for approximately 0.5 kilometers on all sides

of the capture sites of all females. The purpose of these searches was to obtain nesting

information for the Refuge database, but was also relevant for this project because any data

obtained from a nesting female may have biased the results due to altered behavior during

nestmng.

Data Protocols/Management

Protocols were developed to edit the data so that only accurate and reliable data were used

for analysis. Full details on data protocols and management are in Appendix B.

Daily water depths (meters above bedrock) were collected by the USGS I-9 water gauge

located within the study area. Sunrise/sunset tables were obtained using data from the U.S. naval









military astronomical observatories at http://aa.usno.navy.mil. Nocturnal hours were defined as

the first and last hours of the night that were characterized by full darkness, thus excluding the

confounding twilight hours. Daylight hours were determined similarly. Furthermore, season was

divided into calendar spring (from beginning of study season until 20 June 2006), summer (21

June- 22 September 2005, 21 June- 23 September 2006, and fall (beginning 23 September in

2005 until end of study season) for both years. I did not investigate wet season versus dry season

per se, since the onset of these seasons are variable from year to year. Instead, I investigated wet

conditions versus dry conditions. Solar radiation data were collected by the weather station.

Data Analysis

Data were analyzed using the GENMOD procedure in the Statistical Analysis System

(SAS 1985). The analysis was essentially a time-series logistic regression (White 1990), where

the dependent variable was a binomial response of an alligator being emerged or submerged and

independent variables included season, solar radiation, nocturnal hours, and water depth. All

analyses were conducted on an hourly scale. Since two weather readings were recorded every

hour, averages of each independent variable were calculated using SAS and these averaged

values were used in the analysis. The proportion of total alligators emerged at any given hour

was used to investigate patterns of activity.

Since I investigated proportions of animals rather than individual alligator patterns of

activity, effects of alligator size, body condition, and sex on emergence probabilities were

analyzed separately using the GLIMMIX procedure in the Statistical Analysis System. Since the

"size, condition, sex" model involves measurements of individual alligators, I chose the

GLIMMIX procedure since it incorporates random effects. For this analysis, I used a subset of

the data (due to data-related size constraints in the analysis) and analyzed only July emergence

data to address my hypotheses regarding alligator size, body condition, and sex. By examining









one of the hotter months out of the year, I will be able to get a better picture of how alligators

respond to the high cost- low benefit environment characteristic of the south Florida summer. I

calculated body condition of my study animals using head length/mass Fulton' s K as proposed

by Zweig et al. (2002), as this index allows for a spatial comparison of alligator populations.

For each alligator, data collected began on the second day post-attachment to account for

behavior in response to capture and transmitter attachment. Since many transmitters detached

before they were collected, a conservative estimate of transmitter detachment time was

determined for each animal as the end point for data used in this analysis. This estimate was

based on the last collected data points with correct digital IDs and an emerged status.

A preliminary analysis of the data revealed a significant difference in emergence

likelihood among the 2005 and 2006 study periods. However, each Hield season was meant to

represent different seasons of the year. There were differences in emergence rates between

seasons independent of year. Although some overlap existed for summer months the data were

pooled and analyzed using only seasons, not years, as covariates.

Modeling

Environmental variable analysis

For modeling purposes, I modeled the proportion of total telemetered alligators emerged

as a function of season, solar radiation, nocturnal hours, and water depths (Table 2-1). An

Akaike Information Criterion (AIC) for model selection was calculated for each model and was

used to determine which variables or combination of variables created the best fit for modeling

emergence behavior (Pollock et al. 2002). Essentially, AIC penalizes for the addition of

parameters, and thus selects a model that fits well but has a minimum number of parameters.

Akaike weights were also calculated. The Akaike weight of a particular model describes, given

the set of model used, and given that particular dataset, the probability that that particular model









would be the best one to describe the observed data. Model averaging was also done to

incorporate the strengths of each competing model into a final model that would best describe

the data collected. Model averaging essentially allows computation of a weighted average of a

parameter from the competing models in the model set. By doing so, model selection uncertainty

is included in the estimate of precision of the parameter, and thus unconditional estimates of

variances and standard errors are produced.

Size, condition, and sex variable analysis

For this analysis, I modeled the probability of emerged status of all telemetered alligators

as a function of size (large or small as defined by being larger or smaller than the mean weight of

all alligators in the study), condition (Zwieg et al. 2002), and sex (Table 2-2). In addition to

modeling size, condition, and sex, I modeled possible interaction effects between these three

variables and included sex~size, sex~condition, and size~condition. Since the GLIMMIX

procedure generates only psuedo-liklihoods and psuedo-AIC's, a comparison among different

models is not applicable.

Results

Environmental Variable Analysis

"Model One" was the most general model including incorporated all of the individual

parameters tested and was selected as the best overall model in the set. "Model One" had the

lowest AICC and a AICC value, as well as the most significant Akaike weight (0.91) (Table 2-

2). Incorporating the effects of all variables into the model was therefore very important. Of the

entire model set, only four models had any Akaike weight at all. All of these models included the

season variable, the solar radiation variable, water depth, and a seasonal interaction variable.

Models that did not have these variables had no weight (Table 2-2).









Based on regression coefficient values (p-values) of the final averaged model, it is

apparent that alligators in this study showed a higher probability of emergence in the spring

compared to that of autumn (P spring = 1.252 > B autumn = 0. 132) (Table 2-3). It is also apparent that

when compared to spring and autumn, alligators were less likely to be emerged at any given time

during summer (P spring = 1.252 > P summer = 0; B autumn = 0.132 > P summer = 0) (Table 2-3). The

regression coefficients of the final averaged model also indicated that solar radiation had an

overall negative influence on emergence probabilities, but this effect was slight (P solar = -0.001)

(Table 2-3). However, solar radiation had a slight but positive influence on emergence

probabilities in the spring and autumn when compared to summer (P spring = >0.001 > P summer = 0)

(Table 2-3). This result translates into the trend that alligators avoid solar radiation to a greater

degree in the summer, although again the difference was slight. Another finding based on the

final model is that alligators were less likely to be emerged during the day than at night (P day=

-0. 148 < P night = 0) (Table 2-3). Alligators also showed a greater degree of nocturnal behavior in

spring compared to autumn and summer ((8 spring = 0.058 > 8 autumn = -0.683, P summer = 0) (Table

2-3). Finally, based on the regression coefficient values of the final averaged model, relatively

higher water depths had a negative effect on the emergence rates of alligators (P depth = -0.077)

(Table 2-3).

Size, Condition, and Sex Variable Analysis

Regression coefficient values indicated that in the month of July, the relatively smaller

animals used in this study were more likely emerged at any given time compared to the larger

individuals (F small= 0.1705 > F large= 0) (Table 2-4). Females were also less likely to be emerged

than males in this study (F female = -1.4707 < F male = 0) (Table 2-4). Based on regression

coefficient values, it is apparent that emergence rates were positively correlated to body

condition (F condition = 0. 1498) (Table 2-4). Many of the alligators examined in the study had









overall poorer body condition when compared to average body conditions for other areas in

south Florida (Table 2-5), although overall this tendency was not significant (p-value = 0.17)

(Table 2-6). Spring 2006 study animals had overall poorer body condition when compared to

average body conditions for other areas in south Florida (p-value = 0.05) (Table 2-7), but fall

2005 study animals did not differ (p-value = 0.88) (Table 2-8). Body condition was higher in the

fall compared to the spring among the study animals (Table 2-5). Spring-captured 2006 study

animals had poorer body condition even when compared to spring-captured LOX alligators in

other recent years (Table 2-9). This trend was apparent but not quite significant (p-value = 0.07)

(Table 2-10).

Discussion

Seasonal Activities

The final model indicated a higher probability of emergence in spring compared to that of

fall (Table 2-3). If springtime in the Everglades does represent more of a temperate environment

with a low cost: benefit ratio, these results suggest that alligators are investing energy into active

thermoregulation with increased basking behavior, assuming active behavioral thermoregulation

has an associated energetic cost (Huey and Slatkin 1976; Seebacher and Grigg 1997).

Abercrombie et al. (2002) report that Everglades alligators achieved warmer temperatures than

their environment in the spring, when they are thought to more often leave or emerge from the

water to bask. This active heat-seeking behavior is also reflected in the fact that alligator body

temperature is most variable in the spring and often higher than ambient temperatures (Howarter

1999; Abercrombie 2002). Everglades alligators are hypothesized to spend their time feeding in

the spring, taking advantage of the spring concentration of aquatic food resources during the

seasonal dry down (Mazzotti and Brandt 1994; Dalrymple 1996; Barr 1997). Alligators are also

hypothesized to seek heat after feeding (Lang 1979; Fish and Cosgrove 1987). Everglades










alligators may be emerged more often in spring because they are elevating their body

temperature following feeding. This would decrease digestion time and allow the alligator to eat

again while food is relatively plentiful. Alligators would therefore be emerged less in summer

and fall not necessarily because it is too hot but because they are not feeding, and are therefore

not seeking heat for digestion. Because alligators experience reduced benefits in the summer and

fall since they are typically eating less, they may also be reducing the costs by reducing

behavioral thermoregulation and drifting towards thermal conformity on the continuum.

Other natural behaviors besides thermoregulation could also help explain these results.

Alligators move more during the spring in response to the breeding season (Chabreck 1965), and

this may also help to explain the results of this study. In addition, other seasonal variations not

specifically measured in this study may exert additional influence over alligator behavior. Many

reptiles (and indeed other forms of life) are especially sensitive to seasonal photoperiods, and it

is the photoperiod that often acts as a behavioral and physiological trigger (Heatwole 1976; Lang

1976; Christian and Weavers 1996). Lang (1976) proposed that photoperiod may even be a more

important cue than temperature in determining alligator amphibious behavior. If this is the case,

then Everglades alligators might react in a predictable way regardless of water depth. With

consistently low or high water depths across seasons, alligators would not engage in a thermally

optimal behavior, which would have negative effects on individual Sitness and ultimately on

populations.

Solar Radiation

Solar radiation had an overall negative influence on emergence probabilities in this study

(Table 2-3). Alligators also avoided solar radiation to a greater degree in the summer (Table 2-3).

The results of this study suggest that alligator thermoregulatory behavior shifts from heat seeking

to heat avoidance and reflects an environmental transition from a relatively low cost: high benefit









environment to a high cost: low benefit environment. Alligators in south Florida likely have no

problems in achieving optimal temperatures in the spring through active heat seeking.

Heat seeking behavior is generally described for the temperate alligator (Mazzotti 1989).

Specifically, alligators are said to move onto land in the morning to bask and remain emerged, at

least partially, throughout the day. Alternatively, tropical crocodilians such as Crocodylus

porosus generally display heat avoidance; they will bask in the early morning and spend the rest

of the day submerged (Grigg et al. 1985; Mazzotti 1989). However, the same heat avoidance

behavior has been reported for American alligators during summer months in south Florida

(Howarter 1999). Alligators in the Everglades struggle to keep their body temperatures low

enough to be in the optimal range and thus exhibit heat avoidance during the summer months

(Howarter et al. 2000). Summertime heat avoidance by alligators is also suggested by Goodwin

and Marion (1979), who report that alligators in a lake in Alachua county, north-central Florida,

showed a decrease in activity during the hot summer months. Lang (1987) suggested that a

crocodilian's thermal preference is inversely related to its thermal environment. Specifically,

thermoregulation is obvious in species occupying thermally variable environments while

strategies of thermo-conformity characterize species living in thermally equable environments

(Lang 1980). In any case, it can be argued that south Florida alligators exhibit a kind of

fluctuating behavior between thermoregulating and thermoconforming crocodilians.

Although south Florida may be considered an environment with a relatively lower cost-

higher benefit (to an alligator) during the cooler portions of the year, and an environment with a

relatively higher cost- lower benefit during summer and fall, it may not be accurate to say that

alligators invest less energy into thermoregulation. Heat avoidance behavior by alligators is still

thermoregulation and may represent considerable cost. However, alligator body temperature is










hypothesized to show more variability between the environment in the spring compared to

warmer times of the year such as summer and fall (Howarter 1999, Abercrombie et al. 2002).

This suggests that alligators approach thermal conformity in the hotter months as it does in the

colder winter months as well (Howarter 1999).

Strategies of thermoregulation and thermal conformity likely occur on some continuum (C.

O. Da C. Diefenbach 1975). In other words, there may not be an example of a "perfect"

thermoregulator or a "perfect" thermal conformer. Many tropical species have been observed to

display heat seeking behavior (Luiselli and Akani 2002; Seebacher et al. 2005), and it is likely

that many ectotherms have different preferred body temperatures depending on their activity

(Lang 1979). Although alligators seem to approach thermal conformity during the hotter months

in south Florida, they are not "perfect" thermal conformers since the availability of alligator

holes allows an effective escape from the heat. Alligators have also been observed actively

avoiding heat when temperatures approach or exceed 35oC (Fish and Cosgrove 1987).

Unfortunately, data for winter behavior are lacking in this study. Strangely, alligators only

sporadically exhibit heat-seeking behavior in the winter through much of their Florida range

(Brisbin and Standora 1982). Alligators only episodically seek relative warmth in the winter, and

show thermal conformity to deep water temperatures with body temperatures cooler than shallow

water temperatures by an average of 3.6 oC (Howarter et al. 2000). During winter months across

the alligator' s range it is probably too cold to feed and alligators might deal with the lack of food

by staying cool and minimizing their metabolism. It has been suggested that alligators allow their

bodies to cool in the winter but occasionally heat up to help remove metabolic wastes (Howarter

1999). Emergence probabilities as a function of solar radiation winter remain to be tested.









Circadian Rhythms

Alligators were less likely to be emerged during day than at night (Table 2-3). Alligators

in south Florida are often confronted by excess heat and may respond by becoming more active

during cooler nighttime hours. The results of this study showed this trend especially in summer

(Table 2-3). Interestingly, results show that alligators are more nocturnally active in summer

compared to autumn. Summer is presumably the season which brings on the highest level of heat

in south Florida (Barr 1997; Howarter 1999). Alligators probably become more nocturnally

active in the summer months, compared to autumn, to climb onto land and release excess heat.

When confronted by high heat and low food densities that characterize the south Florida autumn,

alligators may start to become less active both day and night.

A comparison between alligator nocturnal behavior across their natural range may yield

interesting results. In the meantime, our results are similar to those reported from earlier studies

on Crocodylus porosus (Grigg et al. 1985) and Crocodylus johnstoni (Seebacher et al. 2005).

Underwater dives occurred more often and for longer periods of time during daylight hours in

the estuarine crocodile (Crocodylus porosus) studied by Grigg et al. (1985). The authors suggest

that this species, like all crocodilians, are good visual predators and that daylight

foraging/feeding is a reasonable explanation for this pattern of activity. Another explanation is

that daylight hours are spent resting on the bottom, but this explanation is less likely due to

apparent irregularity of surfacing intervals. Interestingly, crocodiles spent more time emerged

during daily low tides, perhaps comparable to a relatively shallower aquatic habitat like the

Everglades. Water depths may drive behavior of this species in a different way than researchers

have seen in the American alligator. Seebacher et al. (2005) reported similar results for

Crocodylus johnstoni. This species appears to be diurnally active in terms of diving behavior and

spends most of the nighttime hours at the surface of the water. Activity patterns in C. johnstoni









reflected but preceded both body temperature and solar radiation, and diving behavior began to

decrease as body temperature and solar radiation peaked (Seebacher et al. 2005). Interestingly,

this tropical species appears to show a heat-seeking behavior, being emerged more with high

levels of solar radiation. A possible explanation for this trend is that C. johnstoni may forage

differently than A. mississippiensis, and its behavior reflects that of its prey. Alternatively, C.

johnstoni may operate in a significantly higher or more variable range of optimal body

temperature than does A. mississippiensis. Any interpretation of reptilian thermoregulatory

behavior must consider the physiology of the species in question. For example, some semi-

aquatic tropical lizards have been observed to thermally select for lower temperatures than their

terrestrial counterparts (Christian and Weaver 1996). Also, inferences drawn regarding alligator

thermal selection must also consider other behavioral activities. There always exists the

possibility that thermoregulation may sometimes take a backseat to other natural behavior

including underwater foraging/feeding and social interactions.

Water Depths

Alligator movement is said to increase with increased water depth (Chabreck 1965). In

this study, alligators were less likely to be emerged in relatively deeper water (Table 2-3). These

results support my hypothesis that higher water depth would result in lower emergence rates.

Other seasonal variations, as previously discussed and independent of water fluctuations, may

exert more influence over alligator behavior and may effectively override the influence of water

depths.

Although LOX experiences seasonal fluctuations in water depths as does the rest of the

Everglades ecosystem, the differences are often less extreme (Richardson et al. 1990). Unless it

is an exceptionally dry year, LOX inner marshes are characterized by a year-round hydroperiod.

However, I may have been lucky in my choice of field seasons. Fall 2005 was an exceptionally










wet year and LOX experienced unusually elevated fall water depths as a result of several tropical

storms and hurricanes. Spring 2006 was remarkably dry, as significant rainfall did not occur until

relatively late in the summer. Until then, much of the interior marshes at LOX had turned into

mudflats (CB, pers. obs.).

Effects of water depths versus season are difficult to separate. It becomes difficult

however to test the effects of varying water depths independent of season. Even by correcting for

water depth, other seasonally dependent variables such as photoperiod and prey availability are

not accounted for. To understand relationships between water depth and season, this study would

need to be repeated in a compartment of Everglades where water depths are known to be

exceedingly high or exceedingly low in spite of season, and results then need to be compared.

The Greater Everglades Ecosystem, in regards to its compartmentalization and experimental

water regimes, provides the best natural (or unnatural) laboratory in which to study such a

relationship.

Alligator Size

My hypothesis that larger crocodilians might be expected to show a lower degree of

emergence than smaller individuals was supported by the results of this study (Table 2-4), at

least during a period of high costs and low benefits. Although the sample size was relatively

small, and all alligators were adults, the smaller individuals in the study were more likely

emerged at any given point in time compared to the larger individuals in the study during the

months of July.

Larger crocodilians lose heat at a slower rate compared to smaller crocodilians and have

comparatively more stable body temperatures than smaller individuals (Wright 1987).

Additionally, metabolic heat production may be also significant for larger alligators (Lang 1987;

Mazzotti 1989). During the hot summer months, the largest alligators in this study appear to have









consistently selected the cooler environmental medium, for example the water during the day and

the ambient air at night. They showed lower emergence rates in July and more often remained in

the relatively cooler conductive medium than smaller individuals. Larger alligators would have

the inherent potential to avoid solar radiation and remain in the conductive environment for

longer as they have the physiological potential for longer dives due to their mass-dependent rates

of oxygen consumption (Wright 1987). The smaller alligators in the study may have been able to

more quickly cool off in the conductive environment and as a result could more often return to

the solar radiation at the water surface. As alligator size decreases, the importance of the

convective environment (ambient air temperatures) also becomes more important (Lang 1987;

Mazzotti 1989).

Alligator Condition

My hypothesis that alligators with higher body condition scores will show higher

emergence rates during the hotter parts of the year compared to alligators with low condition was

also supported. Body condition showed a positive relationship with emergence rates in this study

(Table 2-4). I would hypothesize further that individuals in better condition are better able to

handle additional environmental stressors. Although some reptiles have been known to seek heat

while physically ill, this is usually a response to combat pathogens (Lang 1987) and heat-seeking

does not seem to be a response to low energy stores.

Many of the alligators examined in the study were underweight and had overall poorer

body condition when compared to average body conditions for other areas in south Florida

(Table 2-5). Spring-captured 2006 study animals had poorer body condition even when

compared to spring-captured LOX alligators in other recent years (Table 2-10). This may be due

to intense heat experienced by these alligators coupled with the extended hydroperiod at LOX

that does not adequately allow physical concentration of prey, especially following prolonged










high water depths brought about by the storms and hurricanes of 2005. The sub-optimal physical

condition of these individuals may have affected their natural behavior. An individual in poorer

condition will be less able to tolerate environmental stressors. Some of these individuals may not

have been ideal representatives for the species as a whole, or even for other population in south

Florida. The poor condition of some of the females used in the study may also explain the lack of

active nests.

That body condition was higher in the fall compared to the spring among the study

animals (Table 2-4) suggests that summer, fall, and winter seasons are probably energetically

demanding for Everglades alligators. By spring alligators are in poor condition. However, spring

is the season in which alligators are able to recover from seasonal trials (Dalrymple 1996; Barr

1997; Howarter 1999). Spring is metabolically the most important season for alligator

populations in the Everglades due to breeding cycles and feeding on concentrated food supplies

during the dry season (Dalrymple 1996; Abercrombie et al. 2000). Spring feeding will result in a

recovery of fat stores and an increase in body condition by the fall (Abercrombie et al. 2000).

This demonstrates the importance of seasonal conditions to the long-term survival of Everglades

alligators.

Alligator Sex

My hypothesis that male alligators would show higher rates of emergence was supported

by this study. Male alligators in this study were less likely to be emerged than females at any

given point in time in July. Female alligators may be more secretive by nature and would

therefore spend more time underwater. This possible trend was evident during the capture

sessions of study animals across both years. For example, a 7:3 male: female sex bias resulted

from opportunistic captures among the 2005 study animals. In 2006, I actively selected for more

females but still ended up with more males. This may suggest that either there is a male bias in









the local population, or that females are simply more secretive than males by nature. Similar

capture rates sex biases have been described for this species elsewhere (Chabreck 1965;

Woodward and Marion 1979).

In the presence of researcher activity, male alligators may be more likely at the surface

than females due to territorial or other aggressive behaviors but this remains to be tested. Male

alligators are generally thought move more than females (Spratt 1997). Researcher presence

could be included as another independent variable in future studies as human/airboat presence

likely has some short-term effects on crocodilian emergence behavior (Webb and Messel 1979;

Woodward and Linda 1993; Pacheco 1996).

Implications and Future Work

Water depth is known to affect courtship, nesting, growth and survival, but may also have

impacts on other behavioral adaptations of American alligators including thermoregulation.

Summer and autumn temperatures, coupled with low food availability, are such physical

stressors that alligators are dependent on the availability of standing water to escape heat and

avoid activity. When water dries up completely, behavioral patterns are disrupted including those

associated with thermoregulation (Spotila et al.1972). If alligators in south Florida are deprived

of water in summer and fall, their chances of survival, on an individual and population level,

begins to fall. High summer heat requires greater summer water depths to provide thermal

refugia (Howarter 1999), since behavioral avoidance of heat occurs at the bottom of a substantial

water column. However, annual water depths cannot be too high, because Everglades alligators

depend on seasonal dry-downs that result in concentrated food supplies (Jacobsen and Kushlan

1989; Dalrymple 1996; Barr 1997). If natural conditions and water cycles are not maintained in

the Everglades, alligators may not optimally thermoregulate. For example, if water levels are too

high in the spring, and spring shifts to a low cost: low benefit environment, alligators may










respond by allocating energy towards careful behavioral thermoregulation but without the

energetic gains of concentrated aquatic food. Similarly, if water levels are too low in the summer

and fall, and the environment becomes one of high costs and high benefits, would alligators

effectively miss the opportunity to feed and restore energy stores as they avoid heat? The end

result could have negative effects on the fitness of individual animals, and ultimately have

negative impacts at the population level. Everglades alligators are ultimately dependent on the

natural seasonal variations and heterogeneity that characterizes the greater Everglades

ecosystem.

A repeated study of similar design is suggested for locations in north Florida and/or

another northern part of the alligators range for comparison. This would also enable us to

corroborate whether any behavioral shifts occur across alligator populations as a function of

latitude. A repeated study would also offer a comparison between alligators of varying body

condition.

Finally, an interesting variation to the study design is also proposed. By adding an

additional transmitter of similar design, one on the head as well as one attached mid-dorsally on

the base of the tail, researchers could consider when an alligator is emerged or submerged, as

well as when an alligator is in water or on land. This information will offer us more insight into

thermoregulatory behavior and under what specific conditions are alligators leaving and

reentering the aquatic portion of their habitat.

Understanding alligator responses to differences in seasonal conditions allows us to better

understand potential responses to alternate restoration actions in the Everglades. Understanding

the thermal ecology of the American alligator in south Florida will allow managers to make more

informed decisions regarding habitat restoration, especially in regards to appropriate water










depths. The emergence behavior presented here can also be practically applied to improve the

efficacy of south Florida alligator surveys. The results of this study have hopefully shed some

light on alligator behavioral ecology in south Florida, and these results may have important

implications regarding alligator surveys as well as conservation/management decisions.











I _J Arthur R. Marshall
Loxahatchee
Big Cypress -YNational Wildlife
National Refuge
Preserve,

WCA3

WCA2


SWCA3B \Study
Everglades~ Site
National
Park


Florida
Bay



Figure 2-1. Study site at Arthur R. Marshall Loxahatchee National Wildlife Refuge.













Table 2-1. Environmental variables of all models used to describe the emergence dynamics of
alligators in Arthur R. Marshall Loxahatchee National Wildlife Refuge.
Model 1 Model 2 Model 3 Model 4
Season Season Season Season
Water depth Water depth Water depth Water depth
Solar radiation Solar radiation Solar radiation Solar radiation
Night Night Night Night
Solar Solar
radiation*season rad iation*season Night*season
Night*season


Model 5
Water depth
Solar radiation
Night


Model 9
Season
Solar radiation
Night
Solar
radiation~season
Night*season


Model 13
Season
Water depth
Solar radiation
Solar
radiation~season


Model 6
Water depth
Night



Model 10
Season
Solar radiation
Night
Solar
rad iation*season


Model 7
Solar radiation
Night



Model 11
Season
Solar radiation
Night

Night*season


Model 8
Night





Model 12
Season
Solar radiation
Night


Model 14
Season
Water depth
Solar radiation


Model 15
Season
Solar radiation


Model 16
Season
Water depth


Model 17 Model 18
Season Season
Water depth Water depth
Night Night
Night*season
*Model 1 represents the general model


Model 19
Season
Night


Model 20
Season










Table 2-2. The AICC, a AICC, and Akaike weights of 20 models used to describe the emergence
dynamics of alligators in Arthur R. Marshall Loxahatchee National Wildlife Refuge.
MODEL AICC a AICC AKAIKE WEIGHT
1 35074.31 0 0.91
2 35078.91 4.6 0.09
13 35091.25 16.93 <0.01
3 35097.61 23.29 <0.01
4 35102.75 28.44 0.00
14 35117.28 42.96 0.00
5 35177.36 103.05 0.00
9 35879.21 804.90 0.00
10 35883.54 809.23 0.00
11 35899.21 824.90 0.00
12 35904.32 830.01 0.00
15 35918.19 843.88 0.00
7 36129.64 1055.32 0.00
17 43652.47 8578.16 0.00
18 43660.88 8586.56 0.00
6 43737.70 8663.39 0.00
16 43818.98 8744.67 0.00
19 44474.17 9399.86 0.00
20 44633.77 9556.46 0.00
8 44824.13 9749.81 0.00
* AIC values represent a relative index of goodness of fit compared to other models in the
model set; the smaller the value the better the fit. Delta AIC values of< 2 generally
suggest substantial evidence for the model. Values between 3 and 7 indicate that the
model has considerably less support, and values > 10 indicate that the model is highly
unlikely. Akaike weights indicate the probability that the model is the best among the
whole set of candidate models.










Table 2-3. Regression coefficients (p-values) and associated confidence intervals of the averaged
model used to describe the emergence dynamics of Arthur R. Marshall Loxahatchee
National Wildlife Refuge alligators.
PARAMETER (3-VALUE LOWER 95% Cl UPPER 95% Cl
Intercept 15.165 9.600 20.730
Autumn 0.132 -0.066 0.331
Spring 1.252 0.935 1.570
Summer 0.000 0.000 0.000
Water depth -0.077 -0.461 0.308
Daylight -0.148 -0.232 -0.065
Nighttime 0.000 0.000 0.000
Solar radiation -0.001 -0.001 -0.001

Autu mn(n ig ht) -0.683 -0.840 0.527
Spring(night) 0.058 -0.419 0.536
Su mme r(n ig ht) 0.000 0.000 0.000
Autumn(solar) <0.001 <0.001 <0.001
Spring(solar) <0.001 <0.001 <0.001
Summer(solar) 0.000 0.000 0.000
*Intercept' describes the slope of the regression. Parameters with p-values of 0 serve as baseline
measurements from which comparative values are drawn for other parameters in the group. Significant
Pr>ChiSq values (>0.05) indicate the probability under the null hypothesis (the given parameter has no
effect) of obtaining a test statistic at least as extreme as the observed value..










Table 2-4. Regression coefficients of a model used to describe the emergence dynamics of
alligators in Arthur R. Marshall Loxahatchee National Wildlife Refuge based on size,
body condition, and sex.
PARAMETER F-VALUE Pr>F
Intercept -1.9341 <0.0001
Small 0.1705 <0.0001
Large 0.0000 <0.0001
Body condition 0.1498 0.0002
Female -1.4707 <0.0001
Male 0.0000 <0.0001
*Intercept' describes the slope of the regression. Parameters with p-values of 0 serve as baseline
measurements from which comparative values are drawn for other parameters in the group. Significant
Pr>ChiSq values (>0.05) indicate a parameter that has a significant influence in the model.











Table 2-5. Average body condition scores of 1999-2005 south Florida alligators and 2005-2006
Arthur R. Marshall Loxahatchee National Wildlife Refuge alligators.
LOCATION BODY CONDITION SCORE


ENP SS


ENP FC


WCA3A-N41


WCA3A-HD


WCA3B


WCA2A


BICY


LOX

2005-2006
study animals

fall 2005
study animals

spring 2006
study animals


10.8


9.5


9.3


10.7


9.8


10.0


11.1


10.5


9.15


10.1


8.6


Values for all other south Florida locations represent the average values from 1999-2005. All alligators were
caught roughly at the same time of year. 'ENP SS' represents Shark Slough, Everglades National Park. 'ENP FC'
represents Frog City Slough in Everglades National Park. 'WCA3A-N41' represents Water Conservation Area 3A
North of Highway 41. 'WCA3A-HD' represents Holiday Park. 'WCA2A' represents Water Conservation Area 2A.
'BICY' represents locations in Big Cypress National Preserve. 'LOX' represents other areas within A. R. Marshall
Loxahatchee National Wildlife Refuge (Comprehensive Everglades Restoration Plan Monitoring and Assessment
Plan Annual Assessment Report 2006).











Table 2-6. Analysis of variance for average body condition of 2005-2006 Arthur R. Marshall
Loxahatchee National Wildlife Refuge alligators and 1999-2005 south Florida
alligators.
SUMMARY


Groups
1999-2005
2005-2006 study
animals


Count Sum Average Variance
8 81.7 10.21 0.43


1 9.15


9.15


ANOVA
Source of Variation
Between Groups
Within Groups


MS

0.43


F
2.33


P-value F crit
0.17 5.59


Total












Table 2-7. Analysis of variance for average body condition of spring 2006 Arthur R. Marshall
Loxahatchee National Wildlife Refuge alligators and 1999-2005 south Florida
alligators.
SUMMARY
Groups Count Sum Average Variance
1999-2005 8 81.7 10.21 0.43
spring 2006
animals 1 8.6 8.6 N/A

ANOVA
Source of
Variation SS df MS F P-value F crit
Between Groups 2.31 1 2.31 5.38 0.05 5.6
Within Groups 3.01 7 0.43

Total 5.32 8










Table 2-8. Analysis of variance for average body condition of fall 2005 Arthur R. Marshall
Loxahatchee National Wildlife Refuge alligators and 1999-2005 south Florida
alligators.
SUMMARY
Groups Count Sum Average Variance
1999-2005 8 81.7 10.21 0.43
fall 2005 animals 1 10.1 10.1 N/A


ANOVA
Source of Variation SS df MS F P-value F crit
Between Groups 0.01 1 0.01 0.03 0.88 5.59
Within Groups 3.01 7 0.43

Total 3.02 8












Table 2-9. Comparison of average body condition of spring 2006 and spring 1999-2005 Arthur
R. Marshall Loxahatchee National Wildlife Refuge alligators.
BODY CONDITION
YEAR SCORE
1999 10.6
2000 10.5
2001 11.6
2002 10.9
2003 9.4
2004 10.2
2005 9.5
2006 study animals 8.6












Table 2-10. Analysis of variance for average body condition of spring 2006 and spring 1999-
2005 Arthur R. Marshall Loxahatchee National Wildlife Refuge alligators.
SUMMARY


Groups
1999-2005
2006 study
animals



ANOVA
Source of Variation
Between Groups
Within Groups

Total


Count Sum Average Variance
7 72.7 10.39 0.6


8.6 8.6 N/A


SS
2.8
3.59

6.38


F
4.67


P-value
0.07


F crit
5.99









CHAPTER 3
EMERGENCE DYNAMICS OF AMERICAN ALLIGATORS (Alligator mississippiensis) INT
ARTHUR R. MARSHALL LOXAHATCHEE NATIONAL WILDLIFE REFUGE AND THEIR
APPLICATION TO ALLIGATOR MONITORING

Introduction

Alligators are a top conservation concern in the Everglades ecosystem. They are an

excellent indicator of ecological balance and measure of restoration success. The alligator' s

natural sensitivity to fluctuating water depths, as well as their sensitivity to overall system

production as top predators, makes them ideal indicators of the state of the ecosystem (Mazzotti

and Brandt 1994; Rice et al. 2005). Since the success of many other species is dependent on a

natural alligator population (Rice et al. 2004), alligator populations throughout south Florida are

monitored closely as Everglades restoration advances.

Everglades Restoration

Methods are currently being developed for long-term monitoring of American alligator

population trends throughout the Greater Everglades Ecosystem. This monitoring is part of the

Monitoring and Assessment Plan (MAP) of RECOVER (REstoration COordination and

VERification) and has the goal of assessing the impacts of Everglades Restoration. The scope of

work for this study is related to the Comprehensive Everglades Restoration Plan Monitoring and

Assessment Plan (CERP, signed into law in 2000). The relationships between dry season refuge,

aquatic fauna, wading birds, and alligators have been identified as key uncertainties in the CERP.

Alligators were chosen as an indicator of restoration success in this plan due to their ecological

importance and sensitivity to hydrology, salinity, habitat productivity, and total system

productivity (Rice et al. 2005). Models are being developed to predict the response of natural

communities to restoration strategies. Data from this study, among others, will offer information









that will be used to evaluate trade-offs of restoration scenarios. But above all, data from this

study will be used to improve alligator monitoring in the Everglades.

Everglades Alligator Surveys

A network of survey routes was established to assess alligator distribution and abundance

throughout the Greater Everglades Ecosystem beginning in 1998. This network was designed to

monitor changes in alligator populations over time in response to restoration and includes sites in

Arthur R. Marshall Loxahatchee National Wildlife Refuge (LOX). The obj ective of this study

was to improve alligator survey methods within the alligator survey network. Particularly, I

investigated methods that would improve estimates of alligator detectability during spotlight

surveys, thereby decreasing the time required to detect significant trends in alligator populations

following different restoration actions. This research will allow managers to quickly recognize

and respond to a resulting positive or negative population trend, and thus will provide a tool for

adaptive management of Everglades restoration.

Alligator Detectability

During spotlight surveys most individuals in the alligator population are never seen

(Woodward et al. 1996). Previous estimates suggest that the undetected alligators may represent

as much as 91% of the total population (Woodward et al. 1996). During spotlight surveys, the

probability of alligator detection by researchers is a function of observer efficacy, habitat,

alligator wariness due to airboat/human presence, and natural variations in behavior (Graham

and Bell 1969; Murphy 1977; Brandt 1989; Woodward and Linda 1993). This research will

specifically focus on alligator emergence behaviors as they relate to various environmental

factors, with the ultimate goal of correcting survey results in an appropriate manner to account

for bias due to missed individuals. As alligator surveys provide a relative measure of alligator

abundance, information from this study may be used to provide a more accurate index of the real









number of alligators present during surveys, as well as to determine optimal conditions to

conduct surveys.

Determining alligator detectability due to emergence behaviors involves estimating the

probability that an alligator' s head will be above water and therefore available for counting. This

study aims to answer two central questions What proportion of a population would researchers

expect to see under a given set of conditions, and at what time of night and under what

environmental conditions is the largest proportion of alligators at the surface and available for

counting?

Hypotheses

It is assumed that the proportion of time spent emerged is in part a function of

environmental variables including season, water depths, time of night, moon phase, water and air

temperature, rain, and wind speed. My first hypothesis was that time spent emerged will be

highest in the spring, when Everglades alligators are generally more active feeding and breeding

(Mazzotti and Brandt 1994; Howarter 1999; Abercrombie 2002). I also hypothesized that

emergence rates will be higher when water depths are low, both because the dry season occurs

during spring and because there will be less water available water in which to submerge. In

relation to moon phase, I expected to see a positive relationship between emergence rates and

level of moonlight. This assumption is based on results obtained by Woodward and Marion

(1979). In this north-central Florida study, alligator counts during spotlight surveys were

positively correlated with levels of nocturnal light during warm weather. Since south Florida

temperatures are generally higher in all seasons (with the possible exception of summer)

compared to north Florida, I expected to see this positive correlation throughout my study. I

hypothesized that time spent emerged as a function of water temperature will show a slight

positive relationship. This hypothesis was based on results reported from Woodward and Marion









(1979) and Murphy (1977). Woodward and Marion (1979) however suggest that this positive

relationship is strongest during times of relatively cool ambient air temperatures. During warm

weather, this positive relationship between water temperatures and night counts becomes weaker

(Woodward and Marion 1979). Murphy (1977) conducted his research in South Carolina where

relative ambient air temperatures are cooler still. In the warm south Florida climate, the

relationship between water temperature and emergence rates may be slight. I hypothesized that

the relationship between ambient air temperature and emergence rates will be negligible, as

reported by Woodward and Marion (1979). Additionally, I hypothesized that time spent emerged

will show an inverse relationship with wind speed, since submergence is one strategy

crocodilians are known to use to seek protection from wind (Mazzotti 1989; Pacheco 1996).

Relationships between emergence rates and rain were hypothesized to be negligible, as

Woodward and Marion (1979) reported no significant effect of precipitation on nights counts in

their study. Sarkis-Goncalves et al. (2004) reported similar results for Caiman latirostris.

This study will present an index of alligator emergence behavior in response to the above

mentioned environmental predictor variables. The efficiency of the new techniques used in this

study will also be evaluated at the end to determine if they are worth repeating in future studies.

Materials/Methods

Study Area

This study was conducted within the Arthur R. Marshall Loxahatchee National Wildlife

Refuge (LOX) located in western Palm Beach County, Florida (Fig. 2-1). LOX is an

approximately 57,324 hectare refuge that represents the northernmost extent of the Greater

Everglades Ecosystem. LOX is characterized by having a deep layer of peat and organic soil

(Richardson et al. 1990; Davis et al. 1994) atop bottom bedrock with large areas of open sloughs,

wet prairies, and sawgrass strands (Richardson et al. 1990). My study site was within the south-









central portion of LOX, an area defined by a relatively stable, year-round hydroperiod,

comparatively dense vegetation, and a relatively high alligator density (L. Brandt, pers. comm.).

Telemetry

I used radio transmitters attached to the parietals of twenty-eight alligators to investigate

emergence rates in this study. Telemetry equipment for this study included custom VHF

transmitters equipped with conductivity switches used to double the pulses per minute of the

broadcasted signal when the transmitter was underwater. Transmitters were also designed to

broadcast as digital data the proportion of time the transmitter was underwater during the last

hour. A fixed antenna and radio receiver were installed at the study site (UTM 17R 0573247,

2926401) and were used to detect and record the status of all deployed transmitters. The receiver

was programmed to cycle continuously through all deployed transmitters so that each frequency

was searched for and its status was recorded once per hour. In addition to the antenna/receiver, a

weather station was installed at the study site to record environmental data. For the purposes of

this study, weather data were correlated with emergence data recorded by a fixed receiver to

determine potential relationships between alligator behavior and water and air temperature, rain,

and wind speed. Transmitters remained attached for roughly four months, and the study

consisted of a 2005 (wet season, July-November, ten alligators) and 2006 (dry season to onset of

wet season, April-August, eighteen alligators) field season (See Appendix A for full details of

telemetry methodology).

Nest Searches

Nest searches were also conducted for every female used in this study. These searches

consisted of driving the airboat in parallel transects for approximately 0.5 kilometers on all sides

of the capture sites of all females. The purpose of these searches was to obtain nesting

information for the Refuge database, but was also relevant for this project because any data









obtained from a nesting female may have biased the results due to altered behavior during

nestmng.

Data Protocols/Management

Protocols were developed to edit the data so that only accurate and reliable data were used

for analysis. Full details on data protocols and management are in Appendix B.

Water depth data were collected by the USGS I-9 water gauge located within the study

area. Sunrise/sunset tables and moon phase data were obtained using data from the U.S. naval

military astronomical observatories at http://aa.usno.navy.mil. Only nocturnal data were used

since spotlight surveys occur at night. Nocturnal hours were defined as the first and last hours of

the night that were characterized by full darkness, thus excluding the confounding twilight hours.

Moon phases were dived into full moon, half-moon, and quarter moon for analyses. Additional

environmental data were collected by the weather station and included air temperature, water

temperature, rainfall, and wind. Seasons were divided into calendar spring (from beginning of

study season until 20 June 2006), summer (21 June- 22 September 2005, 21 June- 23 September

2006, and fall (beginning 23 September in 2005 until end of study season) for both years. I did

not investigate wet season versus dry season per se, since the onset of these seasons are variable

from year to year. Instead, I investigated wet conditions versus dry conditions.

Data Analysis

Data were analyzed using the GENMOD procedure in the Statistical Analysis System

(SAS 1985). The analysis was essentially a time-series logistic regression (White 1990), where

the dependent variable was a binomial response of an alligator being emerged or submerged and

the independent or predictor variables included season, time of night, moon phase, water depths,

water and air temperature, rain, and wind speed. All analysis was done on an hourly scale. Since

two weather readings were recorded every hour, the averages of each variable were calculated










using SAS and these averaged values were used in the analysis. Due to the vastness of the data

set (28 animals 24 measurements/day ~120 days), l used the proportion of total alligators

emerged at any given hour to investigate patterns of activity.

For each alligator, I deleted data collected during the first day post-attachment to account

for any erroneous behavior in response to capture and transmitter attachment. Since many

transmitters detached before they were collected, a conservative estimate of transmitter

detachment time was determined for each animal as the end point for data used in this analysis.

This estimate was based on the last collected data points with correct digital IDs and an emerged

status.

A significant difference in emergence likelihood among years was apparent in a

preliminary analysis of the data. However, each field season was meant to represent different

seasons of the year. There were differences in emergence rates between seasons independent of

year. Although some overlap existed for summer months the data was pooled and analyzed using

only seasons, not years, as covariates.

Modeling

For modeling purposes, I modeled the proportion of total telemetered alligators emerged

as a function of season, time of night, water depths, water and air temperature, rain, and wind

speed. An Akaike Information Criterion (AIC) for model selection was calculated for each of

several models analyzed and was used to determine which variables or combination of variables

create the best approximating model for emergence behavior data (Burnham and Anderson 2002;

Pollock et al. 2002). AIC penalizes for the addition of parameters, and thus selects a model that

fits well but has a minimum number of parameters. Specifically, AAICC values and Akaike

weights are used in this paper to describe competing models. A negative relationship exists

between AAICC value and fit of a competing model to the data (Burnham and Anderson 2002).









In other words, a model with a relatively small AAICC value is deemed superior when compared

to a model with a larger associated AAICC. The Akaike weight of a particular model describes,

given the data and the model sets tested, the probability that a particular model would be the best

one to describe the observed data. Model averaging was also done to incorporate the strengths of

each competing model into a Einal model that would best describe the data collected. Model

averaging allows computation of a weighted average of a parameter from the competing models

in the model set. By doing so, model selection uncertainty is included in the estimate of precision

of the parameter (Burnham and Anderson 2002). Testing whether or not individual

environmental variables are significantt" is inherent in the model selection process (Burnham

and Anderson 2002). Those environmental variables included in the top models are deemed to be

significant in describing the data observed.

I was also able to examine the effect of each individual environmental variable on

alligator emergence probabilities. Regression coefficients, or 8-values, are used to describe the

slope of the regression (Aiken and West 1991). For every unit change in the value of a measured

predictor variable, the probability of alligator emergence will change as a product of its

associated 8-value (Aiken and West 1991). As such, 8-values were used in this study to describe

the influence of each individual predictor variable on emergence rates, as based on the Einal

averaged model. For example, variables with positive associated 8-values will have a positive

influence on emergence rates, while variables with negative values will have a negative influence

on emergence rates. Levels of categorical variables such as season, time of night, or moon phase,

can be directly compared by comparing their associated 8-values. If for example the 8-value for

categorical variables "x" and "y" are both positive, but the 8-value for variable "x" is greater

than that of variable "y", we can say that variable "x" has a greater positive influence on










emergence rates, or that alligators have a greater chance of being emerged under the influence of

variable "x" compared to variable "y"

Lastly, I randomly extracted 200 lines of data (roughly 10% of the total) and left them out

of the analysis. This data was saved for the purposes of testing model accuracy.

Results

Twenty-nine final models were analyzed (Table 3-1). "Model 5" was essentially the main

model that incorporated all of the individual parameters tested in this study. "Model 1" was

determined as the superior model in the model set based on its small AAICC value (0) and

Akaike weight (0.4133). However, several other models showed relatively close AAICC values

and Akaike weights, and the final averaged model (Table 3-2) accounted for the strengths and

weights of all the significant models. The effect of water temperature and rain may be minor, as

the best model in the set excluded these variables. The next best three models excluded either

water temperature or rain. Common variables found across all significant models based on

Akaike weights (> 0.01) included season, water depth, and wind speed (Table 3-1).

Based on the regression coefficients (8-values) of the final averaged model, it becomes

apparent that alligators in this study showed a higher probability of emergence in the spring

compared to autumn (8 spring = 0.419 > 8 autum = -0.744) (Table 3-2). Also based on the

regression coefficients of the final averaged model, alligators are less likely to be emerged in low

moonlight compared to half moon or full moon cycles (8 quarter moon = -0. 190 < 8 half moon = 0.060,

8 axilmoo = 0) (Table 3-2). Interestingly, alligators are slightly more likely to be emerged during

half moons compared to full moons (8 half moon = 0.060 > 8 axilmoon = 0) (Table 3-2). During

nighttime hours, higher water depths decrease the emergence rates of alligators (8 depth = -0.258)

(Table 3-2). Higher water temperatures result in a slightly lower chance of emergence (8 temp(w)

= -0.012) (Table 3-2). During nocturnal hours higher air temperature results in an increase in










alligator emergence rates (8 temp(a) = 0.016) (Table 3-2). Wind speed had a negative effect on

submergence rates (8 wind = -0.026) as did rainfall (8 rain = -0.003) (Table 3-2).

The data suggested that the proportion of time spent underwater is a function of the

environmental variables tested in this study. My first hypothesis that emergence rates and water

depths will show a negative relationship was supported. My hypothesis that emergence rates will

show a positive relationship with levels of moonlight was only partially supported. In this study,

emergence rates were higher during half and full moons compared to quarter moons, but were

lower during full moons than half moons. My hypothesis that time spent emerged as a function

of water temperature will show a slight positive relationship was not supported. The results of

this study show the opposite trend to be the case. The negative relationship between emergence

rates and wind speed was supported, and the same trend was discovered for precipitation.

The probability of alligator emergence as determined by a given set of environmental

variables is based on the p-estimate of each variable under the model-averaged model. I was able

to generate an equation based on the p-values for each parameter multiplied by values for each

corresponding parameter as measured in the field during a particular survey. The equation is as

follows:


emer"genc =e intrcept + (i~rl Xnrl) Hr (nXnrr2 ** (wind Xwind

In this equation, "P emergency" e TpfeSents the proportion of alligators emerged. "Pintercept"

equals the p-value for the model averaged intercept (Table 3-2). p-values for every

environmental variable, drawn from Table 3-2, are multiplied by values for each equivalent

variable as recorded in the field during a survey ("X"). For example, if during a survey air

temperature is measured at 28.50C, that would be entered into the equation as P temp(air) X temp(air)

or 0.016 28.5 in the equation. For all categorical variables, such as time of night, season, or










moon, enter a "1" for whichever category applies to the survey in question. For example, during

spring surveys, one would enter P spring* X spring Or 0.419 *1 and leave the autumn and summer

parameters out of the equation. The end result of the equation is a prediction of the proportion of

alligators emerged during a given survey.

Equation Accuracy

The accuracy of this equation was tested using the lines of data previously set aside. A

total of 200 randomly picked observations (53 spring, 80 summer, 67 autumn) were used here.

Environmental variables were plugged into the equation, and comparisons were drawn between

the equation-predicted proportion of alligators emerged versus the actual observed proportion of

alligators emerged for each line of data.

The equation tended to over-predict in the spring (Fig. 3-1), and predicted values were

higher than observed 77.36% of the time (Table 3-3). The average difference between predicted

and observed values in the spring was 32.79% (Table 3-3) A paired two-sample t-test for means

revealed a significant difference between predicted proportions emerged and observed proportion

emerged in the spring (df = 52, t-stat = -6.42, Table 3-4). 49.05% of the predicted proportions

fell within one standard deviation of the observed proportions, while 49.05% of the predicted

proportions were greater than one standard deviation over-predicted (Table 3-3).

The equation was much better at predicting proportions of alligators emerged in the

summer and autumn (Fig. 3-1). In the summer, the average difference between predicted and

observed values was 14.23% (Table 3-3) A paired two-sample t-test for means revealed no

significant difference between predicted proportions emerged and observed proportion emerged

in the summer (df = 79, t-stat = -0. 16, Table 3-5). 61.25% of the predicted proportions fell within

one standard deviation of the observed proportions (Table 3-3). 18.75% of the predicted

proportions were greater than one standard deviation over-predicted, while 20% of the predicted










proportions were greater than one standard deviation of the observed proportions under-predicted

(Table 3-3).

In autumn, a paired two-sample t-test for means revealed no significant difference

between predicted proportions emerged and observed proportion emerged (df = 66, t-stat = -0.59,

Table 3-6). 52.23% of the predicted proportions fell within one standard deviation of the

observed proportions, 26.88% of the predicted proportions were greater than one standard

deviation over-predicted, and 20.89% of the predicted proportions were greater than one standard

deviation under-predicted (Table 3-3).

Discussion

Equation Accuracy

The predictive equation was not as accurate in the spring and consistently over-predicted

proportions of alligators emerged (Table 3-3). Additionally, the equation did not seem to account

for the observed variation in emergence rates as well in the spring as it did in the summer and

fall (Fig. 3-1). Alligators were submerged more often than would be expected based on

environmental variables alone. To explain these findings, I suggest that some other variable or

variables that were not measured in this study were effectively overriding the expected influence

of the surrounding environment. The fact that the breeding season of alligators occurs in spring

may account for this unexpected behavior, since most social interactions of alligators occur

underwater (Vliet 1987). Social interactions of alligators are also known to take precedence over

behaviors that may represent an optimal response to environmental conditions (Asa et. al. 1998).

As a result of these findings, managers may opt to conduct alligator surveys in the

summer and fall as opposed to the spring and fall as is the current practice. Conducting surveys

in the summer and fall will allow for better population estimates after adjusting survey results via

the equation presented in this paper.









Seasonal Activities

Based on regression coefficients (8-values) of the Einal averaged model, it becomes

apparent that alligators in this study showed a higher probability of emergence in spring

compared to autumn (8 spring = 0.419 > 8 utumn = -0.744) (Table 3-2). Alligator surveys in south

Florida should take into account the trend that alligators seem to spend less time emerged in

autumn compared to spring, at least in interior marsh habitats. Alligator managers may find that

more alligators are counted during spring surveys than fall surveys as a result of natural alligator

behavior. It is recommended that alligator managers calibrate the results of their seasonal surveys

to account for the naturally occurring difference in emergence rates across seasons. The

generated equation accounts strongly for this seasonal trend in emergence rates and can be used

for such a calibration. Managers should use caution however before applying such a calibration

to canal surveys, as canal alligator dynamics may not mirror those in interior marshes.

Time of Night

Based on the regression coefficients (8-values) generated in this study, it was apparent that

conducting surveys within the first hour of night, as is the case in current survey protocols, will

coincide with a slightly negative alligator emergence rates (Table 3-2). Interestingly, emergence

rates decrease to a maximum low during the second full hour of darkness (Table 3-2). In order to

maximize alligator counts, surveys would have to begin around or after midnight and continue

into the early morning hours when emergence rates begin to rise. As this option may be more

difficult for researchers, it is recommended that alligator surveys in south Florida continue to

occur immediately following sunset, but it is advisable to limit surveys to one per night if

possible to avoid a time-related bias in the results. Alternatively, for surveys expected to run for

approximately one hour then it is recommended they take place in the early hours of night, as per

current protocol. For surveys that might run in excess of two or three hours it is recommended









that they begin later in the night, perhaps beginning at the third hour of darkness, in an attempt to

decrease a time-related bias in results.

Caution must be exercised before applying these results outside of adult size classes.

Alligator body temperatures are probably higher in the early hours of night, or those hours

immediately following daylight hours when alligator body temperatures are highest. Alligators

likely lose heat consistently throughout the night, as this trend has been described in other

crocodilians (Wright 1987; Seebacher et al. 2005). Larger crocodilians lose heat at a slower rate

compared to smaller crocodilians and have comparatively more stable body temperatures than

smaller individuals (Wright 1987). Often, as surveys or other alligator research activities

progress into the night, larger individuals appear to dominate the alligator sightings (Dr. K.G.

Rice, pers. comm.). My results support this observation, as the adult alligators used for this study

showed increased emergence later on in the night. This may not be the case for smaller

individuals, who may be more likely emerged in the early hours of night before their body

temperatures start to drop. The possibility exists that conducting surveys at different times of

night may introduce biases in both absolute numbers and in size classes observed.

Moon Phases

A wide range of results are reported for crocodilian reactions to moonlight. Woodward and

Marion (1979) found a positive correlation between alligator counts and levels of moonlight

during warm weather. Larriera and Del Barco (1992) found no correlation between moon phase

and night counts in Caiman latirostris. Sarkis-Goncalves et al. (2004) report that moonlight

negatively influenced night counts in their study involving Caiman latirostris. Alligator

emergence rates in this study began to increase with increasing lunar light, but decreased during

full moons. These results somewhat agreed with results reported by Woodward and Marion










(1979). Moonlight may stimulate alligators to increase their activity (Woodward and Marion

1979), but very high levels of light may influence a decrease in activity.

Alligator managers in south Florida should take this positive relationship into

consideration when conducting surveys. Surveys conducted during moonlit nights may maximize

alligator detectability in south Florida. However, managers should exercise caution before

applying these results, as data taken from this study occurred in the absence of researcher

presence. Increased moon light may create a situation in which the observers themselves are

more readily detected by the crocodilians, which in turn react by diving or hiding (Sarkis-

Goncalves et al. 2004). Even though relatively more animals may be surfaced at any given point

in time under increasing lunar light, observer presence itself may compromise this response.

Eyeshine may also be more readily detected in darker conditions, resulting in greater counts in

spite of decreased emergence probabilities (Sarkis-Goncalves et al. 2004). It is strongly

recommended that the relationship between detectability and darkness should be tested further.

However, it may be possible that Caiman latirostris and Alligator mississippiensis simply exhibit

different behavioral responses under the influence of lunar light.

Water Depths

During nighttime hours, higher water depths decreased the emergence rates of alligators.

Since the highest water depths generally coincide with the hottest parts of the year, this may be

related to the thermal regime of south Florida alligators as previously discussed. Alligator

managers may increase night counts in south Florida during times of relatively low water. This

generally occurs in the spring, where alligators are more likely to be emerged as previously

discussed. Based on the results of this study, conducting fall surveys during years of unusually

low water might result in higher alligator counts.









It becomes difficult to tease out the effects of varying water depths independent of season.

Even by correcting for water depth, other seasonally dependent variables such as photoperiod

and prey availability are not accounted for. In order to truly understand the relationships between

these two variables, this study would need to be repeated in years where water depths are

exceedingly high or exceedingly low in spite of season, and results then need to be compared.

As a general trend in current alligator surveys, more individuals are recorded in canal

habitats rather than marsh habitats. Canal habitats have a relatively higher occupancy in south

Florida, especially by larger adult alligators (Mazzotti and Brandt 1994; Rice et al. 2005). This

difference in density may be less than it seems, as our data suggest that alligators may spend

more time submerged as water depth increases. In addition, detectability may increase in the

relatively open habitat that is characteristic of canals. This point illustrates importance of

determining the relationship between different aspects of detectability (behavioral vs. observer

biases). Alligators may also select for different habitats (open vs. vegetated) as water depths rise.

If this were the case, alligator detectability to observers is determined by more than emergence

behavior. For this reason it is strongly recommended that the results from this study be

interpreted in conjunction with information regarding habitat selection before being fully applied

to alligator surveys.

Water and Air Temperatures

During nocturnal hours, alligators in this study were less likely to be emerged with higher

water temperatures. Conversely, Woodward and Marion (1979) reported that in their north-

central Florida study, alligator night counts were positively correlated with water temperatures

during cooler weather. During relatively warmer weather, counts were unaffected by water

temperature. Based on these results, alligators seem to show a greater response to high water

temperatures in relatively cooler ambient air temperatures in terms of activity. Woodward and









Marion (1979) and Murphy (1977) report that when looking at a plot of night counts versus

water temperature, a scattering of responses occurred as water temperature exceed 280C. In this

study, a similar scattering of points occurred throughout the study at all water temperatures (Fig

3-2). The apparent scattering of plots is reflective of the fact that water temperatures had only a

slight negative effect on submergence.

Alligators in this study were more likely to be emerged with higher air temperatures.

However, Woodward and Marion (1979) reported that air temperature had no bearing on

alligator night counts, since water generally acted as a buffer between the air and the alligator.

Woodward and Marion (1979) did however suggest a positive correlation between number of

alligators detected and maximum daily temperature. Hutton et al. (1989) reported similar results

for Crocodylus niloticus, and Pacheco (1996) reported similar results for M~elonosuchus niger.

Sarkis-Goncalves et al. (2004) also reported that ambient temperature did not influence night

counts in their study involving Caiman latirostris. I would hypothesize that in the south Florida

summer, when nocturnal air temperatures are at their highest, alligators are thermally stressed

during the day and will emerge at higher rates at night to release excess heat in the relatively

cooler air (Mazzotti 1989). In regards to alligator surveys, alligator managers in south Florida

might opt to conduct surveys during particularly warm nights, and would probably do best to

survey on nights where both air temperatures and water temperatures are particularly high based

on the results of this study.

It should be noted that although alligators are endothermic, thermoregulation is not always

the driving force that determines alligator behavior (Mazzotti 1989; Asa et al. 1998). Since all

crocodilians have the ability to decrease peripheral blood circulation and heat flow through

bradycardia and vasoconstriction to conserve heat, alligator thermoselection may take a backseat









to other natural behavior including underwater foraging/feeding and social interactions (Mazzotti

1989; Asa et al. 1998). Larger, more dominant individuals may even force smaller individuals to

engage in suboptimal behavior (Asa et al. 1998) in much the same way they force less dominant

individuals to inhabit a less desirable physical habitat (Mazzotti and Brandt 1994). Such social

dynamics have been reported in captive alligators, in which a dominant female alligator forced

smaller females out of the relatively warmer water (>20o C) onto land where air temperatures

were much cooler (3-7.9oC) and certainly sub-optimal (Asa et al. 1998).

Rain

Woodward and Marion (1979) reported no relationship between night counts and

precipitation, although sufficient data were lacking. Sarkis-Goncalves et al. (2004) report that

rain did not influence nights counts in their study involving Caiman latirostris. All else being

equal, the presence of rainfall in this study resulted in a steep decline in the proportion of

alligators and a close negative relationship is apparent between rain and emergence rates in this

study (Fig. 3-3). Alligator managers might consider not conducting surveys during rain at any

intensity. Even during just 1 cm/hr of rain the maximum proportion of alligators emerged based

on the results of this study was 60% (Fig. 3-3). After a rain intensity of 3cm/hr or more, a very

small proportion of alligators are likely to be emerged and available for counting.

Rain might have been of little importance in describing emergence behavior of alligators in

this study. Apart from rain, the influence of cloud cover needs to be addressed and how may

interact with lunar phases. Rainfall means cloud cover, but cloud cover may occur without rain

and this was not accounted for in the study. Pacheco et al. (1996) report that cloud cover had a

consistent negative effect on M~elan2osuchus niger night counts. Alternatively, Woodward and

Marion (1979) report that cloud cover had a significant positive relationship on night counts in










cool weather. Whether or not this relationship would hold in the relatively warm south Florida

climate is unknown.

Wind

That wind affects alligator emergence probabilities is not unusual. Crocodilians seek

protection from wind mainly by submerging, or by using lee shores (Mazzotti 1989; Pacheco

1996). In agreement with the results from this study, wind speed had a strong negative

correlation on M~elan2osuchus niger night counts (Pacheco 1996). Alternatively, Sarkis-

Goncalves et al. (2004) report that wind did not influence nights counts in their study involving

Caiman latirostris.

When wind speeds approach 10 km/hr, the proportion of alligators emerged begins to

steadily decline (Figure 3-4). Alligator surveys in south Florida are recommended to be

postponed in the presence of excessive wind speeds due to researcher safety and a decreased

likelihood of alligator emergence.

Implications and Future Work

I advocate that this study warrants repetition and urge other alligator biologists to

consider implementing a similar proj ect. A repeated study of similar design is suggested for

locations in north Florida and/or another northern part of the alligators range for comparison.

This would also enable researchers to document whether any behavioral shifts occur across

alligator populations as a function of latitude. A repeated study would also offer a comparison

between alligators of varying body condition. A repeated study in various compartments in the

Everglades is strongly suggested to address the influence of water depths on behavior

independent of season.

Wariness is known to occur in crocodilians exposed to hunting, repeated capture, or

repeated human presence (Spratt 1997; Pacheco 1996). In future studies researcher presence









could be independently tested as a predictor variable for emergence to determine levels of

wariness in different alligator populations. Moreover, an investigation of sex-specific response to

researcher presence may yield interesting results.

Also, it should be noted again that this study dealt only with adult alligators. Alligator

surveys do not discriminate between size classes as I did when selecting alligators for transmitter

attachment. It is very important to stress that the responses of adult alligators to various

environmental factors may not mirror the responses of juvenile or hatchling alligators, so care

must be taken when applying the results of this study to adjusting surveys results. It is

recommended that alligator surveys adjust their results only among the adult animals counted.

Other studies are currently underway that are looking into detectability of alligators in

varying degrees of vegetation cover and habitat types characterized by different levels of

visibility (Cameron Carter, pers. comm.). It is strongly recommended that the results from this

study are used in conjunction with habitat visibility estimates. The Global Positioning System

(GPS) represents a technology that will prove extremely useful for wildlife studies involving

animal behavior and is rapidly evolving in regards to form and function (Fedak et al. 2002). GPS

transmitters are currently being developed and tested that will eventually allow researchers to

uncover the fine scale habitat preference of adults and sub-adult and juvenile alligators, as these

different age-classes tend to partition available habitat perhaps at a fine scale (Mazzotti and

Brandt 1994). In the future, models of detection that incorporate emergence, habitat visibility,

and habitat preference of alligators will allow managers to incorporate actual population levels

and not indices into their monitoring programs.












Table 3-1. The a AICC and Akaike weights of models used to describe the emergence dynamics
of Arthur R. Marshall Loxahatchee National Wildlife Refuge alligators.


Akaike
Weight
0.4113
0.2556
0.2189
0.0606
0.0513
0.001
0.0004
0.0003
0.0001
0.0001
0


Model
1
2
3
4
5
6
7
8
9
10
11


Model Variables
depth, wind
depth, temp(a), wind
depth, temp(w), temp(a), wind
depth, temp(a), wind, rain
depth, temp(w), temp(a), wind, rain
temp(w), temp(a), wind
temp(a), wind


A AICC
0
0.951
1.261
3.83
4.162
11.898
13.608
14.406
16.159
16.592
33.173


Hour, season,
Hour, season,
Hour, season,
Hour, season,
Hour, season,
Hour, season,
Hour, season,
Hour, season,
Hour, season,
Hour, season,
Hour, season,


moon,
moon,
moon,
moon,
moon,
depth,
depth,
depth,
depth,
depth,
depth,


temp(w), temp(a), wind, rain
temp(a), wind, rain
wind
temp(w), temp(a), rain


12 Hour, moon, depth, temp(a), wind 74.469 0
13 Hour, moon, depth, temp(w), temp(a), wind 75.372 0
14 Hour, moon, depth, temp(a), wind, rain 77.152 0
15 Hour, moon, depth, temp(w), temp(a), wind, rain 78.092 0
16 Hour, moon, depth, wind 81.568 0
17 Hour, season, moon, wind 152.503 0
18 Hour, season, temp(w), temp(a), wind 152.75 0
19 Hour, season, moon, temp(w), temp(a), wind 153.377 0
20 Season, moon, depth, wind 155.59 0
21 Hour, season, moon, temp(w), temp(a), wind, rain 156.267 0
22 Hour, season, moon, temp(w), temp(a), wind, rain 172.652 0
23 Hour, depth 182.238 0
24 Hour, season 280.878 0
25 Hour, temp(w) 462.729 0
26 Hour, temp(a) 568.765 0
27 Hour, wind 578.891 0
28 Hour, moon 599.274 0
29 Hour 703.031 0
* a AIC values of< 2 generally suggest substantial evidence for the model. Values
between 3 and 7 indicate that the model has considerably less support, and values > 10
indicates that the model is highly unlikely. Akaike weights indicate the probability that
the model is the best among the whole set of candidate models.











Table 3-2. Regression coefficients (p-values) and associated confidence intervals of the averaged
model used to describe the emergence dynamics of Arthur R. Marshall Loxahatchee
National Wildlife Refuge alligators.
Parameter P-VALUE Lower 95% Cl Upper 95% Cl
Intercept 3.28 -6.605 13.965
Hrl -0.007 -0.276 0.261
H r2 -0.1 87 -0.353 -0.020
Hr3 -0.067 -0.229 0.094
Hr4 0.000 -0.000 0.000
Hr5 0.105 -0.059 0.271
Hr6 0.010 -0.161 0.181
Hr7 0.095 -0.076 0.268
Hr8 -0.037 -0.215 0.140
Hr9 0.025 -0.293 0.344
Autumn -0.744 -0.917 -0.571
Spring 0.419 -0.068 0.907
Summer 0.000 0.000 0.000
Moon (quarter) -0.1 90 -0.348 0.032
Moon (half) 0.060 -0.066 0.188
Moon (full) 0.000 0.000 0.000
Water depth -0.258 -0.882 0.365
Temp (water) -0.012 -0.052 0.028
Temp (air) 0.016 -0.021 0.053
Rain -0.003 -0.026 0.020
Wind -0.026 -0.039 -0.013
*Intercept' describes the slope of the regression. 'Hrl-Hr9' describes the time of night after sunset.
Parameters with p-values of 0 serve as baseline measurements from which comparative values are drawn.










Table 3-3. Summary of the differences between equation-predicted proportion (P) and actual
observed proportion (0) of alligators emerged at Arthur R. Marshall Loxahatchee
National Wildlife Refuge in 2005-2006.
overall spring summer autumn
Mean difference
between P and O 0.1987 0.3279 0.1423 0.1638
Standard Deviation of
Observed (SDO) 0.2293 0.2529 0.1765 0.1753
Maximum overprediction P= 0.8221>O P= 0.8221>O P= 0.3688>O P= 0.4655>O
Maximum
underprediction P= 0.3563 Minimum difference
between P and O 0.0007 0.0007 0.0007 0.0037
% of observations
overpredicted 59.50% 77.36% 50.00% 56.72%
% of observations
underpred icted 40.50% 22.64% 50.00% 43.28%
% predicted within 1
SDO 71.00% 49.05% 61.25% 52.23%
% greater than 1 SDO
(overpredicted) 20.00% 49.05% 18.75% 26.88%
% greater than 1 SDO
(underpredicted) 9.00% 1.90% 20.00% 20.89%











Table 3-4. Results of a paired two-sample t-test for spring predicted vs. observed proportion of
alligators emerged at Arthur R. Marshall Loxahatchee National Wildlife Refuge in
2005-2006.


Observed
0.480304392
0.063973351
53
-0.222545329

52
-6.422931976
2.056E-08
1.674689154
4.112E-08
2.006646761


Predicted
0.748249448
0.014640959
53


Mean
Variance
Observations
Pearson Correlation
Hypothesized Mean Difference
df
t Stat
P(T<=t) one-tail
t Critical one-tail
P(T<=t) two-tail
t Critical two-tail











Table 3-5. Results of a paired two-sample t-test for summer predicted vs. observed proportion of
alligators emerged at Arthur R. Marshall Loxahatchee National Wildlife Refuge in
2005-2006.


Observed
0.348902486
0.031179662
80
0.251546696

79
-0.164638953
0.434824353
1.66437141
0.869648706
1.990450177


Predicted
0.352117461
0.0064734
80


Mean
Variance
Observations
Pearson Correlation
Hypothesized Mean Difference
df
t Stat
P(T<=t) one-tail
t Critical one-tail
P(T<=t) two-tail
t Critical two-tail











Table 3-6. Results of a paired two-sample t-test for autumn predicted vs. observed proportion of
alligators emerged at Arthur R. Marshall Loxahatchee National Wildlife Refuge in
2005-2006.


Observed
0.184263208
0.030733643
67
-0.092450092

66
-0.591925269
0.277961473
1.668270515
0.555922946
1.996564396


Predicted
0.198132228
0.003998431
67


Mean
Variance
Observations
Pearson Correlation
Hypothesized Mean Difference
df
t Stat
P(T<=t) one-tail
t Critical one-tail
P(T<=t) two-tail
t Critical two-tail

















Predicted
Observed








1 100 199
Observation number


Figure 3-1. Relationships between observed and predicted proportions of alligators emerged at
Arthur R. Marshall Loxahatchee National Wildlife Refuge, 2005-2006. Jagged lines
indicate actual values. Smoothed lines indicate polynomial trend lines. Observation
numbers 1-53 represent springtime observations. Numbers 54-134 represent
summertime observations, and numbers 135-200 represent autumn observations.





























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Water temperature







Figure 3-2. Relationships between water temperature (oC) and proportion of alligators emerged


at Arthur R. Marshall Loxahatchee National Wildlife Refuge, 2005-2006. The


scattering of responses and lack of apparent relationship between emergence and


water temperature agree with findings reported by Woodward and Marion (1979) and


Murphy (1977).




































































82




































0 2 2 3 4 5 6 7
Rain


Figure 3-3. Relationships between rainfall (cm/hr) and proportion of alligators emerged at Arthur
R. Marshall Loxahatchee National Wildlife Refuge, 2005-2006.





















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4 84









CHAPTER 4
CONCLUSIONS

South Florida is characterized by consistent high temperatures and can be a climatically

challenging environment for American alligators (Jacobsen and Kushlan 1989; Dalrymple 1996;

Barr 1997; Howarter 1999). In addition to natural stressors, much of the original Everglades

ecosystem has been spatially reduced, drained, and irreversibly lost as a result of extensive

landscape alterations for agriculture, development, and flood control (Jacobsen and Kushlan

1984; Simmons and Ogden 1998). Once natural hydrological fluctuations are now

anthropogenically influenced or controlled. Alligators are especially sensitive to fluctuating

water levels both spatially and temporally (Mazzotti 1989; Kushlan and Jacobsen 1990; Mazzotti

and Brandt 1994). In the Everglades ecosystem, a balanced alligator population is dependent on

appropriate seasonal water availability, especially in an environment such as the Everglades.

Alligators are a top conservation concern in the Everglades ecosystem as they can serve as

indicators of ecological balance and measure of restoration success (Rice et al. 2005). The

alligator' s natural sensitivity to fluctuating water levels, as well as their sensitivity to overall

system production as top predators makes them ideal candidates for adaptive management

(Mazzotti and Brandt 1994; Rice et al. 2005). Since the success of many other species is

dependent on a balanced alligator population, alligators throughout south Florida are monitored

closely as Everglades restoration advances.

I first set out to investigate patterns of thermoregulation by correlating alligator emergence

behavior and circadian rhythms to season, solar radiation, and water depths in the south Florida

environment. I hypothesized that since the south Florida climate undergoes an annual transition

between a low cost and high cost environment, then alligators will exhibit behavior patterns that

reflect active heat-seeking thermoregulation in the spring, and to conversely exhibit behavior that









reflects no active thermoregulation or heat-avoidance in the summer and fall. I also examined the

effects of size, sex, and body condition on alligator emergence rates.

All models indicated a higher probability of emergence in the spring compared to that of

the fall. Springtime solar radiation had a positive affect on emergence probabilities. This trend

suggested that alligators exhibit behavior patterns that reflect a low cost environment in the

spring in south Florida as they seem to show active heat-seeking thermoregulation at this time.

Alligators in south Florida may have no problems in achieving optimal temperatures in the

spring through increased behavioral thermoregulation, as they seem to seek solar radiation and

are highly active through the night. The results of this study supported my hypothesis that

alligator thermoregulatory behavior reflects an environmental transition. However, other natural

behaviors besides thermoregulation could also help explain these results. The difference in

emergence rates may also be influenced by social behavior, foraging behavior, or photoperiod.

Larger alligators showed a higher degree of heat avoidance in the summer and spent less

time emerged than smaller individuals in this study. Although the sample size was relatively

small and all alligators were adults, the smaller individuals in the study were more likely

emerged at any given point in time compared to the larger individuals in the study during the

months of June and July, reflecting the fact that smaller individuals are better able to disperse

excess heat (Wright 1987). Body condition also had an effect on emergence rates as higher body

condition scores, presumably healthier individuals, showed increased rates of emergence. This

result suggests a higher heat tolerance of relatively robust alligators.

It has been suggested that alligators in south Florida require a sufficient level of standing

water to escape the intense heat during the summer and fall (Howarter 1999; Percival et al. 2000;

Abercrombie 2002). If water depths are too low during these hot months, one could argue that









there may be an added benefit of greater food concentration. This may not be the case, as aquatic

prey species densities are generally low following prolonged dry downs (Loftus and Eklund

1994; DeAngelis et al. 1997). The Everglades ecosystem is primarily a rain-fed wetland and

hydroperiod is naturally determined by patterns of precipitation. Springtime in the Everglades is

generally characterized by drought, and if the drought extends through summer and fall then fish

densities are known to decline and may require years to recover (Loftus and Eklund 1994;

DeAngelis et al. 1997). In other words, aquatic prey species may not be able to adjust to

prolonged unnatural seasonal conditions. Even if prey was sufficiently available during a

summer drought, alligators may still be confined to inactivity and heat avoidance in south

Florida and would therefore be unable to take advantage.

Relatively lower water depths in the spring are recommended as alligators can take

advantage of the increased benefits of concentrated aquatic food resources during natural dry

downs and build energy reserves for the summer. Ambient temperatures are also less intense at

this time and would probably allow less thermal constraints. Lower water depths also provide

adequate nesting sites for females (Mazzotti 1989; Kushlan and Jacobsen 1990; Mazzotti and

Brandt 1994).

Understanding alligator responses to differences in seasonal conditions allows managers to

better understand potential responses to alternate restoration actions in the Everglades.

Anthropogenically controlled water regimes in the Everglades must take into account the

ecology of the ecosystem's top predator. Not only are variations in water depth known to affect

courtship, nesting, growth and survival (Garrick and Lang 1975; Vliet 1987; Kushlan and

Jacobsen 1990; Mazzotti and Brandt 1994), but they may also have negative impacts on other

behavioral adaptations of American alligators reflected by shifts in thermoregulatory behavior.









Understanding the thermal ecology of the American alligator in south Florida will allow

managers to make more informed decisions regarding habitat restoration. This information can

also be practically applied to improve efficacy of south Florida alligator surveys.

The second obj ective of this research was to improve alligator survey methods within the

south Florida alligator survey network. Specifically, I investigated alligator emergence behavior

and how it relates to a variety of environmental variables known to have an effect on crocodilian

behavior. These include season, air and water temperature, moon phase, rain, and wind

(Woodward 1979; Mazzotti 1989; Pacheco 1996; Woodward et al. 1996; Sarkis-Goncalves et al.

2004). The ultimate goal was to develop estimates of alligator detectability that alligator

managers can use to correct their survey results in an appropriate manner to account for missed

individuals (Steinhorst and Samuel 1989).

In this study, alligators spent roughly two thirds of their time submerged. Compared to

spring and fall, alligators were less likely emerged at any given time during summer. Compared

to summer months, alligators in the autumn are only slightly more often emerged during

nighttime hours. Alligators are less likely emerged in low moonlight compared to half moon or

full moon cycles. In addition, alligators are slightly more likely emerged during half moons

compared to full moons. During nighttime hours, higher water depths decreased the emergence

rates of alligators. Higher water temperatures result in decreased emergence rates, while higher

air temperature results in increased emergence rates. I found that the best time for conducting

surveys is in low wind, in half or full moon phases, and on clear, cloud-free nights with relatively

high air and water temperatures and relatively lower water depths. Regardless of conditions, an

equation was generated that allows managers to adjust their survey results to account for

variations in detectability due to natural behavior. Although the equation successfully predicted










alligator emergence rates in the summer and fall, it lost much of its predictive ability in the

spring. I suggest that some other variable or variables that were not measured in this study were

effectively overriding the expected influence of the surrounding environment. The fact that the

breeding season of alligators occurs in spring may account for this unexpected behavior, since

most social interactions of alligators occur underwater (Vliet 1987). Social interactions of

alligators are known to take precedence over behaviors that may represent an optimal response to

environmental conditions (Asa et. al. 1998).

This research can be used by alligator managers to reduce the amount of time needed to

detect significant changes in alligator populations as they respond to different restoration actions,

thus allowing managers to quickly recognize and respond to a resulting positive or negative

population trend. I argue that this study warrants repetition and urge other alligator biologists to

consider implementing a similar proj ect in other habitats and locations. A repeated study of

similar design is suggested for locations in north Florida and/or other more northern regions of

the alligators range for comparison. This would also enable managers to document whether any

behavioral shifts occur across alligator populations as a function of latitude. A repeated study

would also offer a comparison between alligators of varying body condition and relative health.

A repeated study in various compartments in the Everglades is suggested to address the influence

of water depths independent of season. Researcher-induced wariness should also be examined, as

is a study on age/size related fine scale habitat preference. I strongly recommend that the results

from this study are used in conjunction with habitat visibility estimates. Combining emergence

data with habitat detectability variables and habitat preference of alligators will allow mangers to

more quickly detect population changes in response to Everglades restoration. Eventually, as this










type of research advances, alligator managers will be able to incorporate actual population levels

and not indices into their monitoring programs.









APPENDIX A
METHODOLOGY

During night-light surveys, the probability of alligator detection by researchers is a

function of observer efficacy, habitat, alligator wariness due to airboat/human presence, and

natural variation in behavior (Graham and Bell 1969; Murphy 1977; Brandt 1989; Woodward

and Linda 1993). This study focused on the latter and was carried out to develop estimates of

emergence probabilities of alligators during surveys as they relate to various weather-related

environmental factors (the probability that an animal is above the water surface and thus

available for detection). Radio telemetry was chosen as a means to investigate alligator

emergence behavior. This paper presents the method of transmitter attachment used for this

study .

Telemetry has been a common approach to studying crocodilian behavior (Joanen and

McNease 1970; Joanen and McNease 1972; McNease and Joanen 1974; Taylor et al. 1976; Kroll

1977; Murphy 1977; Goodwin 1978; Deitz 1979; Goodwin and Marion 1979; Muller 1979;

Rodda 1984; Magnusson and Lima 1991; Barnett et al. 1997; Addison et al. 1998; Fergusson

1998; Cadi et al. 2002; Morea et al. 2000; Munoz and Thorbjarnarson 2000). Telemetry

equipment for this study included custom VHF transmitters (6.0 cm in length, 3.5 cm in width,

2.5 cm in height, 65 grams in weight) equipped with water conductivity sensors. These sensors

effectively switched the signal output from thirty pulses per minute while emerged to sixty

pulses per minute while submerged. Battery life for all transmitters was approximately four

months. A fixed antenna and solar powered radio receiver were installed at the study site (UTM

17R 0573247, 2926401) and were used to detect and record the status of all deployed

transmitters. The receiver was programmed to cycle continuously through all deployed

transmitters so that each frequency was searched for once per hour. In addition to the









antenna/receiver, a weather station system was installed at the study site. For the purposes of this

study, weather data were correlated with emergence data to determine potential relationships

between alligator emergence and environmental variables.

In this study, transmitters were attached using the parietal/squamosal ridges as the

attachment point. To investigate emergence behavior, all instances when an alligator's head is

surfaced must be recorded. Since a surfaced alligator may only expose its eyes and nostrils, the

logical place to attach transmitters while properly utilizing the conductivity sensors was on top of

the parietal. An extensive search of pertinent publications revealed that standard methods of

transmitter attachment to crocodilians as described in several previous studies were essentially

insufficient for the purposes of this proj ect. Most studies involved surgical implantation of

transmitters (Asa et al. 1998; Barnett et al. 1997; Brisban and Standora 1982; Hocutt et al. 1992;

Morea et al. 2000), attachment of transmitters to the tail (Munoz and Thorbj arnarson 2000),

attachment of transmitters with neck collars (Addison et al. 1998; Fergusson 1998; Joanen and

McNease 1970, 1972; Rootes and Chabreck 1993) and attachment of transmitters to nuchal

scutes (Kay 2004; McNease and Joanen 1974; Taylor et al. 1976). Tethering a buoyant

transmitter (Rodda 1984) was also deemed insufficient, as the aquatic habitat at the study site

was highly vegetated and would leave the transmitter prone to be hung up underwater, resulting

in an inaccurate representation of alligator emergence.

Twenty eight alligators were captured using snare poles and spotlights as described by

Chabreck (1963). All alligators were >2 m in total length in order to accommodate the

procedure. Measurements were taken from all animals captured including total length, head

length, snout-vent length, tail girth, sex, and weight. Prior to surgery, captured alligators were

physically restrained using rope and/or duct tape to bind the legs and secure the animal to a









wooden board. Duct tape was placed over the eyes to inhibit vision and reduce stress. All

surgical procedures were performed in the field, aboard an airboat, to minimize time and stress

on the animals. Methods were consistent with those described and approved by University of

Florida IACUC proposal #D943.

Surgical items included one six-ounce j ar of Lidocaine Hydrochloride (local anesthesia),

3 ml injection needles, one battery-operated Dremel@ 10.8V Lithium-ion cordless drill

(www.dremel.com) with two fully charged drill battery packs, several spools of 16-gauge

surgical grade steel wire, pliers, a cigarette lighter, saline solution, cotton balls, rubber gloves,

Betadine scrub and Betadine solution (disinfectant), and several 15-ounce containers of

Devcon@ 5-minute epoxy (www.devcon.com). Drill bits, steel wire, and the transmitters

themselves were sterilized with 95% rubbing alcohol prior to alligator capture. Drill bits and

steel wire were also sterilized with fire from the lighter. Drill bits were re-sterilized after use on

each animal in the study. After sterilization, all of these items were placed in individual plastic

bags and stored in a water-tight container on the airboat.

After initial capture alligators were loaded onto the bow of the airboat where they were

secured. Once secured, the cranium was thoroughly cleaned using 95% rubbing alcohol followed

by Betadine disinfectant scrub and Betadine disinfectant solution. After cleaning, 2-3 ml of 2%

Lidocaine Hydrachloride was administered via several injections around the perimeter of the

surgical site. After approximately five minutes, four small holes were drilled into the

parietal/squamosal ridges using a 3.175 mm drill bit; two holes either side. Saline solution was

applied liberally to the bit and tissue during drilling to prevent the drill bit from overheating

which results in tissue damage. Once the holes were established, Lidocaine was again

administered inside the new holes, and was dually used to flush out loose material left over from









drilling. The new holes were disinfected with Betadine solution to ensure that infection will not

set it as a delayed response to transmitter attachment. Four separate lengths of steel wire were

woven through the drilled holes and twisted with pliers to secure their placement (Fig. A-1). At

this point, holes were filled with common household superglue to eliminate any free space

between the wire and the bone. Devcon@ brand 5-minute epoxy (www.Devcon.com) was then

applied to both the parietal skin, where the transmitter will rest, and to the underside of the

transmitter itself. The transmitter was then put in place and held tightly for five minutes while

the epoxy hardened. Two lengths of steel wire, previously epoxied to the transmitter, were then

twisted around the other four lengths of wire to secure the transmitter in place (Fig. A-2). After

the first layer of epoxy set, a second layer was applied dorsally to enclose the transmitter and

wires and reinforce the attachment. Care was taken not to enclose the conductivity sensors

during this final step. After a full cure time of approximately twenty minutes the attachment

procedure was complete and the alligator was released at its original point of capture. Since

Lidocaine is a local anesthetic, the alligators may be released before the effects wear off

completely. The entire time from capture to release was typically less than ninety minutes.

Devcon@ brand 5-minute epoxy was chosen as the best overall brand of epoxy for this

research as determined by a series of performance tests of several name-brand glues and epoxies

(Table A-1). In this experiment, model transmitters equipped with eyehooks were glued to the

parietals of deceased farm-raised alligators. Adhesives were allowed to cure for a full 120

minutes, or the maximum desirable amount of time to spend on each individual alligator in the

field for the attachment procedure. Both the model transmitters and the parietal region were

thoroughly cleaned using 91% rubbing alcohol prior to testing. A 20 kg spring scale was attached

to the eyehook on one end and a standard workbench vice on the other. As the vice was cranked









the scale was used to measure the exact amount of pressure needed to detach the model

transmitter from the parietal. The results of experiment indicated that liquid glues and epoxies

tended to perform better than malleable clay epoxies in ability to bond to skin tissue. Devcon

was selected for both its quick cure time and strength of hold. Devcon has been used to attach

transmitters in other studies as well (Boarman et al. 1998; Stokes and Boersma 1999; Reidel et

al. 2003).

Transmitters remained attached for a period of three-four months and were recovered

where they were shed. Some alligators retained their transmitters and needed to be recaptured

(Table A-2). Transmitters are shed as the bone slowly recedes away from the wire over time, and

the wire effectively works its way through the bone until the transmitter is detached, usually

within four months. This natural detachment will leave four grooves in the parietal/squamosal

ridges, but in no cases did I observe any signs of infection associated with these grooves. A

captive specimen on which this procedure was performed was left with only slight scarring as a

long-term effect of transmitter detachment. The effect of capture and transmitter attachment on

behavior was thought to be minimal based on observations of one of the study animals. On one

occasion, a large male was originally observed bellowing with head and tail elevated out of the

water in a social display. This individual was captured and fitted with a transmitter, and was the

first individual of three captured that particular night. After an elapsed time of approximately

four hours, this alligator was observed again in the exact place of capture, seemingly unaffected

by the procedure as it had resumed bellowing with head and tail elevated out of the water. Post

removal inspections of all recaptured animals revealed no signs of infection or necrosis as a

result of transmitter attachment. Several of the study animals were excessively thin and may









have been immuno-compromised; still none of the study animals showed any ill effects as a

result of this procedure (Fig. A-3).

The above described methodology was developed to suit specific obj ectives and is only

recommended for similar studies on crocodilian emergence rates. The maj ority of crocodilian

telemetric studies utilize standard VHF or GPS transmitters to answer questions regarding

movement, home ranges, and habitat use. For these studies, a slight modification of the above

described procedures can be used for longer-term attachment of radio transmitters using the

enlarged dorsal nuchal scutes as the attachment point. In this adaptation, four holes are drilled

through the nuchal scutes instead of the cranial ridges. Newer transmitter models come equipped

with two small hollow channels that run through the base of the transmitter and are used to run

wire through during attachment. This design works particularly well for nuchal scute attachment.

Weaving wire directly through bone material is generally not the most efficient technique

for long-term attachment of transmitters. Using wire alone will decrease attachment time and the

transmitter will be more likely to detach through sheer force, for example in a territorial dispute

or during a flight response. Therefore, it is recommended for nuchal scute attachment that

flexible plastic tubing (with an inside diameter approximately equal to the diameter of the wire)

be woven through the drilled holes first, followed by wire woven through the plastic tubing. This

provides added strength and longevity of attachment. Plastic tubing could certainly be used for

cranial ridge attachment to increase attachment longevity, although most alligators in this study

lacked sufficiently thick enough bone to accommodate plastic tubing as well. This may not be

the case in species with more pronounced cranial ridges, such as Crocodylus porosus or C.

niloticus. In this study, foregoing the use of plastic tubing also made transmitter recovery much

more efficient. In addition to using plastic tubing, a knead-able marine epoxy is used during the










final epoxy application to encase the transmitter, wires, and nuchal scutes. Since marine epoxies

cure underwater, handling time is reduced as animals may be released before the epoxy reaches a

full cure.










Table A-1. Results of epoxy experiment for transmitter attachment.
Cure Cure Strength
Brand Time Temp. of Hold Comments
(min.) (oC) (kg)
DevCon ~20 44.4 18 Full cure; epoxy bonded strongly to skin

SuperMend 120+ 41.1 8 Epoxy very tacky; slid off skull

AquaMend ~60 32.2 9.6 A fairly solid cure but still tacky

Loctite Aquamarine ~120 26.6 13 Solid cure, weak bondage to skin

Loctite Stick n'Seal n/a n/a n/a No cure and no test after two hours

PerfectGlue 120+ n/a 14 Slighty tacky; still took skin upon removal

GOOP Marine ~40 37.2 11 Epoxy still malleable upon testing
FixFast
TriggerBond ~20 40.5 12 No cure underneath surface

*Room temperature was 25.5-27.2 oC for all trials. Heads and transmitters were cleaned with 91% rubbing
alcohol prior to attachment. Cure times are for surfaces. In some instances the epoxy was still wet
underneath. In all trials vice cranking began after two hours time.












Table A-2. Summary of transmitter application and recovery
scute clip capture date frequency transmitter recovery date
202 12-Jul-05 166.696 lost
203 12-Jul-05 166.154 lost
204 13-Jul-05 166.138 lost
205 13-Jul-05 166.875 lost
206 13-Jul-05 166.571 lost
207 13-Jul-05 166.542 lost
208 13-Jul-05 166.934 lost
209 13-Jul-05 166.017 lost
210 13-Jul-05 166.92 lost
211 14-Jul-05 166.28 lost
302 18-Apr-06 166.705 10-Aug-06*
303 18-Apr-06 166.225 8-Aug-06*
304 18-Apr-06 166.489 8-Aug-06
305 18-Apr-06 166.082 8-Aug-06
306 19-Apr-06 166.389 lost
307 19-Apr-06 166.329 10-Aug-06*
308 19-Apr-06 166.468 10-Aug-06*
309 19-Apr-06 166.167 8-Aug-06
310 19-Apr-06 166.511 8-Aug-06
138 20-Apr-06 166.309 10-Aug-06
139 20-Apr-06 166.069 8-Aug-06
121 20-Apr-06 166.548 8-Aug-06
123 25-Apr-06 166.625 10-Aug-06
122 25-Apr-06 166.607 lost
124 26-Apr-06 166.024 8-Aug-06
311 14-Jun-06 166.284 10-Aug-06*
313 14-Jun-06 166.364 10-Aug-06*
312 14-Jun-06 166.406 8-Aug-06*
SAll 2005 transmitters were lost after Hurricane Wilma passed through (24 October 2005) and left no
transmitters to be heard. indicates that the transmitter was still attached to the study animal, otherwise
the transmitter had been shed and was found on the bottom of the water intact.































Figure A-1. Parietal/squamosal wiring. 1) A hole is drilled through parietal/squamosal ridge. 2)
The wire is woven through the new hole. 3) The wire is twisted around itself to secure
its placement. 4) The wire is securely attached to parietal/squamosal ridge.



































Figure A-2. Transmitter attachment. 1) The transmitter is placed in the middle of parietal with
wires from transmitter in line with wires previously attached. 2) Wires are twisted
around each other in a similar manner as described in step 4 of Figure A-1. 3) The
transmitter is wired to parietal. This figure also indicates the placement of the
conductivity switches.










































Figure A-3. One recaptured alligator with the transmitter firmly in place









APPENDIX B
DATA PROTOCOLS AND MANAGEMENT

Due to crossover or reflected signals, some data were recorded in error. Protocols were

developed to sort the data so that only the most accurate and reliable data were used for analysis.

For example, the logged emergence data consisted of eight different fields. These included Field,

Date, Time, Frequency, Pulses per minute, Percent signal, Transmitter ID, and Data bytes. Field

described the kind of chirp the receiver heard. This value was either 0, 1, or 2, meaning the

receiver detected a regular chirp, a chirp with incorrect digital ID, or a chirp with correct digital

ID and temperature respectively. Lines of data that included any of these values were kept,

because in any case the transmitter was above water and was being heard. Time was the time of

day (24 hr) the receiver heard the transmitter, and Frequency was the transmitter frequency that

was heard. Pulses per minute for the 2005 transmitters described whether the transmitter was in

normal running mode or mortality mode. Data with Pulses per minute values ranging from 28-32

(normal running mode) were kept, while data with Pulses per minute values 50 and greater

(mortality mode) were discarded, since the mortality mode did not allow for determination of

emergence. Pulses per minute for the 2006 transmitters described whether the transmitter was

above or below water. Percent signal described the strength of the signal that the receiver heard.

These values ranged from 0 to 99. Data with values that ranged from 2-99 were kept, while data

with values 0 and 1 were discarded. Transmitter ID described the ID of the transmitter being

heard for the 2005 transmitters. Data with both correct and incorrect transmitter ID were kept,

since either way the transmitter was heard and the alligator was surfaced. Transmitter ID

described the proportion of time during the last one hour that the alligator spent submerged for

the 2006 transmitters. Finally, the Data bytes field included digital temperature data.









If any record was missing in 2005, it was assumed that the alligator was submerged, as

our transmitters were programmed to turn off underwater. I also assumed that no alligator

ventured out of range of the receiver (approximately 3 km). Morea et al. (2000) reported that

Everglades alligators have relatively small home ranges and are more or less bound to their

ranges with infrequent emigration. All study animals were captured within 1 km of the fixed

antennae/receiver, and the farthest known distance an alligator traveled was 1.5 km from its

capture location, based on its location at the end of the study. In addition, all alligators were

picked up consistently by the receiver through the course of the study. In 2006, the transmitters

remained on at all times and only the pulses per minute changed as the transmitter was emerged.

This change was made in order to nullify even the possibility that some alligators may have left

the study area in the 2005 season. Some signals in 2006 were missed late in the season as the

transmitter signals grew weaker. For these missed records, I also assumed that the alligator was

underwater and perhaps buried in mud under a floating mat of vegetation, as is common refugia

for alligators in the study area (C. Bugbee, pers. obs.).









APPENDIX C
PERMITS

Permits were used in this proj ect for alligator capture and radio transmitter attachment.

They were obtained from the following agencies:

* Everglades National Park

* Florida Fish and Wildlife Conservation Commission

* University of Florida Animal Care and Use Committee











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BIOGRAPHY

Christopher David Bugbee graduated from Lyme-Old Lyme High School in 1997 and went

on to earn his B.S. from St. Lawrence University in Canton, New York, in 2002. He has since

worked with the Connecticut Department of Environmental Protection, the United States

Geological Survey, the Florida Cooperative Fish and Wildlife Research Unit, and the United

States Forest Service assisting with a variety of ichthyological and herpetological research

projects. Chris has a particular interest in freshwater systems and wetland conservation. He is

also an advocate of the top-down approach to wildlife conservation. For these reasons, he

became particularly interested in American alligators and their important role in the Everglades

ecosystem.





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1 EMERGENCE DYNAMICS OF AMERICAN ALLIGATORS ( Alligator mississippiensis) IN ARTHUR R. MARSHALL LOXAHATCHEE NATIONAL WILDLIFE REFUGE: LIFE HISTORY AND APPLICATION TO STATEWIDE ALLIGATOR SURVEYS By CHRISTOPHER DAVID BUGBEE A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2008

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2 2008 Christopher David Bugbee

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3 To my family: Thank you for lending your guidan ce and support through the years, and for the opportunity to chase my dream and grab it by the tail. To Aletris: Thank you for your encouragem ent, inspiration, advice, support, and patience. I love you.

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4 ACKNOWLEDGMENTS I thank Ken Rice, Frank Mazzotti, an d Franklin Percival for the opportunity to conduct this study and for their guidance along the way. I thank the researchers and tec hnicians who assisted with this project; they include, Justin Davi s, Joe Kern, Wellington Guzman, Mike Rochford, Eliza Gilbert, Aletris Neils, Mike Cherkiss, Hardin Waddle, Brian Je ffery, Mark Parry, and Cameron Carter. I thank Dr. Darry l Heard for his advice in devel oping the surgical protocol. I would also like to thank Laura Br andt for all of her contributions to the project, and Mark Miller, Ikuko Fujisaki, and Meghan Brennan for their statistical guidance.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS...............................................................................................................4 LIST OF TABLES................................................................................................................. ..........7 LIST OF FIGURES.........................................................................................................................9 ABSTRACT...................................................................................................................................10 CHAP TER 1 INTRODUCTION..................................................................................................................12 The American Alligator......................................................................................................... .12 Alligators and the Everglades................................................................................................. 13 Everglades Alligator Thermal Ecology.................................................................................. 14 Alligator Surveys....................................................................................................................17 2 AMERICAN ALLIGATOR ( Alliga tor mississippiensis ) AMPHIBIOUS BEHAVIOR AND THERMAL ECOLOGY IN RESPONSE TO ENVIRONMENTAL FLUCTUATIONS.................................................................................................................. 19 Introduction................................................................................................................... ..........19 Alligator Amphibious Behavior...................................................................................... 19 A Harsh Environment......................................................................................................21 Thermoregulation............................................................................................................ 22 Materials/Methods..................................................................................................................26 Study Area.......................................................................................................................26 Telemetry...................................................................................................................... ...26 Nest Searches...................................................................................................................27 Data Protocols/Management...........................................................................................27 Data Analysis...................................................................................................................28 Modeling....................................................................................................................... ...29 Environmental variable analysis.............................................................................. 29 Size, condition, and sex variable analysis................................................................ 30 Results.....................................................................................................................................30 Environmental Variable Analysis.................................................................................... 30 Size, Condition, and Sex Variable Analysis....................................................................31 Discussion...............................................................................................................................32 Seasonal Activities..........................................................................................................32 Solar Radiation................................................................................................................33 Circadian Rhythms..........................................................................................................36 Water Depths...................................................................................................................37 Alligator Size...................................................................................................................38 Alligator Condition.......................................................................................................... 39

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6 Alligator Sex....................................................................................................................40 Implications and Future Work......................................................................................... 41 3 EMERGENCE DYNAMICS OF AMERICAN ALLIGATORS ( Alligator mississippiensis ) IN ARTHUR R. MARSHALL LOXAHATCHEE NATIONAL WILDLIFE REFUGE AND THEIR APPLICATION TO ALLIGATOR MONITORING..................................................................................................................... ..55 Introduction................................................................................................................... ..........55 Everglades Restoration.................................................................................................... 55 Everglades Alligator Surveys.......................................................................................... 56 Alligator Detectability..................................................................................................... 56 Hypotheses......................................................................................................................57 Materials/Methods..................................................................................................................58 Study Area.......................................................................................................................58 Telemetry...................................................................................................................... ...59 Nest Searches...................................................................................................................59 Data Protocols/Management...........................................................................................60 Data Analysis...................................................................................................................60 Modeling....................................................................................................................... ...61 Results.....................................................................................................................................63 Equation Accuracy..........................................................................................................65 Discussion...............................................................................................................................66 Equation Accuracy..........................................................................................................66 Seasonal Activities..........................................................................................................67 Time of Night.................................................................................................................. 67 Moon Phases....................................................................................................................68 Water Depths...................................................................................................................69 Water and Air Temperatures........................................................................................... 70 Rain..................................................................................................................................72 Wind................................................................................................................................73 Implications and Future Work......................................................................................... 73 4 CONCLUSIONS.................................................................................................................... 85 APPENDIX A METHODOLOGY................................................................................................................. 91 B DATA PROTOCOLS AND MANAGEMENT................................................................... 103 C PERMITS.............................................................................................................................105 LIST OF REFERENCES.............................................................................................................106 BIOGRAPHY..............................................................................................................................115

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7 LIST OF TABLES Table page 2-1 Environmental variables of all models us ed to describe the em ergence dynamics of alligators in Arthur R. Marshall Loxahatchee National Wildlife Refuge.......................... 45 2-2 The AICC, AICC, and Akaike weights of 20 models used to describe the em ergence dynamics of alligators in Art hur R. Marshall Loxahatchee National Wildlife Refuge................................................................................................................ ..46 2-3 Regression coefficients ( -values) and associated confidence intervals of the averaged m odel used to describe the em ergence dynamics of Arthur R. Marshall Loxahatchee National Wildli fe Refuge alligators.............................................................. 47 2-4 Regression coefficients of a model used to describe the em ergence dynamics of alligators in Arthur R. Marshall Loxahatchee National Wildlife Refuge based on size, body condition, and sex............................................................................................. 48 2-5 Average body condition scores of 1999-2005 south Florida alligators and 2005-2006 Arthur R. Marshall Loxahatchee Na tional W ildlife Refuge alligators.............................. 49 2-6 Analysis of variance for average bod y condition of 2005-2006 Arthur R. Marshall Loxahatchee National W ildlife Refuge alligators and 1999-2005 south Florida alligators.............................................................................................................................50 2-7 Analysis of variance for average body condition of spring 2006 Arthur R. Marshall Loxahatchee National W ildlife Refuge alligators and 1999-2005 south Florida alligators.............................................................................................................................51 2-8 Analysis of variance for average body condition of fall 2005 Ar thur R. Marshall Loxahatchee National W ildlife Refuge alligators and 1999-2005 south Florida alligators.............................................................................................................................52 2-9 Comparison of average body condition of spring 2006 and spring 1999-2005 Arthur R. Marshall Loxahatchee National W ildlife Refuge alligators.......................................... 53 2-10 Analysis of variance for average body condition of spring 2006 and spring 19992005 Arthur R. Marshall Loxahatchee Na tional W ildlife Refuge alligators..................... 54 3-1 The AICC and Akaike weights of models used to describe the em ergence dynamics of Arthur R. Marshall Loxahatc hee National Wildlife Refuge alligators......... 75 3-2 Regression coefficients ( -values) and associated confidence intervals of the averaged m odel used to describe the em ergence dynamics of Arthur R. Marshall Loxahatchee National Wildli fe Refuge alligators.............................................................. 76

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8 3-3 Summary of the differences between e quation-predicted proportion (P) and actual observed proportion (O) of alligators emerge d at Arthur R. Marshall Loxahatchee National Wildlife Refuge in 2005-2006............................................................................ 77 3-4 Results of a paired two-sa m ple t-test for spring predicted vs. observed proportion of alligators emerged at Arthur R. Marsha ll Loxahatchee National Wildlife Refuge in 2005-2006..........................................................................................................................78 3-5 Results of a paired two-sample t-test for summ er predicte d vs. observed proportion of alligators emerged at Arthur R. Marshall Loxahatchee National Wildlife Refuge in 2005-2006..........................................................................................................................79 3-6 Results of a paired two-sample t-test for autum n predicted vs. observed proportion of alligators emerged at Arthur R. Marsha ll Loxahatchee National Wildlife Refuge in 2005-2006..........................................................................................................................80 A-1 Results of epoxy experiment for transmitter attachment................................................... 98 A-2 Summary of transmitter application and recovery ............................................................. 99

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9 LIST OF FIGURES Figure page 2-1 Study site at Arthur R. Marshall Loxahatchee National W ildlife Refuge......................... 44 3-1 Relationships between observed and pred icted proportions of al ligators em erged at Arthur R. Marshall Loxahatchee National Wildlife Refuge, 2005-2006........................... 81 3-2 Relationships between water temperature ( C) an d proportion of alligators emerged at Arthur R. Marshall Loxahatche e National Wildlife Refuge, 2005-2006....................... 82 3-3 Relationships between rainfall (cm/hr) and proportion of alligators em erged at Arthur R. Marshall Loxahatchee National Wildlife Refuge, 2005-2006........................... 83 3-4 Relationships between wind speed (km/h r) and proportion of alligators em erged at Arthur R. Marshall Loxahatchee National Wildlife Refuge, 2005-2006........................... 84 A-1 Parietal/squamosal wiring................................................................................................ 100 A-2 Transmitter attachment.................................................................................................... 101 A-3 One recaptured alligator with the tran smitter firm ly in place.......................................... 102

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10 Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science EMERGENCE DYNAMICS OF AMERICAN ALLIGATORS ( Alligator mississippiensis) IN ARTHUR R. MARSHALL LOXAHATCHEE NATIONAL WILDLIFE REFUGE: LIFE HISTORY AND APPLICATION TO STATEWIDE ALLIGATOR SURVEYS By Christopher David Bugbee May 2008 Chair: Frank Mazzotti Major: Interdisciplinary Ecology The purpose of this study was to extend knowledge of the behavioral ecology of alligators in the seasonally fluctuating south Florida environment and then apply this knowledge to develop estimates of alligator detectability for management purposes. I first modeled alligator thermoregulatory response to environmental co nditions by investigating emergence rates and using them as an index of heat seeking or heat avoidance. All models indicated a higher probability of emergence in the sp ring compared to that of the fall. Springtime solar radiation had a positive affect on emergence probabilities. Larger alligators showed a higher degree of heat avoidance in the summer and spent less time emerged than smaller individuals in this study. Body condition also had an effect on emergence rates as alligators with higher body condition scores had higher rates of emergence. I also investigated alligator emergence behavior and how it relates to a variety of environmental variables known to have an effect on crocodilian behavior including season, air and water temperature, moon phase, rain, and wind. Data were analyzed using the GENMOD procedure in the Statistical Analysis System. An Akaike Information Cr iterion (AIC) for model selection was calculated for each model, and mode l averaging was performed to come up with a

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11 final model that best describes and predicts al ligator emergence. Compared to spring and fall, alligators were less likely to be emerged at a ny given time during summer Compared to summer months, alligators in autumn are only slightly more likely to be emerged. Alligators are less likely emerged in low moonlight compared to half moon or full moon cycles. In addition, alligators are slightly more li kely to be emerged during half moons compared to full moons. During nighttime hours, higher water depths decreas ed the emergence rates of alligators. Higher water temperatures result in decreased emergen ce rates, while higher air temperature results in increased emergence rates. I found that the best time for conducting surveys is in low wind, in half or full moon phases, and on clear, cloud-f ree nights with relativ ely high air and water temperatures and relatively lower water dept hs. Regardless of conditions, an equation was developed that south Florida alli gator researchers can use to adju st their survey results in an appropriate manner to correct for the influence of varying environmenta l conditions on alligator detectability. Although the equation successfully predicted alligator emergence rates in the summer and fall, it lost much of its predictive ab ility in the spring. I su ggest that some other variable or variables that we re not measured in this study were effectively overriding the expected influence of the surr ounding environment. This research can be used by alligator managers to reduce the amount of time needed to detect significant changes in alligator populations as they respond to rest oration actions. Eventually, as th is type of research advances, alligator managers will be able to incorporate actual population le vels and not indices into their monitoring programs.

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12 CHAPTER 1 INTRODUCTION The American Alligator The Am erican alligator ( Alligator mississippiensis) is considered a keystone species and top predator in the Greater Everglades Ec osystem (Mazzotti and Brandt 1994). Through construction of holes, caves, and trails, alligators create resources for a wide variety of biota including aquatic plants, fish, amphibians, a nd reptiles including othe r alligators (Beard 1938; Kushlan 1974; Mazzotti and Brandt 1994; Rice et al. 2005). As a reptilian top predator, the American alligator consumes a wide variety of prey species as it grows from a hatchling to an adult. Hatchlings consume small prey such as ins ects and fish and also serve as prey to a variety of other species including their own (Deitz 1979; Barr 1997). Large juveniles function ecologically as Everglades mesopredators, consum ing larger prey but stil l serving as potential prey for adults. Considering these dynamics, alligators play a significant role in shaping the faunal community of the Everglades ecosystem (Rice et al. 2004; 2005). The alligator is also a prominent example of an ecosystem engineer in the Everglades. Alligators create holes in the marsh that provide refugia for a variety of plants and animals, particularly in the dry season (Kushlan 1974; Loftus and Eklund 1994; Palmer 2000). These holes influence the community structure of a quatic fauna and vegeta tion, both concentrating aquatic life for predators and creating conditions that favor certain plant species over others (Craighead 1968; Palmer 2000). A dditionally, alligator nests create suitable habitat for vegetation sensitive to elevati on (Palmer 2000) and provide nesti ng habitat for other reptiles (Craighead 1968; Kushlan and Kushlan 1980; Enge et al. 2000). First and foremost alligator holes serve to benefit alligato rs. Alligators of all size classe s use holes as refugia, from hatchlings to large adults (Campbell 1999). Repr oductive females use associated habitats for

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13 nesting, and both males and female s require alligator holes to c ourt and mate with one another (Garrick and Lang 1975). Of 29 alligator holes surveyed by Campbell (1999), all showed signs of recent alligator activity. Consequently, alligators help to shape the co mmunity structure of both plants and animals in the Everglades ecosystem. Alligators and the Everglades W ithin the last 100 years, the original Ever glades ecosystem has been spatially reduced, drained, and irreversibly lost as a result of extensive landscape alterations for development and flood control (Light and Dineen 1994). Once natural hydrologic fluctuations are now anthropogenically controlled (L ord 1993; Davis and Ogden 1994) Wildlife populations have been affected following development and drainage of the Everglades ecosystem, and this is especially true of alligators (Mazzotti and Brandt 1994). Sp ecifically, alligator population densities are lower in over-drained marshes a nd swamps. Reproductive output is known to be lower in areas characterized by prolonged high water depths due to nest flooding. Alligator body condition may also be consisten tly lower in these areas due to prolonged dispersion of aquatic prey (Mazzotti and Brandt 1994; Dalrymple 1996; Barr 1997). Additionally, although many alligators use manmade canals as habitat, canals may be population sinks as both reproductive and survival rates are lowered due to increa sed nest flooding and cannibalism of smaller individuals (Mazzotti and Brandt 1994; Chopp 2002; Rice et al. 2005). The South Florida Restoration Initiative began in 1992. The Comprehensive Everglades Restoration Plan (CERP) was signed into law in 2000 and repr esents the primary means of achieving Everglades restoration. Restoration efforts include pr ojects to remove canals and increase the extent and quality of natural areas. Wildlife studies in the Everglades ecosystem often focus on the effects of fluctuating wate r depths on the ecology of the study organisms. Population trends of some organisms can be vi ewed as indications of ecosystem change, and

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14 ecological modeling is a vital tool used in the adaptive assessment of re storation (Gunderson et al. 1994; Gentile et al. 2001). Several aspects of alligator ecology have b een shown to be dependent on water levels. These include courtship (Garrick and Lang 1987; Vliet 1987), nesting (K ushlan and Jacobsen 1990), growth and survival (Hines et al. 1968), and body condition (Zweig 2002). Alligators are sensitive to fluctuating water levels both spat ially and temporally, and the success of many other species is linked to the natural presence of alligat ors. For these reasons, alligators represent an ideal performance measure of restoration progre ss and are an integral part of the Adaptive Assessment Process component of CERP (CERP Monitoring and Assessment Plan 2003, section 3.1.3.15). Although alligators have received much scie ntific attention and are a well-studied species, there are still many aspects of its behavioral ecology that remain unknown. Everglades Alligator Thermal Ecology The Am erican alligator has evolved to inha bit warm-temperate rather than tropical environments (Brisbin and Standora 1982; Mazzotti 1989). Among the living crocodilians, alligators (both Alligator mississippiensis and Alligator sinensis ) are the only species that have evolved to inhabit environments that experience sub-freezing temperatures (Brisbin and Standora 1982). South Florida however is subtropical and re presents the southern extent of the natural range of the American alligat or (Mazzotti 1989; Conant and Collins 1991). South Florida is characterized by consistent high temperatures and a distinct wet and dry season that together present a unique set of ch allenges for alligators that inhabit this re gion (Dalrymple 1996; Barr 1997; Howarter 1999; Kushlan and Jacobsen 1990). Alligator habitat south of Lake Okeechobee represents an environment with a high cost: benef it ratio for alligators for a significant part of the year (Dalrymple 1996; Kushlan and Jacobsen 1990) This is especially true during summer and fall due to high levels of virtually inescapable heat (high cost) combined with relatively low

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15 availability of food due to higher water depths and the resulting dispersal of aquatic prey (low benefit). In spring, south Florida can be described as an enviro nment with a comparatively low cost: benefit ratio, or one in which temperatures are less extreme (lower cost) and food is more concentrated (higher benefit). In theory, crocodilians and other reptiles inve st more energy into active thermoregulation in environments that are charac terized by low cost: benefit ratios (Spotila et al. 1972; Heatwole 1976; Huey and Slatkin 1976; Lang 1980; Lang 1987; Shine and Madson 1996). In thermally variable or productive environments, there ar e usually many avenues of heat exchange and adequate energetic resources to invest energy into active ther moregulation (Heatwole 1976; Lang 1987; Slip and Shine 1988; Shine and Madson 1996) In the spring for example, Everglades alligators respond by actively engaging in behaviors such as basking and or ienting their bodies in relation to the suns rays to optimize solar absorp tion (Spotila et al. 1972; Lang 1987; Mazzotti 1989). This active heat-seeking beha vior is reflected in the tre nd that alligator body temperature is most variable and often greater than ambi ent temperatures in the spring (Howarter 1999). Alternatively, reptiles that inhabit thermally -equable environments, or environments characterized by high cost: benef it ratios generally adopt a more thermal generalist strategy and thermoconform to their surrounding environm ent (Heatwole 1976; Lang 1980; Lang 1987; Shine and Madson 1996). The advantage of this strategy is to conserve energy stores. By becoming less active and thermoconforming, meta bolic rates are reduced and en ergy is conserved for other processes such as growth or reproduction (Lang 1987). There is some evidence that south Florida alligators adopt more of a thermoconformer stategy in the hotter summer and fall months (Lang 1977, Abercrombie 2002). Alligator body temperatures are higher, more stable, and better correlate wi th environmental temperatures

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16 during fall compared to spring in south Florida (Abercrombie 2002). During summer and fall, alligators also appear to shif t their behavior by remaining subm erged to keep cool (Howarter 1999, Abercrombie 2002). Alligators appear to be more nocturnal in summer (Woodward and Marion 1979), and the dominant strategy may be to remain submerged for most of the daylight hours. In climates with high ambient temperatures crocodilians often leav e the water altogether at night to release excess heat (Lang 1980; M azzotti 1989). The shift to a primarily nocturnal lifestyle during the hotter portion of the year is typical of reptil es found in tropical environments (Heatwole 1976; Lang 1980; Lang 1987; Luiselli and Akani 2002). Alligator thermoregulatory behavior may closely reflect a seasonal shift in the cost: benefit ratios of the south Florida environment. The first objective of this study was to inves tigate patterns of thermoregulatory behavior by comparing alligator emergence behavior and circadian rhythms to patterns of solar radiation, water level, and seasonal change in the south Florida environment. I expected that if south Florida represents an environment that undergoes a seasonal shift in co st: benefit ratios for alligators, then alligator thermoregulatory beha vior will reflect this by showing some kind of transition. I expected to see behavi or that reflected an environmen t with a low cost: benefit ratio during the relatively cooler portions of the year (i.e. lower heat levels and higher food concentrations) and behavior that suggested an environment with a hi gh cost: benefit during summer and fall (i.e. higher heat levels and lowe r food concentrations). Specifically, I expected alligators to actively engage in heat-seeking thermoregulation dur ing the spring and to transition to thermoconformity during the hotter portion of the year stop when the costs of active thermoregulation outweigh the benefits.

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17 Everglades alligators likely ha ve a built-in response system that governs their behavior in an thermally optimal way when confronted by seasonal change. Lang (1 976) suggested that photoperiod, not necessarily ambient temperatures may be the driving force behind alligator amphibious behavior. If this is the case, then anthropogenically manage d water regimes in the Everglades should approximate natural ones. If natural conditions and water cycles are not maintained in the Everglades, alligators may not optimally thermoregulate. For example, if water levels are too high in the spring, and spring shifts to a low cost low benefit environment, how would alligators respond? Similarl y, if water levels are too low in the summer and fall, and the environment becomes one of high costs and high benefits, would alligators effectively miss the opportunity to feed and restore energy stores? The end result c ould have negative effects on the fitness of individual animals, and ultimately ha ve negative impacts at the population level. Alligator Surveys Successful restoration of the Everglades will be assessed through monitoring of performance measures concerning indicator species (Rice et al. 2005). The alligator has been chosen as one of these indicators and pe rformance measures including abundance and distribution, nesting, body conditi on, and alligator hole occupancy are currently be ing monitored (Rice et al. 2005). Spotlight surveys (or nigh t counts) are a common approach to monitoring crocodilian abundance and distribution (Magnuss un 1982; Bayliss 1987; OBrien 1990; Wood et al. 1985; Hutton and Woolhouse 1989; Woodward a nd Moore 1990). In south Florida, spotlight surveys are used to describe alligator encounter rates (alligators/km). Due to a variety of confounding variables (detectability, habitat use, habitat characteristics, survey speed), encounter rates do not directly translate into esti mates of alligator density (alligators/km2) or abundance (the number of alligators in a defined area). Instead, spotlight surveys serve as a relative index of abundance. Over time, trends in encounter rate data can provide information about alligator

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18 population trajectory in response to management actions. This index becomes more robust when factors such as detection or detectability are considered (C assey and McCardle 1999; Thompson and Seber 1994; Thompson 2002). Estimating wildlife abundance re quires replicated scientif ic and statistical methodology (Steinhorst and Samuel 1989). It is impossible to assess the true number of alligators in a population, but models can be established that desc ribe correlations between survey results and population size. Understanding detectability is essential for the accuracy of such models (Steinhorst and Samuel 1989; Cassey and McCardle 1999; Thompson and Seber 1994; Thompson 2002). This research attempts to descri be alligator detectabilit y during encounter rate surveys to account for individua ls present in the population that were not recorded by the observer due to several reasons: alligators may have been pr esent but simply missed by the observer, they may have been pr esent but in a low visi bility habitat, or they may have been submerged and effectively not present for the researcher to observe (Woodward and Marion 1979). Specifically, I investigated alligator emergence behavior and how it related to a variety of environmental variables known to effect croc odilian behavior (Wood ward and Marion 1979; Pacheco 1996; Sarkis-Goncalves et al. 2004). The ultimate goal was to develop relationships between alligator detectability and various enviro nmental factors that alligator managers can use to reduce bias in survey results. This research is critical for alligator management in south Florida as it will reduce the amount of time needed to statistically detect changes in alligator populations as they respond to diffe rent restoration actions, thus allowing managers information needed to adaptively manage Everglades restoration.

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19 CHAPTER 2 AMERICAN ALLIGATOR ( Alliga tor mississippiensis ) AMPHIBIOUS BEHAVIOR AND THERMAL ECOLOGY IN RESPONSE TO ENVIRONMENTAL FLUCTUATIONS Introduction The Everglades ecosys tem is characteri zed by seasonally fluctuating hydrological conditions due to naturally occurring patterns of precipitation (Mazzotti and Brandt 1994). The American alligator has received scie ntific attention in the Everglades for its ability to indicate the overall health of this ecosystem (Rice et al. 1994). Several aspects of al ligator biology including courtship, nesting, growth and survival have all been examined in some detail in relation to water depths (Hines et al. 1968; Kushlan and Jacobsen 1990; Vliet 1987). However, alligator amphibious behavior and its role in thermoregulation in a fluctu ating environment has not been examined. Alligator Amphibious Behavior For crocodilians, different behavioral activi ties (foraging, resting, thermoregulation, etc.) can occur under water, at the water surface, or on land. For example, in all crocodilians, some social interactions and foraging behavior occur underwater (Webb et al. 1982; Fish and Cosgrove 1987; Vliet 2001). However, it remains unclear as to what extent alligators vary their amphibious behavior depending on seasonal fluctuations and environmental conditions. Alligators may allocate more time and energy towards certa in behaviors (i.e. foraging, socializing, thermoregulating) in response to water depths an d other environmental fluctuations associated with seasonal change (Lang 1979; Howarter et al. 2000). Alligators primarily thermoregulate behaviorally and use various thermal microhabitats in the environment as resources (Lang 1979; La ng 1987; Mazzotti and Br andt 1994). Alligators exposed to different environmental conditions are known to use thermal resources differently (Lang 1976; Lang 1979; Lang 1987; Ab ercrombie et al. 2002). In a seasonally fluctuating

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20 environment like the Everglades, alligators likel y have an optimal behavioral response when confronted by seasonal change (Lang 1976). If th is response is triggered by some natural cue such as photoperiod or ambient temperature (Lan g 1976), then other natural conditions such as water depth should be in harmony. A prolonged divergence from natural conditions in the Everglades, particularly water cycles, may in terfere with alligator thermal behavior. For example, if water depths are cons istently too high in spring, or consistently too low in summer and fall, alligators may not be able to alloca te their energetic resources toward appropriate activities including thermoregulatio n. This may have negative eff ects on survival and fitness of individual animals, and ultimately have negative impacts at the population level. Furthermore, Mazzotti and Brandt (1994) suggest ed that alligators of different sizes and sexes use wetland habitats distinc tly on varying spatial and tempor al scales and in response to changing water depths. Campbell and Mazzotti (2001) suggest further that in the Everglades, alligator holes associated with tree islands more often contain an adult female alligator and hatchlings, while relatively smaller satellite holes in marl substrates t ypically contain juveniles and sub-adults. But with lower spring water depths in the Everglades, these satellite holes tend to dry up faster, and alligators become concentrated in remaining alligator holes and trails (Mazzotti 1989; Kushlan and Jacobsen 1990; Mazzo tti and Brandt 1994; Rice et al. 2005). Adult male alligators have been observed to travel between remaining alligator holes during spring dry downs (Campbell and Mazzotti 2001). Ev erglades alligators of all sizes are thus forced to share the same space in the spring which may result in higher rates of ca nnibalism (Mazzotti and Brandt 1994; Campbell and Mazzotti 2001). Also, al ligators in crowded conditions may not be able to thermoregulate optimally as their natural behaviors are known be affected as a response to overcrowding (Seebacher and Grigg 1997; Asa et al. 1998).

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21 An investigation into the amphi bious behavior of alligators will allow managers to more completely understand the full range of behavioral adaptations Everglades alligators use to deal with the fluctuations that ch aracterize the Everglades. A Harsh Environment The severity of anthropogenic alteration of the Everglades ecosystem has taken a toll on natural alligator population levels, dynamics, a nd distributions (Mazzotti and Brandt 1994; Rice et al. 2005). Alterations have intensified the negative effects of natural droughts (Jacobsen and Kushlan 1984), reduced and altered the amount of available habitat (Kushlan 1974; Kushlan 1990; Gunderson and Loftus 1993), and negatively affected nesting efforts and reproduction (Kushlan and Jacobsen 1990). Sout h Florida poses a unique set of ch allenges for alligators as it represents the southern extent of their natural range. The Everglad es is subtropical whereas most alligator populations occur in a warm-temperate zone (Brisbin and St andora 1982; Conant and Collins 1991; Mazzotti 1989). A general ecological trend is that organisms that inhabit the peripheries of their natural range are often faced by a unique set of challenges and may be physically stressed (Heatwole 1976; Pulliam 1988; Dias 1996). South Florida alligators physically reflect their environmen t as they are generally smaller, thinner, and take longer to grow and mature when compared to alligators from north Florida or Louisiana (Kushlan and Jacobsen 1990; Dalrymple 1996; Barr 1997). This may be due to several reasons including climate and food availability (Jacobsen and Kushlan 1989; Dalrymple 1996; Barr 1997). The American alligator is a crocodilian that has evol ved to inhabit temperate rather than tropical environments (Brisbin and Standora 1982; Mazzo tti 1989). South Florida essentially represents an intermediate between the two, and is ch aracterized by consistently high and equable temperatures compared to other parts of alligators range. This relatively warmer climate may result in high metabolic costs for alligators that inhabit this part of their range (Howarter 1999;

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22 Percival et al. 2000). On the same note, although south Florida wint ers are relatively mild, winter temperatures still reduce alligator body temperat ure to levels that inhibit activity (Howarter 1999). Therefore, south Florida alli gators are inactive for a greater portion of the year than are their northern counterparts. Thermoregulation It has been traditionally argue d that active behavioral ther m oregulation is less important for tropical ectotherms than it is for their temp erate counterparts (Heatw ole 1976; Peterson et al. 1993; Shine and Madson 1996). Specifically, becau se of physiologically compatible thermal conditions characteristic of the tropics, tropical ectotherms allo cate relatively less energy towards behavioral thermoregulation. In theory, reptiles invest more in active th ermoregulation when the benefits outweigh the costs and there are relativel y few physical or energe tic constraints (Spotila et al. 1972; Heatwole 1976; Huey and Slatkin 19 76). This may occur in a thermally variable environment where there are many thermal choices and many avenues of heat exchange for an ectothermic animal (Heatwole 1976; Lang 1979; Lang 1987; Slip and Shine 1988; Shine and Madson 1996). Given the opportunity, a thermal stra tegy tends to evolve in which an animal invests more into remaining, by means of active be havior, within a narrow range of temperatures (Huey and Slatkin 1976). In other words, reptiles will thermoregulate when it is necessary and when there are opportunities to do so. In the sp ring throughout their natural range, alligators respond by actively engaging in behaviors such as basking and orienting th eir bodies in relation to the suns rays to optimize solar absorpti on (Spotila et al. 1972; Fish and Cosgrove 1987; Mazzotti 1989). In the Everglades, this active heat-s eeking behavior is reflected in the fact that alligator body temperature is most variable in the spring and often higher than that of the surrounding environment (Aberc rombie et al. 2002).

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23 Alternatively, reptiles in thermally equable environments (where thermal choices are limited) or in environments with high cost: benefit ratios generally adopt a more thermal generalist strategy and thermally conform to their surrounding environment (Heatwole 1976; Huey and Slatkin 1976; Lang 1987; Shine and Mads on 1996). In other words, reptiles will not thermoregulate when it is physiologically unnece ssary or there are no opportunities to do so. Behavioral thermoregulation has its associated costs and if these costs are great thermoregulation becomes disadvantageous. Behavioral thermoregulat ion can only be beneficial when its costs are relatively low, and thermal specialists will engage in thermoregulation more than thermal generalists unless costs are high (Heuy and Slat kin 1976). The advantage of this strategy is simply to conserve energy stores. By becomi ng less active, metabolic rates are reduced and energy is conserved for other processes such as growth or reproduction (Lang 1987). For example, during the hotter portions of the year, ma ny tropical reptile speci es also become more nocturnally active and thus avoid the intense heat of the day (Heatwole 1976; Huey and Slatkin 1976; Shine and Madson 1996; Luiselli and Akani 2002). Spring in south Florida may be considered an environment with a lower cost: benefit ratio to alligators due to less extreme ambient temperat ures, more variable thermal environments, and more concentrated, available food resources that result from annua l dry downs. During this time, alligators could theoretically afford to invest more in behavioral th ermoregulation and would behave as thermal specialists. In summer and possibly fall, south Florida becomes an environment with a high cost: benefit ratio for al ligators due to consiste ntly high temperatures coupled with low food resources due to increasing water depths and prey dispersal (Barr 1997; Dalrymple 1996; Kushlan and Jacobsen 1990). During this time, south Florida alligators may be unable to invest as much into behavioral thermo regulation and the strategy may shift from that of

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24 a typical thermal specialist species to that more of a typical thermal conformer, as strategies of thermoregulation and thermal conformity likel y occur on some continuum (C. O. Da C. Diefenbach 1975). The purpose of this study was to extend knowledge of the behavioral ecology of alligators in the seasonally fluctuating and anthropogenica lly controlled south Florida environment. I investigated alligator behavi oral response to environmenta l conditions by investigating emergence behavior. I viewed emer gence rates (proportion of time sp ent at the waters surface or on land) as an index of heat se eking or heat avoidance behavior as alligators are known to behaviorally thermoregulate both on land and at the water surface by assuming various postural positions or by varying the proportion of the body that is exposed (Fish and Cosgrove 1987; Lang 1987). Specifically, I investigat ed effects of season, solar radi ation, nocturnal behavior, and water depths on emergence activity. I hypothesized th at Everglades alligators would show lower emergence rates in summer, followed by fall and then spring due to a general avoidance of intense heat and decreasing thermoregulation with increasing heat. Unfortunately I was unable to test emergence rates in winter; however Everglad es alligators are though t to be highly inactive during the colder winter months, usually resting in shallow water with only their nostrils exposed (Morea 2000). I also hypothesized that highe r water depth would reflect higher summer temperatures and result in lower emergence rates. Alligators depend on water for effective cooling during summer, and water depths are highes t in the summer. I expected solar radiation to positively influence emergence rates in the spring, but to negatively influence emergence rates in summer and fall when heat is avoided by alligators I also hypothesized that alligators would be more nocturnally active in summer and fall like many temperate and tropical ectotherms, including other crocodilians (Maz zotti 1989; Luiselli and Akani 2002) Essentially, I expected to

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25 see behavior that reflects low cost: benefit ratios during the relatively cooler portions of the year and behavior that suggests a high cost: benefit ratio during summer and fall. I also examined effects of size, sex, a nd body condition on alligator emergence rates. While large and small individuals within a species generally hold the same body temperatures, they accomplish this by different means (Mazzot ti 1989). For example, all crocodilians depend on solar radiation and conduction in water to al ter their internal temperatures, but as size decreases, the importance of the convective e nvironment (ambient air temperatures) becomes more important (Lang 1987; Mazzotti 1989). Larger cr ocodilians also lose heat at a slower rate compared to smaller crocodilians and have comparatively more stable body temperatures than smaller individuals (Wright 1987). I hypothesized th at since the body temper atures of relatively smaller alligators are more quickly adjusted by the thermal environment, these individuals will more often exploit the full spectrum of thermal options and as a result may be more active in patterns of emergence and submergence. On the other hand, I hypothe sized that larger crocodilians, once having achieved optimal body temperatures in the morning (Lang 1987; Mazzotti 1989) might be expected to spend most of their time submerged in the aqueous portion of their habitat, especially in the hotter m onths, and would invariably would spend less time emerged than smaller individuals. Larger crocodilians are also expected to have potential for longer dives due to their mass-dependent rates of oxygen consumption (Wright 1987). Additionally, metabolic heat pr oduction may be significant for larger alligators (Lang 1987; Mazzotti 1989) and this would result in larger in dividuals having to spend even less time seeking radiation at the water surface. I included the role of body condition to acc ount for the likely variability in physical condition that may influence the effect of alli gator size on emergence ra tes, as measured by

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26 mass/length relationships. Also, the relative phys ical condition of an individual Everglades alligator, as revealed by body c ondition score (Zweig 2002), may have an effect on its ability to tolerate environmental stressors I hypothesized that alligators with higher body condition scores will show higher emergence rates during the hotter pa rts of the year compared to alligators with low scores. Some authors report a male-biased sex ra tio in alligator cap tures (Chabreck 1965; Woodward and Marion 1979; Woodward and Linda 1993). Male alligators are also know to have larger home ranges and higher levels of move ment compared to females (Chabreck 1965; Howarter 1999). Female alligators may be more sedentary and secretiv e in nature. For this reason, I expected to see a hi gher rate of male emergence over female emergence. Materials/Methods Study Area This study was conducted within the Arthur R. Marshall Loxahatchee National W ildlife Refuge (LOX) located in western Palm B each County, Florida (Fig. 2-1). LOX is an approximately 57,324 hectare refuge that represents the northern most extent of the Greater Everglades Ecosystem. LOX is characterized by having a deep layer of peat and organic soil (Richardson et al. 1990; Davis et al. 1994) atop bottom bedrock w ith large areas of open sloughs, wet prairies, and sawgrass stra nds (Richardson et al. 1990). My study site is within the southcentral portion of LOX, an area defined by a relatively stable, year-round hydroperiod, comparatively dense vegetation, a nd a relatively high alligator dens ity (L. Brandt, pers. comm.). Telemetry I used rad io transmitters attached to the pari etal bones of twenty-eight alligators to investigate emergence rates in this study. Cu stom VHF transmitters were equipped with conductivity switches that doubled the pulses per minute of the broadcasted signal when the

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27 transmitter was under water. Transmitters were also designed to digitally broadcast the proportion of time the transmitter was underwater dur ing the last hour. A fixed antenna and radio receiver were installed at the study site (UTM 17R 0573247, 2926401) and were used to detect and record the status of all deployed transmitters. The receiver was programmed to cycle continuously through all deployed transmitters so that each frequency was searched and its status recorded once per hour. In addition to the antenna/receiver, a weather station was installed at the study site to record solar radia tion. Weather data were correlated with emergence data recorded by the fixed receiver to determine potential rela tionships between alligat or behavior and solar radiation. Transmitters remained attached for ro ughly four months, and the study consisted of a 2005 (wet season, July-November, 10 alligators) and 2006 (dry season to onset of wet season, April-August, eighteen alligators) field season (See Appendix A for full details of telemetry methodology). Nest Searches Nest searches were also conducted f or every female used in this study. These searches consisted of driving the airboat in parallel transects for approxima tely 0.5 kilometers on all sides of the capture sites of all females. The purpos e of these searches was to obtain nesting information for the Refuge database, but was also relevant for this project because any data obtained from a nesting female may have biased the results due to altered behavior during nesting. Data Protocols/Management Protocols w ere developed to edit the data so that only accurate and reliable data were used for analysis. Full details on data protocol s and management are in Appendix B. Daily water depths (meters above bedrock) were collected by the USGS I-9 water gauge located within the study area. Sunr ise/sunset tables were obtained using data from the U.S. naval

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28 military astronomical observatories at http://aa.usno.navy.mil. Nocturnal hours were defined as the first and last hours of the nigh t that were characterized by full darkness, thus excluding the confounding twilight hours. Daylight hours were de termined similarly. Furthermore, season was divided into calendar spring (from beginning of study season until 20 June 2006), summer (21 June22 September 2005, 21 June23 September 2006, and fall (beginning 23 September in 2005 until end of study season) for both years. I did not investigate wet season versus dry season per se, since the onset of these seasons are variable from year to year. Instead, I investigated wet conditions versus dry conditions. Solar radiation data were collected by the weather station. Data Analysis Data were analyzed using the GENMOD proce dure in the S tatistical Analysis System (SAS 1985). The analysis was essentially a time -series logistic regression (White 1990), where the dependent variable was a binomial response of an alligator being emerged or submerged and independent variables included season, solar radiation, nocturnal hours, and water depth. All analyses were conducted on an hourly scale. Sin ce two weather readings were recorded every hour, averages of each independent variable were calculated using SAS and these averaged values were used in the analysis. The proportion of total alligators emerged at any given hour was used to investigat e patterns of activity. Since I investigated proportions of animals ra ther than individual al ligator patterns of activity, effects of alligator size, body condi tion, and sex on emergen ce probabilities were analyzed separately using the GL IMMIX procedure in the Statistical Analysis System. Since the size, condition, sex model involves measurem ents of individual al ligators, I chose the GLIMMIX procedure since it incorporates random eff ects. For this analysis, I used a subset of the data (due to data-related size constraints in the analysis) and analyzed only July emergence data to address my hypotheses regarding allig ator size, body condition, and sex. By examining

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29 one of the hotter months out of th e year, I will be able to get a better picture of how alligators respond to the high costlow benefit environment characteristic of the south Florida summer. I calculated body condition of my study animals using head length/mass Fultons K as proposed by Zweig et al. (2002), as this index allows for a spatial comp arison of alligator populations. For each alligator, data collected began on the second day post-attach ment to account for behavior in response to capture and transmitte r attachment. Since many transmitters detached before they were collected, a conservative estimate of transmitter detachment time was determined for each animal as the end point for da ta used in this analysis. This estimate was based on the last collected data points with correct digital IDs and an emerged status. A preliminary analysis of the data reveal ed a significant difference in emergence likelihood among the 2005 and 2006 study periods. However, each field season was meant to represent different seasons of the year. There were differences in emergence rates between seasons independent of year. Although some overl ap existed for summer months the data were pooled and analyzed using only seasons, not years, as covariates. Modeling Environmental variable analysis For m odeling purposes, I modeled the proportion of total telemetered alligators emerged as a function of season, solar radiation, nocturn al hours, and water dept hs (Table 2-1). An Akaike Information Criterion (AIC) for model selection was calculated for each model and was used to determine which variables or combination of variables created the best fit for modeling emergence behavior (Pollock et al. 2002). Essentially, AIC pena lizes for the addition of parameters, and thus selects a model that fits well but has a minimum number of parameters. Akaike weights were also calculated. The Akaike weight of a particular model describes, given the set of model used, and given that particular dataset, the pr obability that that particular model

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30 would be the best one to describe the obser ved data. Model averag ing was also done to incorporate the strengths of each competing model into a final model that would best describe the data collected. Model averaging essentially allows comp utation of a weighted average of a parameter from the competing models in the mode l set. By doing so, model selection uncertainty is included in the estimate of precision of the parameter, and thus unconditional estimates of variances and standard errors are produced. Size, condition, and sex variable analysis For this analysis, I m odeled the probability of emerged status of all telemetered alligators as a function of size (large or small as defined by being larger or smaller than the mean weight of all alligators in the study), c ondition (Zwieg et al. 2002), and se x (Table 2-2). In addition to modeling size, condition, and sex, I modeled possible interaction effects between these three variables and included sex*size, sex*condi tion, and size*condition. Since the GLIMMIX procedure generates only psuedo-liklihoods a nd psuedo-AICs, a comparison among different models is not applicable. Results Environmental Variable Analysis Model One was the most general model incl uding incorporated all of the individual param eters tested and was selected as the best overall model in the set. Model One had the lowest AICC and AICC value, as well as the most signi ficant Akaike weight (0.91) (Table 22). Incorporating the effects of all variables into the model was therefore very important. Of the entire model set, only four models had any Akaike weight at all. All of these models included the season variable, the solar radiation variable, wa ter depth, and a seasonal interaction variable. Models that did not have these va riables had no weight (Table 2-2).

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31 Based on regression coefficient values ( -values) of the final averaged model, it is apparent that alligators in this study showed a higher probability of emergence in the spring compared to that of autumn ( spring = 1.252 > autumn = 0.132) (Table 2-3). It is also apparent that when compared to spring and autumn, alligators were less likely to be em erged at any given time during summer ( spring = 1.252 > summer = 0; autumn = 0.132 > summer = 0) (Table 2-3). The regression coefficients of the final averaged m odel also indicated that solar radiation had an overall negative influence on emergence proba bilities, but this e ffect was slight ( solar = -0.001) (Table 2-3). However, solar radiation had a slight but positive influence on emergence probabilities in the spring and autumn when compared to summer ( spring = >0.001 > summer = 0) (Table 2-3). This result translates into the trend that alligators avoid solar radiation to a greater degree in the summer, although again the difference was slight. Another finding based on the final model is that alligators were less likel y to be emerged during the day than at night ( day = -0.148 < night = 0) (Table 2-3). Alligators also showed a greater degree of nocturnal behavior in spring compared to autumn and summer (( spring = 0.058 > autumn = -0.683, summer = 0) (Table 2-3). Finally, based on the regression coefficient values of the final averaged model, relatively higher water depths had a negative effect on the emergence rates of alligators ( depth = -0.077) (Table 2-3). Size, Condition, and Sex Variable Analysis Regression coefficient v alues indicated that in the month of July, th e relatively smaller animals used in this study were more likely emer ged at any given time compared to the larger individuals (F small= 0.1705 > F large= 0) (Table 2-4). Females were also less likely to be emerged than males in this study (F female = -1.4707 < F male = 0) (Table 2-4). Based on regression coefficient values, it is apparent that emerge nce rates were positively correlated to body condition (F condition = 0.1498) (Table 2-4). Many of the al ligators examined in the study had

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32 overall poorer body condition when compared to average body conditions for other areas in south Florida (Table 2-5), alt hough overall this tendency was not significant (p-value = 0.17) (Table 2-6). Spring 2006 study animals had overa ll poorer body condition when compared to average body conditions for other areas in south Florida (p-value = 0.05) (Table 2-7), but fall 2005 study animals did not differ (p-value = 0.88) (Table 2-8). Body condition was higher in the fall compared to the spring among the study anim als (Table 2-5). Spring-captured 2006 study animals had poorer body condition even when compar ed to spring-captured LOX alligators in other recent years (Table 2-9). Th is trend was apparent but not quite significant (p-value = 0.07) (Table 2-10). Discussion Seasonal Activities The f inal model indicated a highe r probability of emergence in spring compared to that of fall (Table 2-3). If springtime in the Everglades does represent more of a temperate environment with a low cost: benefit ratio, these results suggest that alligators are investing energy into active thermoregulation with increased basking behavior, assuming activ e behavioral thermoregulation has an associated energetic cost (Huey and Slatkin 1976; Seebacher and Grigg 1997). Abercrombie et al. (2002) report that Everglades alligators achi eved warmer temperatures than their environment in the spring, when they are th ought to more often leave or emerge from the water to bask. This active heat-s eeking behavior is also reflecte d in the fact that alligator body temperature is most variable in the spring and often higher than ambient temperatures (Howarter 1999; Abercrombie 2002). Everglades alligators ar e hypothesized to spend their time feeding in the spring, taking advantage of the spring concen tration of aquatic food resources during the seasonal dry down (Mazzotti and Brandt 1994; Dalrymple 1996; Barr 1997). Alligators are also hypothesized to seek heat afte r feeding (Lang 1979; Fish and Cosgrove 1987). Everglades

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33 alligators may be emerged more often in spring because they are elevating their body temperature following feeding. This would decrease digestion time and allow the alligator to eat again while food is relatively plentiful. Alligators would theref ore be emerged less in summer and fall not necessarily because it is too hot but because they are not feeding, and are therefore not seeking heat for digestion. Because alligator s experience reduced benefits in the summer and fall since they are typically eating less, they may also be reducing the costs by reducing behavioral thermoregulation and drifting towa rds thermal conformity on the continuum. Other natural behaviors besides thermoregulat ion could also help explain these results. Alligators move more during the spring in response to the breeding season (Chabreck 1965), and this may also help to explain the results of th is study. In addition, other seasonal variations not specifically measured in this study may exert ad ditional influence over alligator behavior. Many reptiles (and indeed other forms of life) are especially sensitive to seasonal photoperiods, and it is the photoperiod that often act s as a behavioral and physiologi cal trigger (Heatwole 1976; Lang 1976; Christian and Weavers 1996). Lang (1976) pr oposed that photoperiod may even be a more important cue than temperature in determining alli gator amphibious behavior. If this is the case, then Everglades alligators might react in a pr edictable way regardless of water depth. With consistently low or high water de pths across seasons, alligators w ould not engage in a thermally optimal behavior, which would have negative e ffects on individual fitn ess and ultimately on populations. Solar Radiation Solar radiation had an overall negative influence on em ergence probab ilities in this study (Table 2-3). Alligators also avoided solar radiation to a greater degree in the summer (Table 2-3). The results of this study suggest that alligator thermoregulatory beha vior shifts from heat seeking to heat avoidance and reflects an environmental tr ansition from a relatively low cost: high benefit

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34 environment to a high cost: low benefit environmen t. Alligators in sout h Florida likely have no problems in achieving optimal temperatures in the spring through activ e heat seeking. Heat seeking behavior is gene rally described for the temperate alligator (Mazzotti 1989). Specifically, alligators are said to move onto land in the morning to bask and remain emerged, at least partially, thr oughout the day. Alternatively, tr opical crocodilians such as Crocodylus porosus generally display heat avoidance; they will bask in the early morning and spend the rest of the day submerged (Grigg et al. 1985; Mazzo tti 1989). However, the same heat avoidance behavior has been reported for American a lligators during summer mont hs in south Florida (Howarter 1999). Alligators in the Everglades struggle to keep their body temperatures low enough to be in the optimal range and thus exhi bit heat avoidance during the summer months (Howarter et al. 2000). Summertime heat avoidan ce by alligators is also suggested by Goodwin and Marion (1979), who report that alligators in a lake in Alachua county, north-central Florida, showed a decrease in activity during the hot summer months. Lang (1987) suggested that a crocodilians thermal preference is inversely related to its ther mal environment. Specifically, thermoregulation is obvious in species occupyi ng thermally variable environments while strategies of thermo-conformity characterize sp ecies living in thermally equable environments (Lang 1980). In any case, it can be argued that south Florida alligators exhibit a kind of fluctuating behavior between thermoregul ating and thermoconforming crocodilians. Although south Florida may be c onsidered an environment w ith a relatively lower costhigher benefit (to an alligator) during the cooler portions of the year, and an environment with a relatively higher costlower benef it during summer and fall, it may not be accurate to say that alligators invest less energy into thermoregulatio n. Heat avoidance behavior by alligators is still thermoregulation and may represent considerable cost. However, alligator body temperature is

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35 hypothesized to show more variability between the environment in the spring compared to warmer times of the year such as summer and fall (Howarter 1999, Abercrombie et al. 2002). This suggests that alligators approach thermal conf ormity in the hotter months as it does in the colder winter months as well (Howarter 1999). Strategies of thermoregulation and thermal c onformity likely occur on some continuum (C. O. Da C. Diefenbach 1975). In other words, there may not be an example of a perfect thermoregulator or a perfect thermal conformer. Many tropical species have been observed to display heat seeking behavior (Luiselli and Akan i 2002; Seebacher et al. 2005), and it is likely that many ectotherms have different preferred body temperatures depe nding on their activity (Lang 1979). Although alligators seem to approach thermal conformity during the hotter months in south Florida, they are not perfect thermal conformers since the availability of alligator holes allows an effective escape from the heat Alligators have also been observed actively avoiding heat when temperatures approach or exceed 35C (Fish and Cosgrove 1987). Unfortunately, data for winter behavior are l acking in this study. St rangely, alligators only sporadically exhibit heat-seeking behavior in the winter throu gh much of their Florida range (Brisbin and Standora 1982). Alligators only episodi cally seek relative warmth in the winter, and show thermal conformity to deep water temperatur es with body temperatures cooler than shallow water temperatures by an average of 3.6 C (Howarter et al. 2000). Du ring winter months across the alligators range it is probably too cold to feed and alligators might deal with the lack of food by staying cool and minimizing their metabolism. It has been suggested that alligators allow their bodies to cool in the winter but occasionally heat up to help remove meta bolic wastes (Howarter 1999). Emergence probabilities as a function of solar radiation winter remain to be tested.

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36 Circadian Rhythms Alligators were less likely to be emerged during day than at night (Table 2-3). Alligators in south Florida are often confronted by exce ss heat and may respond by becoming more active during cooler nighttime hours. The results of this study showed this trend especially in summer (Table 2-3). Interestingly, results show that alligators are more nocturnally active in summer compared to autumn. Summer is presumably the s eason which brings on the highest level of heat in south Florida (Barr 1997; Howarter 1999). Alligators probably become more nocturnally active in the summer months, compared to autum n, to climb onto land and release excess heat. When confronted by high heat and low food densiti es that characterize th e south Florida autumn, alligators may start to become less active both day and night. A comparison between alligator nocturnal beha vior across their natural range may yield interesting results. In the meantime, our results ar e similar to those report ed from earlier studies on Crocodylus porosus (Grigg et al. 1985) and Crocodylus johnstoni (Seebacher et al. 2005). Underwater dives occurred more often and for longer periods of time during daylight hours in the estuarine crocodile ( Crocodylus porosus ) studied by Grigg et al. ( 1985). The authors suggest that this species, like all crocodilians, are good visual pr edators and that daylight foraging/feeding is a reasonable ex planation for this pattern of activity. Another explanation is that daylight hours are spent res ting on the bottom, but this expl anation is less likely due to apparent irregularity of surfaci ng intervals. Interes tingly, crocodiles spent more time emerged during daily low tides, perhaps comparable to a relatively shallower aquatic habitat like the Everglades. Water depths may driv e behavior of this species in a different way than researchers have seen in the American alligator. Seebach er et al. (2005) reporte d similar results for Crocodylus johnstoni This species appears to be diurnally ac tive in terms of diving behavior and spends most of the nighttime hours at the su rface of the water. Activity patterns in C. johnstoni

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37 reflected but preceded both body temperature and solar radiation, and diving behavior began to decrease as body temperature and solar radiation peaked (Seebach er et al. 2005). Interestingly, this tropical species appears to show a heat-seeking behavior, being emerged more with high levels of solar radiation. A possible explanation for this trend is that C. johnstoni may forage differently than A. mississippiensis, and its behavior reflects that of its prey. Alternatively, C. johnstoni may operate in a significantly higher or more variable range of optimal body temperature than does A. mississippiensis Any interpretation of re ptilian thermoregulatory behavior must consider the physiology of the species in question. For example, some semiaquatic tropical lizards have been observed to thermally select for lower temperatures than their terrestrial counterparts (Christian and Weaver 1996). Also, in ferences drawn regarding alligator thermal selection must also consider other be havioral activities. There always exists the possibility that thermoregulation may sometimes take a backseat to ot her natural behavior including underwater foraging/f eeding and social interactions. Water Depths Alligator movem ent is said to increase w ith increased water depth (Chabreck 1965). In this study, alligators were less likel y to be emerged in relatively deeper water (Table 2-3). These results support my hypothesis that higher water depth would result in lower emergence rates. Other seasonal variations, as previously discussed and independent of water fluctuations, may exert more influence over alligator behavior and may effectively override the influence of water depths. Although LOX experiences seasonal fluctuations in water depths as does the rest of the Everglades ecosystem, the differences are often less extreme (Richardson et al. 1990). Unless it is an exceptionally dry year, LOX inner mars hes are characterized by a year-round hydroperiod. However, I may have been lucky in my choice of field seasons. Fall 2005 was an exceptionally

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38 wet year and LOX experienced unusually elevated fa ll water depths as a result of several tropical storms and hurricanes. Spring 2006 was remarkably dry, as significant rainfall did not occur until relatively late in the summer. Until then, much of the interior marshes at LOX had turned into mudflats (CB, pers. obs.). Effects of water depths versus season ar e difficult to separate. It becomes difficult however to test the effects of varying water de pths independent of seas on. Even by correcting for water depth, other seasonally dependent variables such as photoperiod and prey availability are not accounted for. To understand relationships be tween water depth and season, this study would need to be repeated in a compartment of Ev erglades where water depths are known to be exceedingly high or exceedingly low in spite of se ason, and results then need to be compared. The Greater Everglades Ecosystem, in regards to its compartmentalization and experimental water regimes, provides the best natural (or unnatural) laboratory in which to study such a relationship. Alligator Size My hypothesis that larger crocodilians m ight be expected to show a lower degree of emergence than smaller individuals was supported by the results of this study (Table 2-4), at least during a period of high co sts and low benefits. Although the sample size was relatively small, and all alligators were adults, the sma ller individuals in the study were more likely emerged at any given point in time compared to the larger individuals in the study during the months of July. Larger crocodilians lose heat at a slower rate compared to smaller crocodilians and have comparatively more stable body temperatures than smaller individuals (Wright 1987). Additionally, metabolic heat produ ction may be also si gnificant for larger alligators (Lang 1987; Mazzotti 1989). During the hot summer months, the la rgest alligators in this study appear to have

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39 consistently selected the cooler environmental medium, for example the water during the day and the ambient air at night. They showed lower emer gence rates in July and more often remained in the relatively cooler conductive medium than sma ller individuals. Larger alligators would have the inherent potential to avoi d solar radiation and remain in the conductive environment for longer as they have the physiological potential for longer dives due to th eir mass-dependent rates of oxygen consumption (Wright 1987). The smaller alli gators in the study ma y have been able to more quickly cool off in the conductive environmen t and as a result could more often return to the solar radiation at the water surface. As alligator size decreases, the importance of the convective environment (ambient air temperatur es) also becomes more important (Lang 1987; Mazzotti 1989). Alligator Condition My hypothesis that allig ators with highe r body condition scores will show higher emergence rates during the hotter parts of the year compared to alligators with low condition was also supported. Body condition showed a positive rela tionship with emergence rates in this study (Table 2-4). I would hypothesize further that indi viduals in better conditio n are better able to handle additional environmental st ressors. Although some reptiles have been known to seek heat while physically ill, this is usually a response to combat pathogens (Lang 1987) and heat-seeking does not seem to be a response to low energy stores. Many of the alligators examined in the study were underweight and had overall poorer body condition when compared to average body c onditions for other areas in south Florida (Table 2-5). Spring-captured 2006 study animal s had poorer body condition even when compared to spring-captured LOX alligators in ot her recent years (Table 2-10). This may be due to intense heat experienced by these alligators coupled with the extended hydroperiod at LOX that does not adequately allow physical concen tration of prey, especially following prolonged

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40 high water depths brought about by the storms and hurricanes of 2005. The sub-optimal physical condition of these individuals may have affected their natural behavior. An individual in poorer condition will be less able to tolerate environmental stressors. Some of these individuals may not have been ideal representatives for the species as a whole, or even for other population in south Florida. The poor condition of some of the females used in the study may also explain the lack of active nests. That body condition was higher in the fall compared to the spring among the study animals (Table 2-4) suggests that summer, fall, and winter seasons are probably energetically demanding for Everglades alligators. By spring alligators are in poor condition. However, spring is the season in which alligators are able to recover from seasonal trials (Dalrymple 1996; Barr 1997; Howarter 1999). Spring is metabolically the most important season for alligator populations in the Everglades due to breeding cycles and feedi ng on concentrated food supplies during the dry season (Dalrymple 1996; Abercrombie et al. 2000). Spring feeding will result in a recovery of fat stores and an increase in body condition by the fall (Abercrombie et al. 2000). This demonstrates the importance of seasonal cond itions to the long-term su rvival of Everglades alligators. Alligator Sex My hypothesis that m ale alligators would s how higher rates of emergence was supported by this study. Male alligators in this study were less likely to be emerged than females at any given point in time in July. Female alligators may be more secretive by nature and would therefore spend more time underwater. This pos sible trend was evident during the capture sessions of study animals across both years. For example, a 7:3 male: female sex bias resulted from opportunistic captures among the 2005 study an imals. In 2006, I actively selected for more females but still ended up with more males. This may suggest that either there is a male bias in

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41 the local population, or that females are simply more secretive than males by nature. Similar capture rates sex biases have been describe d for this species el sewhere (Chabreck 1965; Woodward and Marion 1979). In the presence of researcher activity, male alligators may be more likely at the surface than females due to territorial or other aggressive behaviors but th is remains to be tested. Male alligators are generally thought move more than females (Spratt 1997). Researcher presence could be included as another inde pendent variable in future studi es as human/airboat presence likely has some short-term effects on crocodi lian emergence behavior (Webb and Messel 1979; Woodward and Linda 1993; Pacheco 1996). Implications and Future Work Water depth is known to affect courtship, nestin g, growth and survival, but m ay also have impacts on other behavioral adaptations of Am erican alligators including thermoregulation. Summer and autumn temperatures, coupled w ith low food availability, are such physical stressors that alligators are dependent on the avai lability of standing water to escape heat and avoid activity. When water dries up completely, behavioral pattern s are disrupted including those associated with thermoregulation (Spotila et al.1972) If alligators in sout h Florida are deprived of water in summer and fall, their chances of survival, on an individual and population level, begins to fall. High summer heat requires gr eater summer water depths to provide thermal refugia (Howarter 1999), since behavioral avoidance of heat occurs at the bottom of a substantial water column. However, annual water depths can not be too high, because Everglades alligators depend on seasonal dry-downs that result in conc entrated food supplies (Jacobsen and Kushlan 1989; Dalrymple 1996; Barr 1997). If natural conditions and water cycles are not maintained in the Everglades, alligators may not optimally thermo regulate. For example, if water levels are too high in the spring, and spring shifts to a low co st: low benefit environment, alligators may

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42 respond by allocating energy towa rds careful behavioral ther moregulation but without the energetic gains of concentrated aquatic food. Similarly, if water le vels are too low in the summer and fall, and the environment becomes one of high costs and high benefits, would alligators effectively miss the opportunity to feed and rest ore energy stores as they avoid heat? The end result could have negative effects on the fitn ess of individual animals, and ultimately have negative impacts at the population level. Everglad es alligators are ultimately dependent on the natural seasonal variations a nd heterogeneity that character izes the greater Everglades ecosystem. A repeated study of similar de sign is suggested for locations in north Florida and/or another northern part of the alligators range for comparison. This would also enable us to corroborate whether any behavioral shifts occu r across alligator populations as a function of latitude. A repeated study woul d also offer a comparison between alligators of varying body condition. Finally, an interesting vari ation to the study design is also proposed. By adding an additional transmitter of similar design, one on the head as well as one attached mid-dorsally on the base of the tail, researchers could consider when an alligator is emerged or submerged, as well as when an alligator is in water or on land. This information will offer us more insight into thermoregulatory behavior and under what sp ecific conditions are alligators leaving and reentering the aquatic por tion of their habitat. Understanding alligator responses to differences in seasonal conditions allows us to better understand potential responses to alternate restoration actions in the Everglades. Understanding the thermal ecology of the American alligator in south Florida will allow managers to make more informed decisions regarding habitat restoration, especially in regard s to appropriate water

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43 depths. The emergence behavior presented here can also be practically applied to improve the efficacy of south Florida alligator surveys. The results of this study have hopefully shed some light on alligator behavioral ecology in south Florida, and these results may have important implications regarding alligat or surveys as well as conser vation/management decisions.

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44 Figure 2-1. Study site at Arthur R. Marshall Loxahatchee Nati onal Wildlife Refuge.

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45 Table 2-1. Environmental variables of all models used to describe the emergence dynamics of alligators in Arthur R. Marshall Loxahatchee National Wildlife Refuge. Model 1 Model 2 Model 3 Model 4 Season Season Season Season Water depth Water depth Water depth Water depth Solar radiation Solar radiation Solar radiation Solar radiation Night Night Night Night Solar radiation*season Solar radiation*seasonNight*season Night*season Model 5 Model 6 Model 7 Model 8 Water depth Water depth Solar radiation Night Solar radiation Night Night Night Model 9 Model 10 Model 11 Model 12 Season Season Season Season Solar radiation Solar radiation Solar radiation Solar radiation Night Night Night Night Solar radiation*season Solar radiation*seasonNight*season Night*season Model 13 Model 14 Model 15 Model 16 Season Season Season Season Water depth Water depth Solar radiation Water depth Solar radiation Solar radiation Solar radiation*season Model 17 Model 18 Model 19 Model 20 Season Season Season Season Water depth Water depth Night Night Night Night*season *Model 1 represents the general model

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46 Table 2-2. The AICC, AICC, and Akaike weights of 20 mode ls used to describe the emergence dynamics of alligators in Arthur R. Marshall Loxahatchee National Wildlife Refuge. MODEL AICC AICC AKAIKE WEIGHT 1 35074.31 0 0.91 2 35078.91 4.6 0.09 13 35091.25 16.93 <0.01 3 35097.61 23.29 <0.01 4 35102.75 28.44 0.00 14 35117.28 42.96 0.00 5 35177.36 103.05 0.00 9 35879.21 804.90 0.00 10 35883.54 809.23 0.00 11 35899.21 824.90 0.00 12 35904.32 830.01 0.00 15 35918.19 843.88 0.00 7 36129.64 1055.32 0.00 17 43652.47 8578.16 0.00 18 43660.88 8586.56 0.00 6 43737.70 8663.39 0.00 16 43818.98 8744.67 0.00 19 44474.17 9399.86 0.00 20 44633.77 9556.46 0.00 8 44824.13 9749.81 0.00 AIC values represent a relativ e index of goodness of fit compar ed to other models in the model set; the smaller the value the better the fit. Delta AIC values of < 2 generally suggest substantial evidence fo r the model. Values between 3 and 7 indicate that the model has considerably less support, and values > 10 indicate that the model is highly unlikely. Akaike weights indicate the probabi lity that the model is the best among the whole set of candidate models.

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47 Table 2-3. Regression coefficients ( -values) and associated confidence intervals of the averaged model used to describe the emergence dyna mics of Arthur R. Marshall Loxahatchee National Wildlife Refuge alligators. PARAMETER -VALUE LOWER 95% CI UPPER 95% CI Intercept 15.165 9.600 20.730 Autumn 0.132 -0.066 0.331 Spring 1.252 0.935 1.570 Summer 0.000 0.000 0.000 Water depth -0.077 -0.461 0.308 Daylight -0.148 -0.232 -0.065 Nighttime 0.000 0.000 0.000 Solar radiation -0.001 -0.001 -0.001 Autumn(night) -0.683 -0.840 0.527 Spring(night) 0.058 -0.419 0.536 Summer(night) 0.000 0.000 0.000 Autumn(solar) <0.001 <0.001 <0.001 Spring(solar) <0.001 <0.001 <0.001 Summer(solar) 0.000 0.000 0.000 *Intercept describes the slope of the regression. Parameters with -values of 0 serve as baseline measurements from which comparative values are draw n for other parameters in the group. Significant Pr>ChiSq values (>0.05) indicate the probability under the null hypothesis (the given parameter has no effect) of obtaining a test statistic at least as extreme as the observed value..

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48 Table 2-4. Regression coefficients of a model used to describe the emergence dynamics of alligators in Arthur R. Ma rshall Loxahatchee National Wildlife Refuge based on size, body condition, and sex. PARAMETER F-VALUE Pr>F Intercept -1.9341 <0.0001 Small 0.1705 <0.0001 Large 0.0000 <0.0001 Body condition 0.1498 0.0002 Female -1.4707 <0.0001 Male 0.0000 <0.0001 *Intercept describes the slope of the regression. Parameters with -values of 0 serve as baseline measurements from which comparative values are draw n for other parameters in the group. Significant Pr>ChiSq values (>0.05) indicate a parameter th at has a significant influence in the model.

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49 Table 2-5. Average body condition scores of 1999-2005 south Florida alligators and 2005-2006 Arthur R. Marshall Loxahatchee Na tional Wildlife Refuge alligators. LOCATION BODY CONDITION SCORE ENP SS 10.8 ENP FC 9.5 WCA3A-N41 9.3 WCA3A-HD 10.7 WCA3B 9.8 WCA2A 10.0 BICY 11.1 LOX 10.5 2005-2006 study animals 9.15 fall 2005 study animals 10.1 spring 2006 study animals 8.6 Values for all other south Florida locations represent the average values from 1999-2005. All alligators were caught roughly at the same time of y ear. ENP SS represents Shark Slough, Everglades National Park. ENP FC represents Frog City Slough in Everglades National Pa rk. WCA3A-N41 represents Water Conservation Area 3A North of Highway 41. WCA3A-HD represents Holiday Park. WCA2A represents Water Conservation Area 2A. BICY represents locations in Big Cypress National Preser ve. LOX represents other areas within A. R. Marshall Loxahatchee National Wildlife Refuge (Comprehensive Everglades Restoration Plan Monitoring and Assessment Plan Annual Assessment Report 2006).

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50 Table 2-6. Analysis of variance for averag e body condition of 2005-2006 Arthur R. Marshall Loxahatchee National Wildlife Refuge alligators and 1999-2005 south Florida alligators. SUMMARY Groups Count Sum AverageVariance 1999-2005 8 81.7 10.21 0.43 2005-2006 study animals 1 9.15 9.15 N/A ANOVA Source of Variation SS df MS F P-value F crit Between Groups 1 1 1 2.33 0.17 5.59 Within Groups 3 7 0.43 Total 4 8

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51 Table 2-7. Analysis of variance for average body condition of spring 2006 Arthur R. Marshall Loxahatchee National Wildlife Refuge alligators and 1999-2005 south Florida alligators. SUMMARY Groups Count Sum Average Variance 1999-2005 8 81.7 10.21 0.43 spring 2006 animals 1 8.6 8.6 N/A ANOVA Source of Variation SS df MS F P-value F crit Between Groups 2.31 1 2.31 5.38 0.05 5.6 Within Groups 3.01 7 0.43 Total 5.32 8

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52 Table 2-8. Analysis of variance for averag e body condition of fall 2005 Arthur R. Marshall Loxahatchee National Wildlife Refuge alligators and 1999-2005 south Florida alligators. SUMMARY Groups Count Sum Average Variance 1999-2005 8 81.7 10.21 0.43 fall 2005 animals 1 10.1 10.1 N/A ANOVA Source of Variation SS df MS F P-value F crit Between Groups 0.01 1 0.01 0.03 0.88 5.59 Within Groups 3.01 7 0.43 Total 3.02 8

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53 Table 2-9. Comparison of av erage body condition of spring 2006 and spring 1999-2005 Arthur R. Marshall Loxahatchee National Wildlife Refuge alligators. YEAR BODY CONDITION SCORE 1999 10.6 2000 10.5 2001 11.6 2002 10.9 2003 9.4 2004 10.2 2005 9.5 2006 study animals 8.6

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54 Table 2-10. Analysis of variance for averag e body condition of spring 2006 and spring 19992005 Arthur R. Marshall Loxahatchee Na tional Wildlife Refuge alligators. SUMMARY Groups Count Sum Average Variance 1999-2005 7 72.7 10.39 0.6 2006 study animals 1 8.6 8.6 N/A ANOVA Source of Variation SS df MS F P-value F crit Between Groups 2.8 1 2.8 4.67 0.07 5.99 Within Groups 3.59 6 0.6 Total 6.38 7

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55 CHAPTER 3 EMERGENCE DYNAMICS OF AMERICAN ALLIGATORS ( Alligator mississippiensis) IN ARTHUR R. MARSHALL LOXAHATCHEE NA TIONAL W ILDLIFE RE FUGE AND THEIR APPLICATION TO ALLIGATOR MONITORING Introduction Alliga tors are a top conservation concern in the Everglades ecosystem. They are an excellent indicator of ecologica l balance and measure of restor ation success. The alligators natural sensitivity to fluctuati ng water depths, as well as their sensitivity to overall system production as top predators, makes them ideal indi cators of the state of the ecosystem (Mazzotti and Brandt 1994; Rice et al. 2005 ). Since the success of many other species is dependent on a natural alligator populati on (Rice et al. 2004), alligator popula tions throughout south Florida are monitored closely as Evergl ades restoration advances. Everglades Restoration Methods are curren tly being developed for l ong-term monitoring of American alligator population trends throughout the Greater Everglades Ecosystem. This monitoring is part of the Monitoring and Assessment Plan (MAP) of RECOVER (REstorati on COordination and VERification) and has the goal of assessing the imp acts of Everglades Restoration. The scope of work for this study is related to the Comprehens ive Everglades Restoration Plan Monitoring and Assessment Plan (CERP, signed into law in 2000). The relationships betw een dry season refuge, aquatic fauna, wading birds, and alligators have b een identified as key uncertainties in the CERP. Alligators were chosen as an indicator of restor ation success in this plan due to their ecological importance and sensitivity to hydrology, salinity, habitat productivit y, and total system productivity (Rice et al. 2005). Models are bein g developed to predict the response of natural communities to restoration strategies. Data from this study, among others, will offer information

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56 that will be used to evaluate trade-offs of rest oration scenarios. But above all, data from this study will be used to improve alligat or monitoring in the Everglades. Everglades Alligator Surveys A network of survey routes was established to assess alligator di stribution and abundance throughout the Greater E verglades Ecosystem be ginning in 1998. This network was designed to monitor changes in alligator populations over time in response to restoration and includes sites in Arthur R. Marshall Loxahatchee National Wild life Refuge (LOX). The objective of this study was to improve alligator survey methods within the alligator survey network. Particularly, I investigated methods that would improve estima tes of alligator detectability during spotlight surveys, thereby decreasing the time required to de tect significant trends in alligator populations following different restoration actions. This resear ch will allow managers to quickly recognize and respond to a resulting positive or negative popul ation trend, and thus will provide a tool for adaptive management of Everglades restoration. Alligator Detectability During spotlight surveys most individuals in the alligat or population are never seen (W oodward et al. 1996). Previous estimates suggest that the undete cted alligators may represent as much as 91% of the total population (Woodward et al. 1996). During spotlight surveys, the probability of alligator detection by researcher s is a function of observer efficacy, habitat, alligator wariness due to airboa t/human presence, and natural va riations in behavior (Graham and Bell 1969; Murphy 1977; Brandt 1989; Wood ward and Linda 1993). This research will specifically focus on alligator emergence behavior s as they relate to various environmental factors, with the ultimate goal of correcting survey results in an appropriate manner to account for bias due to missed individuals. As alligator surveys provide a relative measure of alligator abundance, information from this study may be used to provide a more accurate index of the real

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57 number of alligators present during surveys, as well as to determine optimal conditions to conduct surveys. Determining alligator detectab ility due to emergence behaviors involves estimating the probability that an alligators head will be above water and therefore available for counting. This study aims to answer two central questions What proportion of a population would researchers expect to see under a given set of conditions and at what time of night and under what environmental conditions is the largest proportion of alligators at the surface and available for counting? Hypotheses It is assum ed that the proportion of time spent emerged is in part a function of environmental variables including season, water de pths, time of night, moon phase, water and air temperature, rain, and wind speed. My first hypothesis was that time spent emerged will be highest in the spring, when Ever glades alligators are generally more active feeding and breeding (Mazzotti and Brandt 1994; Howarter 1999; Abercrombie 2002). I also hypothesized that emergence rates will be higher when water depths are low, both because the dry season occurs during spring and because there will be less wate r available water in which to submerge. In relation to moon phase, I expected to see a positive relationshi p between emergence rates and level of moonlight. This assumption is base d on results obtained by Woodward and Marion (1979). In this north-central Florida study, al ligator counts during spotlight surveys were positively correlated with levels of nocturnal li ght during warm weather. Since south Florida temperatures are generally higher in all s easons (with the possible exception of summer) compared to north Florida, I expected to see this positive correlation throughout my study. I hypothesized that time spent emerged as a functi on of water temperature will show a slight positive relationship. This hypothesis was based on results reported from Woodward and Marion

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58 (1979) and Murphy (1977). Woodward and Mari on (1979) however suggest that this positive relationship is strongest during times of relatively cool ambient air temperatures. During warm weather, this positive relationshi p between water temperatures a nd night counts becomes weaker (Woodward and Marion 1979). Murphy (1977) conducte d his research in South Carolina where relative ambient air temperatures are cooler st ill. In the warm south Florida climate, the relationship between water temperature and emer gence rates may be slight. I hypothesized that the relationship between ambient air temperature and emergence rates will be negligible, as reported by Woodward and Marion (1979). Additiona lly, I hypothesized that time spent emerged will show an inverse relationship with wind speed, since submergence is one strategy crocodilians are known to use to seek prot ection from wind (Mazzotti 1989; Pacheco 1996). Relationships between emergence rates and ra in were hypothesized to be negligible, as Woodward and Marion (1979) report ed no significant effect of precipitation on nights counts in their study. Sarkis-Goncalves et al. (2004) reported similar results for Caiman latirostris This study will present an index of alligator emergence behavior in response to the above mentioned environmental predictor variables. The efficiency of the new techniques used in this study will also be evaluated at th e end to determine if they are wo rth repeating in future studies. Materials/Methods Study Area This study was conducted within the Arthur R. Marshall Loxahatchee National W ildlife Refuge (LOX) located in western Palm B each County, Florida (Fig. 2-1). LOX is an approximately 57,324 hectare refuge that represents the northern most extent of the Greater Everglades Ecosystem. LOX is characterized by having a deep layer of peat and organic soil (Richardson et al. 1990; Davis et al. 1994) atop bottom bedrock w ith large areas of open sloughs, wet prairies, and sawgrass stra nds (Richardson et al. 1990). My study site was within the south-

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59 central portion of LOX, an area defined by a relatively stable, year-round hydroperiod, comparatively dense vegetation, a nd a relatively high alligator dens ity (L. Brandt, pers. comm.). Telemetry I used rad io transmitters attached to the pariet als of twenty-eight alligators to investigate emergence rates in this study. Telemetry eq uipment for this study included custom VHF transmitters equipped with conductivity switches used to double the pulses per minute of the broadcasted signal when the transmitter was unde rwater. Transmitters were also designed to broadcast as digital data the proportion of time the transmitter was underwater during the last hour. A fixed antenna and radio receiver were installed at the study site (UTM 17R 0573247, 2926401) and were used to detect and record the status of all deployed transmitters. The receiver was programmed to cycle continuously through all deployed transmitters so that each frequency was searched for and its status was recorded on ce per hour. In addition to the antenna/receiver, a weather station was installed at the study site to record environm ental data. For the purposes of this study, weather data were correlated with em ergence data recorded by a fixed receiver to determine potential relationships between alligator behavior and wa ter and air temperature, rain, and wind speed. Transmitters remained attached for roughly four months, and the study consisted of a 2005 (wet season, July-November, te n alligators) and 2006 (dry season to onset of wet season, April-August, eighteen alligators) field season (See Appendix A for full details of telemetry methodology). Nest Searches Nest searches were also conducted f or every female used in this study. These searches consisted of driving the airboat in parallel transects for approxima tely 0.5 kilometers on all sides of the capture sites of all females. The purpos e of these searches was to obtain nesting information for the Refuge database, but was also relevant for this project because any data

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60 obtained from a nesting female may have biased the results due to altered behavior during nesting. Data Protocols/Management Protocols w ere developed to edit the data so that only accurate and reliable data were used for analysis. Full details on data protocol s and management are in Appendix B. Water depth data were collect ed by the USGS I-9 water gauge located within the study area. Sunrise/sunset tables and moon phase data were obtained using data from the U.S. naval military astronomical observatories at http://aa.usno.navy.mil Only nocturnal data were used since spotlight surveys occur at night. Nocturnal hours were defined as the first and last hours of the night that were characterized by f ull darkne ss, thus excluding the confounding twilight hours. Moon phases were dived into full moon, half-moon, and quarter moon for analyses. Additional environmental data were collected by the weathe r station and included ai r temperature, water temperature, rainfall, and wind. Seasons were divided into calendar spring (from beginning of study season until 20 June 2006), summer (21 June22 September 2005, 21 June23 September 2006, and fall (beginning 23 September in 2005 until end of study season) for both years. I did not investigate wet season versus dry season per se, since the onset of these seasons are variable from year to year. Instea d, I investigated wet conditions versus dry conditions. Data Analysis Data were analyzed using the GENMOD proce dure in the S tatistical Analysis System (SAS 1985). The analysis was essentially a time -series logistic regression (White 1990), where the dependent variable was a binomial response of an alligator being emerged or submerged and the independent or predictor va riables included seas on, time of night, moon phase, water depths, water and air temperature, rain, and wind speed. All analysis was done on an hourly scale. Since two weather readings were record ed every hour, the averages of each variable were calculated

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61 using SAS and these averaged values were used in the analysis. Due to the vastness of the data set (28 animals 24 measurements/day ~120 days ), I used the proportion of total alligators emerged at any given hour to in vestigate patterns of activity. For each alligator, I deleted data collected during the first day post-attachment to account for any erroneous behavior in response to capture and transmitter attachment. Since many transmitters detached before they were collected, a conservative estimate of transmitter detachment time was determined for each animal as the end point for data used in this analysis. This estimate was based on the last collected data points with correct digital IDs and an emerged status. A significant difference in emergence lik elihood among years was apparent in a preliminary analysis of the data. However, each field season was meant to represent different seasons of the year. There were differences in emergence rates between seasons independent of year. Although some overlap existed for summer m onths the data was pooled and analyzed using only seasons, not year s, as covariates. Modeling For m odeling purposes, I modeled the proportion of total telemetered alligators emerged as a function of season, time of night, water de pths, water and air temp erature, rain, and wind speed. An Akaike Information Criterion (AIC) fo r model selection was calculated for each of several models analyzed and was used to determ ine which variables or co mbination of variables create the best approximating model for emergence behavior data (Burnham and Anderson 2002; Pollock et al 2002). AIC penalizes for the addition of pa rameters, and thus selects a model that fits well but has a minimum numb er of parameters. Specifically, AICC values and Akaike weights are used in this pape r to describe competing models A negative relationship exists between AICC value and fit of a competing model to the data (Burnham and Anderson 2002).

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62 In other words, a model with a relatively small AICC value is deemed superior when compared to a model with a larger associated AICC. The Akaike weight of a particular model describes, given the data and the model sets tested, the probability that a part icular model would be the best one to describe the observed data. Model averagi ng was also done to incor porate the strengths of each competing model into a final model that would best describe the data collected. Model averaging allows computation of a weighted aver age of a parameter from the competing models in the model set. By doing so, model selection uncer tainty is included in th e estimate of precision of the parameter (Burnham and Anderson 2002). Testing whether or not individual environmental variables are si gnificant is inherent in the model selection process (Burnham and Anderson 2002). Those environmental variables included in the top mode ls are deemed to be significant in describing the data observed. I was also able to examine the effect of each individual environmental variable on alligator emergence probabilities. Regression coeffi cients, or -values, are used to describe the slope of the regression (Aiken and West 1991). For every unit change in the value of a measured predictor variable, the probabil ity of alligator emergence will change as a product of its associated -value (Aiken and West 1991). As such, -values were used in this study to describe the influence of each individual predictor variable on emergence rates, as based on the final averaged model. For example, variables with positive associated -values will have a positive influence on emergence rates, while variables with negative values will ha ve a negative influence on emergence rates. Levels of categorical variab les such as season, time of night, or moon phase, can be directly compared by comparing their asso ciated -values. If for example the -value for categorical variables x and y are both positive, but the -value for variable x is greater than that of variable y, we can say that variable x has a greater positive influence on

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63 emergence rates, or that alliga tors have a greater ch ance of being emerged under the influence of variable x compared to variable y. Lastly, I randomly extracted 200 lines of data (roughly 10% of the total) and left them out of the analysis. This data was saved for the purposes of testin g model accuracy. Results Twenty-nine final m odels were analyzed (Table 3-1). Model 5 was essentially the main model that incorporated all of the individual parameters tested in this study. Model 1 was determined as the superior model in the model set based on its small AICC value (0) and Akaike weight (0.4133). However, several other models showed relatively close AICC values and Akaike weights, and the final averaged mode l (Table 3-2) accounted for the strengths and weights of all the significant m odels. The effect of water temperature and rain may be minor, as the best model in the set exclude d these variables. The next best three models excluded either water temperature or rain. Co mmon variables found across all significant models based on Akaike weights (> 0.01) included season, wa ter depth, and wind speed (Table 3-1). Based on the regression coefficients (-values) of the final averaged model, it becomes apparent that alligators in this study showed a higher probability of emergence in the spring compared to autumn ( spring = 0.419 > autumn = -0.744) (Table 3-2). Also based on the regression coefficients of the final averaged model, alligators are less likely to be emerged in low moonlight compared to half moon or full moon cycles ( quarter moon = -0.190 < half moon = 0.060, full moon = 0) (Table 3-2). Interestingly, alligators are slightly more likely to be emerged during half moons compared to full moons ( half moon = 0.060 > full moon = 0) (Table 3-2). During nighttime hours, higher water depths decrease the emergen ce rates of alligators ( depth = -0.258) (Table 3-2). Higher water temperatures result in a slightly lower ch ance of emergence ( temp(w) = -0.012) (Table 3-2). During nocturnal hours highe r air temperature results in an increase in

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64 alligator emergence rates ( temp(a) = 0.016) (Table 3-2). Wind speed had a negative effect on submergence rates ( wind = -0.026) as did rainfall ( rain = -0.003) (Table 3-2). The data suggested that the proportion of time spent underwater is a function of the environmental variables tested in this study. My first hypothesis that emergence rates and water depths will show a negative relationship was su pported. My hypothesis that emergence rates will show a positive relationship with levels of m oonlight was only partially supported. In this study, emergence rates were higher during half and full moons compared to quarter moons, but were lower during full moons than half moons. My hypot hesis that time spent emerged as a function of water temperature will show a slight positiv e relationship was not su pported. The results of this study show the opposite trend to be the ca se. The negative relationship between emergence rates and wind speed was supported, and the same trend was discovered for precipitation. The probability of alligator emergence as determined by a given set of environmental variables is based on the -estimate of each variable under the model-averaged model. I was able to generate an equation based on the -values for each parameter multiplied by values for each corresponding parameter as measured in the field during a particular survey. The equation is as follows: P emergence = e intercept + ( Hr1 xHr1) + (Hr2 xHr2) + + ( wind xwind) In this equation, P emergence represents the proportion of alligators emerged. intercept equals the -value for the model averaged intercept (Table 3-2). -values for every environmental variable, drawn from Table 32, are multiplied by values for each equivalent variable as recorded in the fi eld during a survey (X). For ex ample, if during a survey air temperature is measured at 28.5C, that would be entered into the equation as temp(air) X temp(air) or 0.016 28.5 in the equation. For all ca tegorical variables, such as time of night, season, or

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65 moon, enter a for whichever cat egory applies to the survey in question. For example, during spring surveys, one would enter spring* X spring or 0.419 *1 and leave the autumn and summer parameters out of the equation. The end result of the equation is a predic tion of the proportion of alligators emerged during a given survey. Equation Accuracy The accuracy of this equ ation was tested using the lines of data previously set aside. A total of 200 randomly picked observations (53 spring, 80 summer, 67 autumn) were used here. Environmental variables were plugged into the equation, and co mparisons were drawn between the equation-predicted proportion of alligators emerged versus the actual observed proportion of alligators emerged for each line of data. The equation tended to over-predict in the spri ng (Fig. 3-1), and predicted values were higher than observed 77.36% of the time (Table 3-3). The average difference between predicted and observed values in the spring was 32.79% (Table 3-3) A paired two-sa mple t-test for means revealed a significant difference between predic ted proportions emerged and observed proportion emerged in the spring (df = 52, t-stat = -6.42, Ta ble 3-4). 49.05% of the predicted proportions fell within one standard deviation of the observed proportions, while 49.05% of the predicted proportions were greater than one standard deviation over-pre dicted (Table 3-3). The equation was much better at predicting pr oportions of alligators emerged in the summer and autumn (Fig. 3-1). In the summer, the average difference between predicted and observed values was 14.23% (Table 3-3) A paired two-sample t-test for means revealed no significant difference between predicted proportions emerged and observed proportion emerged in the summer (df = 79, t-stat = -0.16, Table 3-5) 61.25% of the predicted proportions fell within one standard deviation of the observed proportions (Table 3-3). 18.75% of the predicted proportions were greater than one standard deviation over-predict ed, while 20% of the predicted

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66 proportions were greater than one standard deviation of the observed proportions under-predicted (Table 3-3). In autumn, a paired two-sample t-test for means revealed no significant difference between predicted proportions emerged and obs erved proportion emerged (df = 66, t-stat = -0.59, Table 3-6). 52.23% of the predicted proportions fell within one standard deviation of the observed proportions, 26.88% of the predicted pr oportions were greater than one standard deviation over-predicted, and 20.89% of the predicte d proportions were greater than one standard deviation under-predicted (Table 3-3). Discussion Equation Accuracy The predictive equation was not as accurate in the spring and consistently over-predicted proportions of alligators em erged (Table 3-3). Additionally, the equation did not seem to account for the observed variation in emergence rates as well in the spring as it did in the summer and fall (Fig. 3-1). Alligators were submerged more often than would be expected based on environmental variables alone. To explain these fi ndings, I suggest that so me other variable or variables that were not measured in this study were effectively overriding the expected influence of the surrounding environment. The fact that th e breeding season of alligators occurs in spring may account for this unexpected behavior, since mo st social interactions of alligators occur underwater (Vliet 1987). Social interactions of alligators are al so known to take precedence over behaviors that may represent an optimal response to environmental conditions (Asa et. al. 1998). As a result of these findings, managers may opt to conduct alligator surveys in the summer and fall as opposed to the spring and fall as is the current practice. Conducting surveys in the summer and fall will allow for better populati on estimates after adjusting survey results via the equation presented in this paper.

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67 Seasonal Activities Based on regression coefficients (-values) of the final averaged m odel, it becomes apparent that alligators in this study showed a higher probability of emergence in spring compared to autumn ( spring = 0.419 > autumn = -0.744) (Table 3-2). Alligator surveys in south Florida should take into account the trend that alligators seem to spend less time emerged in autumn compared to spring, at le ast in interior marsh habitats. Alligator managers may find that more alligators are counted duri ng spring surveys than fall surveys as a result of natural alligator behavior. It is recommended that alligator managers calibrate the results of their seasonal surveys to account for the naturally occurring differe nce in emergence rates across seasons. The generated equation accounts strongl y for this seasonal trend in em ergence rates and can be used for such a calibration. Managers should use cau tion however before applying such a calibration to canal surveys, as canal alligator dynamics may not mirror those in interior marshes. Time of Night Based on the regression coefficien ts (-values) generated in th is study, it was apparent that conducting surveys within the first ho ur of night, as is the case in current survey protocols, will coincid e with a slightly negative alligator emerge nce rates (Table 3-2). Interestingly, emergence rates decrease to a maximum low during the second full hour of dar kness (Table 3-2). In order to maximize alligator counts, surveys would have to begin around or after midnight and continue into the early morning hours when emergence rate s begin to rise. As this option may be more difficult for researchers, it is recommended that al ligator surveys in south Florida continue to occur immediately following sunset, but it is advi sable to limit surveys to one per night if possible to avoid a time-related bias in the results. Alternatively, for surveys expected to run for approximately one hour then it is recommended they take place in the early hours of night, as per current protocol. For surveys that might run in excess of two or thre e hours it is recommended

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68 that they begin later in the night perhaps beginning at the third hour of darkness, in an attempt to decrease a time-related bias in results. Caution must be exercised before applying th ese results outside of adult size classes. Alligator body temperatures are probably highe r in the early hours of night, or those hours immediately following daylight hours when alliga tor body temperatures are highest. Alligators likely lose heat consistently th roughout the night, as this tren d has been described in other crocodilians (Wright 1987; Seebacher et al. 2005). Larger crocodilians lose heat at a slower rate compared to smaller crocodilians and have comparatively more stable body temperatures than smaller individuals (Wright 1987). Often, as surv eys or other alligato r research activities progress into the night, larger individuals appear to dominate the alligator sightings (Dr. K.G. Rice, pers. comm.). My results s upport this observation, as the adu lt alligators used for this study showed increased emergence later on in the night. This may not be the case for smaller individuals, who may be more likely emerged in the early hours of night before their body temperatures start to drop. The possibility exists that conducting surveys at different times of night may introduce biases in both absolute numbers and in size classes observed. Moon Phases A wide range of results are reported f or cr ocodilian reactions to moonlight. Woodward and Marion (1979) found a positive correlation betwee n alligator counts and levels of moonlight during warm weather. Larriera and Del Barc o (1992) found no correlati on between moon phase and night counts in Caiman latirostris Sarkis-Goncalves et al. ( 2004) report that moonlight negatively influenced night c ounts in their study involving Caiman latirostris Alligator emergence rates in this study began to increase with increasing lunar li ght, but decreased during full moons. These results somewhat agreed wi th results reported by Woodward and Marion

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69 (1979). Moonlight may stimulate alligators to increase their activity (Woodward and Marion 1979), but very high levels of light ma y influence a decrease in activity. Alligator managers in south Florida should take this positive relationship into consideration when conducting surveys. Surveys conducted during moonlit nights may maximize alligator detectability in south Florida. However, manage rs should exercise caution before applying these results, as data taken from this study occurred in the absence of researcher presence. Increased moon light may create a situation in which the observers themselves are more readily detected by the crocodilians, which in turn re act by diving or hiding (SarkisGoncalves et al. 2004). Even though relatively mo re animals may be surfaced at any given point in time under increasing lunar light, observer pres ence itself may compromise this response. Eyeshine may also be more readily detected in darker conditions, resul ting in greater counts in spite of decreased emergence pr obabilities (Sarkis-Goncalves et al. 2004). It is strongly recommended that the relationship between detect ability and darkness shoul d be tested further. However, it may be possible that Caiman latirostris and Alligator mississippiensis simply exhibit different behavioral responses under the influence of lunar light. Water Depths During nighttime hours, higher water depths de creased the emergence rates of alligators. Since the highest water depths gene rally coincide with the hottest parts of the year, this may be related to the thermal regime of south Florida alligators as previously discussed. Alligator managers may increase night counts in south Florida during times of relatively low water. This generally occurs in the spring, where alligators are more likely to be emerged as previously discussed. Based on the results of this study, c onducting fall surveys during years of unusually low water might result in higher alligator counts.

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70 It becomes difficult to tease out the effects of varying water depths independent of season. Even by correcting for water depth, other season ally dependent variables such as photoperiod and prey availability are not acc ounted for. In order to truly u nderstand the relationships between these two variables, this study would need to be repeated in years where water depths are exceedingly high or exceedingly low in spite of se ason, and results then need to be compared. As a general trend in current alligator survey s, more individuals are recorded in canal habitats rather than marsh habitats. Canal habita ts have a relatively higher occupancy in south Florida, especially by larger ad ult alligators (Mazzotti and Bra ndt 1994; Rice et al. 2005). This difference in density may be less than it seems, as our data sugg est that alligators may spend more time submerged as water depth increases. In addition, detectability may increase in the relatively open habitat that is characteristic of canals. This point illustrates importance of determining the relationship between different asp ects of detectability (behavioral vs. observer biases). Alligators may also select for different habitats (open vs. vegetated) as water depths rise. If this were the case, alligator detectability to observers is determined by more than emergence behavior. For this reason it is strongly reco mmended that the result s from this study be interpreted in conjunction with information regard ing habitat selection before being fully applied to alligator surveys. Water and Air Temperatures During nocturnal hours, alligators in this study were less likely to be em erged with higher water temperatures. Conversely, Woodward and Ma rion (1979) reported that in their northcentral Florida study, alligator night counts were positively correlated with water temperatures during cooler weather. During relatively warmer weather, co unts were unaffected by water temperature. Based on these results, alligators seem to show a greater response to high water temperatures in relatively cooler ambient air temperatures in terms of activity. Woodward and

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71 Marion (1979) and Murphy (1977) report that when looking at a plot of night counts versus water temperature, a scattering of responses occu rred as water temperature exceed 28C. In this study, a similar scattering of points occurred throughout the study at all wa ter temperatures (Fig 3-2). The apparent scattering of plots is reflectiv e of the fact that water temperatures had only a slight negative effect on submergence. Alligators in this study were more likely to be emerged with higher air temperatures. However, Woodward and Marion (1979) reported that air te mperature had no bearing on alligator night counts, since water generally acte d as a buffer between the air and the alligator. Woodward and Marion (1979) did however suggest a positive correlation between number of alligators detected and maximum daily temperatur e. Hutton et al. (1989) reported similar results for Crocodylus niloticus and Pacheco (1996) reported similar results for Melonosuchus niger. Sarkis-Goncalves et al. (2004) also reported that ambient temper ature did not influence night counts in their study involving Caiman latirostris I would hypothesize that in the south Florida summer, when nocturnal air temperatures are at their highest, alligators are thermally stressed during the day and will emerge at higher rates at night to release excess heat in the relatively cooler air (Mazzotti 1989). In regards to alligator surveys, alligator managers in south Florida might opt to conduct surveys during particularly warm nights, and woul d probably do best to survey on nights where both air temperatures and water temperatures are particularly high based on the results of this study. It should be noted that although alligators are endothermic, thermoregulation is not always the driving force that determines alligator beha vior (Mazzotti 1989; Asa et al. 1998). Since all crocodilians have the ability to decrease pe ripheral blood circulation and heat flow through bradycardia and vasoconstriction to conserve heat, alli gator thermoselection may take a backseat

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72 to other natural behavior includ ing underwater foraging/feeding a nd social interactions (Mazzotti 1989; Asa et al. 1998). Larger, more dominant indi viduals may even force smaller individuals to engage in suboptimal behavior (Asa et al. 1998) in much the same way they force less dominant individuals to inhabit a less de sirable physical habitat (Mazzotti and Brandt 1994). Such social dynamics have been reported in captive alligators in which a dominant female alligator forced smaller females out of the relatively warmer water (>20 C) onto land where air temperatures were much cooler (3-7.9 C) and certainly sub-optimal (Asa et al. 1998). Rain Woodward and Marion (1979) reported no relationship betw een night counts and precipitation, although sufficient data were lack ing. Sarkis-Goncalves et al. (2004) report that rain did not influence nights counts in their study involving Caiman latirostris All else being equal, the presence of rainfall in this study resulted in a steep decline in th e proportion of alligators and a close negative re lationship is apparent between ra in and emergence rates in this study (Fig. 3-3). Alligator managers might consid er not conducting surveys during rain at any intensity. Even during just 1 cm /hr of rain the maximum proporti on of alligators emerged based on the results of this study was 60% (Fig. 3-3). Af ter a rain intensity of 3cm/hr or more, a very small proportion of alligators are likely to be emerged and available for counting. Rain might have been of little importance in de scribing emergence behavior of alligators in this study. Apart from rain, the influence of cl oud cover needs to be addressed and how may interact with lunar phases. Rainfall means cloud cover, but cl oud cover may occur without rain and this was not accounted for in the study. Pachec o et al. (1996) report that cloud cover had a consistent negative effect on Melanosuchus niger night counts. Alternatively, Woodward and Marion (1979) report that cloud co ver had a significant positive relationship on night counts in

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73 cool weather. Whether or not this relationship would hold in the relatively warm south Florida climate is unknown. Wind That wind affects alligator em ergence probabi lities is not unusual. Crocodilians seek protection from wind mainly by submerging, or by using lee shores (Mazzotti 1989; Pacheco 1996). In agreement with the results from this study, wi nd speed had a strong negative correlation on Melanosuchus niger night counts (Pacheco 1996). Alternatively, SarkisGoncalves et al. (2004) report th at wind did not influence nights counts in their study involving Caiman latirostris. When wind speeds approach 10 km/hr, the prop ortion of alligators emerged begins to steadily decline (Figure 3-4). Alligator surv eys in south Florida are recommended to be postponed in the presence of excessive wind speeds due to researcher safety and a decreased likelihood of alligator emergence. Implications and Future Work I advocate that this study warrants repetiti on and urge other alli gator biologists to consider implem enting a similar project. A repe ated study of similar design is suggested for locations in north Florida and/or another northern part of the alligators range for comparison. This would also enable researchers to documen t whether any behavioral shifts occur across alligator populations as a function of latitude. A repeated stud y would also offer a comparison between alligators of varying body condition. A repe ated study in various compartments in the Everglades is strongly suggested to address the influence of water depths on behavior independent of season. Wariness is known to occur in crocodilians exposed to hunting, repeated capture, or repeated human presence (Spratt 1997; Pacheco 1996). In future studies researcher presence

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74 could be independently tested as a predictor va riable for emergence to determine levels of wariness in different alligator popu lations. Moreover, an investigation of sex-specific response to researcher presence may yi eld interesting results. Also, it should be noted again that this study dealt only with adult alligators. Alligator surveys do not discriminate between size classes as I did when selecting alligators for transmitter attachment. It is very important to stress that the responses of adult alligators to various environmental factors may not mirror the responses of juvenile or hatchling alligators, so care must be taken when applying the results of this study to adjusting surveys results. It is recommended that alligator surveys adjust thei r results only among the adult animals counted. Other studies are currently underw ay that are looking into det ectability of alligators in varying degrees of vegetation cover and habita t types characterized by different levels of visibility (Cameron Carter, pers. comm.). It is strongly recommended that the results from this study are used in conjunction with habitat visi bility estimates. The Global Positioning System (GPS) represents a technology that will prove ex tremely useful for wildlife studies involving animal behavior and is rapidly evolving in regards to form and function (Fedak et al 2002). GPS transmitters are currently being developed and test ed that will eventually allow researchers to uncover the fine scale habitat pref erence of adults and sub-adult a nd juvenile alligators, as these different age-classes tend to pa rtition available hab itat perhaps at a fine scale (Mazzotti and Brandt 1994). In the future, models of detection that incorporate emergence, habitat visibility, and habitat preference of alligators will allow ma nagers to incorporate actual population levels and not indices into their monitoring programs.

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75 Table 3-1. The AICC and Akaike weights of models used to describe the emergence dynamics of Arthur R. Marshall Loxahatchee National Wildlife Refuge alligators. Model Model Variables AICC Akaike Weight 1 Hour, season, moon, depth, wind 0 0.4113 2 Hour, season, moon, depth, temp(a), wind 0.951 0.2556 3 Hour, season, moon, depth, temp(w), temp(a), wind 1.261 0.2189 4 Hour, season, moon, depth, temp(a), wind, rain 3.83 0.0606 5 Hour, season, moon, depth, temp(w), temp(a), wind, rain 4.162 0.0513 6 Hour, season, depth, temp(w), temp(a), wind 11.898 0.001 7 Hour, season, depth, temp(a), wind 13.608 0.0004 8 Hour, season, depth, temp(w), temp(a), wind, rain 14.406 0.0003 9 Hour, season, depth, temp(a), wind, rain 16.159 0.0001 10 Hour, season, depth, wind 16.592 0.0001 11 Hour, season, depth, temp(w), temp(a), rain 33.173 0 12 Hour, moon, depth, temp(a), wind 74.469 0 13 Hour, moon, depth, temp(w), temp(a), wind 75.372 0 14 Hour, moon, depth, temp(a), wind, rain 77.152 0 15 Hour, moon, depth, temp(w), temp(a), wind, rain 78.092 0 16 Hour, moon, depth, wind 81.568 0 17 Hour, season, moon, wind 152.503 0 18 Hour, season, temp(w), temp(a), wind 152.75 0 19 Hour, season, moon, temp(w), temp(a), wind 153.377 0 20 Season, moon, depth, wind 155.59 0 21 Hour, season, moon, temp(w), temp(a), wind, rain 156.267 0 22 Hour, season, moon, temp(w), temp(a), wind, rain 172.652 0 23 Hour, depth 182.238 0 24 Hour, season 280.878 0 25 Hour, temp(w) 462.729 0 26 Hour, temp(a) 568.765 0 27 Hour, wind 578.891 0 28 Hour, moon 599.274 0 29 Hour 703.031 0 AIC values of < 2 generally suggest substantial evidence for the model. Values between 3 and 7 indicate that the model has considerably less support, and values > 10 indicates that the model is highly unlikely. Akaike weights indicate the probability that the model is the best among the whole set of candidate models.

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76 Table 3-2. Regression coefficients ( -values) and associated confidence intervals of the averaged model used to describe the emergence dyna mics of Arthur R. Marshall Loxahatchee National Wildlife Refuge alligators. Parameter -VALUE Lower 95% CI Upper 95% CI Intercept 3.28 -6.605 13.965 Hr1 -0.007 -0.276 0.261 Hr2 -0.187 -0.353 -0.020 Hr3 -0.067 -0.229 0.094 Hr4 0.000 -0.000 0.000 Hr5 0.105 -0.059 0.271 Hr6 0.010 -0.161 0.181 Hr7 0.095 -0.076 0.268 Hr8 -0.037 -0.215 0.140 Hr9 0.025 -0.293 0.344 Autumn -0.744 -0.917 -0.571 Spring 0.419 -0.068 0.907 Summer 0.000 0.000 0.000 Moon (quarter) -0.190 -0.348 0.032 Moon (half) 0.060 -0.066 0.188 Moon (full) 0.000 0.000 0.000 Water depth -0.258 -0.882 0.365 Temp (water) -0.012 -0.052 0.028 Temp (air) 0.016 -0.021 0.053 Rain -0.003 -0.026 0.020 Wind -0.026 -0.039 -0.013 *Intercept describes the slope of the regression. Hr1-Hr9 describes the time of night after sunset. Parameters with -values of 0 serve as baseline measurements from which comparative values are drawn.

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77 Table 3-3. Summary of the differences between equation-predicted pr oportion (P) and actual observed proportion (O) of alligators emerge d at Arthur R. Marshall Loxahatchee National Wildlife Refuge in 2005-2006. overall spring summer autumn Mean difference between P and O 0.1987 0.3279 0.1423 0.1638 Standard Deviation of Observed (SDO) 0.2293 0.2529 0.1765 0.1753 Maximum overprediction P= 0.8221>O P= 0.8221>O P= 0.3688>O P= 0.4655>O Maximum underprediction P= 0.3563
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78 Table 3-4. Results of a paired two-sample t-test for spring predicted vs. observed proportion of alligators emerged at Arthur R. Marsha ll Loxahatchee National Wildlife Refuge in 2005-2006. Observed Predicted Mean 0.4803043920.748249448 Variance 0.0639733510.014640959 Observations 53 53 Pearson Correlation -0.222545329 Hypothesized Mean Difference 0 df 52 t Stat -6.422931976 P(T<=t) one-tail 2.056E-08 t Critical one-tail 1.674689154 P(T<=t) two-tail 4.112E-08 t Critical two-tail 2.006646761

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79 Table 3-5. Results of a paired two-sample t-test for summer predicted vs. observed proportion of alligators emerged at Arthur R. Marsha ll Loxahatchee National Wildlife Refuge in 2005-2006. Observed Predicted Mean 0.3489024860.352117461 Variance 0.0311796620.0064734 Observations 80 80 Pearson Correlation 0.251546696 Hypothesized Mean Difference 0 df 79 t Stat -0.164638953 P(T<=t) one-tail 0.434824353 t Critical one-tail 1.66437141 P(T<=t) two-tail 0.869648706 t Critical two-tail 1.990450177

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80 Table 3-6. Results of a paired two-sample t-test for autumn predicted vs. observed proportion of alligators emerged at Arthur R. Marsha ll Loxahatchee National Wildlife Refuge in 2005-2006. Observed Predicted Mean 0.1842632080.198132228 Variance 0.0307336430.003998431 Observations 67 67 Pearson Correlation -0.092450092 Hypothesized Mean Difference 0 df 66 t Stat -0.591925269 P(T<=t) one-tail 0.277961473 t Critical one-tail 1.668270515 P(T<=t) two-tail 0.555922946 t Critical two-tail 1.996564396

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81 Figure 3-1. Relationships between observed and pr edicted proportions of al ligators emerged at Arthur R. Marshall Loxahatchee Nati onal Wildlife Refuge, 2005-2006. Jagged lines indicate actual values. Sm oothed lines indicate polynomial trend lines. Observation numbers 1-53 represent springtime ob servations. Numbers 54-134 represent summertime observations, and numbers 135-200 represent autumn observations. 0 0.2 0.4 0.6 0.8 1 1.2 1100 199 Observation numbe r Predicted Observed Proportion emerged

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82 Figure 3-2. Relationships between water temperature ( C) and proportion of alligators emerged at Arthur R. Marshall Loxahatche e National Wildlife Refuge, 2005-2006. The scattering of responses and lack of apparent relationship between emergence and water temperature agree with findings re ported by Woodward and Marion (1979) and Murphy (1977).

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83 Figure 3-3. Relationships between rainfall (cm/hr) and proportion of alligators emerged at Arthur R. Marshall Loxahatchee Nati onal Wildlife Refuge, 2005-2006.

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84 Figure 3-4. Relationships between wind speed (km/hr) and proportion of alligators emerged at Arthur R. Marshall Loxahatchee National Wildlife Refuge, 2005-2006.

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85 CHAPTER 4 CONCLUSIONS South Florida is characterized by consistent high tem peratures and can be a climatically challenging environment for American alligato rs (Jacobsen and Kushlan 1989; Dalrymple 1996; Barr 1997; Howarter 1999). In addition to natural stressors, much of the original Everglades ecosystem has been spatially reduced, drained, an d irreversibly lost as a result of extensive landscape alterations for agricu lture, development, and flood c ontrol (Jacobsen and Kushlan 1984; Simmons and Ogden 1998). Once natura l hydrological fluctuations are now anthropogenically influenced or controlled. Allig ators are especially sensitive to fluctuating water levels both spatially and temporally (Maz zotti 1989; Kushlan and Jacobsen 1990; Mazzotti and Brandt 1994). In the Everglades ecosystem, a balanced alligator popul ation is dependent on appropriate seasonal water availability, especially in an environment such as the Everglades. Alligators are a top conservation concern in the Everglades ecosystem as they can serve as indicators of ecological balance and measure of restoration success (R ice et al. 2005). The alligators natural sensitivity to fluctuating water levels, as well as their sensitivity to overall system production as top predators makes them ideal candidates for adaptive management (Mazzotti and Brandt 1994; Rice et al. 2005). Since the success of many other species is dependent on a balanced alligator population, alligato rs throughout south Florida are monitored closely as Everglades restoration advances. I first set out to investigate patterns of th ermoregulation by correlating alligator emergence behavior and circadian rhythms to season, solar radiation, and water depths in the south Florida environment. I hypothesized that since the sout h Florida climate undergoes an annual transition between a low cost and high cost environment, then alligators will exhibit behavior patterns that reflect active heat-s eeking thermoregulation in the spring, and to conversely exhibit behavior that

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86 reflects no active thermoregulation or heat-avoidance in the summer and fall. I also examined the effects of size, sex, and body conditi on on alligator emergence rates. All models indicated a higher probability of em ergence in the spring compared to that of the fall. Springtime solar radiation had a positiv e affect on emergence pr obabilities. This trend suggested that alligators exhibit behavior patterns that reflect a low cost environment in the spring in south Florida as they seem to show active heat-seeking thermoregulation at this time. Alligators in south Florida may have no problems in achieving optimal temperatures in the spring through increased behavioral thermoregulati on, as they seem to seek solar radiation and are highly active through the ni ght. The results of this st udy supported my hypothesis that alligator thermoregulatory behavi or reflects an environmental tr ansition. However, other natural behaviors besides thermoregulation could also help explain these results. The difference in emergence rates may also be influenced by soci al behavior, foraging behavior, or photoperiod. Larger alligators showed a higher degree of heat avoidance in the summer and spent less time emerged than smaller individuals in this study. Although the sample size was relatively small and all alligators were adults, the sma ller individuals in the study were more likely emerged at any given point in time compared to the larger individuals in the study during the months of June and July, reflecting the fact that smaller individuals are better able to disperse excess heat (Wright 1987). Body condition also ha d an effect on emergence rates as higher body condition scores, presumably healthier individuals showed increased rate s of emergence. This result suggests a higher heat tolera nce of relatively robust alligators. It has been suggested that al ligators in south Florida require a sufficient level of standing water to escape the intense heat during the summ er and fall (Howarter 1999; Percival et al. 2000; Abercrombie 2002). If water depths are too low during these hot months, one could argue that

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87 there may be an added benefit of greater food con centration. This may not be the case, as aquatic prey species densities are generally low fo llowing prolonged dry downs (Loftus and Eklund 1994; DeAngelis et al. 1997). The Everglades ec osystem is primarily a rain-fed wetland and hydroperiod is naturally determined by patterns of precipitation. Springtime in the Everglades is generally characterized by drought, and if the drought extends through summer and fall then fish densities are known to decline and may require years to recover (Loftus and Eklund 1994; DeAngelis et al. 1997). In other words, aquatic prey species may not be able to adjust to prolonged unnatural seasonal conditions. Even if prey was sufficiently available during a summer drought, alligators may still be confined to inactivity and heat avoidance in south Florida and would therefore be unable to take advantage. Relatively lower water depths in the spri ng are recommended as alligators can take advantage of the increased benefits of concen trated aquatic food resources during natural dry downs and build energy reserves for the summer. Ambient temperatures are also less intense at this time and would probably allow less thermal constraints. Lower wate r depths also provide adequate nesting sites for females (Mazzotti 19 89; Kushlan and Jacobsen 1990; Mazzotti and Brandt 1994). Understanding alligator responses to differences in seasonal conditions allows managers to better understand potential responses to altern ate restoration actions in the Everglades. Anthropogenically controlled water regimes in the Everglades must take into account the ecology of the ecosystems top predator. Not only are variations in water depth known to affect courtship, nesting, growth and survival (Gar rick and Lang 1975; Vliet 1987; Kushlan and Jacobsen 1990; Mazzotti and Bra ndt 1994), but they may also ha ve negative impacts on other behavioral adaptations of American alligators reflected by shifts in thermoregulatory behavior.

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88 Understanding the thermal ecology of the Ameri can alligator in south Florida will allow managers to make more informed decisions rega rding habitat restorati on. This information can also be practically applied to improve efficacy of south Florida alligator surveys. The second objective of this research was to improve alligator survey methods within the south Florida alligator survey network. Specificall y, I investigated alligator emergence behavior and how it relates to a variety of environmental variables known to have an effect on crocodilian behavior. These include season, air and wate r temperature, moon phase, rain, and wind (Woodward 1979; Mazzotti 1989; Pacheco 1996; Woodw ard et al. 1996; Sarkis-Goncalves et al. 2004). The ultimate goal was to develop estimates of alligator detectability that alligator managers can use to correct their survey results in an appropriate manner to account for missed individuals (Steinhorst and Samuel 1989). In this study, alligators spen t roughly two thirds of their time submerged. Compared to spring and fall, alligators were less likely em erged at any given time during summer. Compared to summer months, alligators in the autumn are only slightly more often emerged during nighttime hours. Alligators are less likely emerged in low moonlight compared to half moon or full moon cycles. In addition, alligators are slig htly more likely emer ged during half moons compared to full moons. During nighttime hours, higher water depths decreased the emergence rates of alligators. Higher water temperatures result in decreased emergence rates, while higher air temperature results in increased emergence rates. I found that the best time for conducting surveys is in low wind, in half or full moon phase s, and on clear, cloud-free nights with relatively high air and water temperatures and relatively lower water depths. Regardless of conditions, an equation was generated that allows managers to adjust their survey results to account for variations in detectability due to natural be havior. Although the equatio n successfully predicted

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89 alligator emergence rates in the summer and fall, it lost much of its predictive ability in the spring. I suggest that some other variable or vari ables that were not measured in this study were effectively overriding the expected influence of the surrounding environment. The fact that the breeding season of alligators occurs in spring may account for this unexpected behavior, since most social interactions of alligators occur underwater (Vliet 1987). Social interactions of alligators are known to take precedence over behavi ors that may represent an optimal response to environmental conditions (Asa et. al. 1998). This research can be used by alligator managers to reduce the amount of time needed to detect significant changes in al ligator populations as they respond to different restoration actions, thus allowing managers to quickly recognize and respond to a resulting positive or negative population trend. I argue that this study warrants repetition and urge other alligator biologists to consider implementing a similar project in other habitats and locations A repeated study of similar design is suggested for locations in north Florida and/or other mo re northern regions of the alligators range for comparison. This would al so enable managers to document whether any behavioral shifts occur across alligator populatio ns as a function of latitude. A repeated study would also offer a comparison be tween alligators of varying body condition and relative health. A repeated study in various compartments in the Ev erglades is suggested to address the influence of water depths independent of season. Researche r-induced wariness should also be examined, as is a study on age/size related fine scale habitat preference. I strongly r ecommend that the results from this study are used in conjunction with habitat visibility estimates. Combining emergence data with habitat detectability variables and habi tat preference of alligators will allow mangers to more quickly detect population changes in response to Everglades restoration. Eventually, as this

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90 type of research advances, alligator managers w ill be able to incorporat e actual population levels and not indices into their monitoring programs.

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91 APPENDIX A METHODOLOGY During night-light surveys, the probability of alligator detecti on by researchers is a function of observer efficacy, habi tat, alligator wariness due to airboat/hum an presence, and natural variation in behavior (Graham a nd Bell 1969; Murphy 1977; Brandt 1989; Woodward and Linda 1993). This study focused on the latter and was carried out to develop estimates of emergence probabilities of alligators during survey s as they relate to various weather-related environmental factors (the probability that an animal is above the water surface and thus available for detection). Radio telemetry was chosen as a means to investigate alligator emergence behavior. This paper presents the method of transmitter attachment used for this study. Telemetry has been a common approach to studying crocodilian behavior (Joanen and McNease 1970; Joanen and McNease 1972; McNease and Joanen 1974; Taylor et al. 1976; Kroll 1977; Murphy 1977; Goodwin 1978; Deitz 1979; Goodwin and Marion 1979; Muller 1979; Rodda 1984; Magnusson and Lima 1991; Barnett et al. 1997; Addison et al. 1998; Fergusson 1998; Cadi et al. 2002; Morea et al. 2000; Munoz and Thorbjarnarson 2000). Telemetry equipment for this study included custom VHF transmitters (6.0 cm in length, 3.5 cm in width, 2.5 cm in height, 65 grams in weight) equipped with water conductivity se nsors. These sensors effectively switched the signal ou tput from thirty pulses per minute while emerged to sixty pulses per minute while submerged. Battery life for all transmitters was approximately four months. A fixed antenna and solar powered radio receiver were installed at the study site (UTM 17R 0573247, 2926401) and were used to detect a nd record the status of all deployed transmitters. The receiver was programmed to cycle continuously through all deployed transmitters so that each frequency was sear ched for once per hour. In addition to the

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92 antenna/receiver, a weather station system was inst alled at the study site. Fo r the purposes of this study, weather data were correlated with emerge nce data to determine potential relationships between alligator emergence a nd environmental variables. In this study, transmitters were attached using the parietal/squamosal ridges as the attachment point. To investigate emergence behavi or, all instances when an alligators head is surfaced must be recorded. Since a surfaced alligator may only expose its eyes and nostrils, the logical place to attach transmitters while properl y utilizing the conductivity sensors was on top of the parietal. An extensive search of pertinent publications revealed that standard methods of transmitter attachment to crocodilians as described in several previous studies were essentially insufficient for the purposes of this project. Mo st studies involved surgical implantation of transmitters (Asa et al. 1998; Barnett et al. 1997; Brisban and Standora 1982; Hocutt et al. 1992; Morea et al. 2000), attachment of transmitters to the tail (Munoz and Thorbjarnarson 2000), attachment of transmitters with neck collars (Addison et al. 1998; Fergusson 1998; Joanen and McNease 1970, 1972; Rootes and Chabreck 1993) and attachment of transmitters to nuchal scutes (Kay 2004; McNease and Joanen 1974; Taylor et al. 1976). Tethering a buoyant transmitter (Rodda 1984) was also deemed insufficie nt, as the aquatic habitat at the study site was highly vegetated and would leave the tran smitter prone to be hung up underwater, resulting in an inaccurate representati on of alligator emergence. Twenty eight alligators were captured using snare poles and spotlights as described by Chabreck (1963). All alligators were >2 m in total length in orde r to accommodate the procedure. Measurements were taken from all animals captured including total length, head length, snout-vent length, tail gi rth, sex, and weight. Prior to su rgery, captured alligators were physically restrained using rope and/or duct tape to bind the legs and secure the animal to a

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93 wooden board. Duct tape was placed over the ey es to inhibit vision and reduce stress. All surgical procedures were performed in the field, aboard an air boat, to minimize time and stress on the animals. Methods were consistent with those described and approved by University of Florida IACUC proposal #D943. Surgical items included one six-ounce jar of Li docaine Hydrochloride (local anesthesia), 3 ml injection needles, one battery-op erated Dremel 10.8V Lithium-ion cordless drill ( www.dremel.com ) with two f ully charged drill battery packs, several spools of 16-gauge surgical grade steel wire, pliers, a cigarette lighter, saline solution, co tton balls, rubber gloves, Betadine scrub and Betadine solution (disinfe ctant), and several 15-ounce containers of Devcon 5-minute epoxy (www.devcon.com). Dril l bits, steel wire, and the transmitters themselves were sterilized with 95% rubbing alc ohol prior to alligator ca pture. Drill bits and steel wire were also sterilized with fire from th e lighter. Drill bits were re-sterilized after use on each animal in the study. After sterilization, all of these items were placed in individual plastic bags and stored in a water-ti ght container on the airboat. After initial capture alligators were loaded onto the bow of the airboat where they were secured. Once secured, the craniu m was thoroughly cleaned usi ng 95% rubbing alcohol followed by Betadine disinfectant scrub a nd Betadine disinfectant solution. After cleaning, 2-3 ml of 2% Lidocaine Hydrachloride was administered via several injections around the perimeter of the surgical site. After approximately five minutes, four small holes were drilled into the parietal/squamosal ridges using a 3.175 mm drill b it; two holes either side. Saline solution was applied liberally to the bit and tissue during dr illing to prevent the drill bit from overheating which results in tissue damage. Once the hol es were established, Lidocaine was again administered inside the new holes and was dually used to flush out loose material left over from

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94 drilling. The new holes were disinf ected with Betadine solution to ensure that infection will not set it as a delayed response to transmitter attachment. Four separate lengths of steel wire were woven through the drilled holes a nd twisted with pliers to secure their placement (Fig. A-1). At this point, holes were filled with common household superglue to eliminate any free space between the wire and the bone. Devcon br and 5-minute epoxy (www.Devcon.com) was then applied to both the parietal skin, where the transmitter will rest, and to the underside of the transmitter itself. The transmitter was then put in place and held tightly for five minutes while the epoxy hardened. Two lengths of steel wire, prev iously epoxied to the transmitter, were then twisted around the other four lengths of wire to secure the tran smitter in place (Fig. A-2). After the first layer of epoxy set, a se cond layer was applied dorsally to enclose the transmitter and wires and reinforce the attachment. Care was taken not to enclose th e conductivity sensors during this final step. After a full cure time of approximately twenty minutes the attachment procedure was complete and the alligator was rele ased at its original point of capture. Since Lidocaine is a local anesthetic the alligators may be released before the effects wear off completely. The entire time from capture to re lease was typically less than ninety minutes. Devcon brand 5-minute epoxy was chosen as the best overall brand of epoxy for this research as determined by a series of performance tests of several name-brand glues and epoxies (Table A-1). In this experiment, model transmitte rs equipped with eyehooks were glued to the parietals of deceased farm-raised alligators. Adhesives were allowed to cure for a full 120 minutes, or the maximum desirable amount of time to spend on each individual alligator in the field for the attachment procedure. Both the mo del transmitters and the parietal region were thoroughly cleaned using 91% rubbing alcohol prior to testing. A 20 kg spring scale was attached to the eyehook on one end and a standard workbe nch vice on the other. As the vice was cranked

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95 the scale was used to measure the exact amount of pressure needed to detach the model transmitter from the parietal. The results of expe riment indicated that liquid glues and epoxies tended to perform better than malleable clay ep oxies in ability to bond to skin tissue. Devcon was selected for both its quick cure time and st rength of hold. Devcon has been used to attach transmitters in other studies as well (Boarman et al. 1998; Stokes and Boersma 1999; Reidel et al. 2003). Transmitters remained attached for a period of three-four months and were recovered where they were shed. Some alligators retained their transmitters and needed to be recaptured (Table A-2). Transmitters are shed as the bone sl owly recedes away from the wire over time, and the wire effectively works its way through the bo ne until the transmitter is detached, usually within four months. This natu ral detachment will leave four grooves in the parietal/squamosal ridges, but in no cases did I observe any signs of infection associated with these grooves. A captive specimen on which this procedure was perfo rmed was left with only slight scarring as a long-term effect of transmitter detachment. The effect of capture and transmitter attachment on behavior was thought to be mini mal based on observations of one of the study animals. On one occasion, a large male was originally observed bello wing with head and tail elevated out of the water in a social display. This individual was captured and fitted with a transmitter, and was the first individual of three captured that particular night. After an elapsed time of approximately four hours, this alligator was observed again in the exact place of capture, seemingly unaffected by the procedure as it had resumed bellowing with head and tail elevated out of the water. Post removal inspections of all recaptured animals rev ealed no signs of infection or necrosis as a result of transmitter attachment. Several of the study animals were excessively thin and may

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96 have been immuno-compromised; still none of the study animals showed any ill effects as a result of this procedure (Fig. A-3). The above described methodology was developed to suit specific objectives and is only recommended for similar studies on crocodilian em ergence rates. The majority of crocodilian telemetric studies utilize standard VHF or G PS transmitters to answer questions regarding movement, home ranges, and habitat use. For th ese studies, a slight modification of the above described procedures can be used for longer-te rm attachment of radio transmitters using the enlarged dorsal nuchal scutes as the attachment point. In this ad aptation, four holes are drilled through the nuchal scutes instead of the cranial ridges. Newer transmitter models come equipped with two small hollow channels th at run through the base of the tr ansmitter and are used to run wire through during attachment. This design works particularly well for nuchal scute attachment. Weaving wire directly through bone material is generally not the most efficient technique for long-term attachment of transmitters. Using wire alone will decrease attachment time and the transmitter will be more likely to detach through sheer force, for ex ample in a territorial dispute or during a flight response. Th erefore, it is recommended for nuchal scute attachment that flexible plastic tubing (with an in side diameter approximately equa l to the diameter of the wire) be woven through the drilled holes first, followe d by wire woven through the plastic tubing. This provides added strength and longevi ty of attachment. Plastic tubing could certainly be used for cranial ridge attachment to increase attachment longevity, although most alligators in this study lacked sufficiently thick enough bone to accommodate plastic tubing as well. This may not be the case in species with more pr onounced cranial ridges, such as Crocodylus porosus or C. niloticus. In this study, foregoing the use of plastic tubing also made transmitter recovery much more efficient. In addition to using plastic tu bing, a knead-able marine epoxy is used during the

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97 final epoxy application to encase the transmitter, wi res, and nuchal scutes. Since marine epoxies cure underwater, handling time is reduced as animal s may be released before the epoxy reaches a full cure.

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98 Table A-1. Results of epoxy experi ment for transmitter attachment. Brand Cure Time (min.) Cure Temp. (C) Strength of Hold (kg) Comments DevCon ~20 44.4 18 Full cure; epoxy bonded strongly to skin SuperMend 120+ 41.1 8 Epoxy very tacky; slid off skull AquaMend ~60 32.2 9.6 A fairly solid cure but still tacky Loctite Aquamarine ~120 26.6 13 So lid cure, weak bondage to skin Loctite Stick nSeal n/a n/a n/a No cure and no test after two hours PerfectGlue 120+ n/a 14 Slighty tack y; still took skin upon removal GOOP Marine FixFast ~40 37.2 11 Epoxy still malleable upon testing TriggerBond ~20 40.5 12 No cure underneath surface *Room temperature was 25.5-27.2 C for all trials. He ads and transmitters were cleaned with 91% rubbing alcohol prior to attachment. Cure times are for su rfaces. In some instances the epoxy was still wet underneath. In all trials vice cranking began after two hours time.

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99 Table A-2. Summary of transm itter application and recovery scute clip capture date frequency transmitter recovery date 202 12-Jul-05 166.696 lost 203 12-Jul-05 166.154 lost 204 13-Jul-05 166.138 lost 205 13-Jul-05 166.875 lost 206 13-Jul-05 166.571 lost 207 13-Jul-05 166.542 lost 208 13-Jul-05 166.934 lost 209 13-Jul-05 166.017 lost 210 13-Jul-05 166.92 lost 211 14-Jul-05 166.28 lost 302 18-Apr-06 166.705 10-Aug-06* 303 18-Apr-06 166.225 8-Aug-06* 304 18-Apr-06 166.489 8-Aug-06 305 18-Apr-06 166.082 8-Aug-06 306 19-Apr-06 166.389 lost 307 19-Apr-06 166.329 10-Aug-06* 308 19-Apr-06 166.468 10-Aug-06* 309 19-Apr-06 166.167 8-Aug-06 310 19-Apr-06 166.511 8-Aug-06 138 20-Apr-06 166.309 10-Aug-06 139 20-Apr-06 166.069 8-Aug-06 121 20-Apr-06 166.548 8-Aug-06 123 25-Apr-06 166.625 10-Aug-06 122 25-Apr-06 166.607 lost 124 26-Apr-06 166.024 8-Aug-06 311 14-Jun-06 166.284 10-Aug-06* 313 14-Jun-06 166.364 10-Aug-06* 312 14-Jun-06 166.406 8-Aug-06* All 2005 transmitters were lost after Hurricane Wilma passed through (24 Oc tober 2005) and left no transmitters to be heard. indicates that the transm itter was still attached to the study animal, otherwise the transmitter had been shed and was found on the bottom of the water intact.

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100 Figure A-1. Parietal/squamosal wi ring. 1) A hole is drilled through parietal/squamosal ridge. 2) The wire is woven through the new hole. 3) The wire is twisted around itself to secure its placement. 4) The wire is securely attached to parietal/squamosal ridge.

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101 Figure A-2. Transmitter attachment. 1) The transmitte r is placed in the middle of parietal with wires from transmitter in line with wires previously attached. 2) Wires are twisted around each other in a similar manner as desc ribed in step 4 of Figure A-1. 3) The transmitter is wired to parietal. This fi gure also indicates the placement of the conductivity switches.

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102 Figure A-3. One recaptured alligator w ith the transmitter firmly in place

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103 APPENDIX B DATA PROTOCOLS AND MANAGEMENT Due to crossover or reflected signals, som e da ta were recorded in error. Protocols were developed to sort the data so that only the most accurate and reliable data were used for analysis. For example, the logged emergence data consis ted of eight different fields. These included Field, Date, Time, Frequency, Pulses per minute, Percent signal, Transmitter ID, and Data bytes. Field described the kind of chirp the receiver heard. This value was either 0, 1, or 2, meaning the receiver detected a regular chirp, a chirp with incorrect digital ID, or a chirp with correct digital ID and temperature respectively. Lines of data that included any of these values were kept, because in any case the transmitter was above water and was being heard. Time was the time of day (24 hr) the receiver heard the transmitter, and Frequency was the transmitter frequency that was heard. Pulses per minute for the 2005 transmitters described whether the transmitter was in normal running mode or mortality mode. Data with Pulses per minute values ranging from 28-32 (normal running mode) were kept, while data with Pulses per minute values 50 and greater (mortality mode) were discarded, since the mortality mode did not allow for determination of emergence. Pulses per minute for the 2006 transmitters described whether the transmitter was above or below water. Percent signal described the strength of the signal that the receiver heard. These values ranged from 0 to 99. Data with values that ranged from 2-99 were kept, while data with values 0 and 1 were discarded. Transmitter ID described the ID of the transmitter being heard for the 2005 transmitters. Data with both co rrect and incorrect transmitter ID were kept, since either way the transmitter was heard and the alligator was surfaced. Transmitter ID described the proportion of time during the last one hour that the alligator spent submerged for the 2006 transmitters. Finally, the Data bytes field included digita l temperature data.

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104 If any record was missing in 2005, it was assu med that the alligator was submerged, as our transmitters were programmed to turn off underwater. I also assumed that no alligator ventured out of range of the re ceiver (approximately 3 km). Mor ea et al. (2000) reported that Everglades alligators have re latively small home ranges and are more or less bound to their ranges with infrequent emigration. All study anim als were captured within 1 km of the fixed antennae/receiver, and the farthe st known distance an alligator traveled was 1.5 km from its capture location, based on its locat ion at the end of th e study. In addition, a ll alligators were picked up consistently by the receiver through th e course of the study. In 2006, the transmitters remained on at all times and only the pulses pe r minute changed as the transmitter was emerged. This change was made in order to nullify even the possibility that some alligators may have left the study area in the 2005 season. Some signals in 2006 were missed late in the season as the transmitter signals grew weaker. For these missed r ecords, I also assumed that the alligator was underwater and perhaps buried in mud under a floating mat of vegetation, as is common refugia for alligators in the study area (C. Bugbee, pers. obs.).

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105 APPENDIX C PERMITS Perm its were used in this project for alliga tor capture and radio transmitter attachment. They were obtained from the following agencies: Everglades National Park Florida Fish and Wildlife Conservation Commission University of Florida Animal Care and Use Committee

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106 LIST OF REFERENCES Abercrom bie, C. L., S. R. Howarter, C. R. Morea, K.G. Rice, and H. F. Percival. 2000. Thermoregulation of alligators ( Alligator mississippiensis ) in southern Florida. J. Thermal Biology. SUBMITTED Abercrombie, C.L., S. R. Howarter, H. F. Perc ival, K. G. Rice, C. R. Morea. 2002. Everglades Alligator thermoregulation: unanswered questions. In Proc. 16th Working Meet. Crocodile Specialist Group, pp. 131-138. IUCN, Gland, Switzerland. Addison, B. G., R. H. Chabrec k, and V. L. Wright. 1998. Movement of juvenile farm-released and wild American alligators in a freshwater marsh in Louisiana. In Proc. 14th Working Meet. Crocodile Specialist Group, pp 305-310. IUCN, Gland, Switzerland. Aiken, L. S., and S. G. West. 1991. Multiple regression: Testing and interpreting interactions Newbury Park, London, Sage. 224 pp. Asa, C.S., G.D. London, R. R. Goellner, N. Haskell, G. Roberts, and C. Wilson. 1998. Thermoregulatory behavior of cap tive American alligators ( Alligator mississippiensis ). J. Herpetol. 32:191-197. Barnett, J., K. G. Rice, H. F. Percival and P. T. Cardeilhac. 1997. A method for the intramuscular implantation of transmitters in al ligators. Proc. Inter. Assoc. Aquatic Animal Medicine. 28:45-48. Barr, B. 1997. Food habits of the American alligator, Alligator mississippiensis, in the southern Everglades. Ph.D Dissertation, Univer sity of Miami, Miami, Florida. Bayliss, P. 1987. Survey methods and monitori ng within crocodile management programmes. In G. J. W. Webb, G. J., S. C. Manolis, and P. J. Whitehead (eds.), Wildlife Management: Crocodiles and Alligators, pp157-175. Surre y Beatty and Sons Pty Ltd., Chipping Norton, Australia. Beard, D. B. 1938. Wildlife reconnaissance. U.S. Department of the In terior, National Park Service, Everglades National Park Project. 106pp. Boarman, W. I., T. Goodlett, G. Goodlett, a nd P. Hamilton. 1998. Review of radio transmitter attachment techniques for turtle research and recommendations for improvement. Herp. Review 29:26-33. Brandt, L. A. 1989. The status and ec ology of the Am erican alligator (Alligator mississippiensis ) in Par Pond, Savannah River Site. M.S. Thes is, Florida Internati onal University, Fort Lauderdale, Florida. 89 pp. Brisbin, L., and E. Standora. 1982. Body temperature and behavior of American alligators during cold winter weather. The Am. Midl. Nat. 107:209-218.

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107 Burnham, K. P., and D. R. Anderson. 2002. M odel selection and multimodel inference: a practical information-theoretic approac h. 2nd Edition. Springer-Verlag, New York, New York, USA. 488 pp. Cadi, A., S. Martin, A. Barlow, L. Fougeirol and T. Maskey. 2002. Gharial conservation in Nepal: First results of a population reinforcem ent program in the Narayani river, Royal Chitwan National Park. Proc. 16th Work ing Meet. Crocodile Specialist Group, pp. 343346. IUCN, Gland, Switzerland. Cassey, P., and B. H. McCardle. 1999. An asse ssment of distance sampling techniques for estimating animal abundance. Environmetrics 10:261-278. Chabreck, R. H. 1963. Methods of captu ring, marking, and sexing alligators. In Proc. 17th Ann. Conf. Southeastern Assoc. Game Fish Comm. 1963, pp. 47-50. Chabreck, R. H. 1965. The movement of alligators in Louisiana. In Proc. 19th Ann. Conf. Southeastern Assoc. Game and Fish Comm. 1965, pp. 102-110. Chopp, M. P., H. F. Percival, K. G. Rice. 2002. Everglades alligator production differences between marsh interior and marsh canal habi tats in A. R. M. Loxahatchee National Wildlife Refuge. Proc. 16th Working Meet. Crocodile Specialist Group, pp. 41-59. IUCN, Gland, Switzerland. Christian, K. A., and B. W. Weavers. 1996. Thermo regulation of monitor liz ards in Australia: An evolution of methods in thermal biology. Ecol. Monographs 66:139-157. Conant, R., and J. T. Collins. 1991. Reptiles an d Amphibians: Eastern/Central North America. Houghton Mifflin Company, Boston, Mass. 450 pp. Craighead, F. C. 1968. The role of the alligator in shaping plant communities and maintaining wildlife in the southern Everglades. Florida Naturalist 41:2-7, 69-74, 94. Dalrymple, G. H. 1996. Growth of American allig ators in the Shark Valley region of Everglades National Park. Copeia. 1996:212-216. Davis, S., L. H. Gunderson, W. A. Park, J. E. Mattson. 1994. Landscape dimension, composition and function in a changing Everglades ecosystem. In S. M. Davis, and J. C. Ogden (eds). Everglades: the ecosystem and its rest oration, pp. 419. St. Lucie Press, Delray Beach, Florida, USA. DeAngelis, D. L., W. F. Loftus, J. C. Trexler, R. E. Ulanowicz. 1997. Modelling fish dynamics and effects of stress in a hydr ologically pulsed ecosystem. J. Aquatic Ecosystem Stress and Recovery. 6:1-13.

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108 Deitz, D. C. 1979. Behavioral ecology of young Amer ican alligators. Dissertation, University of Florida, Gainesville, Florida. 151pp. Dias, P. C. 1996. Sources and sinks in popul ation biology. Trends Ecol. Evol. 11:326-330. Diefenbach, C. O. Da. C. 1975. Thermal preferences and thermoregulation in Caiman crocodilus. Copeia. 3: 530-540. Fedak, M., P. Lovel, and B. McConnel. 2002. Ov ercoming the constraints of long range radio telemetry from animals: Getting more useful data from smaller packages. Integr. Comp. Biol. 42: 3-10. Fergusson, R. A. 1992. A radiotelemet ry and mark recapture experiment to assess the survival of juvenile crocodiles released from farms into the wild in Zimbabwe. In Proc. 11th Working Meet. Crocodile Specialist Group, pp 98-106. IUCN, Gland, Switzerland. Fergusson, R. 1998. Re-introduction of Nile crocodiles to Lake Kariba, Zimbabwe. In Proc. 14th Working Meet. Crocodile Specialist Group, pp. 311-312. IUCN, Gland, Switzerland. Fish, F. E., and L. A. Cosgrove, 1987. Behavioral thermoregulation of small American alligators in water: postural changes in relation to thermal environment. Copeia. 3: 804-807. Garrick, L. D., and J. W. Lang. 1975. A lligator courtship. Am. Zool. 15: 813. Gentile, J. H., M. A. Harwell, W. Cropper, Jr., C. C. Harwell, D. DeAngelis, S. Davis, J. C. Ogden, D. Lirman. 2001. Ecological Conceptu al Models: A Framework and Case Study on Ecosystem Management for South Florida Sustainability. The Science of the Total Environment 274: 231-253. Goodwin, T. 1978. Use of radio telemetry for tr acking alligators. Florida Wildlife 32: 14-15. Goodwin, T. M., and W. R. Marion. 1979. Seasona l activity ranges and ha bitat preferences of adult alligators (Reptilia, Crocodilidae ) in a north-central Flor ida lake. J. Herpetol. 13:157. Graham, A., and R. Bell. 1969. Factor s influencing the countability of animals. East Afr. Agric. Forest. J. 34:38-43. Grigg, G. C., W. D. Farwell, J. L. Kinney, P. Ha rlow, L. E. Taplin, J. Johansen, K. Johansen. 1985. Diving and amphibious behaviour in a free-living Crocodylus porosus. Aust. Zool. 21: 599-605. Gunderson, L. H., and W. F. Loftus. 1993. The Everglades. In John Wiley and Sons (eds). Biodiversity of the Southeastern United States: Lowland. NewYork, pp. 199-255.

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112 Palmer, M. L. 2000. The structure and function of Everglades alligator holes. M.S. Thesis, University of Florida, Ga inesville, Florida. 59 pp. Percival, H. F., K. G. Rice, S. R. Howa rter. 2000. American al ligator distribution, thermoregulation, and biotic po tential relative to hydroperiod in the Everglades. Fla. Coop. Fish and Wildl. Res. Unit, USGS Tech. Rep. 155 pp. Peterson C. R., R. A. Gibson, M. E. Dorcas 1993. Snake thermal ecology: the causes and consequences of body-temperature variation. In R. A. Siegel and J. T. Collins (eds.), Snakes: Ecology and Behavior, pp. 241. McGraw-Hill, New York. Pollock, K. H., J. D. Nichols, T. R. Simons, G. L. Farnsworth, L. L. Bailey, and J. R. Saurer. 2002. Large scale wildlife monitoring studies: st atistical methods for design and analysis. Environmetrics. 13:105-119. Pulliam, H. R. 1988. Sources, sinks, and popul ation regulation. Am. Nat. 132:652-661. Reidel, J. D., D. K. Bolen, R. C. Averill-Mu rray. 2003. Desert tortoise habitat use and home range size of the Florence Military Reserva tion: progress report 214. Arizona Game Fish, Phoenix, AZ. 131 pp. Rice, K. G., F. J. Mazzotti, L. A. Bra ndt. 2004. Status of the American alligator ( Alligator mississippiensis) in southern Florida, USA and its ro le in measuring restoration success in the Everglades. In Proc. 17th Ann. Working Meet. Crocodil e Specialist Group, Species Survival Commission, pp. 395-400. IUCN, Gland, Switzerland. Rice, K. G., F. J. Mazzotti, L. A. Brandt. 2005. Status of the American alligator in southern Florida and its role in meas uring restoration success. In W. E. Meshaka, and K. J. Babbitt (eds). Amphibians and Reptil es: status and conservation in Florida, pp. 145. Krieger Publishing Co., Malibar, Florida, USA. Richardson, J. R., W. L. Bryant, W. M. Kitche ns, J. E. Mattson, K. R. Pope. 1990. An evaluation of refuge habitats and relationships to water quality, quantity, and hydroperiod: a synthesis report. Final Report to Arthur R. Marshall Loxahatchee National Wildlife Refuge, Boynton Beach, Florida. Rodda, G. H. 1984. Homeward paths of displaced juvenile alligators as determined by radiotelemetry. Behav. Ecol. Sociobiol. 14: 241-246. Rootes, W. L., and R. H. Chabreck. 1993. Repr oductive status and movement of adult female alligators. J. Herpetol. 27: 121-126. Sarkis-Goncalves, F., A. M. V. Castro, L. M. Verdade. 2004. The influence of weather conditions on caiman night-counts. In Proc. 17th Ann. Working Meet. Crocodile Specialist Group, Species Survival Commission, pp. 387-393. IUCN, Gland, Switzerland.

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113 Seebacher, F., C. E. Franklin, M. Re ad. 2005. Diving behaviour of a reptile ( Crocodylus johnstoni ) in the wild: Inte ractions with heart rate a nd body temperature. Physiol. Biochem. Zool. 78:1-8. Seebacher, F., and G. C. Grigg. 1997. Patterns of body temperature in wild freshwater crocodiles, Crocodylus johnstoni : Thermoregulation versus thermoconformity, seasonal acclimatization, and the effect of so cial interactions. Copeia. 3:549-557. Shine, R., and T. Madsen. 1996. Is thermoregulation unimportant for most reptiles? An example using water pythons ( Liasus fuscus ) in tropical Australia. Phys. Zool. 69:252. Simmons, G., and L. Ogden. 1998. Gladesmen. University of Florida Press, Gainesville, Florida. Slip, D. J., and R. Shine. 1988. Thermoregulation of free-ranging Diamond Pythons, Morelia spilota ( Serpentes, Boidae ). Copeia 1988:984. Spotila, J. R., O. H. Soule, D. M. Gates. 1972. The biophysical ecology of the alligator: heat energy budgets and climat e spaces. Ecology 53:1092-1104. Spratt, R. G. 1997. Harvest-induced wariness in Am erican alligators in Florida. M.S. Thesis, University of Florida, Gain esville, Florida. 27 pp. Steinhorst, R. K, Samuel M. D. 1989. Sightability adjustment methods for aerial surveys of wildlife populations. Biometrics 45:415-426. Stokes, D., P. D. Boersma. 1999. Wh ere breeding Magellanic penguins ( Speniscus magellanicus ) forage: satellite telemetry results and their implications for penguin conservation. Mar. Ornithol. 27:59-65. Taylor, D., T. Joanen, L. McNease. 1976. A comparison of native and introduced immature alligators in northeas t Louisiana. Proc. 30th Ann. Meet. Southeastern Assoc. Game Fish Comm., pp Thompson, W. L. 2002. Towards reliable bird survey s: accounting for individuals present but not detected. Auk 119:18-25. Thompson, S. K., Seber, G. A. F. 1994. Detect ability in conventiona l and adaptive sampling. Biometrics 50:712-724. Vliet, K. A. 1987. A quantitative analysis of the courtship behavior of the American alligator ( Alligator mississippiensis). Dissertation, University of Fl orida, Gainesville, Florida. 198pp. Vliet, K. 2001. Courtship of captive American alligators ( Alligator mississippiensis ). In G. C. Grigg, F. Seebacher, and C. E. Franklin (e ds). Crocodilian Biology and Evolution, pp. 383-408. Surrey Beatty and Sons Pty. Ltd., Chipping Norton, Australia.

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114 Webb, G. J. W., and H. Messel. 1979. Wariness in Crocodylus porosus. Austral. Wildl. Res. 6: 227-234. Webb, G. J. W., S. C. Manolis, R. Buckworth. 1982. Crocodylus johnstoni in the McKinley River area, N. T. I. Variation in the diet and a new method of assessing the relative importance of prey. Aust. J. Zool. 30:877-899. White, G. C., and Garrott, R. A. 1990. Analysis of Wildlife Radio-Track ing Data. Academic Press Limited, San Diego, California, USA. Wood, J. M., A. R. Woodward, S. C. Humphrey, a nd T. C. Hines. 1985. Night counts as an index of American alligator population tr ends. Wildl. Soc. Bull. 13:262-273. Woodward, A. R, and W. R. Marion 1979. An evalua tion of factors affec ting night-light counts of alligators. In Proc. 32nd Ann. Conf. Southeastern Assoc. Fish and Wildl. Agencies, 1979, pp. 291-302. Woodward, A. R, and C. T. Moore. 1990. Statewide alligator surveys. Bureau Wildl. Res., Fla. Game and Freshwater Fish Co mm., Tallahassee, Florida. 24 pp. Woodward, A. R., and S. B. Linda. 1993. Alligator populatio n estimation. Final Report, Fla. Game and Freshwater Fish Co mm., Tallahassee, Florida. 36 pp. Woodward, A. R., K. G. Rice, S. B. Linda. 1996. Estimating sighting proportions of American alligators during nigh t-light and aerial helicopter surveys. In Proc. 50th Ann. Conf. Southeastern Assoc. Game Fish Comm. 1996, pp. 509-519. Wright, J. C. 1987. Energy metabolism during un restrained submergence in the saltwater crocodile Crocodylus porosus. Physio. Zool. 60:515-523. Zweig, C., F. Mazzotti, K. Rice, C. Abercr ombie, L. Brandt. 2002. Body condition factor analysis for the American alligator ( Alligator mississippiensis). In Proc. 16th Ann. Working Meet. Crocodile Specialist Gr oup, Species Survival Commission, pp. 165. IUCN, Gland, Switzerland.

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115 BIOGRAPHY Christopher David Bugbee graduated from Ly me-Old Lyme High School in 1997 and went on to earn his B.S. from St. Lawrence Universi ty in Canton, New York, in 2002. He has since worked with the Connecticut Department of Environmental Protection, the United States Geological Survey, the Florida Cooperative Fish and Wildlife Research Unit, and the United States Forest Service assisti ng with a variety of ichthyological and herpetological research projects. Chris has a particular interest in freshwater systems and wetland conservation. He is also an advocate of the top-dow n approach to wildlife conserva tion. For these reasons, he became particularly interested in American alligat ors and their important role in the Everglades ecosystem.


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