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Effects of Chronic and Low Methylmercury Exposure on Juvenile White Ibises (Eudocimus albus)

Permanent Link: http://ufdc.ufl.edu/UFE0021286/00001

Material Information

Title: Effects of Chronic and Low Methylmercury Exposure on Juvenile White Ibises (Eudocimus albus)
Physical Description: 1 online resource (62 p.)
Language: english
Creator: Adams, Evan M
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2007

Subjects

Subjects / Keywords: bird, disruptor, endocrine, everglades, experiment, foraging, hormone, methylmercury
Wildlife Ecology and Conservation -- Dissertations, Academic -- UF
Genre: Wildlife Ecology and Conservation thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Methylmercury is a global contaminant with reported neurological, endocrine disrupting, and teratogenic effects that has been a problem specifically in the Everglades ecosystem in South Florida. I used a free-flight aviary to hold White Ibises (Eudocimus albus) captive and allow the controlled delivery of dietary methylmercury to four exposure groups?control, 0.05, 0.1, and 0.3 mg/kg per day in diet, wet weight. My research has focused upon the sublethal effects of chronic, environmentally relevant exposure on the behavior and endocrine development in juvenile White Ibises. In this study I examine the method we used to capture 220 nestling White Ibises from two colonies in Florida and in the process monitored a colony-wide starvation event. During my week long collection period in the Everglades I report a significant decrease in the proportion of females caught by my methods and report on differences in size-corrected mass. In Chapter 2, I design an experiment testing the foraging efficiency of juvenile White Ibises in a group setting. Using stereotyped foraging arenas with varying quantities of structural complexity, I allowed all exposure groups to a set amount of time to forage upon a pre-defined number of small fish. I hypothesized that increasing methylmercury exposure and increasing structural complexity would negatively affect a young ibises foraging efficiency and that increasing methylmercury would decrease this ability to improve foraging efficiency with time. I found that while structural complexity had a strong negative effect upon group foraging efficiency, methylmercury had a weak (though statistical significant) effect that is non-linear with respect to exposure. The low and medium groups were the best foragers, while the high and control groups were the worst overall. Methylmercury did not affect the improvement of foraging efficiency with time. In Chapter 3, I investigated the changes in fecal estradiol, testosterone, and corticosterone metabolites over time with respect to methylmercury exposure group in juvenile White Ibises. I collected over 350 samples non-invasively from individual birds over 7 months and developed tests for each hormone of interest for this species. I hypothesized that increasing methylmercury would impact estradiol, testosterone, and corticosterone in dose-dependent fashion with respect to time and that sex would affect each hormone. I found that estradiol and testosterone did not change in any biologically explicable manner with respect to dose, and that sex was not important in determining steroid hormone levels. With corticosterone, I found that a significant non-linear relationship with methylmercury exposure. While this result was not predicted, a biological explanation of hormesis may explain these data. In conclusion, I found no linear relationships between endpoint behavior or endocrine function and methylmercury exposure. White Ibises may not be sensitive to methylmercury exposure at either 1) these dose ranges or 2) while juveniles. Future research during the breeding season will test these new hypotheses.
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.
Statement of Responsibility: by Evan M Adams.
Thesis: Thesis (M.S.)--University of Florida, 2007.
Local: Adviser: Frederick, Peter C.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2007
System ID: UFE0021286:00001

Permanent Link: http://ufdc.ufl.edu/UFE0021286/00001

Material Information

Title: Effects of Chronic and Low Methylmercury Exposure on Juvenile White Ibises (Eudocimus albus)
Physical Description: 1 online resource (62 p.)
Language: english
Creator: Adams, Evan M
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2007

Subjects

Subjects / Keywords: bird, disruptor, endocrine, everglades, experiment, foraging, hormone, methylmercury
Wildlife Ecology and Conservation -- Dissertations, Academic -- UF
Genre: Wildlife Ecology and Conservation thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Methylmercury is a global contaminant with reported neurological, endocrine disrupting, and teratogenic effects that has been a problem specifically in the Everglades ecosystem in South Florida. I used a free-flight aviary to hold White Ibises (Eudocimus albus) captive and allow the controlled delivery of dietary methylmercury to four exposure groups?control, 0.05, 0.1, and 0.3 mg/kg per day in diet, wet weight. My research has focused upon the sublethal effects of chronic, environmentally relevant exposure on the behavior and endocrine development in juvenile White Ibises. In this study I examine the method we used to capture 220 nestling White Ibises from two colonies in Florida and in the process monitored a colony-wide starvation event. During my week long collection period in the Everglades I report a significant decrease in the proportion of females caught by my methods and report on differences in size-corrected mass. In Chapter 2, I design an experiment testing the foraging efficiency of juvenile White Ibises in a group setting. Using stereotyped foraging arenas with varying quantities of structural complexity, I allowed all exposure groups to a set amount of time to forage upon a pre-defined number of small fish. I hypothesized that increasing methylmercury exposure and increasing structural complexity would negatively affect a young ibises foraging efficiency and that increasing methylmercury would decrease this ability to improve foraging efficiency with time. I found that while structural complexity had a strong negative effect upon group foraging efficiency, methylmercury had a weak (though statistical significant) effect that is non-linear with respect to exposure. The low and medium groups were the best foragers, while the high and control groups were the worst overall. Methylmercury did not affect the improvement of foraging efficiency with time. In Chapter 3, I investigated the changes in fecal estradiol, testosterone, and corticosterone metabolites over time with respect to methylmercury exposure group in juvenile White Ibises. I collected over 350 samples non-invasively from individual birds over 7 months and developed tests for each hormone of interest for this species. I hypothesized that increasing methylmercury would impact estradiol, testosterone, and corticosterone in dose-dependent fashion with respect to time and that sex would affect each hormone. I found that estradiol and testosterone did not change in any biologically explicable manner with respect to dose, and that sex was not important in determining steroid hormone levels. With corticosterone, I found that a significant non-linear relationship with methylmercury exposure. While this result was not predicted, a biological explanation of hormesis may explain these data. In conclusion, I found no linear relationships between endpoint behavior or endocrine function and methylmercury exposure. White Ibises may not be sensitive to methylmercury exposure at either 1) these dose ranges or 2) while juveniles. Future research during the breeding season will test these new hypotheses.
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.
Statement of Responsibility: by Evan M Adams.
Thesis: Thesis (M.S.)--University of Florida, 2007.
Local: Adviser: Frederick, Peter C.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2007
System ID: UFE0021286:00001


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EFFECTS OF CHRONIC AND LOW METHYLMERCURY EXPOSURE IN JUVENILE
WHITE IBISES (Eudocimus albus)




















By

EVAN M. ADAMS


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

2007


































2007 Evan M. Adams



































To my parents, for encouraging me to explore









ACKNOWLEDGMENTS

First, I would like to thank the Florida Department of Environmental Protection and

specifically Don Axelrad for having the vision to see this project through. I thank Peter

Frederick for being willing to take risks (on me and science) and my committee for their

guidance. I owe Mary Christman and Iske Larkin a great deal of thanks for all the statistics

consulting and radioimmunoassay tutoring, respectively. This work was supported by Florida

Department of Environmental Protection, the United States Army Corps of Engineers and the

United States Fish and Wildlife Service.











TABLE OF CONTENTS

page

A CK N O W LED G M EN T S ................................................................. ........... ............. .....

LIST OF TABLES ......... ..... .... ....................................................6

LIST OF FIGURES .................................. .. ..... ..... ................. .7

CHAPTER

1 SEX-RELATED MORTALITY DUE TO A STARVATION EVENT IN WHITE IBIS
(Eudocimus albus) IN THE FLORIDA EVERGLADES.................................. .................10

Intro du action ........................................... .. ....10..........
M e th o d s .. ....... ..... ........ .. ............. .. .............................................................1 1
R e su lts ....... ......... .. ............. .. ........................................................... 12
D discussion ..................................................................................13

2 EFFECTS OF METHYLMERCURY AND SPATIAL COMPLEXITY ON
FORAGING BEHAVIOR AND EFFICIENCY IN JUVENILE WHITE IBISES
(E u d o cim u s a lb u s) ............................................................................................................ 19

Introdu action ............... ......... ............... ..............................................19
Methods ........................................ 21
R e su lts ............... ...... .......... ................ ......... ...................................... ............ 2 3
D discussion ......... ...... ... ......... .. ............................................25

3 SUBLETHAL EFFECTS OF METHYLMERCURY ON TESTOSTERONE,
ESTRADIOL, AND CORTICOSTERONE FECAL METABOLITES IN CAPTIVE
JUVENILE W HITE IBISES (Eudocimus albus) ........................................ ............... 31

Introdu action ............... ......... ............... .............................................. 3 1
Methods ........................................ 33
S tu d y S ite .................................... ..... ...... ...................................3 3
Fecal Hormone Sampling Technique, Storage and Extraction .....................................34
Radioimmunoassay........................................................36
Statistical A n aly sis ................................................................37
R e su lts ............... ...... .......... ......................................................................... 3 9
D discussion ......... ...... ... ......... .. ............................................4 1

LIST OF REFEREN CES ................................................................................................... 52

B IO G R A PH IC A L SK E T C H ................................................................................................... 62









LIST OF TABLES


Table page

1-1 The number of male and female nestlings captured for each collection date. The
proportion of males captured is display parenthetically after the column totals ...............17

2-1 Overall effect of factors in our best model. Significance was determined using an F-
test based on Kenward-Rogers degrees of freedom estimation..................................28

2-2 Parameter estimates from the best model (PROC MIXED). Note that Beta values are
relative to the control group in the case of methylmercury exposure and the high
group in the habitat com plexity .............................................................. .....................28

3-1 The average extraction efficiencies for each hormone by percent ethanol used for
extraction ....................................................................................................... 45

3-2 Ranking of various models for all hormone metabolites by Akaike weight. Only
models with a weight greater than 0.01 were included..........................................45

3-3 Estradiol parameter estimates from our best model selected by AIC with their
respective standard error of the estimate. P-value is determined using an F-test.
Note that treatment and sex effects are categorical and the control and male groups,
respectively, act as a reference and all others are estimated relative to that group ..........46

3-4 Testosterone parameter estimates from our best model selected by AIC with their
respective standard error of the estimate. P-value is determined using an F-test.
Note that treatment and sex effects are categorical and the control and male groups,
respectively, act as a reference and all others are estimated relative to that group ..........46

3-5 Corticosterone parameter estimates from our best model selected by AIC with their
respective standard error of the estimate. P-value is determined using an F-test.
Note that treatment and sex effects are categorical and the control and male groups,
respectively, act as a reference and all others are estimated relative to that group ..........46

3-6 Parameter estimates, standard errors and P-values (t-test) for each treatment group
subdivided by median feather mercury quantities (Fig. 1) for each hormone. The
treatment grouping was added to our best model selected by AIC. The parameter
estimate is for the highest order term that includes treatment; estradiol is
treatment*time, testosterone is treatment, and corticosterone is treatment. All
parameter estimates are relative to the control group ....................................... ........... 47










LIST OF FIGURES


Figure page

1-1 The increase in mean mass corrected for tarsus length over collection date split by
sex. N=21, 39, 68, and 49 in ascending order of collection dates. Error bars indicate
the standard error of the mean for each data point ......................................................10

2-1 Mean proportion of fish remaining for each week for each methylmercury exposure
group for A) complexity level 1 (control), B) complexity level 2 (low), C)
complexity level 3 (medium), D) complexity level 4 (high) ..........................................29

2-2 Mean proportion of prey remain grouped by methylmercury exposure group and
structural complexity over all weeks. Error bars represent standard error of the mean ...30

3-1 Feather mercury levels for individual birds in each exposure group. Data are
presented in box plots with outliers represented as dots, the gray box showing where
50% of the data lie, the line in box is m ean ................................... ......... ....... ........ 48

3-2 Mean estradiol concentration by treatment group for each collection period. Error
bars represent the standard error of the calculated mean and do not consider
intracollection dependency issues as our statistical models do ......................................49

3-3 Mean testosterone concentration by treatment group for each collection period.
Error bars represent the standard error of the calculated mean for each collection
period and do not consider intracollection dependency issues as our statistical models
d o .............. ........................ ................................................. ...... 50

3-4 Mean corticosterone concentration by treatment group for each collection period.
Error bars represent the standard error of the calculated mean for each collection
period and do not consider intracollection dependency issues as our statistical models
d o .............. ....................... .................................................. ...... 19









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

EFFECTS OF CHRONIC AND LOW METHYLMERCURY EXPOSURE IN JUVENILE
WHITE IBISES (Eudocimus albus)

By

Evan M. Adams

August 2007

Chair: Peter Frederick
Major: Wildlife Ecology and Conservation

Methylmercury is a global contaminant with reported neurological, endocrine disrupting,

and teratogenic effects that has been a problem specifically in the Everglades ecosystem in South

Florida. I used a free-flight aviary to hold White Ibises (Eudocimus albus) captive and allow the

controlled delivery of dietary methylmercury to four exposure groups-control, 0.05, 0.1, and

0.3 mg/kg per day in diet, wet weight. My research has focused upon the sublethal effects of

chronic, environmentally relevant exposure on the behavior and endocrine development in

juvenile White Ibises. In this study I examine the method we used to capture 220 nestling White

Ibises from two colonies in Florida and in the process monitored a colony-wide starvation event.

During my week long collection period in the Everglades I report a significant decrease in the

proportion of females caught by my methods and report on differences in size-corrected mass.

In Chapter 2, I design an experiment testing the foraging efficiency of juvenile White

Ibises in a group setting. Using stereotyped foraging arenas with varying quantities of structural

complexity, I allowed all exposure groups to a set amount of time to forage upon a pre-defined

number of small fish. I hypothesized that increasing methylmercury exposure and increasing

structural complexity would negatively affect a young ibises foraging efficiency and that

increasing methylmercury would decrease this ability to improve foraging efficiency with time.









I found that while structural complexity had a strong negative effect upon group foraging

efficiency, methylmercury had a weak (though statistical significant) effect that is non-linear

with respect to exposure. The low and medium groups were the best foragers, while the high and

control groups were the worst overall. Methylmercury did not affect the improvement of

foraging efficiency with time.

In Chapter 3, I investigated the changes in fecal estradiol, testosterone, and corticosterone

metabolites over time with respect to methylmercury exposure group in juvenile White Ibises. I

collected over 350 samples non-invasively from individual birds over 7 months and developed

tests for each hormone of interest for this species. I hypothesized that increasing methylmercury

would impact estradiol, testosterone, and corticosterone in dose-dependent fashion with respect

to time and that sex would affect each hormone. I found that estradiol and testosterone did not

change in any biologically explicable manner with respect to dose, and that sex was not

important in determining steroid hormone levels. With corticosterone, I found that a significant

non-linear relationship with methylmercury exposure. While this result was not predicted, a

biological explanation of hormesis may explain these data.

In conclusion, I found no linear relationships between endpoint-behavior or endocrine

function-and methylmercury exposure. White Ibises may not be sensitive to methylmercury

exposure at either 1) these dose ranges or 2) while juveniles. Future research during the breeding

season will test these new hypotheses.









CHAPTER 1
SEX-RELATED MORTALITY DUE TO A STARVATION EVENT IN WHITE IBIS
(Eudocimus albus) IN THE FLORIDA EVERGLADES

Introduction

Sexually size dimorphic (SSD) avian species have often been found to exhibit sex

dependent pre-fledgling mortality during periods of food limitation (Hipkiss et al. 2002). This

may be because larger sized nestlings have higher mortality due to greater nutritional need

(Clutton-Brock 1985; Arroyo 2002; Laaksonen et al. 2004; Bortolotti 1986; Anderson et al.

1993; Kalmbach et al. 2005), but there are also numerous examples in which both the smaller sex

has higher mortality as nestlings or juveniles (Nager et al. 2000; Torres and Drummond 1999;

Teather and Weatherhead 1989; Roskaft and Slagsvold 1985). This suggests that a different

mechanism of mortality must be acting upon these nestlings. Possible mechanisms include, large

siblings dominating smaller ones (Oddie 2000), larger offspring being better able to withstand

starvation or extreme temperature resilience (Greenberg 1979) and sex specific, size unrelated

mortality (Miiller et al. 2005) are potential mechanisms. Covariates linked to sex-related

mortality that are independent of size and sex are brood size (Raberg et al. 2005), prey size

(Anderson et al. 1993), prey availability (McDonald et al. 2005), and hatching asynchrony

(Gonzalez-Solis et al. 2005; Ostreiher 1997); these factors influence the dynamics of sibling

competition in nests and may determine whether a species or population exhibits significant sex-

related mortality.

Here, we report on differential sex related mortality in young of the sexually dimorphic

White Ibis (Eudocimus albus). Adult males are larger than females in most measurements of

body size by roughly 15% (Babbitt and Frederick 2007; Kushlan 1977). A variety of selective

costs and benefits to adults have been proposed for sustaining the sexual dimorphism (Bildstein









1993; Petit and Bildstein 1987; Kushlan 1974; Babbitt and Frederick 2007), but there has been

little research on the costs and benefits of SSD in nestlings.

Breeding propensity and breeding success are largely limited by prey availability in White

Ibises (Kushlan 1974; Kushlan and Bildstein 1992; Frederick 2002). In south Florida, USA,

patterns of surface water recession is typically associated with highly available prey (fishes and

crustaceans), while rising surface waters are typically associated with poor availability and

abandonment of nesting (Kushlan 1974; Frederick and Spalding 1994; Frederick and Collopy

1989; Gawlik 2002). In many years, nesting may be wholly or partly abandoned in response to

unseasonable rainfall and associated water level increases (Frederick 2001). Incubation and

hatching of eggs in this species is asynchronous, and a size differential is typical for nestmates

up to the approximate midpoint of the 40-50 d nestling stage (Kushlan 1974). A sex related size

differential is also typical of nestlings, ranging from very little at hatching to nearly adult ratios

at fledging.

In this paper, we document changes in secondary sex ratio and body condition in nestling

White Ibises during a widespread nest abandonment event resulting from a food shortage.

Methods

As part of a study of captive ibis behavior and reproduction we collected young ibises from

1) in the Alley North colony in Water Conservation Area 3 (WCA3) in the Florida Everglades

(Broward Co. Florida, N 260 11.179, W -80 31.431) and 2) a colony in White Springs,

Hamilton County, FL (30019.900 N, -82045.367 W). Alley North is one of the largest multi-

species wading bird colonies in North America and is composed of a 4-km long willow tree

island/cattail complex in the northeast corer of WCA3. In an attempt to collect only the first-

hatched chick (i.e., the largest nestling) of each brood we banded 300 nestlings before they could









leave the nest (about 10 days old). The bands were individually numbered plastic spirals

(National Band and Tag Co., Lexington, KY, USA).

Some of the banded birds were re-captured at 25-32 d on 14, 17, 19, and 21 April 2005

when they had become vagile and existed in large, somewhat mobile creches (De Santo et al.

1990). We collected birds using a combination of herding techniques to concentrate them,

followed by capture by hand or with hand nets. All 21 birds collected on 14 April 2005 were

banded, first-hatched nestlings marked previously (above). After this date we were able to

discover no other banded birds, and so we collected any birds available to our techniques. All

birds were transported overnight to a free-flight aviary. The following morning prior to any

feeding all birds were weighed, had both the culmen and tarsus measured, and blood samples

(about 50 tL) were drawn from the brachial vein. We used blood for DNA sexing (Fridolfsson

and Hellegren 1999) at Avian Biotech (Tallahassee, FL).

The White Springs colony was on an island within a dredge-spoil lake. Here, we banded

chicks between ca. 2 and 7 d of age and identified the first-hatched chicks by relative size and

development. We sexed 60 first-hatched chicks by blood DNA, and returned a week later (ca. 10

d of age) to collect chicks.

We used an ANOVA to examine size and mass corrected size (culmen length/total mass)

by collection date and sex. The binomial test (expected value = 0.5) was used to test a departure

from random for each collection period. All analyses were conducted using JMP IN v. 5.1.

Results

Prior to our first collection date there was evidence of colony-wide nest abandonment at

the Alley North colony. Dead chicks were a common sight beginning in early April and

continuing through the collection dates. Circling vultures were observed during the first pre-

collection foray into the colony where we banded first-hatched chicks. However, adults were









still attending many nests. The abandonments temporally co-occurred with sharp increases in

water level due to heavy rains in middle and late March and again in early April (Cook and Call

2005). Between the middle of March and April 21, local water levels increased by 22.9 cm.

Over the course of the week-long collections of ibises at the Alley North colony, the ratio

of male to female chicks captured increased dramatically (Table 1-1). We found marginally

significant or significant departures from a 50:50 male/female ratio on both the third and fourth

collection dates (P= 0.0571 and 0.0427, respectively, binomial test) while birds collected from

the first and second collection did not significantly differ from 0.5 (binomial test, P=0.662 and

P=0.37, respectively). The sex ratio of first-hatched birds from the White Springs, FL colony,

did not differ significantly from 0.5 (P=0.84, n=59, binomial test). The first collection in Alley

North and the collection at White Springs only included first-hatched nestlings and we found no

evidence of sex ratio bias in the samples of 21 and 69 birds, respectively.

Body condition-as quantified bythe ratio of weight (g) to tarsus length (cm)-changed

during the course of the one-week collections and was different between the sexes (Fig. 1-1).

We found a significant effect of collection date and sex on mass/tarsus ratio (ANCOVA,

P<0.001 for both tests), but found no significant interaction (P= 0.6639). Both sexes increased in

body condition index over time. While males had significantly higher condition indices than

females, the rate of condition increase was virtually identical between the sexes.

Discussion

Our data suggest that there were sex-related differences in mortality and body condition

in 25-32 d White Ibis nestlings during a widespread food shortage event that this was not a result

of sex bias in the hatch order. Water level had been increasing for about a month previous to our

collection and such increases are associated with nest abandonment and limited prey availability

in White Ibises (Russell et al. 2002,; Frederick and Collopy 1989; Bildstein et al. 1990; Frederick









1987a; Gawlik 2002). We found no evidence of predation or disease at the colony; in fact, most

dead ibis chicks were untouched by predators or scavengers. Although disease seems unlikely

because no adult birds were found dead, it is sometimes difficult to determine if disease or

parasites are causing nest abandonments and colony failure (Frederick and Spalding 1994) and

some SSD birds have been found to have sex-related differences in immunity (Fargello et al.

2003). However, the repeated examples of co-occurrence of food shortage and abandonment

under very similar hydrological conditions (Frederick and Collopy 1989; Frederick and Spalding

1994) lend strong support to interpretation of food shortage as a causative factor.

We do not believe that the differences in sex ratio of captive birds were due to our

capture techniques. The technique did not change over the collection period and was not size-

specific in any apparent way. We also would not expect a size-biased collection technique to

result in a changing capture sex ratio. The data indicate a linear pattern between sex ratio and

collection only after the first (biased) collection, with the later three collection dates showing

progressively larger departures from parity. Despite the statistical difficulties with hypothesis

testing in sex ratio studies due to small sample size when the expected values of a ratio is 0.5

(Ewen et al. 2002) our data showed biologically and statistically significant trends toward a male

bias.

We found that male body condition was higher than female condition on each collection

date, though rate of increase in body condition over time was not different between the sexes.

Size-corrected mass increased for both sexes over the sampling period which implies that these

birds were not starving; however, our technique only sampled the live birds, not the many dead.

An increase in size-corrected mass has been correlated with increased survival and reproduction

in non-SSD avian species (Magrath 1991; Krementz et al. 1989). While this implies that male









ibises were in better condition than females, an alternative hypothesis would be that male body

size is allometrically scaling with mass. The adaptive significance of allometric scaling between

sexes in SSD species has been well-researched and allometric scaling is generally correlated with

body size in adult (Fairbairn 1997) and nestling (Teather and Weatherhead 1994) birds. In

breeding adults and in juvenile ibises, males have higher size-corrected mass than females

(Kushlan 1977a, Kushlan and Bildstein 1992, Kushlan 1977b, unpublished data). The apparent

lack of difference in rate of increase in body condition between males and females that we found

is consistent with the allometric scaling hypothesis. We do not know when sex-related

differences in size-corrected mass would begin to manifest in White Ibises, and therefore

allometric scaling remains a plausible explanation for males being larger.

We suggest three possible mechanisms by which females might obtain less food than

males when food is scarce. First, male nestlings may out-compete their female counterparts for

food given by parents. Older and larger ibis nestlings typically are fed first by parents (Bildstein

1992, Rudegeair 1975); if food is limiting then the smaller sex may get few or no regurgitated

boluses. There is some evidence to suggest that among birds there is higher mortality in the

smaller sex when prey items are small (Anderson et al. 1993) and the size of the brood is small

(Raberg et al. 2005). Using relative definitions supplied by these studies, White Ibises deliver

small prey and have small brood sizes. Males may also be better equipped to deal with long

intervals between feedings. Poor foraging is associated with longer feeding intervals (Bildstein

et al. 1990; Rudegair 1975; Frederick 2001), and a larger animal may also be better able to

survive longer periods between food deliveries. This explanation is not necessarily mutually

exclusive of the food dominance explanation (above). Finally, parent birds could be investing

more food in male offspring during times of food limitation. It is not clear that there would be a









benefit to doing so, but the decision would be presumably be affected by the likelihood of male

survival in relation to nutrition, and by the breeding sex ratio likely to be in place at the time that

the young birds become mature. The evidence presented here suggests that females were dying

during the food shortage at a higher rate than males, probably because they were receiving less

food than males. The mechanism by which this occurred is unknown, but there seems to be good

circumstantial evidence that males would be in a better position to compete for food and to

survive long interfeeding intervals because of their size.









Table 1-1. The number of male and female nestlings captured for each collection date. The
proportion of males captured is display parenthetically after the column totals.
Sex Collection date Total
4/14/2005 4/17/2005 4/19/2005 4/21/2005
Males 10 21 41 31 103
Females 11 18 27 18 74
Total 21(0.476) 39 (0.538) 68 (0.603) 49 (0.633) 177 (0.582)
















8.5 -


8.0




7.5 -
C
0

C
0 7.0

O


6.5 --- Male Nestlings
-o-- Female Nestlings


6.0
14 April 17 April 19 April 21 April

Collection Date

Figure 1-1. The increase in mean mass corrected for tarsus length over collection date split by
sex. N=21, 39, 68, and 49 in ascending order of collection dates. Error bars indicate
the standard error of the mean for each data point.









CHAPTER 2
EFFECTS OF METHYLMERCURY AND SPATIAL COMPLEXITY ON FORAGING
BEHAVIOR AND EFFICIENCY IN JUVENILE WHITE IBISES (Eudocimus albus)

Introduction

Methylmercury is a neurotoxin, endocrine disrupting chemical (EDC), and teratogen in

which exposure has been connected to changes in behavior in humans and wildlife

(Scheuhammer et al. 2007). The most common acute, neurological effects are a loss of motor

skills, coordination and reduction in motivation (Wolfe 1998; Scheuhammer 1987). In captive

mallards (Anasplatyrynchos) (Heinz 1979) 3 ppm (wet weight in diet) methylmercury caused

changes in the duckling flight response, brain lesions and demyelination of neurons (Heinz and

Locke 1976) and 5 ppm (wet weight in diet) methylmercury caused decreases in weight and

appetite in Great Egrets (Ardea alba) (Spalding et al. 2000a) along with changes in hematology,

neurology and histology (Spalding et al. 2000b). Nocera and Taylor (1998) found

methylmercury exposure to be correlated with behavioral changes in young Common Loons

(Gavia immer). Bouton et al. (1999) found that at a much lower dose, (0.5 mg/kg ww in diet)

juvenile Great Egrets showed decreased activity, altered thermoregulatory behavior, and

decreased motivation to hunt. Although there appeared to be no effect of mercury dose upon

foraging efficacy, any potential effects seemed confounded by individual foraging strategies.

There are direct and indirect links between methylmercury exposure and learning; first,

methylmercury has been suggested to alter thyroid hormones in vertebrates (Facemire et al.

1995), which has been correlated to changes in testosterone, estradiol, and perhaps progesterone

in the White Ibis (Eudocimus albus) (Heath 2002). Estrogens, androgens, thyroid hormones and

glucocorticoids have important roles in brain development; steroid hormones are involved in

critical to early development (Schlinger 1997) and song learning in passerines (Gahr 2004) and

hippocampal (i.e. spatial) learning, while thyroid (Schantz and Widholm 2001; Zala and Penn









2004) and glucocorticoid (Kitayski 2003; Zala and Penn 2004) hormones help regulated nervous

system development, and impact learning and memory. Prenatal exposure to methylmercury in

humans can lead to learning disabilities later in the life of the child (Grandjean et al. 1997).

Therefore, it seems reasonable to expect low level methylmercury exposure to have an impact on

learning in other vertebrates. However, the level of mercury necessary to induce this kind of

effect is unknown.

Behaviors under high levels of hormonal control are at risk of changing in response to

endocrine disrupting chemicals (EDCs) like methylmercury and such changes may have a large

impact on important ecological and demographic parameters (Vos et al. 2000). Avian behaviors

linked to changes in the hypothalamus-pituitary-adrenal axis and its associated hormones may

also impact foraging rates and suppression of breeding behavior (Wingfield et al. 1998). Steroid

hormones influence a variety of physiological parameters (i.e., metabolism), and behaviors (i.e.,

territoriality, foraging rates, courtship, incubation) (Ketterson and Nolan 1992). A wide variety

of behaviors are tightly linked with endocrine function and may therefore be susceptible to

EDCs, including courtship and breeding behaviors, altered social and dominance behaviors, and

learning (Zala and Penn 2004).

We report here on an experimental examination of the effects of low, chronic doses of

methylmercury on the ability of naive juvenile White Ibises to forage in differing levels of

habitat complexity. White Ibises (hereafter, ibises) are a tactile-foraging aquatic bird that

forages in flocks on crabs, crayfish, insects and small fish in a variety of aquatic habitats

(Kushlan 1974). Foraging efficiency is directly linked with conditions that produce high

availability of prey (Frederick and Collopy 1989; Gawlik 2002), and this parameter has high









biological relevance because food intake can be related to reproductive success (Frederick and

Collopy 1989; Frederick and Spalding 1994; Frederick 2001).

We hypothesized that the learning of novel foraging behaviors may be more difficult for

birds exposed to methylmercury at environmentally realistic levels. In this experiment we

attempted to test the specific prediction that mercury would impair the ability of ibises to forage

in the context of increasing difficulty-in this case, structural complexity in the foraging arena.

We tested the assumptions that 1) increasing structural complexity would decrease capture rates,

and 2) foraging efficiency would increase over the weeks of the experiment. We used foraging

efficiency (prey depleted in a given time) and motivation (numbers of birds attempting to forage

over time) of groups of foraging ibises as response variables to four different exposure levels of

mercury.

Methods

We used 168 captive White Ibises in a large, free-flight aviary at the US Department of

Agriculture Wildlife Research Center in Gainesville, FL, USA to conduct this experiment.

These birds were collected as nestlings at 10-35 d of age from breeding colonies in the northern

Everglades (Broward Co., FL, N 260 11.179, W -80 31.431) and from White Springs, FL, USA

(Hamilton Co, FL, 30019.900 N, -82045.367 W) (Ch. I). Young birds were randomly assigned to

one of four dietary exposure groups receiving 0, 0.05, 0.1, or 0.3 mg/kg methylmercury (wet

weight in diet) after 90 d of age. Exposure groups were housed in the same circular, open-air

aviary (cf. 1200 m2) separated into quadrants by interior net walls. These levels of exposure

mimic the range that might be encountered in the Everglades (Frederick et al. 2002; Loftus

1999).

This experiment was run from 11 Oct to 17 Nov 2005. During each daily bout, all

treatment groups were simultaneously presented with 200 live fathead minnow juveniles









(Pimephalespromelas) in 2.4 x 3.7 m rectangular foraging pools between 0800 and 0900 h. All

groups were given access to the fish for 15 min. The foraging arenas were all similar, and had

continuously varying water depths of 2-15 cm as a result of a sloping floor. Water depth was

standardized for each experimental run each morning because of the possibility of prey

availability differing with water depth (as mentioned above) and we placed varying levels of

physical structure (see below). All cages were deprived of food starting at sundown the night

before each bout, and food was restored ad libitum after each bout. All bouts were video

recorded and reviewed later to determine how many birds participated at standard times in each

bout.

The experiment was run for six weeks, and during each week each cage experienced four

bouts in a total of four different levels of structural complexity. No more or less than one bout

was experienced on any day by any treatment group, and on any one day no two cages would be

assigned the same structural complexity level. Daily and weekly order of habitat complexity

given to each treatment was pseudorandom. We used four levels of structural complexity: 1)

Open pools, 2) pools with panels of agricultural fencing (mesh size ranging from 13-38 cm)

supported approximately 3 cm off the bottom of the pool and occupying the entire surface of the

pool), 3) the same as #2 but we attached six pieces of 1 m by 1 m shade cloth and about 30

artificial plant leaves-evenly spaced-to the panels, and 4) Same as #2 but with 16 pieces of

shade cloth and about 60 artificial plant leaves/fronds. All shade cloth and plastic plants

provided a partial visual and physical barrier, but were flexible and did not make any area of the

arena inaccessible to the foraging ibises.

After birds had foraged for 15 min, two researchers entered the cages and placed large

pieces of shade cloth over the foraging arena to ensure that no more foraging could take place.









Once foraging was stopped in all cages we drained the foraging arenas through a seine net, and

counted the remaining fish.

The video recordings were used to obtain an accurate measure of the number of birds in

each treatment group that were foraging at standardized times. Each video was analyzed by

stopping the tape 30, 60, 240, 420, 600, 780 s into the experiment and the number of ibises in

(not around or on the edges of) the wading pool were counted. We estimated the total number of

bird-minutes foraged during the entire bout by using rectangles bounded by the total time

foraged and the number of birds to estimate the area under the curve. This approximation was a

consistent underestimate of the true area under the curve.

We used a repeated measures general linear model for analysis. The response was

proportion of fish remaining and the dependent variables were day, week, methylmercury

exposure group, and structural complexity. We modeled the proportion of fish remaining adding

1 to the number of fish remaining and the number given (to eliminate zeroes) and transforming

these data with an arcsine square root. This transformation was found to produce a set of

residuals with an approximately normal distribution. We also modeled group motivation with

the same factors to test our assumption of equal motivation. We used ANOVAs to compare

numbers of birds foraging across exposure groups while controlling for the effects of structural

complexity. We selected models from a base apriori set using backward selection. The linear

models were analyzed using SAS v. 7.2 (PROC MIXED) and all other statistics were analyzed

using JMP IN v. 5.1. Alpha was equal to 0.05.

Results

Time, structural complexity, and exposure group were all determined to be important

variables apriori, and were all included as main effects in our best model (Table 2-1). However,

while structural complexity showed a significant (and quadratic) relationship with time,









methylmercury exposure did not. The resulting model fit well and all these terms were

considered to be biologically important and plausible. The repeated measures aspect of our

analysis (date) explained a small amount of the variance; this implies that our Latin square

experimental design was effective in removing the potential bias of day effect. While there was

an effect of mercury dose group on foraging, it was small by comparison with effects of

structural complexity and time.

The hypothesis that structural complexity would decrease foraging efficiency was

supported by this experiment (Fig. 2-1). Foraging efficiency decreased with increasing

vegetation/structure (Table 2-2), and this effect varied with time. When compared to the highest

group of habitat complexity the lowest two levels showed significantly faster learning (the

time*complexity effect) but no significant non-linear change in their improvement (the

time*time*complexity effect). While the medium complexity level did not differ from the high

in linear improvement, there was a significant non-linear effect and had significantly less fish

remaining independent of time. Thus, the hypothesis that feeding efficiency would increase over

time was supported and the degree of improvement was related to degree of structural

complexity.

Although we predicted that methylmercury exposure would decrease foraging efficiency,

result in a change in foraging efficiency over time, or both, in a dose dependent fashion we did

not find any interaction of treatment group with time. The medium dose group has the most

efficient foragers, the low dose group has the second most efficient and the control and high dose

being almost equally less efficient than the other two groups (Fig. 2-2). Statistically, the control

and high dose were similarly worse than the low and medium groups (Table 2-2). Contrary to

our predictions, this relationship was highly nonlinear.









One assumption of the experiment was that foraging efficiency during the bout would not

decline as a result of decreased motivation. The number of birds foraging during the course of

the bouts was first analyzed as a response variable by using the same model and dependent

variables. This model showed no significant effects. When the model was stripped down to the

main effects, complexity was found to be significant (P<0.O001) while time and exposure group

were not. In summary, our attempt to control motivational differences between exposure groups

via temporary food restriction appears to have been successful.

Discussion

One of our objectives was to establish a foraging environment that offered enough

challenge to motivated foraging groups that it would gradually decrease foraging efficiency.

This was achieved, as evidenced by the inhibitory effect of increasing structural complexity. We

also wanted to establish an environment in which the birds might learn how to improve foraging

efficiency over time and thus test whether learning might be affected by treatment. We also

achieved this goal, since we found an effect of time on foraging efficiency at all levels of

foraging difficulty. Although we found a significant effect of methylmercury exposure in this

experimental context, methylmercury did not have the expected linearly increasing effect; the

middle two exposure groups were more efficient foragers than the control and high dose groups.

More to the point, our strongest prediction was that the high and control treatment groups should

provide the greatest contrast in mercury effects, yet they were not significantly different.

Controlling for group motivation also proved successful and differences between exposure

groups are not due to differences in participation.

Over time, all treatment groups improved in their foraging efficiency, with no interaction

with dietary methylmercury exposure. Our results do indicate that all cages learned at an

exponential rate (the time*time term in the model) when challenged by higher habitat complexity









and that the degree of improvement in foraging efficiency depended on the difficulty of the task

(the time*complexity and the time*time*complexity terms). The prediction that methylmercury

(at the dose rates given) would inhibit learning seemed to have little supporting evidence.

However, this finding does not rule out the possibility that learning may be affected at higher

dose rates or with different behaviors.

There are two potential explanations for the nonlinear effect of mercury seen in this

experiment: hormesis and/or confounding effects. Hormesis suggests that certain toxicants

stimulate an animal in apparently positive ways at low doses, yet cause negative effects at higher

doses (Noel et al. 2006; Calabrese 2005). This pattern has been found increasingly in studies of

endocrine effects, and especially with behavioral endpoints (Clotfelter et al. 2004). The amount

of methylmercury with which these birds were exposed could be considered quite low by

comparison with the existing literature on effects (Wolfe 1998), and it is possible that we

approached a threshold for hormesis.

There are two potential factors in the experimental setup that could confound effects of

methylmercury exposure: individual composition of groups, and location. Due to differences in

social structure of groups between cages and asymmetrical natural events (like the differential

effect of light or shade on different cage locations) we may be placing certain cages at a foraging

advantage over the others. While we cannot find any ready mechanisms that suggest such a

location effect, we also cannot rule such an effect out, since we had only a single replicate for

each group.

Increasing structural complexity made it more difficult for ibises to forage. Our

measurement of motivation indicates that higher structural complexity encourage more birds to

forage longer; despite such differences there were still large differences in foraging efficiency









between complexity groups. While availability of prey to visual and tactile aquatic birds is

known to be affected by prey density, hydroperiod, temperature, dissolved oxygen and water

depth (Maccarone and Brzorad 2005; Smith et al. 2003; Gawlik 2002; Frederick 2001) the effect

of vegetation and obstructions has received relatively little attention (Bancroft et al. 2002;

Surdick 1998). Although the ibises showed improvement in the more challenging habitat

structure, they never achieved the levels of efficiency seen in the low complexity environment.

Although such an effect has been suggested by habitat selection studies of wading birds (Stolen

2006; Surdick 1998; Bancroft et al. 1994), we believe this is the first experimental demonstration

of an experimentally measured effect of structural complexity for foraging by long-legged

wading birds. It therefore seems likely that vegetation density and type is an important

determinant of foraging success and habitat selection for tactile-foraging waders.









Table 2-1. Overall effect of factors in our best model. Significance was determined using an F-
test based on Kenward-Rogers degrees of freedom estimation.


Effect
Time
Exposure Group
Time*Time
Structural Complexity
Structural Complexity*Time
Structural Complexity*Time*Time


P-value
<.0001
0.0038
<.0001
<.0001
<.0001
0.0061


Table 2-2. Parameter estimates from the best model (PROC MIXED). Note that Beta values are
relative to the control group in the case of methylmercury exposure and the high
group in the habitat complexity.


Effect
Time
Time*Time
Methylmercury Exposure





Habitat Complexity





Habitat Complexity Time





Habitat Complexity Time *Time


Parameter
estimate (p)
-0.354
0.03337


Control
Low
Medium
High

High
Medium
Low
Control

High
Medium
Low
Control

High
Medium
Low
Control


-0.07665
-0.09188
-0.00482


-0.4599
-1.0468
-1.2913


0.007242
0.2388
0.3547


0.006126
-0.02057
-0.03347


Standard
error
0.06221
0.008699


0.03069
0.03069
0.03069


0.1345
0.1345
0.1345


0.08797
0.08797
0.08797


0.0123
0.0123
0.0123


P-value
<.0001
0.0002


0.0145
0.0036
0.8756


0.001
<.0001
<.0001


0.9346
0.0081
0.0001


0.008
0.0983
0.6199


































A


08


E
a 06






a 02



00









10.


08


E 06
o

























- 04
0
a)





2
a0


\
0 -'

V^-- _&^r'


o7
0 \
t.. \


0 1 2 3 4 5 6 7 0 1 2 3 4 5 6 7

Time (week) Time (week)

Figure 2-1. Mean proportion of fish remaining for each week for each methylmercury exposure

group for A) complexity level 1 (control), B) complexity level 2 (low), C) complexity

level 3 (medium), D) complexity level 4 (high).


2 3 4 5 6 7 0 1 2 3 4 5 6 7

Control
o Low
------ Medium
-^- High
,,-


) 1

















o) MI No complexity
0.4 l Low complexity
.7z Medium complexity
:E High complexity

) 0.3-

0



r-
0.2 -
0







0.0
Control Low Medium High

Treatment Group





Figure 2-2. Mean proportion of prey remain grouped by methylmercury exposure group and
structural complexity over all weeks. Error bars represent standard error of the mean.









CHAPTER 3
SUBLETHAL EFFECTS OF METHYLMERCURY ON TESTOSTERONE, ESTRADIOL,
AND CORTICOSTERONE FECAL METABOLITES IN CAPTIVE JUVENILE WHITE
IBISES (Eudocimus albus)

Introduction

Methylmercury is a globally distributed contaminant that has a wide range of endocrine

disrupting, neurological, and developmental effects in animals (Wolfe et al. 1998) with

significant differences between avian species (Heinz et al. 2006). Within an environmentally

relevant exposure range however, endocrine effects have not been well studied, especially in

birds. Increased levels of methylmercury in feather samples over the past thirty years are also

indirectly correlated with a decrease in number of breeding White Ibises (Eudocimus albus) in

the Florida Everglades, where mercury contamination has been high (Heath and Frederick 2005).

Heath and Frederick (2005) showed that methylmercury in breeding White Ibises was correlated

with a decrease in estradiol in females and an increase in testosterone in males. In Common

loons (Gavia immer) Evers et al. (2003) demonstrated a positive association between blood

mercury concentrations and blood corticosterone levels and Nocera and Taylor (1998) correlated

mercury exposure with changes in chick behaviors. In contrast, Thaxton et al. (1982) showed a

decrease in corticosterone with increasing methylmercury in chickens (Gallus domesticus) and

Heath and Frederick (2005) found no relationship between mercury exposure and corticosterone

in breeding White Ibises. Methylmercury exposure is correlated to changes in endocrine

function; however such changes are sensitive to species, dose range, and season.

The mechanism by which mercury exposure affects endocrine function in birds is also

unknown. Methylmercury may impact the endocrine system of birds in ovo, during the rapid

growth stage as nestlings, as non-breeding juveniles. Alternatively, there may be no

developmental aspect to the effect, and methylmercury exposure as an adult may be the primary









route by which adult breeding is affected. Currently, evidence for methylmercury as an

endocrine disrupting chemical (EDC) in birds is solely correlative; a causal relationship between

exposure and endocrine function needs to be demonstrated.

The case for causal relationships between various EDCs and birds is strong; effects in birds

have been commonly found using the steroid hormones estradiol (MacLellan et al. 1996; Giesy

et al. 2003) and testosterone (Colbom et al. 1993; Giesy et al. 2003) along with corticosterone

(Baos et al. 2006; Thaxton et al. 1982), a hormone that is part of the hypothalamus-pituitary-

adrenal stress axis. Estradiol is the sex determining hormone in early development (Bigsby et al.

1999) and is correlated with breeding cycle as adults (Wingfield and Farner 1978; Maguet et al.

1994). Testosterone has been linked to territoriality (Beleskey et al. 1990) and mating behaviors

(Wingfield 1984; Brunstrom et al. 1999). Corticosterone plays an important role in coping with

environmental stressors (Harvey et al. 1984; Kitaysky et al. 1999; Marra and Holberton 1998;

Holberton et al. 1999).

Currently, we lack causal evidence in support of the connection between changes in steroid

and glucocorticoid hormones and methylmercury exposure, however, most studies have not been

adequately designed to answer such a question and we believe this has yet to be fully explored.

As a result we lack strong evidence connecting endocrine changes to reproductive failure in birds

(Bosveld and van den Berg 2002). Field studies are primarily correlative when causality is

needed for decision-making, contaminant exposure may be correlated to confounded ecological

variables (Meyer et al. 1998), and multiple contaminants-with unknown synergies-may be

present at field sites (Tyler et al. 1998). Captive studies may be difficult to generalize to a free-

living population of interest by selecting ecologically irrelevant endpoints (Zala and Penn 2002;

Chapman 2002), species selection (Ottinger et al. 2005), and differential endpoint sensitivities









(Clotfelter et al. 2004). Complicating issues further is our lack of knowledge of endocrine

disruption in juvenile birds and the effect this may have on adults; in mammals, EDCs can delay

the onset of juvenile sexual maturation (Marty et al. 1999). Such relationship may exist in EDC-

exposed juvenile birds, however, no studies have looked at this experimentally.

The available literature therefore suggests that methylmercury exposure in birds could be

altering expression of hormones that are important for development and reproduction. If these

effects exist, they may have the potential to result in population change, by affecting survival and

fecundity rates. Here, we report on a study of the effects of mercury on endocrine function in a

developing juvenile aquatic bird, the White Ibis, using a controlled experimental approach. We

studied the White Ibis because there is considerable information on its breeding ecology

(Kushlan 1974; Kushlan and Bildstein 1992; Bildstein 1994; Frederick 1987a; Frederick 1987b),

because there are demonstrated effects of methylmercury on endocrine function in adult birds

(Heath et al. 2003), and because the species continues to be exposed to methylmercury in the

wild (Frederick and Heath 2005). We measured estradiol, testosterone, and corticosterone

metabolites in fecal samples, and used an environmentally relevant range of experimental

mercury exposures. We hypothesized that increasing exposure to methylmercury would

significantly alter fecal estradiol, testosterone, and corticosterone concentrations in a dose-

dependent fashion.

Methods

Study Site

We used an experimental approach by measuring endocrine responses of captive White

Ibises that were exposed to differing levels of methylmercury through their diet. In April 2005,

wild-caught White Ibis nestlings were raised in four dose groups in a large free-flight aviary. The

aviary was circular (21 m radius, 10 m tall) and divided into quadrants with net walls. The









interior of the aviary contained numerous perches, artificial nest cups and a feeding/loafing pool.

We fed all birds in each enclosure on a different diet containing methylmercury: control, 0.05

ppm MeHg, 0.1 ppm MeHg, and 0.3 ppm MeHg (all values in diet, wet weight). The flooring

was impermeable PVC sheeting that drained towards a common central drain. White Ibises were

collected as 25-32 d old nestlings from the northern Everglades (Water Conservation Area 3,

Broward Co. Florida, N 260 11.179, W -80 31.431) and from a colony near White Springs,

Hamilton Co., Florida (N 300 19.900, W -82 45.367). The Alley North birds were collected on

14, 17, 19, and 21 April 2005 and transported overnight to Gainesville, FL (see also Chapter 1).

We sexed, weighed, measured, banded and removed approximately 4 scapular feathers for

mercury analysis from all nestlings before randomly distributing them to enclosure/exposure

groups.

Methylmercury was administered via diet beginning at 90 d of age by dissolving MeHgCL

into corn oil and spraying the mixture onto Flamingo diet pelletized feed (Mazuri Company,

Brentwood, MO, USA) while the mass was being rotated in a cement mixer in 11.3 kg batches.

Each dose group had a complete set of glassware and mixing devices (including cement mixers)

dedicated solely to that dose regime. Stock solution concentrations of methylmercury were fine

tuned by direct measurements of mercury content of food prior to the onset of feeding to ibises.

Dose regime was also verified by determining mercury concentrations of scapular feathers

(Frederick et al. 2002) in January of 2006 and 2007 using standard cold vapor techniques (Figure

3-1).

Fecal Hormone Sampling Technique, Storage and Extraction

Steroid and corticosteroid hormones are most commonly measured in the blood plasma of

animals. However, a number of recent studies (Creel 2001, Palme et al. 2005, Wasser and Hunt

2005, Hinson and Raven 2006) have demonstrated that useful hormone levels can also be









obtained from fecal samples. The latter sampling method is noninvasive, thus avoiding the need

to correct for short term stress response. In addition, hormone levels in feces represent an

integration of fluctuating hormone levels over the gut passage time, which allows for a more

reliable measure of baseline hormone levels (Tyler et al. 1998). Potential difficulties with the

method include validating the relationship between blood hormones and fecal metabolites, and

developing effective extraction techniques (Goymann 2005).

We collected fecal samples on clean black plastic sheeting placed below perching

structures, and identified feces of individual ibises by observing excretion of individually banded

birds directly. The location, time, and band number of each excretion was recorded. On

collection days, we collected feces for two 1-hr periods separated by 1 hr (typically between

1100-1200 h and 1300-1400 h). During collection bouts we removed samples from the plastic

every 10 min. Two observers usually watched during each collection bout, and at each 10-min

interval both observers approached the plastic sheets at the same time and collected fecal

samples that were visually marked. Unidentified samples were crossed-out to avoid confusion.

If unidentified samples were in very close proximity (e.g., within 0.5 m) to the sample of

interest, the sample was considered contaminated and was not collected. We estimated through-

put time (time from ingestion to excretion) at 2-3 h using food marked with colored plastic

beads.

There were 4 collection periods during this study. The first was early June 2005

immediately before dosing began (when birds were ca. 90 d old), the second was late June

immediately after the initiation of dosing (ca. 110 d old), the third was late July 2005 (ca. 140 d

old), and the fourth was in late December 2005 and early January 2006 (ca. 290 d old).









Individual fecal samples were collected in 2 mL plastic cryotubes and placed in an ice-

filled cooler for no more than 3 hours until they could be stored at -200C temperature; all

samples were analyzed for hormone concentrations in May 2006. Fecal samples were

individually lyophilized and the dried and stable samples were then weighed and placed into

glass extraction vials. Samples that contained more than 0.05 g of sample were homogenized

and subsampled while samples that contained 0.05 g or less were used in their entirety.

Using a combination of techniques (Hunt and Wasser 2003; Wasser and Hunt 2005) we

used ethanol diluted by deionized water to extract hormone metabolites from the sample. We

added the ethanol to a measured amount of fecal hormone in a capped glass culture tube, and

used a multi-tube vortexer to shake the mixture for 30 min, cycling the vortexer on for 1 min and

off for the next. Culture tubes were then spun in a refrigerated ultra-centrifuge at 3000 rpm for

20 min. The resulting ethanol supernatant was decanted into clean culture tubes and placed in -

800C freezer for storage. We compared the extraction efficiency of 80% (20% deionized water),

90% (10% deionized water), and 100% ethanol solutions by adding a known amount of radio-

labeled hormone to standardized desiccated fecal matrix then performing the extraction

procedure. We used 80% ethanol because its extraction efficiency was highest when considering

all hormone tests (Table 3-1). All results were adjusted for mean extraction efficiency (estradiol

77%, testosterone 64%, corticosterone, 90%).

Radioimmunoassay

We tested each sample extract for estradiol metabolites using Estradiol 125I Coat-a-Count

RIA kits (Diagnostic Products, Los Angeles, CA, USA). We used the 3 h, room temperate

incubation for all samples. The manufacturer's protocol was used with 100 [tL of extract used

initially and dilutions used when needed. This kit has shown high accuracy and dependability in

previous avian fecal hormone studies (Wasser and Hunt 2005). The manufacturer-reported









antibody cross-reactivities were 10% for estrone, 4.4% for 6-Equilenin, 1.8% for Estrone-0-6-

glucuronide and less than 1% for all other tested steroids.

We tested for testosterone metabolites using Testosterone 125I double-antibody RIA kits

(MP Biomedicals, Solon, OH, USA). The manufacturer's protocol was used with 50 tL of

extract used initially and dilutions used when needed. This kit has been validated for fecal

metabolites previously in birds (Wasser and Hunt 2005) and other vertebrates (Hunt and Wasser

2003). The manufacturer reported cross-reactivities were 3.4% for 5a-dihydrotestosterone, 2.2%

for 5a-androstane-3p, 17p-diol, 2% for 11-oxotestosterone, and less than 1% for all other tested

steroids.

We tested for corticosterone metabolites using Corticosterone 125I double-antibody RIA

kits (MP biomedicals, Solon, OH, USA). The manufacturer's protocol was used with 50 gL of

extract used initially and dilutions used when needed. This and similar kits have been validated

in several avian fecal glucorticoid studies (Wasser and Hunt 2005; Ludders et al. 2001). The

manufacturer-reported cross-reactivites were 34% for desoxycorticosterone, 10% for

testosterone, 5% for cortisol, 3% for aldosterone, 2% for progesterone, 1% for androstenedione,

1% 5a-dihydrotestosterone, and less than 1% for all other tested steroids and glucocorticoids.

All kits were validated by running a set of internal standards into standard hormone extract

and hormone-stripped extract using the manufacturer's standard curve. In order to determine

whether the extraction matrix would interfere with the accuracy of the assay we tested for

differences between all curves for all kits and found none to be significantly different (ANCOVA

all P's> 0.22). Thus, we find our assay to be internally valid for each hormone.

Statistical Analysis

We looked for differences in hormone concentration due to treatment using a repeated

measures ANCOVA. Sampling was not uniform across sampling periods (i.e. certain individuals









were not represented in some sampling periods) so traditional repeated measures methods could

not be used. After averaging individual hormone concentrations for each collection for

immunoreactive estradiol (E) and testosterone (T) and for each day for corticosterone (CORT))

we took the natural log of the hormone concentration to normalize them. Because we wished to

correlate hormone values from the same individuals at different collection times, we used a

compound symmetry structure to the covariance matrix to link individuals (nested within

treatment) over time (SAS v. 9.1 PROC MIXED). We also used Kenward-Rogers calculated

degrees of freedom-a technique that has been shown to minimize Type I errors in repeated

measures studies with gaps in the data due to sampling inequity (Padilla and Algina 2004).

Using treatment group, time (either collection period or collection day as above), and sex as

main effects, we developed a set of 21 biologically relevant apriori models based on our

predictions (see Introduction). We included all possible combinations of the three terms up to

the most complicated model that included a time*treatment*sex term. We also included a

time*time interaction that allowed for non-linear changes in hormone concentration over time

but we did not allow this term to interact with other main effects. We included one term a

posteriori: a categorical grouping that compared the control group against all experimental

groups. Model selection was based upon AIC, (Burnham and Anderson 2002) and models were

ranked by AIC weight. The AIC method is invalid when used with data generated via restricted

maximum likelihood methods (REML) that are default in PROC MIXED, and we used standard

maximum likelihood methods instead.

Finally, in an effort to examine the possible effects due to individual variation in

methylmercury exposure within groups (Fig. 3-1) we regrouped each individual as being either

high or low methylmercury exposure based upon the median feather mercury quantity for each









exposure group. We then removed the apriori treatment factor (control, low, medium and high)

from the model and replaced it with the new (control, low-low, high-low, low-medium, high-

medium, low-high, and high-high) in the best model as previously selected by AIC. The new

parameter estimates are then indicators of difference from each new group and the control.

Alpha was set at 0.05.

Results

The model that best explained variation in E included treatment, sex, and time as main

effects with time*time and treatment*time interactions (Table 3-2). This model was

substantially better than all remaining models, with a difference in AIC, greater than two for the

next closest model. Fecal E metabolites showed an overall downward trend with time (Fig. 3-2),

and showed significant upward curvature via the time*time term (Table 3-4). Although the

effect of treatment was significant (F test, P<.0022), it was also nonlinear with respect to

exposure group. The medium dose group was the only group significantly different than the

control group, and high, low and control groups were not different. This pattern was also found

for the treatment*time interaction (F test, P<.0136) (Table 3-4). The medium group had less E

than all other groups, but relatively greater increase over time. Our aposteriori test of non-linear

dose-response relationship (control compared to all experimental groups) also ranked poorly

relative to our best model (AAIC= 4.8). Finally, although female ibises tended to have less E

than males, the difference was not significant and there was no overall effect of sex on E (Table

3-4).

Fecal T metabolites tended to decrease over time and showed few differences between

treatment groups (Fig. 3-3). Two models received similar support from the model selection

process. The top model included time, time*time, exposure group. The second-ranked model

(AAICc = 1) included time as a main effect and a time*time interaction (Table 3-2). However,









the top-ranked model is an aposteriori test of control versus all experimental groups combined;

we chose to analyze this model to test our prediction of methylmercury exposure with the caveat

that any effect is unpredicted. Looking at the results of the top model in greater depth, T

increased over time (F-test, P=0.0015) with a significant (F-test, P<0.001) negative parameter

estimate for the time*time interaction allows for concave curvature (and an overall decrease) of

T with increasing time (Table 3-4). The aposteriori treatment term did not show significant

differences between groups. Females tended to have less T than males, though the effect was

non-significant (e.g., P=0.6484).

Three models seemed to explain fecal CORT metabolite concentrations well (i.e., AAIC,<

2) (Table 3-2). The third model, however, was marginal compared to the first two, so we will

limit the discussion to the two top models. Further, the two top models had similar structure-

the only difference was the inclusion of the sex effect-so our discussion will focus upon the

more complicated model to test our hypothesis on the importance of sex. There was no obvious

trend in CORT over time (Fig. 3-4). The model shows an insignificant upward trend and a

significant negative time*time interaction suggesting concave curvature (Table 3-5). Treatment

group had a significant, nonlinear effect on CORT (F-test, P=0.0148). While no individual

exposure groups differed significantly from the control, both the low and high groups were

significantly different from each other. Females had lower levels of CORT than males, although

the effect of sex was not significant (Table 3-5).

In our analysis of within-group variance in mercury exposure showed differences

depending on hormone endpoint and exposure group (Table 3-6). Variance in methylmercury

effect appears to increase with increasing methylmercury exposure; the low group is relatively

consistent in direction and magnitude of effect. The medium and high group parameter estimates









show larger differences between there subgroups than the low groups, particularly in the CORT

endpoint.

Discussion

Our predictions about the relationship between methylmercury and the hormones studied

were not generally supported by our findings. The most consistently violated prediction was that

responses would be linearly related to methylmercury exposure. While we found effects of

experimentally administered methylmercury on hormones, all were non-linear. Methylmercury

exposure significantly altered E, although this result appeared to be driven by large differences

between the medium exposure group and all other groups. T showed no significant dose-

response relationship with all apriori tests of methylmercury exposure, although the aposteriori

test comparing the control and all other groups showed an apparent decrease in T with mercury

exposure. CORT varied significantly with methylmercury exposure, but the lowest mean

concentrations were found in the low exposure group and the highest in the high exposure group

with control and medium groups between the two. Our prediction that levels of steroid and

glucocorticoid hormones would be affected by sex were not supported by any of the tests.

Finally, our analysis of variation in intragroup methylmercury exposure did not aid in explaining

these nonlinear patterns as they did not suggest that higher intragroup exposure yielded a

response of greater magnitude; however, these data do suggest there are differences within these

groups and the high intragroup variance may be a product of exposure variance.

It is possible that the levels of mercury exposure were simply not high enough to have an

effect, and/or that effects of mercury were overwhelmed by random or confounding effects. For

example, the dose-dependent patterns identified in the E, T and CORT data sets may have been

confounded with location effect, since each treatment was represented by only one replicate. We

attempted to control for cage effect though physical and experimental design; the cages were









physically identical within a circular aviary that carried equal edge effects. We also chose

response variables that were measured by individual bird and used statistical techniques (like

repeated measures) that take use the individual as the base unit-albeit nested within exposure

group. Cage effect might also have derived from a cohort effect, whereby the makeup of

individuals in the group affected the endocrine expression within that group.

There appears to be no biologically significant explanation for the medium dose group

having more E than other groups; we therefore suggest that at the dose levels we use,

methylmercury has little effect on fecal E metabolites in juvenile ibises in the non-breeding

season. This conclusion is reinforced somewhat by the fact that there was no effect of sex on E

levels. Thus in first-year ibises, it may be that E has simply not been expressed to the degree that

it is in breeding adults, at which point there is a marked difference (Heath and Frederick 2005).

Thus the capacity for expressing E in juveniles may not have been tested during the juvenile

period, and so may not be a very good indicator of potential EDC effects.

With T, the only near-significant effect occurred when all experimental groups were a

posteriori combined and compared with the control-all apriori models that included the effect

of uncombinedd) methylmercury had little support from AIC. The pattern from this last analysis

suggested that the control group may have, on average, higher T levels than all others during the

non-breeding season. However, as with E, the lack of sexual differences in testosterone indicates

that expression of T is not very active during the juvenile period, and therefore may not be a very

useful indicator of endocrine dysfunction.

Thus while steroid hormones may be important to sexual differentiation in ovo and to the

timing and onset of breeding, there is little information on endocrine expression in developing

juvenile birds (though see Schlinger 1997 for information on hormones and song learning).









The significant effect of time in all models shows that T and E are changing, however, the lack

of sexual differences imply that these changes are not related to reproduction or differential

sexual development. While we have found patterns that suggest an effect of methylmercury

exposure on E and T levels in developing ibises, the patterns are not supportive of a linear dose

response relationship, and the most likely explanation appears to be that these endpoints may be

insensitive to methylmercury exposure.

Effects of methylmercury on fecal corticosterone metabolites are more explicable as non-

linear responses have been reported in this endpoint. In the American Kestrel (Falco

sparverius), Love et al. (2003) found that plasma CORT levels varied similar to an inverted

parabola when compared to liver EDC load. This apparently hormetic pattern may be due to the

multiple roles that CORT plays in the physiological function of birds. Short-term increases in

CORT can be caused by environmental stressors like heat, handling or capture, cohabitating with

conspecifics, and food consumption (Siegel 1980). In wild migrating birds high baseline CORT

suppresses the acute CORT increase, at least in response to handling stress (Holberton et al.

1996). It is possible that high, chronic levels of methylmercury simulate high levels

physiological stress or disease, resulting in an increase in baseline CORT. The lower exposure

levels could be causing a decrease in baseline CORT by either mechanistically altering

hormonogenesis or by providing low enough levels of physiological stress to downregulate the

production of CORT. Further research is needed to evaluate these as explanations for the pattern

we have reported.

Potential (non-exclusive) hypotheses explaining these findings are (1) that

methylmercury does not alter the steroid hormones at these dose levels, and (2) that

methylmercury does not alter steroid hormones in juvenile ibises. We have no direct evidence









for supporting or rejecting either hypothesis, although the earlier work of Heath (2005) suggests

strongly that there is an effect of mercury on expression of these hormones in wild breeding

adults. Since the dose levels in this study spanned the range of exposures estimated in the wild

birds studied by Heath (2003), we believe the mercury effect seen in adults may simply not be

manifested in young birds. It is also possible that there is something about the captive situation

other than methylmercury exposure (lack of typical stressors, social environment, etc) that has

blocked an effect of methylmercury on steroid hormones.

In conclusion, we found immunoreactive fecal estradiol, testosterone, and corticosterone

levels were changing over time in captive juvenile White Ibises. While estradiol and

testosterone showed an effect of dose, only corticosterone changed in manner that seemed to be

explicable on biological principles. We suggest future studies of endocrine effects of

methylmercury might profitably focus on endocrine expression during the breeding season, since

the results with juveniles were inconclusive.









Table 3-1. The average extraction efficiencies for each hormone by percent ethanol used for
extraction.
Percent
ethanol Estradiol Testosterone Corticosterone
80 77% 64% 90%
90 72% 62% 98%
100 38% 80% 102%

Table 3-2. Ranking of various models for all hormone metabolites by Akaike weight. Only
models with a weight greater than 0.01 were included.
Akaike
Hormone Model AICc AAICc weight
Estradiol time sex trt time*time time*trt 260.8 0 0.4697
time sex trt time*time sex*time trt*time 262.9 2.1 0.1643
time time*time trt 264.2 3.4 0.0858
time time*time 264.3 3.5 0.0816
time sex trt time*time 265 4.2 0.0575
time time*time sex 265.4 4.6 0.0471
time time*time control 265.6 4.8 0.0426
time sex trt time*time time*trt sex*trt 267 6.2 0.0212
time sex trt time*time sex*time 267.2 6.4 0.0191

Testosterone
time control time*time 158.7 0 0.4663
time time*time 159.7 1 0.2828
time sex time*time 161.7 3 0.1040
time trt time*time 161.9 3.2 0.0941
time sex trt time*time 163.9 5.2 0.0346
time sex trt time*time sex*time 166 7.3 0.0121

Corticosterone
time sex trt time*time 380.8 0 0.2350
time time*time trt 380.8 0 0.2350
time sex trt time*time time*trt 382.6 1.8 0.0955
time sex trt time*time sex*time 382.9 2.1 0.0822
time time*time 384.1 3.3 0.0451
time sex trt time*time sex*time trt*time 384.8 4 0.0318
time sex trt time*time sex*trt 384.9 4.1 0.0303
time time*time sex 384.9 4.1 0.0303
time time*time control 386.2 5.4 0.0158
time sex trt time*time sex*time sex*trt 386.9 6.1 0.0111
time sex trt time*time time*trt sex*trt 387.3 6.5 0.0091










Table 3-3. Estradiol parameter estimates from our best model selected by AIC with their
respective standard error of the estimate. P-value is determined using an F-test. Note
that treatment and sex effects are categorical and the control and male groups,
respectively, act as a reference and all others are estimated relative to that group.
Model Parameter Standard
parameter estimate (p) error P-value
Time -0.6394 0.1379 <.0001
Time*Time 0.052 0.066
Sex Male
Female -0.05325 0.0521 0.3089
Treatment Control
Low -0.08078 0.1253 0.5199
Medium -0.4526 0.1318 0.0007
High -0.09285 0.129 0.4723
Time*Treatment Control
Low 0.004207 0.0294 0.8862
Medium 0.1002 0.0348 0.0044
High 0.03288 0.031 0.2901

Table 3-4. Testosterone parameter estimates from our best model selected by AIC with their
respective standard error of the estimate. P-value is determined using an F-test. Note
that treatment and sex effects are categorical and the control and male groups,
respectively, act as a reference and all others are estimated relative to that group.
Model Parameter Standard
Parameter estimate (p) error P-value
Time 0.1547 0.0481 0.0015
Time*Time -0.02085 0.005 <.0001
Treatment Control
Experimental -0.09756 0.0542 0.0737

Table 3-5. Corticosterone parameter estimates from our best model selected by AIC with their
respective standard error of the estimate. P-value is determined using an F-test. Note
that treatment and sex effects are categorical and the control and male groups,
respectively, act as a reference and all others are estimated relative to that group.
Model Parameter Standard
Parameter estimate (p) error P-value
Time 0.002567 0.002 0.195
Time*Time -0.00002 9E-06 0.0351
Sex Male
Female -0.1065 0.0732 0.1486
Treatment Control
Low -0.17 0.0978 0.0851
Medium -0.0174 0.1006 0.865
High 0.14 0.0969 0.151









Table 3-6. Parameter estimates, standard errors and P-values (t-test) for each treatment group
subdivided by median feather mercury quantities (Fig. 1) for each hormone. The
treatment grouping was added to our best model selected by AIC. The parameter
estimate is for the highest order term that includes treatment; estradiol is
treatment*time, testosterone is treatment, and corticosterone is treatment. All
parameter estimates are relative to the control group.
Parameter Standard
Hormone Treatment Group Estimate (0) error P-value
Estradiol
Control
Low-Low 0.0139 0.0349 0.6917
High-Low -0.0160 0.0353 0.6498
Low-Medium 0.1402 0.0505 0.0060
High-Medium 0.0771 0.0399 0.0548
Low-High 0.0010 0.0394 0.9795
High-High 0.0578 0.0354 0.1046

Testosterone
Control
Low-Low -0.1524 0.0794 0.0575
High-Low -0.1067 0.0760 0.1628
Low-Medium -0.0907 0.0815 0.2677
High-Medium -0.1531 0.0828 0.0662
Low-High -0.1143 0.0805 0.1584
High-High -0.0268 0.0751 0.7223

Corticosterone
Control
Low-Low -0.1745 0.1177 0.1416
High-Low -0.1880 0.1168 0.1108
Low-Medium 0.1096 0.1229 0.3745
High-Medium -0.1078 0.1249 0.3897
Low-High 0.2258 0.1201 0.0631
High-High 0.0456 0.1126 0.6865

















*
40



30 S
0)

S 20

LL

10
20 /







Control Low Medium High

Treatment Group



Figure 3-1. Feather mercury levels for individual birds in each exposure group. Data are
presented in box plots with outliers represented as dots, the gray box showing where
50% of the data lie, the line in box is mean.
















100


E

80-
.Q
0Q


.0 60
CU



o 40



U Control
S20- -m-- Low
S_--.--_. Medium
S...... ...... High
U-
0-
0 14 50 214

Days After Experiment Start
Figure 3-2. Mean estradiol concentration by treatment group for each collection period. Error
bars represent the standard error of the calculated mean and do not consider
intracollection dependency issues as our statistical models do.














100



80



60



40



20



0


--Control
- -- Low
-- -A- Medium
........ ........ H ig h


Days After Experiment Start
Figure 3-3. Mean testosterone concentration by treatment group for each collection period.
Error bars represent the standard error of the calculated mean for each collection
period and do not consider intracollection dependency issues as our statistical models
do.


















0- 350

30 Control
o 300 Low
--A.--- Medium
......... ........ H ig h
250 H
0
S 200-


o 150

0
100 -


1 50 -
o

0
c

S -50 0 50 100 150 200 250

Days After Experiment Start


Figure 3-4. Mean corticosterone concentration by treatment group for each collection period.
Error bars represent the standard error of the calculated mean for each collection
period and do not consider intracollection dependency issues as our statistical models
do.









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BIOGRAPHICAL SKETCH

Evan Adams was born and raised in Richland, WA, where he decided to delve into

science at an early age with his investigation on how to protect strawberry plants from

herbivory. Soon after, he began working for the local National Laboratory in particle

physics. He earned an honors Bachelor of Arts in biology from Whitman College in

Walla Walla, WA. There he discovered his true love for tropical avian ecology. In August

2007, he received his master's degree in wildlife ecology and conservationfrom the University

of Florida, focusing on avian ecotoxicology. He plans to start his doctorate at the University of

Maine, studying the ecology of neotropical migratory birds.





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1 EFFECTS OF CHRONIC AND LOW METHYL MERCURY EXPOSURE IN JUVENILE WHITE IBISES ( Eudocimus albus) By EVAN M. ADAMS 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 2007

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2 2007 Evan M. Adams

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3 To my parents, for encouraging me to explore

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4 ACKNOWLEDGMENTS First, I would like to thank the Florida De partment of Environmental Protection and specifically Don Axelrad for having the vision to see this project through. I thank Peter Frederick for being willing to take risks (on me and science) and my committee for their guidance. I owe Mary Christman and Iske Larkin a great deal of thanks for all the statistics consulting and radioimmunoassay tu toring, respectively. This wo rk was supported by Florida Department of Environmental Protection, the Un ited States Army Corps of Engineers and the United States Fish and Wildlife Service.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS...............................................................................................................4 LIST OF TABLES................................................................................................................. ..........6 LIST OF FIGURES................................................................................................................ .........7 CHAPTER 1 SEX-RELATED MORTALITY DUE TO A ST ARVATION EVENT IN WHITE IBIS ( Eudocimus albus ) IN THE FLORI DA EVERGLADES.......................................................10 Introduction................................................................................................................... ..........10 Methods........................................................................................................................ ..........11 Results........................................................................................................................ .............12 Discussion..................................................................................................................... ..........13 2 EFFECTS OF METHYLMERCURY AND SPATIAL COMPLEXITY ON FORAGING BEHAVIOR AND EFFICIEN CY IN JUVENILE WHITE IBISES ( Eudocimus albus )..................................................................................................................19 Introduction................................................................................................................... ..........19 Methods........................................................................................................................ ..........21 Results........................................................................................................................ .............23 Discussion..................................................................................................................... ..........25 3 SUBLETHAL EFFECTS OF METHYLMERCURY ON TESTOSTERONE, ESTRADIOL, AND CORTICOSTERONE FE CAL METABOLITES IN CAPTIVE JUVENILE WHITE IBISES ( Eudocimus albus)...................................................................31 Introduction................................................................................................................... ..........31 Methods........................................................................................................................ ..........33 Study Site..................................................................................................................... ....33 Fecal Hormone Sampling Technique, Storage and Extraction.......................................34 Radioimmunoassay..........................................................................................................36 Statistical Analysis..........................................................................................................37 Results........................................................................................................................ .............39 Discussion..................................................................................................................... ..........41 LIST OF REFERENCES............................................................................................................. ..52 BIOGRAPHICAL SKETCH.........................................................................................................62

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6 LIST OF TABLES Table page 1-1 The number of male and female nestli ngs captured for each collection date. The proportion of males captured is display pa renthetically after the column totals...............17 2-1 Overall effect of factors in our best model. Significan ce was determined using an Ftest based on Kenward-Rogers degrees of freedom estimation.........................................28 2-2 Parameter estimates from the best model (PROC MIXED). Note that Beta values are relative to the control gro up in the case of methylmercury exposure and the high group in the habitat complexity.........................................................................................28 3-1 The average extraction efficiencies fo r each hormone by percent ethanol used for extraction..................................................................................................................... .......45 3-2 Ranking of various models for all horm one metabolites by Akaike weight. Only models with a weight greater than 0.01 were included......................................................45 3-3 Estradiol parameter estimates from our best model selected by AIC with their respective standard error of the estimate. P-value is determined using an F-test. Note that treatment and sex effects are cat egorical and the control and male groups, respectively, act as a refere nce and all others are estimat ed relative to that group...........46 3-4 Testosterone parameter estimates from our best model selected by AIC with their respective standard error of the estimate. P-value is determined using an F-test. Note that treatment and sex effects are cat egorical and the control and male groups, respectively, act as a refere nce and all others are estimat ed relative to that group...........46 3-5 Corticosterone parameter estimates from our best model selected by AIC with their respective standard error of the estimate. P-value is determined using an F-test. Note that treatment and sex effects are cat egorical and the control and male groups, respectively, act as a refere nce and all others are estimat ed relative to that group...........46 3-6 Parameter estimates, standard errors a nd P-values (t-test) for each treatment group subdivided by median feather mercury quant ities (Fig. 1) for each hormone. The treatment grouping was added to our best model selected by AIC. The parameter estimate is for the highest order term that includes treatment; estradiol is treatment*time, testosterone is treatment, and corticosterone is treatment. All parameter estimates are relati ve to the control group........................................................47

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7 LIST OF FIGURES Figure page 1-1 The increase in mean mass corrected fo r tarsus length over collection date split by sex. N=21, 39, 68, and 49 in ascending order of collection dates. Error bars indicate the standard error of the mean for each data point.............................................................10 2-1 Mean proportion of fish remaining fo r each week for each methylmercury exposure group for A) complexity level 1 (control) B) complexity level 2 (low), C) complexity level 3 (medium), D) complexity level 4 (high).............................................29 2-2 Mean proportion of prey remaing grouped by methylmercury exposure group and structural complexity over al l weeks. Error bars represen t standard error of the mean...30 3-1 Feather mercury levels for individual birds in each exposure group. Data are presented in box plots with outliers repres ented as dots, the gray box showing where 50% of the data lie, the line in box is mean.......................................................................48 3-2 Mean estradiol concentration by treatm ent group for each collection period. Error bars represent the standard error of the calculated mean and do not consider intracollection dependency issues as our statistical models do.........................................49 3-3 Mean testosterone concentration by tr eatment group for each collection period. Error bars represent the st andard error of the calculated mean for each collection period and do not consider intracollection depe ndency issues as our statistical models do............................................................................................................................. ...........50 3-4 Mean corticosterone concentration by treatment group for each collection period. Error bars represent the st andard error of the calculated mean for each collection period and do not consider intracollection depe ndency issues as our statistical models do............................................................................................................................. ...........19

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8 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 EFFECTS OF CHRONIC AND LOW METHYL MERCURY EXPOSURE IN JUVENILE WHITE IBISES ( Eudocimus albus) By Evan M. Adams August 2007 Chair: Peter Frederick Major: Wildlife Ecology and Conservation Methylmercury is a global contaminant with reported neurological endocrine disrupting, and teratogenic effects that has been a problem sp ecifically in the Everglades ecosystem in South Florida. I used a free-flight aviary to hold White Ibises ( Eudocimus albus ) captive and allow the controlled delivery of dietary methylmercury to four exposure groupscontrol, 0.05, 0.1, and 0.3 mg/kg per day in diet, wet weight. My res earch has focused upon the sublethal effects of chronic, environmentally relevant exposure on the behavior and endocrine development in juvenile White Ibises. In this study I examine the method we used to capture 220 nestling White Ibises from two colonies in Florida and in the process monitored a colony-wide starvation event. During my week long collection pe riod in the Everglades I report a significant decrease in the proportion of females caught by my methods and re port on differences in size-corrected mass. In Chapter 2, I design an experiment testi ng the foraging efficiency of juvenile White Ibises in a group setting. Using stereotyped fora ging arenas with varying quantities of structural complexity, I allowed all exposure groups to a se t amount of time to forage upon a pre-defined number of small fish. I hypothesized that in creasing methylmercury exposure and increasing structural complexity would negatively affect a young ibises foraging efficiency and that increasing methylmercury would decrease this abil ity to improve foraging efficiency with time.

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9 I found that while structural complexity ha d a strong negative effect upon group foraging efficiency, methylmercury had a weak (though statis tical significant) effect that is non-linear with respect to exposure. The low and medium groups were the best foragers, while the high and control groups were the worst overall. Methylmercury did no t affect the improvement of foraging efficiency with time. In Chapter 3, I investigated the changes in f ecal estradiol, testosterone, and corticosterone metabolites over time with respect to methylmerc ury exposure group in juvenile White Ibises. I collected over 350 samples non-invasively from individual birds over 7 months and developed tests for each hormone of interest for this spec ies. I hypothesized that increasing methylmercury would impact estradiol, testoste rone, and corticosterone in dose -dependent fashion with respect to time and that sex would affect each hormone. I found that estradiol a nd testosterone did not change in any biologically explicable manner with respect to dose, and that sex was not important in determining steroid hormone levels. With corticosterone, I found that a significant non-linear relationship with met hylmercury exposure. While th is result was not predicted, a biological explanation of hormesis may explain these data. In conclusion, I found no linear relationships between endpointbehavior or endocrine functionand methylmercury exposure. White Ibis es may not be sensitive to methylmercury exposure at either 1) these dose ra nges or 2) while juveniles. Fu ture research during the breeding season will test these new hypotheses.

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10 CHAPTER 1 SEX-RELATED MORTALITY DUE TO A ST ARVATION EVENT IN WHITE IBIS ( Eudocimus albus ) IN THE FLORIDA EVERGLADES Introduction Sexually size dimorphic (SSD) avian species have often been found to exhibit sex dependent pre-fledgling mortalit y during periods of food limitati on (Hipkiss et al. 2002). This may be because larger sized nestlings have higher mortality due to greater nutritional need (Clutton-Brock 1985; Arroyo 2002; Laaksonen et al 2004; Bortolotti 1986; Anderson et al. 1993; Kalmbach et al. 2005), but there are also nu merous examples in which both the smaller sex has higher mortality as nestlings or juveniles (Nager et al 2000; Torres and Drummond 1999; Teather and Weatherhead 1989; Rsk aft and Slagsvold 1985). This suggests that a different mechanism of mortality must be acting upon these nestlings. Possible mechanisms include, large siblings dominating smaller ones (Oddie 2000), larger offspring be ing better able to withstand starvation or extreme temperatur e resilience (Greenberg 1979) and sex specific, size unrelated mortality (Mller et al. 2005) ar e potential mechanisms. Covariates linked to sex-related mortality that are independent of size and sex are brood size (Raberg et al. 2005), prey size (Anderson et al. 1993), prey availability (M cDonald et al. 2005), and hatching asynchrony (Gonzalez-Solis et al. 2005; Os treiher 1997); these factors influe nce the dynamics of sibling competition in nests and may determine whether a species or population exhibits significant sexrelated mortality. Here, we report on differential sex related mo rtality in young of the sexually dimorphic White Ibis ( Eudocimus albus ). Adult males are larger than females in most measurements of body size by roughly 15% (Babbitt and Frederick 2007; Kushlan 1977). A variety of selective costs and benefits to adults have been proposed for sustaining the sexual dimorphism (Bildstein

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11 1993; Petit and Bildstein 1987; Kushlan 1974; Babb itt and Frederick 2007), but there has been little research on the costs and benefits of SSD in nestlings. Breeding propensity and breeding success are larg ely limited by prey availability in White Ibises (Kushlan 1974; Kushlan and Bildstein 19 92; Frederick 2002). In south Florida, USA, patterns of surface water recession is typically asso ciated with highly available prey (fishes and crustaceans), while rising surface waters are typi cally associated with poor availability and abandonment of nesting (Kushlan 1974; Freder ick and Spalding 1994; Frederick and Collopy 1989; Gawlik 2002). In many years, nesting may be wholly or partly abandoned in response to unseasonable rainfall and associated water leve l increases (Frederick 2001). Incubation and hatching of eggs in this species is asynchronous, and a size differe ntial is typical for nestmates up to the approximate midpoint of the 40-50 d ne stling stage (Kushlan 1974). A sex related size differential is also typical of nestlings, ranging fro m very little at hatching to nearly adult ratios at fledging. In this paper, we document changes in s econdary sex ratio and body condition in nestling White Ibises during a widespread nest abandonment event resulting from a food shortage. Methods As part of a study of captive ibis behavior and reproduction we collected young ibises from 1) in the Alley North colony in Water Conserva tion Area 3 (WCA3) in the Florida Everglades (Broward Co. Florida, N 26 11.179, W -80 31.431) and 2) a colony in White Springs, Hamilton County, FL (30.900 N, -82.367 W). Alley North is one of the largest multispecies wading bird colonies in North Ameri ca and is composed of a 4-km long willow tree island/cattail complex in the northeast corner of WCA3. In an attempt to collect only the firsthatched chick (i.e., the largest nestling) of each brood we banded 300 nestlings before they could

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12 leave the nest (about 10 days old). The bands were individually numbered plastic spirals (National Band and Tag Co., Lexington, KY, USA). Some of the banded birds were re-captu red at 25 d on 14, 17, 19, and 21 April 2005 when they had become vagile and existed in la rge, somewhat mobile crches (De Santo et al. 1990). We collected birds using a combination of herding techniques to concentrate them, followed by capture by hand or with hand nets. All 21 birds collected on 14 April 2005 were banded, first-hatched nestlings marked previously (above). After this date we were able to discover no other banded birds, a nd so we collected any birds avai lable to our techniques. All birds were transported overnight to a free-fli ght aviary. The following morning prior to any feeding all birds were weighed, had both the culmen and tarsus measured, and blood samples (about 50 L) were drawn from the brachial vein. We used blood for DNA sexing (Fridolfsson and Hellegren 1999) at Avian Biotech (Tallahassee, FL). The White Springs colony was on an island with in a dredge-spoil lake. Here, we banded chicks between ca. 2 and 7 d of age and identifi ed the first-hatched ch icks by relative size and development. We sexed 60 first-hatched chicks by blood DNA, and returned a week later (ca. 10 d of age) to collect chicks. We used an ANOVA to examine size and mass corrected size (culmen length/total mass) by collection date and sex. The binomial test (exp ected value = 0.5) was used to test a departure from random for each collection period. All analyses were conducted using JMP IN v. 5.1. Results Prior to our first collection date there was evidence of co lony-wide nest abandonment at the Alley North colony. Dead chicks were a common sight beginning in early April and continuing through the collection dates. Circli ng vultures were observed during the first precollection foray into the colony where we banded first-hatched chicks. However, adults were

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13 still attending many nest s. The abandonments temporally co -occurred with sharp increases in water level due to heavy rains in middle and late March and again in ea rly April (Cook and Call 2005). Between the middle of March and April 21, local water levels increased by 22.9 cm. Over the course of the week-l ong collections of ibises at th e Alley North colony, the ratio of male to female chicks captured increased dr amatically (Table 1-1) We found marginally significant or significant departur es from a 50:50 male/female ratio on both the third and fourth collection dates (P= 0.0571 and 0.0427, respectively, binomial test) while birds collected from the first and second collection did not significantly differ from 0.5 (binomial test, P=0.662 and P=0.37, respectively). The sex ratio of first-hatched birds from the White Springs, FL colony, did not differ significantly from 0.5 (P=0.84, n=59, bi nomial test). The first collection in Alley North and the collection at White Springs only included first-hatched ne stlings and we found no evidence of sex ratio bias in the samp les of 21 and 69 birds, respectively. Body conditionas quantified bythe ratio of we ight (g) to tarsus length (cm)changed during the course of the one-week collections and was different between the sexes (Fig. 1-1). We found a significant effect of collection date and sex on mass/tarsus ratio (ANCOVA, P<0.001 for both tests), but found no significant inte raction (P= 0.6639). Both sexes increased in body condition index over time. While males ha d significantly higher condition indices than females, the rate of conditi on increase was virtually id entical between the sexes. Discussion Our data suggest that there were sex-relate d differences in mortality and body condition in 25-32 d White Ibis nestlings during a widespread food shortage event that this was not a result of sex bias in the hatch order. Water level had been increasing for about a month previous to our collection and such increases are associated with nest abandonment and limited prey availability in White Ibises (Russell et al. 2002,; Frederick and Collopy 1989; B ildstein et al. 1990; Frederick

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14 1987a; Gawlik 2002). We found no evidence of preda tion or disease at the colony; in fact, most dead ibis chicks were untouched by predators or scavengers. Although disease seems unlikely because no adult birds were found dead, it is sometimes difficult to determine if disease or parasites are causing nest abandonments and col ony failure (Frederick and Spalding 1994) and some SSD birds have been found to have sex-rela ted differences in immu nity (Fargello et al. 2003). However, the repeated ex amples of co-occurrence of food shortage and abandonment under very similar hydrological conditions (Frede rick and Collopy 1989; Frederick and Spalding 1994) lend strong support to interpretation of food shortage as a causative factor. We do not believe that the differences in sex ratio of captive birds were due to our capture techniques. The technique did not chan ge over the collection period and was not sizespecific in any apparent way. We also would not expect a size -biased collection technique to result in a changing capture sex ratio. The data indica te a linear pattern between sex ratio and collection only after the first (b iased) collection, with the late r three collection dates showing progressively larger departures from parity. Despite the statis tical difficulties with hypothesis testing in sex ratio studies due to small sample size when the expected values of a ratio is 0.5 (Ewen et al. 2002) our data showed biologically a nd statistically significant trends toward a male bias. We found that male body condition was higher than female condition on each collection date, though rate of increase in body condition over time was not different between the sexes. Size-corrected mass increased for both sexes ove r the sampling period which implies that these birds were not starving; however, our technique only sampled the li ve birds, not the many dead. An increase in size-corrected ma ss has been correlated with in creased survival and reproduction in non-SSD avian species (Magrath 1991; Krementz et al. 1989). While this implies that male

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15 ibises were in better condition than females, an alternative hypothesis would be that male body size is allometrically scaling with mass. The adaptive significance of allometric scaling between sexes in SSD species has been well-researched and allometric scaling is generally correlated with body size in adult (Fairbairn 1997) and nestling (Teather and W eatherhead 1994) birds. In breeding adults and in juvenile ibises, males have higher size-corrected mass than females (Kushlan 1977a, Kushlan and Bildstein 1992, Ku shlan 1977b, unpublished data). The apparent lack of difference in rate of increase in body condition between males and females that we found is consistent with the allometric scaling hypothesis. We do not know when sex-related differences in size-corrected mass would begin to manifest in White Ibises, and therefore allometric scaling remains a plausible explanation for males being larger. We suggest three possible mechanisms by which females might obtain less food than males when food is scarce. First, male nestli ngs may out-compete their female counterparts for food given by parents. Older and larger ibis nes tlings typically are fed fi rst by parents (Bildstein 1992, Rudegeair 1975); if food is limiting then the smaller sex may get few or no regurgitated boluses. There is some evidence to suggest that among birds ther e is higher mortality in the smaller sex when prey items are small (Anderson et al. 1993) and the size of the brood is small (Raberg et al. 2005). Using relati ve definitions supplied by these studies, White Ibises deliver small prey and have small brood sizes. Males ma y also be better equipped to deal with long intervals between feedings. Poor foraging is a ssociated with longer feed ing intervals (Bildstein et al. 1990; Rudegair 1975; Fred erick 2001), and a larger animal may also be better able to survive longer periods between food deliveries. This explanation is not necessarily mutually exclusive of the food dominance e xplanation (above). Finally, pa rent birds could be investing more food in male offspring during times of food limitation. It is not clear that there would be a

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16 benefit to doing so, but the deci sion would be presumably be aff ected by the likelihood of male survival in relation to nutrition, and by the breeding sex ratio likely to be in place at the time that the young birds become mature. The evidence presented here suggests that females were dying during the food shortage at a higher rate than ma les, probably because they were receiving less food than males. The mechanism by which this occurred is unknown, but there seems to be good circumstantial evidence that males would be in a better position to compete for food and to survive long interfeeding intervals because of their size.

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17 Table 1-1. The number of male and female ne stlings captured for each collection date. The proportion of males captured is display pa renthetically after the column totals. Sex Collection date Total 4/14/2005 4/17/2005 4/19/2005 4/21/2005 Males 10 21 41 31 103 Females 11 18 27 18 74 Total 21 (0.476) 39 (0.538) 68 (0.603) 49 (0.633) 177 (0.582)

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18 Collection Date 14 April17 April19 April21 AprilBody Condition (g/cm) 6.0 6.5 7.0 7.5 8.0 8.5 Male Nestlings Female Nestlings Figure 1-1. The increase in mean mass corrected for tarsus length over collection date split by sex. N=21, 39, 68, and 49 in ascending order of collection dates. Error bars indicate the standard error of the mean for each data point.

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19 CHAPTER 2 EFFECTS OF METHYLMERCURY AND SPATIAL COMPLEXITY ON FORAGING BEHAVIOR AND EFFICIENCY IN JUVENILE WHITE IBISES ( Eudocimus albus) Introduction Methylmercury is a neurotoxin, endocrine disr upting chemical (EDC), and teratogen in which exposure has been connected to cha nges in behavior in humans and wildlife (Scheuhammer et al. 2007). The most common acu te, neurological effects are a loss of motor skills, coordination and reduction in motivati on (Wolfe 1998; Scheuhammer 1987). In captive mallards ( Anas platyrynchos ) (Heinz 1979) 3 ppm (wet weight in diet) methylmercury caused changes in the duckling flight re sponse, brain lesions and demye lination of neurons (Heinz and Locke 1976) and 5 ppm (wet weight in diet) me thylmercury caused decreases in weight and appetite in Great Egrets ( Ardea alba ) (Spalding et al. 2000a) along with changes in hematology, neurology and histology (Spalding et al 2000b). Nocera and Ta ylor (1998) found methylmercury exposure to be correlated with behavioral changes in young Common Loons ( Gavia immer ). Bouton et al. (1999) f ound that at a much lower dose, (0.5 mg/kg ww in diet) juvenile Great Egrets showed decreased act ivity, altered thermore gulatory behavior, and decreased motivation to hunt. Although there appeared to be no effect of mercury dose upon foraging efficacy, any potential effects seemed confounded by individual foraging strategies. There are direct and indirect links between methylmercury exposure and learning; first, methylmercury has been suggested to alter thyr oid hormones in vertebrates (Facemire et al. 1995), which has been correlated to changes in te stosterone, estradiol, and perhaps progesterone in the White Ibis ( Eudocimus albus ) (Heath 2002). Estrogens, a ndrogens, thyroid hormones and glucocorticoids have important roles in brai n development; steroid hor mones are involved in critical to early development (Schlinger 1997) and song learning in passerines (Gahr 2004) and hippocampal (i.e. spatial) learning, while thyr oid (Schantz and Widhol m 2001; Zala and Penn

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20 2004) and glucocorticoid (Kitayski 2003; Zala and Penn 2004) hormones help regulated nervous system development, and impact learning and me mory. Prenatal exposure to methylmercury in humans can lead to learning disabilities later in the life of the child (G randjean et al. 1997). Therefore, it seems reasonable to expect low leve l methylmercury exposure to have an impact on learning in other vertebrates. However, the le vel of mercury necessary to induce this kind of effect is unknown. Behaviors under high levels of hormonal control are at risk of changing in response to endocrine disrupting chemicals (EDCs) like met hylmercury and such changes may have a large impact on important ecological and demographic pa rameters (Vos et al. 2000). Avian behaviors linked to changes in the hypothala mus-pituitary-adrenal axis and its associated hormones may also impact foraging rates and suppression of bree ding behavior (Wingfield et al. 1998). Steroid hormones influence a variety of physiological para meters (i.e., metabolism), and behaviors (i.e., territoriality, foraging rates, courtship, incuba tion) (Ketterson and Nolan 1992). A wide variety of behaviors are tightly linked with endocrine function and may therefore be susceptible to EDCs, including courtship and bree ding behaviors, altered social and dominance behaviors, and learning (Zala and Penn 2004). We report here on an experimental examinati on of the effects of low, chronic doses of methylmercury on the ability of naive juvenile Wh ite Ibises to forage in differing levels of habitat complexity. White Ibises (hereafter, ib ises) are a tactile-foraging aquatic bird that forages in flocks on crabs, crayfish, insects a nd small fish in a variety of aquatic habitats (Kushlan 1974). Foraging efficiency is dir ectly linked with condi tions that produce high availability of prey (Frederick and Collopy 1989; Gawlik 2002), and this parameter has high

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21 biological relevance because food intake can be related to reproductive success (Frederick and Collopy 1989; Frederick and Sp alding 1994; Frederick 2001). We hypothesized that the lear ning of novel foraging behaviors may be more difficult for birds exposed to methylmercury at environmentally realistic levels. In this experiment we attempted to test the specific prediction that merc ury would impair the ability of ibises to forage in the context of increasing difficultyin this case structural complexity in the foraging arena. We tested the assumptions that 1) increasing stru ctural complexity would decrease capture rates, and 2) foraging efficiency would increase over th e weeks of the experiment. We used foraging efficiency (prey depleted in a given time) and motivation (numbers of birds attempting to forage over time) of groups of foraging ibis es as response variables to f our different exposure levels of mercury. Methods We used 168 captive White Ibises in a large, fr ee-flight aviary at th e US Department of Agriculture Wildlife Research Center in Gaines ville, FL, USA to conduct this experiment. These birds were collected as ne stlings at 10 d of age from br eeding colonies in the northern Everglades (Broward Co., FL, N 26 11.179, W 80 31.431) and from White Springs, FL, USA (Hamilton Co, FL, 30.900 N, -82.367 W) (Ch. I). Young birds were randomly assigned to one of four dietary exposure groups receiving 0, 0.05, 0.1, or 0.3 mg/kg methylmercury (wet weight in diet) after 90 d of age. Exposure gr oups were housed in the same circular, open-air aviary (cf. 1200 m2) separated into quadrants by interior net walls. These levels of exposure mimic the range that might be encountered in the Everglades (Frederi ck et al. 2002; Loftus 1999). This experiment was run from 11 Oct to 17 Nov 2005. During each daily bout, all treatment groups were simultaneously presen ted with 200 live fathead minnow juveniles

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22 ( Pimephales promelas ) in 2.4 x 3.7 m rectangular foraging pools between 0800 and 0900 h. All groups were given access to the fish for 15 min. The foraging arenas were all similar, and had continuously varying water depths of 2 cm as a result of a sloping floor. Water depth was standardized for each experimental run each morning because of the possibility of prey availability differing with wate r depth (as mentioned above) and we placed varying levels of physical structure (see below). All cages were deprived of f ood starting at sundown the night before each bout, and food was restored ad libitum after each bout. All bouts were video recorded and reviewed later to determine how many birds participat ed at standard times in each bout. The experiment was run for six weeks, a nd during each week each cage experienced four bouts in a total of four different levels of structural complexity. No more or less than one bout was experienced on any day by any treatment gr oup, and on any one day no two cages would be assigned the same structural complexity level. Daily and weekly order of habitat complexity given to each treatment was pseudorandom. We used four levels of structural complexity: 1) Open pools, 2) pools with panels of agricultu ral fencing (mesh size ranging from 13 cm) supported approximately 3 cm off the bottom of th e pool and occupying the entire surface of the pool), 3) the same as #2 but we attached six pieces of 1 m by 1 m shade cloth and about 30 artificial plant leavesevenly spacedto the panels, and 4) Sa me as #2 but with 16 pieces of shade cloth and about 60 artifi cial plant leaves/fronds. All shade cloth and plastic plants provided a partial visual and physic al barrier, but were flexible a nd did not make any area of the arena inaccessible to the foraging ibises. After birds had foraged for 15 min, two resear chers entered the cages and placed large pieces of shade cloth over the foraging arena to en sure that no more foraging could take place.

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23 Once foraging was stopped in all cages we draine d the foraging arenas through a seine net, and counted the remaining fish. The video recordings were used to obtain an accurate measure of th e number of birds in each treatment group that were foraging at standa rdized times. Each video was analyzed by stopping the tape 30, 60, 240, 420, 600, 780 s into the experiment and the number of ibises in (not around or on the edges of) th e wading pool were counted. We estimated the total number of bird-minutes foraged during the entire bout by using rectangles bounded by the total time foraged and the number of birds to estimate the area under the curve. This approximation was a consistent underestimate of the true area under the curve. We used a repeated measures general linear model for analysis. The response was proportion of fish remaining and the dependent variables were day, week, methylmercury exposure group, and structural complexity. We m odeled the proportion of fish remaining adding 1 to the number of fish remaining and the number given (to eliminate zeroes) and transforming these data with an arcsine square root. Th is transformation was found to produce a set of residuals with an approximately normal distribu tion. We also modeled group motivation with the same factors to test our assumption of e qual motivation. We used ANOVAs to compare numbers of birds foraging across exposure groups wh ile controlling for the effects of structural complexity. We selected models from a base a priori set using backward selection. The linear models were analyzed using SAS v. 7.2 (PROC MI XED) and all other statistics were analyzed using JMP IN v. 5.1. Alpha was equal to 0.05. Results Time, structural complexity, and exposure gr oup were all determined to be important variables a priori and were all included as main effects in our best model (Table 2-1). However, while structural complexity showed a signifi cant (and quadratic) re lationship with time,

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24 methylmercury exposure did not. The resulti ng model fit well and all these terms were considered to be biologically important and plausible. The re peated measures aspect of our analysis (date) explained a small amount of th e variance; this implies that our Latin square experimental design was effective in removing the potential bias of day effect. While there was an effect of mercury dose group on foraging, it was small by comparison with effects of structural complexity and time. The hypothesis that structural complexity would decrease foraging efficiency was supported by this experiment (Fig. 2-1). Fora ging efficiency decrea sed with increasing vegetation/structure (Table 2-2), and this effect varied with ti me. When compared to the highest group of habitat complexity the lowest two leve ls showed significantl y faster learning (the time*complexity effect) but no significant non-linear change in their improvement (the time*time*complexity effect). While the medium complexity level did not differ from the high in linear improvement, there was a significant non-linear effect a nd had significantly less fish remaining independent of time. Thus, the hypothe sis that feeding effici ency would increase over time was supported and the degree of improvement was related to degree of structural complexity. Although we predicted that met hylmercury exposure would d ecrease foraging efficiency, result in a change in foraging efficiency over time, or both, in a dose de pendent fashion we did not find any interaction of tr eatment group with time. The me dium dose group has the most efficient foragers, the low dose group has the sec ond most efficient and th e control and high dose being almost equally less efficient than the othe r two groups (Fig. 2-2). Statistically, the control and high dose were similarly worse than the low and medium groups (Table 2-2). Contrary to our predictions, this rela tionship was highly nonlinear.

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25 One assumption of the experiment was that foraging efficiency dur ing the bout would not decline as a result of decreased motivation. The number of birds foraging during the course of the bouts was first analyzed as a response vari able by using the same model and dependent variables. This model showed no significant eff ects. When the model was stripped down to the main effects, complexity was found to be signi ficant (P<0.0001) while time and exposure group were not. In summary, our attempt to control motivational differences between exposure groups via temporary food restriction ap pears to have been successful. Discussion One of our objectives was to establish a foraging environment that offered enough challenge to motivated foraging groups that it would gradually decrease foraging efficiency. This was achieved, as evidenced by the inhibitory effect of increasing structural complexity. We also wanted to establish an environment in wh ich the birds might learn how to improve foraging efficiency over time and thus test whether lear ning might be affected by treatment. We also achieved this goal, since we found an effect of time on foraging efficiency at all levels of foraging difficulty. Although we fo und a significant effect of me thylmercury exposure in this experimental context, methylmercury did not have the expected linearly increasing effect; the middle two exposure groups were more efficient fo ragers than the control and high dose groups. More to the point, our strongest prediction was that the high a nd control treatment groups should provide the greatest contrast in mercury effects, yet they were not significantly different. Controlling for group motivation also proved su ccessful and differences between exposure groups are not due to differences in participation. Over time, all treatment groups improved in th eir foraging efficienc y, with no interaction with dietary methylmercury exposure. Our resu lts do indicate that all cages learned at an exponential rate (the time*time term in the mode l) when challenged by higher habitat complexity

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26 and that the degree of improvement in foraging e fficiency depended on the difficulty of the task (the time*complexity and the time*time*complex ity terms). The prediction that methylmercury (at the dose rates given) would inhibit learning seemed to have little supporting evidence. However, this finding does not rule out the possi bility that learning may be affected at higher dose rates or with different behaviors. There are two potential explanations for the nonlinear effect of me rcury seen in this experiment: hormesis and/or confounding effects. Hormesis suggests that certain toxicants stimulate an animal in apparently positive ways at low doses, yet cause negative effects at higher doses (Noel et al. 2006; Calabrese 2005). This pattern has been found increasingly in studies of endocrine effects, and especially with behavior al endpoints (Clotfelter et al. 2004). The amount of methylmercury with which these birds were exposed could be considered quite low by comparison with the existing lite rature on effects (Wolfe 1998), and it is possible that we approached a threshold for hormesis. There are two potential factors in the experime ntal setup that could confound effects of methylmercury exposure: individual composition of groups, and location. Due to differences in social structure of groups between cages and asy mmetrical natural events (like the differential effect of light or shade on differe nt cage locations) we may be plac ing certain cages at a foraging advantage over the others. While we cannot fi nd any ready mechanisms that suggest such a location effect, we also cannot rule such an e ffect out, since we had onl y a single replicate for each group. Increasing structural complexity made it mo re difficult for ibises to forage. Our measurement of motivation indicate s that higher structural comple xity encourage more birds to forage longer; despite such diffe rences there were still large di fferences in foraging efficiency

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27 between complexity groups. While availability of prey to visual and tactile aquatic birds is known to be affected by prey density, hydrope riod, temperature, dissolved oxygen and water depth (Maccarone and Brzorad 2005; Smith et al 2003; Gawlik 2002; Frederick 2001) the effect of vegetation and obstructions ha s received relatively little attention (Ban croft et al. 2002; Surdick 1998). Although the ib ises showed improvement in the more challenging habitat structure, they never achieved th e levels of efficiency seen in the low complexity environment. Although such an effect has been suggested by ha bitat selection studies of wading birds (Stolen 2006; Surdick 1998; Bancroft et al. 1994), we believe this is the first experimental demonstration of an experimentally measured effect of st ructural complexity for foraging by long-legged wading birds. It therefore seems likely that vegetation density and type is an important determinant of foraging success and habita t selection for tactile-foraging waders.

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28 Table 2-1. Overall effect of f actors in our best model. Signi ficance was determined using an Ftest based on Kenward-Rogers degrees of freedom estimation. Effect P-value Time <.0001 Exposure Group 0.0038 Time*Time <.0001 Structural Complexity <.0001 Structural Complexity*Time <.0001 Structural Complexity*Time*Time 0.0061 Table 2-2. Parameter estimates fr om the best model (PROC MIXED). Note that Beta values are relative to the control gro up in the case of methylmercury exposure and the high group in the habitat complexity. Effect Parameter estimate ( ) Standard error P-value Time -0.3540.06221 <.0001 Time*Time 0.033370.008699 0.0002 Methylmercury Exposure Control Low -0.076650.03069 0.0145 Medium -0.091880.03069 0.0036 High -0.004820.03069 0.8756 Habitat Complexity High Medium -0.45990.1345 0.001 Low -1.04680.1345 <.0001 Control -1.29130.1345 <.0001 Habitat Complexity Time High Medium 0.0072420.08797 0.9346 Low 0.23880.08797 0.0081 Control 0.35470.08797 0.0001 Habitat Complexity Time *Time High Medium 0.0061260.0123 0.008 Low -0.020570.0123 0.0983 Control -0.033470.0123 0.6199

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29 DTime (week) 01234567 0.0 0.2 0.4 0.6 0.8 1.0 CTime (week) 01234567Proportion of Prey Remaining 0.0 0.2 0.4 0.6 0.8 1.0 Control Low Medium High B 01234567 0.0 0.2 0.4 0.6 0.8 1.0 A 01234567Proportion of Prey Remaining 0.0 0.2 0.4 0.6 0.8 1.0 Figure 2-1. Mean proportion of fish remaini ng for each week for each methylmercury exposure group for A) complexity level 1 (control), B) complexity level 2 (low), C) complexity level 3 (medium), D) complexity level 4 (high).

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30 Figure 2-2. Mean proportion of prey rema ing grouped by methylmercury exposure group and structural complexity over al l weeks. Error bars represen t standard erro r of the mean. Treament Group ControlLowMediumHighMean proportion of prey remaining 0.0 0.1 0.2 0.3 0.4 0.5 No complexity Low complexity Medium complexity High complexity

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31 CHAPTER 3 SUBLETHAL EFFECTS OF METHYLMERCURY ON TESTOSTERONE, ESTRADIOL, AND CORTICOSTERONE FECAL METABOLI TES IN CAPTIVE JUVENILE WHITE IBISES ( Eudocimus albus ) Introduction Methylmercury is a globally distributed cont aminant that has a wide range of endocrine disrupting, neurological, and de velopmental effects in animals (Wolfe et al. 1998) with significant differences between avian species (Hei nz et al. 2006). Within an environmentally relevant exposure range however endocrine effects have not b een well studied, especially in birds. Increased levels of methylmercury in f eather samples over the past thirty years are also indirectly correlated with a decrease in number of breeding White Ibises ( Eudocimus albus ) in the Florida Everglades, where mercury contamina tion has been high (Heath and Frederick 2005). Heath and Frederick (2005) showed that methyl mercury in breeding White Ibises was correlated with a decrease in estradiol in females and an increase in testosterone in males. In Common loons ( Gavia imme r) Evers et al. (2003) demonstrated a positive associ ation between blood mercury concentrations and blood corticosterone levels and Nocera and Taylor (1998) correlated mercury exposure with changes in chick behaviors. In contrast, Thaxton et al. (1982) showed a decrease in corticosterone with in creasing methylmercury in chickens ( Gallus domesticus ) and Heath and Frederick (2005) found no relationship between mercury exposure and corticosterone in breeding White Ibises. Methylmercury expos ure is correlated to changes in endocrine function; however such changes are sens itive to species, dose range, and season. The mechanism by which mercury exposure aff ects endocrine function in birds is also unknown. Methylmercury may impact the endocrine system of birds in ovo during the rapid growth stage as nestlings, as non-breeding j uveniles. Alternatively, there may be no developmental aspect to the eff ect, and methylmercury exposure as an adult may be the primary

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32 route by which adult breeding is affected. Currently, evidence for methylmercury as an endocrine disrupting chemical (EDC) in birds is solely correlative; a cau sal relationship between exposure and endocrine function needs to be demonstrated. The case for causal relationships between various EDCs and birds is strong; effects in birds have been commonly found using the steroid hormones estradiol (MacLellan et al. 1996; Giesy et al. 2003) and testosterone (C olborn et al. 1993; Giesy et al. 2003) along with corticosterone (Baos et al. 2006; Thaxton et al. 1982), a hormone that is part of the hypothalamus-pituitaryadrenal stress axis. Estradiol is the sex determ ining hormone in early development (Bigsby et al. 1999) and is correlated with breed ing cycle as adults (Wingfield and Farner 1978; Maguet et al. 1994). Testosterone has been linked to territori ality (Beleskey et al. 1990) and mating behaviors (Wingfield 1984; Brunstrom et al. 1999). Corticosterone plays an important role in coping with environmental stressors (Harvey et al. 1984; K itaysky et al. 1999; Marra and Holberton 1998; Holberton et al. 1999). Currently, we lack causal evidence in support of the connection between changes in steroid and glucocorticoid hormones and methylmercury e xposure, however, most studies have not been adequately designed to answer such a question and we believe this has yet to be fully explored. As a result we lack strong evidence connecting e ndocrine changes to reproduc tive failure in birds (Bosveld and van den Berg 2002). Field studie s are primarily correlati ve when causality is needed for decision-making, contaminant exposur e may be correlated to confounded ecological variables (Meyer et al. 1998), and multiple contaminantswith unknown synergiesmay be present at field sites (Tyler et al. 1998). Captive studies may be difficult to generalize to a freeliving population of interest by selecting ecologically irreleva nt endpoints (Zala and Penn 2002; Chapman 2002), species selection (Ottinger et al 2005), and differential endpoint sensitivities

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33 (Clotfelter et al. 2004). Comp licating issues further is our lack of knowledge of endocrine disruption in juvenile birds and the effect this may have on adults; in mammals, EDCs can delay the onset of juvenile sexual maturation (Marty et al. 1999). Such relationship may exist in EDCexposed juvenile birds, however, no studies have looked at th is experimentally. The available literature therefore suggests th at methylmercury exposure in birds could be altering expression of hormones that are importa nt for development and reproduction. If these effects exist, they may have the potential to result in population ch ange, by affecting survival and fecundity rates. Here, we report on a study of th e effects of mercury on endocrine function in a developing juvenile aquatic bird, the White Ibis, using a controlled experimental approach. We studied the White Ibis because there is c onsiderable information on its breeding ecology (Kushlan 1974; Kushlan and Bildstein 1992; B ildstein 1994; Frederick 1987a; Frederick 1987b), because there are demonstrated effects of met hylmercury on endocrine function in adult birds (Heath et al. 2003), and because the species conti nues to be exposed to methylmercury in the wild (Frederick and Heath 2005). We measured estradiol, testosterone and corticosterone metabolites in fecal samples, and used an envi ronmentally relevant range of experimental mercury exposures. We hypothesized that in creasing exposure to methylmercury would significantly alter fecal estradiol, testosterone and corticosterone concentrations in a dosedependent fashion. Methods Study Site We used an experimental approach by m easuring endocrine responses of captive White Ibises that were exposed to di ffering levels of methylmercury through their diet. In April 2005, wild-caught White Ibis nestlings were raised in f our dose groups in a large free-flight aviary. The aviary was circular (21 m radi us, 10 m tall) and divided into quadrants with net walls. The

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34 interior of the aviary contained numerous perches, artificial nest cups a nd a feeding/loafing pool. We fed all birds in each enclosure on a different diet containing methylmercury: control, 0.05 ppm MeHg, 0.1 ppm MeHg, and 0.3 pp m MeHg (all values in diet wet weight). The flooring was impermeable PVC sheeting that drained toward s a common central drain. White Ibises were collected as 25 d old nestlings from the nor thern Everglades (Water Conservation Area 3, Broward Co. Florida, N 26 11.179, W -80 31.431) and from a colony near White Springs, Hamilton Co., Florida (N 30 19.900, W -82 45.367). The Alley North birds were collected on 14, 17, 19, and 21 April 2005 and transported overnight to Gainesville, FL (see also Chapter 1). We sexed, weighed, measured, banded and rem oved approximately 4 scapular feathers for mercury analysis from all nestlings before ra ndomly distributing them to enclosure/exposure groups. Methylmercury was administered via diet be ginning at 90 d of age by dissolving MeHgCL into corn oil and spraying the mixture onto Fl amingo diet pelletized feed (Mazuri Company, Brentwood, MO, USA) while the mass was being ro tated in a cement mixer in 11.3 kg batches. Each dose group had a complete set of glasswar e and mixing devices (including cement mixers) dedicated solely to that dose regime. Stock so lution concentrations of methylmercury were fine tuned by direct measurements of mercury content of food prior to the onset of feeding to ibises. Dose regime was also verified by determining mercury concentrations of scapular feathers (Frederick et al. 2002) in January of 2006 and 2007 using standard cold vapor techniques (Figure 3-1). Fecal Hormone Sampling Technique, Storage and Extraction Steroid and corticosteroid hormones are most commonly measured in the blood plasma of animals. However, a number of recent studi es (Creel 2001, Palme et al. 2005, Wasser and Hunt 2005, Hinson and Raven 2006) have demonstrated th at useful hormone levels can also be

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35 obtained from fecal samples. The latter sampli ng method is noninvasive, thus avoiding the need to correct for short term stress response. In addition, hormone levels in feces represent an integration of fluctuating hormone levels over the gut passage time, which allows for a more reliable measure of baseline hormone levels (T yler et al. 1998). Potential difficulties with the method include validating the relationship betw een blood hormones and fecal metabolites, and developing effective extract ion techniques (Goymann 2005). We collected fecal samples on clean black plastic sheeting placed below perching structures, and identified feces of individual ibises by observing excretion of individually banded birds directly. The location, time, and band number of each excretion was recorded. On collection days, we collected feces for two 1-hr periods separated by 1 hr (typically between 1100-1200 h and 1300-1400 h). During collection bout s we removed samples from the plastic every 10 min. Two observers usually watched du ring each collection bout and at each 10-min interval both observers appro ached the plastic sheets at the same time and collected fecal samples that were visually marked. Unidentifie d samples were crossed-out to avoid confusion. If unidentified samples were in very close pr oximity (e.g., within 0.5 m) to the sample of interest, the sample was consid ered contaminated and was not collected. We estimated throughput time (time from ingestion to excretion) at 2-3 h using food marked with colored plastic beads. There were 4 collection periods during th is study. The first was early June 2005 immediately before dosing began (when birds we re ca. 90 d old), the second was late June immediately after the ini tiation of dosing (ca. 110 d old), th e third was late July 2005 (ca. 140 d old), and the fourth was in late Decembe r 2005 and early January 2006 (ca. 290 d old).

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36 Individual fecal samples were collected in 2 mL plastic cryotubes and placed in an icefilled cooler for no more than 3 hours until they could be stored at -20C temperature; all samples were analyzed for hormone concentrations in May 2006. Fecal samples were individually lyophilized and the dried and stable samples were then weighed and placed into glass extraction vials. Sample s that contained more than 0.0 5 g of sample were homogenized and subsampled while samples th at contained 0.05 g or less were used in their entirety. Using a combination of techniques (Hunt and Wasser 2003; Wasser and Hunt 2005) we used ethanol diluted by deionized water to extr act hormone metabolites from the sample. We added the ethanol to a measured amount of f ecal hormone in a capped glass culture tube, and used a multi-tube vortexer to shake the mixture for 30 min, cycling the vortexer on for 1 min and off for the next. Culture tubes were then spun in a refrigerated ultra-cen trifuge at 3000 rpm for 20 min. The resulting ethanol supernatant was d ecanted into clean culture tubes and placed in 80C freezer for storage. We compared the extrac tion efficiency of 80% (20% deionized water), 90% (10% deionized water), and 100% ethanol solutions by adding a known amount of radiolabeled hormone to standardized desiccated fecal matrix then pe rforming the extraction procedure. We used 80% ethanol because its ex traction efficiency was highest when considering all hormone tests (Table 3-1). A ll results were adjusted for mean extraction efficiency (estradiol 77%, testosterone 64%, corticosterone, 90%). Radioimmunoassay We tested each sample extract for estradiol metabolites using Estradiol 125I Coat-a-Count RIA kits (Diagnostic Products, Los Angeles, CA USA). We used the 3 h, room temperate incubation for all samples. The manufacturers protocol was used with 100 L of extract used initially and dilutions used when needed. This kit has shown high accuracy and dependability in previous avian fecal hormone studies (Wasse r and Hunt 2005). The manufacturer-reported

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37 antibody cross-reactivities were 10% for estrone, 4.4% for -Equilenin, 1.8% for Estroneglucuronide and less than 1% fo r all other tested steroids. We tested for testosterone metabolites using Testosterone 125I double-antibody RIA kits (MP Biomedicals, Solon, OH, USA). The ma nufacturers protocol was used with 50 L of extract used initially and dilutions used when needed. This kit has been validated for fecal metabolites previously in birds (Wasser and H unt 2005) and other vertebrates (Hunt and Wasser 2003). The manufacturer reported cr oss-reactivities were 3.4% for 5 -dihydrotestosterone, 2.2% for 5 -androstane-3 17 -diol, 2% for 11-oxotestosterone, and less than 1% for all other tested steroids. We tested for corticosterone metabolites using Corticosterone 125I double-antibody RIA kits (MP biomedicals, Solon, OH, USA). Th e manufacturers protoc ol was used with 50 L of extract used initially and dilutions used when need ed. This and similar kits have been validated in several avian fecal glucorticoid studies (Wasser and Hunt 2005; Ludders et al. 2001). The manufacturer-reported cross -reactivites were 34% for desoxycorticosterone, 10% for testosterone, 5% for cortisol, 3% for aldosterone, 2% for proges terone, 1% for androstenedione, 1% 5 -dihydrotestosterone, and less than 1% for al l other tested steroids and glucocorticoids. All kits were validated by runni ng a set of internal standards into standard hormone extract and hormone-stripped extract using the manufacture rs standard curve. In order to determine whether the extraction matrix would interfere w ith the accuracy of the assay we tested for differences between all curves for all kits a nd found none to be signifi cantly different (ANCOVA all Ps> 0.22). Thus, we find our assay to be internally valid for each hormone. Statistical Analysis We looked for differences in hormone concen tration due to treatme nt using a repeated measures ANCOVA. Sampling was not uniform acr oss sampling periods (i.e certain individuals

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38 were not represented in some sampling periods) so traditional repeated measures methods could not be used. After averaging individual hormone concentrations for each collection for immunoreactive estradiol (E) and testosterone (T ) and for each day for corticosterone (CORT)) we took the natural log of the hormone concentra tion to normalize them. Because we wished to correlate hormone values from the same indivi duals at different collection times, we used a compound symmetry structure to the covariance matrix to link individuals (nested within treatment) over time (SAS v. 9.1 PROC MIXED). We also used Kenward-Rogers calculated degrees of freedoma technique that has been sh own to minimize Type I errors in repeated measures studies with gaps in the data due to sampling inequity (Pad illa and Algina 2004). Using treatment group, time (either collection peri od or collection day as above), and sex as main effects, we developed a set of 21 biologically relevant a priori models based on our predictions (see Introduction). We included all po ssible combinations of the three terms up to the most complicated model that included a time *treatment*sex term. We also included a time*time interaction that allowe d for non-linear changes in horm one concentration over time but we did not allow this term to interact wi th other main effects. We included one term a posteriori : a categorical grouping that compared th e control group against all experimental groups. Model selection was based upon AICc (Burnham and Anderson 2002) and models were ranked by AIC weight. The AIC met hod is invalid when used with data generated via restricted maximum likelihood methods (REML) that are defa ult in PROC MIXED, and we used standard maximum likelihood methods instead. Finally, in an effort to examine the possi ble effects due to in dividual variation in methylmercury exposure within groups (Fig. 3-1) we regrouped each individual as being either high or low methylmercury exposure based upon th e median feather mercury quantity for each

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39 exposure group. We then removed the a priori treatment factor (control low, medium and high) from the model and replaced it with the new (control, low-low, high-low, low-medium, highmedium, low-high, and high-high) in the best model as previously selected by AIC. The new parameter estimates are then indicators of di fference from each new group and the control. Alpha was set at 0.05. Results The model that best explained variation in E included treatment, sex, and time as main effects with time*time and treatment*time inte ractions (Table 3-2). This model was substantially better than all remaini ng models, with a difference in AICc greater than two for the next closest model. Fecal E metabolites showed an overall downward trend with time (Fig. 3-2), and showed significant upward curvature via th e time*time term (Table 3-4). Although the effect of treatment was significant (F test, P<.0022), it was also nonlin ear with respect to exposure group. The medium dose group was the only group significantly different than the control group, and high, low and c ontrol groups were not different. This pattern was also found for the treatment*time interaction (F test, P<.01 36) (Table 3-4). The medium group had less E than all other groups, but relativel y greater increase over time. Our a posteriori test of non-linear dose-response relationship (contr ol compared to all experiment al groups) also ranked poorly relative to our best model ( AICc= 4.8). Finally, although female ibises tended to have less E than males, the difference was not significant and there was no overall effect of sex on E (Table 3-4). Fecal T metabolites tended to decrease ove r time and showed few differences between treatment groups (Fig. 3-3). Two models recei ved similar support from the model selection process. The top model included time, time* time, exposure group. The second-ranked model ( AICc = 1) included time as a main effect and a tim e*time interaction (Table 3-2). However,

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40 the top-ranked model is an a posteriori test of control versus all ex perimental groups combined; we chose to analyze this model to test our pr ediction of methylmercury exposure with the caveat that any effect is unpredicted. Looking at the results of the top model in greater depth, T increased over time (F-test, P=0.0015) with a significant (F-test, P< 0.001) negative parameter estimate for the time*time interaction allows for concave curvature (and an overall decrease) of T with increasing time (Table 3-4). The a posteriori treatment term did not show significant differences between groups. Females tended to have less T than males, though the effect was non-significant (e.g., P=0.6484). Three models seemed to explain fecal CO RT metabolite concentrations well (i.e., AICc< 2) (Table 3-2). The third model, however, was marginal compared to the first two, so we will limit the discussion to the two top models. Furt her, the two top models had similar structure the only difference was the inclusion of the se x effectso our discussion will focus upon the more complicated model to test our hypothesis on the importance of sex. There was no obvious trend in CORT over time (Fig. 3-4). The mode l shows an insignifican t upward trend and a significant negative time*time interaction suggesti ng concave curvature (Tab le 3-5). Treatment group had a significant, nonlinear effect on CO RT (F-test, P=0.0148). While no individual exposure groups differed significantly from the control, both the low and high groups were significantly different from each other. Females had lower levels of CORT than males, although the effect of sex was not significant (Table 3-5). In our analysis of within-group variance in mercury exposure showed differences depending on hormone endpoint and exposure group (Table 3-6). Variance in methylmercury effect appears to increase with increasing me thylmercury exposure; th e low group is relatively consistent in direction and magn itude of effect. The medium a nd high group parameter estimates

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41 show larger differences between there subgroups than the low gr oups, particularly in the CORT endpoint. Discussion Our predictions about the relationship betw een methylmercury and the hormones studied were not generally supported by our findings. The most consistently violated prediction was that responses would be linearly related to methyl mercury exposure. While we found effects of experimentally administered methylmercury on hormones, all were non-linear. Methylmercury exposure significantly altered E, although this re sult appeared to be driv en by large differences between the medium exposure group and all other groups. T showed no significant doseresponse relationship with all a priori tests of methylmercury exposure, although the a posteriori test comparing the control and all other groups s howed an apparent decrease in T with mercury exposure. CORT varied significantly with me thylmercury exposure, but the lowest mean concentrations were found in th e low exposure group and the highe st in the high exposure group with control and medium groups between the two. Our prediction that le vels of steroid and glucocorticoid hormones would be affected by se x were not supported by any of the tests. Finally, our analysis of variation in intragroup methylmercur y exposure did not aid in explaining these nonlinear patte rns as they did not suggest that higher intragroup exposure yielded a response of greater magnitude; how ever, these data do suggest ther e are differences within these groups and the high intragroup variance ma y be a product of exposure variance. It is possible that the levels of mercury e xposure were simply not high enough to have an effect, and/or that effects of mercury were overwhelmed by random or confounding effects. For example, the dose-dependent patterns identified in the E, T and CORT data sets may have been confounded with location effect, si nce each treatment was represented by only one replicate. We attempted to control for cage effect though physi cal and experimental design; the cages were

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42 physically identical within a circular aviary that carried equal edge effects. We also chose response variables that were measured by individu al bird and used statis tical techniques (like repeated measures) that take use the individual as the base unitalbeit nested within exposure group. Cage effect might also have derived from a cohort effect, whereby the makeup of individuals in the group affected the endoc rine expression within that group. There appears to be no biologically signifi cant explanation for the medium dose group having more E than other groups; we therefore suggest that at the dose levels we use, methylmercury has little effect on fecal E meta bolites in juvenile ib ises in the non-breeding season. This conclusion is reinforced somewhat by the fact that there was no effect of sex on E levels. Thus in first-year ibises, it may be that E has simply not been expressed to the degree that it is in breeding adults, at which point there is a marked difference (Heath and Frederick 2005). Thus the capacity for expressing E in juveniles may not have been tested during the juvenile period, and so may not be a very good indicator of poten tial EDC effects. With T, the only near-significant effect o ccurred when all experimental groups were a posteriori combined and compared with the controlall a priori models that included the effect of (uncombined) methylmercury had little support from AIC. The pattern from this last analysis suggested that the control group ma y have, on average, higher T leve ls than all others during the non-breeding season. However, as w ith E, the lack of sexual differe nces in testosterone indicates that expression of T is not very active during the juvenile period, and therefore may not be a very useful indicator of endocrine dysfunction. Thus while steroid hormones may be important to sexual differentiation in ovo and to the timing and onset of breeding, there is little in formation on endocrine ex pression in developing juvenile birds (though see Schli nger 1997 for information on hormones and song learning).

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43 The significant effect of time in all models s hows that T and E are changing, however, the lack of sexual differences imply that these changes are not related to reproduction or differential sexual development. While we have found pattern s that suggest an effect of methylmercury exposure on E and T levels in developing ibises, the patterns are not s upportive of a linear dose response relationship, and the most likely explana tion appears to be that these endpoints may be insensitive to methylmercury exposure. Effects of methylmercury on fecal corticoste rone metabolites are more explicable as nonlinear responses have been reported in this endpoint. In the American Kestrel ( Falco sparverius ), Love et al. (2003) found th at plasma CORT levels varied similar to an inverted parabola when compared to liver EDC load. This apparently hormetic pattern may be due to the multiple roles that CORT plays in the physiological function of birds. S hort-term increases in CORT can be caused by environmental stressors li ke heat, handling or cap ture, cohabitating with conspecifics, and food consumption (Siegel 1980). In wild migrating bi rds high baseline CORT suppresses the acute CORT increas e, at least in response to ha ndling stress (Holberton et al. 1996). It is possible that high, chronic levels of methylmercury simulate high levels physiological stress or disease, resulting in an increase in baseline CORT. The lower exposure levels could be causing a decr ease in baseline CORT by e ither mechanistically altering hormonogenesis or by providing low enough levels of physiological stress to downregulate the production of CORT. Furthe r research is needed to evaluate th ese as explanations for the pattern we have reported. Potential (non-exclusive) hypotheses e xplaining these findings are (1) that methylmercury does not alter the steroid horm ones at these dose levels, and (2) that methylmercury does not alter steroid hormones in j uvenile ibises. We have no direct evidence

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44 for supporting or rejecting either hypothesis, a lthough the earlier work of Heath (2005) suggests strongly that there is an eff ect of mercury on expression of these hormones in wild breeding adults. Since the dose levels in this study spanned the range of exposures estimated in the wild birds studied by Heath (2003), we believe the mercur y effect seen in adults may simply not be manifested in young birds. It is also possible that there is so mething about the captive situation other than methylmercury exposure (lack of typical stressors, social environment, etc) that has blocked an effect of methyl mercury on steroid hormones. In conclusion, we found immunoreactive fecal es tradiol, testosterone, and corticosterone levels were changing over time in captive j uvenile White Ibises. While estradiol and testosterone showed an effect of dose, only corticosterone changed in manner that seemed to be explicable on biological princi ples. We suggest future stud ies of endocrine effects of methylmercury might profitably focus on endocri ne expression during th e breeding season, since the results with juveniles were inconclusive.

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45 Table 3-1. The average extracti on efficiencies for each hormone by percent ethanol used for extraction. Percent ethanol Estradiol Testos terone Corticosterone 80 77% 64%90% 90 72% 62%98% 100 38% 80%102% Table 3-2. Ranking of various models for all hormone metabolites by Akaike weight. Only models with a weight great er than 0.01 were included. Hormone Model AICc AICc Akaike weight Estradiol time sex trt time*time time*trt 260.80 0.4697 time sex trt time*time sex*time trt*time 262.92.1 0.1643 time time*time trt 264.23.4 0.0858 time time*time 264.33.5 0.0816 time sex trt time*time 2654.2 0.0575 time time*time sex 265.44.6 0.0471 time time*time control 265.64.8 0.0426 time sex trt time*time time*trt sex*trt 2676.2 0.0212 time sex trt time*time sex*time 267.26.4 0.0191 Testosterone time control time*time 158.70 0.4663 time time*time 159.71 0.2828 time sex time*time 161.73 0.1040 time trt time*time 161.93.2 0.0941 time sex trt time*time 163.95.2 0.0346 time sex trt time*time sex*time 1667.3 0.0121 Corticosterone time sex trt time*time 380.80 0.2350 time time*time trt 380.80 0.2350 time sex trt time*time time*trt 382.61.8 0.0955 time sex trt time*time sex*time 382.92.1 0.0822 time time*time 384.13.3 0.0451 time sex trt time*time sex*time trt*time 384.84 0.0318 time sex trt time*time sex*trt 384.94.1 0.0303 time time*time sex 384.94.1 0.0303 time time*time control 386.25.4 0.0158 time sex trt time*time sex*time sex*trt 386.96.1 0.0111 time sex trt time*time time*trt sex*trt 387.36.5 0.0091

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46 Table 3-3. Estradiol parameter estimates from our best model selected by AIC with their respective standard error of th e estimate. P-value is determined using an F-test. Note that treatment and sex effects are cate gorical and the control and male groups, respectively, act as a refere nce and all others are estim ated relative to that group. Model parameter Parameter estimate ( ) Standard error P-value Time -0.63940.1379<.0001 Time*Time 0.0520.066 Sex Male Female -0.053250.05210.3089 Treatment Control Low -0.080780.12530.5199 Medium -0.45260.13180.0007 High -0.092850.1290.4723 Time*Treatment Control Low 0.0042070.02940.8862 Medium 0.10020.03480.0044 High 0.032880.0310.2901 Table 3-4. Testosterone parameter estimates from our best model selected by AIC with their respective standard error of th e estimate. P-value is determined using an F-test. Note that treatment and sex effects are cate gorical and the control and male groups, respectively, act as a refere nce and all others are estim ated relative to that group. Model Parameter Parameter estimate ( ) Standard error P-value Time 0.15470.04810.0015 Time*Time -0.020850.005<.0001 Treatment Control Experimental -0.097560.05420.0737 Table 3-5. Corticosterone parameter estimates fr om our best model selected by AIC with their respective standard error of th e estimate. P-value is determined using an F-test. Note that treatment and sex effects are cate gorical and the control and male groups, respectively, act as a refere nce and all others are estim ated relative to that group. Model Parameter Parameter estimate ( ) Standard error P-value Time 0.0025670.0020.195 Time*Time -0.000029E-060.0351 Sex Male Female -0.10650.07320.1486 Treatment Control Low -0.170.09780.0851 Medium -0.01740.10060.865 High 0.140.09690.151

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47 Table 3-6. Parameter estimates, standard errors and P-values (t-test) for each treatment group subdivided by median feather mercury quant ities (Fig. 1) for each hormone. The treatment grouping was added to our best model selected by AIC. The parameter estimate is for the highest order term that includes treatment; estradiol is treatment*time, testosterone is treatment, and corticosterone is treatment. All parameter estimates are rela tive to the control group. Hormone Treatment Group Parameter Estimate ( ) Standard error P-value Estradiol Control Low-Low 0.01390.03490.6917 High-Low -0.01600.03530.6498 Low-Medium 0.14020.05050.0060 High-Medium 0.07710.03990.0548 Low-High 0.00100.03940.9795 High-High 0.05780.03540.1046 Testosterone Control Low-Low -0.15240.07940.0575 High-Low -0.10670.07600.1628 Low-Medium -0.09070.08150.2677 High-Medium -0.15310.08280.0662 Low-High -0.11430.08050.1584 High-High -0.02680.07510.7223 Corticosterone Control Low-Low -0.17450.11770.1416 High-Low -0.18800.11680.1108 Low-Medium 0.10960.12290.3745 High-Medium -0.10780.12490.3897 Low-High 0.22580.12010.0631 High-High 0.04560.11260.6865

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48 Figure 3-1. Feather mercury levels for indivi dual birds in each e xposure group. Data are presented in box plots with outliers repres ented as dots, the gray box showing where 50% of the data lie, the line in box is mean. Treatment Group ControlLowMediumHighFeather Hg 0 10 20 30 40 50

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49 Days After Experiment Start 01450214Fecal Estradiol Concent ration (ppb/g sample) 0 20 40 60 80 100 Control Low Medium High Figure 3-2. Mean estradiol concentration by tr eatment group for each collection period. Error bars represent the standard error of the calculated mean and do not consider intracollection dependency issues as our statistical models do.

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50 Days After Experiment Start 01450214Mean Testosterone Concentration (ppb/g sample) 0 20 40 60 80 100 Control Low Medium High Figure 3-3. Mean testosterone concentration by treatment gro up for each collection period. Error bars represent the standard error of the calculated mean for each collection period and do not consider intracollection depe ndency issues as our statistical models do.

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51 Days After Experiment Start -50050100150200250Mean Corticosterone Concentration (ppb/g of sample) 0 50 100 150 200 250 300 350 Control Low Medium High Figure 3-4. Mean corticosterone concentration by treatment gr oup for each collection period. Error bars represent the standard error of the calculated mean for each collection period and do not consider intracollection depe ndency issues as our statistical models do.

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61 Torres, R. and H. Drummond. 1999. Variably ma le-biased sex ratio in a marine bird with females larger than males. Oecologia 118: 16-22. Tyler, C. R., S. Jobling and J. P. Sumpter. 1998. Endocrine disruption in wildlife: a critical review of the evidence. Critical Reviews in Toxicology 28: 319-361. Vedder, O., A. L. Dekker, G. H. Visser and C. Dijkstra. 2005. Sex-specific energy requirements in nestlings of an extremel y sexually size dimorphic bir d, the European sparrowhawk ( Accipiter nisus ). Behavioral Ecology and Sociobiology 58: 429-436. Vos, J. G., E. Dybing, H. A. Greim, O. Ladetoge d, C. Lambre, J. V. Tarazona, I. Brandt and A. D. Vethaak. 2000. Health effects of endocri ne-disrupting chemicals on wildlife, with special reference to the European situation. Critical Reviews in Toxicology 30: 71-133. Wasser, S. K. and K. E. Hunt. 2005. Noninvasi ve of reproductive function and disturbance in the Barred Owl, Great Horned Owl, and the No rthern Spotted Owl. Annals of the New York Academy of Sciences 1046: 109-137. Weatherhead, P. J. and K. L. Teather. 1991. Are skewed fledgling se x ratios in sexually dimorphic birds adaptive? The American Naturalist 138: 1159-1172. Weatherhead, P. J. and K. W. Dufour. 2005. Li mits to sexual size dimorphism in red-winged blackbirds: the cost of gett ing big? Biological Journal of the Linnean Society 85: 353361. Wingfield, J. C. and D. S. Farner. 1978. The annual cycle of plasma irLH and steroid hormones in feral populations of th e White-crowned Sparrow, Zonotrichia leucophrys gambelii Biology of Reproduction 19: 1046-1056. Wingfield, J. C. 1984. Androgens and mating systems: testosteroneinduced polygyny in normally monogamous birds. The Auk 101: 665-671. Wingfield, J. C., D. L. Maney, C. W. Breuner, J. D. Jacobs, S. Lynn, M. Ramenofsky and R. D. Richardson. 1998. Ecological bases of hormone -behavior interactions: the emergency life history stage. Integrative and Comparative Biology 38: 191-206. Wolfe, M. F., S. Scharzbach and R.A. Sula men. 1998. Effects of mercury on wildlife: a comprehensive review. Environmental Toxicology and Chemistry 17: 146-60. Zuk, M. and T. S. Johnson. 2000. Social enviro nment and immunity in male red jungle fowl. Behavioral Ec ology 11: 146-153.

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62 BIOGRAPHICAL SKETCH Evan Adams was born and raised in Richla nd, WA, where he decided to delve into science at an early age with his investigation on how to prot ect strawberry plants from herbivory. Soon after, he began working fo r the local National Laboratory in particle physics. He earned an honors Bach elor of Arts in biology from Whitman College in Walla Walla, WA. There he discovered his true l ove for tropical avian ecology. In August 2007, he received his masters degree in wildlife ecology and conservationfrom the University of Florida, focusing on avian ecotoxicology. He plans to start his doctorate at the University of Maine, studying the ecology of ne otropical migratory birds.


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