Relationship between plasma triiodothyronine concentrations and plasma inorganic iodide concentrations of alligators.

<p>Merritt Island  =  black circles and black line, Lake Woodruff  =  white circles and dotted line, Lake Apopka  =  gray diamonds and gray line. A. Neonates B. Juveniles.</p

Thyroid gland histology from neonatal alligators.

<p>Thyroids were rated from 0 to 3 according to hyperplasia severity, hyperplasia area, and hypertrophy. A. All ratings of 1 (mild). B. All ratings of 2 (moderate). C. All ratings of 3 (severe). D. An example of follicular cell involution. F  =  follicular cell, C  =  colloid, L  =  lumen, IN  =  involution.</p

Plasma thyroid hormone concentrations from different sites and life stages of American alligators from Florida.

<p>Merritt Island  =  black, Lake Woodruff  =  white, Lake Apopka  =  gray. Letters represent statistical differences among sites within age groups. Numbers within bars represent sample size. Error bars are ± SE. A. Mean plasma thyroxine concentrations. B. Mean plasma triiodothyronine concentrations.</p

Growth comparisons of alligators from three sites in Florida.

<p>Merritt Island  =  black circles and black line, Lake Woodruff  =  white circles and dotted line, Lake Apopka  =  gray diamonds and gray line. Letters represent significant differences among sites. Numbers within bars represent sample size. Error bars are ± SE. A. Snouth-vent length (SVL) measurements at hatching. B. Body mass measurements at hatching. C. Linear regression of body mass growth rates and mean body mass of captive reared juvenile alligators from three central Florida sites. R² values were 0.997 for Lake Apopka, 0.993 for Merritt Island, and 0.997 for Lake Woodruff. D. Linear regression of snout-to-vent- length (SVL) growth rates and mean SVL mass of captive reared juvenile alligators from three central Florida sites. R² values were 0.705 for Lake Apopka, 0.383 for Merritt Island, and 0.623 for Lake Woodruff respectively. E. Analysis of mean body mass adjusted rate of body mass gain in captive juvenile alligators from three different sites. F. ANCOVA of mean SVL adjusted rate of SVL gain in captive juvenile alligators from Lake Woodruff and Lake Apopka.</p

Mean classification for thyroid histological markers of American alligators.

*<p>Indicates statistically different from the reference (LWNWR)</p><p>Number in parenthesis is standard error</p

Thyroid follicular cell hyperplasia.

<p>Mean proportions of follicular cell layers per thyroid gland of alligators from three sites in Florida. Merritt Island  =  black, Lake Woodruff  =  white, Lake Apopka  =  gray. A. Neonatal alligators. (AP: N = 16; MINWR: N = 11; LWNWR: N = 13) B. Juvenile alligators (N = 18 for all sites). Error bars are ± SEM. Letters represent significant differences among sites within follicular cell layer classifications.</p

Animal-Borne Imaging Reveals Novel Insights into the Foraging Behaviors and Diel Activity of a Large-Bodied Apex Predator, the American Alligator (<i>Alligator mississippiensis</i>)

<div><p>Large-bodied, top- and apex predators (e.g., crocodilians, sharks, wolves, killer whales) can exert strong top-down effects within ecological communities through their interactions with prey. Due to inherent difficulties while studying the behavior of these often dangerous predatory species, relatively little is known regarding their feeding behaviors and activity patterns, information that is essential to understanding their role in regulating food web dynamics and ecological processes. Here we use animal-borne imaging systems (Crittercam) to study the foraging behavior and activity patterns of a cryptic, large-bodied predator, the American alligator (<i>Alligator mississippiensis</i>) in two estuaries of coastal Florida, USA. Using retrieved video data we examine the variation in foraging behaviors and activity patterns due to abiotic factors. We found the frequency of prey-attacks (mean = 0.49 prey attacks/hour) as well as the probability of prey-capture success (mean = 0.52 per attack) were significantly affected by time of day. Alligators attempted to capture prey most frequently during the night. Probability of prey-capture success per attack was highest during morning hours and sequentially lower during day, night, and sunset, respectively. Position in the water column also significantly affected prey-capture success, as individuals’ experienced two-fold greater success when attacking prey while submerged. These estimates are the first for wild adult American alligators and one of the few examples for any crocodilian species worldwide. More broadly, these results reveal that our understandings of crocodilian foraging behaviors are biased due to previous studies containing limited observations of cryptic and nocturnal foraging interactions. Our results can be used to inform greater understanding regarding the top-down effects of American alligators in estuarine food webs. Additionally, our results highlight the importance and power of using animal-borne imaging when studying the behavior of elusive large-bodied, apex predators, as it provides critical insights into their trophic and behavioral interactions.</p></div

AIC values for Poisson GLMs, predicting prey-capture attempt frequency.

<p>AIC values for Poisson GLMs, predicting prey-capture attempt frequency.</p

Two sided <i>P</i>-values from random permutation test for independence of proportion spent performing activities from time of day.

<p><b>Bold</b> values indicate significant effect of time of day on the proportion of time spent performing an activity.</p

Study sites and capture locations.

<p>A) Map of southeastern United States, study areas are labeled by black boxes. B) Map of Guana Lake. C) Map of Merritt Island National Wildlife Refuge (MINWR). Red circles indicate capture and release locations of American alligators outfitted with Crittercam units. All image data was sourced from USGS National Map Viewer: <a href="http://viewer.nationalmap.gov/viewer/" target="_blank">http://viewer.nationalmap.gov/viewer/</a>. Maps were created with Grass GIS analysis software (CC-BY-SA): <a href="http://grass.osgeo.org/" target="_blank">http://grass.osgeo.org/</a>.</p