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

AIC values for logistical GLMs, predicting the probability of prey-capture success.

<p>AIC values for logistical GLMs, predicting the probability of prey-capture success.</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

Crittercam unit attached to American alligator.

<p>Photograph of a 2.6 meter male American alligator (<i>Alligator mississippiensis</i>) with Crittercam unit attached. Reprinted with permission from J.C. Nifong.</p

Alligator diel activity.

<p>Pie-charts of proportion of alligators spent time performing basic activities during A) all recordings, B) Morning (0400–0900), C) Day (0900–1800), D) Evening (1800–2200), and E) Night (2200–0400). Proportions are calculated as the sum of elapsed time performing an activity divided by the total time of video recordings during each time interval.</p