Jake M. Ferguson

Estimating the Diets of Animals Using Stable Isotopes and a Comprehensive Bayesian Mixing Model

Using stable isotope mixing models (SIMMs) as a tool to investigate the foraging ecology of animals is gaining popularity among researchers. As a result, statistical methods are rapidly evolving and numerous models have been produced to estimate the diets of animals—each with their benefits and their limitations. Deciding which SIMM to use is contingent on factors such as the consumer of interest, its food sources, sample size, the familiarity a user has with a particular framework for statistical analysis, or the level of inference the researcher desires to make (e.g., population- or individual-level). In this paper, we provide a review of commonly used SIMM models and describe a comprehensive SIMM that includes all features commonly used in SIMM analysis and two new features. We used data collected in Yosemite National Park to demonstrate IsotopeRs ability to estimate dietary parameters. We then examined the importance of each feature in the model and compared our results to inferences from commonly used SIMMs. IsotopeRs user interface (in R) will provide researchers a user-friendly tool for SIMM analysis. The model is also applicable for use in paleontology, archaeology, and forensic studies as well as estimating pollution inputs.

Loss of animal seed dispersal increases extinction risk in a tropical tree species due to pervasive negative density dependence across life stages

Overhunting in tropical forests reduces populations of vertebrate seed dispersers. If reduced seed dispersal has a negative impact on tree population viability, overhunting could lead to altered forest structure and dynamics, including decreased biodiversity. However, empirical data showing decreased animal-dispersed tree abundance in overhunted forests contradict demographic models which predict minimal sensitivity of tree population growth rate to early life stages. One resolution to this discrepancy is that seed dispersal determines spatial aggregation, which could have demographic consequences for all life stages. We tested the impact of dispersal loss on population viability of a tropical tree species, Miliusa horsfieldii, currently dispersed by an intact community of large mammals in a Thai forest. We evaluated the effect of spatial aggregation for all tree life stages, from seeds to adult trees, and constructed simulation models to compare population viability with and without animal-mediated seed dispersal. In simulated populations, disperser loss increased spatial aggregation by fourfold, leading to increased negative density dependence across the life cycle and a 10-fold increase in the probability of extinction. Given that the majority of tree species in tropical forests are animal-dispersed, overhunting will potentially result in forests that are fundamentally different from those existing now.

The changing anthropogenic diets of American black bears over the past century in Yosemite National Park

We used carbon (δ13C) and nitrogen (δ15N) stable isotopes derived from the tissues of American black bears (Ursus americanus) to estimate the proportion of human-derived foodstuffs and food waste (“human foods”) in the diets of human food-conditioned bears over the past century in Yosemite National Park, located in central–eastern California. Our goal was to understand how the foraging ecology of bears responded to changing management strategies. We found that the proportion of human foods increased in bear diets when park personnel and visitors fed bears intentionally in 1923–1971, remained relatively high and constant after artificial feeding areas were closed, and declined drastically in 1999–2007, following a

Animal-borne imaging reveals novel insights into the foraging behaviors and Diel activity of a large-bodied apex predator, the American alligator (Alligator mississippiensis).

500 000 annual government appropriation used to mitigate human–bear conflicts in the park. This reduction in the amount of human foods in bear diets suggests that Yosemite managers have been successful in reducing the availability of human foods to bears. Yosemite bears currently consume human f...

Predicting the process of extinction in experimental microcosms and accounting for interspecific interactions in single‐species time series

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 (Alligator mississippiensis) 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.

Evidence and implications of higher-order scaling in the environmental variation of animal population growth.

Predicting population extinction risk is a fundamental application of ecological theory to the practice of conservation biology. Here, we compared the prediction performance of a wide array of stochastic, population dynamics models against direct observations of the extinction process from an extensive experimental data set. By varying a series of biological and statistical assumptions in the proposed models, we were able to identify the assumptions that affected predictions about population extinction. We also show how certain autocorrelation structures can emerge due to interspecific interactions, and that accounting for the stochastic effect of these interactions can improve predictions of the extinction process. We conclude that it is possible to account for the stochastic effects of community interactions on extinction when using single-species time series.

An updated perspective on the role of environmental autocorrelation in animal populations.

Significance We show that the variation of plant and animal populations through time can provide basic insights into how populations interact with their environment, even when environmental covariates are unobserved. We contrasted the effects of two types of temporal variation on population dynamics showing that fluctuations in the strength of competition among individuals can change a well-known scaling relation between the population variance and population abundances. The scaling of the population variance is explored using a large database of time series, as well as two well-studied ungulate populations. Our results suggest that higher-order variance scaling may be present in many animal populations, both reducing the long-run population variance relative to the standard model and providing important information on how populations are regulated by their environment. Environmental stochasticity is an important concept in population dynamics, providing a quantitative model of the extrinsic fluctuations driving population abundances. It is typically formulated as a stochastic perturbation to the maximum reproductive rate, leading to a population variance that scales quadratically with abundance. However, environmental fluctuations may also drive changes in the strength of density dependence. Very few studies have examined the consequences of this alternative model formulation while even fewer have tested which model better describes fluctuations in animal populations. Here we use data from the Global Population Dynamics Database to determine the statistical support for this alternative environmental variance model in 165 animal populations and test whether these models can capture known population–environment interactions in two well-studied ungulates. Our results suggest that variation in the density dependence is common and leads to a higher-order scaling of the population variance. This scaling will often stabilize populations although dynamics may also be destabilized under certain conditions. We conclude that higher-order environmental variation is a potentially ubiquitous and consequential property of animal populations. Our results suggest that extinction risk estimates may often be overestimated when not properly taking into account how environmental fluctuations affect population parameters.

Optimal sampling strategies for detecting zoonotic disease epidemics.

Ecological theory predicts that the presence of temporal autocorrelation in environments can considerably affect population extinction risk. However, empirical estimates of autocorrelation values in animal populations have not decoupled intrinsic growth and density feedback processes from environmental autocorrelation. In this study, we first discuss how the autocorrelation present in environmental covariates can be reduced through nonlinear interactions or by interactions with multiple limiting resources. We then estimated the degree of environmental autocorrelation present in the Global Population Dynamics Database using a robust, model-based approach. Our empirical results indicate that time series of animal populations are affected by low levels of environmental autocorrelation, a result consistent with predictions from our theoretical models. Claims supporting the importance of autocorrelated environments have been largely based on indirect empirical measures and theoretical models seldom anchored in realistic assumptions. It is likely that a more nuanced understanding of the effects of autocorrelated environments is necessary to reconcile our conclusions with previous theory. We anticipate that our findings and other recent results will lead to improvements in understanding how to incorporate fluctuating environments into population risk assessments.

BREEDING SEASON HOME RANGE AND HABITAT USE OF MEXICAN SPOTTED OWLS (STRIX OCCIDENTALIS LUCIDA) BELOW THE SOUTH RIM OF GRAND CANYON NATIONAL PARK

The early detection of disease epidemics reduces the chance of successful introductions into new locales, minimizes the number of infections, and reduces the financial impact. We develop a framework to determine the optimal sampling strategy for disease detection in zoonotic host-vector epidemiological systems when a disease goes from below detectable levels to an epidemic. We find that if the time of disease introduction is known then the optimal sampling strategy can switch abruptly between sampling only from the vector population to sampling only from the host population. We also construct time-independent optimal sampling strategies when conducting periodic sampling that can involve sampling both the host and the vector populations simultaneously. Both time-dependent and -independent solutions can be useful for sampling design, depending on whether the time of introduction of the disease is known or not. We illustrate the approach with West Nile virus, a globally-spreading zoonotic arbovirus. Though our analytical results are based on a linearization of the dynamical systems, the sampling rules appear robust over a wide range of parameter space when compared to nonlinear simulation models. Our results suggest some simple rules that can be used by practitioners when developing surveillance programs. These rules require knowledge of transition rates between epidemiological compartments, which population was initially infected, and of the cost per sample for serological tests.

Selecting the best stable isotope mixing model to estimate grizzly bear diets in the Greater Yellowstone Ecosystem

ABSTRACT We studied breeding season home range characteristics and habitat of paired male Mexican Spotted Owls (Strix occidentalis lucida) below the south rim of Grand Canyon National Park from 2004–2005. Adult male owls (n = 5) were captured and radio-tracked using tail-mounted VHF transmitters. We used minimum convex polygons and 90% fixed kernels to estimate breeding season home range size (mean = 355 ha and 372 ha, respectively). We also generated adaptive kernel home range estimates to describe areas of concentrated use within home ranges. Home ranges were located in the upper reaches of relatively narrow rocky canyons, and Spotted Owls showed limited use of adjacent forested plateaus. We conducted an analysis of habitat use and selection at two scales and found that owls selected (i.e., used disproportionate to availability) limestone cliffs present in their home ranges. Home ranges were approximately centered on nest and associated roost sites located on limestone cliffs within canyons. Our results contrasted with observations in Utah where spotted owls nested primarily on sandstone cliffs. In Grand Canyon, both sandstone and limestone cliffs were present in the home range, but limestone appeared to be the preferred substrate. At the landscape level, owls placed home ranges in areas dominated by piñon-juniper (Pinus edulis – Juniperus monosperma) woodland. We delineated 40 ha use-areas around nest sites and found that these conservation zones closely approximated adaptive kernel 30% isopleths, thus supporting core area designation of the Mexican Spotted Owl Recovery Plan.