Hawthorne L. Beyer

WOLVES INFLUENCE ELK MOVEMENTS: BEHAVIOR SHAPES A TROPHIC CASCADE IN YELLOWSTONE NATIONAL PARK

A trophic cascade recently has been reported among wolves, elk, and aspen on the northern winter range of Yellowstone National Park, Wyoming, USA, but the mechanisms of indirect interactions within this food chain have yet to be established. We investigated whether the observed trophic cascade might have a behavioral basis by exploring environmental factors influencing the movements of 13 female elk equipped with GPS radio collars. We developed a simple statistical approach that can unveil the concurrent influence of several environmental features on animal movements. Paths of elk traveling on their winter range were broken down into steps, which correspond to the straight-line segment between successive locations at 5-hour intervals. Each observed step was paired with 200 random steps having the same starting point, but differing in length and/or direction. Comparisons between the characteristics of observed and random steps using conditional logistic regression were used to model environmental features influencing movement patterns. We found that elk movements were influenced by multiple factors, such as the distance from roads, the presence of a steep slope along the step, and the cover type in which they ended. The influence of cover type on elk movements depended on the spatial distribution of wolves across the northern winter range of the park. In low wolf-use areas, the relative preference for end point locations of steps followed: aspen stands > open areas > conifer forests. As the risks of wolf encounter increased, the preference of elk for aspen stands gradually decreased, and selection became strongest for steps ending in conifer forests in high wolf-use areas. Our study clarifies the behavioral mechanisms involved in the trophic cascade of Yellowstones wolf-elk-aspen system: elk respond to wolves on their winter range by a shift in habitat selection, which leads to local reductions in the use of aspen by elk.

The interpretation of habitat preference metrics under use–availability designs

Models of habitat preference are widely used to quantify animal–habitat relationships, to describe and predict differential space use by animals, and to identify habitat that is important to an animal (i.e. that is assumed to influence fitness). Quantifying habitat preference involves the statistical comparison of samples of habitat use and availability. Preference is therefore contingent upon both of these samples. The inferences that can be made from use versus availability designs are influenced by subjectivity in defining what is available to the animal, the problem of quantifying the accessibility of available resources and the framework in which preference is modelled. Here, we describe these issues, document the conditional nature of preference and establish the limits of inferences that can be drawn from these analyses. We argue that preference is not interpretable as reflecting the intrinsic behavioural motivations of the animal, that estimates of preference are not directly comparable among different samples of availability and that preference is not necessarily correlated with the value of habitat to the animal. We also suggest that preference is context-dependent and that functional responses in preference resulting from changing availability are expected. We conclude by describing advances in analytical methods that begin to resolve these issues.

State-space models link elk movement patterns to landscape characteristics in yellowstone national park

Explaining and predicting animal movement in heterogeneous landscapes remains challenging. This is in part because movement paths often include a series of short, localized displacements separated by longer-distance forays. This multiphasic movement behavior reflects the complex response of an animal to present environmental conditions and to its internal behavioral state. This state is an autocorrelated process influenced by preceding behaviors and habitats visited. Movement patterns depending on the behavioral state of an animal represent the broad-scale response of that animal to the environment. Quantifying how animals respond both to local conditions and to their internal state reveals how animals respond to spatial heterogeneity at different spatial scales. We used a state-space statistical approach to model the internal behavioral state and the proximate movement response of elk (Cervus elaphus) to available forage biomass, landscape composition, topography, and wolf (Canis lupus) density during summer in Yellowstone National Park, USA. We analyzed movement paths of 16 female elk fitted with global positioning system (GPS) radio collars that recorded locations at 5-h intervals. Habitat variables were quantified within 175 m radii (one-half of the median 5-h displacement) centered on the beginning location of each interval. Stepwise model selection identified models that best explained the movement distances of each animal. The behavioral state changed very slowly for most animals (median autocorrelation r = 0.93), and all animals responded strongly to time of day (with more movement in the crepuscular hours). However, the spatial variables included in the best-fitting models varied substantially among individual elk. These results suggest that strong patterns of habitat selection observed in other studies may result from frequent visits to preferred areas rather than a reduction of movement in those areas.

WILLOW ON YELLOWSTONE'S NORTHERN RANGE: EVIDENCE FOR A TROPHIC CASCADE?

Reintroduction of wolves (Canis lupus) to Yellowstone National Park in 1995-1996 has been argued to promote a trophic cascade by altering elk (Cervus elaphus) density, habitat-selection patterns, and behavior that, in turn, could lead to changes within the plant communities used by elk. We sampled two species of willow (Salix boothii and S. geyeriana) on the northern winter range to determine whether (1) there was quantitative evidence of increased willow growth following wolf reintroduction, (2) browsing by elk affected willow growth, and (3) any increase in growth observed was greater than that expected by climatic and hydrological factors alone, thereby indicating a trophic cascade caused by wolves. Using stem sectioning techniques to quantify historical growth patterns we found an approximately twofold increase in stem growth-ring area following wolf reintroduction for both species of willow. This increase could not be explained by climate and hydrological factors alone; the presence of wolves on the landscape was a significant predictor of stem growth above and beyond these abiotic factors. Growth-ring area was positively correlated with the previous years ring area and negatively correlated with the percentage of twigs browsed from the stem during the winter preceding growth, indicating that elk browse impeded stem growth. Our results are consistent with the hypothesis of a behaviorally mediated trophic cascade on Yellowstones northern winter range following wolf reintroduction. We suggest that the community-altering effects of wolf restoration are an endorsement of ecological-process management in Yellowstone National Park.

SCALE-DEPENDENT SUMMER RESOURCE SELECTION BY REINTRODUCED ELK IN WISCONSIN, USA

Abstract Identifying how habitat use is influenced by environmental heterogeneity at different scales is central to understanding ungulate population dynamics on complex landscapes. We used resource selection functions (RSF) to study summer habitat use in a reintroduced and expanding elk (Cervus elaphus nelsoni) population in the Chequamegon National Forest, Wisconsin, USA. Factors were examined that influenced where elk established home ranges and that influenced habitat use within established home ranges. We also determined grain sizes over which elk responded to environmental heterogeneity and the number of categories of habitat selection from low to high that the elk distinguished. At a large spatial extent, elk home-range establishment was largely explained by the spatial distribution of wolf (Canis lupus) territories. Forage abundance was also influential but was relatively more important at a small spatial extent when elk moved within established home ranges. Areas near roads were avoided when establishing a home-range, but areas near roads were selected for use within the established home range. Elk distinguished among 4 different categories of habitat selection when establishing and moving within home ranges. Spatial and temporal cross validation demonstrated that to improve the predictive strength of habitat models in areas of low inter-annual variability in the environment, it is better to follow more individuals across diverse environmental conditions than to follow the same individuals over a longer time period. Last, our results show that the effects of environmental variables on habitat use were scale-dependent and reemphasize the necessity of analyzing habitat use at multiple scales that are fit to address specific research questions.

Functional responses, Seasonal variation and thresholds in behavioural responses of moose to road density

Summary: Understanding the consequences of environmental change on populations is an essential prerequisite for informed management of ecosystems and landscapes. In lieu of quantifying fitness effects directly, which is often difficult, behavioural functional responses provide insight into how animals balance trade-offs, and into thresholds in responses to environmental change. Here, we explore this principle using the response of moose Alces alces L. to roads and restricted-access tracks as a case study. Because roads are associated with the conversion of conifer to mixed deciduous-conifer forest that provides better foraging opportunities, moose in Ontario favour areas of moderate road density at a landscape scale. At a finer scale, however, moose avoid roads. These opposing effects indicate a cost-benefit trade-off. We quantified behavioural responses of moose to roads using road-crossing rate. An expected distribution of crossing rates was derived from correlated random walk null model simulations. Moose exhibited a seasonally variable, nonlinear functional response in road-crossing rate at the within seasonal range scale. A pronounced response to roads was observed when road density reached approximate thresholds of 0·2 and 0·4 km km-2 in summer and winter respectively. Road-crossing rate was proportional to road density, though crossing rates were higher in summer than winter. Crossing rates were best explained by the interaction between mean movement rate and road density. Seasonal differences in road-crossing rate arise from seasonal differences in movement rate and seasonal range area, but not road density within seasonal ranges. Within the protected park, moose did not appear to respond to tracks. Our analysis implies that for the majority of the landscape outside of protected areas the response of moose to roads is pronounced. Synthesis and applications. Identifying thresholds in nonlinear responses to landscape modification is a key management objective as they represent transition zones where small changes can have disproportionately large effects on wildlife populations. We establish these thresholds for moose and roads, but find no response to tracks, implying that the effects of tracks can be mitigated by restricting access to them. We discuss the implications of this work on the problem of moose-vehicle collisions. Identifying thresholds in nonlinear responses to landscape modification is a key management objective as they represent transition zones where small changes can have disproportionately large effects on wildlife populations. We establish these thresholds for moose and roads, but find no response to tracks, implying that the effects of tracks can be mitigated by restricting access to them. We discuss the implications of this work on the problem of moose-vehicle collisions.

Biodiversity Risks from Fossil Fuel Extraction

The overlapping of biodiverse areas and fossil fuel reserves indicates high-risk regions. Despite a global political commitment to reduce biodiversity loss by 2010 through the 2002 Convention on Biological Diversity, declines are accelerating and threats are increasing (1). Major threats to biodiversity are habitat loss, invasion by exotic species and pathogens, and climate change, all principally driven by human activities. Although fossil fuel (FF) extraction has traditionally been seen as a temporary and spatially limited perturbation to ecosystems (2), even local or limited biodiversity loss can have large cascade effects on ecosystem function and productivity. We explore the overlap between regions of high marine and terrestrial biodiversity and FF reserves to identify regions at particular risk of ecosystem destruction and biodiversity loss from exposure to FF extraction.

The effectiveness of Bayesian state‐space models for estimating behavioural states from movement paths

Bayesian state-space movement models have been proposed as a method of inferring behavioural states from movement paths (Morales et al. 2004), thereby providing insight into the behavioural processes from which patterns of animal space use arise in heterogeneous environments. It is not clear, however, how effective state-space models are at estimating behavioural states. We use stochastic simulations of two movement models to quantify how behavioural state movement characteristics affect classification error. State-space movement models can be a highly effective approach to estimating behavioural states from movement paths. Classification accuracy was contingent upon the degree of separation between the distributions that characterize the states (e.g. step length and turn angle distributions) and the relative frequency of the behavioural states. In the best case scenarios classification accuracy approached 100%, but was close to 0% when step length and turn angle distributions of each state were similar, or when one state was rare. Mean classification accuracy was uncorrelated with path length, but the variance in classification accuracy was inversely related to path length. Importantly, we find that classification accuracy can be predicted based on the separation between distributions that characterize the movement paths, thereby providing a method of estimating classification accuracy for real movement paths. We demonstrate this approach using radiotelemetry relocation data of 34 moose (Alces alces). We conclude that Bayesian state-space models offer powerful new opportunities for inferring behavioural states from relocation data.

Competition, predation, and migration: Individual choice patterns of Serengeti migrants captured by hierarchical models

Large-herbivore migrations occur across gradients of food quality or food abundance that are generally determined by underlying geographic patterns in rainfall, elevation, or latitude, in turn causing variation in the degree of interspecific competition and the exposure to predators. However, the role of top-down effects of predation as opposed to the bottom-up effects of competition for resources in shaping migrations is not well understood. We studied 30 GPS radio-collared wildebeest and zebra migrating seasonally in the Serengeti-Mara ecosystem to ask how predation and food availability differentially affect the individual movement patterns of these co-migrating species. A hierarchical analysis of movement trajectories (directions and distances) in relation to grass biomass, high-quality food patches, and predation risk show that wildebeest tend to move in response to food quality, with little attention to predation risk. In contrast, individual zebra movements reflect a balance between the risk of predation and the access to high-quality food of sufficient biomass. Our analysis shows how two migratory species move in response to different attributes of the same landscape. Counterintuitively and in contrast to most other animal movement studies, we find that both species move farther each day when resources are locally abundant than when they are scarce. During the wet season when the quality of grazing is at its peak, both wildebeest and zebra move the greatest distances and do not settle in localized areas to graze for extended periods. We propose that this punctuated movement in high-quality patches is explained by density dependency, whereby large groups of competing individuals (up to 1.65 million grazers) rapidly deplete the localized grazing opportunities. These findings capture the roles of predation and competition in shaping animal migrations, which are often claimed but rarely measured.

Metapopulation dynamics of rabies and the efficacy of vaccination

Spatial structure in a host population results in heterogeneity in transmission dynamics. We used a Bayesian framework to evaluate competing metapopulation models of rabies transmission among domestic dog populations in villages in Tanzania. A proximate indicator of disease, medical records of animal-bite injuries, is used to infer the occurrence (presence/absence) of suspected rabid dog cases in one month intervals. State-space models were used to explore the implications of different levels of reporting probability on model parameter estimates. We find evidence for a relatively high rate of infection of these populations from neighbouring districts or from other species distributed throughout the study area, rather than from adjacent wildlife protected areas, suggesting wildlife is unlikely to be implicated in the long-term persistence of rabies. Stochastic simulation of our highest ranked models in vaccinated and hypothetical unvaccinated populations indicated that pulsed vaccination campaigns occurring from 2002 to 2007 reduced rabies occurrence by 57.3 per cent in vaccinated villages in the 1 year following each pulse, and that a similar regional campaign would deliver an 80.9 per cent reduction in occurrence. This work demonstrates how a relatively coarse, proximate sentinel of rabies infection is useful for making inferences about spatial disease dynamics and the efficacy of control measures.