Time-to-kill: measuring attack rates in a heterogenous landscape with multiple prey types

Factors influencing space-use and kill distribution of sympatric lion prides in a semi-arid savanna landscape

Understanding lions' (Panthera leo) space-use is important for the management of multi-species wildlife systems because lions can have profound impacts on ecosystem-wide ecological processes. Semi-arid savanna landscapes are typically heterogeneous with species space-use driven by the availability and distribution of resources. Previous studies have demonstrated that lions select areas close to water as encounter rates with prey are higher and hunting success is greater in these regions. Where multiple lion prides exist, landscape partitioning is expected to follow a despotic distribution in which competitively superior prides occupy high-quality areas while subordinates select poorer habitats. In this study, Global Positioning System collar data and logistic regression were used to investigate space-use and hunting success among 50% of lion prides at Malilangwe Wildlife Reserve, Zimbabwe. Our findings show that lion space-use was driven by surface water availability and that home range selection was socially hierarchical with the dominant pride occupying habitat in which water was most abundant. In addition, we found that the effect of shrub cover, clay content and soil depth on kill probability was area specific and not influenced by hierarchical dominance. Where multiple lion prides are studied, we recommend treating prides as individual units because pooling data may obscure site and pride specific response patterns.

Functional Responses Shape Node and Network Level Properties of a Simplified Boreal Food Web

Ecological communities are fundamentally connected through a network of trophic interactions that are often complex and difficult to model. Substantial variation exists in the nature and magnitude of these interactions across various predators and prey and through time. However, the empirical data needed to characterize these relationships are difficult to obtain in natural systems, even for relatively simple food webs. Consequently, prey-dependent relationships and specifically the hyperbolic form (Holling’s Type II), in which prey consumption increases with prey density but ultimately becomes saturated or limited by the time spent handling prey, are most widely used albeit often without knowledge of their appropriateness. Here, we investigate the sensitivity of a simplified food web model for a natural, boreal system in the Kluane region of the Yukon, Canada to the type of functional response used. Intensive study of this community has permitted best-fit functional response relationships to be determined, which comprise linear (type I), hyperbolic (type II), sigmoidal (type III), prey- and ratio-dependent relationships, and inverse relationships where kill rates of alternate prey are driven by densities of the focal prey. We compare node- and network-level properties for a food web where interaction strengths are estimated using best-fit functional responses to one where interaction strengths are estimated exclusively using prey-dependent hyperbolic functional responses. We show that hyperbolic functional responses alone fail to capture important ecological interactions such as prey switching, surplus killing and caching, and predator interference, that in turn affect estimates of cumulative kill rates, vulnerability of prey, generality of predators, and connectance. Exclusive use of hyperbolic functional responses also affected trends observed in these metrics over time and underestimated annual variation in several metrics, which is important given that interaction strengths are typically estimated over relatively short time periods. Our findings highlight the need for more comprehensive research aimed at characterizing functional response relationships when modeling predator-prey interactions and food web structure and function, as we work toward a mechanistic understanding linking food web structure and community dynamics in natural systems.

Hunger mediates apex predator's risk avoidance response in wildland-urban interface

Conflicts between large mammalian predators and humans present a challenge to conservation efforts, as these events drive human attitudes and policies concerning predator species. Unfortunately, generalities portrayed in many empirical carnivore landscape selection studies do not provide an explanation for a predator's occasional use of residential development preceding a carnivore-human conflict event. In some cases, predators may perceive residential development as a risk-reward trade-off. We examine whether state-dependent mortality risk-sensitive foraging can explain an apex carnivore's (Puma concolor) occasional utilization of residential areas. We assess whether puma balance the risk and rewards in a system characterized by a gradient of housing densities ranging from wildland to suburban. Puma GPS location data, characterized as hunting and feeding locations, were used to assess landscape variables governing hunting success and hunting site selection. Hunting site selection behaviour was then analysed conditional on indicators of hunger state. Residential development provided a high energetic reward to puma based on increases in prey availability and hunting success rates associated with increased housing density. Despite a higher energetic reward, hunting site selection analysis indicated that pumas generally avoided residential development, a landscape type attributed with higher puma mortality risk. However, when a puma experienced periods of extended hunger, risk avoidance behaviour towards housing waned. This study demonstrates that an apex carnivore faces a trade-off between acquiring energetic rewards and avoiding risks associated with human housing. Periods of hunger can help explain an apex predator's occasional use of developed landscapes and thus the rare conflicts in the wildland-urban interface. Apex carnivore movement behaviours in relation to human conflicts are best understood as a three-player community-level interaction incorporating wild prey distribution.

Diverse foraging opportunities drive the functional response of local and landscape-scale bear predation on Pacific salmon

The relationship between prey abundance and predation is often examined in single habitat units or populations, but predators may occupy landscapes with diverse habitats and foraging opportunities. The vulnerability of prey within populations may depend on habitat features that hinder predation, and increased density of conspecifics in both the immediate vicinity and the broader landscape. We evaluated the relative effects of physical habitat, local, and neighborhood prey density on predation by brown bears on sockeye salmon in a suite of 27 streams using hierarchical Bayesian functional response models. Stream depth and width were inversely related to the maximum proportion of salmon killed, but not the asymptotic limit on total number killed. Interannual variation in predation was density dependent; the number of salmon killed increased with fish density in each stream towards an asymptote. Seven streams in two geographical groups with ≥23 years of data in common were then analyzed for neighborhood density effects. In most (12 of 18) cases predation in a stream was reduced by increasing salmon abundance in neighboring streams. The uncertainty in the estimates for these neighborhood effects may have resulted from interactions between salmon abundance and habitat that influenced foraging by bears, and from bear behavior (e.g., competitive exclusion) and abundance. Taken together, the results indicated that predator-prey interactions depend on density at multiple spatial scales, and on habitat features of the surrounding landscape. Explicit consideration of this context dependency should lead to improved understanding of the ecological impacts of predation across ecosystems and taxa.

Habitat-mediated timing of migration in polar bears: an individual perspective

Migration phenology is largely determined by how animals respond to seasonal changes in environmental conditions. Our perception of the relationship between migratory behavior and environmental cues can vary depending on the spatial scale at which these interactions are measured. Understanding the behavioral mechanisms behind population‐scale movements requires knowledge of how individuals respond to local cues. We show how time‐to‐event models can be used to predict what factors are associated with the timing of an individual's migratory behavior using data from GPS collared polar bears (Ursus maritimus) that move seasonally between sea ice and terrestrial habitats. We found the concentration of sea ice that bears experience at a local level, along with the duration of exposure to these conditions, was most associated with individual migration timing. Our results corroborate studies that assume thresholds of >50% sea ice concentration are necessary for suitable polar bear habitat; however, continued periods (e.g., days to weeks) of exposure to suboptimal ice concentrations during seasonal melting were required before the proportion of bears migrating to land increased substantially. Time‐to‐event models are advantageous for examining individual movement patterns because they account for the idea that animals make decisions based on an accumulation of knowledge from the landscapes they move through and not simply the environment they are exposed to at the time of a decision. Understanding the migration behavior of polar bears moving between terrestrial and marine habitat, at multiple spatiotemporal scales, will be a major aspect of quantifying observed and potential demographic responses to climate‐induced environmental changes.

Separating spatial search and efficiency rates as components of predation risk

Predation risk is an important driver of ecosystems, and local spatial variation in risk can have population-level consequences by affecting multiple components of the predation process. I use resource selection and proportional hazard time-to-event modelling to assess the spatial drivers of two key components of risk--the search rate (i.e. aggregative response) and predation efficiency rate (i.e. functional response)--imposed by wolves (Canis lupus) in a multi-prey system. In my study area, both components of risk increased according to topographic variation, but anthropogenic features affected only the search rate. Predicted models of the cumulative hazard, or risk of a kill, underlying wolf search paths validated well with broad-scale variation in kill rates, suggesting that spatial hazard models provide a means of scaling up from local heterogeneity in predation risk to population-level dynamics in predator-prey systems. Additionally, I estimated an integrated model of relative spatial predation risk as the product of the search and efficiency rates, combining the distinct contributions of spatial heterogeneity to each component of risk.

Hierarchical predation: wolf (Canis lupus) selection along hunt paths and at kill sites

Predation is a hierarchical process whereby a predator is constrained to killing prey within the area they select while hunting. We demonstrate the hierarchical nature of predation using movement data from six GPS-collared wolves ( Canis lupus L., 1758) in the Rocky Mountains of Alberta, Canada, by coupling the kill locations of their ungulate prey with their preceding hunt path. Selection of where to hunt constrained the characteristics influencing where wolves killed within hunt paths. Specifically, wolves selected to hunt where prey densities were higher than the mean density for their territories, but prey densities were not related to kill site locations within the selected hunt path. Wolves selected to hunt in open valleys and near habitat edges, where prey may be most predictable, detectable, or vulnerable, which may have been reinforced by a higher likelihood of killing within these characteristics along hunt paths. In contrast, wolves selected to hunt relatively farther from frozen water bodies and closer to well sites than kill site locations, indicating different processes were occurring during the hunting and killing phases. Treating predation as a hierarchical sequence will ensure the role of prey and landscape characteristics on the processes of predation are not over- or under-emphasized by decoupling kill sites from hunt paths, which will lead to a better mechanistic understanding of predation in heterogeneous environments.

How linear features alter predator movement and the functional response

In areas of oil and gas exploration, seismic lines have been reported to alter the movement patterns of wolves (Canis lupus). We developed a mechanistic first passage time model, based on an anisotropic elliptic partial differential equation, and used this to explore how wolf movement responses to seismic lines influence the encounter rate of the wolves with their prey. The model was parametrized using 5 min GPS location data. These data showed that wolves travelled faster on seismic lines and had a higher probability of staying on a seismic line once they were on it. We simulated wolf movement on a range of seismic line densities and drew implications for the rate of predator-prey interactions as described by the functional response. The functional response exhibited a more than linear increase with respect to prey density (type III) as well as interactions with seismic line density. Encounter rates were significantly higher in landscapes with high seismic line density and were most pronounced at low prey densities. This suggests that prey at low population densities are at higher risk in environments with a high seismic line density unless they learn to avoid them.