A model baiting system suitable for the delivery of an oral rabies vaccine to freeranging raccoons (Procyon lotor) was developed and tested on barrier islands in South Carolina (USA). Features of barrier island physiography and ecology were studied relative to selective bait deployment and site biosecurity. Capture-mark-recapture data were obtained from 228 raccoons. 93 to 100% of placebo baits were consistently disturbed by 7 days post-bait deployment, and bait acceptance rates by raccoons ranged from 49 to 85%, by using a modular systems approach to select the optimum combination of bait attractant, biomarker, matrix, density, and distribution. These results suggest that a large proportion (up to 85%) of a free-ranging island raccoon population can be selectively and safely targeted, marked and monitored utilizing a proposed oral bait delivery system for recombinant or other rabies vaccines.

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BackgroundAnimal use is a dynamic phenomenon, emerging from the movements of animals responding to a changing environment. Interactions between animals are reflected in patterns of joint space use, which are also dynamic. High frequency sampling associated with GPS telemetry provides detailed data that capture space use through time. However, common analyses treat joint space use as static over relatively long periods, masking potentially important changes. Furthermore, linking temporal variation in interactions to covariates remains cumbersome. We propose a novel method for analyzing the dynamics of joint space use that permits straightforward incorporation of covariates. This method builds upon tools commonly used by researchers, including kernel density estimators, utilization distribution intersection metrics, and extensions of linear models.MethodsWe treat the intersection of the utilization distributions of two individuals as a time series. The series is linked to covariates using copula-based marginal beta regression, an alternative to generalized linear models. This approach accommodates temporal autocorrelation and the bounded nature of the response variable. Parameters are easily estimated with maximum likelihood and trend and error structures can be modeled separately. We demonstrate the approach by analyzing simulated data from two hypothetical individuals with known utilization distributions, as well as field data from two coyotes (Canis latrans) responding to appearance of a carrion resource in southern Texas.ResultsOur analysis of simulated data indicated reasonably precise estimates of joint space use can be achieved with commonly used GPS sampling rates (s.e.=0.029 at 150 locations per interval). Our analysis of field data identified an increase in spatial interactions between the coyotes that persisted for the duration of the study, beyond the expected duration of the carrion resource. Our analysis also identified a period of increased spatial interactions before appearance of the resource, which would not have been identified by previous methods.ConclusionsWe present a new approach to the analysis of joint space use through time, building upon tools commonly used by ecologists, that permits a new level of detail in the analysis of animal interactions. The results are easily interpretable and account for the nuances of bounded serial data in an elegant way.

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The landscape of fear (LOF) hypothesis is a unifying idea explaining the effects of predators on the space use of their prey. However, empirical evidence for this hypothesis is mixed. Recent work suggests that the LOF is dynamic, depending on the daily activity of predators, which allows prey to utilize risky places during predator down times. While this notion clarifies some discrepancies between predictions and observations, support for a dynamic LOF remains mixed. The underlying assumption of a dynamic LOF is strong predictability in predator activity cycles. Work in multi-predator systems demonstrates the effect of differential behavior between predator species on the predictions of prey space use. However, none have considered the effect of intraspecific variation in predator behavior.Most, if not all, dynamic LOF studies base inference on the species-level average activity pattern, implicitly assuming similarity within the predator population.We examined the dynamics and intraspecific variation in activity cycles within a population of coyotes (Canis latrans). We found seasonality in the predictability of coyote behavior, as well as divergent nocturnal and crepuscular activity patterns between individuals during summer. Activity dynamics were not related to range size, sex, body mass, or habitat complexity, but did vary by year. These results suggest that the predictability of activity patterns is seasonally dynamic, and failure to account for intraspecific variation in activity may cloud inference in LOF studies. We argue that future studies should not neglect the potential complexity of predator behavior with simplistic assumptions. By considering intraspecific variation in activity patterns, we may gain a clear picture of LOF dynamics.