Impacts of Heterogeneous Host Densities and Contact Rates on Pathogen Transmission in the Channel Island Fox (Urocyon littoralis).

Diseases threaten wildlife populations worldwide and have caused severe declines resulting in host species being listed as threatened or endangered. The risk of a widespread epidemic is especially high when pathogens are introduced to naive host populations, often leading to high morbidity and mortality. Prevention and control of these epidemics is based on knowledge of what drives pathogen transmission among hosts. Previous disease outbreaks suggest the spread of directly transmitted pathogens is determined by host contact rates and local host density. While theoretical models of disease spread typically assume a constant host density, most wildlife populations occur at a variety of densities across the landscape. We explored how spatial heterogeneity in host density influences pathogen spread by simulating the introduction and spread of rabies and canine distemper in a spatially heterogeneous population of Channel Island foxes (Urocyon littoralis), coupling fox density and contact rates with probabilities of viral transmission. For both diseases, the outcome of pathogen introductions varied widely among simulation iterations and depended on the density of hosts at the site of pathogen introduction. Introductions into areas of higher fox densities resulted in more rapid pathogen transmission and greater impact on the host population than if the pathogen was introduced at lower densities. Both pathogens were extirpated in a substantial fraction of iterations. Rabies was over five times more likely to go locally extinct when introduced at low host density sites than at high host-density sites, leaving an average of >99% of foxes uninfected. Canine distemper went extinct in >98% of iterations regardless of introduction site, but only after >90% of foxes had become infected. Our results highlight the difficulty in predicting the course of an epidemic, in part due to complex interactions between pathogen biology and host behavior, exacerbated by the spatial variation of most host populations.

Defining and evaluating the umbrella species concept for conserving and restoring landscape connectivity.

Conserving or restoring landscape connectivity between patches of breeding habitat is a common strategy to protect threatened species from habitat fragmentation. By managing connectivity for some species, usually charismatic vertebrates, it is often assumed that these species will serve as conservation umbrellas for other species. We tested this assumption by developing a quantitative method to measure overlap in dispersal habitat of 3 threatened species-a bird (the umbrella), a butterfly, and a frog-inhabiting the same fragmented landscape. Dispersal habitat was determined with Circuitscape, which was parameterized with movement data collected for each species. Despite differences in natural history and breeding habitat, we found substantial overlap in the spatial distributions of areas important for dispersal of this suite of taxa. However, the intuitive umbrella species (the bird) did not have the highest overlap with other species in terms of the areas that supported connectivity. Nevertheless, we contend that when there are no irreconcilable differences between the dispersal habitats of species that cohabitate on the landscape, managing for umbrella species can help conserve or restore connectivity simultaneously for multiple threatened species with different habitat requirements.

How complex do models need to be to predict dispersal of threatened species through matrix habitats?

Persistence of species in fragmented landscapes depends on dispersal among suitable breeding sites, and dispersal is often influenced by the "matrix" habitats that lie between breeding sites. However, measuring effects of different matrix habitats on movement and incorporating those differences into spatially explicit models to predict dispersal is costly in terms of time and financial resources. Hence a key question for conservation managers is: Do more costly, complex movement models yield more accurate dispersal predictions? We compared the abilities of a range of movement models, from simple to complex, to predict the dispersal of an endangered butterfly, the Saint Francis' satyr (Neonympha mitchellii francisci). The value of more complex models differed depending on how value was assessed. Although the most complex model, based on detailed movement behaviors, best predicted observed dispersal rates, it was only slightly better than the simplest model, which was based solely on distance between sites. Consequently, a parsimony approach using information criteria favors the simplest model we examined. However, when we applied the models to a larger landscape that included proposed habitat restoration sites, in which the composition of the matrix was different than the matrix surrounding extant breeding sites, the simplest model failed to identify a potentially important dispersal barrier, open habitat that butterflies rarely enter, which may completely isolate some of the proposed restoration sites from other breeding sites. Finally, we found that, although the gain in predicting dispersal with increasing model complexity was small, so was the increase in financial cost. Furthermore, a greater fit continued to accrue with greater financial cost, and more complex models made substantially different predictions than simple models when applied to a novel landscape in which butterflies are to be reintroduced to bolster their populations. This suggests that more complex models might be justifiable on financial grounds. Our results caution against a pure parsimony approach to deciding how complex movement models need to be to accurately predict dispersal through the matrix, especially if the models are to be applied to novel or modified landscapes.

Induced changes in island fox (Urocyon littoralis) activity do not mitigate the extinction threat posed by a novel predator.

Prey response to novel predators influences the impacts on prey populations of introduced predators, bio-control efforts, and predator range expansion. Predicting the impacts of novel predators on native prey requires an understanding of both predator avoidance strategies and their potential to reduce predation risk. We examine the response of island foxes (Urocyon littoralis) to invasion by golden eagles (Aquila chrysaetos). Foxes reduced daytime activity and increased night time activity relative to eagle-naïve foxes. Individual foxes reverted toward diurnal tendencies following eagle removal efforts. We quantified the potential population impact of reduced diurnality by modeling island fox population dynamics. Our model predicted an annual population decline similar to what was observed following golden eagle invasion and predicted that the observed 11% reduction in daytime activity would not reduce predation risk sufficiently to reduce extinction risk. The limited effect of this behaviorally plastic predator avoidance strategy highlights the importance of linking behavioral change to population dynamics for predicting the impact of novel predators on resident prey populations.

Vaccination and monitoring strategies for epidemic prevention and detection in the Channel Island fox (Urocyon littoralis).

Disease transmission and epidemic prevention are top conservation concerns for wildlife managers, especially for small, isolated populations. Previous studies have shown that the course of an epidemic within a heterogeneous host population is strongly influenced by whether pathogens are introduced to regions of relatively high or low host densities. This raises the question of how disease monitoring and vaccination programs are influenced by spatial heterogeneity in host distributions. We addressed this question by modeling vaccination and monitoring strategies for the Channel Island fox (Urocyon littoralis), which has a history of substantial population decline due to introduced disease. We simulated various strategies to detect and prevent epidemics of rabies and canine distemper using a spatially explicit model, which was parameterized from field studies. Increasing sentinel monitoring frequency, and to a lesser degree, the number of monitored sentinels from 50 to 150 radio collared animals, reduced the time to epidemic detection and percentage of the fox population infected at the time of detection for both pathogens. Fox density at the location of pathogen introduction had little influence on the time to detection, but a large influence on how many foxes had become infected by the detection day, especially when sentinels were monitored relatively infrequently. The efficacy of different vaccination strategies was heavily influenced by local host density at the site of pathogen entry. Generally, creating a vaccine firewall far away from the site of pathogen entry was the least effective strategy. A firewall close to the site of pathogen entry was generally more effective than a random distribution of vaccinated animals when pathogens entered regions of high host density, but not when pathogens entered regions of low host density. These results highlight the importance of considering host densities at likely locations of pathogen invasion when designing disease management plans.

Interactions between density, home range behaviors, and contact rates in the Channel Island fox (Urocyon littoralis).

Many of the mechanisms underlying density-dependent regulation of populations, including contest competition and disease spread, depend on contact among neighboring animals. Understanding how variation in population density influences the frequency of contact among neighboring animals is therefore an important aspect to understanding the mechanisms underlying, and ecological consequences of, density-dependent regulation. However, contact rates are difficult to measure in the field and may be influenced by density through multiple pathways. This study explored how local density affects contact rates among Channel Island foxes (Urocyon littoralis) through two pathways: changes in home range size and changes in home range overlap. We tracked 40 radio-collared foxes at four sites on San Clemente Island, California. Fox densities at the four sites ranged from 2.8 ± 1.28 to 42.8 ± 9.43 foxes/km(2). Higher fox densities were correlated with smaller home ranges (R (2) = 0.526, F 1,38 = 42.19, P < 0.001). Thirty foxes wore collars that also contained proximity loggers, which recorded the time and duration of occasions when collared foxes were within 5 m of one another. Contact rates between neighboring fox dyads were positively correlated with home range overlap (R (2)  = 0.341, P = 0.008), but not fox density (R (2)  = 0.012, P = 0.976). Individuals at high densities had more collared neighbors with overlapping home ranges (R (2)  = 0.123, P = 0.026) but not an increase in the amount of contact between individual neighbors. This study was the first time contact rates were directly measured and compared to density and home range overlap. Results suggest that foxes exhibit a threshold in their degree of tolerance for neighbors, overlap is a reliable index of the amount of direct contact between island foxes, and disease transmission rates will likely scale with fox density.

Predicting which species will benefit from corridors in fragmented landscapes from population growth models.

Connecting isolated patches of habitat in fragmented landscapes with corridors is a popular conservation strategy. This strategy is also controversial in large part because of uncertainty about what characteristics of a species and its environment promote corridor use. In this article we address the question, For what types of species will populations benefit from corridors? We asked this question using a model of two logistically growing populations connected by migration in which both emigration and migration success were determined by the presence or absence of a corridor. We found that in the short run (e.g., during recovery from disaster), corridors are most effective for species with fast-growing populations that have low survivorship when dispersing through unsuitable (matrix) habitat. We also found that emigration rates and habitat-specific mortality rates are key determinants of the effects of corridors on population size. In the long term, corridors are most likely to benefit species with slow-growing populations that have low survivorship when dispersing through matrix habitat. Our results confirm the major conclusions from previous empirical studies of corridor benefits. However, most studies fail to consider the most appropriate questions to determine the potential benefits of habitat corridors. First, what is the time scale of the conservation goal? Corridors have positive effects on different suites of species in the short and long term. Second, is the major threat of local extinction due to sustained population decline or boom-bust cycles? Third, what is the migration rate through the matrix? Fourth, what fraction of migrants dispersing through the matrix successfully immigrate to another patch?