Abstract. Estimating abundance is an essential component of monitoring and recovery of rare species, and spatially explicit capture-recapture (SECR) models provide the means for robust density estimation. Previous work has elucidated principles of SECR study design for large, generalist carnivores, but less attention has been paid to study design considerations for smaller species, with less extensive home ranges. Here, we integrated data from an intensive pilot study with simulation modeling to evaluate the influence of survey sampling intensity on precision and accuracy in SECR abundance estimation for a rare lagomorph that specializes on patchily distributed early-successional habitats. Doing so, we obtained the first mark-recapture density estimates for the New England cottontail (Sylvilagus transitionalis). Capture probability and density on the landscape both impacted the required intensity of the sampling design. The optimal study design for robust estimation also required a greater number of traps relative to home range size or spatial extent than those recommended in prior SECR studies. This divergence emphasizes that SECR study design considerations will differ among organisms with varying spatial extent and habitat use. Demonstrating the appropriate sampling design for a study system is important prior to embarking in a SECR study. Integrating pilot empirical data with simulations provides a powerful means for optimizing SECR study design and for facilitating applicability of SECR approaches to a wider array of organisms with varying habitat and space use. This methodology may be employed in planning a monitoring program that maximizes effectiveness while minimizing cost and effort, as part of the adaptive management approach to monitor and recover rare or endangered species.

Bottlenecks, founder events, and genetic drift often result in decreased genetic diversity and increased population differentiation. These events may follow abundance declines due to natural or anthropogenic perturbations, where translocations may be an effective conservation strategy to increase population size. American black bears (Ursus americanus) were nearly extirpated from the Central Interior Highlands, USA by 1920. In an effort to restore bears, 254 individuals were translocated from Minnesota, USA, and Manitoba, Canada, into the Ouachita and Ozark Mountains from 1958 to 1968. Using 15 microsatellites and mitochondrial haplotypes, we observed contemporary genetic diversity and differentiation between the source and supplemented populations. We inferred four genetic clusters: Source, Ouachitas, Ozarks, and a cluster in Missouri where no individuals were translocated. Coalescent models using approximate Bayesian computation identified an admixture model as having the highest posterior probability (0.942) over models where the translocation was unsuccessful or acted as a founder event. Nuclear genetic diversity was highest in the source (AR = 9.11) and significantly lower in the translocated populations (AR = 7.07-7.34; P = 0.004). The Missouri cluster had the lowest genetic diversity (AR = 5.48) and served as a natural experiment showing the utility of translocations to increase genetic diversity following demographic bottlenecks. Differentiation was greater between the two admixed populations than either compared to the source, suggesting that genetic drift acted strongly over the eight generations since the translocation. The Ouachitas and Missouri were previously hypothesized to be remnant lineages. We observed a pretranslocation remnant signature in Missouri but not in the Ouachitas.

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Previously, American black bears (Ursus americanus) were thought to follow the pattern of female philopatry and male-biased dispersal. However, recent studies have identified deviations from this pattern. Such flexibility in dispersal patterns can allow individuals greater ability to acclimate to changing environments. We explored dispersal and spatial genetic relatedness patterns across ten black bear populations-including long established (historic), with known reproduction >50 years ago, and newly established (recent) populations, with reproduction recorded <50 years ago-in the Interior Highlands and Southern Appalachian Mountains, United States. We used spatially explicit, individual-based genetic simulations to model gene flow under scenarios with varying levels of population density, genetic diversity, and female philopatry. Using measures of genetic distance and spatial autocorrelation, we compared metrics between sexes, between population types (historic and recent), and among simulated scenarios which varied in density, genetic diversity, and sex-biased philopatry. In empirical populations, females in recent populations exhibited stronger patterns of isolation-by-distance (IBD) than females and males in historic populations. In simulated populations, low-density populations had a stronger indication of IBD than medium- to high-density populations; however, this effect varied in empirical populations. Condition-dependent dispersal strategies may permit species to cope with novel conditions and rapidly expand populations. Pattern-process modeling can provide qualitative and quantitative means to explore variable dispersal patterns, and could be employed in other species, particularly to anticipate range shifts in response to changing climate and habitat conditions.