Eastern spotted skunk (Spilogale putorius) populations have declined throughout much of their range in the eastern United States over recent decades. Declines have been attributed to habitat loss or change, increased competition with sympatric mesocarnivore species, or disease. To better understand the extant distribution of spotted skunks in the Appalachian Mountains of western Virginia, USA, we used a detection‐non‐detection sampling approach using baited camera traps to evaluate the influence of landscape‐level environmental covariates on spotted skunk detection probability and site occupancy. We conducted camera trap surveys at 91 sites from January to May in 2014 and 2015. Spotted skunk occupancy was associated with young‐aged forest stands at lower elevations and more mature forest stands at higher elevations. Both land cover types in this region can be characterized as having complex forest structure, providing cover that varies with stand age, species composition, elevation, and management regime. Our results provide insight into factors that influence spotted skunk spatial distribution and habitat selection, information that can be used to generate conservation assessments and inform management decisions. © 2017 The Wildlife Society.

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Wildlife managers tasked with understanding habitat and resource selection at the population level attempt to characterize patterns in nature that aid and inform conservation. Resource selection functions (RSFs), such as discrete choice analyses, are the standard convention to characterize the effects of habitat attributes on resource selection patterns. These tools are invaluable for wildlife management and conservation and have proven successful in numerous studies. However, the analysis of small datasets using RSF becomes problematic when attempting to account for complex sources of variation, and the inclusion of factors such as weather or intrinsic variation on target species' response may produce models with poor predictive ability. We compared the application of generalized linear mixed-effects modeling (GLMM) and redundancy analysis (RDA) on Appalachian spotted skunk (Spilogale putorius putorius) den selection data at four study sites within the George Washington, Jefferson, and Monongahela National Forests, and surrounding private lands in the Appalachian Mountains of western Virginia and northeastern West Virginia. We assessed the need for the inclusion of alternative sources of variation (i.e., weather conditions and individual intrinsic variation) in addition to standard habitat attributes to better identify sources of variation in den selection. The RDA elucidated complex and opposing relationships, whereby den type use was based on reproductive status or weather condition, which were not evident in the GLMM model that relied solely on habitat measures. Our results demonstrated the importance of examining resource selection data using multivariate techniques in addition to conventional discrete choice analyses to better understand intricate habitat-species relationships, especially for small datasets. Furthermore, from our analyses, we proposed that spotted skunks are neither a true generalist nor specialist species. We introduced and define the term "conditional specialist" to represent a species that is conditionally selective of a given resource in response to one or more current environmental or intrinsic conditions.

Allegheny woodrats Neotoma magister are an imperiled small mammal species most associated with emergent rock habitats in the central Appalachian Mountains and the Ohio River Valley. The monitoring of populations and their spatio-temporal distributions typically has relied on labor-intensive live-trapping. The use of remote-detecting cameras holds promise for being an equally or more effective method to determine species presence, although trap-based captures permit the estimation of other parameters (e.g., survival, population size, site fidelity). In 2017, 2018, and 2020 we compared standard live-trapping with paired cameras for determining site occupancy of Allegheny woodrats in the central Appalachian Mountains of western Virginia. We further examined the influence of baited versus unbaited cameras at several sites of confirmed occupancy in 2019. We observed that the detection probability using cameras was approximately 1.7 times that of live-traps. Also, detection probability at baited camera traps was 1.3–2.0 times that of unbaited camera traps. Estimates of occupancy ranged from 0.44 to 0.49. Our findings suggest that the use of baited remote-detecting cameras provides a more effective method than live-trapping for detecting Allegheny woodrats. Our study provides a framework for the development of a large-scale, long-term monitoring protocol of Allegheny woodrats with the goals of identifying changes in the distribution of the species and quantifying local extinction and colonization rates at emergent rock outcrops and caves throughout the species’ known distribution.

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Understanding spatiotemporal variation in habitat quality is essential for guiding wildlife reintroduction and restoration programs. The habitat productivity hypothesis posits that home range size is inversely related to habitat quality. Thus, home range size may be used as a proxy for habitat quality and can identify important land cover features for a recovering species. We sought to quantify variation in home range size across the biological cycle (seasons) for a reintroduced elk (Cervus canadensis) population in southwestern Virginia, USA and quantify habitat quality by linking home range sizes to the land cover types they contain using linear mixed-effects models. We found mean home range size was largest during late gestation for female elk. Additionally, throughout the year, smaller home ranges were associated with larger proportions of non-forested habitats whereas forested habitats were generally the opposite. However, both presumed poor- and high-quality habitats influenced female elk space use. Our approach revealed spatial variation in habitat quality for a recovering elk herd, demonstrated the importance of non-forested habitats to elk, can guide decisions regarding the location of future elk reintroduction programs, and serve as a model for evaluating habitat quality associated with wildlife reintroductions.

The geographic distribution of a species is a fundamental component in understanding its ecology and is necessary for forming effective conservation plans. For rare and elusive species of conservation concern, accurate maps of predicted occurrence are particularly problematic and often highly subjective. Spilogale putorius (Eastern Spotted Skunk) populations have experienced large declines since the 1940s. Their elusive behavior and perceived rarity result in low detection probability when using conventional methods for sampling small mammals. Low detection probability often causes uncertainty as to where Eastern Spotted Skunks could be a management concern. We modeled the distribution of predicted occurrence of Eastern Spotted Skunks using verifiable occurrence and non-detection records obtained throughout Virginia from 2010 to 2020. Occurrence data consisted of trapping records reported to the Virginia Department of Wildlife Resources, incidental photo-verified reports of sightings and road-killed animals, and remote-camera detections. Non-detections were presumed at baited remote-camera locations following intense survey efforts. We fit predicted occurrence models using generalized linear modeling in an information-theoretic framework using the package 'stats' in Program R. Our results incidated a greater probability of presence from the Blue Ridge westward, increasing with slope steepness along northeastern-to southeastern-facing slopes and decreasing with slope steepness along southeastern-to southwestern-facing slopes. Emergent rock outcrops prominent along northeastern slopes offer ample protective rocky cover, whereas mixed Quercus spp. (oak), Kalmia latifolia (Mountain Laurel), and Rhododendron maximum (Rosebay Rhododendron) forest communities along southern-facing slopes provide suitable areas of cover, both of which are critical for spotted skunk survival and reproductive success. Our analysis provides insight into the relationships between landscape features and Eastern Spotted Skunk distributions across Virginia. Understanding these relationships is critical for the effective management and conservation of this vulnerable species.

Spilogale putorius (Eastern Spotted Skunk) is a small, secretive carnivore that has substantially declined throughout the eastern United States since the mid-1900s. To better understand the current status of Eastern Spotted Skunks, we studied survival and reproduction of the S. p. putorius (Appalachian Spotted Skunk) subspecies across 4 states in the central and southern Appalachian Mountains from 2014 to 2020. Using encounter histories from 99 radio-collared Appalachian Spotted Skunks in a Kaplan-Meier known-fate survival analysis, we calculated a mean annual adult survival rate of 0.58. We did not find support for this survival rate varying by sex, predator cover (canopy cover and topographic ruggedness), or climate. Compared to estimates of survival from previous research, our data suggest that Appalachian Spotted Skunk survival is intermediate to the S. p. interrupta (Plains Spotted Skunk) and S. p. ambarvalis (Florida Spotted Skunk) subspecies of Eastern Spotted Skunk. We located 11 Appalachian Spotted Skunk natal dens and estimated mean litter size to be 2.8 juveniles per female. We used a Lefkovitch matrix to identify the most important demographic rates and found that adult survivorship had the largest impact on the population growth rate. These results provide important demographic information for future Eastern Spotted Skunk population viability analyses and can serve as a baseline for future comparative assessments of the effects of management interventions on the species.