Peter E. Schlichting

Chronic wasting disease (CWD) is an invariably fatal neurodegenerative disease of cervids detected in wild and captive herds in the United States, Canada, Norway, Sweden, and Finland since its disc...

Members of the family Cervidae, both wild and captive, are becoming increasingly affected by chronic wasting disease (CWD), a prion disease with high transmissibility and a 100% fatality rate [1–3]...

Wild pig ( Sus scrofa Linnaeus, 1758) social behaviour affects disease transmission and landscape-level population management. Recent research has incorporated analysis of social structure to better understand the risk of disease transmission in wild pigs, although the relationship between overall social structure of wild pigs remains unclear. Here, we seek to improve understanding of the spatial and temporal dynamics of wild pig social structure and contact rates to better inform management strategies. Using GPS tracking data, we measured home range overlap, and estimated contact rates of wild pigs at four study sites in the southern USA to identify pairwise social associations (i.e., contacts) based on synchronous movement. Contact rate was strongly associated with home range overlap, but exhibited substantial variation, especially at moderate levels of home range overlap. We found that female–female dyads had higher contact rates and longer duration phases of social association compared to female–male and male–male dyads. We found male–male dyads tended to experience social associations farther from their home range centers than female–female or female–male dyads. Social associations between wild pig dyads are highly dynamic in their spatial and temporal structure. Further, dyads with strong social associations still experience substantial time apart. Our findings highlight the challenges of predicting spatial and social associations in wild pig social pairs due to their dynamic social structure over space and time.

Daily activity patterns of animals can be dynamic across seasons in response to changing environmental conditions. Daily activity, though, has rarely been evaluated in relation to multiple factors (e.g., seasons, demographics, and data collection methods), which could be important for understanding what drives activity patterns. Here, we evaluated the daily activity patterns of a widespread invasive species, wild pigs (Sus scrofa), across two ecologically different study areas at Buck Island Ranch, FL, and Tejon Ranch, CA, from 2015 to 2018. Using GPS telemetry data (62 individuals in FL, 21 individuals in CA) and detections from grids of systematically placed motion‐activated cameras (44 cameras in FL, 48 cameras in CA), we compared activity patterns among seasons, sexes, and data collection methods (GPS and camera traps). Overall, wild pigs were mostly active during crepuscular and nocturnal periods, with their lowest activity during diurnal periods; however, activity patterns varied due to several factors. Daily activity patterns were similar between methods, among seasons, and between sexes in the subtropical climate of Florida. In contrast, daily activity patterns exhibited greater differences between methods and among seasons in California, where seasonal differences in temperature and precipitation were more pronounced. Overall, daily activity patterns estimated using GPS telemetry and camera‐based methods not only exhibited a high degree of overlap in several comparisons but also exhibited marked differences that should be recognized. Given the increasing evaluation of daily activity patterns of animals using multiple types of datasets, our study provides ecologists with valuable information to consider when designing ecological studies, interpreting their results, and comparing research across systems and studies.

Reproduction is the most energetically expensive life stage with the demands of productivity representing a balance between physiological requirements and environmental conditions. Wild pigs (Sus scrofa) throughout most of North America are genetic hybrids of feral domestic pigs and wild boar and have the highest reproductive potential of any wild ungulate. The phenology of reproduction, extent of multiple reproductive events per year, how individual and extrinsic factors contribute to variability in productivity, and impact of genetic lineage on these parameters is not well understood in wild pigs. We quantified reproductive parameters in wild pigs relative to a suite of individual and environmental attributes across seasons and multiple years in South Carolina, USA, from March 2017 and May 2020. We hypothesized that individual attributes (mass, age class, number of teats, rump fat, relative genetic association to wild boar vs. domestic pigs) and extrinsic factors (mast availability) would influence probability of pregnancy and fetal litter size. Wild pigs produced offspring throughout all months with peaks in conception corresponding to a seasonal pulse in food availability. The likelihood of pregnancy was influenced by female mass and nutritional condition and was greatest during years with abundant resources. Similarly, litter size increased with female mass and age, implying larger and older females represent the most important group for population recruitment. In evaluating the relationship between reproductive output and ancestral associations to domestic pigs versus wild boar, the proportion of wild boar ancestry was not an important influence on productivity in our population. We determined juveniles reach a physiological threshold of sexual maturity at approximately 30 kg. Average litter size was comparable to other populations, and wild pigs maintain an average fetal litter size of 5.43 offspring despite 13.6% embryonic mortality. A thorough understanding of biotic and extrinsic factors influencing reproduction are important for realistic population models, which are necessary for identifying areas to focus management needs and implementation.

Sample size sufficiency is a critical consideration for estimating resource selection functions (RSFs) from GPS‐based animal telemetry. Cited thresholds for sufficiency include a number of captured animals and as many relocations per animal N as possible. These thresholds render many RSF‐based studies misleading if large sample sizes were truly insufficient, or unpublishable if small sample sizes were sufficient but failed to meet reviewer expectations. We provide the first comprehensive solution for RSF sample size by deriving closed‐form mathematical expressions for the number of animals M and the number of relocations per animal N required for model outputs to a given degree of precision. The sample sizes needed depend on just 3 biologically meaningful quantities: habitat selection strength, variation in individual selection and a novel measure of landscape complexity, which we define rigorously. The mathematical expressions are calculable for any environmental dataset at any spatial scale and are applicable to any study involving resource selection (including sessile organisms). We validate our analytical solutions using globally relevant empirical data including 5,678,623 GPS locations from 511 animals from 10 species (omnivores, carnivores and herbivores living in boreal, temperate and tropical forests, montane woodlands, swamps and Arctic tundra). Our analytic expressions show that the required M and N must decline with increasing selection strength and increasing landscape complexity, and this decline is insensitive to the definition of availability used in the analysis. Our results demonstrate that the most biologically relevant effects on the utilization distribution (i.e. those landscape conditions with the greatest absolute magnitude of resource selection) can often be estimated with much fewer than animals. We identify several critical steps in implementing these equations, including (a) a priori selection of expected model coefficients and (b) regular sampling of background (pseudoabsence) data within a given definition of availability. We discuss possible methods to identify a priori expectations for habitat selection coefficients, effects of scale on RSF estimation and caveats for rare species applications. We argue that these equations should be a mandatory component for all future RSF studies.

The present study is aimed at evaluating the genetic diversity, genetic status and the extent of hybridization with the domestic horse for the Przhevalski’s horse (Equus ferus przewalskii Poliakov 1881) population free-ranging in the territory of the Chernobyl Exclusion Zone (CEZ) in Belarus and Ukraine. The sample size included 12 individuals (10 sampled in the Belarusian part of the CEZ and 2 from the Ukrainian part of the CEZ). Ten microsatellites recommended by the International Society for Animal Genetics (ISAG) for horse genetic status and pedigree determination were used as markers in this study. The fragment analysis data obtained utilising this microsatellite panel determined that two individuals from Belarus possess no allelic variants typical for Przhevalski’s horse. Most of the other individuals presented diagnostically valuable allelic variants. Demographic history analysis for the population did not indicate any drastic population shrinkage events in the population’s recent history. The studied population is characterised by heterogeneous population structure with signs of inbreeding (0.21 %), intermediate level of genetic diversity (He = 0.63) and allelic richness (5.15), possesses 16 unique alleles among 2 microsatellite loci and valuable alleles for loci HMS3 and HMS7 (46.4 and 67.9 % specific alleles for Przhevalski’s horse, respectively). Genetic structure evaluation for the population was performed via Bayesian population structure analysis and factorial correspondence analysis (FCA), which indicated the presence of intrapopulation genetic subdivision. Taking into account the obtained indicators of genetic diversity, we may conclude on the relatively favourable status of Przewalski’s horse in the exclusion zone with good potential for the long-term existence of the species population in the wild. In order to minimise inbreeding effects and the risk of a decline in genetic diversity in the population of Przewalski’s horse of the exclusion zone, as well as to increase the value of this free-living group to preserve the gene pool of the species as a whole, it is necessary to provide detailed genetic monitoring of the livestock’s state, as well as develop a regional population management plan, including measures aimed to minimise the possibility of further hybridisation of wild horses with domestic ones.

Reliable and efficient population estimates are a critical need for effective management of invasive wild pigs ( Sus scrofa ). We evaluated the use of 10‐day camera grids for rapid population assessment (RPA) of wild pigs at 3 study sites that varied in vegetation communities and wild pig densities. Study areas included Buck Island Ranch, Florida; Tejon Ranch, California; and the Savannah River Site, South Carolina, USA, during 2016–2018. Rapid population assessments grids were composed of baited camera traps spaced approximately 500 or 750 m apart. Two RPA grids were deployed per study site and each grid was deployed twice (4–6 months apart) to assess changes in response to season or population control efforts. We assessed the ability of RPA grids to track population trends, how camera number influenced estimate precision, and how relative abundance indices related to density estimates. We detected changes in occupancy probability, detection probability, and N‐mixture estimates following removal operations and between seasons, but the ability of RPA grids to track population trends was dependent on the statistical method used and number of cameras traps. Increasing the number of cameras traps used in RPA grids increased precision, and these results can be used in determining survey design and estimate choice. We found that estimates of occupancy probability, detection probability, and N‐mixture estimates were positively correlated with spatially explicit capture–recapture density estimates. Thus, these less labor‐intensive estimates from RPA grids showed potential to index the relative abundance of wild pigs in some systems. Our evaluation of RPAs indicates that using study‐specific combinations of statistical method and number of cameras can provide a useful tool for monitoring wild pig presence, tracking population trends, and evaluating the effectiveness of management actions. © 2020 The Wildlife Society.

The metapopulation concept has far-reaching implications in ecology and conservation biology. Hanski’s criteria operationally define metapopulations, yet testing them is hindered by logistical and financial constraints inherent to the collection of long-term demographic data. Hence, ecologists and conservationists often assume metapopulation existence for dispersal-limited species that occupy patchy habitats. To advance understanding of metapopulation theory and improve conservation of metapopulations, we used population and landscape genetic tools to develop a methodological framework for evaluating Hanski’s criteria. We used genotypic data (11 microsatellite loci) from a purported metapopulation of Boreal Chorus Frogs (Pseudacris maculata (Agassiz, 1850)) in Colorado, U.S.A., to test Hanski’s four criteria. We found support for each criterion: (1) significant genetic differentiation between wetlands, suggesting distinct breeding populations; (2) wetlands had small effective population sizes and recent bottlenecks, suggesting populations do not experience long-term persistence; (3) population graphs provided evidence of gene flow between patches, indicating potential for recolonization; and (4) multiscale bottleneck analyses suggest asynchrony, indicating that simultaneous extinction of all populations was unlikely. Our methodological framework provides a logistically and financially feasible alternative to long-term demographic data for identifying amphibian metapopulations.