Bayesian model-based age classification using small mammal body mass and capture dates

Accurate age determination is a fundamental prerequisite for demographic studies as well as population monitoring efforts that provide information for management and conservation. Yet, common age determination methods suffer from low accuracy rates, impose additional handling and time costs on animals and biologists, or rely on invasive techniques such as tooth extraction. We introduce an alternative, mixture modeling approach for age determination that exploits mammalian growth patterns to classify newly encountered animals as juveniles or adults, and present an example analysis that classifies Allegheny woodrats based solely on their capture dates and mass at capture, in combination with data from known adults. We also introduce and validate a simulation-based heuristic to evaluate potential classification accuracy when no known-age test cases are available. In the Allegheny woodrat example, the mixture model achieved a 90–92% accuracy rate (heuristic range: 89–94%), far better than the 36–43% achieved with a fixed mass criterion, and comparable to accuracies reported for other species using more data-intensive, multivariate classification techniques. The model can be extended to classify multiple age groups, estimate chronological age, or further improve accuracy by including additional morphometric measures

Rooting Out Genetic Structure of Invasive Wild Pigs in Texas

Invasive wild pigs (Sus scrofa), also called feral swine or wild hogs, are recognized as among the most destructive invasive species in the world. Throughout the United States, invasive wild pigs have expanded rapidly over the past 40 years with populations now established in 38 states. Of the estimated 6.9 million wild pigs distributed throughout the United States, Texas supports approximately 40% of the population and similarly bears disproportionate ecological and economic costs. Genetic analyses are an effective tool for understanding invasion pathways and tracking dispersal of invasive species such as wild pigs and have been used recently in California and Florida, USA, which have similarly long-established populations and high densities of wild pigs. Our goals were to use molecular approaches to elucidate invasion and migration processes shaping wild pig populations throughout Texas, compare our results with patterns of genetic structure observed in California and Florida, and provide insights for effective management of this invasive species. We used a high-density single nucleotide polymorphism (SNP) array to evaluate population genetic structure. Genetic clusters of wild pigs throughout Texas demonstrate 2 distinct patterns: weakly resolved, spatially dispersed clusters and well-resolved, spatially localized clusters. The disparity in patterns of genetic structure suggests disparate processes are differentially shaping wild pig populations in various localities throughout the state. Our results differed from the patterns of genetic structure observed in California and Florida, which were characterized by localized genetic clusters. These differences suggest distinct biological and perhaps anthropogenic processes are shaping genetic structure in Texas. Further, these disparities demonstrate the need for location-specific management strategies for controlling wild pig populations and mitigating associated ecological and economic costs

Mitochondrial genome of an Allegheny Woodrat (\u3ci\u3eNeotoma magister\u3c/i\u3e)

The Allegheny woodrat (Neotoma magister) is endemic to the eastern United States. Population numbers have decreased rapidly over the last four decades due to habitat fragmentation, disease-related mortality, genetic isolation and inbreeding depression; however, effective management is hampered by limited genetic resources. To begin addressing this need, we sequenced and assembled the entire Allegheny woodrat mitochondrial genome. The genome assembly is 16,310 base pairs in length, with an overall base composition of 34% adenine, 27% thymine, 26% cytosine and 13% guanine. This resource will facilitate our understanding of woodrat population genetics and behavioral ecology

Genomic tools reveal complex social organization of an invasive large mammal (\u3ci\u3eSus scrofa\u3c/i\u3e)

A comprehensive understanding of sociality in wildlife is vital to optimizing conservation and management efforts. However, sociality is complicated, especially for widely distributed species that exhibit substantive behavioral plasticity. Invasive wild pigs (Sus scrofa), often representing hybrids of European wild boar and domestic pigs, are among the most adaptable and widely distributed large mammals. The social structure of wild pigs is believed to be similar to European wild boar, consisting of matriarchal groups (sounders) and solitary males. However, wild pig social structure is understudied and largely limited to visual observations. Using a hierarchical approach, we incorporated genomic tools to describe wild pig social group composition in two disparate ecoregions within their invaded range in North America. The most common social unit was sounders, which are characterized as the association of two or more breeding-aged wild pigs with or without dependent offspring. In addition to sounders, pseudo-solitary females and male-dominated bachelor groups were observed at a greater frequency than previously reported. Though primarily composed of close female kin, some sounders included unrelated females. Bachelor groups were predominantly composed of young, dispersal-aged males and almost always included only close kin. Collectively, our study suggests social organization of wild pigs in their invaded range is similar to that observed among wild boar but is complex, dynamic, and likely variable across invaded habitats

Reducing Baylisascaris procyonis Roundworm Larvae in Raccoon Latrines

Baylisascaris procyonis roundworms, a parasite of raccoons, can infect humans, sometimes fatally. Parasite eggs can remain viable in raccoon latrines for years. To develop a management technique for parasite eggs, we tested anthelmintic baiting. The prevalence of eggs decreased at latrines, and larval infections decreased among intermediate hosts, indicating that baiting is effective

Optimal spatial prioritization of control resources for elimination of invasive species under demographic uncertainty

Populations of invasive species often spread heterogeneously across a landscape, consisting of local populations that cluster in space but are connected by dispersal. A fundamental dilemma for invasive species control is how to optimally allocate limited fiscal resources across local populations. Theoretical work based on perfect knowledge of demographic connectivity suggests that targeting local populations from which migrants originate (sources) can be optimal. However, demographic processes such as abundance and dispersal can be highly uncertain, and the relationship between local population density and damage costs (damage function) is rarely known. We used a metapopulation model to understand how budget and uncertainty in abundance, connectivity, and the damage function, together impact return on investment (ROI) for optimal control strategies. Budget, observational uncertainty, and the damage function had strong effects on the optimal resource allocation strategy. Uncertainty in dispersal probability was the least important determinant of ROI. The damage function determined which resource prioritization strategy was optimal when connectivity was symmetric but not when it was asymmetric. When connectivity was asymmetric, prioritizing source populations had a higher ROI than allocating effort equally across local populations, regardless of the damage function, but uncertainty in connectivity structure and abundance reduced ROI of the optimal prioritization strategy by 57% on average depending on the control budget. With low budgets (monthly removal rate of 6.7% of population), there was little advantage to prioritizing resources, especially when connectivity was high or symmetric, and observational uncertainty had only minor effects on ROI. Allotting funding for improved monitoring appeared to be most important when budgets were moderate (monthly removal of 13–20% of the population). Our result showed that multiple sources of observational uncertainty should be considered concurrently for optimizing ROI. Accurate estimates of connectivity direction and abundance were more important than accurate estimates of dispersal rates. Developing cost-effective surveillance methods to reduce observational uncertainties, and quantitative frameworks for determining how resources should be spatially apportioned to multiple monitoring and control activities are important and challenging future directions for optimizing ROI for invasive species control programs

Feral swine harming insular sea turtle reproduction: The origin, impacts, behavior and elimination of an invasive species

Feral swine are among the world\u27s most destructive invasive species wherever they are found, with translocations figuring prominently in their range expansions. In contrast, sea turtles are beloved species that are listed as threatened or endangered throughout the world and are the focus of intense conservation efforts. Nest predation by feral swine severely harms sea turtle reproduction in many locations around the world. Here we quantify and economically assess feral swine nest predation at North Island, South Carolina, an important loggerhead sea turtle nesting beach. Feral swine depredation of North Island sea turtle nests was first detected in 2005, with annual nest monitoring initiated in 2010 documenting nearly total losses to feral swine in 2010 and 2011. The cumulative valuation of annual losses for North Island from 2010 to 2016 ranged as high as $1,166,500. To improve nesting success, an integrated approach for eliminating feral swine was implemented in 2010 and greatly intensified in 2013 by adding federal experts. Removal efforts were challenging due to the island\u27s remoteness and impenetrable habitats, weather, hazards in accessing the island, and wariness of the animals, especially as their population diminished. Removal of the final 11 swine required efforts from 2014 to 2016. Nest predation was highly variable and provided another example of the significance of conditioning by feral swine to sea turtle nests on the consequent severity of nest predation. Even the final individual inflicted heavy losses before his removal. Genetic analyses of feral swine removed from North Island and the adjacent mainland revealed that the island\u27s population did not originate from the nearby mainland, meaning they were (illegally) introduced to the island

Feral swine harming insular sea turtle reproduction: The origin, impacts, behavior and elimination of an invasive species

Feral swine are among the world\u27s most destructive invasive species wherever they are found, with translocations figuring prominently in their range expansions. In contrast, sea turtles are beloved species that are listed as threatened or endangered throughout the world and are the focus of intense conservation efforts. Nest predation by feral swine severely harms sea turtle reproduction in many locations around the world. Here we quantify and economically assess feral swine nest predation at North Island, South Carolina, an important loggerhead sea turtle nesting beach. Feral swine depredation of North Island sea turtle nests was first detected in 2005, with annual nest monitoring initiated in 2010 documenting nearly total losses to feral swine in 2010 and 2011. The cumulative valuation of annual losses for North Island from 2010 to 2016 ranged as high as $1,166,500. To improve nesting success, an integrated approach for eliminating feral swine was implemented in 2010 and greatly intensified in 2013 by adding federal experts. Removal efforts were challenging due to the island\u27s remoteness and impenetrable habitats, weather, hazards in accessing the island, and wariness of the animals, especially as their population diminished. Removal of the final 11 swine required efforts from 2014 to 2016. Nest predation was highly variable and provided another example of the significance of conditioning by feral swine to sea turtle nests on the consequent severity of nest predation. Even the final individual inflicted heavy losses before his removal. Genetic analyses of feral swine removed from North Island and the adjacent mainland revealed that the island\u27s population did not originate from the nearby mainland, meaning they were (illegally) introduced to the island

Assessing the utility of metabarcoding for diet analyses of the omnivorous wild pig (\u3ci\u3eSus scrofa\u3c/i\u3e)

Wild pigs (Sus scrofa) are an invasive species descended from both domestic swine and Eurasian wild boar that was introduced to North America during the early 1500s. Wild pigs have since become the most abundant free-ranging exotic ungulate in the United States. Large and ever-increasing populations of wild pigs negatively impact agriculture, sport hunting, and native ecosystems with costs estimated to exceed $1.5 billion/ year within the United States. Wild pigs are recognized as generalist feeders, able to exploit a broad array of locally available food resources, yet their feeding behaviors remain poorly understood as partially digested material is often unidentifiable through traditional stomach content analyses. To overcome the limitation of stomach content analyses, we developed a DNA sequencing-based protocol to describe the plant and animal diet composition of wild pigs. Additionally, we developed and evaluated blocking primers to reduce the amplification and sequencing of host DNA, thus providing greater returns of sequences from diet items. We demonstrate that the use of blocking primers produces significantly more sequencing reads per sample from diet items, which increases the robustness of ascertaining animal diet composition with molecular tools. Further, we show that the overall plant and animal diet composition is significantly different between the three areas sampled, demonstrating this approach is suitable for describing differences in diet composition among the locations