Effects of Wild Pig Disturbance on Forest Vegetation and Soils

In North America, wild pigs (Sus scrofa; feral pigs, feral swine, wild boars) are a widespread exotic species capable of creating large‐scale biotic and abiotic landscape perturbations. Quantification of wild pig environmental effects has been particularly problematic in northern climates, where they occur only recently as localized populations at low densities. Between 2016 and 2017, we assessed short‐term (within ~2 yrs of disturbance) effects of a low‐density wild pig population on forest features in the central Lower Peninsula of Michigan, USA. We identified 16 8‐ha sites using global positioning system locations from 7 radio‐collared wild pigs for sampling.Within each site, we conducted fine‐scale assessments at 81 plots and quantified potential disturbance by wild pigs. We defined disturbance as exposure of overturned soil, often resulting from rooting behavior by wild pigs.We quantified ground cover of plants within paired 1‐m2 frames at each plot, determined effects to tree regeneration using point‐centered quarter sampling, and collected soil cores from each plot. We observed less percent ground cover of native herbaceous plants and lower species diversity, particularly for plants with a coefficient of conservatism ≥5, in plots disturbed by wild pigs.We did not observe an increase in colonization of exotic plants following disturbance, though the observed prevalence of exotic plants was low. Wild pigs did not select for tree species when rooting, and we did not detect any differences in regeneration of light‐ and heavy‐seeded tree species between disturbed or undisturbed plots. Magnesium and ammonium content in soils were lower in disturbed plots, suggesting soil disturbance accelerated leaching of macronutrients, potentially altering nitrogen transformation. Our study suggested that disturbances by wild pigs, even at low densities, alters short‐term native herbaceous plant diversity and soil chemistry. Thus, small‐scale exclusion of wild pigs from vulnerable and rare plant communities may be warranted

Behavioral states in space and time: Understanding landscape use by an invasive mammal

Animal movement models can be used to understand species behavior and assist with implementation of management activities. We explored behavioral states of an invasive wild pig (Sus scrofa) population that recently colonized central Michigan, USA, 2014–2018. To quantify environmental factors related to wild pig movement ecology and spatio‐temporal landscape use, we predicted wild pig behavioral states relative to land cover type, landscape structure (i.e., edge and patch cohesion), and weather conditions. We used global positioning system (GPS)‐collars and monitored 8 wild pigs from 2014–2018. We fit local convex hulls and calculated movement metrics revealing 3 wild pig behavioral states (resting, exploratory, and relocating) and constructed a 3‐level model to predict behavioral state probabilities relative to biotic and abiotic conditions. Probabilities of exploratory and resting behaviors were higher nearer to riparian and open herbaceous cover types (oftentimes emergent marsh), indicating that these cover types provided security cover during activity and bedding. Hard mast cover types had a strong positive association with relocating behaviors. More cohesive patches of agriculture and shrub cover types were associated with higher probabilities of exploratory behaviors, while resting was more likely in continuous patches of agriculture (mostly mid‐summer corn). The probability of exploratory behaviors increased exponentially with warming ambient temperature. Our results may be used by managers to develop control strategies conducive to landscape and environmental conditions where the likelihood of encountering wild pigs is highest or targeting wild pigs when in a behavioral state most vulnerable to a particular removal technique

Feasibility and Comparative Effectiveness for the Delivery of the National Diabetes Prevention Program through Cooperative Extension in Rural Communities

The U.S. Cooperative Extension Service (CE) has potential to deliver the National Diabetes Prevention Program (NDPP) to rural residents with prediabetes. However, the CE remains underutilized for the delivery of NDPP. We compared the feasibility/effectiveness of the NDPP (0–6 mos.) delivered by CE personnel to rural residents with prediabetes using Zoom® (CE-Zoom®) or by our research staff using Facebook® (FB). Adults (n = 31, age ~55 years) were enrolled (CE-Zoom® n = 16, FB n = 15). Attendance did not differ significantly between groups (CE Zoom® = 69%, FB = 83%, p = 0.15). Participant retention was similar in the CE Zoom® (88%) and FB groups (87%). CE-Zoom® and FB® groups provided weekly, self-monitoring data for 83% and 84% of the 24 potential weeks, respectively. Six-month weight loss was not different between groups (CE-Zoom® = −5.99 ± 8.0 kg, −5.4%, FB = −1.68 ± 3.3 kg, −1.6% p = 0.13). Participants achieving ≥5% weight loss was greater in the CE-Zoom® (44%) compared with the FB group (7%, p = 0.04). Participants achieving the NDPP program goal for physical activity (≥150 min/week) did not differ (CE-Zoom® = 75%, FB = 67%, p = 0.91). This pilot trial demonstrated the potential feasibility and effectiveness of the NDPP delivered by CE personnel in a group remote format (Zoom®) to adults with prediabetes living in rural areas

The many faces of fear:A synthesis of methodological variation in characterizing predation risk from carnivores

Predators affect prey by killing them directly (lethal effects) and by inducing costly antipredator behaviours in living prey (risk effects). Risk effects can strongly influence prey populations and cascade through trophic systems. A prerequisite for assessing risk effects is characterizing the spatiotemporal variation in predation risk. Risk effects research has experienced rapid growth in the last several decades. However, preliminary assessments of the resultant literature suggest that researchers characterize predation risk using a variety of techniques. The implications of this methodological variation for inference and comparability among studies have not been well recognized or formally synthesized. We couple a literature survey with a hierarchical framework, developed from established theory, to quantify the methodological variation in characterizing risk using carnivore-ungulate systems as a case study. Via this process, we documented 244 metrics of risk from 141 studies falling into at least 13 distinct subcategories within three broader categories. Both empirical and theoretical work suggest risk and its effects on prey constitute a complex, multi-dimensional process with expressions varying by spatiotemporal scale. Our survey suggests this multi-scale complexity is reflected in the literature as a whole but often underappreciated in any given study, which complicates comparability among studies and leads to an overemphasis on documenting the presence of risk effects rather than their mechanisms or scale of influence. We suggest risk metrics be placed in a more concrete conceptual framework to clarify inference surrounding risk effects and their cascading effects throughout ecosystems. We recommend studies (i) take a multi-scale approach to characterizing risk; (ii) explicitly consider 'true' predation risk (probability of predation per unit time); and (iii) use risk metrics that facilitate comparison among studies and the evaluation of multiple competing hypotheses. Addressing the pressing questions in risk effects research, including how, to what extent and on what scale they occur, requires leveraging the advantages of the many methods available to characterize risk while minimizing the confusion caused by variability in their application.The NSF Graduate Research Fellowship Program (RJM), the Michigan State University MasterCard Foundation Scholars Program (ABM), CNPq-Brasil (LA), and the University of Montana Boone and Crockett Program (JJM).http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1365-26562018-07-30cs2017Centre for Wildlife Managemen

ORegAnno 3.0: A community-driven resource for curated regulatory annotation

The Open Regulatory Annotation database (ORegAnno) is a resource for curated regulatory annotation. It contains information about regulatory regions, transcription factor binding sites, RNA binding sites, regulatory variants, haplotypes, and other regulatory elements. ORegAnno differentiates itself from other regulatory resources by facilitating crowd-sourced interpretation and annotation of regulatory observations from the literature and highly curated resources. It contains a comprehensive annotation scheme that aims to describe both the elements and outcomes of regulatory events. Moreover, ORegAnno assembles these disparate data sources and annotations into a single, high quality catalogue of curated regulatory information. The current release is an update of the database previously featured in the NAR Database Issue, and now contains 1 948 307 records, across 18 species, with a combined coverage of 334 215 080 bp. Complete records, annotation, and other associated data are available for browsing and download at http://www.oreganno.org/