Environmental drivers of seasonal shifts in abundance of wild pigs (Sus scrofa) in a tropical island environment

Four raster datasets are included that were developed using data derived from game camera traps. These data were used as inputs in a species distribution modeling approach using environmental correlates (please find more detailed information in the referenced publication). The resulting raster datasets are a relative abundance index (0 - 100) of feral pigs on Maui using seasonal (Fall and Spring) and combined annual data as well as an averaged ensemble model using seasonal outputs. For those interested in a single model that best represents average pig distribution please use the averaged ensemble model (Maui_pig_ensemble_distribution.tif). *Please note: Additional raster datasets for feral goat (Maui_feralgoats_distribution.tif) and Axis deer (Maui_axisdeer_distribution.tif) distributions are included but are currently unpublished data. Please reach out should you have any questions.Background: Non-native wild pigs (Sus scrofa) threaten sensitive flora and fauna, cost billions of dollars in economic damage, and pose a significant human–wildlife conflict risk. Despite growing interest in wild pig research, basic life history information is often lacking throughout their introduced range and particularly in tropical environments. Similar to other large terrestrial mammals, pigs possess the ability to shift their range based on local climatic conditions or resource availability, further complicating management decisions. The objectives of this study were to (i) model the distribution and abundance of wild pigs across two seasons within a single calendar year; (ii) determine the most important environmental variables driving changes in pig distribution and abundance; and (iii) highlight key differences between seasonal models and their potential management implications. These study objectives were achieved using zero-inflated models constructed from abundance data obtained from extensive field surveys and remotely sensed environmental variables. Results: Our models demonstrate a considerable change in distribution and abundance of wild pigs throughout a single calendar year. Rainfall and vegetation height were among the most influential variables for pig distribution during the spring, and distance to adjacent forest and vegetation density were among the most significant for the fall. Further, our seasonal models show that areas of high conservation value may be more vulnerable to threats from wild pigs at certain times throughout the year, which was not captured by more traditional modeling approaches using aggregated data. Conclusions: Our results suggest that (i) wild pigs can considerably shift their range throughout the calendar year, even in tropical environments; (ii) pigs prefer dense forested areas in the presence of either hunting pressure or an abundance of frugivorous plants, but may shift to adjacent areas in the absence of either of these conditions; and (iii) seasonal models provide valuable biological information that would otherwise be missed by common modeling approaches that use aggregated data over many years. These findings highlight the importance of considering biologically relevant time scales that provide key information to better inform management strategies, particularly for species whose ranges inc

A comparison of abundance and distribution model outputs using camera traps and sign surveys for feral pigs

Two raster datasets are included that were developed using data derived from game camera traps (Oahu_pigcam_distribution.tif) and visual sign surveys (Oahu_pigsign_distribution.tif). These data were used as inputs in a species distribution modeling approach using environmental correlates (please find more detailed information in the referenced publication). The resulting raster datasets are a relative abundance index (0 - 100) of feral pigs on Oʻahu.Species distribution models play a central role in informing wildlife management. For models to be useful, they must be based on data that best represent the presence or abundance of the species. Data used as inputs in the development of these models can be obtained through numerous methods, each subject to different biases and limitations but, to date, few studies have examined whether these biases result in different predictive spatial models, potentially influencing conservation decisions. In this study, we compare distribution model predictions of feral pig (Sus scrofa) relative abundance using the two most common monitoring methods: detections from camera traps and visual surveys of pig sign. These data were collected during the same period using standardised methods at survey sites generated using a random stratified sampling design. We found that although site-level observed sign data were only loosely correlated with observed camera detections (R2 ¼ 0.32–0.45), predicted sign and camera counts from zero-inflated models were well correlated (R2 ¼ 0.78–0.88). In this study we show one example in which fitting two different forms of abundance data using environmental covariates explains most of the variance between datasets. We conclude that, as long as outputs are produced through appropriate modelling techniques, these two common methods of obtaining abundance data may be used interchangeably to produce comparable distribution maps for decision-making purposes. However, for monitoring purposes, sign and camera trap data may not be used interchangeably at the site level

Large-scale analyses of common and rare variants identify 12 new loci associated with atrial fibrillation

Atrial fibrillation affects more than 33 million people worldwide and increases the risk of stroke, heart failure, and death. Fourteen genetic loci have been associated with atrial fibrillation in European and Asian ancestry groups. To further define the genetic basis of atrial fibrillation, we performed large-scale, trans-ancestry meta-analyses of common and rare variant association studies. The genome-wide association studies (GWAS) included 17,931 individuals with atrial fibrillation and 115,142 referents; the exome-wide association studies (ExWAS) and rare variant association studies (RVAS) involved 22,346 cases and 132,086 referents. We identified 12 new genetic loci that exceeded genome-wide significance, implicating genes involved in cardiac electrical and structural remodeling. Our results nearly double the number of known genetic loci for atrial fibrillation, provide insights into the molecular basis of atrial fibrillation, and may facilitate the identification of new potential targets for drug discovery

SNAPSHOT USA 2019 : a coordinated national camera trap survey of the United States

This article is protected by copyright. All rights reserved.With the accelerating pace of global change, it is imperative that we obtain rapid inventories of the status and distribution of wildlife for ecological inferences and conservation planning. To address this challenge, we launched the SNAPSHOT USA project, a collaborative survey of terrestrial wildlife populations using camera traps across the United States. For our first annual survey, we compiled data across all 50 states during a 14-week period (17 August - 24 November of 2019). We sampled wildlife at 1509 camera trap sites from 110 camera trap arrays covering 12 different ecoregions across four development zones. This effort resulted in 166,036 unique detections of 83 species of mammals and 17 species of birds. All images were processed through the Smithsonian's eMammal camera trap data repository and included an expert review phase to ensure taxonomic accuracy of data, resulting in each picture being reviewed at least twice. The results represent a timely and standardized camera trap survey of the USA. All of the 2019 survey data are made available herein. We are currently repeating surveys in fall 2020, opening up the opportunity to other institutions and cooperators to expand coverage of all the urban-wild gradients and ecophysiographic regions of the country. Future data will be available as the database is updated at eMammal.si.edu/snapshot-usa, as well as future data paper submissions. These data will be useful for local and macroecological research including the examination of community assembly, effects of environmental and anthropogenic landscape variables, effects of fragmentation and extinction debt dynamics, as well as species-specific population dynamics and conservation action plans. There are no copyright restrictions; please cite this paper when using the data for publication.Publisher PDFPeer reviewe

Mammal responses to global changes in human activity vary by trophic group and landscape

Wildlife must adapt to human presence to survive in the Anthropocene, so it is critical to understand species responses to humans in different contexts. We used camera trapping as a lens to view mammal responses to changes in human activity during the COVID-19 pandemic. Across 163 species sampled in 102 projects around the world, changes in the amount and timing of animal activity varied widely. Under higher human activity, mammals were less active in undeveloped areas but unexpectedly more active in developed areas while exhibiting greater nocturnality. Carnivores were most sensitive, showing the strongest decreases in activity and greatest increases in nocturnality. Wildlife managers must consider how habituation and uneven sensitivity across species may cause fundamental differences in human–wildlife interactions along gradients of human influence.Peer reviewe

Atrial fibrillation genetic risk differentiates cardioembolic stroke from other stroke subtypes

AbstractObjectiveWe sought to assess whether genetic risk factors for atrial fibrillation can explain cardioembolic stroke risk.MethodsWe evaluated genetic correlations between a prior genetic study of AF and AF in the presence of cardioembolic stroke using genome-wide genotypes from the Stroke Genetics Network (N = 3,190 AF cases, 3,000 cardioembolic stroke cases, and 28,026 referents). We tested whether a previously-validated AF polygenic risk score (PRS) associated with cardioembolic and other stroke subtypes after accounting for AF clinical risk factors.ResultsWe observed strong correlation between previously reported genetic risk for AF, AF in the presence of stroke, and cardioembolic stroke (Pearson’s r=0.77 and 0.76, respectively, across SNPs with p &lt; 4.4 × 10−4 in the prior AF meta-analysis). An AF PRS, adjusted for clinical AF risk factors, was associated with cardioembolic stroke (odds ratio (OR) per standard deviation (sd) = 1.40, p = 1.45×10−48), explaining ∼20% of the heritable component of cardioembolic stroke risk. The AF PRS was also associated with stroke of undetermined cause (OR per sd = 1.07, p = 0.004), but no other primary stroke subtypes (all p &gt; 0.1).ConclusionsGenetic risk for AF is associated with cardioembolic stroke, independent of clinical risk factors. Studies are warranted to determine whether AF genetic risk can serve as a biomarker for strokes caused by AF.</jats:sec

Quantifying the Impact of Wild Pigs on Global Biodiversity and the Spatiotemporal Ecology of Feral Pigs on Maui, Hawai‘i

Wild pigs (Sus scrofa) are one of the most-wide spread terrestrial mammals on the planet and have costly impacts to both natural and managed environments. They were listed as one of the top 100 world’s worst invasive species and have caused precipitous population declines and extinctions of some of the most critically endangered species on the planet. Their ability to function as both a top predator and destructive herbivore has made them a particularly serious threat throughout island ecosystems where species are not evolutionarily adapted to defend against such behaviors. In continental ecosystems, they have been shown to fundamentally alter predator-prey dynamics, compete with native fauna, and cause billions of dollars of environmental damage. Given the extensive body of literature documenting these various threats there remain large gaps in our basic understanding of pig ecology and the extent at which they threaten biodiversity. To address these knowledge gaps, this thesis quantified the extent of wild pig threats to 59,590 terrestrial taxa using the largest species data base available: The International Union for the Conservation of Nature’s Red List. This thesis also analyzed the spatial ecology of feral pigs on Maui over the spring and fall of 2018 using species distribution models. Results from this thesis indicate that wild pigs threaten 672 taxa world-wide, with plant taxa and herpetofauna (amphibians and reptiles) particularly at risk. Wild pigs threaten nearly as many taxa as domestic dogs and feral cats, who are often regarded by the conservation community as the most problematic invasive species to biodiversity. On Maui, the spatial ecology of feral pigs appeared heavily driven by both temporally variable environmental conditions and differences in hunting pressure. Between the spring and fall of 2018 feral pigs significantly shifted from mixed alien forests into sensitive native mesic shrublands. Management efforts to reduce the significant shift of pig abundance into these sensitive native ecosystems are of the utmost concern

IL23R Variation Determines Susceptibility But Not Disease Phenotype in Inflammatory Bowel Disease

Background & Aims: Identification of inflammatory bowel disease (IBD) susceptibility genes is key to understanding pathogenic mechanisms. Recently, the North American IBD Genetics Consortium provided compelling evidence for an association between ileal Crohn’s disease (CD) and the IL23R gene using genome-wide association scanning. External replication is a priority, both to confirm this finding in other populations and to validate this new technique. We tested for association between IL23R and IBD in a large independent UK panel to determine the size of the effect and explore subphenotype correlation and interaction with CARD15. Methods: Eight single nucleotide polymorphism markers in IL23R tested in the North American study were genotyped in 1902 cases of Crohn’s disease (CD), 975 cases of ulcerative colitis (UC), and 1345 controls using MassARRAY. Data were analyzed using χ2 statistics, and subgroup association was sought. Results: A highly significant association with CD was observed, with the strongest signal at coding variant Arg381Gln (allele frequency, 2.5% in CD vs 6.2% in controls [P = 1.1 × 10−12]; odds ratio, 0.38; 95% confidence interval, 0.29–0.50). A weaker effect was seen in UC (allele frequency, 4.6%; odds ratio, 0.73; 95% confidence interval, 0.55–0.96). Analysis accounting for Arg381Gln suggested that other loci within IL23R also influence IBD susceptibility. Within CD, there were no subphenotype associations or evidence of interaction with CARD15. Conclusions: This study shows an association between IL23R and all subphenotypes of CD with a smaller effect on UC. This extends the findings of the North American study, providing clear evidence that genome-wide association scanning can successfully identify true complex disease genes