1,125 research outputs found

    Human Fatalities Resulting from Wild Pig Attacks Worldwide: 2000–2019

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    Although reported to be rare, human fatalities resulting from wild pig (Sus scrofa) attacks do occur. Toward a better understanding of patterns in fatal wild pig attacks, we synthesized worldwide reports of wild pig attacks on humans between 2000 and 2019. We documented 163 separate reports of fatal wild pig attacks that resulted in 172 human deaths. On average, 8.6 human deaths occurred annually due to wild pig attacks during those 2 decades. The majority of fatal attacks resulted in a single human death; however, there were 6 cases in which an individual fatal attack resulted in 2–4 human deaths. These fatal wild pig attacks occurred in 29 countries, mostly within the wild pig’s native global range. Fatal attacks primarily occurred under non-hunting circumstances and involved seemingly unprovoked wild pigs. Under hunting circumstances, fatal attacks primarily involved provoked or wounded wild pigs. Fatal attacks typically involved a solitary wild pig, with 12% involving multiple pigs. Solitary pigs involved in fatal attacks were typically large boars that in most attacks exhibited defensive behaviors, although we discovered 7 attacks during which the pig’s behaviors appeared to be predatory. Three fatal attacks were initially investigated as homicides. Overall, victims of fatal wild pig attacks were between 3 and 85 years old and were traveling on foot when the attack occurred. The majority of victims of fatal attacks were adult (20–59 years old), male, traveling on foot, and working in isolation. Among all fatal attacks, 50% identified the cause of death, which included exsanguination/hemorrhagic shock, severe injury, heart attack, craniocerebral injury, severe injury/disembowelment/intestinal prolapse, and toxemia/septicemia. Fatal wild pig attacks occurred primarily in rural areas, with fatal attacks 390% more likely to occur in rural areas with large populations and at least 45% forested and agricultural cover. The greater the rural human population size within a country is, the greater the number of fatal wild pig attacks

    Quantitative analysis of woodpecker habitat using high-resolution airborne LiDAR estimates of forest structure and composition

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    Light detection and ranging (LiDAR) technology has the potential to radically alter theway researchers and managers collect data onwildlife–habitat relationships. To date, the technology has fostered several novel approaches to characterizing avian habitat, but has been limited by the lack of detailed LiDAR-habitat attributes relevant to species across a continuum of spatial grain sizes and habitat requirements. We demonstrate a novel three-step approach for using LiDAR data to evaluate habitat based on multiple habitat attributes and accounting for their influence at multiple grain sizes using federally endangered red-cockaded woodpecker (RCW; Picoides borealis) foraging habitat data fromthe Savannah River Site (SRS) in South Carolina, USA. First,we used high density LiDAR data (10 returns/m2) to predict detailed forest attributes at 20-mresolution across the entire SRS using a complementary application of nonlinear seemingly unrelated regression andmultiple linear regressionmodels. Next,we expanded on previous applications of LiDAR by constructing 95% joint prediction confidence intervals to quantify prediction error at various spatial aggregations and habitat thresholds to determine a biologically and statistically meaningful grain size. Finally,we used aggregations of 20-m cells and associated confidence interval boundaries to demonstrate a newapproach to produce maps of RCWforaging habitat conditions based on the guidelines described in the species\u27 recovery plan. Predictive power (R2) of regression models developed to populate raster layers ranged from 0.34 to 0.81, and prediction error decreased as aggregate size increased, but minimal reductions in prediction error were observed beyond 0.64-ha (4 × 4 20-m cells) aggregates. Mapping habitat quality while accounting for prediction error provided a robust method to determine the potential range of habitat conditions and specific attributes that were limiting in terms of the amount of suitable habitat. The sequential steps of our analytical approach provide a useful framework to extract detailed and reliable habitat attributes for a forest-dwelling habitat specialist, broadening the potential to apply LiDAR in conservation and management of wildlife populations. A zipped folder of Google maps is attached below as a related file

    Quantitative analysis of woodpecker habitat using high-resolution airborne LiDAR estimates of forest structure and composition

    Get PDF
    Light detection and ranging (LiDAR) technology has the potential to radically alter theway researchers and managers collect data onwildlife–habitat relationships. To date, the technology has fostered several novel approaches to characterizing avian habitat, but has been limited by the lack of detailed LiDAR-habitat attributes relevant to species across a continuum of spatial grain sizes and habitat requirements. We demonstrate a novel three-step approach for using LiDAR data to evaluate habitat based on multiple habitat attributes and accounting for their influence at multiple grain sizes using federally endangered red-cockaded woodpecker (RCW; Picoides borealis) foraging habitat data fromthe Savannah River Site (SRS) in South Carolina, USA. First,we used high density LiDAR data (10 returns/m2) to predict detailed forest attributes at 20-mresolution across the entire SRS using a complementary application of nonlinear seemingly unrelated regression andmultiple linear regressionmodels. Next,we expanded on previous applications of LiDAR by constructing 95% joint prediction confidence intervals to quantify prediction error at various spatial aggregations and habitat thresholds to determine a biologically and statistically meaningful grain size. Finally,we used aggregations of 20-m cells and associated confidence interval boundaries to demonstrate a newapproach to produce maps of RCWforaging habitat conditions based on the guidelines described in the species\u27 recovery plan. Predictive power (R2) of regression models developed to populate raster layers ranged from 0.34 to 0.81, and prediction error decreased as aggregate size increased, but minimal reductions in prediction error were observed beyond 0.64-ha (4 × 4 20-m cells) aggregates. Mapping habitat quality while accounting for prediction error provided a robust method to determine the potential range of habitat conditions and specific attributes that were limiting in terms of the amount of suitable habitat. The sequential steps of our analytical approach provide a useful framework to extract detailed and reliable habitat attributes for a forest-dwelling habitat specialist, broadening the potential to apply LiDAR in conservation and management of wildlife populations. A zipped folder of Google maps is attached below as a related file

    Integrating forest structural diversity measurement into ecological research

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    The measurement of forest structure has evolved steadily due to advances in technology, methodology, and theory. Such advances have greatly increased our capacity to describe key forest structural elements and resulted in a range of measurement approaches from traditional analog tools such as measurement tapes to highly derived and computationally intensive methods such as advanced remote sensing tools (e.g., lidar, radar). This assortment of measurement approaches results in structural metrics unique to each method, with the caveat that metrics may be biased or constrained by the measurement approach taken. While forest structural diversity (FSD) metrics foster novel research opportunities, understanding how they are measured or derived, limitations of the measurement approach taken, as well as their biological interpretation is crucial for proper application. We review the measurement of forest structure and structural diversity—an umbrella term that includes quantification of the distribution of functional and biotic components of forests. We consider how and where these approaches can be used, the role of technology in measuring structure, how measurement impacts extend beyond research, and current limitations and potential opportunities for future research

    Paneth cell - rich regions separated by a cluster of Lgr5+ cells initiate crypt fission in the intestinal stem cell niche

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    The crypts of the intestinal epithelium house the stem cells that ensure the continual renewal of the epithelial cells that line the intestinal tract. Crypt number increases by a process called crypt fission, the division of a single crypt into two daughter crypts. Fission drives normal tissue growth and maintenance. Correspondingly, it becomes less frequent in adulthood. Importantly, fission is reactivated to drive adenoma growth. The mechanisms governing fission are poorly understood. However, only by knowing how normal fission operates can cancer-associated changes be elucidated. We studied normal fission in tissue in three dimensions using high-resolution imaging and used intestinal organoids to identify underlying mechanisms. We discovered that both the number and relative position of Paneth cells and Lgr5+ cells are important for fission. Furthermore, the higher stiffness and increased adhesion of Paneth cells are involved in determining the site of fission. Formation of a cluster of Lgr5+ cells between at least two Paneth-cell-rich domains establishes the site for the upward invagination that initiates fission

    Pathogenetics of alveolar capillary dysplasia with misalignment of pulmonary veins.

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    Alveolar capillary dysplasia with misalignment of pulmonary veins (ACDMPV) is a lethal lung developmental disorder caused by heterozygous point mutations or genomic deletion copy-number variants (CNVs) of FOXF1 or its upstream enhancer involving fetal lung-expressed long noncoding RNA genes LINC01081 and LINC01082. Using custom-designed array comparative genomic hybridization, Sanger sequencing, whole exome sequencing (WES), and bioinformatic analyses, we studied 22 new unrelated families (20 postnatal and two prenatal) with clinically diagnosed ACDMPV. We describe novel deletion CNVs at the FOXF1 locus in 13 unrelated ACDMPV patients. Together with the previously reported cases, all 31 genomic deletions in 16q24.1, pathogenic for ACDMPV, for which parental origin was determined, arose de novo with 30 of them occurring on the maternally inherited chromosome 16, strongly implicating genomic imprinting of the FOXF1 locus in human lungs. Surprisingly, we have also identified four ACDMPV families with the pathogenic variants in the FOXF1 locus that arose on paternal chromosome 16. Interestingly, a combination of the severe cardiac defects, including hypoplastic left heart, and single umbilical artery were observed only in children with deletion CNVs involving FOXF1 and its upstream enhancer. Our data demonstrate that genomic imprinting at 16q24.1 plays an important role in variable ACDMPV manifestation likely through long-range regulation of FOXF1 expression, and may be also responsible for key phenotypic features of maternal uniparental disomy 16. Moreover, in one family, WES revealed a de novo missense variant in ESRP1, potentially implicating FGF signaling in the etiology of ACDMPV

    Search for narrow resonances in dilepton mass spectra in proton-proton collisions at root s=13 TeV and combination with 8 TeV data

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    Observation of Charge-Dependent Azimuthal Correlations in p-Pb Collisions and Its Implication for the Search for the Chiral Magnetic Effect

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    Peer reviewe

    Search for heavy gauge W ' bosons in events with an energetic lepton and large missing transverse momentum at root s=13TeV

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