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10,356 results for “Severity”
Severe environmental conditions create severe conflicts? A novel ecological pathway to extreme coyote attacks on humans
<p>1) Identifying the circumstances and causes of carnivore attacks on humans is important for prevention of future incidents as well as employing effective wildlife management strategies. Cape Breton Highlands National Park (CBHNP) in Nova Scotia has experienced multiple attacks by coyotes (Canis latrans) on humans, including a fatal attack on an adult in 2009.</p> <p>2) Here we use a combination of data on space use and diet collected from 2011–2013 to reveal that limited resources and a reliance on a large ungulate (moose, Alces americanus) as the mechanism leading to aggression by coyotes in CBHNP.</p> <p>3) Resident coyotes exhibited large home range sizes (mean=77.5 km2) indicative of limited resources and spatiotemporal avoidance of human activity. Carbon (d13C) and nitrogen (d15N) isotope values of sub-sampled coyote whiskers (n=32), which provide a longitudinal record of diet over the months before collection, revealed little intra- and inter-individual variation with nearly all individuals specializing on moose, a pattern that agrees with indices of natural resource availability. Specifically, stable isotope mixing models show that moose was the most important prey for most coyotes (25/32), representing between 41% and 78% of dietary inputs. Only four coyotes exhibited use of anthropogenic resources (food), and only one of seven coyotes involved in attacks on people had been consuming human foods before the attacks.</p> <p>4) Synthesis and Applications: We have described a unique ecological system in which a generalist carnivore has expanded its niche to specialize on a large prey species, with the unfortunate consequence of also expanding pathways to conflicts with people. Our results suggest extreme unprovoked predatory attacks by coyotes on people are likely to be quite rare and associated with unique ecological characteristics. Extreme management actions such as bounties are unnecessary, but managers may need to employ hazing or lethal removal earlier in the conflict process than under normal circumstances. Also, users of these areas should be made aware of the risks coyotes pose and encouraged to take precautions. </p>
Low-severity winds reduce tropical forest structural complexity regardless of climate, topography or forest age
<p>Forests are often exposed to regular, non-severe winds (chronic wind exposure), yet the effect of such winds on canopy structure in tropical forests remains understudied. The height and structural complexity of a forest canopy are strongly and positively correlated with biodiversity and carbon accumulation. Understanding the drivers of canopy structural complexity across broad environmental gradients can therefore improve the mapping and modeling of diversity and carbon dynamics. Here we predict the height and structural complexity of forests in the heterogeneous island of Puerto Rico, with a particular focus on the impacts of chronic wind exposure. To do so, we used remote sensing to randomly sample ~20,000, 0.28 ha forested sites stratified by forest age, and used airborne LiDAR data from 2016 to quantify canopy height and a key metric of structural complexity, rugosity – the standard deviation in canopy height. We then ran random forest models to predict canopy height and rugosity based on chronic wind exposure, forest age, mean annual precipitation, elevation, slope, soil type, soil available water storage, and exposure to two previous hurricanes (in 1989 and 1998). Canopy height was 4 m taller on average (41%) between forests aged 17-25 years and old-growth forests and by 4 m on average (41%) between 1,000 and 2,000 mm<sup>-yr</sup> precipitation, leveling off at 2,000 mm<sup>-yr</sup>. Height was 2.12 m (16%) shorter on average between sites exposed to chronic winds and protected sites after accounting for all other factors. Rugosity was 1 m (32%) greater between the tallest and shortest forests, by 0.5 m (15%) between 1,000 and 2,000 mm<sup>-yr</sup> precipitation, and smaller by 0.5 m (15%) between forests above and below 1,000 m elevation. Rugosity was highest in forests of intermediate age (25-40 years), and lowest in old-growth forests, possibly because of higher elevation and chronic wind exposure in old-growth forests. We found no effect of slope, soil characteristics or previous hurricane exposure on either height or rugosity. Our results suggest that alongside forest age and climate context, chronic wind exposure plays an integral role in shaping the structure and carbon cycle of tropical forests.</p>
Not all roads lead to the immune system: The genetic basis of multiple sclerosis severity
<p>Multiple sclerosis is a leading cause of neurological disability in adults. Heterogeneity in multiple sclerosis clinical presentation has posed a major challenge for identifying genetic variants associated with disease outcomes. To overcome this challenge, we used prospectively ascertained clinical outcomes data from the largest international multiple sclerosis Registry, MSBase. We assembled a cohort of deeply phenotyped individuals of European ancestry with relapse-onset multiple sclerosis. We used unbiased genome-wide association study and machine learning approaches to assess the genetic contribution to longitudinally defined multiple sclerosis severity phenotypes in 1,813 individuals. Our primary analyses did not identify any genetic variants of moderate to large effect sizes that met genome-wide significance thresholds. The strongest signal was associated with rs7289446 (β=-0.4882, P = 2.73 × 10−7), intronic to SEZ6L on chromosome 22. However, we demonstrate that clinical outcomes in relapse-onset multiple sclerosis are associated with multiple genetic loci of small effect sizes. Using a machine learning approach incorporating over 62,000 variants together with clinical and demographic variables available at multiple sclerosis disease onset, we could predict severity with an area under the receiver operator curve of 0.84 (95% CI 0.79–0.88). Our machine learning algorithm achieved positive predictive value for outcome assignation of 80% and negative predictive value of 88%. This outperformed our machine learning algorithm that contained clinical and demographic variables alone (area under the receiver operator curve 0.54, 95% CI 0.48–0.60). Secondary, sex-stratified analyses identified two genetic loci that met genome-wide significance thresholds. One in females (rs10967273; βfemale =0.8289, P = 3.52 × 10<sup>-8</sup>), the other in males (rs698805; βmale = -1.5395, P = 4.35 × 10<sup>-8</sup>), providing some evidence for sex dimorphism in multiple sclerosis severity. Tissue enrichment and pathway analyses identified an overrepresentation of genes expressed in central nervous system compartments generally, and specifically in the cerebellum (P = 0.023). These involved mitochondrial function, synaptic plasticity, oligodendroglial biology, cellular senescence, calcium and g-protein receptor signalling pathways. We further identified six variants with strong evidence for regulating clinical outcomes, the strongest signal again intronic to SEZ6L (adjusted hazard ratio 0.72, P = 4.85 × 10<sup>-4</sup>). Here we report a milestone in our progress towards understanding the clinical heterogeneity of multiple sclerosis outcomes, implicating functionally distinct mechanisms to multiple sclerosis risk. Importantly, we demonstrate that machine learning using common single nucleotide variant clusters, together with clinical variables readily available at diagnosis can improve prognostic capabilities at diagnosis, and with further validation has the potential to translate to meaningful clinical practice change.</p>
Data for: A new paradigm for medium-range severe weather forecasts: Probabilistic random forest-based predictions
<p>Historical observations of severe weather and simulated severe weather environments (i.e., features) from the Global Ensemble Forecast System v12 (GEFSv12) Reforecast Dataset (GEFS/R) are used in conjunction to train and test random forest (RF) machine learning (ML) models to probabilistically forecast severe weather out to days 4–8. RFs are trained with ~9 years of the GEFS/R and severe weather reports to establish statistical relationships. Feature engineering is briefly explored to examine alternative methods for gathering features around observed events, including simplifying features using spatial averaging and increasing the GEFS/R ensemble size with time-lagging. Validated RF models are tested with ~1.5 years of real-time forecast output from the operational GEFSv12 ensemble and are evaluated alongside expert human-generated outlooks from the Storm Prediction Center (SPC). Both RF-based forecasts and SPC outlooks are skillful with respect to climatology at days 4 and 5 with diminishing skill thereafter. The RF-based forecasts exhibit tendencies to slightly underforecast severe weather events, but they tend to be well-calibrated at lower probability thresholds. Spatially averaging predictors during RF training allows for prior-day thermodynamic and kinematic environments to generate skillful forecasts, while time-lagging acts to expand the forecast areas, increasing resolution but decreasing overall skill. The results highlight the utility of ML-generated products to aid SPC forecast operations into the medium range.</p>
Data from: Physiological response of mature red spruce trees to partial and complete sapwood severing
<p> Drought frequency and severity are projected to increase in many regions of the world, yet it remains unclear how mesic forest trees will respond to these novel climate conditions. Experimentally imposing drought in forests at the stand scale is logistically difficult, however, disturbing the hydraulic functioning of individual trees can induce severe water stress and may inform how large trees respond to future droughts. In this study, we manipulated water availability of red spruce (Picea rubens Sarg.) trees by partially or completely severing sapwood, and measured impacts on water relations and photosynthetic efficiency over four months. Trees with total sapwood severed (TOT) experienced a rapid 96.7% reduction in daily sap flow whereas trees with only partial sapwood severed (PAR; estimated 2 – 5% sapwood remaining) and no sapwood severed (CON; phloem girdled) experienced average reductions of 74.3% and 4.6%, respectively. Sapwood severing in TOT trees resulted in declining midday shoot water potential compared to PAR and CON trees, but TOT trees did not surpass the water potential indicative of 50% loss of conductivity until approximately 12 weeks post treatment. At seven weeks post treatment, TOT trees had 6.8 times lower midday stomatal conductance than PAR and CON trees. Furthermore, branch- and crown-wood water potentials reached extreme values (below measurement threshold of -7.7 MPa) in TOT trees by the time of tree harvest at 18 weeks but remained high and did not differ between PAR and CON trees. Our results indicate that with minimal intact sapwood, PAR trees still had sufficient hydraulic functioning to avoid water stress, while TOT trees had temporary resistance to water stress likely associated with declines in carbon sequestration and growth. These findings advance our understanding of how red spruce may physiologically respond to periods of water stress in future climates.</p>
Supplemental materials for Altered expression of several molecular mediators of cerebral spinal fluid production in Hyp mice
<p>X-Linked Hypophosphatemia (XLH) is a genetic disease causing life-long hypophosphatemia due to overproduction of FGF23. XLH is associated with Chiari malformations, cranial synostosis, and syringomyelia. FGF23 signals through FGFR1c and requires a co-receptor, a-Klotho, which is expressed in the renal distal convoluted tubules and the choroid plexus (ChP). In the ChP, a-Klotho participates in regulating cerebral spinal fluid (CSF) production by shuttling the sodium/potassium adenosine triphosphatase (Na+/K+-ATPase) to the luminal membrane. The sodium/potassium/chloride cotransporter 1 (NKCC1) also makes a substantial contribution to CSF production. Real-time PCR (RT-PCR) demonstrated significant upregulation of Klotho transcripts in the fourth ventricle but a trend toward reduced expression in the lateral ventricles of Hyp mice compared to controls. Transcript levels for Fgfr1c were unchanged in Hyp mice. Na+/K+-ATPase alpha-1 subunit transcripts were downregulated in all three ventricles, reaching significance in the third and lateral ventricles. Expression levels of the Slc12a2 transcript (which encodes NKCC1) were unchanged in Hyp mice compared to controls. In situ hybridization (ISH) was used to obtain anatomical corelates to the changes observed by RT-PCR. ISH confirmed the presence of all four transcripts in the lateral ventricle ChP of both WT and Hyp mice. This is the first study to document a significant change in the level of expression of the molecular machinery required for CSF production in Hyp mice. Whether similar changes occur in patients with XLH, potentially contributing to the cranial and spinal cord abnormalities frequently seen in XLH remains to be determined.</p>
Widespread flood severity index time series for Germany
<p>The dataset provides time series from 1951 to 2013 of monthly flood severity index and mean monthly precipitation derived for Germany (DE) and its three hydroclimatic regions (NW: North-Western region; NE: North-Eastern region; South: Southern region). The dataset also provides most frequent event type recorded in Germany for each months. </p> <p>The dataset was used to train and test a dilated Convolutional Neural Network for forecasting monthly flood severity in Germany (Tarasova et al., submitted to Earth's Future). </p>
Data from: Reduced fire severity offers near-term buffer to climate-driven declines in conifer resilience across the western United States
<p>The combination of increasing fire-caused tree mortality and warmer, drier post-fire conditions is making forests in the western United States (West) vulnerable to ecological transformation. Yet, the relative importance of and interactions between these drivers of forest change remain unresolved, particularly over upcoming decades. Here we assess how the interactive impacts of changing climate and wildfire activity influenced conifer regeneration after 334 wildfires, using a novel dataset of post-fire conifer regeneration from 10,230 field plots. Our findings highlight declining regeneration capacity across the West over the past four decades for the eight dominant conifer species studied. Post-fire regeneration is sensitive to high-severity fire, which limits seed availability, and post-fire climate, which influences seedling establishment and survival. In the near-term, projected differences in recruitment probability between low- and high-severity fire scenarios were larger than projected impacts of climate change for most species, suggesting that reductions in fire severity, and resultant impacts on seed availability, could partially offset expected climate-driven declines in post-fire regeneration. Across 40–42% of the study area, we project post-fire conifer regeneration to be likely following low-severity but not high-severity fire under future climate scenarios (2031–2050). However, increasingly warm, dry climate conditions are projected to eventually outweigh the influence of fire severity and seed availability. The percent of the study area considered unlikely to experience conifer regeneration, regardless of fire severity, increased from 5% in 1981–2000 to 26–31% by mid-century, highlighting a limited time window over which management actions that reduce fire severity may effectively support post-fire conifer regeneration.</p>
A method for creating a burn severity atlas: an example from Alberta, Canada
<p>Relativized Burn Ratio (RBR) grids derived from Landsat imagery for large fires in Alberta and adjacent national parks (1985 - 2018).</p>
Raw_data_Combining several indicators to assess the effectiveness of tailor-made health plans in pig farms
<p>Raw data for a paper submitted to Peer Community In Animal Science. </p>
data and code for "Depression and social anxiety in relation to problematic TikTok use severity: The mediating role of boredom proneness and distress intolerance "
<p>data and code for the paper titled "Depression and social anxiety in relation to problematic TikTok use severity: The mediating role of boredom proneness and distress intolerance", to be published on Computers in Human Behavior.</p> <p> </p> <p> </p>
Figure data for "Layered structures in the upper several hundred meters of the Moon along the Chang'E-4 rover's first 1000-m traverse"
<p>These are the raw data and derived data used to generate figures in the paper "Layered structures in the upper several hundred meters of the Moon along the Chang'E-4 rover's first 1000-m traverse." The data files are in the .mat format, and each column in the channel 1 files represents one trace, which contains 8192 rows (samples). Channel 1 has a time window of 20480 ns, with a sampling interval of 2.5 ns. The CE4-channel-2-imaging-result file refers to the subsurface profile of the regolith along the traverse, with a distance resolution of 3.74 cm and a depth resolution of 2.54 cm. </p>
Fire severity as a key determinant of aboveground and belowground biological community recovery in managed even-aged boreal forests
<p><span>Changes in fire regime of boreal forests in response to climate warming are expected to impact post-fire recovery. However, quantitative data on how managed forests sustain and recover from recent fire disturbance are limited. </span></p> <p><span>Two years after a large wildfire in managed even-aged boreal forests in Sweden,</span><span> we investigated how recovery of aboveground and belowground communities, i.e., understory vegetation and soil microbial and faunal communities, responded to variation in the severity of soil (i.e., consumption of soil organic matter) and canopy fires (i.e., tree mortality). </span></p> <p><span>While fire overall enhanced diversity of understory vegetation through colonization of fire adapted plant species, it reduced the abundance and diversity of soil biota. We observed contrasting effects of tree- and soil-related fire severity on survival and recovery of understory vegetation and soil biological communities. </span><span>Severe fires that killed overstory <em>Pinus sylvestris</em> promoted a successional stage dominated by the mosses <em>Ceratodon purpureus</em> and <em>Polytrichum juniperum</em>, but reduced regeneration of tree seedlings and disfavoured the ericaceous dwarf-shrub<em> Vaccinium vitis-idaea</em> and the grass<em> Deschampsia flexuos</em>a. Moreover, high tree mortality from fire reduced fungal biomass and changed fungal community composition, in particular that of ectomycorrhizal fungi, and reduced the fungivorous soil Oribatida. In contrast, soil-related fire severity had little impact on vegetation composition, fungal communities and soil animals. Bacterial communities responded to both tree- and soil-related fire severity. </span></p> <p><span>Synthesis: Our results two years post-fire suggest that a change in fire regime from a historically low-severity ground-fire regime, with fires that mainly burns into the soil organic layer, to a </span><span>stand-replacing </span><span>fire regime with a high degree of tree mortality, as may be expected with climate change, is likely to impact the short-term recovery of stand structure and above- and belowground species composition of even-aged <em>P. sylvestris</em> </span><span>boreal forests.</span></p>
COVID-19 and Traffic Safety: Exploring Exposure, Crash Frequency and Severity, and Roadway and Network Design
<p>Early COVID-19 lockdowns in the first half of 2020 largely kept people at home, thereby reducing motor vehicle traffic levels. Theoretically, reduced traffic exposure should have resulted in reduced motor vehicle crashes. However, a variety of factors may have complicated this relationship. In order to better understand the impact of COVID-19 lockdowns on traffic safety outcomes, we explore fatalities, injuries, and total crashes before and during the lockdowns on both the national and state levels. We provide descriptive statistics and create negative binomial regressions exploring the role of vehicle, user, and built environment factors on traffic safety outcomes. Findings suggest that crash counts in Region 6 were 35%-50% lower in 2020 during the COVID-19 lockdowns. Crashes that occurred during the COVID-19 lockdowns were more likely to be more severe. Fatal pedestrian crashes across the U.S. decreased during COVID-19 (although not as much as overall fatal crashes) and fatal bicyclist crash counts increased. Drunk drivers were less prevalent in nationwide fatalities but more prevalent in overall Region 6 crashes. Overall, crashes were more likely single-vehicle fixed-object or rollover crashes involving unsafe speeds. In Texas, suburban areas saw the most crashes before and during COVID-19, although they also saw the greatest decrease. Rural Texas crashes were most likely to result in a fatality or serious injury, and that likelihood got worse during the COVID-19 lockdowns. While Texas freeways and arterials saw the largest decreases in crash counts, these functional classifications still had the most crashes. Urban interstates and rural local roads in Texas were notable because these two functional classifications actually saw increases in the number of fatal and serious injury crashes during COVID-19 lockdowns.</p>
Strong HONO Emissions from Dew and Guttation Evaporation Trigger Severe Photochemical Pollution Formation
<p>Data for the manuscript "Strong HONO Emissions from Dew and Guttation Evaporation Trigger Severe Photochemical Pollution Formation" by Xu et al.</p>
Single-Cell Mapping Reveals Several Immune Subsets Associated with Liver Metastasis of Pancreatic Ductal Adenocarcinoma
<p>Identifying a metastasis-correlated immune cell composition within the tumor microenvironment (TME) of pancreatic ductal adenocarcinoma (PDAC) will help to develop promising and innovative therapeutic strategies. Twenty-six samples from 11 patients (including 11 primary tumor tissues, 10 blood, and 5 lymph nodes) with different stages were used to develop a multiscale immune profile. High-dimensional single-cell analysis with mass cytometry was performed to search for metastasis-correlated immune changes in the microenvironment.</p> <p>The details about the files uploaded are as follows:</p> <p>1. panelA_Blood.zip includes 10 .fcs files from blood samples in Panel A;</p> <p>2. panelA_LN.zip includes 5 .fcs files from lymph node samples in Panel A;</p> <p>3. panelA_Tumor.zip includes 11 .fcs files from tumor tissue samples in Panel A;</p> <p>4. panelB_Tumor.zip includes 11 .fcs files from tumor tissue samples in Panel B;</p> <p>5. panel_metadata.xlsx describes marker used in Panel A and B;</p> <p>6. sample_metadata.xlsx describes detailed sample information.</p>
Incorporating real-time traffic data into air quality mapping uncovers more severe exposure disparities at the community level
<p>Data and codes for the XGBoost model training in our manuscript titled "Incorporating real-time traffic data into air quality mapping uncovers more severe exposure disparities at the community level"</p>
Evaluation of local movement of Bemisia tabaci MEAM1 and tomato severe rugose virus transmission to tomato plants using labeled and unlabeled whiteflies
<p>The data presents the effects of two types of labels on whiteflies' behavior. Besides, it shows the flight distances at close range and ToSRV transmission.</p>
Validation of the EQ-5D-3L in Patients with Severe COVID-19 One Year After Hospital Discharge
<p>This is a prospective cohort study database aimed at validating the EQ-5D-3L in patients with COVID-19 who underwent invasive mechanical ventilation, assessing their quality of life one year after hospital discharge.</p>
Neighbours matter and the weak succumb: chalara ash dieback infection is more severe in trees with fewer conspecific neighbours and lower prior growth rate
<p>The epidemiology and severity of ash dieback (ADB), the disease caused by the ascomycete fungus, <em>Hymenoscyphus</em> <em>fraxineus</em>, has been linked to a variety of site conditions, however, there has been a lack of analysis at an individual-tree scale. <br> <br>Symptoms of ADB were scored on ca. 400 trees of <em>Fraxinus</em> <em>excelsior</em> (ash) in permanent sample plots during two successive years in a UK natural woodland reserve. Using comprehensive plot records maintained since 1945, and detailed spatial records updated since 1977, we assembled an array of potential explanatory variables, including site environment factors, ash tree density, previous and present tree condition and near neighbourhood summary statistics (NNSS), such as species mingling and size dominance. Their impact on the severity of ADB of focal ash trees was tested with generalised linear mixed effects models (GLMM).<br> <br>The severity of ADB was much greater in the lower slope parts of the site with moister soils and least in a managed area subject to tree thinning in the previous 35 years. Severity of ADB had a negative association with focal ash tree prior relative growth rate over a period of a decade immediately before the disease was detected at the site. Greater ADB severity was also significantly associated with smaller diameter-at-breast-height of ash trees. Additionally, ADB was significantly positively associated with a greater proportion of heterospecific trees amongst the six nearest neighbours of the focal tree. <br> <br><em>Synthesis</em>. The relationship of the severity of ADB disease with site environment, tree condition and neighbourhood is complex but nevertheless important in the progression of the disease. The findings suggest some silvicultural interventions, such as thinning to increase the vigour of retained ash trees, might reduce the impact of ADB.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.