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18,658 results for “impacts”
Dataset for: Paleoenvironmental models for Australia and the impact of aridification on blindsnake diversification
<p><strong>Aim</strong>: Shifts in diversification rates of Australian flora and fauna have been associated with aridification, but the relationship between diversification rates and aridity has never been quantified. We employed multiple approaches to accurately reconstruct paleoenvironments of Australia for the first time. We used this information, and phylogenetic-based analyses, to explore how changes in temperature and increasing aridity during the Neogene influenced the diversification of the Australian blindsnakes. We tested whether diversification rates differ between arid-adapted and mesic-adapted lineages.</p> <p><strong>Taxon</strong>: Typhlopidae, <em>Anilios </em>blindsnakes</p> <p><strong>Location</strong>: Australia</p> <p><strong>Materials and Methods</strong>: We estimated the historical biogeography of blindsnakes using BioGeoBEARS. We synthesised multiple approaches to reconstruct paleotemperature and paleoaridity of Australia during the Neogene. We fit several birth-death models and estimate diversification rates under paleoenvironmental conditions using RPANDA. We further compare diversification rates between arid-adapted lineages versus mesic-adapted lineages using ClaDS and GeoHiSSE.</p> <p><strong>Results</strong>: Ancestral area estimation indicated Australian blindsnakes have tropical grassland origins. We found that Australia-specific regional paleotemperature and paleoaridity provided a better explanation for diversification rate variation than global paleotemperature. Specifically, our best-fitting model indicated that speciation rates of blindsnakes decreased with increasing aridity. We found no difference in diversification rates between arid- and mesic-adapted lineages.</p> <p><strong>Main conclusions</strong>: Soon after dispersing to Australia, the common ancestors of Australian blindsnakes diversified rapidly in mesic habitats during the early Miocene. However, as the continent became increasingly arid, diversification rates decreased. We found that shifts in the environment led to the emergence of two major clades: one remaining in primarily mesic habitats and the other adapting to the expanding arid biome. Our results emphasise the importance of both arid and tropical biomes as sources and sinks of diversification.</p>
Spatiotemporal impacts of ideology and social vulnerability on COVID-19 for the United States
<p><span>In early 2020, the Coronavirus Disease 19 (COVID-19) rapidly spread across the United States, exhibiting significant geographic </span><span>variability. While several studies have examined the predictive relationships of differing factors on COVID-19 deaths, few have </span><span>looked at spatiotemporal variation at refined geographic scales. The objective of this analysis is to examine county-level </span><span>spatiotemporal variation of COVID-19 deaths in association with socioeconomic, health, demographic, and political factors, </span><span>using regionalized multivariate regression as well as nationwide geographically weighted random forest (GWRF) models. </span><span>Regionalized regression results across three time windows—pandemic onset until May 2021, May 2021 through November </span><span>2021, and December 2021 until April 2022—suggest that existing measures of social vulnerability for disaster preparedness </span><span>(SVI) are associated with a higher degree of mortality from COVID-19. In comparison, GWRF models provide a more robust </span><span>evaluation of feature importance and prediction, exposing the importance of local features, such as obesity, which is obscured </span><span>by regional delineation. Overall, GWRF results indicate this more nuanced modeling strategy is useful for capturing the diverse </span><span>spatial and temporal nature of the COVID-19 pandemic.</span></p>
Dataset corresponding to the « Reasons for concern » about climate change impacts from all IPCC reports (TAR to AR6)
<p>This data corresponds to all the "burning embers" diagrams for the "Reasons for Concern" published in IPCC reports (and the related paper Smith et al. 2009 for AR4) until AR6 (thus including TAR, AR4, AR5, SR1.5 and AR6). For TAR to SR1.5, the data is the result of extracting information from the original figures, as presented in the related technical document <a href="https://doi.org/10.5281/zenodo.3992856">10.5281/zenodo.3992856</a>. As also explained in the Supplementary Information of Zommers et al. (2020), the data does not come directly from the IPCC, although it is based on the assessment provided in the IPCC reports listed in the references. For IPCC AR6, the source is the supplementary material of chapter 16. Details regarding specific values provided in the dataset are explained alongside the values in the main file: "RFCs-ALL-2023_05_12.xlsx". </p> <p>The main file includes the parameters needed to produce a diagram that supplements figure 3 from Zommers et al. (2020) with AR6 data and the confidence levels from previous reports when available. The Excel files in RFCs-2023-UsageExamples.zip contain the same data with different parameters, so that uploading these files to the Ember Factory (<a href="https://climrisk.org/emberfactory">https://climrisk.org/emberfactory</a>) produces different figures - including a comparison between AR5 and AR6 (as in IPCC AR6 Synthesis Report, but with AR5 confidence levels included). The resulting diagrams are also provided.</p>
Impact of forest disturbance on microarthropod communities depends on underlying ecological gradient and species traits
<p>Dataset and R scripts used in the publication "Impact of forest disturbance on microarthropod communities depends on underlying ecological gradient and species traits", PeerJ</p>
Data for thesis titled: The impact of processing conditions on enzymatic protein hydrolysis performance from sardine (Sardina pilchardus) by-products using Alcalase 2.4L, and the influence on final spray dried hydrolysate powder properties
<p>The data answer the objectives that focused on:</p> <ol> <li>determining the substrate-specific optimum hydrolysis temperature and pH for the particular enzyme-substrate (Alcalase-sardine by-product) combination,</li> <li>investigating the effect of mixing speed, solids concentration and enzyme dosage on dry solids yield and protein recovery during enzymatic hydrolysis of sardine processing by-products,</li> <li>evaluating the influence of solids concentration on emulsion formation during enzymatic hydrolysis,</li> <li>determining the effect of solids concentration and emulsion formation on molecular weight distribution of protein hydrolysates,</li> <li>investigating the effect of mixing speed and solids concentration on the viscosity and mixing regime of material during enzymatic hydrolysis,</li> <li>establishing the role played by processing conditions (degree of hydrolysis (DH), maltodextrin addition and inlet air temperature) on powder recovery during spray drying, and</li> <li>investigating the role of DH, maltodextrin concentration and spray drying temperature on handling and storage properties of spray dried protein hydrolysates.</li> </ol> <p>This data also appears in journal papers with the following titles:</p> <p>Chiodza, K. & Goosen, N.J. 2023a. Evaluation of handling and storage stability of spray dried protein hydrolysates from sardine (Sardina pilchardus) processing by-products: Effect of enzymatic hydrolysis time, spray drying temperature and maltodextrin concentration. <em>Food and Bioproducts Processing</em>. (June, 30). DOI: <a href="https://www.sciencedirect.com/science/article/pii/S0960308523000743?via%3Dihub">https://doi.org/10.1016/j.fbp.2023.06.009</a>.</p> <p>Chiodza, K. & Goosen, N.J. 2023b. Influence of mixing speed, solids concentration and enzyme dosage on dry solids yield and protein recovery during enzymatic hydrolysis of sardine (Sardina pilchardus) processing by-products using Alcalase 2.4L: a multivariable optimisation approach. <em>Biomass Conversion and Biorefinery</em>. 1:1–23. DOI: <a href="https://link.springer.com/article/10.1007/s13399-023-03829-2">https://doi.org/10.1007/s13399-023-03829-2</a>. </p> <p>Chiodza, K. & Goosen, N.J. 2023c. Emulsion formation during enzymatic protein hydrolysis and its effect on protein recovery and molecular weight distribution of protein hydrolysates from sardine (Sardina pilchardus) by-products. <em>Biomass Conversion and Biorefinery</em>. 1:1–12. DOI: <a href="https://link.springer.com/article/10.1007/s13399-023-04438-9">https://doi.org/10.1007/s13399-023-04438-9</a>.</p>
Data from: Quantifying the impact of crop coverings on honey bee orientation and foraging in sweet cherry orchards using RFID
<p>Advancements in agricultural production have seen the rapid adoption of protected cropping systems globally. Such systems have been optimised for plant growth and efficiency, with little understanding of the potential impacts on key insect pollinators. Here we investigate the effect of netting and polythene rain covers on the health and performance of honey bees (<em>Apis mellifera </em>L.) during the pollination of sweet cherry crops. Over two consecutive seasons, twelve full-strength colonies were equipped with tagged bees and radio frequency identification (RFID) systems. The colonies were equally divided between open control, netted, and polythene (semi-permanent VOEN in 2019 and retractable Cravo in 2020) groups. Over 1,300 individual bees were monitored for the duration of the commercial pollination period to determine behavioural parameters such as foraging commencement age, number and duration of trips, and overall survival. Bees began foraging within the optimum age range (mean 15.7-24.1 days) under all covering types, with little indication of prolonged stress or increased mortality during the short season. Polythene covers (VOEN & Cravo) were found to significantly increase the total time needed for bees to orientate successfully. Once orientated, bees placed under covers conducted up to 155% more foraging trips, with a longer cumulative duration. Covering type was found to significantly impact the amount and type of pollen collected, with the most restrictive system (VOEN) yielding the highest proportion of cherry pollen. Overall, we found little evidence to suggest that protective covers have a detrimental impact on honey bee foraging in cherry crops.</p>
START Workshop - Use of Life Cycle Assessment as an Environmental Impact Tool
<p>Video from an internal workshop on Life Cycle Assessment that was held in June 2023 by 3drivers (speakers were Eduardo Santos and Ana Braga) as a basic training for other consortium members, with the goal of creating a common ground among partners for the subsequent environmental impact assessment activities that START will carry out on the thermoelectric solutions that will be delivered.</p> <p>The video is related to the general introduction given by E. Santos on the basics of the LCA approach and applications. It may be useful to you if new to the topic.</p>
2022 NNLM Member Survey Respondents Impact
<p>Thank-you note for survey respondents describing 2022 Member Survey and highlighting its main findings. </p> <p>This resource is supported by the National Library of Medicine of the National Institutes of Health under Award Number U24LM013751<strong><span>.</span></strong> The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.</p> <p> </p>
Quantification of the global and regional impacts of gas flaring on human health via spatial differentiation
<p>Supplementary material for the associated publication.</p>
Datasets of paper "Towards Assessing the Real-World Impact of Defects in Blockchain-based Smart Contracts"
<p>Datasets of paper "Towards Assessing the Real-World Impact of Defects in Blockchain-based Smart Contracts" published on the 1st International Workshop on Software Defect Datasets (SDD 2023).</p> <p>The GitHub repository is available here: <a href="https://github.com/MichaelHettmer/sdd23">https://github.com/MichaelHettmer/sdd23</a></p>
Carbon storage and carbon-equivalent albedo impact for US forests, by age and forest type
<p>These tables document estimates of carbon storage (Mg/ha +/- Standard Error) and carbon-equivalent albedo impacts (same units) of US forests by age and forest type (Healey et al., in review). Carbon estimates are derived from field measurements made by the USDA Forest Service on approximately 125,000 forested field plots (Domke et al., 2022). Soil organic carbon is omitted from these estimates, but all other above- and below-ground pools are included. Albedo impacts (time-dependent emissions equivalent, TDEE; Bright et al., 2016) were developed by applying atmospheric kernels (Bright and O'Halloran) to a new Landsat blue sky albedo product for the Landsat archive (Erb et al., 2022), as described by Healey et al. (in review). Standard error is supplied for each age/forest type bin for carbon storage, but upper and lower standard error bounds are specified for TDEE because log transformation creates an asymmetrical uncertainty envelope. </p> <p> </p> <p>Bright, Bogren, Bernier, Astrup, (2016). Carbon-equivalent metrics for albedo changes in land management contexts: Relevance of the time dimension. <em>Ecol. Appl.</em> 26, 1868–1880</p> <p>Bright, R. M., & O'Halloran, T. L. (2019). Developing a monthly radiative kernel for surface albedo change from satellite climatologies of Earth's shortwave radiation budget: CACK v1. 0. <em>Geoscientific Model Development, </em>12(9), 3975-3990.</p> <p>Domke, Walters, Nowak, Greenfield, Smith, Nichols, Ogle, Coulston, Wirth (2022). Greenhouse Gas Emissions and Removals From Forest Land, Woodlands, Urban Trees, and Harvested Wood Products in the United States, 1990–2020. (US Dept. Ag. For. Service, Madison, WI; <a href="https://doi.org/10.2737/FS-RU-382">https://doi.org/10.2737/FS-RU-382</a>).</p> <p>Erb, Li, Sun, Paynter, Wang, & Schaaf, (2022). Evaluation of the Landsat-8 Albedo Product across the Circumpolar Domain. <em>Remote Sensing</em>, <em>14</em>(21), 5320.</p> <p>Healey, Yang, Erb, Bright, Domke, Frescino, Schaaf, (in review) New satellite observations expose albedo dynamics offsetting half of carbon storage benefits in US forests.</p>
PoqueiraSurveys: A Dataset on Economic Impact Surveys in the region of Barranco del Poqueira in the Alpujarra Granadina.
<p>This dataset is related to a series of surveys carried out in the Sierra Nevada National Park, specifically in the parking area of the municipality of Pampaneira, in three rounds conducted in January, March and July 2023. The main objective of these surveys was to collect relevant information on the direct and indirect costs associated with visitor travel, as well as relevant socioeconomic data and its impact on the local economy.</p> <p>To ensure that the sample of surveys was representative, they were conducted on alternate days between holidays and working days. In total, 528 valid surveys were collected, divided into 103 in the first round, 105 in the second round and 320 in the third round.</p> <p>The information obtained from these surveys provides a detailed view of how visits to the Sierra Nevada National Park impact the local economy, which is fundamental for decision making and policy planning in the park's management.</p>
Modeling archive of How does humidity data impact land surface modeling of hydrothermal regimes at a permafrost site in Utqiaġvik, Alaska?
<p>Modeling archive contains the meteorological forcings, model input files, and Jupyter notebooks used to generate model meshes and figures for the paper entitled "How does humidity data impact land surface modeling of hydrothermal regimes at a permafrost site in Utqiaġvik, Alaska?"</p>
Data set on the impact of selected plant protection products on ecosystem service providers, including interactive effects
<p>The Excel files contain the results of ecotoxicological tests for the effects of selected insecticides on ESP species. The objective of this dataset is to provide original data from acute and semi-chronic laboratory tests on a few important beneficial species with broad geographic distribution. The data allow the evaluation of delayed effects and possible interactive effects of combined treatments for those pesticides that are commonly used in mixtures or sprayed next to each other in short time intervals, effectively exposing non-target arthropods to combined/sequential effects. Each data file contains the “Description” sheet where all details of the test and the exact meaning of data fields in the database are reported. The data files are named in a self-explanatory manner, starting with the name of the institution that produced the data (UC – University of Coimbra; UJA – Jagiellonian University), followed by the name of the tested species and names of tested products.</p>
The potential impact of climate change on European renewable energy droughts
<p>The file contains a supplementary material for an article entitled <em>The potential impact of climate change on European renewable energy droughts</em> (currently under review):</p> <p>The projected change of the total number of drought days for a wind, solar and hybrid generator in relation to the reference period as predicted by the models considered</p> <p> </p>
Data from: The biogeographic history of neosuchian crocodiles and the impact of saltwater tolerance variability
<p>Extant neosuchian crocodiles are represented by only 24 taxa that are confined to the tropics and subtropics. However, at other intervals during their 200 million-year evolutionary history, the clade reached considerably higher levels of species-richness, matched by more widespread distributions. Neosuchians have occupied numerous habitats and niches, ranging from dwarf riverine forms to large marine predators. Despite numerous previous studies, several unsolved questions remain with respect to their biogeographic history, including the geographic origins of major groups, e.g., Eusuchia and Neosuchia itself. We carried out the most comprehensive biogeographic analysis of Neosuchia to date, based on a multivariate K-means clustering approach followed by the application of two ancestral area estimation methods (BioGeoBEARS and Bayesian Ancestral Location Estimation) applied to two recently published phylogenies. Our results placed the origin of Neosuchia in north-western Pangaea, with subsequent radiations into Gondwana. Eusuchia probably emerged in the European archipelago during the Late Jurassic/Early Cretaceous, followed by dispersal to the North American and Asian landmasses. We show that putative transoceanic dispersal events are statistically significantly less likely to happen in alligatoroids. This finding is consistent with the saltwater intolerant physiology of extant alligatoroids, bolstering inferences of such intolerance in their ancestral lineages.</p>
Data from: The impacts of climate change, energy policy, and traditional ecological practices on future firewood availability for Diné (Navajo) People
<p>These data are part of a data portal that accompanies the special issue 'Climate change adaptation needs a science of culture,' published in Philosophical Transactions of the Royal Society B in 2023. To access the data portal, please visit <a href="https://doi.org/10.5061/dryad.bnzs7h4h4"><strong>https://doi.org/10.5061/dryad.bnzs7h4h4</strong></a>.</p> <p>The files consist of the code of an agent-based model (ABM) in a NetLogo, detailed documentation of the ABM in a standard format, and a table of data exported from the simulation experiment reported on in the paper. By downloading the Netlogo file, one could not only rerun the experiment we report on and recreate the data table but toggle parameters or edit the model to explore other dynamics.</p>
Data for: Drainage impacts on the productivity of wetland species Spartina alterniflora and Salicornia pacifica
<p>Coastal wetlands display ecohydrological zonation such that vertical differences of plant zones are driven by varying groundwater levels over tidal cycles. It is unclear how variable levels of tidal drainage directly impact biotic and abiotic factors in coastal wetland ecosystems. To determine the impacts of drainage levels, simulated tides in mesocosms with varying degrees of drainage were created with <em>Spartina alterniflora</em>, the salt marsh coastal ecosystem dominant species on the United States Atlantic Coast, and <em>Salicornia pacifica</em>, the Pacific Coast dominant. We measured biomass production and photosynthesis as indicators of plant health, and we also measured soil and porewater characteristics to help interpret patterns of productivity. These measures included above and belowground biomass, porewater pH, salinity, ammonium concentration, sulfide concentration, soil redox potential, net ecosystem exchange, photosynthesis rate, respiration rate, and methane flux. We found the greatest plant production in soils with intermediate drainage levels, with production values that were 13.7% higher for <em>S. alterniflora</em> and 57.7% higher for <em>S. pacifica</em> in the intermediate flooding levels than found in more inundated and more drained conditions. Understanding how drainage impacts plant species is important for predicting wetland resilience to sea level rise, as increasing water levels alter ecohydrological zonation.</p>
SIRIUS - Synthesized Inventory of CRitical Infrastructure and HUman-Impacted Areas in Permafrost Regions of AlaSka
<p>The SIRIUS inventory integrates data from (i) the Sentinel-1/2 derived Arctic coastal human impact dataset (SACHI) (Bartsch et al., 2021), (ii) OpenStreetMap dataset for the infrastructure and land use information (OpenStreetMap Contributors and Geofabrik GmbH, 2018), (iii) the pan-Arctic catchments summary database (ARCADE) for the watersheds (Speetjens et al., 2022), (iv) the modeled Northern Hemisphere permafrost map by Obu et al. (2018), and (v) the contaminated sites database and reports by the State of Alaska Department of Environmental Conservation (2023) (DEC) to create a unified new dataset of critical infrastructure and human-impacted areas as well as permafrost and watershed information for Alaska.</p> <p>The dataset is deployed as a GeoPackage and can be imported to spatial databases (e.g. PostgreSQL/PostGIS), a Geographic Information System (e.g. QGIS), and used within geospatial processing libraries (e.g. Python's GeoPandas). All layers can be queried either in dependence or combination with one another.</p> <p>Each GeoPackage contains the following layers:</p> <ul> <li>ARCADE_WatershedsDB</li> <li>DEC_ContaminatedSitesAK</li> <li>OSM_Point_InfrastructureHIElements</li> <li>SACHI_OSM_InfrastructureHIElements</li> <li>SACHI_OSM_InfrastructureHIElements_RRNetwork</li> <li>UiO_MAGT</li> <li>UiO_PermafrostProbability</li> <li>UiO_PermafrostZones</li> </ul> <p>A corresponding manuscript, including application examples and a thorough description of the individual components, was submitted to be published in an open-access journal.</p> <p><strong>Download Data</strong></p> <ul> <li><strong>Python Scripts</strong> <ul> <li>01_InfrastructureDataETL: reprojects the input Shapefiles and raster datasets to a common coordinate system (EPSG:5936) and then clips datasets to the boundary of Alaska. It also includes a step for filtering the permafrost probability raster dataset based on a minimum probability threshold of 50% and rounds the values in the mean annual ground temperature raster dataset.</li> <li>02_OSM-aggregation: processes the OpenStreetMap (OSM) geospatial data. It imports and merges OSM polygon and point data, cleans and extracts unique values of "fclass" and "osm_type", and aggregates these values for manual categorization, based on the OSM key-value-scheme. The script assigns Land Use/Cover Area frame Statistical Survey (LUCAS) categories to the data, filters out natural objects and places, and resolves unknown categories by identifying intersections between datasets.</li> <li>03_SACHI-aggregation: assigns LUCAS categories to the SACHI dataset based on the 'Use' column.</li> <li>04_SACHI-OSM_decisiontree: performs a series of geospatial operations to determine the overlap between polygonal OSM features and SACHI features and assigns LUCAS categories to the overlapping features based on certain criteria and dissolves them. The overlapping and non-overlapping features are then combined into a single dataset: the harmonized critical infrastructure and human-impacted areas dataset.</li> <li>05_TextMiningNLTK-CSSites: performs text mining and data preprocessing on the reports of the DEC contaminated sites database. It extracts dates, calculates cleanup times for inactive sites, identifies contaminants based on abbreviations and text entries, and extracts information related to contaminants and the medium they are found in.</li> </ul> </li> <li><strong>GeoPackages</strong> <ul> <li>PermaRisk_RRNetworkLine_v01_r00.gpkg contains the rail and road network as line geometries.</li> <li>PermaRisk_RRNetworkPolygonal_v01_r00.gpkg contains the rail and road network as polygon geometries.</li> </ul> </li> </ul> <p> </p> <ul> </ul> <p> </p>
A dynamic von Mises-based model to evaluate the impact of urbanization and climate change on flood timing in Yangtze and Huaihe River Basins, China
<p>The daily streamflow data extracted from 8 selected stations from the Huaihe and Yangtze River Basins, China.</p>
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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.