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14,867 results for “Determinants”
Fig. 4 in Determining Spatial Parameters Of The Ecological Niche Of Parus Major (Passeriformes, Paridae) On The Base Of Remote Sensing Data
Fig. 4. Distribution of resources (light bars) and distribution of resources used by P. major (grey bars).
Fig. 5 in Determining Spatial Parameters Of The Ecological Niche Of Parus Major (Passeriformes, Paridae) On The Base Of Remote Sensing Data
Fig. 5. Distribution of pseudo absence cells: a — the distance to the presence cells is not less than 1000 meters; b — the distance to the presence cells is not less than 500 meters; c — the distance to the presence cells is not less than 250 meters; d — distance to the presence cells is not less than 100 meters.
Local chromatin context dictates the genetic determinants of the heterochromatin spreading reaction. Analysis Code, Numerical and Primary data.
<p>Uploaded under this Zenodo DOI is the following:</p> <p>1. the Analysis Code used for Flow Cytometry analysis in the paper, GO complex analysis (Figure 3) and Hit visualization (Figure 1, 2 S1, S4 Figs).</p> <p>2. The primary Flow Cytometry data from both the initial screen (ScreenFlowFCS) and validation experiments (ValidationFlowFCS) are included as .zip files.</p> <p>3. a .zip folder is uploaded that contains all the analysis code for the ChIP-Seq experiments. </p> <p>4. Excel worksheets that contain the numerical source data for all qPCR bar plots.</p>
Statistically Determined Global Fire Regimes (GFRs) Empirically Characterized Using Historical MODIS Hotspots
<p><strong>Statistically Determined Global Fire Regimes (GFRs) Empirically Characterized Using Historical MODIS Hotspots</strong></p> <p>Fire regimes are areas having similar fire characteristics, and show the spatial pattern, frequency and intensity of fires that prevail in that area over long periods of time. Fire regimes are created and maintained by multivariate interactions between climate, vegetation/fuels, and ignitions. Like ecoregions, fire regimes indicate the extent and overlap of particular vegetative/fuel communities and climatic conditions, and are important for understanding, monitoring, predicting and managing fire.</p> <p>More than 83M MODIS “hotspot” thermal detections from 2002-2019 were grouped into 10km cells, and 21 derived variables describing fire characteristics of fire intensity, return frequency, and seasonality within each cell were developed and subjected to unsupervised Multivariate Geographic Clustering to produce world maps of Global Fire Regimes (GFRs), each having similar fire intensity and timing characteristics.</p> <p>Methodology behind these datasets are described in manuscript currently in review.</p> <p><strong>W. W. Hargrove, Jitendra Kumar, Steven P. Norman, Forrest M. Hoffman (2022), "Empirical Characterization of Global Fire Regimes Show Shared Fire Relationships" 2022 (in review)</strong></p> <p>This data collection includes:</p> <p>1. Multivariate Geographic Clustering Global Fire Regimes at 3000, 1000, 500, 100, 50, 20, 10 levels of divisions in form of geospatial raster in IMG formats, and associated color tables.</p> <p>2. Characteristics of GFRs</p> <p>3. Location groups</p> <p>4. Geospatial maps of global fire frequency modes, global seasonality strength, and 12 types of global fires.</p> <p>5. PNG maps for all data products </p> <p>6. Description and script for global date transform algorithm.</p>
Dataset for "Experimental determination of the relationship between organic aerosol viscosity and ice nucleation at upper free tropospheric conditions"
<p><strong>Data and scripts used to create the figures in the manuscript titled: "Experimental determination of the relationship between organic aerosol viscosity and ice nucleation at upper free tropospheric conditions"</strong></p>
SDUST2020 MSS: A global 1′×1′ mean sea surface model determined from multi-satellite altimetry data
<p>SDUST2020 MSS (Shandong University of Science and Technology 2020 mean sea surface) model with a grid of 1′×1′ is established with 19-year moving average method from multi-satellite altimetry data over 27-year (from January 1993 to December 2019). Its spatial coverage is 80°S-84°N. The missions data of Topex/Poseidon, Jason-1, Jason-2, Jason-3, ERS-1, ERS-2, GFO, Envisat, SARAL, HY-2A, Sentinel-3A and Cryosat-2 are ingested in the SDUST2020 MSS model.</p>
Community diversity determines the evolution of synthetic bacterial communities under artificial selection
<p>These data and script are related to the article entitled "Community diversity determines the evolution of synthetic bacterial communities under artificial selection". This study reports the results of an experiment that involved bacterial communities differing for their richness level (1, 2, 4, 8, 16 species) and subjected to artificial selection or not. The property under selection was the optical density (OD). All the data needed to reproduce the figures and tables presented in the manuscript are provided.</p>
Data from: Chromosome-scale assembly with a phased sex-determining region resolves features of early Z and W chromosome differentiation in a wild octoploid strawberry
<p>Abstract: When sex chromosomes stop recombining, they start to accumulate differences. The sex-limited chromosome (Y or W) especially is expected to degenerate via the loss of nucleotide sequence and the accumulation of repetitive sequences. However, how early signs of degeneration can be detected in a new sex chromosome is still unclear. The sex determining region (SDR) of the octoploid strawberries is young, small, and dynamic. Using PacBio HiFi reads, we obtained a chromosome scale assembly of a female (ZW) <em>Fragaria chiloensis</em> plant carrying the youngest and largest of the known SDR on the W in strawberries. We fully characterized the previously incomplete SDR, confirming its gene content, genomic location and evolutionary history. Resolution of gaps in the previous characterization of the SDR added 10 kbp of sequence including a non-canonical LTR-retrotransposon; whereas the Z sequence revealed a <em>Harbinger</em> transposable element adjoining the SDR insertion site. Limited genetic differentiation of the sex chromosomes coupled with structural variation may indicate an early stage of W degeneration. The sex chromosomes have a similar percentage of repeats but differ in their repeat distribution. Differences in the pattern of repeats (transposable element polymorphism) apparently precede sex chromosome differentiation, thus potentially contributing to recombination cessation as opposed to being a consequence of it.</p> <p>Repository content: data (sequence alignments, phylogenetic trees, genome assembly, and vcf files) and scripts associated with the manuscript "Chromosome-scale assembly with a phased sex-determining region resolves features of early Z and W chromosome differentiation in a wild octoploid strawberry"</p>
Analysis Data, "Drivers and Determinants of Strain Dynamics Following Fecal Microbiota Transplantation"
<p>This package contains datasets in `Rdata` format that underlie the analyses presented in the study, "Drivers and Determinants of Strain Dynamics Following Fecal Microbiota Transplantation" by Schmidt, Li et al.<br> </p> <p>Corresponding code, referring to these datasets, is available via `github`:</p> <p>https://github.com/grp-bork/fmt_metastudy</p> <p> </p> <p>The study is available as a preprint:</p> <p>https://www.biorxiv.org/content/10.1101/2021.09.30.462010v1</p> <p> </p> <p>The present package contains processed/derived data. Metagenome-Assembled Genomes generated for the same study are available via `Zenodo` under:</p> <p>https://zenodo.org/record/5534163#.YpoRFy8RrzA<br> doi: 10.5281/zenodo.5534163</p>
Nitrogen availability determines ecosystem productivity in response to climate warming
<p><span>One of the major uncertainties for carbon-climate feedback predictions is an inadequate understanding of the mechanisms governing variations in ecosystem productivity response to warming. Temperature and water availability are regarded as the primary controls over the direction and magnitude of warming effects, but some unexplained results signal that our understanding is incomplete. Using two complementary meta-analyses, we present evidence that soil nitrogen (N) availability drives the warming effects on ecosystem productivity more strongly than thermal and hydrological factors over a broad geographical scale. First, by synthesizing temperature manipulation experiments, meta-regression model analysis showed that the warming effect on productivity is mainly driven by its effect on soil N availability. Sites with higher warming-induced increase in N availability were characterized by stronger productivity enhancement and vice versa, suggesting that N is a limiting factor across sites. Second, a synthesis of full-factorial warming×N addition experiments demonstrated that N addition significantly weakened the positive warming effect, because the additional N induced by warming may not further benefit plant growth when N limitation is relieved, providing experimental evidence that N regulates the warming effect. Further, we demonstrated that warming effects on soil N availability were modulated by changes in dissolved organic N and soil microbes. Overall, our findings enrich a new mechanistic understanding of the varying magnitudes of observed productivity response to warming, and the N scaling of warming effects may help constrain climate projections.</span></p>
Dataset to "Bulk thermodynamics determines surface hydrogen concentrations in membranes"
<p>Dataset to "Bulk thermodynamics determines surface hydrogen concentrations in membranes" as published in Advanced Materials Interfaces</p>
Predation and parasitism as determinants of animal personalities
<p>1. Within the same population, proactive (i.e. bolder, more exploratory, active and aggressive) and reactive (i.e. more timid, less exploratory, less active and more passive) individuals could be hypothetically maintained due a trade-off between foraging and anti-predator behaviour, provided that both phenotypes differ in their state (e.g. metabolic rates, body condition or energetic needs).</p> <p>2. Yet, recent findings indicate that among-individual variation in intrinsic state can explain only a small proportion of variation in behaviour, meaning that other mechanisms, such as the presence of trophically transmitted parasites, might contribute to maintaining inter-individual behavioural differences. Empirical evidence, indeed, suggests strong relationships between certain animal personality traits and parasitic load within host populations. However, the direction of causation between these traits remains unclear: are different behaviours in infected hosts in contrast to uninfected ones the result of manipulation by parasites to increase host predation, or are some personalities inherently more susceptible to infection than others?</p> <p>3. To better understand the role of parasites in shaping behavioural differences within host populations and examine to what extent parasite manipulation and/or intrinsic differences in parasite susceptibility contribute to maintaining behavioural differences, we used a simulation approach and analyzed the change in the frequencies of proactive and reactive individuals over time under different predation and starvation scenarios, when individual phenotype either affected a host's risk of infection or not.</p> <p>4. We found that in the absence of parasites, predation pressure strongly affected the expression of host personality, but trade-offs between foraging and anti-predator behaviour alone could not explain the maintenance of inter-individual behavioural differences without temporal variation in predation pressure. By contrast, in the presence of parasites, the two host phenotypes could coexist within populations even when individuals experienced no temporal variations in predation risk, but only when proactive and reactive hosts were equally susceptible to parasitism.</p> <p>5. Our findings thus indicate that parasites can play an important role in maintaining genetic diversity in their host populations in addition to generating behavioural differences though manipulation.</p>
Data, scripts, and figures of the article: Processing weights of chickens determined by Dual-Energy X-Ray Absorptiometry. 3. Validation of prediction models
<p>This data set contains the data, JMP scripts, and figures of the article titled "Processing weights of chickens determined by Dual-Energy X-Ray Absorptiometry. 3. Validation of prediction models" to be published in the journal Animal - Open Space.</p>
Dataset for a Feasibility Study for Accelerated Reference Point Determination Using Close Range Photogrammetry
<p>The Global Geodetic Observing System (GGOS) aims for an accuracy of 1 mm in position concerning a global geodetic reference frame such as the International Terrestrial Reference Frame (ITRF). To derive a global frame, several space geodetic techniques are combined. The combination procedure requires the geometric relations between the invariant reference points of these techniques, the so-called local tie vectors. Each space geodetic technique defines its reference point individually, so the determination of the position of the reference point varies significantly between techniques. Within the international GeoMetre project, measurement systems and analysis strategies are developed to improve the quality of local tie vectors and, thus, the quality of the resulting global frame.</p> <p>The use of close range photogrammetry to determine the reference point of a telescope used for Satellite Laser Ranging (SLR) at the GGOS core station Wettzell in September 2020 is considered as a milestone in this project. This contribution deals with a novel approach for an accelerated reference point determination using close range photogrammetry. In comparison to the conventional photogrammetric approach, published so far, this new approach leads to a significant reduction in recording time. However, in case of inappropriate measurement configuration the approach also bears the risk of biased results. Most importantly, the new approach has the potential to be automated, which is one of the primary calls of GGOS for reference point determinations.</p>
Data from: Historic deforestation and non-native plant invasions determine vegetation trajectories across an oceanic archipelago
<p>This archive contains data produced in a study of the vegetation trajectories of Ogasawara Islands in 77 years related to following article:</p> <p>Ohashi, H., Kato, H., Murao, M., Kato, H., Kawakami, K., Kurokawa, H., Oguro, M., Kimura, F., Niiyama, K., Matsui, T., and Shibata, M. (2024) Historic deforestation and non-native plant invasions determine vegetation trajectories across an oceanic archipelago. <em>Applied Vegetation Science</em>, 27 (1), e12767. <a href="https://doi.org/10.1111/avsc.12767">https://doi.org/10.1111/avsc.12767</a></p> <p> </p> <p><strong>Archive contents</strong><br>The archive contents are organized into five parts, each stored as a .zip compressed file.</p> <p><strong>X1_tif_original_vegmap_scan_georeference</strong></p> <p>Scanned and georeferenced original vegetation maps in GeoTiff format, which was drawn in 1935, scanned at 300 dpi. Coordinate reference system was set at WGS84 (ESPG: 4326).</p> <p>This directory includes:</p> <p><em>kitanoshima_isl_WGS84.tif<br>mukojima_isl_WGS84.tif<br>yomejima_isl_WGS84.tif<br>ototojima_isl_WGS84.tif<br>anijima_isl_WGS84.tif<br>nishijima_isl_WGS84.tif<br>chichijima_isl_WGS84.tif<br>hahajima_isl_WGS84.tif<br>mukohjima_isl_WGS84.tif<br>kitaiwoto_isl_WGS84.tif<br>iwoto_isl_WGS84.tif</em></p> <p> </p> <p><strong>X2_shp_vegmap</strong></p> <p>Shapefile of the geospatial polygon data of vegetation map of Ogasawara Islands surveyed in 1935, and stored as a .zip compressed file. Coordinate reference system was set at WGS84 (ESPG: 4326).</p> <p>This directory includes:</p> <p><em>VegetationMap_OgasaawraIsl_1935_en_UTF8_v0.dbf<br>VegetationMap_OgasaawraIsl_1935_en_UTF8_v0.prj<br>VegetationMap_OgasaawraIsl_1935_en_UTF8_v0.shp<br>VegetationMap_OgasaawraIsl_1935_en_UTF8_v0.shx<br>attribute_ForSect_code_en.csv<br>attribute_Veg_name_en.csv<br>metadata_vegmap_shp_ogasawara1935_en.csv</em></p> <p>Following files includes Japanese character (which may corrupt in non-Japanese environment):</p> <p><em>attribute_ForSect_jp.csv<br>attribute_Veg_name_jp.csv<br>metadata_vegmap_shp_ogasawara1935_jp.csv</em></p> <p> </p> <p><strong>X3_tif_vegmap_converted_from_shp</strong></p> <p>Rasterized data of polygon data of vegetation map for analysis. Coordinate reference system was set at JGD2000 / Japan Plane Rectangular CS XIV (EPSG: 2456)</p> <p>This directory includes:</p> <p><em>vegmap_1935.zip (compressed “vegmap_1935.tif (0.7GB)”)<br>vegnap_1979.zip (compressed “vegmap_1979.tif (1.5GB)”)<br>vegmap_2011.zip (compressed “vegmap_2011.tif (1.5GB)”)<br>islcode_raster.zip (compressed “vegmap_2011.tif (1.5GB)”)<br>attribute_integratedveg_ecoltype.csv<br>attribute_vegid_1935.csv<br>attribute_vegid_1979.csv<br>attribute_vegid_2011.csv</em></p> <p> </p> <p><strong>X4_scanned_image_vegdata</strong></p> <p>Scanned images of original vegetation data in 1935.</p> <p>The directory includes:<br><em>vegetation_survey_sheet_1.pdf<br>vegetation_survey_sheet_2.pdf</em><br><em>vegetation_survey_sheet_3.pdf</em></p> <p> </p> <p><strong>X5_digitized_vegdata</strong></p> <p>Digitized vegetation data.</p> <p>The directory includes:<br><em>plot_species_abundance_matrix_v0.csv<br>plotinfo_v0.csv<br>attribute_Species_en_v0.csv</em></p> <p>Following file includes Japanese character (which may corrupt in non-Japanese environment)<br><em>attribute_Species_jp_v0.csv</em><br> </p> <p><strong>X6_code_for_analysis</strong></p> <p>Tentative.</p> <p> </p> <p>このアーカイブには、小笠原諸島の77年間の植生の変遷(1935年、1979年、2012年)に関するデータが含まれています。</p> <p> </p>
Research data in support of: An Interplay of Mechanical and Structural Properties of DNA Determines Its Electrostatic Interactions with Lipids
<p>The data collected and reported for the publication entitled: An Interplay of Mechanical and Structural Properties of DNA Determines Its Electrostatic Interactions with Lipids. by Diana Morzy et al.</p> <p>Data is divided by the technique used, with folders named accordingly. Each dataset has a readme file, explaining the basic technical details, as well as how to open each file type.</p> <p>Please do not hesitate to contact the corresponding author (MMCB) for further details.</p>
METHICILLIN-RESISTANT STAPHYLOCOCCUS AUREUS AND ITS DETERMINANTS OF RAW COW MILK CONTAMINATION IN SELECTED GAMO ZONE DISTRICT OF SOUTHERN ETHIOPIA
<p>We conducted this study, titled "Methicillin-Resistant Staphylococcus aurous and its Determinants of Raw Cow Milk Contamination in a Selected Gamo Zone District of Southern Ethiopia," in order to disseminate our findings to the scientific community. The research has its own strengths, such as the work we did on milk quality and potential milk borne pathogens, as well as the determinants of contamination at the selling point, which is only on fresh milk after it has been checked for freshness. As a result, the authors initiated this research based on practical challenges encountered while providing professional support to various producers in the milk selling point. Because of the irrational use of antibiotics among human and animal health in the study area, this research aimed to estimate the microbial load, prevalence of methicillin resistant <em>S. aurous</em> (MRSA), and determinants of raw cow milk contamination at selling points. This could be a source of drug resistance development in Ethiopia and in the study area in particular. Furthermore, due to resource constraints, the study focuses on bacteriological analysis, risk factor association, and drug sensitivity testing, which can serve as baseline data for future characterization and intervention. Hoping that we authors are interested to publish our research output in your journal with your eminent support for the article gets published.</p>
Supplementary material: Does functional redundancy determine the ecological severity of a mass extinction event?
<p>Many authors have noted the apparent "decoupling" of the taxonomic and ecological severity of mass extinction events, with no widely accepted mechanistic explanation for this pattern having been offered. Here we test between two key factors that potentially influence ecological severity: biosphere entropy (a measure of functional redundancy), and the degree of functional selectivity (in terms of deviation from a pattern of random extinction with respect to functional entities). While theoretical simulations suggest that the Shannon entropy of a given community prior to an extinction event determines the expected outcome following a perturbation of a given magnitude, actual variation in Shannon entropy between major extinction intervals is insufficient to explain the observed variation in ecological severity. Within this information-theoretic framework, we show that it is the degree of functional selectivity which is expected to primarily determine the ecological impact of a given perturbation when levels of functional redundancy are not substantially different.</p>
Shared biophysical mechanisms determine early biofilm architecture development across different bacterial species
<p>These data are the numerical values that underlie the Figures 1 - 4, and the Supplementary Figures 1 - 10 for the article "Shared biophysical mechanisms determine early biofilm architecture development across different bacterial species" by the same authors. The content of the data files is organized according to the figures and figure panels of this article. </p>
Hierarchical trait filtering at different spatial scales determines beetle assemblages in deadwood: Additional data
<p>Contains data used in the following publication:</p> <p>Felix Neff, Jonas Hagge, Rafael Achury, Didem Ambarlı, Christian Ammer, Peter Schall, Sebastian Seibold, Michael Staab, Wolfgang W. Weisser, Martin M. Gossner (2022). <em>Hierarchical trait filtering at different spatial scales determines beetle assemblages in deadwood. </em>Functional Ecology. <a href="https://doi.org/10.1111/1365-2435.14186">https://doi.org/10.1111/1365-2435.14186</a></p> <p>These are complementary data, which are needed to reproduce the analyses. Most data are archived in the Biodiversity Exploratories Information System (<a href="https://doi.org/10.17616/R32P9Q">https://doi.org/10.17616/R32P9Q</a>).</p> <p>The following data are included:</p> <ul> <li><strong>BELongDead_Subplots_Normal.csv</strong>: List of <em>normal</em> subplots within the BELongDead projects (only these were included in the analyses)</li> <li><strong>Body_length.csv</strong>: Body length data for study species assembled from Freude et al. (1965-1998)</li> <li><strong>Lightness_completion.csv</strong>: Colour lightness recorded from measured individuals and photos from coleonet.de (Lompe, 2002)</li> <li><strong>Name_standardisation.csv</strong>: Dataset used to standardise taxonomic names from different sources</li> <li><strong>Saproxylic_species_sub.csv</strong>: List of saproxylic species (according to Schmidl & Bussler (2004)), which were recorded in the project</li> <li><strong>Similar_Species.csv</strong>: List of similar species for species with missing traits. Based on these, missing traits were estimated</li> </ul> <p><strong>References</strong></p> <p>Freude, H., Harde, K. W., & Lohse, G. A. (1965–1998). <em>Die Käfer Mitteleuropas Band 1-15</em>. Goecke und Evers.</p> <p>Lompe, A. (2002). <em>Käfer Europas</em>. <a href="http://coleonet.de/">http://coleonet.de/</a></p> <p>Schmidl, J., & Bussler, H. (2004). Ökologische Gilden xylobionter Käfer Deutschlands. <em>Naturschutz und Landschaftsplanung</em>, <em>36</em>(7), 202–218.</p>
ScienceDex guides
Understand access before you commit
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.