Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
172
datasets available to search
ShareScore release 0.9.0
Dataset results
172 results for “global scale”
Data from: Net plant interactions are highly variable and weakly dependent on climate at the global scale
<p>Data were collected from the literature. The dataset is a compilation of published studies.</p> <p>An ISI Web of Science search covering the time period from 1900 onwards was conducted to identify the publications on plant interactions. Each publication was individually reviewed, and the reference list was inspected to identify additional relevant publications. We collected a total 1,220 publications for data compilation. We built a global dataset of 10,502 pairs of plant interaction data.</p>
Afterslip Model Database RC2022 (Afterslip Moment Scaling and Variability from a Global Compilation of Estimates)
<p>Churchill2022AfterslipDatabase.xlsx is a detailed database of aseismic afterslip models and corresponding mainshock information compiled by Robert Churchill (under the supervision of Maximilian Werner, Juliet Biggs and Åke Fagereng). The database contains afterslip models of mainshocks since 1979, with a publication cut-off at the end of 2018. The database is near complete, but not exhaustive. Descriptions of each column can be found as comments in the header field, as well as in the accompanying paper. Not all fields are not complete, some are also approximate or inferred values.</p> <p>This accompanies the paper:</p> <p>Churchill, R.M., Werner, M.J., Biggs, J. and Fagereng, Å., 2022. Afterslip Moment Scaling and Variability from a Global Compilation of Estimates. <em>Journal of Geophysical Research: Solid Earth</em>, p.e2021JB023897. <a href="https://doi.org/10.1029/2021JB023897">https://doi.org/10.1029/2021JB023897</a>.</p> <p>We hope the database serves as a useful resource to the afterslip community. Please reference our associated paper when using this database, as well as the database itself. References for individual afterslip papers can be found on the second sheet of the database, and references for additional data used in our study can be found in the third sheet. In the future, the database may be updated to include additional (missed) studies, however, this first version accompanies our study.</p> <p>*Headers for columns U and V are mislabelled Afterslip Upper Depth Limit (km) and Afterslip Lower Depth Limit (km), when these should be Coseismic Slip Upper Depth Limit (km) and Coseismic Slip Lower Depth Limit (km). The data in these columns is otherwise correct.</p> <p> </p>
Data from: Repeatability of adaptive radiation depends on spatial scale: regional versus global replicates of stickleback in lake versus stream habitats
The repeatability of adaptive radiation is expected to be scale dependent, with determinism decreasing as greater spatial separation among "replicates" leads to their increased genetic and ecological independence. Threespine stickleback (Gasterosteus aculeatus) provide an opportunity to test whether this expectation holds for the early stages of adaptive radiation -their diversification in freshwater ecosystems has been replicated many times. To better understand the repeatability of that adaptive radiation, we examined the influence of geographic scale on levels of parallel evolution by quantifying phenotypic and genetic divergence between lake and stream stickleback pairs sampled at regional (Vancouver Island) and global (North America and Europe) scales. We measured phenotypes known to show lake-stream divergence and used reduced representation genome-wide sequencing to estimate genetic divergence. We assessed the scale-dependence of parallel evolution by comparing effect sizes from multivariate models and also the direction and magnitude of lake-stream divergence vectors. At the phenotypic level, parallelism was greater at the regional than the global scale. At the genetic level, putative selected loci showed greater lake-stream parallelism at the regional than the global scale. Generally, the level of parallel evolution was low at both scales, except for some key univariate traits. Divergence vectors were often orthogonal, highlighting possible ecological and genetic constraints on parallel evolution at both scales. Overall, our results confirm that the repeatability of adaptive radiation decreases at increasing spatial scales. We suggest that greater environmental heterogeneity at larger scales imposes different selection regimes, thus generating lower repeatability of adaptive radiation at larger spatial scales.
Three-dimensional mapping of carbon, nitrogen, and phosphorus in soil microbial biomass and their stoichiometry at the global scale
<p>R code, raw datasets, and predicted global maps of soil microbial biomass C, N, and P and their stoichiometric ratios at 0-30 cm depth.</p> <p>When using any of these layers, please cite: Gao et al., Three-dimensional mapping of carbon, nitrogen, and phosphorus in soil microbial biomass and their stoichiometry at the global scale (2022). Global Change Biology. DOI: 10.1111/gcb.16374</p>
The June 2012 North American Derecho: A testbed for evaluating regional and global climate modeling systems at cloud-resolving scales
<p>This is the companion data for the manuscript titled 'The June 2012 North American Derecho: A testbed for evaluating regional and global climate modeling systems at cloud-resolving scales', submitted to the Journal of Advances in Modeling Earth Systems in September 2022.</p> <p>derecho_simulation_result: this folder contains part of the SCREAM RRM outputs I ran on NERSC Cori in 2021-2022 corresponding to the simulation in Table 1 of the manuscript.</p> <p>wrf_simulation_result: this folder contains part of the WRF outputs run by Jianfeng Li from PNNL (jianfeng.li@pnnl.gov) in 2022 corresponding to the simulations in Table 4 of the manuscript.</p> <p>plot_script: this folder includes python scripts to plot figures shown in the manuscript.</p> <p>ASOS_station: this txt file contains the processed ASOS station wind speed used in the manuscript.</p> <p><br> Unfortunately, all model outputs are large (~ 3.8 TB for SCREAM RRM and 3.1 TB for WRF). Therefore, I only provide the variables (i.e., OLR, precipitation, composite radar reflectivity, and 10-m wind speed) used directly to generate figures in this repository. All model outputs are archived on tape at NERSC.</p> <p>For more details, refer to the manuscript, or contact me (wrliu@ucdavis.edu).</p>
Supporting material for von Fromm et al (2024) Moisture and soil depth govern relationships between soil organic carbon and oxalate-extractable metals at the global scale
<p>This file contains the supporting material for von Fromm et al (2024) Moisture and soil depth govern relationships between soil organic carbon and oxalate-extractable metals at the global scale (<em>submitted</em>). </p> <p>For more details see the corresponding manuscript (once it is published) and the github repository (https://github.com/SophievF/Global_Mox_analysis/tree/main). </p>
Processed Data for Short Gianotti et al., "Two Sub-Annual Time-Scales and Coupling Modes for Terrestrial Water and Carbon Cycles" (2024), Global Change Biology.
<p>These files include all data used to create Figures in Short Gianotti et al., "Two Sub-Annual Time-Scales and Coupling Modes for Terrestrial Water and Carbon Cycles" (2024), Global Change Biology. Raw data provenances and methodological processing are cited in the published manuscript.</p> <p>See README file for metadata information.</p>
A global-scale geodatabase of mine areas
<p>Globally, the mine area include open cut pits, milling infrastructure, waste rock dumps, and tailings storage facilities of global. Totaled 24605 polygons were studied.</p> <p> </p>
Mapping soil microbial residence time at the global scale
<p>Soil microbes ultimately drive the mineralization of soil organic carbon and thus ecosystem functions. We compiled a dataset of the seasonality of microbial biomass carbon (MBC) and developed a semi-mechanistic model to map monthly MBC across the globe. MBC exhibits an equatorially symmetric seasonality between the Northern and Southern Hemispheres. In the Northern Hemisphere, MBC peaks in autumn and is minimal in spring at low latitudes (<25° N), peaks in the spring and is minimal in autumn at mid-latitudes (25°-50° N), while peaks in autumn and is minimal in spring at high latitudes (>50° N). This latitudinal shift of MBC seasonality is attributed to an interaction of soil temperature, soil moisture, and substrate availability. The MBC seasonality is inconsistent with patterns of heterotrophic respiration, indicating that MBC as a proxy for microbial activity is inappropriate at this resolution. This study highlights the need to explicitly represent microbial physiology in microbial models. The interactive controls of environments and substrate on microbial seasonality provide insights for better representing microbial mechanisms in simulating ecosystem functions at the seasonal scale.</p>
Global-scale modeling of early factors and country-specific trajectories of COVID-19 incidence: a cross-sectional study of the first 6 months of the pandemic
<p><span>Studies examining factors responsible for COVID-19 incidence </span><span>are</span><span> mostly focused at the national or sub-national level. A global-level characterization of contributing factors and temporal trajectories of disease incidence is lacking. Here we conducted a global-scale analysis of COVID-19 infections to identify key factors associated with early disease incidence. Additionally, we compared longitudinal trends of COVID-19 incidence at a per-country level and classified countries based on COVID-19 incidence trajectories and effects of lockdown responses. </span><span>Univariate analysis identified</span> <span>eleven variables as independently associated with COVID-19 infections at a global level (p<1e-05). Multivariable analysis identified a 4-variable model as optimal for explaining global variations in COVID-19 (p<0.01). COVID-19 case trajectories for most countries were best captured by a log-logistic model, as determined by AIC estimates. Six predominant country clusters were identified when characterizing the effects of lockdown intervals on variations in COVID-19 new cases per country.</span> <span>Globally, economic and meteorological factors are important determinants of early COVID-19 incidence. Analysis of longitudinal trends and lockdown effects on COVID-19 highlights important nuances in country-specific responses to infections. These results </span><span>provide valuable insights into disease incidence at a per-country level, possibly allowing for more informed decision making by individual governments in future disease outbreaks.</span></p>
Dataset for: Indirect nitrous oxide emission factors of fluvial networks can be predicted by dissolved organic carbon and nitrate from local to global scales
<p>Streams and rivers are important sources of nitrous oxide (N<sub>2</sub>O), a powerful greenhouse gas. Estimating global riverine N<sub>2</sub>O emissions is critical for the assessment of anthropogenic N<sub>2</sub>O emission inventories. The indirect N<sub>2</sub>O emission factor (EF<sub>5r</sub>) model, one of the bottom-up approaches, adopts a fixed EF<sub>5r</sub> value to estimate riverine N<sub>2</sub>O emissions based on IPCC methodology. However, the estimates have considerable uncertainty due to the large spatiotemporal variations in EF<sub>5r</sub> values. Factors regulating EF<sub>5r</sub> are poorly understood at the global scale. Here, we combine 4-year in situ observations across rivers of different land use types in China, with a global meta-analysis over six continents, to explore the spatiotemporal variations and controls on EF<sub>5r</sub> values. Our results show that the EF<sub>5r</sub> values in China and other regions with high N loads are lower than those for regions with lower N loads. Although the global mean EF<sub>5r</sub> value is comparable to the IPCC default value, the global EF<sub>5r</sub> values are highly skewed with large variations, indicating that adopting region-specific EF<sub>5r</sub> values rather than revising the fixed default value is more appropriate for the estimation of regional and global riverine N<sub>2</sub>O emissions. The ratio of dissolved organic carbon to nitrate (DOC/NO<sub>3</sub><sup>-</sup>) and NO<sub>3</sub><sup>-</sup> concentration are identified as the dominant predictors of region-specific EF<sub>5r</sub> values at both regional and global scales because stoichiometry and nutrients strictly regulate denitrification and N<sub>2</sub>O production efficiency in rivers. A multiple linear regression model using DOC/NO<sub>3</sub><sup>-</sup> and NO<sub>3</sub><sup>-</sup> is proposed to predict region-specific EF<sub>5r</sub> values. The good fit of the model associated with easily obtained water quality variables allows its widespread application. This study fills a key knowledge gap in predicting region-specific EF<sub>5r</sub> values at the global scale and provides a pathway to estimate global riverine N<sub>2</sub>O emissions more accurately based on IPCC methodology.</p> <p>This dataset is a global integrated N<sub>2</sub>O dataset including data from 4-year (2017-2020) in situ measurements of six large rivers in China, 3-year (2018-2020) in situ measurements of urban river networks in Beijing of China, and 825 measurements from 70 published papers over six continents. The data includes dissolved N<sub>2</sub>O concentration, biogeochemical (DOC, NO<sub>3</sub><sup>-</sup>, NH<sub>4</sub><sup>+</sup>, temperature, and DO), climatological (climate zones), and geographic (region, location, and land cover) information.</p>
Interview Transcriptions related to PhD Thesis "Degrowth at a Global Scale? Geographies of Chile's Fruit Production and Export between Extractivism and Socio-Ecological Transformation"
<p>The material is composed of transcriptions of interviews conducted for the empirical work of this PhD Thesis.</p> <p>Not all conducted interviews are included (which can be seen from the accompanying table); those not included are not available mostly due to lack of consent of interviewees or because certain interviews were not registered and only hand-written notes were taken.</p>
'Projected Landscape-scale Repercussions of Global Action for Climate and Biodiversity Protection' - model outputs
<p>Archive of model outputs produced for the MAgPIE v4.3.5 paper 'Projected Landscape-scale Repercussions of Global Action for Climate and Biodiversity Protection'.</p> <p>The model code of the MAgPIE and SEALS models can be accessed via:</p> <p><strong>MAgPIE model code</strong>: <a href="https://doi.org/10.5281/zenodo.5394196">https://doi.org/10.5281/zenodo.5394196</a> and <a href="https://github.com/magpiemodel/magpie">https://github.com/magpiemodel/magpie</a></p> <p><strong>MAgPIE model documentation</strong>: <a href="https://rse.pik-potsdam.de/doc/magpie/4.3.5/">https://rse.pik-potsdam.de/doc/magpie/4.3.5/</a></p> <p><strong>SEALS model code</strong>: <a href="https://doi.org/10.5281/zenodo.7795957">https://doi.org/10.5281/zenodo.7795957</a></p> <p>Data descriptions:</p> <p><strong>glosem_input.zip </strong>contains the spatially-explicit RLSK and C-factor data for each of the modelled scenarios at 10 arcseconds and the R code to estimate C-factor values based on the MAgPIE-SEALS outputs.</p> <p><strong>glosem_output.zip</strong> contains the spatially-explicit soil loss estimates for all scenarioso and the R code used to process the input data. The data was used to create Fig. 7.</p> <p><strong>magpie_ouput.zip</strong> contains the MAgPIE model outputs of all scenarios. The data is shown in Figs. 2, 3, 4, & 5.</p> <p><strong>pollination_sufficiency.zip</strong> contains the spatially-explicit pollination sufficiency estimates for all modelled scenarios and the R code used to derive the pollination sufficiency scores. The data is displayed in Fig. 6.</p>
Disentangling the relative contributions of factors determining seed physical defence: a global-scale data synthesis
<p>Physical defence investment in seeds varies greatly among plant species and is affected by many potential factors. However, the relative importance of influential factors has not yet been systematically evaluated. Here, we compiled a global database of the seed coat ratio (SCR), a proxy of seed physical defence, for 1,357 species. Using partial R<sup>2</sup> calculation that can estimate the reduction in explained variance of a given factor after removing it from a full model containing all the other factors, we disentangled the relative contributions of seven factors commonly used to explain variation in the SCR. Seed desiccation response and phylogeny explained a large amount of SCR variation among species, with a partial R<sup>2</sup><sub>lik</sub> value of 13.31% and 10.62%, respectively. Seed dormancy, plant growth form, seed mass, climate region, and fruit type showed little power to explain SCR variation, although they are often cited in the literature as potential factors. Our results highlight the important roles of seed desiccation response and phylogeny in shaping interspecific variation in the SCR. These findings provide a detailed interpretation of both evolutionary and ecological patterns underlying the physical defence mechanisms and allocation strategies of plant seeds.</p>
Ensemble of optimised machine learning algorithms for predicting surface soil moisture content at global scale (v1.0)
<p>This study investigates the estimation of daily SSM using eight optimised ML algorithms and ten ensemble models (constructed via model bootstrap aggregating techniques and five-fold cross-validation). The algorithmic implementations were trained and tested using the international soil moisture network (ISMN) data collected from 1722 stations distributed across the World. </p>
Simulations for impacts of large-scale Saharan solar farms on the global terrestrial carbon cycle
<p>Four experiments were conducted to investigate the impact of a large scale Saharan solar farm on the global carbon cycle. Here a fully coupled Earth System model (ESM) EC-Earth was used to investigate the impact of a Saharan solar farm on the terrestrial carbon cycle, simulated with prescribed reduced surface albedo approximating the albedo effect of Photovoltaic (PV) solar panels over the Sahara desert. These experiments considered solar panel coverage at 5, 20 or 50% of a region of the Sahara Desert. The dataset contains selected output data from the simulations. Simulations were run for 200 years. The last 60 years were used for analysis after the model reached an equilibrium. </p> <p>The dataset contains Earth system model results from EC-Earth3 presented in the study by Power et al. (2023).</p>
Data from: Disentangling the relative contributions of factors determining seed physical defence: a global-scale data synthesis
Open the record for dataset details and reuse information.
Data from: Multiple global change factors alter the scaling of nitrogen to phosphorus in alpine plants
Open the record for dataset details and reuse information.
Global-scale modeling of early factors and country-specific trajectories of COVID-19 incidence: a cross-sectional study of the first 6 months of the pandemic
Open the record for dataset details and reuse information.
Temporal changes in taxon abundances are positively correlated but poorly predicted at the global scale
Open the record for dataset details and reuse information.
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.