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”
Kilometer-scale global warming simulations and active sensors reveal changes of tropical deep convection
<p>This zip file contains data and codes to reproduce the figures of a manuscript on X-SHiELD.</p> <p>Contact mbolot@princeton.edu for questions.</p>
Streamflow drought hazard indicators for monitoring drought hazard for human water supply and river ecosystems at the global scale (WaterGAP 2.2d, WFDEI-GPCC)
<p><strong>1) Streamflow drought hazard indicators (SDHIs) as computed by WaterGAP 2.2d (climate data WFDEI-GPCC) for the whole globe except Antarctica, spatial resolution: 0.5°, monthly data for the reference period 1986-2015:</strong></p> <p><strong>Indicators of drought magnitude: </strong>SSI1, SSI12, EP1, RDQI1</p> <p><strong>Indicators of drought severity: </strong></p> <p>CDQI1-Q50, CDQI1-Q50_f, CDQI1-Q80, CDQI1-Q80_f, CDQI1-Q80-HS, CDQI6-Q80, CDQI6-Q80_f,</p> <p>CDQI1-WUs, CDQI1-WUs-EFR, CDQI1-WUs-EFR_f,</p> <p>CEP1(20%), CEP1(20%)_f, CRDQI1(-50%), CRDQI1(-50%)_f</p> <p><strong>2) WaterGAP grid cell IDs ("arcid") with longitude and latitude:</strong></p> <p>(WaterGAP_ArcID_lon_lat.txt)</p> <p><strong>3) Streamflow observations at 220 GRDC gauging stations and list of the 220 GRDC station numbers with related WaterGAP grid cell ID ("arcid"):</strong></p> <p>Observed_monthly_streamflow_km3month_220_calstations_1986_2015.txt</p> <p>GRDC_number_WaterGAP_ArcID_220_stations.txt</p> <p><strong>4) SDHIs for four GRDC gauging stations:</strong></p> <p>time_series_danube_river.txt, time_series_angara_river.txt, time_series_white_river.txt, time_series_orange_river.txt</p> <p><strong>5) WaterGAP output: Mean monthly surface water abstractions in km3 per month: </strong>Mean_monthly_WUs_km3_per_month_WFDEI_GPCC_ant_22d_1986_2015.txt</p> <p> </p>
Potassium fertilization effects on cereal yield and soil organic carbon in agricultural ecosystems at the global scale
<p>This dataset includes the raw data of a global meta-analysis study on the responses of cereal yield and soil organic carbon to potassium fertilization in agricultural ecosystems.</p>
Data from: Predicting undetected native vascular plant diversity at a global scale
Open the record for dataset details and reuse information.
Rapid in situ diversification rates in Rhamnaceae explain the parallel evolution of high diversity in temperate biomes from global to local scales
Open the record for dataset details and reuse information.
Ecological and evolutionary drivers of stingless bee honey variation at the global scale
Open the record for dataset details and reuse information.
Data for: Historical and contemporary processes drive global phylogenetic structure across geographical scales: Insights from bat communities
Open the record for dataset details and reuse information.
Forest resilience to global warming is strongly modulated by local-scale topographic, microclimatic and biotic conditions
Open the record for dataset details and reuse information.
Drivers and projections of global surface temperature anomalies at the local scale
Open the record for dataset details and reuse information.
Microbial biomass and soil properties data, global scale,1970s-2010s
The data for Microbial Data System. We will collect data for soil and microbial characteristics in terrestrial ecosystems and update regularly. The date of publications used spans from the late 1970s to 2012. The data were aggregated into 11 major biome types. These data points were collected exclusively for surface soils, primarily 0–15 cm depth with some 0–30 cm. We obtained 3259 data points with geographical information.
Correlation of native and exotic species richness: a global meta-analysis finds no invasion paradox across scales
This data set is also available on the Dryad Digital repository (link : https://doi.org/10.5061/dryad.59kv753) This dataset was created for investigating the biotic resistance hypothesis, that is, the idea that species‐rich communities are more successful at resisting invasion by exotic species than are species‐poor communities. It has been argued that native–exotic richness relationships (NERR) are negative at small spatial scales and positive at large scales, but evidence for the role of spatial scale on NERR has been contradictory. However, no formal quantitative synthesis had previously examined whether NERR is scale‐dependent across multiple studies, and previous studies on NERR have not distinguished spatial grain and extent, which may drive very different ecological processes Therefore, a global systematic review was carried out to create this dataset, which includes 204 individual cases of observational (non‐experimental) NERRs from 101 publications. Further, the above-mentioned hypotheses were investigated using a hierarchical mixed‐effects meta‐analysis, which showed that NERR was indeed highly scale dependent across studies and increased with the log of grain size. Also, no clear patterns of NERR across different spatial extents were found, suggesting that extent plays a less important role in determining NERR than does grain, although there was a complex interaction between extent and grain size. Almost all studies on NERR were found to have been conducted in North America, western Europe, and a few other regions, with little information on tropical or Arctic regions. NERR was also found to increase northward in temperate regions and vary with longitude. These results were published in the paper titled Correlation of native and exotic species richness: a global meta‐analysis finds no invasion paradox across scales (Peng et al. 2018), which represents the first global quantitative analysis of scale‐based NERR.
Supplementary Files to "Towards a global understanding of vegetation-climate dynamics at multiple time scales"
<p><strong>TimeSeriesPaper_main_processing.html</strong></p> <p>Html version of Jupyter notebook exemplifying main data analysis steps in "Towards a global understanding of vegetation-climate dynamics at multiple time scales" (doi:10.5194/bg-17-945-2020). Please see the publication for further details. Notebook written in Julia v0.6</p> <p><strong>Fig2_Co_Oscillation_Regimes.nc</strong></p> <p>Data underlying Fig. 2 in "Towards a global understanding of vegetation-climate dynamics at multiple time scales" (doi:10.5194/bg-17-945-2020).</p> <p>Classification of land surface by dominant scale of variability in Normalized Difference Vegetation Index (NDVI), air temperature, and precipitation. Dominant scale of variability was determined after Fourier decomposition, separately for each grid cell and summarized as unique combinations between variables (S - short-term, A - seasonal, L - longer-term, T - trend, listed in order NDVI, air temperature, precipitation). The semi-annual cycle is included in the seasonal band. Please see the publication for further details.</p>
Shared geographic histories and dispersal contribute to congruent phylogenies between amphipods and their microsporidian parasites at regional and global scales
<p>In parasites that strongly rely on a host for dispersal, geographic barriers that act on the host will simultaneously influence parasite distribution as well. If their association persists over macroevolutionary time it may result in congruent phylogenetic and phylogeographic patterns due to shared geographic histories. Here, we investigated the level of congruent evolutionary history at a regional and global scale in a highly specialised parasite taxon infecting hosts with limited dispersal abilities: the microsporidians <i>Dictyocoela</i> spp. and their amphipod hosts. <i>Dictyocoela</i> can be transmitted both vertically and horizontally and is the most common microsporidian genus occurring in amphipods in Eurasia. However, little is known about its distribution elsewhere. We started by conducting molecular screening to detect microsporidian parasites in endemic amphipod species in New Zealand; based on phylogenetic analyses, we identified nine species-level microsporidian taxa including six belonging to <i>Dictyocoela</i>. With a distance-based cophylogenetic analysis at the regional scale, we identified overall congruent phylogenies between <i>Paracalliope</i>, the most common New Zealand freshwater amphipod taxon, and their <i>Dictyocoela</i> parasites. Also, hosts and parasites showed similar phylogeographic patterns suggesting shared biogeographic histories. Similarly, at a global scale, phylogenies of amphipod hosts and their <i>Dictyocoela</i> parasites showed broadly congruent phylogenies. The observed patterns may have resulted from covicariance and/or codispersal, suggesting that the intimate association between amphipods and <i>Dictyocoela</i> may have persisted over macroevolutionary time. We highlight that shared biogeographic histories could play a role in the codiversification of hosts and parasites at a macroevolutionary scale.</p>
Mammal population densities at a global scale are higher in human-modified areas
Global landscapes are changing due to human activities with consequences for both biodiversity and ecosystems. For single species, terrestrial mammal population densities have shown mixed responses to human pressure, with both increasing and decreasing densities reported in the literature. How the impacts of human activities on mammal populations translates into altered global density patterns remains unclear. Here we aim to disentangle the effect of human impacts on large-scale patterns of mammal population densities using a global dataset of 6729 population density estimates for 468 mammal species (representing 59% and 44% of mammalian orders and families). We fitted a mixed effect model to explain the variation in density based on a 1-degree resolution as a function of the Human Footprint Index (HFI), a global proxy of direct and indirect human disturbances, while accounting for body mass, trophic level and primary productivity (Normalized Vegetation Index; NDVI). We found a significant positive relationship between population density and HFI, where population densities were higher in areas with a higher HFI (e.g., agricultural or suburban areas – no populations were located in very high HFI urban areas) compared to areas with a low HFI (e.g., wilderness areas). We also tested the effect of the individual components of the HFI and still found a consistent positive effect. The relationships remained positive even across populations of the same species, although variability among species was high. Our results indicate shifts in mammal population densities in human modified landscapes, which is due to the combined effect of species filtering, increased resources, and a possible reduction in competition and predation. Our study provides further evidence that macroecological patterns are being altered by human activities, where some species will benefit from these activities, while others will be negatively impacted or even extirpated.
Data from: Form–function relationships in a marine foundation species depend on scale: a shoot to global perspective from a distributed ecological experiment
Form-function relationships in plants underlie their ecosystem roles in supporting higher trophic levels through primary production, detrital pathways, and habitat provision. For widespread, phenotypically-variable plants, productivity may differ not only across abiotic conditions, but also from distinct morphological or demographic traits. A single foundation species, eelgrass (Zostera marina), typically dominates north temperate seagrass meadows, which we studied across 14 sites spanning 32-61° N latitude and two ocean basins. Body size varied by nearly two orders of magnitude through this range, and was largest at mid-latitudes and in the Pacific Ocean. At the global scale, neither latitude, site-level environmental conditions, nor body size helped predict productivity (relative growth rate 1-2% d-1 at most sites), suggesting a remarkable capacity of Z. marina to achieve similar productivity in summer. Furthermore, among a suite of stressors applied within sites, only ambient leaf damage reduced productivity; grazer reduction and nutrient addition had no effect on eelgrass size or growth. Scale-dependence was evident in different allometric relationships within and across sites for productivity and for modules (leaf count) relative to size. Z. marina provides a range of ecosystem functions related to both body size (habitat provision, water flow) and growth rates (food, carbon dynamics). Our observed decoupling of body size and maximum production suggests that geographic variation in these ecosystem functions may be independent, with a future need to resolve how local adaptation or plasticity of body size might actually enable more consistent peak productivity across disparate environmental conditions.
Predicted lake dissolved organic carbon at a global scale
<p>The pool of dissolved organic carbon (DOC), is one of the main regulators of the ecology and biogeochemistry of inland water ecosystems, and an important loss term in the carbon budgets of land ecosystems. We used a novel machine learning technique and global databases to test if and how different environmental factors contribute to the variability of <em>in situ</em> DOC concentrations in lakes. In order to estimate DOC in lakes globally we predicted DOC in each lake with a surface area larger than 0.1 km<sup>2</sup>. Catchment properties and meteorological and hydrological features explained most of the variability of the lake DOC concentration, whereas lake morphometry played only a marginal role. The predicted average of the global DOC concentration in lake water was 3.88 mg L<sup>-1</sup>. The global predicted pool of DOC in lake water was 729 Tg from which 421 Tg was the share of the Caspian Sea. The results provide global-scale evidence for ecological, climate and carbon cycle models of lake ecosystems and related future prognoses.</p>
Quantifying the Impact of Vertical Resolution on the Representation of Marine Boundary Layer Physics for Global-Scale Models
<p>Data supporting the findings of DOI: 10.1175/MWR-D-23-0078.1, a 2023 Monthly Weather Review publication with the same title as this dataset.</p>
A global meta-analysis of yield-scaled N2O emissions and its mitigation efforts for maize, wheat, and rice
<p>Maintaining or even increasing crop yields while reducing nitrous oxide (N<sub>2</sub>O) emissions is necessary to reconcile food security and climate change, while the metric of yield-scaled N<sub>2</sub>O emission (i.e., N<sub>2</sub>O emissions per unit of crop yield) is at present poorly understood. Here we conducted a global meta-analysis with more than 6000 observations to explore the variation patterns and controlling factors of yield-scaled N<sub>2</sub>O emissions for maize, wheat, and rice and associated potential mitigation options. Our results showed that the average yield-scaled N<sub>2</sub>O emissions across all available data followed the order wheat (322 g N Mg<sup>-1</sup>, with the 95% confidence interval (CI): 301-346) > maize (211 g N Mg<sup>-1</sup>, CI: 198-225) > rice (153 g N Mg<sup>-1</sup>, CI: 144-163). Yield-scaled N<sub>2</sub>O emissions for individual crops were generally higher in tropical or subtropical zones than in temperate zones, and also showed a trend towards lower intensities from low to high latitudes. This global variation was better explained by climatic and edaphic factors than by N fertilizer management, while their combined effect predicted more than 70% of the variance. Furthermore, our analysis showed a significant decrease in yield-scaled N<sub>2</sub>O emissions with increasing N use efficiency or in N<sub>2</sub>O emissions for production systems with cereal yields > 10 Mg ha<sup>-1</sup> (maize), 6.6 Mg ha<sup>-1</sup> (wheat) or 6.8 Mg ha<sup>-1</sup> (rice), respectively. This highlights that N use efficiency indicators can be used as valuable proxies for reconciling trade-offs between crop production and N<sub>2</sub>O mitigation. For all three major staple crops, reducing N fertilization by up to 30%, optimizing the timing and placement of fertilizer application or using enhanced-efficiency N fertilizers significantly reduced yield-scaled N<sub>2</sub>O emissions at similar or even higher cereal yields. Our data-driven assessment provides some key guidance for developing effective and targeted mitigation and adaptation strategies for the sustainable intensification of cereal production.</p>
ChatEarthNet: A Global-Scale Image-Text Dataset Empowering Vision-Language Geo-Foundation Models
<p>We introduce a new image-text dataset, providing high-quality natural language descriptions for global-scale satellite data. Specifically, we utilize Sentinel-2 data for its global coverage as the foundational image source, employing semantic segmentation labels from the European Space Agency's WorldCover project to enrich the descriptions of land covers. By conducting in-depth semantic analysis, we formulate detailed prompts to elicit rich descriptions from ChatGPT. We then include a manual verification process to enhance the dataset's quality further. This step involves manual inspection and correction to refine the dataset. Finally, we offer the community ChatEarthNet, a large-scale image-text dataset characterized by global coverage, high quality, wide-ranging diversity, and detailed descriptions. ChatEarthNet consists of 163,488 image-text pairs with captions generated by ChatGPT-3.5 and an additional 10,000 image-text pairs with captions generated by ChatGPT-4V(ision). This dataset has significant potential for both training and evaluating vision-language geo-foundation models for remote sensing.</p>
Data used in JAMES paper "Sensitivity of the Horizontal Scale of Convective Self‐Aggregation to Sea Surface Temperature in Radiative Convective Equilibrium Experiments Using a Global Nonhydrostatic Model"
<p>Data used in JAMES paper "Sensitivity of the Horizontal Scale of Convective Self‐Aggregation to Sea Surface Temperature in Radiative Convective Equilibrium Experiments Using a Global Nonhydrostatic Model" by Shuhei Matsugishi and Masaki Satoh doi: 10.1029/2021MS002636</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.