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.
1,425
datasets available to search
ShareScore release 0.7.1
Dataset results
1,425 results for “Agriculture”
Typology of agricultural land systems of Germany at a resolution of 100 hectares.
The decline of farmland biodiversity has widely been recognized in society and politics. Many factors that negatively affect biodiversity are associated with agriculture. European policy instruments and measures, which aimed at mitigating these impacts, have not been successful in counteracting the negative trends of farmland biodiversity. There is a growing recognition that conservation policy instruments need to be spatially targeted, given the heterogeneity of agricultural landscapes and extent of agricultural intensification in Europe. For Germany, we developed a typology of agricultural land systems (ALS) that captures the regional characteristics of agricultural intensification. For this purpose, we applied a cluster-analysis integrating indicators for land cover, landscape structure, land-use intensity, climate and relief at a resolution of with a spatial resolution of 1 km². As a result, we present a typology of eight ALS ranging from large-scale, intensive arable farming to extensive grassland/forest mosaics in mountains. The data included in this package contain the typology ALS and the corresponding values for the indicators for each hexagonal grid cell of 1 km²cell size. The typology of ALS could be used as a spatial framework for regional targeting of conservation policy instruments and for monitoring regional-specific trends of biodiversity indicators and their drivers. The data are supplement to the publication: Pingel, M; Sietz, D; Röder, N; Klimek, S and Golla, B. (2025) Typology of Agricultural Land Systems to Support Tailored Agri-Environmental Schemes for Farmland Biodiversity: A Case Study from Germany. [Preprint]. http://dx.doi.org/10.2139/ssrn.5162566.
Simulated bioenergy crop yield on agricultural land in a 10-county region of western North Carolina.
We used a mechanistic plant growth model, ALMANAC (Kiniry 1996), to simulate the growth of bioenergy crops including switchgrass, miscanthus, and hybrid poplar. We selected simulation points by overlaying SSURGO soil data polygons with a 1-km resolution observed climate dataset (Thornton et al. 2012). The centroid of each unique soil polygon and climate cell combination was used as a simulation point, resulting in over 69,000 simulation points. Crop growth was simulated at each point for 10 (grasses) or 12 (poplar) years and replicated 10 times. We limited our simulation to area currently identified as agriculture, pasture, grass- or shrubland in the 2012 National Cropdata Layer.
The effects of agricultural land-use history on non-native plant invasion in Bent Creek Experimental Forest in 2006
The researchers considered the effects of agricultural land-use legacies on the distribution of non-native invasive plants a century after abandonment in a watershed in western North Carolina, USA. The study was conducted at the Bent Creek Experimental Forest (BCEF) 15 km southwest of Asheville, North Carolina, USA, in the Pisgah National Forest. Forest sites that were previously in cultivation and abandoned ca. 1905 were compared with nearby reference sites that were never cultivated. The most common invasive plants were Celastrus orbiculatus Thunb., Microstegium vimineum Trin., and Lonicera japonica Thunb. (Kuhman, Pearson, and Turner 2011). Disentangling the cause–effect relationships between land-use history, the biotic community, and the abiotic template presents a challenge, but understanding the role of land-use legacies may provide important insights regarding the mechanisms underlying the establishment and spread of invasive plants in forest ecosystems (Kuhman, Pearson, and Turner 2011). A total of 86 plots were established at Bent Creek Experimental Forest during the summer of 2006. Specifically, the study was conducted between June and August 2006. Half of these were established in historic agricultural plots and half in reference plots that were not formerly used for agriculture (pasture or rowcrops) based on the 1941 Forest Service Report by William Nesbitt and the appended land-use history map (History of early settlement and land use on the Bent Creek Experimental Forest Buncombe County, NC. 1941). Historic agriculture and reference plots were paired based on similarities in topography and bedrock geology (typically in relatively close proximity to one another). Within sites, two plots were established, one adjacent to the road and one 50 m away from the road (labeled as "A" and "B", respectively, in the "Plot #").
Institutional Dimensions of Restoring Everglades Water Quality - Social Capital Analysis (FCE), Florida Everglades Agricultural Area from September 2014 to July 2015
These data were compiled through the Institutional Dimensions of Restoring Everglades Water Quality research project. One of the manuscripts generated by this project focused on the social capital dynamics in the Everglades Agricultural Area. These data represent different social capital aspects reflected by the responses of interview subjects. The purpose of analyzing social capital was to explore why and how farmers cooperated given that the state law, the Everglades Forever Act, which required the adoption of best management practices, relied on shared compliance for farmers to improve water quality. The study sought to undrestand how different aspects of social capital (broadly pro-social norms of reciprocity and trust) either encouraged or discouraged farmers to adopt BMPs effectively.
Supplementary dataset for "Global agricultural economic water scarcity"
<p>This repository contains supporting data for: "<strong>Global agricultural economic water scarcity"</strong></p> <p>Cite: Rosa, L., Chiarelli, D.D., Rulli, M.C., Dell’Angelo J., and D’Odorico, P. Global agricultural economic water scarcity. Science Advances. 2020<br> Email: lorenzo_rosa@berkeley.edu</p> <p>The dataset contains the number of months (#months) croplands are facing green water scarcity (GWS), blue water scarcity (BWS), and economic water scarcity (EWS). Where "0" indicates that the pixel does not face water scarcity, "1" indicates that the pixel is facing water scarcity for 1 month, "12" indicates that the pixel is facing water scarcity for 12 months. Files are uploaded in arcmap and netcdf formats. </p> <p> </p>
Figure 7 in Diversity and life-history traits of wild bees (Insecta: Hymenoptera) in intensive agricultural landscapes in the Rolling Pampa, Argentina
Figure 7. Mean number of (a) above-ground nesting bee individuals, (b) floral specialist bee individuals, (c) oligolectic bee individuals and (d) oil-collecting bee individuals in cropped area (n = 28 points) and semi-natural area (n = 11 points). ns indicates a non-significant result. Asterisks indicate that means are significantly different (Wilcoxon rank sum test, ** = P <0.01). Bars show SEs.
Figure 2 in Diversity and life-history traits of wild bees (Insecta: Hymenoptera) in intensive agricultural landscapes in the Rolling Pampa, Argentina
Figure 2. Semi-natural area of the study site: (a) semi-natural grassland; (b) the stream 'Arroyo Dulce' and its banks (Photos: Violette Le Féon).
MAGIC Deliverable 5.5 - Datasets - Report on the Quality Check of the Robustness of the Narrative behind the Common Agricultural Policy (CAP)
<p>This repository contains datasets used in the production of figures contained in MAGIC Deliverable 5.5</p> <p>Matthews K.B., Blackstock K.L., Waylen K.A., Juarez-Bourke A., Miller D.G., Wardell-Johnson D.H., Rivington M. (2018) Report on the Quality Check of the Robustness of the Narrative behind the Common Agricultural Policy (CAP).</p> <p>MAGIC (H2020-GA 689669) Project Deliverable 5.5 - 29th November 2018</p> <p><a href="https://magic-nexus.eu/documents/d55-report-narratives-behind-cap">MAGIC Deliverable 5.5</a></p>
Agriculture Keywords Dataset
<p>This dataset consists of 193 agricultural keywords in English and Luganda. 64 keywords are in English and 129 keywords are in Luganda. The list of keywords was compiled by obtaining the counts of the most used agricultural words in Luganda radio discussions and online newspaper in Uganda. The keywords are categorized into crops, diseases, fertilisers, herbicides and general agriculture-related keywords. The data consists of folders containing .wav files with unique IDs as file names. The name of each folder in dataset refers to the name of the keyword. The dataset consists of 5290 keyword utterances in Luganda. These were collected from different age groups and gender. </p>
Drone-based aerial imagery of rivers, wetlands and agricultural systems in Zambia
<p>Unmanned aerial vehicle (UAV) imagery of rivers, wetlands and agricultural systems across Zambia. Collected during two flying seasons in March and September 2018, with a total of 122 scenes at 48 sites.</p> <p>All imagery is made available on OpenAerialMap (<a href="https://map.openaerialmap.org">https://map.openaerialmap.org</a>), a set of tools for searching, sharing, and using openly licensed satellite and UAV imagery. Detailed description of the dataset provided in a .csv file.</p>
Proactive conservation to prevent habitat losses to agricultural expansion
<p>The projected loss of millions of square kilometres of natural ecosystems to meet future demand for food, animal feed, fibre, and bioenergy crops is likely to massively escalate threats to biodiversity. Reducing these threats requires a detailed knowledge of how and where they are likely to be most severe. We developed a geographically explicit model of future agricultural land clearance based on observed historic changes and combine the outputs with species-specific habitat preferences for 19,859 species of terrestrial vertebrates. We project that 87.7% of these species will lose habitat to agricultural expansion by 2050, with 1,280 species projected to lose ≥25% of their habitat. Proactive policies targeting how, where, and what food is produced could reduce these threats, with a combination of approaches potentially preventing almost all these losses while contributing to healthier human diets. As international biodiversity targets are set to be updated in 2021, these results highlight the importance of proactive efforts to safeguard biodiversity by reducing demand for agricultural land.</p>
Farmer adaptive behavior and risk management in EU agriculture
<p>Risk and risk management are essential elements of agriculture and affect the wellbeing of farm households. Farmers react to production, market and institutional risks and challenges by taking measures on or off the farm. Such risk management measures are often costly and have implications for up- and downstream industries as well as the environment. The risk exposure of European farms is increasing. For example, climate change will increase the frequency and magnitude of extreme weather events like droughts, heatwaves and heavy rainfalls that potentially have detrimental effects on agricultural production. Thus, the adaptive capacity and risk management options in European agriculture need to be improved. Policy shall support this process. Policies are needed to support a diversity of risk management solutions and not only focus on a few solutions. Strategies to cope with risk often go beyond the level of the individual farm. Cooperation, learning and sharing of risks play a vital role in European agriculture and shall be strengthened. Thus, coordinated policies targeting beyond the individual farm and considering all the stakeholders involved in the risk management strategies are needed to ensure their effective implementation. Moreover, policies need to facilitate to take full advantage of the rapid technological progress and improved data availability (e.g. based on satellite imagery) to develop a wider set of risk management strategies.</p>
Data from: Reduced snow cover increases wintertime nitrous oxide (N2O) emissions from an agricultural soil in the upper U.S. Midwest
Throughout most of the northern hemisphere, snow cover decreased in almost every winter month from 1967 to 2012. Because snow is an effective insulator, snow cover loss has likely enhanced soil freezing and the frequency of soil freeze–thaw cycles, which can disrupt soil nitrogen dynamics including the production of nitrous oxide (N2O). We used replicated automated gas flux chambers deployed in an annual cropping system in the upper Midwest US for three winters (December–March, 2011–2013) to examine the effects of snow removal and additions on N2O fluxes. Diminished snow cover resulted in increased N2O emissions each year; over the entire experiment, cumulative emissions in plots with snow removed were 69% higher than in ambient snow control plots and 95% higher than in plots that received additional snow (P < 0.001). Higher emissions coincided with a greater number of freeze–thaw cycles that broke up soil macroaggregates (250–8000 µm) and significantly increased soil inorganic nitrogen pools. We conclude that winters with less snow cover can be expected to accelerate N2O fluxes from agricultural soils subject to wintertime freezing.
Global agricultural land use scenarios for estimating the potential of forest regeneration for climate mitigation to 2050
<p>The dataset includes 90 global food system and land use scenarios developed with the model BioBaM-GHG 2.0. The scenarios have been developed for assessing the global potential of forest regeneration for climate mitigation to 2050 under various food system pathways, i.e. diets, crop yield developments, land requirements for energy crops, and two variants of grassland use.</p> <p>The scenarios include the following data on country level: Land use and land-use change, cropland area by crop group, grazing area by quality classes, crop production by crop groups, crop consumption by crop groups and use types, crop wastes (losses), net imports/exports, production and consumption of animal products, grass supply and demand, GHG emissions from land-use change, GHG emissions from agricultural activities, and total cumulated GHG emissions.</p> <p>The main model result in this context, cumulative carbon sequestration from forest regeneration until 2050, is calculated as difference between the parameters "GHG emissions from land use change (cumulative) (Mt CO2e)" and "GHG emissions from land use change excluding C stock changes from natural succession (cumulative) (Mt CO2e)".</p> <p>Please refer to the related publication "Exploring the option space for land system futures at regional to global scales: The diagnostic agro-food, land use and greenhouse gas emission model BioBaM-GHG 2.0" (Kalt et al., 2021 - currently under review at Ecological Modelling) for further information.</p> <p>This work was funded by the Austrian Science Fund (FWF) within project P29130-G27 GELUC.</p>
Data from: Long-term nitrous oxide fluxes in annual and perennial agricultural and unmanaged ecosystems in the upper Midwest USA
Differences in soil nitrous oxide (N2O) fluxes among ecosystems are often difficult to evaluate and predict due to high spatial and temporal variabilities and few direct experimental comparisons. For 20 years, we measured N2O fluxes in 11 ecosystems in southwest Michigan USA: four annual grain crops (corn–soybean–wheat rotations) managed with conventional, no-till, reduced input, or biologically based/organic inputs; three perennial crops (alfalfa, poplar, and conifers); and four unmanaged ecosystems of different successional age including mature forest. Average N2O emissions were higher from annual grain and N-fixing cropping systems than from nonleguminous perennial cropping systems and were low across unmanaged ecosystems. Among annual cropping systems full-rotation fluxes were indistinguishable from one another but rotation phase mattered. For example, those systems with cover crops and reduced fertilizer N emitted more N2O during the corn and soybean phases, but during the wheat phase fluxes were ~40% lower. Likewise, no-till did not differ from conventional tillage over the entire rotation but reduced emissions ~20% in the wheat phase and increased emissions 30–80% in the corn and soybean phases. Greenhouse gas intensity for the annual crops (flux per unit yield) was lowest for soybeans produced under conventional management, while for the 11 other crop × management combinations intensities were similar to one another. Among the fertilized systems, emissions ranged from 0.30 to 1.33 kg N2O-N ha−1 yr−1 and were best predicted by IPCC Tier 1 and ΔEF emission factor approaches. Annual cumulative fluxes from perennial systems were best explained by soil inline image pools (r2 = 0.72) but not so for annual crops, where management differences overrode simple correlations. Daily soil N2O emissions were poorly predicted by any measured variables. Overall, long-term measurements reveal lower fluxes in nonlegume perennial vegetation and, for conservatively fertilized annual crops, the overriding influence of rotation phase on annual fluxes.
Dataset on soil hydraulic properties under contrasted plant covers and agricultural practices
<p>Complete dataset on the temporal variation of soil infiltrability along a homogeneous fluvisol, on bare soil or soil planted with two plant species with contrasted root systems (a Malvaceae with a tap-root system and a Poaceae with a fibrous root system), and impacted by three different management practices (burning, mowing, and chemical weeding). An original protocol, based on specific ring infiltrometers, able to measure the temporal dynamics of soil infiltrability was used. This dispositive takes into account the variability of the measurement across space.</p> <p> </p>
Supplementary Information S1 - Detailed results of the CAPRI N-LCA and S2 - Quantification of the main N budget flows in the EU25 agriculture sector of Leip, A., Billen, G., Garnier, J., Grizzetti, B., Lassaletta, L., Reis, S., Simpson, D., Sutton, M. a, de Vries, W., Weiss, F., Westhoek, H. (2015). Impacts of European livestock production: nitrogen, sulphur, phosphorus and greenhouse gas emissions, land-use, water eutrophication and biodiversity. Environ. Res. Lett. 10, 115004. doi:10.1088/1748-9326/10/11/115004
<p>Table S1-1 Quantification of GHG and Nr flow intensities [kg CO2eq (kg product)<sup>-1</sup> yr<sup>-1</sup>] or [g N (kg product)<sup>-1</sup> yr<sup>-1</sup>] with the CAPRI N-LCA model for six main livestock products (BEEF: beef, PORK: pork, EGGS: eggs, POUM: poultry meat; DAIR: milk and dairy products, SGMP: meat from sheep and goats) and six main vegetable food groups (POTA: potatoes, SUGB: sugar beet before processing, OILP: oil seeds before processing; CERR: cereals, LEGU: leguminous crops) as well as other crops (OCRP) and aggregated livestock (ANIMP) and vegetable (CROPP) food. </p> <p>Table S2-1 Quantification of the main N budget flows in the EU25 agriculture sector</p>
Dataset supplementing Lichtenberg et al. (2017) A global synthesis of the effects of diversified farming systems on arthropod diversity within fields and across agricultural landscapes. Global Change Biology
<p>This dataset contains data and scripts that supplement the publication</p> <p>Lichtenberg et al. (2017) A global synthesis of the effects of diversified farming systems on arthropod diversity within fields and across agricultural landscapes. Global Change Biology. DOI: 10.1111/gcb.13714</p> <p> </p> <p>Please cite the above article if you use any of the included data or code.</p> <p> </p> <p>Files are described in README.md.</p>
World Map of Agricultural Robot Manufacturer & services
<p>This Data Base is a World Map of all the manufacturers of agricultural robot for field. this data base was created by 3 student of the University of UniLaSalle Beauvais. You can fin the LINK of the GOOGLE EARTH "only reading" on the PDF document.</p>
CESM2 Atmospheric CO2 without agricultural management
This dataset was created to understand the impacts of agriculture on CO2 concentrations. Two 1-degree simulations were branched from the CMIP6 "CESM2-esm-hist" simulation in 1970. The first of these turned off the explicit representation of agriculture so that all crop areas are represented as "generic" C3 crops, where crop phenology is simulated as C3 grasses and do not include irrigation or fertilization (referred to as "generic crop"). The second uses the explicit representation of agriculture but removes industrial N fertilization (referred to as "no fertilization"). To ensure that changes in CO2 fluxes were minimally impacted by model drift, each simulation equilibrated carbon fluxes in 1970 by cycling over a single year of forcing for ten years. The CESM2 simulated these alternative representations of agriculture in a CO2 emissions-forced historical scenario following the "esm-hist" experimental protocol.
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.