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.
154
datasets available to search
ShareScore release 0.9.0
Dataset results
154 results for “croplands”
A synthesis of nitric oxide emissions across global fertilized croplands from crop-specific emission factors
Open the record for dataset details and reuse information.
Soil structure changes under reduced tillage and cover cropping enhance carbon mineralization in Mediterranean croplands
Open the record for dataset details and reuse information.
Quantifying nitrogen deposition inputs to cropland: A national scale dataset from 1961 to 2020
Open the record for dataset details and reuse information.
Woodland, cropland and hedgerows promote pollinator abundance in intensive grassland landscapes, with saturating benefits of flower cover
Open the record for dataset details and reuse information.
Data from: Cropland connectivity affects genetic divergence of Colorado potato beetle along an invasion front
Open the record for dataset details and reuse information.
Cropland management impacts on soil organic carbon stock changes in US croplands from 1990 to 2015
Open the record for dataset details and reuse information.
Common birds have higher abundances in croplands with lower pesticide purchases
Open the record for dataset details and reuse information.
The super-rich and cropland expansion via direct investments in agriculture
Open the record for dataset details and reuse information.
Fearfulness of geese and swans on cropland in winter: A multi-species Flight Initiation Distance approach
Open the record for dataset details and reuse information.
Dataset for: Water, environment, and socioeconomic justice in California: A multi-benefit cropland repurposing framework
Open the record for dataset details and reuse information.
Data to support manuscript "Fates and fingerprints of sulfur and carbon following wildfire in economically important croplands of California, U.S."
Abstract Sulfur (S) is widely used in agriculture, yet little is known about its fates within upland watersheds, particularly in combination with disturbances like wildfire. This dataset includes samples collected within the Napa River Watershed, California, U.S., where high S applications to vineyards are common, and ~20% of the watershed burned in October 2017. The data package includes soil, soil leachate, and stream chemistry data from sites representing a combination of land use (vineyard agriculture and grasslands) and burn (burned and unburned). Bulk soil chemical measurements include total sulfur and carbon concentrations and sulfur stable isotopes. We then used a laboratory rainfall experiment to simulate a wet season of precipitation in order to compare unburned and low severity burned vineyard and grassland soil leachate chemistry. Soil leachate measurements include total dissolved sulfur, sulfate, and dissolved organic carbon concentrations, sulfate-sulfur stable isotopes, and the specific ultraviolet absorbance at 254 nm (SUVA254), an index strongly correlated with DOC aromaticity. We compared soil leachate chemistry to stream samples draining sub-catchments with differing land use and degrees of burn and severity to understand combined effects at broader spatial scales. Soil and stream chemistry are provided in separate data tables, and data from the laboratory rainfall experiment is included in the leachingexpts (leaching experimental record), leachingexpchem (chemistry), and leachingexpisotopes (sulfur stable isotopes) data tables.
Natural potential for future cropland expansion
<p><strong>Natural potentials for future cropland expansion </strong></p> <p>The potential for the expansion of cropland is restricted by the availability of land resources and given local natural conditions. As a result, area that is highly suitable for agriculture according to the prevailing local biophysical conditions but is not under cultivation today has a high natural potential for expansion. Policy regulations can further restrict the availability of land for expansion by designating protected areas, although they may be suitable for agriculture. Conversely, by applying e.g. irrigation practices, land can be brought under cultivation, although it may naturally not be suitable. Here, we investigate the potentials for agricultural expansion for near future climate scenario conditions to identify the suitability of non-cropland areas for expansion according to their local natural conditions.</p> <p>We determine the available energy, water and nutrient supply for agricultural suitability from climate, soil and topography data, by using a fuzzy logic approach according to Zabel et al. (2014). It considers the 16 globally most important staple and energy crops. These are: barley, cassava, groundnut, maize, millet, oil palm, potato, rapeseed, rice, rye, sorghum, soy, sugarcane, sunflower, summer wheat, winter wheat. The parameterization of the membership functions that describe each of the crops’ specific natural requirements is taken from Sys et al. (1993). The considered natural conditions are: climate (temperature, precipitation, solar radiation), soil properties (texture, proportion of coarse fragments and gypsum, base saturation, pH content, organic carbon content, salinity, sodicity), and topography (elevation, slope). As a result of the fuzzy logic approach, values in a range between 0 and 1 describe the suitability of a crop for each of the prevailing natural conditions at a certain location. The smallest suitability value over all parameters finally determines the suitability of a crop. The daily climate data is provided by simulation results from the global climate model ECHAM5 (Jungclaus et al. 2006) for near future (2011-2040) SRES A1B climate scenario conditions. Soil data is taken from the Harmonized World Soil Database (HWSD) (FAO et al. 2012), and topography data is applied from the Shuttle Radar Topography Mission (SRTM) (Farr et al. 2007). In order to gather a general crop suitability, which does not refer to one specific crop, the most suitable crop with the highest suitability value is chosen at each pixel.</p> <p>In addition the natural biophysical conditions, we consider today’s irrigated areas according to (Siebert et al. 2013). We assume that irrigated areas globally remain constant until 2040, since adequate data on the development of irrigated areas do not exist, although it is likely that freshwater availability for irrigation could be limited in some regions, while in other regions surplus water supply could be used to expand irrigation practices (Elliott et al. 2014). However, it is difficult to project where irrigation practices will evolve, since it is driven by economic investment costs that are required to establish irrigation infrastructure.</p> <p>In principle, all agriculturally suitable land that is not used as cropland today has the natural potential to be converted into cropland. We assume that only urban and built-up areas are not available for conversion, although more than 80% of global urban areas are agriculturally suitable (Avellan et al. 2012). However, it seems unlikely that urban areas will be cleared at the large scale due to high investment costs, growing cities and growing demand for settlements. Concepts of urban and vertical farming usually are discussed under the aspects of cultivating fresh vegetables and salads for urban population. They are not designed to extensively grow staple crops such as wheat or maize for feeding the world in the near future. Urban farming would require one third of the total global urban area to meet only the global vegetable consumption of urban dwellers (Martellozzo et al. 2015). Thus, urban agriculture cannot substantially contribute to global agricultural production of staple crops.</p> <p>Protected areas or dense forested areas are not excluded from the calculation, in order not to lose any information in the further combination with the biodiversity patterns (see chapter 2.3). We use data on current cropland distribution by Ramankutty et al. (2008) and urban and built-up area according to the ESA-CCI land use/cover dataset (ESA 2014). From this data, we calculate the ‘natural expansion potential index’ (I<sub>exp</sub>) that expresses the natural potential for an area to be converted into cropland as follows:</p> <p>I<sub>exp</sub> = S * A<sub>av</sub></p> <p>The index is determined by the quality of agricultural suitability (S) (values between 0 and 1) multiplied with the amount of available area (A<sub>av</sub>) for conversion (in percentage of pixel area). The available area includes all suitable area that is not cultivated today, and not classified as urban or artificial area. The index ranges between 0 and 100 and indicates where the conditions for cropland expansion are more or less favorable, when taking only natural conditions into account, disregarding socio-economic factors, policies and regulations that drive or inhibit cropland expansion. The index is a helpful indicator for identifying areas where cropland expansion could take place in the near future.</p> <p><strong>Further information</strong></p> <p>Detailled information are available in the following publication:</p> <p>Delzeit, R., F. Zabel, C. Meyer and T. Václavík (2017).<strong> Addressing future trade-offs between biodiversity and cropland expansion to improve food security</strong>. Regional Environmental Change 17(5): 1429-1441. DOI: 10.1007/s10113-016-0927-1</p> <p><strong>Contact</strong></p> <p>Please contact: Dr. Florian Zabel, <a href="mailto:f.zabel@lmu.de">f.zabel@lmu.de</a>, Department für Geographie, LMU München (<a href="http://www.geografie.uni-muenchen.de">www.geografie.uni-muenchen.de</a>)</p>
Impact of cropland physiology and phenology on watershed hydrology in a semi-arid watershed in the Pacific Northwest in a changing climate
<p>The scripts and figures for the study.</p> <p> </p> <p>The scripts for creating the CLM5 case with transient CO2 concentration over UCPR watershed</p> <p>For the CO2 concentration and N deposition inputs, please find at <a href="https://svn-ccsm-inputdata.cgd.ucar.edu/trunk/inputdata/lnd/clm2/">https://svn-ccsm-inputdata.cgd.ucar.edu/trunk/inputdata/lnd/clm2/</a></p> <p>inputdata: <a href="https://github.com/bwZh/SFA-CO2-effects-using-CLM5">https://github.com/bwZh/SFA-CO2-effects-using-CLM5</a></p> <p>domain data: domain.lnd.1kmx1km_UCPR_c20190605.nc.</p> <p>parameter data: clm5_params_calibration3_wwrainfed_UCPRvcmax.c171117.nc</p> <p>surface data: Please contact <a href="mailto:bowen.zhu@pnnl.gov">bowen.zhu@pnnl.gov</a> or <a href="mailto:bwzhu@mail.bnu.edu.cn">bwzhu@mail.bnu.edu.cn</a></p> <p> </p>
Detailed global modelling of soil organic carbon in cropland, grassland and forest soils
<p>Supporting information of the paper: Morais, T.G., Teixeira, R.F.M., Domingos, T. 2019. Detailed global modelling of soil organic carbon in cropland, grassland and forest soils. PloS One.</p> <p>Version 2 includes raster files (.tif) for each land use class (including: Attainable SOC stock, mineralization rate, and fator K).</p>
Data from: Changes in levels of enzymes and osmotic adjustment compounds in key species and their relevance to vegetation succession in abandoned croplands of a semiarid sandy region
<p>Reclamation of cropland from grassland is regarded as a main reason for grassland degradation; understanding succession from abandoned cropland to grassland is thus crucial for vegetation restoration in arid and semiarid areas. Soil becomes dry when cropland is reverted to grassland, and enzyme and osmotic adjustment compounds may help plants to adapt to a drying environment. Croplands that were abandoned in various years on the Ordos Plateau in China, were selected for the analysis of the dynamics of enzymes and osmotic adjustment compounds in plant species during vegetation succession. With increasing number of years since abandonment, levels of superoxide dismutase<span> increased</span><span> in </span><i><span><span>Stipa</span></span></i><i><span><span> bungeana</span></span></i><span>, first decreased </span><span>and then increased in </span><i><span><span>Lespedeza</span></span></i><i><span><span> davurica</span></span></i><span> and </span><i><span><span>Artemisia f</span></span></i><i><span><span>rigida</span></span></i><span>, and fluctuated in </span><i><span><span>Heteropappus altaicus</span></span></i><span>. Levels</span> of<span> peroxidase and catalase in the four species fluctuated</span><span>;</span> levels of<span> proline, soluble sugar and soluble protein either</span><i> </i><span>decreas</span><span>ed</span><span> or</span><span> first </span><span>increase</span><span>d</span><span> and</span><span> then</span><span> generally decreased.</span> According to <span>a </span><span>drought resistance</span><span> index</span>, the <span>drought resistance of the </span><span>four </span><span>species</span><span> was </span><span>ranked in descending order as follows</span>: <i><span>S. bungeana </span></i><span>> </span><i><span>A. frigida </span></i><span>> </span><i><span>H. altaicus</span></i> <span>> </span><i><span>L. davurica</span></i>. The drought resistance ability of the different species was<span> closely linked with vegetation succession from communities dominated by annual and biennial species (with main accompanying species of </span><i><span><span>L.</span></span></i><i><span><span> davurica</span></span></i> <span>and</span><i><span><span> H. altaicus</span></span></i><span>) to communities dominated by perennial species (</span><i><span><span>S.</span></span></i><i><span><span> bungeana</span></span></i><span> and </span><i><span><span>A. f</span></span></i><i><span><span>rigida</span></span></i><span>) when soil became dry owing to increasing evapotranspiration after cropland abandonment. </span>The restoration of <i><span>S. bungeana </span></i>steppe after cropland abandonment on the Ordos Plateau<span> is recommended both as high-quality forage and for environmental sustainability</span>.</p>
Data from: Pervasive cropland in protected areas highlight trade-offs between conservation and food security
<p>Global cropland expansion over the last century caused widespread habitat loss and degradation. Establishment of protected areas aims to counteract the loss of habitats and to slow species extinctions. However, many protected areas also include high levels of habitat disturbance and conversion for uses such as cropland. Understanding where and why this occurs may realign conservation priorities and inform protected area policy in light of competing priorities such as food security. Here we use a new global synthesis cropland dataset to quantify cropland in protected areas globally, and assess their relationship to conservation aims and socio-environmental context. We estimate that cropland occupies 1.4 million km<sup>2</sup> or 6% of global protected area. Cropland occurs across all protected area management types, with 22% occurring in strictly protected areas. Cropland inside protected areas is more prevalent in countries with higher population density, lower income inequality, and with higher agricultural suitability of protected lands. While this phenomenon is dominant in mid-northern latitudes, areas of cropland in protected areas of the tropics and subtropics may present greater trade-offs due to higher levels of both biodiversity and food insecurity. Although area-based targets are prominent in biodiversity goal-setting, our results show that they can mask persistent anthropogenic land uses detrimental to native ecosystem conservation. To ensure the long-term efficacy of protected areas, post-2020 goal setting must link aims for biodiversity and human health and improve monitoring of conservation outcomes in cropland-impacted protected areas.</p>
Data from: Comparing the impact of future cropland expansion on global biodiversity and carbon storage across models and scenarios
<p>Land-use change is a direct driver of biodiversity and carbon storage loss. Projections of future land-use often include notable expansion of cropland areas in response to changes in climate and food demand, although there are large uncertainties in results between models and scenarios. This study examines these uncertainties by comparing three different socio-economic scenarios (SSP1-3) across three models (IMAGE, GLOBIOM and PLUMv2). It assesses the impacts on biodiversity metrics and direct carbon loss from biomass and soil as a direct consequence of cropland expansion. Results show substantial variation between models and scenarios, with little overlap across all nine projections. Although SSP1 projects the least impact, there are still significant impacts projected. IMAGE and GLOBIOM project the greatest impact across carbon storage and biodiversity metrics due to both extent and location of cropland expansion. Furthermore, for all the biodiversity and carbon metrics used, there is a greater proportion of variance explained by model used. This demonstrates the importance of improving the accuracy of land-based models. Incorporating effects of land-use change in biodiversity impact assessments would also help better prioritise future protection of biodiverse and carbon-rich areas.</p>
Performance Evaluation of Seven Remote Sensing Datasets for TRB Cropland Area Estimation (Accuracy Metrics and Temporal Trends)
<p>This dataset contains accuracy assessments and trend analyses for cropland area estimation using seven remote sensing datasets in the TRB region. The data is organized into the following structure:<br>1. Accuracy Evaluation ("RMSE+Rt+MPE" directory)</p> <p>Contains individual evaluation files for each of the seven remote sensing products<br>File naming convention: [DatasetName]_Evaluation.csv<br>Each file contains four columns:</p> <p>County: Administrative region<br>Rt: Temporal correlation<br>RMSE: Root Mean Square Error<br>MPE: Mean Percentage Error</p> <p>2. Area Change Trends ("Trend" directory)</p> <p>Contains trend analysis files for seven remote sensing products and reference observations (OBS)<br>File naming convention: [DatasetName/OBS]_trend.csv<br>Each file contains three columns:</p> <p>County: Administrative region<br>Slope: Trend slope coefficient<br>P_value: Statistical significance value</p> <p>3. Spatial Correlation (Rs.csv)</p> <p>Single file containing annual spatial correlation coefficients (Rs) for all seven remote sensing datasets.</p>
salinity of arid croplands
<p>Salinity time series</p>
Persistence of seed dispersal in agroecosystems: effects of landscape modification and intensive soil management practices in avian frugivores, frugivory and seed deposition in olive croplands
<p>Farming impacts on animal-mediated seed dispersal through mechanisms operating at least at two spatial scales: first, at the landscape scale, through habitat loss and land conversion to agriculture/livestock grazing, and second, by local intensification (farm scale) of the agricultural practices. Nonetheless, these two scales of farming impact on the seed dispersal function have been rarely integrated. In particular, studies evaluating the effect of agriculture in the seed dispersal function of frugivorous birds in Mediterranean ecosystems are lacking. We evaluate the role of the landscape transformation, from fruit-rich woodland habitats to olive grove landscapes, together with the local intensive practices of soil management on the persistence of the seed dispersal function for Mediterranean fleshy-fruited plants in olive landscapes of south Spain.</p> <p>We used bird censuses, mist-nets and seed traps to characterize avian frugivore assemblages, frugivory, and seed deposition in seminatural woodland habitat (SNWH) patches and olive fields of 40 olives farms of 20 localities distributed across the whole range of olive cultivation in Andalusia (southern Spain).</p> <p>We found that despite of a still remarkable dispersal function in olive grove landscapes, avian frugivore abundance and diversity, frugivory, and seed arrival decreased in olive fields compared to SNWH patches. Likewise, SNWH cover loss and/or olive growing expansion decreased avian frugivory and seed arrival. Interestingly, habitat effects in the olive farms often depended on the landscape context. In particular, less diverse fruit-eating bird assemblages pooled in SNWH patches as olive grove cover increased or SNWH decreased in the landscape, while remained relatively invariant in the olive fields. Finally, compared to conventional intensive agriculture, low-intensity management increased frugivory and seed deposition.</p> <p>We conclude that olive fields are less permeable to frugivores than expected by its agroforest-like nature, and that presence of SNWH patches is crucial for the maintenance of frugivory and seed dispersal in agricultural landscapes. Results evidence that woodland habitat loss by olive expansion and the intensive practices seriously threaten the dispersal service in olive-dominated landscapes. Maintenance, restoration and promotion of woodland patches should be prioritized for the conservation of the seed dispersal service and for enhancing the functional connectivity in human-shaped olive landscapes.</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.