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118
datasets available to search
ShareScore release 0.9.0
Dataset results
118 results for “cropping systems”
Data from: Soil microbes alter herbivore-induced volatile emissions in response to cereal cropping systems
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Data from: Comparative productivity of six bioenergy cropping systems on marginal lands in the Great Lakes Region, United States
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Dataset for manuscript entitled: Switchgrass cropping systems affect soil carbon and nitrogen and microbial diversity and activity on marginal lands
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Synergies and trade-offs between ecosystem services and economics in dryland cover crop systems
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Data from: Soil carbon maintained by perennial grasslands over 30 years but lost in field crop systems in a temperate Mollisol
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Sustainable landscape, soil and crop management practices enhance biodiversity and yield in conventional cereal systems
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Data from: Soil phosphorus drawdown by perennial bioenergy cropping systems in the Midwestern US
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Data from: Field-scale experiments reveal persistent yield gaps in low-input and organic cropping systems
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Contribution of wheat and maize to soil organic carbon in a wheat-maize cropping system: a field and laboratory study
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Data from: Nitrous oxide emissions during establishment of eight alternative cellulosic bioenergy cropping systems in the North Central United States
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Final eddy covariance dataset to support lessons from long-term monitoring of carbon gains and losses in cropping systems
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Data from: Crop performance and profitability for the initial transition years of a regenerative cropping system in the Upper Midwest USA
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Overyielding is accounted for partly by plasticity and dissimilarity of crop root traits in maize/legume intercropping systems
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Data from: Highly diversified crop-livestock farming systems reshape wild bird communities
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Soil nitrous oxide emissions from global specialty crop systems
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Data from: Impacts of rotation, tillage, cover cropping, and drainage on soil health in soybean-based cropping systems: Evidence from 4–50-year trials across the US
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Data for: Biochar co-compost improves nitrogen retention and reduces carbon emissions in a winter wheat cropping system
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Surface Elevation on the Main Cropping System Experiment at the Kellogg Biological Station, Hickory Corners, MI (2004 to 2004)
Dataset Abstract Surface elevations were measured on the Main Cropping System Experiment. original data source http://lter.kbs.msu.edu/datasets/125
KBS Stand Counts in Row Crop Agriculture on the Main Cropping System Experiment at the Kellogg Biological Station, Hickory Corners, MI (2003 to 2006)
Dataset Abstract Annual stand count data from the Main site Agronomic Plots T1 through T4. original data source http://lter.kbs.msu.edu/datasets/33
Data from: Machine learning improves predictions of agricultural nitrous oxide (N2O) emissions from intensively managed cropping systems
<p><span>The potent greenhouse gas nitrous oxide (N</span><sub><span>2</span></sub><span>O) is accumulating in the atmosphere at unprecedented rates largely due to agricultural intensification, and cultivated soils contribute ~60% of the agricultural flux. Empirical models of N</span><sub><span>2</span></sub><span>O fluxes for intensively managed cropping systems are confounded by highly variable fluxes and limited </span><span><span>geographic coverage;</span></span><span> process-based biogeochemical models are rarely able to predict daily to monthly emissions with > 20% accuracy even with site-specific calibration. Here we show the promise for machine learning (ML) to significantly improve field-level flux predictions, especially when coupled with a cropping systems model to simulate unmeasured </span><span><span>soil</span></span><span> parameters. We used sub-daily N</span><sub><span>2</span></sub><span>O flux data from six years of automated flux chambers installed in a continuous corn rotation at a site in the upper U.S. Midwest (~3000 sub-daily flux observations), supplemented with weekly to biweekly manual chamber measurements (~1100 daily fluxes), to train an ML model that explained 65-89% of daily flux variance with very few input variables –soil moisture, days after fertilization, soil texture, air temperature, soil carbon, precipitation, and N fertilizer rate. When applied to a long-term test site not used to train the model, the model explained 38% of the variation observed in weekly to biweekly manual chamber measurements from corn, and 51% upon coupling the ML model with a cropping systems model that predicted daily soil N availability. </span><span><span>This represents a 2-3 times improvement over conventional process-based models and with substantially fewer input requirements.</span></span><span> This coupled approach </span><span><span>offers promise</span></span><span> for better predictions of agricultural N</span><sub><span>2</span></sub><span>O emissions and thus more precise global models and more effective </span><span><span>agricultural mitigation interventions.</span></span></p>
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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)
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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.