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1,425 results for “Agriculture”
Data from: Nitrification is a minor source of nitrous oxide (N2O) in an agricultural landscape and declines with increasing management intensity
<p>The long-term contribution of nitrification to nitrous oxide (N<sub>2</sub>O) emissions from terrestrial ecosystems is poorly known and thus poorly constrained in biogeochemical models. Here, using Bayesian inference to couple 25 years of <i>in situ</i> N<sub>2</sub>O flux measurements with site-specific Michaelis-Menten kinetics of nitrification-derived N<sub>2</sub>O, we test the relative importance of nitrification-derived N<sub>2</sub>O across six cropped and unmanaged ecosystems along a management intensity gradient in the U.S. Midwest. We found that the maximum potential contribution from nitrification to <i>in situ</i> N<sub>2</sub>O fluxes was 13-17% in a conventionally fertilized annual cropping system, 27-42% in a low-input cover-cropped annual cropping system, and 52-63% in perennial systems including a late successional deciduous forest. Actual values are likely to be less than 10% of these values because of low N<sub>2</sub>O yields in cultured nitrifiers (typically 0.04 to 8% of NH<sub>3</sub> oxidized) and competing sinks for available NH<sub>4</sub><sup>+</sup> <i>in situ</i>. Most nitrification-derived N<sub>2</sub>O was produced by ammonia oxidizing bacteria (AOB) rather than archaea (AOA), who appeared responsible for no more than 30% of nitrification-derived N<sub>2</sub>O production in all but one ecosystem. Although the proportion of nitrification-derived N<sub>2</sub>O production was lowest in annual cropping systems, these ecosystems nevertheless produced more nitrification-derived N<sub>2</sub>O (higher V<sub>max</sub>) than perennial and successional ecosystems. We conclude that nitrification is minor relative to other sources of N<sub>2</sub>O in all ecosystems examined.</p>
Detection histories of mesocarnivores in agricultural areas of Southern Chile
<p>We obtained mesocarnivore detection/non-detection data from 180 sampling units (4 km<sup>2</sup> each) located in the agricultural landscapes of southern Chile from January-April of 2019. We used single-species occupancy models to investigate the associations of forest fragmentation, forest loss, and private land ownership subdivision (as a measure of human use intensification) with the occurrence of four mesocarnivores (güiña, grey fox, culpeo fox, and Molina's hog-nosed skunk), and extended this framework to two-species occupancy models to assess patterns of mesocarnivore co-occurrence with domestic carnivores. We also assessed whether co-occurrence of native and domestic carnivores led to shifts in species' temporal activity.</p> <p>We hypothesized that the occurrence of native mesocarnivores was largely mediated by human use intensification variables only, the occurrence of domestic mesocarnivores only, or a combination of both. Our results largely supported the human use intensification hypothesis, with some influence of domestic mesocarnivores. Mesocarnivore occurrence shifted from a native to a domestic species composition as private land ownership subdivision increased, and native mesocarnivores shifted their behaviour temporally when co-occurring with domestics. In addition, the presence of domestic dogs was associated with an absence of native mesocarnivores, possibly driving a defaunation process in agricultural areas.</p>
Abundance of Drosophila suzukii in the agricultural landscape
<p>We sampled the abundance of males and females in the agricultural landscape in Slovenia. We selected 10 locations in the central part of Slovenia, five of which were closer than 200 m from the forest edge and five of which were more than 200 m from the forest edge. We collected SWD adults in three habitat types per location from the end of June until the end of October 2020. Also the actual distance is taken into account. We have two datasets in which the abundance is pooled for the whole period and one in which the sampling period is every two weeks. In the analysis of the article the number of SWD were standardized to number of SWD per 14 days.</p>
CS16: Policy for sustainable development ( development of "Croatian Case Study - Legumes: their potential role in Croatian agricultural production")
<p>(i)The main aim is to develop a document that will gave an overview of current situation regarding legumes consumption and production in Croatia and also to develope a reccomendations for policy makers. <br> (ii) Purpose of this Case Study and the whole project implementation is to raise awareness about consumption and production of legumes both for human consumption and animal feed.<br> (iii) April 2019.- September 2019. <br> (iv) Species - N.A. <br> (v) PIRED facilities<br> (vi) Following different methodological tools was applied like: desk research, analysis of available quantitative historical data, interviews with key regional retailers and company managers, focus groups, benchmarking, expert analysis and expert drafting<br> (vii) detection of number of producers, utilized areas, processing infrastructure and development of recommendations for policy makers and local decision makers. <br> (viii) in progress<br> (ix) This document will have significant impact on policy, mainly on local level ( for local decision makers) because developed recommendations will gave an directions, guideline and examples of good practice.</p>
CS16: Policy for sustainable development ( development of "Croatian Case Study - Legumes: their potential role in Croatian agricultural production")
<p>(i)The main aim is to develop a document that will gave an overview of current situation regarding legumes consumption and production in Croatia and also to develop recommendations for policy makers. <br> (ii) Purpose of this Case Study and the whole project implementation is to raise awareness about consumption and production of legumes both for human consumption and animal feed.<br> (iii) April 2019.- September 2019. <br> (iv) Species - N.A. <br> (v) PIRED facilities</p>
Datasets regarding agricultural colonisation of riverine islands of Huallaga River, Peru. Shiringal locality
<p>Data</p>
Dataset for Assessing Multi-Dimensional Impacts of Achieving Sustainability Goals by Projecting the Sustainable Agriculture Matrix into the Future
<p>This data repository feeds into the meta-repository setup for post-processing of GCAM-SAM outputs. GitHub link of meta-repository is: <a href="https://github.com/JGCRI/Kyle-etal_2022_EF">https://github.com/JGCRI/Kyle-etal_2022_EF</a> <br> <br> Folders: <br> <strong>model/</strong> is the static version of the model used to simulate 8 scenarios. See the <a href="https://github.com/pkyle/gcam-core/tree/gpk/paper/sam">GitHub GCAM-SAM repository</a> to follow active development of this model. <br> <strong>inputs/</strong> folder contains input datasets and scripts used to prepare files while postprocessing. This is to be used with <a href="https://github.com/JGCRI/Kyle-etal_2022_EF">GitHub post-processing meta-repository</a>. <br> <strong>outdata/</strong> contains <a href="http://github.com/pkyle/gcam-core/tree/gpk/paper/sam">GCAM-SAM</a> output and <a href="http://github.com/JGCRI/Kyle-etal_2022_EF">post-processed</a> output files used to plot figures. <br> <br> Key files: <br> <em><strong>SAM-matrix.dat</strong></em> is the consolidated GCAM-SAM output. Use <em>proj_load.R</em> in the <a href="https://github.com/JGCRI/Kyle-etal_2022_EF">metarepo</a> to read the file. <br> <em><strong>region_vals.csv</strong></em> has all 8 indicators in all 8 scenarios for years 2020 till 2100 on a 10 year time step. <br> <br> Short introduction to the study:</p> <p>In this paper sustainable agriculture matrix (SAM) is estimated to 2100 using Global Change Analysis Model (GCAM). We model combinatorial variations of yield intensification, dietary shift, and greenhouse gas mitigation scenarios. Findings include scenarios having significant tradeoffs across multiple environmental, economic, and social dimensions. Assessment of these multi-dimensional tradeoffs in a consistent framework improves the quality of information for decision-making.<br> <br> Should you have any questions, feel free to reach out Page Kyle at <a href="mailto:pkyle@pnnl.gov">pkyle@pnnl.gov</a>. </p>
Occurrence patterns of crop-foraging sika deer distribution in an agriculture-forest landscape revealed by nitrogen stable isotopes
<p>Conflicts arising from the consumption of anthropogenic foods by wildlife are increasing worldwide. Conventional tools for evaluating the spatial distribution pattern of large terrestrial mammals that consume anthropogenic foods have various limitations, despite their importance in management to mitigate conflicts. In this study, we examined the spatial distribution pattern of crop-foraging sika deer by performing nitrogen stable isotope analyses of bone collagen. We evaluated whether crop-foraging deer lived closer to agricultural crop fields during the winter and spring, when crop production decreases. We found that female deer in proximity to agricultural crop fields during the winter and spring were more likely to be crop-foraging individuals. Furthermore, the likelihood of crop consumption by females decreased by half as the distance to agricultural crop fields increased to 5-10 km. We did not detect a significant trend in the spatial distribution of crop-foraging male deer. The findings of spatial distribution patterns of crop-foraging female deer will be useful for the establishment of management areas, such as zonation, for efficient removal of them.</p>
Data for: Population genomic insights into invasion success in the polyphagous agricultural pest, Halyomorpha halys
<p>Invasive species are increasingly threatening ecosystems and agriculture by rapidly expanding their range and adapting to environmental and human-imposed selective pressures. The genomic mechanisms that underlie such rapid changes remain unclear, especially for agriculturally important pests. Here<span>,</span> we use genome-wide polymorphisms derived from native, invasive<span>,</span> and intercepted <span>samples and </span>populations of the brown marmorated stink bug (BMSB), <em>Halyomorpha</em> <em>halys</em>, to gain insights into population genomics processes that <span>have promoted</span> the successful global invasion of this polyphagous pest. Our analysis demonstrated that BMSB <span>exhibits spatial</span> structure but admixture rates are high among introduced populations, resulting in similar levels of genomic diversity across native and introduced populations. These spatial genomic patterns suggest a complex invasion scenario<span>, potentially</span> with multiple bridgehead events<span>, posing </span>a challenge for accurately assigning BMSB incursions to their source using reduced-representation genomic data. By associating allele frequencies with the invasion status of BMSB populations, we found significantly differentiated SNPs located in <span>close </span>proximity <span>to</span> genes for insecticide resistance and olfaction. <span>Comparing</span> variations in allele frequencies among populations for outlier SNPs suggests that BMSB invasion success has likely evolved from standing genetic variation. In addition to being a major nuisance of households, BMSB has caused significant economic losses to agriculture in recent years and continues to expand its range. Despite no record of BMSB insecticide resistance to date, our results show <span>high capacity for potential </span>evolution <span>of such characters</span>, highlighting the need for future sustainable and targeted management strategies.</p>
Data from: Eastern Whip-poor-wills have larger nonbreeding home ranges in areas with more agriculture and forest fragmentation
<p>Migratory bird populations can be limited by events in disparate parts of the world. Birds in tropical regions are facing rapid habitat loss, climate change, and intensive agricultural regimes, potentially contributing to population declines. However, an understanding of basic non-breeding ecology of species, such as habitat and space use, is critical for determining if this is the case. Populations of the nocturnal/crepuscular Eastern Whip-poor-will (<em>Antrostomus</em> <em>vociferus</em>) have declined by 70% since the 1960's, yet data on the species are sparse outside of the breeding season. We extracted data from 41 archival GPS tags deployed on whip-poor-wills and estimated non-breeding home ranges and land covers used. We used satellite imagery and stable carbon and nitrogen isotope values from claws grown during the non-breeding season to analyze how land cover and habitat moisture impacted home range size and relative trophic level. Forest was by far the most prevalent land cover used by whip-poor-wills, occurring in all home ranges and accounting for >80% of diurnal roosting points. We found that less forest, the presence of agriculture, and more edge (irrespective of land cover) were associated with larger home ranges. Stable isotope values differed by broadscale ecoregion but not local land cover characteristics in our study, indicating that regional idiosyncrasies or broadscale processes can be more important in determining stable isotope ratios. Our findings suggest that the loss, fragmentation, and replacement of forest by agriculture in the core of the whip-poor-will's non-breeding range may represent a threat to the species, as they rely heavily upon forest, and appear to alter space use in response to changes in forest cover.</p>
Reducing pesticides without organic certification? Potentials and limits of an intermediate form of agricultural production
<p><span>A growing number of farmer cooperatives cultivate crops without chemical pesticides, but also without organic certification. How does this intermediate form of agriculture between conventional and organic production function? What are the outcomes of this production form on cropland biodiversity? How does this model contribute to the transition toward more sustainable forms of agriculture? We address these research questions using original data collected in the AgroBioDiv project from the farmers' cooperative "KraichgauKorn" based in the German State of Baden-Württemberg. This cooperative is a collection of conventional farmers, who refrain from pesticide use during cultivation periods for KraichgauKorn grains, with products being produced without pesticide inputs in the growing season. Our study finds higher levels of weed species biodiversity on KGK cereal fields compared to conventional fields, but lower than organic fields. In addition, more endangered wild species monitored by the State of Baden-Württemberg were found on KGK fields than on conventional fields, with organic fields exhibiting the highest presence of endangered flora. We conclude that such kinds of enterprises may indeed contribute substantially to a successful transformation toward sustainable agricultural systems. </span></p>
Deforestation for agriculture increases microbial carbon use efficiency in subarctic soils
<p>This repository contains all necessary raw data as well as the R code used to conduct statistical analysis and create figures of the publication</p><p> </p><p><strong>Deforestation for agriculture increases microbial carbon use efficiency in subarctic soils</strong></p><p>Julia Schroeder1, Tino Peplau1, Frank Pennekamp2, Edward Gregorich3, Christoph C. Tebbe4, Christopher Poeplau1</p><p>1 Thünen Institute of Climate-Smart Agriculture, Bundesallee 68, 38116 Braunschweig, Germany</p><p>2 Department of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, 8057 Zürich, Switzerland</p><p>3 Research and Development Centre, Central Experimental Farm, Agriculture and Agri-Food Canada, 960 Carling Ave, Ottawa, Ontario K1A 0C6, Canada</p><p>4 Thünen Institute of Biodiversity, Bundesallee 65, 38116 Braunschweig, Germany</p><p>DOI: https://doi.org/10.1007/s00374-022-01669-2 </p><p>This study investigated how and through which pathways deforestation and conversion to agricultural land (i.e. grassland, cropland) alters the microbial carbon use efficiency (CUE) in subarctic soils to allow the development of mitigation strategies to alleviate C losses. We assessed CUE using 18O-labelled water in a paired-plot approach on soils collected from 19 farms across the subarctic region of Yukon, Canada, comprising 14 pairs of forest-to-grassland conversion and 15 pairs of forest-to-cropland conversion. Microbial CUE significantly increased following conversion to grassland and cropland. Land-use conversion resulted in a lower estimated abundance of fungi, while the archaeal abundance increased, as assessed by qPCR. Interestingly, structural equation modelling revealed that increases in CUE were mediated by a rise in soil pH and a decrease in soil C:N ratio rather than by shifts in microbial community composition, i.e. the ratio of fungi, bacteria and archaea. Our findings indicate a direct control of abiotic factors on microbial CUE via improved nutrient availability and facilitated conditions for microbial growth.</p><p>The R code was developed under R v3.6.3 and adapted to work under version R v.4.1.2.</p><p>The repository includes the following files:</p><ul><li>general_soil_parameters_per_site.csv - general soil data assessed on pooled reference forest plot (n=19)</li><li>general_soil_parameters_per_plot.csv - general soil data assessed on pooled replicated field samples (n=48)</li><li>sample_data.csv - data measured for each laboratory sample (n=147)</li></ul><p> </p><ul><li>Land-use change effects on 18O-CUE.Rproj - Rproject (load project to work on provided scripts and data)</li><li>load_data_script.R - loads required data</li><li>Multivariate_normality_script.R - tests for multivariate normaility in dataset</li><li>PCA_script.R - calculates PC1 and 2 of clay mineralogy data to reduce dimensions</li><li>map_Yukon_script.R - create Figure 1</li><li>plot_density_script.R - create Figure 2</li><li>linear_mixed-effects_models_script.R - calculates response ratios</li><li>plot_boxplots_script.R - plot boxplots per land use including compact letter display indicating significant differences, create Figure 3 + 4</li><li>correlogram_script.R - correlation analysis to identify drivers of CUE, create Figure 6</li><li>plot_correlations_script.R - plot drivers of CUE, create Figure 5 + 7</li><li>SEM_script.R - development of structural equation model, create Figure 8</li></ul>
Data from: Classification and mapping of low-statured 'shrubland' cover types in post-agricultural landscapes of the US Northeast
<p>This directory contains data used in the paper "Classification and mapping of low-statured 'shrubland' cover types in<br> post-agricultural landscapes of the US Northeast" published in the journal International Journal of Remote Sensing. No data was collected specifically for this study; instead, we made use of publicly available LiDAR data and LANDSAT imagery.</p>
Literature review of Design in Open Source Agriculture - Images
<p>Literature review of Design in Open Source Agriculture - Images</p> <ol> <li>Fig. 1. Publications by subject areas</li> <li>Fig. 2. Publications by country</li> <li>Fig. 3. Yearly output of publications</li> <li>Fig. 4. Network of co-authorship (generated with VOSviewer) <em>(Extra image not included in the article)</em></li> <li>Fig. 5. Network of co-citation (generated with VOSviewer) <em>(Extra image not included in the article)</em></li> <li>Fig. 6. Network of bibliographic coupling(generated with VOSviewer) <em>(Extra image not included in the article)</em></li> <li>Fig. 7. Co-word analysis: network of terms from title and abstract (generated with VOSviewer) <em>(Extra image not included in the article)</em></li> <li>Fig. 8. Co-word analysis: network of keywords (generated with VOSviewer) <em>(Extra image not included in the article)</em></li> <li>Fig. 9. Thematic Map based on Authors’ keywords (generated with bibliometrix) <em>(Extra image not included in the article)</em></li> <li>Fig. 10. Thematic Map based on Titles (just single words - unigrams) (generated with bibliometrix) <em>(Extra image not included in the article)</em></li> <li>Fig. 11. Thematic Map based on Abstracts (just single words - unigrams) (generated with bibliometrix) <em>(Extra image not included in the article)</em></li> <li>Fig. 12. Trend Topics (generated with bibliometrix) <em>(Extra image not included in the article)</em></li> </ol>
Data from: Smoke-driven changes in photosynthetically active radiation during the U.S. agricultural growing season
<p>Wildfire smoke is frequently present over the U.S. during the agricultural growing season and will likely increase with climate change. Studies of smoke impacts have largely focused on air quality and human health; however, understanding smoke's impact on photosynthetically active radiation (PAR) is essential for predicting how smoke affects plant growth. We compare surface shortwave irradiance and diffuse fraction (DF) on smoke-impacted and smoke-free days from 2006-2020 using data from multifilter rotating shadowband radiometers at ten U.S. Department of Agriculture (USDA) UV-B Monitoring and Research Program stations and smoke plume locations from operational satellite products. On average, 20% of growing season days are smoke-impacted, but smoke prevalence increases over time (r = 0.60, p < 0.05). Smoke presence peaks in the mid- to late growing season (i.e., July, August), particularly over the northern Rocky Mountains, Great Plains, and Midwest. We find an increase in the distribution of PAR DF on smoke-impacted days, with larger increases at lower cloud fractions. On clear-sky days, daily average PAR DF increases by 10 percentage points when smoke is present. Spectral analysis of clear-sky days shows smoke increases DF (average: +45%) and decreases total irradiance (average: -6%) across all six wavelengths measured from 368-870 nm. Optical depth measurements from ground and satellite observations both indicate that spectral DF increases and total spectral irradiance decreases with increasing smoke plume optical depth. Our analysis provides a foundation for understanding smoke's impact on PAR, which carries implications for agricultural crop productivity under a changing climate.</p>
Annual maps of swidden agriculture landscape derived from MODIS vegetation index in northern Laos during 2001-2020
<p>This document (Word) is a brief introduction about the resultant maps of swidden agricultural landscape in northern Laos during 2001-2020 derived from the MODIS13Q1 Normalized Difference Vegetation Index (NDVI) time-series products using a threshold method. For more information about the dataset, one can refer to the paper entitled “Swidden agriculture landscape mapping using MODIS vegetation index time series and its spatio-temporal dynamics in northern Laos” published in Remote Sensing. The format of this dataset (swidden agriculture landscape) is raster (.tif) with an attribute value of 1. It has a spatial resolution of 250m×250m and covers eleven provinces (including Bokeo, Borikhamxay, Huaphanh, Luangnamtha, Luangprabang, Oudomxay, Phongsaly, Vientiane, Xayaboury, Xaysomboon and Xieng-khuang) and one prefecture (Vientiane, Figure 1). The geographic projection is WGS_1984_UTM_Zone_48N.</p>
Data for: Simulating effects of agricultural intensification and climate change: Nitrogen fertilization and drought stress decrease insect herbivore performance
<p>Biodiversity is globally under pressure, and the current decline in insect biomass and diversity is likely caused by human activities. Key drivers of biodiversity loss include agricultural intensification and anthropogenic climate change. Nevertheless, a thorough understanding of potential interactions between both factors and the mechanisms underlying insect declines in general is still lacking.</p> <p>Here, we investigate the combined effects of nitrogen fertilization and drought, as applied to host plants, on the preference and performance of the butterfly <em>Lycaena tityrus</em>.</p> <p>Individuals performed best on plants having received medium nitrogen levels, while performance was reduced by either a lack of or strong fertilization, the former potentially caused by nitrogen limitation and the latter by increased concentrations of toxic allelochemicals. Female oviposition preference though was positively related to nitrogen fertilization, resulting in a mismatch between preference and offspring performance at high nitrogen levels. Plant drought stress additionally reduced herbivore performance, and females appeared to suffer more from low-quality food than males.</p> <p>Our results indicate that increasing nitrogen fertilization, as applied in intensive agriculture, may substantially reduce host-plant quality for insect herbivores, which may be exaggerated in the course of climate change due to the more frequent occurrence of droughts. Our study thus contributes to a better understanding of the mechanisms underlying human-driven insect declines in agricultural landscapes and beyond.</p>
National High-Resolution Cropland Classification of Japan with Agricultural Census Information and Multi-temporal Multi-modality datasets
<p>Multi-modality datasets offer advantages for processing frameworks with complementary information, particularly for large-scale cropland mapping. Extensive training datasets are required to train machine learning algorithms, which can be challenging to obtain. To alleviate the limitations, we extract the training samples from the agricultural census information. We focus on Japan and demonstrate how agricultural census data in 2015 can map different crop types for the entire country. Due to the lack of Sentinel-2 datasets in 2015, this study utilized Sentinel-1 and Landsat-8 collected across Japan and combined observations into composites for different prefecture periods (monthly, bimonthly, seasonal). Recent deep learning techniques have been investigated the performance of the samples from agricultural census information.<br> Finally, we obtain nine crop types on a countrywide scale (around 31 million parcels) and compare our results to those obtained from agricultural census testing samples as well as those obtained from recent land cover products in Japan. The generated map accurately represents the distribution of crop types across Japan and achieves an overall accuracy of 87% for nine classes in 47 prefectures.</p>
Agricultural margins could enhance landscape connectivity for pollinating insects across the Central Valley of California, U.S.A.
<p>One of the defining features of the Anthropocene is eroding ecosystem services as a function of decreases in biodiversity and overall reductions in the abundance of once-common organisms, including many insects that play innumerable roles in natural communities and agricultural systems that support human society. It is now clear that the preservation of insects cannot rely solely on the legal protection of natural areas far removed from the densest areas of human habitation. Instead, a critical challenge moving forward is to intelligently manage areas that include intensively farmed landscapes, such as the Central Valley of California. Here we attempt to meet this challenge with a tool for modeling landscape connectivity for insects (with pollinators in particular in mind) that builds on available information including lethality of pesticides and expert opinion on insect movement. Despite the massive fragmentation of the Central Valley, we find that connectivity is possible, especially utilizing the restoration or improvement of agricultural margins which (in their summed-area) exceed natural areas. Finally, we highlight steps moving forward and the great many knowledge gaps that could be addressed in the field to improve future iterations of our modeling approach.</p>
The influence of inherent soil factors and agricultural management on soil organic matter
<p>The accumulation of soil organic matter (SOM) is vital to the agronomic and environmental functioning of agroecosystems, yet the relative influence of inherent soil properties and agricultural management practices on SOM dynamics are not often addressed in individual studies. Using a network of 218 operating farm fields across Wisconsin and southern Minnesota, USA, this research employs single variable analysis (ANOVA and regression) and regression tree analysis to assess the effects of soil properties (texture, drainage class, pH) and management variables related to crop rotation, tillage, cover cropping, and manure application on SOM, as well as total organic carbon (TOC) and total nitrogen (TN) in the upper 15 cm. Single variable analysis revealed that greater SOM, TOC, and TN were associated with poorly drained soil, tile-drained fields, high-clay content soil, and high biomass crop rotations. Soil organic matter (SOM) and TOC were strongly related (R<sup>2</sup>=0.71), but different regression trees were produced; SOM was most influenced by clay content, while TOC was most influenced by drainage class. Future assessment for the building of SOM or TOC should be conducted with drainage and texture class categories and on a regional basis, given that these factors influence the practices that occur within landscapes. A rapid building of data sets through unstructured sampling, including an abundance of meta-data, should be a research priority in agricultural science to identify practices to build SOM on a regional basis.</p>
ScienceDex guides
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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.