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100 results for “agricultural land”
Dancing bees evaluate central urban forage resources as superior to agricultural land
<p class="ColorfulList-Accent11CxSpFirst">Recent evidence suggests that flower-rich areas within cities could play an important role in pollinator conservation, but direct comparison of floral resources within agricultural and urban areas has proved challenging to perform over large scales.</p> <p class="ColorfulList-Accent11CxSpMiddle">Here we use the waggle dances of honeybees (<i>Apis mellifera</i> L.) to perform large-scale landscape surveys at heavily urban or agricultural sites for a key pollinator of wild and crop plants. We analyzed 2827 dances that were performed by 20 colonies in SE England.</p> <p class="ColorfulList-Accent11CxSpMiddle">We show that hive median foraging trip distance is consistently lower at urban sites across the entire season. The sucrose content of collected nectar did not significantly differ between urban and agricultural land, ruling out the possibility that longer foraging distances in agricultural sites were driven by distant but nectar-rich resources.</p> <p class="ColorfulList-Accent11CxSpMiddle">Within cities, bees preferentially targeted residential areas on foraging trips, while trips to mass-flowering crops overwhelmingly dominated at agricultural sites. For both land-use types, distances flown increased in the summer, but there was high variation in temporal patterns between individual sites</p> <p class="ColorfulList-Accent11CxSpLast"><i>Policy implications: </i>From the self-reported perspective of a generalist pollinator, forage was easier to find in heavily urbanized areas than in the modern agricultural landscapes that we studied. A focus on continuous spatial and temporal provision within agricultural environments is key to redressing this imbalance.</p>
Data from: Multi-level thresholds of residential and agricultural land use for elk avoidance across the Greater Yellowstone Ecosystem
<p>1. Conversion of land for settlements and agriculture is increasing globally and can influence wildlife space use. However, there is limited research to identify the thresholds of land use change that incur wildlife avoidance, and how these thresholds might vary across levels of selection.</p> <p>2. We evaluated multi-level avoidance thresholds of elk (<em>Cervus canadensis</em>) impacted by residential development and irrigated agriculture across the Greater Yellowstone Ecosystem in Idaho, Montana, and Wyoming. Using GPS data from 765 elk in 21 herds, we estimated habitat selection in relation to development and agriculture at 3 levels (home range selection, within home range selection, and movement path selection). Next, using individual selection covariates and associated measures of land use availability, we used functional-response models to evaluate how selection varied based on availability, and in turn, to estimate avoidance thresholds.</p> <p>3. We found individual and level-specific variation in elk responses to environmental factors. Elk exhibited stronger responses (either selection or avoidance) when selecting home range locations (i.e. second-order selection) than when selecting areas within home ranges (i.e. third-order selection) or selecting movement paths (i.e. fourth order selection). Importantly, elk avoidance of development and agriculture changed as the amount of land in these categories changed. Across all levels of selection, elk exhibited neutral selection for human development at low levels of availability (<1.1–2.2% developed) but avoided areas that were >1.1–2.2% developed. Conversely, elk selected positively for irrigated agriculture at low to moderate levels of availability (<52.0–66.2% agriculture) but exhibited neutral selection in areas that were > 52.0–66.2% agriculture.</p> <p>4. Synthesis and Applications: Elk avoidance of low levels of human development suggests conservation efforts such as restrictions on future development or conservation easements could focus on areas that are still below 2% developed. Additionally, because elk selection was strongest at the landscape scale, conservation actions that are based on information about the overall landscape structure may be most impactful. Our results highlight the importance of understanding variability in wildlife habitat selection at multiple levels, particularly in relation to land use change and highlight how functional response modelling can help inform landscape conservation.</p>
A secure future? Human urban and agricultural land use benefits a flightless island-endemic rail despite climate change
<p class="MsoNormal"><span>Identifying environmental characteristics that limit species' distributions is important for contemporary conservation and inferring responses to future environmental change. The Tasmanian native hen is an island-endemic flightless rail and a survivor of a prehistoric extirpation event. Little is known about the regional-scale environmental characteristics influencing the distribution of native hens, or how their future distribution might be impacted by environmental shifts (e.g., climate change). </span><span>Using a combination of local fieldwork and species distribution modelling, we assess environmental factors shaping the contemporary distribution of the native hen, and project future distribution changes under predicted climate change. We find 37.2% of Tasmania is currently suitable for the native hens, owing to low summer precipitation, low elevation, human-modified vegetation, and urban areas. <span>Moreover</span>, in unsuitable regions, </span><span>urban areas can create 'oases' of habitat, able to support populations with high breeding activity by providing resources and buffering against environmental constraints. Under climate change predictions, </span><span>native hens were predicted to lose only 5% of their occupied range by 2055. We conclude that the species is resilient to climate change and benefits overall from anthropogenic landscape modifications. As such, this constitutes a rare example of a flightless rail to have adapted to human activity.</span></p>
Analysis data for "The effect of agricultural land retirement on pesticide use"
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A secure future? Human urban and agricultural land use benefits a flightless island-endemic rail despite climate change
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Data from: From microbes to mammals: pond biodiversity homogenization across different land-use types in an agricultural landscape
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Agricultural intensification and land use change: assessing country-level induced intensification, land sparing and rebound effect
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Dancing bees evaluate central urban forage resources as superior to agricultural land
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Data from: Multi-level thresholds of residential and agricultural land use for elk avoidance across the Greater Yellowstone Ecosystem
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Soil microbiome dataset from the University of Wisconsin Arlington and Lancaster agricultural research stations and cheese maker and vegetable processor wastewater land application sites
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Effects of land clearing for agriculture on soil organic carbon stocks in drylands: A meta-analysis
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Data from: Agricultural land-use history and restoration impact soil microbial biodiversity
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Data from: Where money grows on trees: a socio-ecological assessment of land use change in an agricultural frontier
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Global Agricultural Land Resources – A High Resolution Suitability Evaluation and Its Perspectives until 2100 under Climate Change Conditions (v2.0)
<p><strong>Agricultural land resources – a global suitability evaluation</strong></p> <p><em>An inventory is required on the changing potentially suitable areas for agriculture under changing climate conditions. Within the context of the GLUES project, researchers at the Ludwig-Maximilians University (LMU) investigated the global agricultural suitability of land under changing climate conditions at high spatial resolution. The growing demand for food, feed, fiber and bioenergy increases pressure on land and causes land use/cover change and trade-offs between different uses of land and ecosystem services. In order to ensure food security, agricultural potentials need to be used more efficiently in the future. Therefore, the agricultural suitability of land are important information e.g. in order to identify todays suitable areas and possible future changes. The potential suitability of todays forested and protected areas can be used to identify possible hotspots of land use/cover change. Therefore, LMU is working on improving the knowledge of global agricultural potentials of land and better understanding the interdependencies between ecological and socio-economic systems which are driving land use/cover change.</em></p> <p><strong>Determining Agricultural Suitability</strong></p> <p>Local climate, soil and topography determine the available energy, water and nutrient supply for agricultural crops and thus their natural suitability. In order to allow for computing the natural agricultural constraints on the globe at 30 arc seconds (1km) spatial resolution, the following high resolution data were applied:</p> <p>Daily data for temperature, precipitation and solar radiation from the global climate model ECHAM5. Soil data comes from the Harmonized World Soil Database (HWSD). Considered soil properties are texture, proportion of coarse fragments and gypsum, base saturation, pH content, organic carbon content, salinity, sodicity. Topography data was applied from the Shuttle Radar Topography Mission (SRTM). Irrigation has strong impact on the crop’s suitability. It is considered on todays irrigated areas as given by the FAO Aquastat Global Maps of Irrigated Areas (GMIA) dataset. The determinant factors are contrasted with the crop-specific requirements, using a fuzzy-logic approach. The crop requirements are taken from literature.</p> <p><strong>Agricultural Suitability</strong></p> <p>General agricultural suitability at a spatial resolution of 30 arcsec, considering rainfed conditions and irrigation on currently irrigated areas. The agricultural suitability represents for each pixel the maximum suitability value of the considered 16 plants. The dataset contains four time periods (1961-1990, 1981-2010, 2011-2040, 2071-2100).</p> <p><strong>Suitability Change due to Climate until 2100</strong></p> <p>Change in agricultural suitability and crop suitability due to climate change for SRES A1B scenario conditions for 16 crops between 1981-2010 and 2071-2100 at a spatial resolution of 30 arcsec.</p> <p><strong>Multiple Cropping</strong></p> <p>Potential number of suitable crop cycles for 16 crops at a spatial resolution of 30 arcsec, considering rainfed conditions and irrigation on currently irrigated areas. The dataset contains four time periods (1961-1990, 1981-2010, 2011-2040, 2071-2100).</p> <p><strong>Growing Cycle</strong></p> <p>Start of the growing cycle for 16 crops at a spatial resolution of 30 arcsec, considering rainfed conditions and irrigation on currently irrigated areas. In case of multiple cropping, the start of the first growing cycle is shown. The dataset contains four time periods (1961-1990, 1981-2010, 2011-2040, 2071-2100).</p> <p><strong>Further information</strong></p> <p>Detailled information are available in the following publication:<br> Zabel F., Putzenlechner B., Mauser W. (2014): <strong>Global agricultural land resources – a high resolution suitability evaluation and its perspectives until 2100 under climate change conditions. </strong> Online available: <a href="http://dx.plos.org/10.1371/journal.pone.0107522">PLOS ONE</a>. DOI: 10.1371/journal.pone.0107522</p> <p><strong>Improvements in v2.0</strong></p> <p>Compared to previous versions, v2.0 uses updated input data for soil and minor improvements of the statistical downscaling and the bias correction of the climate model data.</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>
Permeability of Neotropical agricultural lands to a key native ungulate – are well-connected forests important?
<p>Much of what remains of the Earth's tropical forests is embedded within agricultural landscapes, where forest is reduced and fragmented. As native forest ungulates are critical to maintaining forest function, it is imperative to understand how this functional group responds to declines in forest cover and connectivity resulting from agricultural expansion. We addressed this issue by evaluating selection of forest cover and forest connectivity by a key native ungulate of Neotropical forests, the white-lipped peccary (<i>Tayassu pecari </i>Link 1795<i>, </i>Tayassuidae, Cetartiodactyla), in agricultural landscapes of Brazil. We evaluated selection using compositional analysis at two hierarchical levels, landscape and home range. From 2013 to 2019, we GPS-tracked eight white-lipped peccary herds in Southwest Brazil, resulting in a total of 14,460 GPS locations. We found that herds can live in landscapes with a wide range of forest cover (35-81% of home ranges covered by native forest), with significant, but not strong, selection at the landscape level (p = 0.045). Nevertheless, herds strongly select for forest cover within their home ranges (81-97% of locations within native forest; highly significant selection at the home-range level: p = 0.008). As for connectivity, herds significantly select the largest, most connected forest fragments at the landscape level (p=0.04), but not at the home-range level (p=0.07). Our results support that Neotropical forests within agricultural landscapes need to be well-connected in order to preserve this key native ungulate, and maintain long-term forest function.</p>
Data from: Beyond plant-soil feedbacks: mechanisms driving plant community shifts due to land-use legacies in post-agricultural forests
Although biotic legacies of past agricultural practices are widespread and increasing in contemporary ecosystems, our understanding of the mechanisms driving such legacies is still poor. Forest understories on former agricultural land show low frequencies and abundance of typical woodland species when compared with ancient forests. These community shifts have been ascribed to the effects of dispersal limitation. A rarely considered mechanism is that post-dispersal processes driven by plant-associated communities determine the poor performance and recruitment of woodland indicators. Given the strong alterations in soil conditions due to former agricultural practices, we hypothesized that (abiotic) plant–soil feedbacks could be a major factor in community shifts. We addressed this hypothesis by comparing plant-associated communities in the soil and above the ground in ancient and post-agricultural alluvial forests; then, we experimentally tested whether the changes in biotic and abiotic soil properties could affect above-ground herbivore abundance and pressure and plant performance. Ancient and post-agricultural communities clearly differed in composition at different levels of the food web. Besides the plant community, we also observed the differences in the microbial and nematode community with increased abundance of root-feeding nematodes in post-agricultural soils. The composition of the above-ground invertebrate community did not differ in ancient and post-agricultural forest parcels; however, plants growing in post-agricultural sites showed higher abundance of invertebrate herbivores and suffered more herbivory. Nutrient analyses of soil and plants showed that increased levels of phosphorus (and to a lesser extent, nitrogen) made plants more nutritious for insect herbivores. Laboratory experiments further pointed to this mechanism as an explanation of the poorer performance of woodland indicators in post-agricultural woodlands. Our results point to biotic and abiotic plant–soil feedbacks coupled with herbivory as a new mechanism to explain the legacy effects in temperate forests. The modification of the below-ground community and soil abiotic characteristics by previous agricultural activity affects not only the plant growth but also the plant nutrient content in the compared understorey species, making them more susceptible to above-ground herbivory. Our results provide one of the first examples of integrating plant–soil feedback and above- and below-ground interactions to explain land-use legacies.
Data from: Flower resource and land management drives hoverfly communities and bee abundance in semi-natural and agricultural grasslands
1. Pollination is a key ecosystem service, and appropriate management, particularly in agricultural systems, is essential to maintain a diversity of pollinator guilds. However, management recommendations frequently focus on maintaining plant communities, with the assumption that associated invertebrate populations will be sustained. 2. We tested whether plant community, flower resources and soil moisture would influence hoverfly (Syrphidae) abundance and species richness in floristically-rich semi-natural and floristically-impoverished agricultural grassland communities in Wales (U.K.), and compared these to two Hymenoptera genera, Bombus and Lasioglossum. Interactions between environmental variables were tested using generalised linear modelling, and hoverfly community composition examined using canonical correspondence analysis. 3. There was no difference in hoverfly abundance, species richness, or bee abundance, between grassland types. There was a positive association between hoverfly abundance, species richness and flower abundance in unimproved grasslands. However, this was not evident in agriculturally improved grassland, possibly reflecting intrinsically low flower resource in these habitats, or the presence of plant species with low or relatively inaccessible nectar resources. There was no association between soil moisture content and hoverfly abundance or species richness. 4. Hoverfly community composition was influenced by agricultural improvement and the amount of flower resource. Hoverfly species with semi-aquatic larvae were associated with both semi-natural and agricultural wet grasslands, possibly because of localised larval habitat. Despite the absence of differences in hoverfly abundance and species-richness, distinct hoverfly communities are associated with marshy grasslands, agriculturally improved marshy grasslands and unimproved dry grasslands, but not with improved dry grasslands. 5. Grassland plant community cannot be used as a proxy for pollinator community. Management of grasslands should aim to maximise the pollinator feeding resource, as well as maintain plant communities. Retaining waterlogged ground may enhance the number of hoverflies with semi-aquatic larvae.
Data from: Breeding bird species diversity across gradients of land use from forest to agriculture in Europe
Loss, fragmentation and decreasing quality of habitats have been proposed as major threats to biodiversity world-wide, but relatively little is known about biodiversity responses to multiple pressures, particularly at very large spatial scales. We evaluated the relative contributions of four landscape variables (habitat cover, diversity, fragmentation and productivity) in determining different components of avian diversity across Europe. We sampled breeding birds in multiple 1-km2 landscapes, from high forest cover to intensive agricultural land, in eight countries during 2001−02. We predicted that the total diversity would peak at intermediate levels of forest cover and fragmentation, and respond positively to increasing habitat diversity and productivity; forest and open-habitat specialists would show threshold conditions along gradients of forest cover and fragmentation, and respond positively to increasing habitat diversity and productivity; resident species would be more strongly impacted by forest cover and fragmentation than migratory species; and generalists and urban species would show weak responses. Measures of total diversity did not peak at intermediate levels of forest cover or fragmentation. Rarefaction-standardized species richness decreased marginally and linearly with increasing forest cover and increased non-linearly with productivity, whereas all measures increased linearly with increasing fragmentation and landscape diversity. Forest and open-habitat specialists responded approximately linearly to forest cover and also weakly to habitat diversity, fragmentation and productivity. Generalists and urban species responded weakly to the landscape variables, but some groups responded non-linearly to productivity and marginally to habitat diversity. Resident species were not consistently more sensitive than migratory species to any of the landscape variables. These findings are relevant to landscapes with relatively long histories of human land-use, and they highlight that habitat loss, fragmentation and habitat-type diversity must all be considered in land-use planning and landscape modeling of avian communities.
Agricultural land use (raster) : National-scale crop type maps for Germany from combined time series of Sentinel-1, Sentinel-2 and Landsat data (2017 to 2021)
<p>The dataset contains maps of the main classes of agricultural land use (dominant crop types and other land use types) in Germany, which are produced annually at the Thünen Institute beginning with the year 2017 on the basis of satellite data. The maps cover the entire open landscape, i.e., the agriculturally used area (UAA) and e.g., uncultivated areas. The map was derived from time series of Sentinel-1, Sentinel-2, Landsat 8 and additional environmental data. Map production is based on the methods described in <a href="https://doi.org/10.1016/j.rse.2021.112831">Blickensdörfer et al. (2022)</a>.</p> <p>All optical satellite data were managed, pre-processed and structured in an analysis-ready data (ARD) cube using the open-source software <a href="https://force-eo.readthedocs.io/en/latest/">FORCE </a>- Framework for Operational Radiometric Correction for Environmental monitoring (Frantz, D., 2019), in which SAR and environmental data were integrated.</p> <p>The map extent covers all areas in Germany that are defined in the respective year as cropland, grassland, small woody features, heathland, peatland or unvegetated areas according to ATKIS Basis-DLM (Geobasisdaten: © GeoBasis-DE / BKG, 2020). </p> <p>Version v201:<br>Post-processing of the maps included a sieve filter as well as a ruleset for the reduction of non-plausible areas using the Basis-DLM and the digital terrain model of Germany (Geobasisdaten: © GeoBasis-DE / BKG, 2015).</p> <p>Version v202:<br>Additional post-processing was performed to detect and mask additional non-plausible areas that were not adequately covered by the first post-processing (e.g., areas with sparse vegetation, montane forests) based on the „Ökosystematlas Deutschland“ (© Statistisches Bundesamt, Deutschland, 2024). As a consequence, the current version includes a new class “Small woody features on other land”. Furthermore, the class "permanent grassland" was refined. Each pixel that was classified as "cultivated grassland" in at least five years (between 2017 and 2022) was translated to "permanent grassland" in the annual maps.</p> <p>The maps are available as cloud optimized GeoTiffs, which makes downloading the full dataset optional. All data can directly be accessed in QGIS, R, Python or any supported software of your choice using the provided URL to the datasets (right click on the respective data set --> “copy link address”). By doing so the entire map area or only the regions of interest can be accessed. QGIS legend files for data visualization can be downloaded separately.</p> <p>Class-specific accuracies for each year are provided in the respective tables. We provide this dataset "as is" without any warranty regarding the accuracy or completeness and exclude all liability. </p> <p> </p> <p><strong>References:<br></strong><br><em>Blickensdörfer, L., Schwieder, M., Pflugmacher, D., Nendel, C., Erasmi, S., & Hostert, P. (2022). Mapping of crop types and crop sequences with combined time series of Sentinel-1, Sentinel-2 and Landsat 8 data for Germany. Remote Sensing of Environment, 269, 112831.</em></p> <p><em>BKG, Bundesamt für Kartographie und Geodäsie (2015). Digitales Geländemodell Gitterweite 10 m. DGM10. https://sg.geodatenzentrum.de/web_public/gdz/dokumentation/deu/dgm10.pdf (last accessed: 28. April 2022).</em></p> <p><em>BKG, Bundesamt für Kartographie und Geodäsie (2020). Digitales Basis-Landschaftsmodell. </em><br><em>https://sg.geodatenzentrum.de/web_public/gdz/dokumentation/deu/basis-dlm.pdf (last accessed: 28. April 2022).</em></p> <p><em>Frantz, D. (2019). FORCE—Landsat + Sentinel-2 Analysis Ready Data and Beyond. Remote Sensing, 11, 1124.</em></p> <p><em>Statistisches Bundesamt, Deutschland (2024). Ökosystematlas Deutschland <br>https://oekosystematlas-ugr.destatis.de/ (last accessed: 08.02.2024).</em></p> <p>___________________________________________________________________________<br>National-scale crop type maps for Germany from combined time series of Sentinel-1, Sentinel-2 and Landsat data (2017 to 2021) © 2024 by Schwieder, Marcel; Tetteh, Gideon Okpoti; Blickensdörfer, Lukas; Gocht, Alexander; Erasmi, Stefan; licensed under CC BY 4.0. </p> <p>Funding was provided by the German Federal Ministry of Food and Agriculture as part of the joint project “Monitoring der biologischen Vielfalt in Agrarlandschaften” (<a href="https://www.agrarmonitoring-monvia.de/en/">MonViA</a>, Monitoring of biodiversity in agricultural landscapes).</p> <p>The study was financially supported by the European Environment Agency and the European Union’s Horizon Europe Research and Innovation programme under Grant Agreement No 101060423 (LAMASUS).</p>
Is switchgrass good for carbon savings? Long-term results in marginal land Running title: Switchgrass SOC storage capacity in marginal land Walter Zegada-Lizarazu 1, Federica Zanetti 1, Nicola Di Virgilio 2, Andrea Monti 1 1Department of Agricultural and Food Sciences, University of Bologna, Viale G. Fanin 44 – 40127, Bologna, Italy; 2CNR, Institute for the BioEcononomy, National Research Council of Italy, Via P Gobetti 101, I-40129 Bologna, Italy
<p>Growing switchgrass in marginal land can be a valuable option to mitigate the risk of agricultural land abandonment whilst storing a significant amount of soil C. It was found a significant increase in SOC in a 13-years period. A significant positive correlation was observed between the C derived from switchgrass and SOC gain (the estimated switchgrass derived C was 12.7 Mg C ha<sup>-1</sup>). The increased SOC along the field, however, was patchy, with the highest increments registered in the center of the field, while the lowest ones in the top and bottom of the hill.</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.