Input data to model multiple effects of large-scale deployment of grass in crop-rotations at European scale Input data to model multiple effects of large-scale deployment of grass in crop-rotations at European scale 2024-384-1 Swedish National Data Service Svensk nationell datatjänst Landing page Input data to model multiple effects of large-scale deployment of grass in crop-rotations at European scale Input data to model multiple effects of large-scale deployment of grass in crop-rotations at European scale 2024-384-1 10.1111/gcbb.13015 Englund, Oskar Englund, Oskar P48364-1 Swedish National Data Service Svensk nationell datatjänst Landing page This is the input dataset to a Python script (https://github.com/oskeng/MF-bio-grass) used to model the effects of widespread deployment of grass in rotations with annual crops to provide biomass while remediating soil organic carbon (SOC) losses and other environmental impacts. For more information about the dataset and the study, see the original article: Englund, O., Mola-Yudego, B., Börjesson, P., Cederberg, C., Dimitriou, I., Scarlat, N., Berndes, G. Large-scale deployment of grass in crop rotations as a multifunctional climate mitigation strategy. GCB Bioenergy Usage Notes: The data file (Geopackage) can be opened using standard GIS software, preferably GRASS GIS or QGIS (both open source).This dataset is intended as input to a Python script (https://github.com/oskeng/MF-bio-grass) that must be run from within a GRASS GIS session. The dataset was originally published in DiVA and moved to SND in 2024. This is the input dataset to a Python script (https://github.com/oskeng/MF-bio-grass) used to model the effects of widespread deployment of grass in rotations with annual crops to provide biomass while remediating soil organic carbon (SOC) losses and other environmental impacts. For more information about the dataset and the study, see the original article: Englund, O., Mola-Yudego, B., Börjesson, P., Cederberg, C., Dimitriou, I., Scarlat, N., Berndes, G. Large-scale deployment of grass in crop rotations as a multifunctional climate mitigation strategy. GCB Bioenergy Usage Notes: The data file (Geopackage) can be opened using standard GIS software, preferably GRASS GIS or QGIS (both open source).This dataset is intended as input to a Python script (https://github.com/oskeng/MF-bio-grass) that must be run from within a GRASS GIS session. Datasetet har ursprungligen publicerats i DiVA och flyttades över till SND 2024. Geospatial Software Other Access to data through an external actor. Data are freely accessible. Åtkomst till data via extern aktör. Data är fritt tillgängliga. openAccess Englund, O., Mola-Yudego, B., Börjesson, P., Cederberg, C., Dimitriou, I., Scarlat, N., & Berndes, G. (2023). Large-scale deployment of grass in crop rotations as a multifunctional climate mitigation strategy. GCB Bioenergy, 15, 166–184. https://doi.org/10.1111/gcbb.13015 Englund, O., Mola-Yudego, B., Börjesson, P., Cederberg, C., Dimitriou, I., Scarlat, N., & Berndes, G. (2023). Large-scale deployment of grass in crop rotations as a multifunctional climate mitigation strategy. GCB Bioenergy, 15, 166–184. https://doi.org/10.1111/gcbb.13015 10.1111/gcbb.13015 2023