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• W2901355911 abstract "Raw data underlying the figures in Balmford et al. “The environmental costs and benefits of high-yield farming”. There are eight datasets, covering all farming sector-externality combinations studied in the associated paper. Across all datasets, rows represent a paired measure of yield and externality under a specific farming system or combination of management practices. Where farming sectors produce significant co-products (e.g. dairy systems producing milk and beef), allocated values of externality and yield have also been included. Rice-GHG, Rice-Water and Beef-GHG-empirical comprised of data from multiple published experimental or LCA-based studies. Data for Dairy-GHG, Dairy-N/P/Soil and Beef-GHG-Ruminant were produced using process-based models of dairy or beef farming systems. Wheat-GHG data were sourced from the Agricultural Greenhouse Gas Inventory Research Platform, with additional GHG sources accounted for using the Yara emissions database. Wheat-N data were sourced from Rothamsted’s long-term Broadbalk wheat experiment. Note: Data presented in the published figures for Rice-GHG, Rice-Water, Wheat-GHG, and Beef-GHG-empirical have undergone correction for site effects using generalised linear mixed models. The datasets here contain the raw data only, before modelling has been carried out. Full details of methods are given in the text of the associated paper. Important note: An author correction to the associated article in Nature Sustainability was published on 26 March 2019. As a result, an .xlsx file ('Wheat-GHG.xlsx') that was part of the original dataset uploaded has been replaced with the following file: 'Wheat-GHG - Correction070118.xlsx'." @default.
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• W2901355911 date "2018-11-12" @default.
• W2901355911 modified "2023-10-17" @default.
• W2901355911 title "Research data supporting The environmental costs and benefits of high-yield farming" @default.
• W2901355911 doi "https://doi.org/10.17863/cam.30360" @default.
• W2901355911 hasPublicationYear "2018" @default.
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