Dataset
Restoring nature at lower food production costs
- Documentation:
- Primary data for the present analysis was derived from open source domains and was compiled through a bottom up approach to provide a global coverage of financial information on costs of agricultural production for ten major crops. Data edit, processing and analysis was conducted with the use of the statistical software R and the package "dplyr".
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Authors/Creators
+ Wellcome Trust
More from this funder
- Funder identifier:
- http://dx.doi.org/10.13039/100004440
- Funding agency for:
- Vittis, Y
- Grant:
- 205212/Z/16/Z
- Programme:
- Our Planet Our Health Programme
- Publisher:
- University of Oxford
- Publication date:
- 2020
- Spatial coverage:
- Global coverage, per country, for 151 countries.
- Digital size:
- 650MB
- File format:
- .csv
- Digital storage location:
- In the present study, existing data has been used to conduct the analysis. For biophysical information data and corresponding source is listed bellow: -Attainable yields and corresponding nutrient requirements were derived from the established global gridded crop model EPIC-IIASA (Williams JR, Jones CA, Kiniry JR, Spanel DA. The EPIC crop growth model. Trans ASAE. 1989;32(2):497–0511., Izaurralde RC, Williams JR, McGill WB, Rosenberg NJ, Jakas MCQ. Simulating soil C dynamics with EPIC: Model description and testing against long-term data. Ecol Model. 2006 Feb 25;192(3):362–84.) - Current yields and harvested area were derived from SPAM 2010 v1.1 (International Food Policy Research Institute. Global Spatially-Disaggregated Crop Production Statistics Data for 2010 Version 1.1 [Internet]. Harvard Dataverse; 2019 [cited 2020 Apr 1]. Available from: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/PRFF8V) - Optimal cropland extent (Folberth C, Khabarov N, Balkovič J, Skalský R, Visconti P, Ciais P, et al. The global cropland-sparing potential of high-yield farming. Nat Sustain. 2020 Apr;3(4):281–9.) - Soil characteristics (Fischer G, Nachtergaele FO, Prieler S, Teixeira E, Toth G, van Velthuizen H, et al. Global Agro-ecological Zones (GAEZ v3.0)- Model Documentation [Internet]. Laxenburg, Austria; Rome, Italy: IIASA, Laxenburg, Austria and FAO, Rome, Italy.; 2012 [cited 2020 Mar 30]. Available from: http://www.fao.org/soils-portal/soil-survey/soil-maps-and-databases/harmonized-world-soil-database-v12/en/) - Cropland field sizes (Fritz S, See L, McCallum I, You L, Bun A, Moltchanova E, et al. Mapping global cropland and field size. Glob Change Biol. 2015 May 1;21(5):1980–92. ) For financial information data and corresponding source is listed bellow: - Purchasing Power Parity Index (https://data.worldbank.org/indicator/PA.NUS.PPP) - Crop production financial data for: EU countries (https://agridata.ec.europa.eu/extensions/DashboardFarmEconomyFocusCrops/DashboardFarmEconomyFocusCrops.html) USA (https://www.ers.usda.gov/data-products/commodity-costs-and-returns/) India (https://eands.dacnet.nic.in/Cost_of_Cultivation.htm) Russia (https://eng.gks.ru/) - Machinery expenses for crop cultivation, KTBL Process Calculator Plant (https://daten.ktbl.de/vrpflanze/prodverfahren/loadKulturpflanze.action#auswahl)
- Version number:
- Version 1 (Crop commodities)
- DOI:
- Temporal coverage:
- 2000 - 2017
- Data collected:
- 2019-11-01 - 2020-05-01
- Language:
-
English
- Deposit date:
-
2020-09-30
Terms of use
- Copyright date:
- 2020
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