d347ed22-2b57-4dce-88e3-31a4d00d4358 English ISO/IEC 8859-1 (also known as Latin 1) dataset dataset NERC EDS Environmental Information Data Centre Lancaster Environment Centre, Library Avenue, Bailrigg Lancaster LA1 4AP UK info@eidc.ac.uk https://eidc.ac.uk/ EIDC website The Environmental Information Data Centre (EIDC) is the UK's national data centre for terrestrial and freshwater sciences. information pointOfContact 2025-11-13T16:17:17 UK GEMINI 2.3 WGS 84 Yield Constraint Score (YCS) for the effect of five crop stresses on global production of four staple food crops 2020-07-20 publication https://catalogue.ceh.ac.uk/id/d347ed22-2b57-4dce-88e3-31a4d00d4358 10.5285/d347ed22-2b57-4dce-88e3-31a4d00d4358 doi: Sharps, K., Mills, G., Simpson, D., Pleijel, H., Frei, M., Burkey, K., Emberson, L., Uddling, J., Broberg, M., Feng, Z., Kobayashi, K., Agrawal, M. (2020). Yield Constraint Score (YCS) for the effect of five crop stresses on global production of four staple food crops. NERC Environmental Information Data Centre 10.5285/d347ed22-2b57-4dce-88e3-31a4d00d4358 A Yield Constraint Score (YCS; scale of 1-5) was developed for the effect of five key crop stresses (ozone, pests and diseases, soil nutrients, heat stress and aridity) on the production of the crops maize (Zea mays), rice (Oryza sativa), soybean (Glycine max) and wheat (Triticum aestivum). Data are on a global scale at 1 deg by 1deg resolution, based on the distribution of production for each crop, according to the Food and Agriculture Organisation’s (FAO) Global Agro-Ecological Zones (GAEZ) crop production data for the year 2000. To derive the YCS for each crop stress, spatial data on a global scale were gathered. Modelled ozone data (2010-2012) were derived from the EMEP MSC-W (European Monitoring and Evaluation Programme, Meteorological Synthesising Centre-West) chemical transport model (version 4.16). Pests and diseases data (2002-2004) were downloaded from a Centre for Agriculture and Biosciences International (CABI) database providing estimates for pre-harvest crop losses due to weeds, animal, pathogens and viruses, compiled from the literature. Soil nutrient classifications (for 2009, derived using soil attributes from the Harmonized World Soil Database (HWSD)) were downloaded from the GAEZ data portal. A heat stress index was calculated using daily temperature data (1990-2014) to determine whether the temperature within a 30-day thermal-sensitive period exceeded crop tolerance thresholds. Global Aridity Index data (1950-2000) were downloaded from the Consultative Group for International Agricultural Research’s Consortium for Spatial Information (CGIAR-CSI). The Yield Constraint Score provides an indication of where each stress is predicted to be affecting crop yield globally and the magnitude of the effect. The YCS data were developed as part of the NERC funded SUNRISE project and the National Capability Project NC-Air quality impacts on food security, ecosystems and health. Full details about this dataset can be found at https://doi.org/10.5285/d347ed22-2b57-4dce-88e3-31a4d00d4358 Sharps, K. UK Centre for Ecology & Hydrology enquiries@ceh.ac.uk author Mills, G. UK Centre for Ecology & Hydrology enquiries@ceh.ac.uk author Simpson, D. EMEP MSC‐W, Norwegian Meteorological Institute EMAIL NOT PROVIDED https://orcid.org/0000-0001-9538-3208 ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information author Pleijel, H. University of Gothenburg EMAIL NOT PROVIDED https://orcid.org/0000-0002-6975-5984 ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information author Frei, M. Institute of Crop Science and Resource Conservation, University of Bonn EMAIL NOT PROVIDED https://orcid.org/0000-0002-2474-6558 ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information author Burkey, K. Agricultural Research Service EMAIL NOT PROVIDED author Emberson, L. Stockholm Environment Institute at York EMAIL NOT PROVIDED https://orcid.org/0000-0003-3463-0054 ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information author Uddling, J. University of Gothenburg EMAIL NOT PROVIDED author Broberg, M. University of Gothenburg EMAIL NOT PROVIDED https://orcid.org/0000-0001-5370-4894 ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information author Feng, Z. State Key Laboratory of Urban and Regional Ecology EMAIL NOT PROVIDED author Kobayashi, K. University of Tokyo EMAIL NOT PROVIDED author Agrawal, M. Institute of Science, Banaras Hindu University EMAIL NOT PROVIDED author NERC EDS Environmental Information Data Centre info@eidc.ac.uk custodian NERC Environmental Information Data Centre info@eidc.ac.uk publisher Sharps, K. UK Centre for Ecology & Hydrology enquiries@ceh.ac.uk https://orcid.org/0000-0003-3265-1505 ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information pointOfContact Environmental Monitoring Facilities theme GEMET - INSPIRE themes, version 1.0 2008-06-01 publication Zea mays Oryza sativa Triticum aestivum Glycine max Wikidata 2012-10-29 creation Agriculture Soil Sunrise otherRestrictions no limitations otherRestrictions This resource is available under the terms of the Open Government Licence otherRestrictions © UK Centre for Ecology & Hydrology otherRestrictions © Norwegian Meteorological Institute otherRestrictions © University of Bonn otherRestrictions © Stockholm Environment Institute at York otherRestrictions © University of Gothenburg otherRestrictions © The University of Tokyo otherRestrictions © Banaras Hindu University otherRestrictions If you reuse this data, you should cite: Sharps, K., Mills, G., Simpson, D., Pleijel, H., Frei, M., Burkey, K., Emberson, L., Uddling, J., Broberg, M., Feng, Z., Kobayashi, K., Agrawal, M. (2020). Yield Constraint Score (YCS) for the effect of five crop stresses on global production of four staple food crops. NERC Environmental Information Data Centre https://doi.org/10.5285/d347ed22-2b57-4dce-88e3-31a4d00d4358 vector 100000 English utf8 climatologyMeteorologyAtmosphere 1950-01-01 2014-12-31 -180 180 -90 90 Shapefile NERC EDS Environmental Information Data Centre info@eidc.ac.uk distributor https://data-package.ceh.ac.uk/data/d347ed22-2b57-4dce-88e3-31a4d00d4358 Download the data Download a copy of this data download https://data-package.ceh.ac.uk/sd/d347ed22-2b57-4dce-88e3-31a4d00d4358.zip Supporting information Supporting information available to assist in re-use of this dataset information dataset dataset Commission Regulation (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services 2010-12-08 A 1° by 1° resolution grid was created using ArcMap. Crop production data (0.0833° resolution) from the Food and Agriculture Organisation’s (FAO) Global Agro-Ecological Zones (GAEZ) dataset (for the year 2000) was downloaded for maize, rice, soybean and wheat. For each crop, total production was summed per 1° by 1° grid cell. Then average production for the period 2010-2012 for each grid cell was estimated using a conversion factor from FAO national crop production data, based on the difference between average production for the period 1999-2001 and 2010-2012. For each crop, only grid cells with >500 tonnes crop production were included when mapping the Yield Constraint Score (YCS). Modelled ozone data (2010-2012) were derived from the EMEP MSC-W (European Monitoring and Evaluation Programme, Meteorological Synthesising Centre-West) chemical transport model (version 4.16). Percentage yield loss per grid cell was calculated using the ozone dose-response relationship for wheat, following the most recent methodology adopted by the Convention for Long-Range Transboundary Air Pollution (CLRTAP) in 2017. Pests and diseases data (2002-2004) were downloaded from a Centre for Agriculture and Biosciences International (CABI) database providing estimates for pre-harvest crop losses due to weeds, animal, pathogens and viruses, compiled from the literature. Soil nutrient classifications (for 2009, derived using soil attributes from the Harmonized World Soil Database (HWSD)) were downloaded from the GAEZ data portal. A heat stress index was calculated using daily temperature data from the European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (ECMWF) for 1990-2014 to determine whether the temperature within a 30-day thermal-sensitive period exceeded crop tolerance thresholds. Global Aridity Index data (1950-2000) were downloaded from the Consultative Group for International Agricultural Research’s Consortium for Spatial Information (CGIAR-CSI). For ozone and pests, crop yield loss data was used to derive the YCS on a scale of 1-5, with 1 = 0-5% loss; 2 = 5- 10% loss; 3 = 10-25% loss; 4 = 25-40% loss; 5 = >40% loss. Percentage yield loss data was not available for the other 3 crop stresses, therefore categorical classes were used to designate the YCS from 1 (No/very little stress) – 5 (severe stress). The highest yield loss class (>40%) was expected to be comparable to severe stress (i.e. YCS = 5) for all yield constraints. YCS values for each crop stress, and the total YCS (i.e. sum of the score for all stresses) were added to the 1° by 1° resolution grid and saved as GIS shapefiles, with one file per crop. Full detail on the methodology used to obtain data for each crop stress is available in the Supporting Information for this dataset.