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</script>A global dataset for the projected impacts of climate change on four major crops
AbstractReliable estimates of the impacts of climate change on crop production are critical for assessing the sustainability of food systems. Global, regional, and site-specific crop simulation studies have been conducted for nearly four decades, representing valuable sources of information for climate change impact assessments. However, the wealth of data produced by these studies has not been made publicly available. Here, we develop a global dataset by consolidating previously published meta-analyses and data collected through a new literature search covering recent crop simulations. The new global dataset builds on 8314 simulations from 203 studies published between 1984 and 2020. It contains projected yields of four major crops (maize, rice, soybean, and wheat) in 91 countries under major emission scenarios for the 21st century, with and without adaptation measures, along with geographical coordinates, current temperatures, local and global warming levels. This dataset provides a basis for a comprehensive understanding of the impacts of climate change on crop production and will facilitate the rapidly developing data-driven machine learning applications.
- University of Paris-Saclay France
- University of Illinois at Urbana Champaign United States
- Humboldt-Universität zu Berlin Germany
- University of the West Indies Jamaica
- International Center for Tropical Agriculture Kenya
[SDV.SA]Life Sciences [q-bio]/Agricultural sciences, Data Descriptor, 550, Adaptation to Climate Change in Agriculture, Agricultural engineering, Climate Change and Variability Research, Plant Science, Precipitation, Crop, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Agricultural and Biological Sciences, Engineering, Climate change, Environmental resource management, Global change, [SDV.SA] Life Sciences [q-bio]/Agricultural sciences, Global and Planetary Change, Geography, Ecology, Q, Life Sciences, Forestry, Crop Production, Computer Science Applications, Sustainability, Physical Sciences, Statistics, Probability and Uncertainty, Information Systems, [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], Statistics and Probability, Impacts of Elevated CO2 and Ozone on Plant Physiology, [SDE.MCG]Environmental Sciences/Global Changes, Science, yields, Library and Information Sciences, Environmental science, Education, Meteorology, Biology, Ecology, Evolution, Behavior and Systematics, [SDE.MCG] Environmental Sciences/Global Changes, FOS: Biological sciences, Environmental Science, Crop Yield, Climate Modeling
[SDV.SA]Life Sciences [q-bio]/Agricultural sciences, Data Descriptor, 550, Adaptation to Climate Change in Agriculture, Agricultural engineering, Climate Change and Variability Research, Plant Science, Precipitation, Crop, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Agricultural and Biological Sciences, Engineering, Climate change, Environmental resource management, Global change, [SDV.SA] Life Sciences [q-bio]/Agricultural sciences, Global and Planetary Change, Geography, Ecology, Q, Life Sciences, Forestry, Crop Production, Computer Science Applications, Sustainability, Physical Sciences, Statistics, Probability and Uncertainty, Information Systems, [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], Statistics and Probability, Impacts of Elevated CO2 and Ozone on Plant Physiology, [SDE.MCG]Environmental Sciences/Global Changes, Science, yields, Library and Information Sciences, Environmental science, Education, Meteorology, Biology, Ecology, Evolution, Behavior and Systematics, [SDE.MCG] Environmental Sciences/Global Changes, FOS: Biological sciences, Environmental Science, Crop Yield, Climate Modeling
