2016
DOI: 10.1088/1748-9326/11/9/094021
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Drought effects on US maize and soybean production: spatiotemporal patterns and historical changes

Abstract: Maximizing agricultural production on existing cropland is one pillar of meeting future global food security needs. To close crop yield gaps, it is critical to understand how climate extremes such as drought impact yield. Here, we use gridded, daily meteorological data and county-level annual yield data to quantify meteorological drought sensitivity of US maize and soybean production from 1958 to 2007. Meteorological drought negatively affects crop yield over most US crop-producing areas, and yield is most sen… Show more

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Cited by 237 publications
(152 citation statements)
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“…Although drought is considered to be a major problem in soybean production worldwide [4345], ERA1 homologs in soybean have not been reported to date. Therefore, we searched the Soybean Knowledge Base (SoyKB, http://soykb.org/) using BlastP program and the amino acid sequence of Arabidopsis ERA1 as query.…”
Section: Resultsmentioning
confidence: 99%
“…Although drought is considered to be a major problem in soybean production worldwide [4345], ERA1 homologs in soybean have not been reported to date. Therefore, we searched the Soybean Knowledge Base (SoyKB, http://soykb.org/) using BlastP program and the amino acid sequence of Arabidopsis ERA1 as query.…”
Section: Resultsmentioning
confidence: 99%
“…Remote sensing indicators have been widely used for forecasting yield and monitoring crop condition (Becker-Reshef et al, 2010;Wardlow et al, 2012;Basso et al, 2013;Bolton and Friedl, 2013;Johnson, 2014;Zipper et al, 2016), often based on statistical regression. Recently there have been initiatives to move toward more physically based crop simulation frameworks for estimating yields (Rosenzweig et al, 2013), culminating in methods that can implemented spatially using gridded datasets (Elliott et al, 2015).…”
Section: Use Of F Ret Time Series In Crop Simulationsmentioning
confidence: 99%
“…Gridded drought indices have been widely used in a variety of systems to identify drought impacts, including tree morbidity and mortality at various spatial scales [43,44], crop yield reductions and crop failures [45], forest fires [46,47], and decreased vegetation activity [48,49]. The developed …”
Section: Data Use and Applicationmentioning
confidence: 99%