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Title: Crop yield response to climate change varies with crop spatial distribution pattern

Abstract

The linkage between crop yield and climate variability has been confirmed in numerous studies using statistical approaches. A crucial assumption in these studies is that crop spatial distribution pattern is constant over time. Here, we explore how changes in county-level corn spatial distribution pattern modulate the response of its yields to climate change at the state level over the Contiguous United States. Our results show that corn yield response to climate change varies with crop spatial distribution pattern, with distinct impacts on the magnitude and even the direction at the state level. Corn yield is predicted to decrease by 20~40% by 2050s when considering crop spatial distribution pattern changes, which is 6~12% less than the estimates with fixed cropping pattern. The beneficial effects are mainly achieved by reducing the negative impacts of daily maximum temperature and strengthening the positive impacts of precipitation. Our results indicate that previous empirical studies could be biased in assessing climate change impacts by ignoring the changes in crop spatial distribution pattern. As a result, this has great implications for understanding the increasing debates on whether climate change will be a net gain or loss for regional agriculture.

Authors:
 [1]; ORCiD logo [1]
  1. Pacific Northwest National Lab. (PNNL), College Park, MD (United States)
Publication Date:
Research Org.:
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1363996
Report Number(s):
PNNL-SA-125055
Journal ID: ISSN 2045-2322; KP1703030
Grant/Contract Number:  
AC05-76RL01830
Resource Type:
Accepted Manuscript
Journal Name:
Scientific Reports
Additional Journal Information:
Journal Volume: 7; Journal Issue: 1; Journal ID: ISSN 2045-2322
Publisher:
Nature Publishing Group
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; climate-change impacts; environmental impact

Citation Formats

Leng, Guoyong, and Huang, Maoyi. Crop yield response to climate change varies with crop spatial distribution pattern. United States: N. p., 2017. Web. doi:10.1038/s41598-017-01599-2.
Leng, Guoyong, & Huang, Maoyi. Crop yield response to climate change varies with crop spatial distribution pattern. United States. https://doi.org/10.1038/s41598-017-01599-2
Leng, Guoyong, and Huang, Maoyi. Wed . "Crop yield response to climate change varies with crop spatial distribution pattern". United States. https://doi.org/10.1038/s41598-017-01599-2. https://www.osti.gov/servlets/purl/1363996.
@article{osti_1363996,
title = {Crop yield response to climate change varies with crop spatial distribution pattern},
author = {Leng, Guoyong and Huang, Maoyi},
abstractNote = {The linkage between crop yield and climate variability has been confirmed in numerous studies using statistical approaches. A crucial assumption in these studies is that crop spatial distribution pattern is constant over time. Here, we explore how changes in county-level corn spatial distribution pattern modulate the response of its yields to climate change at the state level over the Contiguous United States. Our results show that corn yield response to climate change varies with crop spatial distribution pattern, with distinct impacts on the magnitude and even the direction at the state level. Corn yield is predicted to decrease by 20~40% by 2050s when considering crop spatial distribution pattern changes, which is 6~12% less than the estimates with fixed cropping pattern. The beneficial effects are mainly achieved by reducing the negative impacts of daily maximum temperature and strengthening the positive impacts of precipitation. Our results indicate that previous empirical studies could be biased in assessing climate change impacts by ignoring the changes in crop spatial distribution pattern. As a result, this has great implications for understanding the increasing debates on whether climate change will be a net gain or loss for regional agriculture.},
doi = {10.1038/s41598-017-01599-2},
journal = {Scientific Reports},
number = 1,
volume = 7,
place = {United States},
year = {Wed May 03 00:00:00 EDT 2017},
month = {Wed May 03 00:00:00 EDT 2017}
}

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Cited by: 52 works
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