Different time windows provide divergent estimates of climate variability and change impacts on maize yield in Northeast China

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Abstract

Maize is the main crop in Northeast China (NEC), but is susceptible to climate variations. Using county-level data from 1980 to 2010, we established multiple linear regression models between detrended changes in maize yield and climate variables at two time windows-whole-season and vegetative and reproductive (V&R) phases. Based on climate change trends, these regression models were used to assess climate variability and change impacts on maize yield in different regions of NEC. The results show that different time windows provide divergent estimates. Climate change over the 31 years induced a 1.3% reduction in maize yield at the time window of whole-season, but an increase of 9.1% was estimated at the time window of V&R phases. The yield improvement is attributed to an increase in minimum temperature at the vegetative phase when the temperatures were much lower than the optimum. Yield fluctuations due to inter-annual climate variability were estimated to be ±9% per year at the time window of V&R phases, suggesting that the impact of climate variability on maize yield is much greater than climate change. Trends in precipitation were not responsible for the yield change, but precipitation anomalies contributed to the yield fluctuations. The impacts of warming on maize yield are regional specific, depending on the local temperatures relative to the optimum. Increase in maximum temperature led to a reduction of maize yield in western NEC, but to an increase in mid-east part of NEC. Our findings highlight the necessity of taking into account the phenological phase when assessing the climate impacts on crop yield, and the importance of buffering future crop production from climate change in NEC.

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APA

Deng, X., Huang, Y., Sun, W., Yu, L., Hu, X., & Wang, S. (2019). Different time windows provide divergent estimates of climate variability and change impacts on maize yield in Northeast China. Sustainability (Switzerland), 11(23). https://doi.org/10.3390/su11236659

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