Varying temporal and spatial effects of climate on maize and soybean affect yield prediction

Abstract

ABSTRACT:The relationship between climatic factors and crop yields for maize and soybeans in 3 major producing countries (the United States, Brazil, and China) was analyzed statistically. Temporal changes in the climate−yield relationship were considered, and the temporal and spatial variations were evaluated. County-level data from 1980 to 2006 were collected for each country and allocated to 1.125°× 1.125°grids. Data were analyzed for temporal changes in the effect of climate on yields using the particle filtering method for each grid. The 'current' effect of temperature on crop yields was shown to be geographically symmetric around the optimal temperatures (19.51°C for maize and 20.66°C for soybeans) in the Northern Hemisphere. In the Southern Hemisphere, the 'current' effect of precipitation was more influential than that of temperature. The effects of these climatic factors changed over time. Whereas the negative effect of high temperatures has been mitigated around the corn belt of the United States during the last 3 decades, it has intensified in Brazil, northern China, and the southern United States for maize. Consequently, predicted future yields differed marginally depending on the relationship (past or current effect) used for the prediction, even when they were summarized on country scales. This study suggests that temporal changes in the relationship between weather and crop yields should be considered for better future predictions.

Increasing influence of heat stress on French maize yields from the 1960s to the 2030s

“…Lobell et al ., ), so as to reduce the chances of overfitting on certain parameters, in contrast to other studies (e.g. Sakurai et al ., ). In addition, the choice of technology trend has been much discussed, with many arbitrary assumptions used.…”

“…Schlenker & Roberts, ; Lobell et al ., ), or removed using local linear regression (e.g. Sakurai et al ., ) or first differences (e.g. Nicholls, ).…”

“…For example, the validation statistics of the model were found to be significantly improved if the direct influence of precipitation (β 2 ) varies with time (also see e.g. Sakurai et al ., ), and so this factor was included. However, we also tested versions of the empirical model with higher order terms (such as quadratic in X and P ) and also considered time‐varying β 1 and β 3 , but found that these changes did not improve the empirical relationship significantly (see Supporting Information).…”

“…Although this relative importance will vary regionally (e.g. Sakurai et al ., ), some generalizations may be possible through an analysis of mechanisms. For regions where irrigation is increasing, for example, it seems likely that the sensitivity of yield to rainfall will be decreasing.…”

Soybean production in 2025 and 2050 in the southeastern USA based on the SimCLIM and the CSM-CROPGRO-Soybean models

“…Numerous scientific studies indicate that the climate is changing (Alley et al 2003, IPCC 2007, 2013, Trenberth 2011 and agriculture is vulnerable to the expected change in future climate conditions (Rosenzweig et al 2007, Ainsworth & Ort 2010, Sakurai et al 2011. Several studies have been conducted to determine the vulnerability of soybean production to climate change, including in the southeastern USA where agriculture is a dominant economic sector.…”