Tack Jesse, Barkley Andrew, Nalley Lawton Lanier
Department of Agricultural Economics, Mississippi State University, Mississippi State, MS 39762;
Department of Agricultural Economics, Kansas State University, Manhattan, KS 66506; and.
Proc Natl Acad Sci U S A. 2015 Jun 2;112(22):6931-6. doi: 10.1073/pnas.1415181112. Epub 2015 May 11.
Climate change is expected to increase future temperatures, potentially resulting in reduced crop production in many key production regions. Research quantifying the complex relationship between weather variables and wheat yields is rapidly growing, and recent advances have used a variety of model specifications that differ in how temperature data are included in the statistical yield equation. A unique data set that combines Kansas wheat variety field trial outcomes for 1985-2013 with location-specific weather data is used to analyze the effect of weather on wheat yield using regression analysis. Our results indicate that the effect of temperature exposure varies across the September-May growing season. The largest drivers of yield loss are freezing temperatures in the Fall and extreme heat events in the Spring. We also find that the overall effect of warming on yields is negative, even after accounting for the benefits of reduced exposure to freezing temperatures. Our analysis indicates that there exists a tradeoff between average (mean) yield and ability to resist extreme heat across varieties. More-recently released varieties are less able to resist heat than older lines. Our results also indicate that warming effects would be partially offset by increased rainfall in the Spring. Finally, we find that the method used to construct measures of temperature exposure matters for both the predictive performance of the regression model and the forecasted warming impacts on yields.
气候变化预计会使未来气温升高,这可能导致许多关键产区的作物产量下降。量化天气变量与小麦产量之间复杂关系的研究正在迅速增加,最近的进展采用了各种模型规格,这些规格在统计产量方程中纳入温度数据的方式上有所不同。利用一个独特的数据集,该数据集将1985 - 2013年堪萨斯州小麦品种田间试验结果与特定地点的天气数据相结合,通过回归分析来研究天气对小麦产量的影响。我们的结果表明,在9月至次年5月的生长季节中,温度暴露的影响各不相同。产量损失的最大驱动因素是秋季的低温和春季的极端高温事件。我们还发现,即使考虑到减少低温暴露的益处,变暖对产量的总体影响仍是负面的。我们的分析表明,不同品种的平均(均值)产量与抗极端高温能力之间存在权衡。与旧品种相比,最近发布的品种抗热能力较弱。我们的结果还表明,春季降雨量增加将部分抵消变暖的影响。最后,我们发现用于构建温度暴露指标的方法,对于回归模型的预测性能以及预测的变暖对产量的影响都很重要。