Estimated parameters of the model of growth rate.

Predictions from process-based crop models have suggested that shorter growing seasons due to increases in temperature will lead to reductions in crop yields. However, a study to assess this relationship using statistical data would not be sufficient. In this study, a statistical analysis was carried out using historical crop calendar data and yield data for common buckwheat (Fagopyrum esculentum) to investigate how increased temperature affects crop yields through changes in the growing season. First, the parameters of the model representing the relationship between weather and growth rate were estimated using crop calendar data in Japan. Second, the relationship between climate factors and yield was estimated using the generalized additive model. We then examined how rising temperatures under future weather conditions would affect yield through changes in buckwheat growth rate. The results suggested that integrated solar radiation before flowering had a negative effect on buckwheat yield, while integrated solar radiation after flowering had a positive effect on yield. It was suggested that the growth rate of buckwheat was faster at higher temperatures and slower at longer day lengths. Under future climate conditions, higher temperatures and shorter pre-flowering periods were predicted to result in longer post-flowering day lengths and more integrated post-flowering solar radiation due to a longer post-flowering growing season. As a result, the increase in growth rate due to increased temperatures had a positive effect on yield outweighed the slight negative effect of the temperature increase after flowering. Based on historical statistical data, this study analyzed the complex effects of phenology changes due to increased temperature on crop yields, and similar analyses are expected to be conducted for other crops in the future.基于过程的作物模型（process-based crop models）的预测结果显示，气温升高导致的生育期缩短会造成作物产量下降。然而，仅通过统计数据评估这一关联并不充分。本研究针对普通荞麦（Fagopyrum esculentum），利用历史作物物候历数据与产量数据开展统计分析，以探究气温升高如何通过生育期变化影响作物产量。首先，借助日本的作物物候历数据，估算出表征气象条件与生长速率之间关联的模型参数；其次，采用广义加性模型（generalized additive model）估算气候因子与产量之间的关联。随后，我们分析了未来气候情景下，气温升高如何通过改变荞麦生长速率对产量产生影响。研究结果表明，开花前累积太阳辐射对荞麦产量具有负向影响，而开花后累积太阳辐射则对产量产生正向影响。荞麦的生长速率随气温升高而加快，随日照时长增加而减缓。在未来气候情景中，更高的气温与更短的开花前生育期，将因开花后生育期延长，导致开花后日照时长更长、开花后累积太阳辐射总量更高。最终，气温升高带来的生长速率提升对产量的正向影响，超过了开花后气温升高所产生的轻微负向影响。本研究基于历史统计数据，分析了气温升高引发的物候学（phenology）变化对作物产量的复杂影响，未来有望针对其他作物开展同类分析。