Climate change is projected to decrease maize yields due to warmer temperatures and their consequences. Studies using crop growth models (CGMs), however, have predicted that, through a combination of alterations to planting date, flowering time, and maturity, these yield losses can be mitigated or even reversed. Here, we examine three assumptions of such studies: (1) that climate has driven historical phenological trends, (2) that CGM ensembles provide unbiased estimates of yields under high temperatures, and (3) that the effects of temperature on yields are an emergent property of interactions between phenology and environment. We used data on maize phenology from the United States Department of Agriculture, a statistical model of maize hybrid heat tolerance derived from 80 years of public yield trial records across four US states, and outputs of an ensemble of CMIP6 climate models. While planting dates have advanced historically, we found a trend toward later planting dates after 2005 and no trend for silking or maturity, shifting more time into the reproductive period. We then projected maize yields using the historical model and crop calendars devised using three previously proposed adaptation strategies. In contrast to studies using CGMs, our statistical yield model projected severe yield losses under all three strategies. Finally, we projected maize yields accounting for historical genetic variability for heat tolerance, discovering that it was insufficient to overcome the negative effects of projected warming. These projections are driven by greater heat stress exposure under all crop calendars and climate scenarios. Combined with analysis of the internal sensitivities of CGMs to temperature, our results suggest that current projections do not adequately account for the effects of increasing temperatures on maize yields. Climate adaptation in the US Midwest must utilize a richer set of strategies than phenological adaptation, including improvements to heat tolerance and crop diversification.

中文翻译：

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物候适应不足以抵消气候变化引起的美国杂交玉米产量损失


由于气温升高及其后果，预计气候变化将导致玉米产量下降。然而，使用作物生长模型 （CGM） 的研究预测，通过改变种植日期、开花时间和成熟度的组合，可以减轻甚至逆转这些产量损失。在这里，我们研究了此类研究的三个假设：（1） 气候推动了历史物候趋势，（2） CGM 集合提供了高温下产量的无偏估计，以及 （3） 温度对产量的影响是物候与环境之间相互作用的新兴特性。我们使用了来自美国农业部的玉米物候数据、来自美国四个州 80 年公共产量试验记录的玉米杂交耐热性统计模型，以及 CMIP6 气候模型集合的输出。虽然种植日期在历史上有所提前，但我们发现 2005 年之后有推迟种植日期的趋势，并且没有出丝或成熟的趋势，将更多时间转移到繁殖期。然后，我们使用历史模型和作物日历预测玉米产量，这些模型和作物日历是使用先前提出的三种适应策略设计的。与使用 CGM 的研究相比，我们的统计产量模型预测了所有三种策略下的严重产量损失。最后，我们预测玉米产量考虑了耐热性的历史遗传变异性，发现它不足以克服预测变暖的负面影响。这些预测是由所有作物日历和气候情景下更大的热应激暴露所驱动的。 结合对 CGM 对温度的内部敏感性的分析，我们的结果表明，目前的预测没有充分考虑温度升高对玉米产量的影响。美国中西部的气候适应必须采用比物候适应更丰富的策略，包括提高耐热性和作物多样化。