Model-aided climate adaptation for future maize in the U.S.

J. Hsiao, Soo-Hyung Kim, Dennis Timlin, Nathan Mueller, A. Swann
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引用次数: 1

Abstract

Over the next three decades rising population and changing dietary preferences are expected to increase food demand by 25–75%. At the same time climate is also changing — with potentially drastic impacts on food production. Breeding new crop characteristics and adjusting management practices are critical avenues to mitigate yield loss and sustain yield stability under a changing climate. In this study, we use a mechanistic crop model (MAIZSIM) to identify high-performing trait and management combinations that maximize yield and yield stability for different agro-climate regions in the US under present and future climate conditions. We show that morphological traits such as total leaf area and phenological traits such as grain-filling start time and duration are key properties that impact yield and yield stability; different combinations of these properties can lead to multiple high-performing strategies under present-day climate conditions. We also demonstrate that high performance under present-day climate does not guarantee high performance under future climate. Weakened trade-offs between canopy leaf area and reproductive start time under a warmer future climate led to shifts in high-performing strategies, allowing strategies with higher total leaf area and later grain-filling start time to better buffer yield loss and out-compete strategies with a smaller canopy leaf area and earlier reproduction. These results demonstrate that focused effort is needed to breed plant varieties to buffer yield loss under future climate conditions as these varieties may not currently exist, and showcase how information from process-based models can complement breeding efforts and targeted management to increase agriculture resilience.
为美国未来玉米的气候适应提供模型辅助
未来三十年,人口的增长和饮食偏好的改变预计将使粮食需求增加 25-75%。与此同时,气候也在发生变化,可能会对粮食生产产生巨大影响。培育新的作物特性和调整管理方法是在不断变化的气候条件下减少产量损失和维持产量稳定的关键途径。在本研究中,我们利用一个机械作物模型(MAIZSIM)来确定高效的性状和管理组合,以最大限度地提高美国不同农业气候地区在当前和未来气候条件下的产量和产量稳定性。我们的研究表明,总叶面积等形态性状和谷粒开始饱满的时间和持续时间等物候性状是影响产量和产量稳定性的关键特性;这些特性的不同组合可在当今气候条件下产生多种高效策略。我们还证明,当今气候条件下的高性能并不能保证未来气候条件下的高性能。在未来较暖的气候条件下,冠层叶面积和生殖开始时间之间的权衡减弱,导致高性能策略的转变,使总叶面积较大、谷物开始成熟时间较晚的策略能够更好地缓冲产量损失,并在竞争中胜过冠层叶面积较小、生殖开始时间较早的策略。这些结果表明,需要集中精力培育在未来气候条件下能缓冲产量损失的植物品种,因为这些品种目前可能还不存在,并展示了基于过程的模型所提供的信息如何能补充育种工作和有针对性的管理,以提高农业的抗灾能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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