Model-aided climate adaptation for future maize in the US

Authors: HSIAO, JENNIFER - University Of Washington; KIM, SOO-HYUNG - University Of Washington; Timlin, Dennis; MUELLER, NATHAN - University Of Washington; SWANN, ABIGAIL - University Of Washington

Submitted to: Environmental Research: Food Systems
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/6/2024
Publication Date: 4/2/2024
Citation: Hsiao, J., Kim, S., Timlin, D.J., Mueller, N., Swann, A. 2024. Model-aided climate adaptation for future maize in the US. Environmental Research: Food Systems. 1(1). Article e015004. https://doi.org/10.1088/2976-601X/ad3085.
DOI: https://doi.org/10.1088/2976-601X/ad3085

Interpretive Summary: 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. In this study, we use a mechanistic corn crop model (MAIZSIM) to identify high-performing trait and management combinations that maximize yield and yield stability of corn for different agro-climate regions in the US under present and future climate conditions. We found that the corn plant properties that produce high and stable yields under present-day climate conditions do not guarantee high performance under future climate conditions. The simulations showed that plants with higher total leaf area and later grain-filling start time better buffer yield loss and out-compete plants with a smaller stature 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.

Technical 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 for 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, and a balanced compromise between yield and yield stability is critical to achieving high performance. We also demonstrate that high performance under present-day climate does not guarantee high performance under future climate. Weakened trade-offs between canopy size 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 stature 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.