Yang Li-Na, Ren Maozhi, Zhan Jiasui
Fujian Key Laboratory on Conservation and Sustainable Utilization of Marine Biodiversity, Fuzhou Institute of Oceanography, Minjiang University, Fuzhou, 350108, China.
Institute of Urban Agriculture, Chinese Academy of Agricultural Sciences, Chengdu National Agricultural Science and Technology Center, Chengdu, China.
Trends Plant Sci. 2023 May;28(5):519-526. doi: 10.1016/j.tplants.2022.12.011. Epub 2022 Dec 31.
Infectious plant diseases are a major threat to global agricultural productivity, economic development, and ecological integrity. There is widespread concern that these social and natural disasters caused by infectious plant diseases may escalate with climate change and computer modeling offers a unique opportunity to address this concern. Here, we analyze the intrinsic problems associated with current modeling strategies and highlight the need to integrate evolutionary principles into polytrophic, eco-evolutionary frameworks to improve predictions. We particularly discuss how evolutionary shifts in functional trade-offs, relative adaptability between plants and pathogens, ecosystems, and climate preferences induced by climate change may feedback to future plant disease epidemics and how technological advances can facilitate the generation and integration of this relevant knowledge for better modeling predictions.
传染性植物病害对全球农业生产力、经济发展和生态完整性构成重大威胁。人们普遍担心,由传染性植物病害引发的这些社会和自然灾害可能会随着气候变化而加剧,而计算机建模提供了一个独特的机会来应对这一担忧。在此,我们分析了当前建模策略存在的内在问题,并强调需要将进化原理纳入多营养、生态进化框架,以改进预测。我们特别讨论了气候变化引起的功能权衡、植物与病原体之间的相对适应性、生态系统和气候偏好的进化转变如何反馈到未来的植物病害流行,以及技术进步如何促进生成和整合这些相关知识以实现更好的建模预测。