Modeling plant diseases under climate change: evolutionary perspectives. (May 2023)

• Record Type: Journal Article
• Authors: Yang, Li-Na; Ren, Maozhi; Zhan, Jiasui
• Is Part Of: Trends in plant science. Volume 28:Number 5(2023)
• Page Start: 519
• Page End: 526
• Publication Date: 2023-05
• Subjects: trade-offs -- evolutionary adaptation -- climate preference -- sustainability -- polytrophic models; Botany -- Periodicals; Botanique -- Périodiques; Botany; Periodicals; 580.5
• DOI: 10.1016/j.tplants.2022.12.011
• Languages: English
• ISSNs: 1360-1385

Abstract

Highlights: Modeling is a unique and cost-effective approach to predict the long-term impacts of climate change on infectious plant diseases and sustainability. Model predictions are hindered by a lack of evolutionary understanding of the individual and interactive impacts of climate change on plants, pathogens, and ecosystems. Climate change creates a series of intra- and inter-specific trade-offs that modulate the entire epidemiological process of infectious plant diseases. Climatic preferences of plants, pathogens, and their interactions evolve in response to change in local climatic conditions. Technological advances offer unprecedented opportunities to generate and integrate biological, ecological, and evolutionary knowledge in polytrophic models. Abstract: 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.