2023
DOI: 10.1098/rstb.2022.0017
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Mechanistic models to meet the challenge of climate change in plant–pathogen systems

Abstract: Evidence that climate change will impact the ecology and evolution of individual plant species is growing. However, little, as yet, is known about how climate change will affect interactions between plants and their pathogens. Climate drivers could affect the physiology, and thus demography, and ultimately evolutionary processes affecting both plant hosts and their pathogens. Because the impacts of climate drivers may operate in different directions at different scales of infection, and, furthermore, may be no… Show more

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Cited by 6 publications
(7 citation statements)
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References 100 publications
(127 reference statements)
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“…Once these have been resolved, coupled epidemiological–oceanographic models may yield promise for understanding the dispersal characteristics of spores throughout the fishery and potential infection hotspots, since physical ocean models have already been developed for the ETBF region and applied to fish and crustacean larval transport dynamics (Hewitt et al, 2022; Kerry & Roughan, 2020; Schilling et al, 2022; Wijeratne et al, 2018). Mechanistic, process‐based models that quantify relationships between climate and pathogen dynamics—integrating field and experimental data—have already yielded promising results in other host–pathogen systems in terms of understanding physiological, demographic and evolutionary responses to climate change (Jiranek et al, 2023; Rohr et al, 2011).…”
Section: Discussionmentioning
confidence: 99%
“…Once these have been resolved, coupled epidemiological–oceanographic models may yield promise for understanding the dispersal characteristics of spores throughout the fishery and potential infection hotspots, since physical ocean models have already been developed for the ETBF region and applied to fish and crustacean larval transport dynamics (Hewitt et al, 2022; Kerry & Roughan, 2020; Schilling et al, 2022; Wijeratne et al, 2018). Mechanistic, process‐based models that quantify relationships between climate and pathogen dynamics—integrating field and experimental data—have already yielded promising results in other host–pathogen systems in terms of understanding physiological, demographic and evolutionary responses to climate change (Jiranek et al, 2023; Rohr et al, 2011).…”
Section: Discussionmentioning
confidence: 99%
“…Understanding how weather anomalies mediate plant disease outbreaks is critical for anticipating and mitigating climate change impacts for agricultural and wild plant systems, which affect food security 2 and ecosystem integrity 7 . Here, we compile and analyze a novel spatiotemporal plant disease database, revealing that disease outbreaks occur more commonly during periods of warm temperatures in agricultural and cool-climate wild plant systems.…”
Section: Discussionmentioning
confidence: 99%
“…Both temperature and moisture exert strong effects on plants and the parasites that infect them 4 and can be key to accurately predict plant disease across time and space 5 , making these systems highly susceptible to environmental effects across biological scales 6 . Critically, relatively little is known about how plant–disease systems will respond to novel weather caused by climate change 7 , despite the fact that these responses may have implications for global food security, plant conservation, and ecosystem management. To anticipate and mitigate climate change effects, we must understand how past climate and current weather have shaped plant disease around the world.…”
Section: Main Textmentioning
confidence: 99%
“…By contrast, Jiranek et al. [ 32 ] review the use of mechanistic models to study host–pathogen interactions under different scenarios of climate change, with a focus on plant systems. They outline the challenge of linking disease outbreaks with weather variables when climate change will likely affect many aspects of host and pathogen physiology, host demography, and pathogen life cycles, and these effects may frequently be nonlinear.…”
Section: Theme 2: Understanding Host–pathogen Interactions In Dynamic...mentioning
confidence: 99%