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Linking plant disease risk and precipitation drivers: a dynamical systems framework
Sally Thompson1, Simon Levin, Ignacio Rodriguez-Iturbe
1Department of Civil and Environmental Engineering, University of California, Berkeley, California 94703, USA. sally.thompson@berkeley.edu
The American Naturalist
|December 14, 2012
Summary
Global change impacts plant pathogens, especially those sensitive to water. This study models pathogen risk using ecohydrological frameworks, linking precipitation and soil to disease severity, offering insights for climate change adaptation.
Area of Science:
- Plant pathology
- Ecohydrology
- Global change ecology
Background:
- Plant pathogens are sensitive to environmental shifts, indicating their role in ecological responses to global change.
- While temperature and CO2 effects on plant pathogens are studied, precipitation changes remain less explored.
- Water potential significantly influences many plant pathogen classes.
Purpose of the Study:
- To apply ecohydrological frameworks to link precipitation, soil, and host properties with plant pathogen risk.
- To develop simple models connecting pathogen dynamics to water potentials for two specific pathogens.
- To illustrate the framework's application in predicting pathogen distribution and disease severity.
Main Methods:
- Utilized existing ecohydrological frameworks to model pathogen risk.
- Developed simple models linking pathogen dynamics to soil water potentials.
- Focused on water-sensitive pathogens: Phytophthora cinnamomi and Botryosphaeria doithidea.
Main Results:
- Pathogen colonization risk varied significantly with soil and climate conditions.
- Model predictions were made for Phytophthora distribution in Western Australia.
- Disease severity in blueberry trials was predicted under varying irrigation rates.
Conclusions:
- The developed modeling approach provides a tractable framework for assessing regional-scale ecosystem responses to climatic drivers.
- The framework accounts for the probabilistic and variable nature of plant diseases.
- Further extensions could incorporate spatial hydrology and epidemic feedbacks for detailed disease pattern reproduction.
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