Literature DB >> 24515971

Rainfall and temperatures changes have confounding impacts on Phytophthora cinnamomi occurrence risk in the southwestern USA under climate change scenarios.

Sally E Thompson1, Simon Levin, Ignacio Rodriguez-Iturbe.   

Abstract

Global change will simultaneously impact many aspects of climate, with the potential to exacerbate the risks posed by plant pathogens to agriculture and the natural environment; yet, most studies that explore climate impacts on plant pathogen ranges consider individual climatic factors separately. In this study, we adopt a stochastic modeling approach to address multiple pathways by which climate can constrain the range of the generalist plant pathogen Phytophthora cinnamomi (Pc): through changing winter soil temperatures affecting pathogen survival; spring soil temperatures and thus pathogen metabolic rates; and changing spring soil moisture conditions and thus pathogen growth rates through host root systems. We apply this model to the southwestern USA for contemporary and plausible future climate scenarios and evaluate the changes in the potential range of Pc. The results indicate that the plausible range of this pathogen in the southwestern USA extends over approximately 200,000 km(2) under contemporary conditions. While warming temperatures as projected by the IPCC A2 and B1 emissions scenarios greatly expand the range over which the pathogen can survive winter, projected reductions in spring rainfall reduce its feasible habitat, leading to spatially complex patterns of changing risk. The study demonstrates that temperature and rainfall changes associated with possible climate futures in the southwestern USA have confounding impacts on the range of Pc, suggesting that projections of future pathogen dynamics and ranges should account for multiple pathways of climate-pathogen interaction.
© 2014 John Wiley & Sons Ltd.

Entities:  

Keywords:  California; Phytophthora cinnamomi; climate change; edaphic; multiple stressors; plant pathogen; rainfall; stochastic modeling

Mesh:

Year:  2014        PMID: 24515971     DOI: 10.1111/gcb.12463

Source DB:  PubMed          Journal:  Glob Chang Biol        ISSN: 1354-1013            Impact factor:   10.863


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