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https://doi.org/10.1016/b978-0...
Part of book or chapter of book . 2016 . Peer-reviewed
License: Elsevier TDM
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https://doi.org/10.1016/b978-0...
Part of book or chapter of book . 2021 . Peer-reviewed
License: Elsevier TDM
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Plant Pathogens as Indicators of Climate Change

Authors: Garrett, K. A.; Nita, M.; De Wolf, E. D.; Esker, P. D.; Gomez-Montano, L.; Sparks, A. H.;

Plant Pathogens as Indicators of Climate Change

Abstract

The response of plant disease to weather variables such as temperature and precipitation is well known and has been the basis for disease forecasting models used in decision-making by farmers and policy makers. Thus, plant disease risk can readily shift under climate change. Predicting changes in risk under climate change is complicated by the many biological interactions that result in disease. For example, some plant diseases occur when the phenology of plant and pathogen are aligned, in the case of Fusarium head blight so that spores are ready to infect during wheat flowering. There are numerous examples of experiments involving simulated climate change that have shown changes in disease risk. Finding indicators of climate change effects on disease in real agricultural or natural systems is more challenging, because of the correlative nature of the observations and the potential for many other factors to influence disease, such as changes in host abundance. Assessments of global disease databases suggest some pathogen range shifts consistent with predicted outcomes for climate change. There are also several cases of emerging tree diseases in which climate change has likely played a role.

Countries
France, France, Australia
Keywords

580, plant pathology, Blight, food security, phytopathology, Carbon dioxide elevation, climate change, weather, Climate change, Plant diseases, Pathogens, plant disease, risk, agriculture

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    73
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
73
Top 1%
Top 10%
Top 10%
Green