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Approaches to predicting potential impacts of climate change on forest disease: An example with Armillaria root disease
Klopfenstein, Ned B.; Kim, Mee-Sook; Hanna, John W.; Richardson, Bryce A.; Lundquist, John E. 2011. Approaches to predicting potential impacts of climate change on forest disease: An example with Armillaria root disease. In: Chavarrigga, D. M., H., ed. Proteccion Fitosanitaria Forestal. Colombia: Instituto Colombiano Agropecuario ICA, Comunicaciones. p. 101-117.
Climate change will likely have dramatic impacts on forest health because many forest trees could become maladapted to climate. Furthermore, climate change will have additional impacts on forest health through changes in the distribution and severity of forest disease. Methods are needed to predict the influence of climate change on forest disease so that appropriate forest management practices can be implemented to minimize disease impacts. Initial approaches for predicting the future distribution of pathogens are dependent on reliable data sets that document the current, precise location of accurately identified pathogens and hosts. Precise distribution information can be used in conjunction with available climate surfaces to determine which climatic factors and interactions influence species distribution. This information can be used to develop bioclimatic models to predict the probability of suitable climate space for host and pathogen species across the landscape. A similar approach using climate surfaces under predicted future climate scenarios can be used to project suitable climate space for hosts and pathogens in the future. Currently such predictions are well developed for many forest host species, but predictive capacity is extremely limited for forest pathogens because of lacking distribution data. Continued surveys and research are needed to further refine bioclimatic models to predict influences of climate and climate change on forest disease.
Keywords: climate change, forest disease, Armillaria root
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Publications: Approaches to predicting potential impacts of climate
change on forest disease: An example with Armillaria root disease
Electronic Publish Date: February 6, 2012
Last Update: February 6, 2012
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