Approaches to predicting potential impacts of climate change on forest disease: an example with Armillaria root disease

Ned B. Klopfenstein; Mee-Sook Kim; John W. Hanna; Bryce A. Richardson; John E. Lundquist

doi:10.2737/RMRS-RP-76

Treesearch

Approaches to predicting potential impacts of climate change on forest disease: an example with Armillaria root disease

Informally Refereed

Authors:

Ned B. Klopfenstein, Mee-Sook Kim, John W. Hanna, Bryce A. Richardson, John E. Lundquist

Year:

2009

Type:

Research Paper

Station:

Rocky Mountain Research Station

DOI:

https://doi.org/10.2737/RMRS-RP-76

Source:

Res. Pap. RMRS-RP-76. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 10 p.

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Download (PDF 1.70 MB): https://research.fs.usda.gov/download/treesearch/33179.pdf

Abstract

Predicting climate change influences on forest diseases will foster forest management practices that minimize adverse impacts of diseases. Precise locations of accurately identified pathogens and hosts must be documented and spatially referenced to determine which climatic factors influence species distribution. With this information, bioclimatic models can predict the occurrence and distribution of suitable climate space for host and pathogen species under projected climate scenarios. Predictive capacity is extremely limited for forest pathogens because distribution data are usually lacking. Using Armillaria root disease as an example, predictive approaches using available data are presented.

Keywords

climate change, forest diseases, Armillaria, bioclimatic models, forest pathogens, global warming, MaxEnt

Citation

Klopfenstein, Ned B.; Kim, Mee-Sook; Hanna, John W.; Richardson, Bryce A.; Lundquist, John E. 2009. Approaches to predicting potential impacts of climate change on forest disease: an example with Armillaria root disease. Res. Pap. RMRS-RP-76. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 10 p.