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Assessing potential Armillaria spp. distributions in western Oregon, western Washington, and AlaskaAuthor(s): John W. Hanna; Mee-Sook Kim; Amy C. Ramsey; Dan W. Omdal; Robin L. Mulvey; Betsy A. Goodrich; Brennan A. Ferguson; Josh J. Bronson; Kristen L. Chadwick; Jane E. Stewart; Helen M. Maffei; Geral I McDonald; Eric W. I Pitman; Marcus V Warwell; Ned B. Klopfenstein
Source: In: Cleaver, C.; Palacious, P., compilers. Proceedings of the 65th annual Western International Forest Disease Work Conference; 2-6 October 2017; Parksville, BC, Canada. WIFDWC. p. 109-1115.
Publication Series: Scientific Journal (JRNL)
Station: Rocky Mountain Research Station
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DescriptionArmillaria species are key components of forest ecosystems throughout most regions of western North America. Their ecological roles range from beneficial saprobes to damaging root pathogens, and their impacts vary with environment and host. Under climate change, the impact of pathogenic species within these regions is predicted to increase (Kliejunas et al 2009), which could result in increased tree mortality, growth loss, and hazard trees that threaten public safety. In 2016, a collaborative project was initiated to survey of Armillaria spp. distributions in western Oregon, western Washington, and Alaska. Methods and preliminary results of the 2016 and 2017 (ongoing) field surveys/collections are described herein. Armillaria isolates derived from collaborative surveys are identified using DNA-based methods (e.g., translation elongation factor-1α gene sequence; tef1). DNA-based identification and 19 location-specific climatic variables are used to develop models to predict areas suitable for the occurrence of Armillaria spp. Preliminary predictions of geographic distributions of suitable habitat for Armillaria under current and predicted future climates are presented, based on Maximum entropy distribution models (MaxEnt). MaxEnt models are especially useful because of their ability to produce statistically robust models using limited occurrence-only data (see Phillips et al. 2006). This information will contribute to habitat-specific management strategies for reducing impacts and increasing the benefits of these ecologically important fungal species.
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CitationHanna, John W.; Kim, Mee-Sook; Ramsey, Amy C.; Omdal, Dan W.; Mulvey, Robin L.; Goodrich, Betsy A.; Ferguson, Brennan A.; Bronson, Josh J.; Chadwick, Kristen L.; Stewart, Jane E.; Maffei, Helen M.; McDonald, Geral I.; Pitman, Eric W. I.; Warwell, Marcus V.; Klopfenstein, Ned B. 2019. Assessing potential Armillaria spp. distributions in western Oregon, western Washington, and Alaska: Including preliminary contemporary and future bioclimatic models for Armillaria solidipes. In: Cleaver, C.; Palacious, P., compilers. Proceedings of the 65th annual Western International Forest Disease Work Conference; 2-6 October 2017; Parksville, BC, Canada. WIFDWC. p. 109-1115.
KeywordsArmillaria, forest ecosystems, saprobes, root pathogens, climate change, Maximum entropy distribution models (MaxEnt), habitat-specific management
- Maximum entropy-based bioclimatic models predict areas of current and future suitable habitat for Armillaria species in western Oregon and western Washington
- Armillaria root disease in the western USA
- Survey of Armillaria spp. in the Oregon East Cascades: Baseline data for predicting climatic influences on Armillaria root disease
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