Synoptic climatology of the long-distance dispersal of white pine blister rust II. Combination of surface and upper-level conditions.
An invasive forest pathogen, Cronartium ribicola, white pine blister rust (WPBR), is believed to have arrived in the Sacramento Mountains of south-central New Mexico about 1970. Epidemiological and genetic evidence supports the hypothesis that introduction was the result of long-distance dispersal (LDD) by atmospheric transport from California. This study applies a method to identify the atmospheric conditions favorable for rust transport and infection. An upper level synoptic classification (ULSC) identifies patterns of upper-level flow favorable for the transport of rust spores from a source to a target. Transport data are coupled with data for surface conditions favorable for infection at a designated target. A resulting calendar lists likelihood classes for establishment by four-times-daily observations during a dispersal season from April through July in the years 1965 to 1974. The single most-favorable period for transport and infection at the New Mexico site was identified as 1-15 June 1969. Five additional sites in the western United States with susceptible white pine populations and known infestation status were then evaluated to verify the model. Only the infested sites exhibit an establishment likelihood of "high" or "very high." This suggests that the methodology correctly identifies locations with elevated establishment likelihood. Finally, likelihoods at nine additional points in the southwestern United States are determined and used to map regional patterns of transport, infection and establishment. The ULSC combined with appropriate surface meteorological data could be used to further investigate transport and infection, identify other areas at risk, assess the potential for gene flow of WPBR and evaluate long-distance dispersal of other pathogens.
Frank
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Center for Climatic Research, Department of Geography, University of Delaware, Newark, DE 19716, USA. klfrank@udel.edu
Geils
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Kalkstein
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Thistle
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D001272:Atmosphere; D001487:Basidiomycota / Q000302:isolation & purification*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D017753:Ecosystem; D015233:Models, Statistical; D009656:North America; D028223:Pinus / Q000382:microbiology*; D010935:Plant Diseases / Q000382:microbiology* / Q000706:statistics & numerical data*; D014887:Weather