Estimate of Whitebark Pine Blister Rust Infection in Whitebark Pine for the US

Metadata:

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Identification_Information:

Citation:

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Originator:

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Publication_Date:

REQUIRED: The date when the data set is published or otherwise made available for release.

Title:

Estimate of Whitebark Pine Blister Rust Infection in Whitebark Pine for the US

Geospatial_Data_Presentation_Form: vector digital data

Online_Linkage:

<http://www.fs.fed.us/r1/gis/thematic_data/WhitebarkPineBlisterRustEstUS.zip>

Description:

Abstract:

The whitebark pine blister rust data layer (percent_wbpbr) represents an estimate of white pine blister rust (Cronartium ribicola) infection in whitebark pine (Pinus albicaulis) throughout the tree's range within the United States. Percent blister rust infection was mapped using a gradient modeling approach. Gradient modeling identifies key environmental gradients (independent variables) that drive a response (dependent variable), which are then mathematically represented in a statistical model to predict and map ecosystem characteristics across the landscape. The independent variables used were:

1. daily average water vapor pressure (hv) 2. average precipitation event size (pe) 3. precipitation frequency (pf) 4. total precipitation (pt) 5. relative humidity (rh) 6. daily total shortwave radiation (rt) 7. daily average air temperature (ta) 8. daily minimum air temperature (tn) 9. daily maximum air temperature (tx) 10. elevation 11. latitude 12. longitude

The first nine of these variables were acquired from DAYMET climatological summaries for the months of June through October separately. Therefore there were a total of 48 independent variables. The dependent variable was percent blister rust infection in whitebark pine and 869 plots were used from the Whitebark-Limber Pine Information System (WLIS). The Random Forest method was used to build a predictive model using R statistical software.

Purpose:

Whitebark pine populations are rapidly declining across many parts of its range in the United States and Canada due to the combined effects of native mountain pine beetle (Dendroctonus ponderosae) epidemics, fire exclusion, and, most importantly, exotic white pine blister rust (Cronartium ribicola). Managers would find digital maps of whitebark pine distribution and rust infection useful in prioritizing areas for restoration. This data will provide a critical base layer for developing spatially explicit data layers that prioritize rust restoration activities at multiple spatial scales and will be used in the development of a regional restoration strategy USFS, General Technical Report.

Supplemental_Information:

DAYMET data are climatological summaries of meteorological observations for the period of record 1980-1997 interpolated to a 1 km² grid over the conterminous U.S. (www.daymet.org). The Whitebark-Limber Pine Information System (WLIS) is a database of plot-level surveys on whitebark and limber pine distribution and condition developed by the USDA Forest Service (<http://www.fs.fed.us/r1-r4/spf/fhp/prog/programs2.html>).

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Theme_Keyword: Biology, Ecology & Biophysical

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Source_Used_Citation_Abbreviation: E:\Projects\RustModeling\Results\percent_wbpbr

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E:\C\fsfiles\unit\e\geospatial\projects\current\library_work\BlisterRust\rust2\percent_wbpbr

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