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Geographic analysis of forest health indicators using spatial scan statistics
John W Coulston1, Kurt H Riitters
1Department of Forestry, North Carolina State University, Southern Research Station, Forestry Sciences Laboratory P.O. Box 12254, Research Triangle Park, North Carolina 27709, USA. jcoulston@fs.fed.us
Environmental Management
|October 21, 2003
Summary
Spatial scan statistics identify forest health hotspots. This method detected clusters of forest fragmentation in the southeastern US and insect/pathogen outbreaks in the Pacific Northwest, aiding in problem identification.
Area of Science:
- Forestry
- Spatial Analysis
- Ecology
Background:
- Assessing large-scale forest health requires geographically explicit tools.
- Spatial scan statistics offer a method for detecting clusters of extreme indicator values.
Purpose of the Study:
- To demonstrate the utility of spatial scan statistics for analyzing forest health indicators across large regions.
- To identify spatial clusters of forest fragmentation and insect/pathogen occurrence.
Main Methods:
- Application of spatial scan statistics to forest fragmentation data in the southeastern US.
- Analysis of insect and pathogen occurrence data in the Pacific Northwest using spatial scan statistics.
Main Results:
- Four spatial clusters of forest fragmentation were detected, including a hotspot in the Piedmont and Coastal Plain.
- Three recurring clusters of insect and pathogen occurrence were identified in the Pacific Northwest.
Conclusions:
- Spatial scan statistics are effective for identifying potential forest health issues over large areas.
- This approach provides a powerful tool for pinpointing areas needing forest health management interventions.