title: Geographic analysis of forest health indicators using spatial scan statistics.
abstract: Geographically explicit analysis tools are needed to assess forest health indicators that are measured over large regions. Spatial scan statistics can be used to detect spatial or spatiotemporal clusters of forests representing hotspots of extreme indicator values. This paper demonstrates the approach through analyses of forest fragmentation indicators in the southeastern United States and insect and pathogen indicators in the Pacific Northwest United States. The scan statistic detected four spatial clusters of fragmented forest including a hotspot in the Piedmont and Coastal Plain region. Three recurring clusters of insect and pathogen occurrence were found in the Pacific Northwest. Spatial scan statistics are a powerful new tool that can be used to identify potential forest health problems.
authors.affiliation: Department 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
authors.forename: John W
authors.initials: JW
authors.lastname: Coulston
authors.forename: Kurt H
authors.initials: KH
authors.lastname: Riitters
mesh_terms: D000818:Animals; D004784:Environmental Monitoring; D005658:Fungi / Q000472:pathogenicity; D040362:Geographic Information Systems; D007313:Insecta; D011157:Population Dynamics; D014197:Trees / Q000145:classification*; D014481:United States