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    Author(s): William BechtoldKaDonna Randolph; Stanley Zarnoch
    Date: 2009
    Source: In: McWilliams, Will; Moisen, Gretchen; Czaplewski, Ray, comps. Forest Inventory and Analysis (FIA) Symposium 2008; October 21-23, 2008; Park City, UT. Proc. RMRS-P-56CD. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 21 p.
    Publication Series: Proceedings (P)
    Station: Rocky Mountain Research Station
    PDF: View PDF  (197.51 KB)

    Description

    The goal of Phase 3 Detection Monitoring as implemented by the Forest Inventory and Analysis Program is to identify forest ecosystems where conditions might be deteriorating in subtle ways over large areas. At the relatively sparse sampling intensity of the Phase 3 plot network, a rough measure of success for the forest health indicators developed for this purpose is the ability to detect meaningful change when indicator data are pooled across two or three States. The statistical power of a test is the probability of detecting a difference of a certain magnitude when it indeed exists, and is defined as 1 minus the type II error (i.e., 1-beta). This study applies statistical power analysis to Phase 3 Crown-Indicator variables (crown density, foliage transparency, and crown dieback) to determine how many plots are necessary to detect various degrees of change at various levels of statistical power.

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    Citation

    Bechtold, William A.; Randolph, Kadonna C.; Zarnoch, Stanley J. 2009. The power of FIA Phase 3 Crown-Indicator variables to detect change. In: McWilliams, Will; Moisen, Gretchen; Czaplewski, Ray, comps. Forest Inventory and Analysis (FIA) Symposium 2008; October 21-23, 2008; Park City, UT. Proc. RMRS-P-56CD. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 21 p.

    Keywords

    statistical power analysis, forest health indicators, tree crown condition, tree crown health, tree health indicators, tree crown measurement

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