Abstract
Natural resource statistics are often unavailable for small ecological or economic regions and policymakers have to rely on state-level datasets to evaluate the status of their resources (i.e., forests, rangelands, grasslands, agriculture, etc.) at the regional or local level. These resources can be evaluated using small-area estimation techniques. However, it is unknown which small area technique produces the most valid and precise results. The reliability and accuracy of two methods, synthetic and regression estimators, used in small-area analyses, were examined in this study. The two small-area analysis methods were applied to data from Jalisco’s state-wide natural resource inventory to examine how well each technique predicted selected characteristics of forest stand structure. The regression method produced the most valid and precise estimates of forest stand characteristics at multiple geographical scales. Therefore, state and local resource managers should utilize the regression method unless appropriate auxiliary information is not available.
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Biography: Dr. Robin M. Reich (1954–), male, is a professor of forest biometrics/spatial statistics in the Department of Forest, Rangeland and Watershed Stewardship at Colorado State University. Dr. Reich is an expert in the application of spatial statistics in designing natural resource inventories and ecosystem modeling.
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Reich, R.M., Aguirre-Bravo, C. Small-area estimation of forest stand structure in Jalisco, Mexico. Journal of Forestry Research 20, 285–292 (2009). https://doi.org/10.1007/s11676-009-0050-y
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DOI: https://doi.org/10.1007/s11676-009-0050-y