The USDA Forest Service’s Forest Inventory and Analysis Database and the National Register of Champion Trees — A Potentially Symbiotic Relationship

Abstract

Abstract This article shows how probability sampling and citizen science efforts can complement each other, using the USDA Forest Service’s Forest Inventory and Analysis (FIA) program and the ongoing search by the National Register of Champion Trees (NRCT) for the largest specimen of each naturally occurring tree species in the United States as an example. We develop a ratio statistic (Zs) that uses the difference in size of the largest tree of a species from each database to order the tree species according to the assumed ease with which a larger specimen than the current national champion might be found. Our results show ninety-two candidate species that have been recorded by FIA for which there is no national champion and sixty-five species for which a new champion should be easy to find. In a supplemental table, we show ninety-four species listed as observable by FIA in the NRCT but not recorded in the FIA sample. Study Implications: An interest in forests and forestry is always accompanied by an interest in trees, especially very big trees. Two very different ways of learning about trees are analyzed concurrently in a way that reveals their complementarity. The two efforts are the probability sample, conducted by the USDA Forest Service’s Forest Inventory and Analysis (FIA) Program, and the citizen science effort known as the National Register of Champion Trees (NRCT). We develop a statistic that will help tree sleuths find champion trees and provide FIA practitioners with a quality control measure and an indication of which species would benefit from an increase in sample intensity.