Measurement uncertainty in a national forest inventory :results from the northern region of the USA

Statistical confidence in estimates of timber volume, carbon storage, and other forest attributes depends, in part, on the uncertainty in field measurements. Surprisingly, measurement uncertainty is rarely reported, even though national forest inventories routinely repeat field measurements for quality assurance. We compared measurements made by field crews and quality assurance crews in the Forest Inventory and Analysis program of the U.S. Forest Service, using data from 2790 plots and 51 740 trees and saplings across the 24 states of the Northern Region. We characterized uncertainty in 12 national core tree-level variables; seven tree crown variables used in forest health monitoring; three variables describing seedlings; and 11 variables describing the site, such as elevation, slope, and distance from a road. Discrepancies in measurement were generally small but were higher for some variables requiring judgment, such as tree class, decay class, and cause of mortality. When scaled up to states, forest types, or the region, uncertainties in basal area, timber volume, and aboveground biomass were negligible. Understanding all sources of uncertainty is important to designing forest monitoring systems, managing the conduct of the inventory, and assessing the uncertainty of forest attributes required for making regional and national forest policy decisions.

Automated summary

Statistical confidence in estimates of timber volume, carbon storage, and other forest attributes is influenced by uncertainty in field measurements. This study compared measurements made by field crews and quality assurance crews in the US Forest Service's Forest Inventory and Analysis program. The results showed that measurement uncertainty is generally small, but higher for certain variables requiring judgment. Uncertainties in basal area, timber volume, and aboveground biomass were negligible when scaled up to larger areas. Understanding sources of uncertainty is important for forest monitoring, inventory management, and policy decision making.