Robustness of ecological indicators to species misidentification in the national forest inventory of the United States

Longitudinal data are essential to assessing change in environmental parameters over space and through time. This is particularly true in forest ecosystems where demographic patterns are controlled by many biotic and abiotic factors that may only be observed through repeated measures of tree (e.g., height, diameter, status), stand (e.g., tree density, litter depth), and site conditions (e.g., evidence of disturbance). Data from the United States Department of Agriculture Forest Service, Forest Inventory and Analysis Program (FIA), support a variety of research and reporting efforts in forest resources and ecology. Remeasurements of the same plots provide invaluable information about the temporal dynamics of forest ecosystems. However, changes in attributes between remeasurements, such as species identification code (SPCD), can impact a variety of forest measurements such as species richness, species range dynamics, and carbon estimates. Here, we linked over 12 million tree remeasurements from approximately 140,000 FIA plots to explore how SPCD changes can lead to differences in key indicators of forest dynamics. Our workflow identified >114,000 trees with SPCD changes, with the frequency of SPCD changes highest in the southeastern United States. Two SPCD correction methods—adjusting a tree's SPCD based on either the earliest or the most recently recorded SPCD—led to species range centroids that differed by 0.3–24.5 km. Plot-level species richness varied by ±4 species between the two SPCD correction methods, but many plots (58%) had the same richness despite reassignment of individual trees to different SPCDs. Tree-level carbon stock estimates were correlated between the two SPCD correction methods, but some trees were more sensitive to changes when species-specific allometric model form, coefficients, and/or carbon fractions changed. However, population estimates of parameters such as carbon stocks per unit area were robust to SPCD corrections because trees with consistent SPCDs vastly outnumbered trees with SPCD changes. Our results illustrate that decisions on how to handle nuances in remeasurement data can have substantial implications on the biological and ecological conclusions drawn from large-scale, strategic-level inventories such as the national forest inventory in the United States.