Approaches for Landscape-scale Forest Carbon Assessment

Increasingly, public and private forest landowners need to estimate their carbon stocks and analyze the impacts of alternate management plans. Here we describe approaches designed to work at landscape scales: one involves estimating carbon stocks from existing Forest Inventory and Analysis (FIA) data; another involves downscaling results from a continental-scale biogeochemistry model known as InTEC; and the third uses LiDAR remote sensing to provide high-resolution biomass maps. Combining FIA data with a biogeochemistry model gives the most useful information for analyzing causes of historical trends, while the biomass maps support implementation of management decisions. These approaches are illustrated by pilot studies in the Eastern U.S. Analysis of FIA data for Northern Wisconsin revealed that private landowners held more than half of the forest carbon but that the rate of carbon sequestration had slowed dramatically over two decades. Causes of the decline were hypothesized to include increased harvesting, aging forests, and increasing disturbances. The InTEC model for the same region revealed trends over a much longer historical period as well as providing information about changes in soil C that are lacking in the FIA data analysis. The effects of long-term forest age dynamics and higher interannual climate variability became evident, and there is evidence of a significant contribution to net sequestration from increasing soil C stocks. Using this information base, we identified several ways to increase landscape-scale average forest carbon stocks: allow some forests to reach full maturity and highest carbon stocks; manage other forests to maximize carbon uptake and transfer of harvested carbon into wood products; and avoid conversion of existing forests to nonforest land uses. Strategic implementation of these kinds of management decisions can be facilitated with high-resolution biomass maps.