Abstract
Abstract
The recovery of biomass in secondary forests plays a vital role in global carbon sequestration processes and carbon emission mitigation. However, accurately quantifying the accumulation rate of aboveground biomass density in these forests is challenging owing to limited longitudinal field data. An alternative monitoring strategy is characterizing the mean biomass at a single point in time across stands with a range of known ages. This chronosequence approach can also be used with remotely sensed data by combining biomass measured with platforms such as NASA’s Global Ecosystem Dynamics Investigation (GEDI) mission with forest age strata provided by historic Landsat imagery. However, focusing on the low-biomass conditions common in newly regenerating forests will accentuate commonly observed over-prediction of low biomass values. We propose a vicarious calibration approach that develops a correction for GEDI’s biomass models in young forests, which may be mapped using Landsat time series, using an assumption that the aboveground biomass of newly cleared forests is zero. We tested this approach, which requires no additional local field data, in the U.S. Pacific Northwest, where extensive inventory data from the USDA Forest Service are available. Our results show that the calibration did not significantly improve the fit of predicted biomass as a function of age across 12 ecoregions (one-side t-test; p = 0.20), but it did significantly reduce bias for the youngest age groups with respect to reference data. Calibrated GEDI-based biomass estimates for < 20 year old forests were more accurate than 2006 IPCC defaults in most ecoregions (with respect to authoritative inventory estimates) and may represent a basis for refining carbon storage expectations for secondary forests globally.