  The United States national forest inventory (NFI) serves as the foundation
for forest aboveground biomass (AGB) and carbon accounting across the nation.
These data enable design-based estimates of forest carbon stocks and
stock-changes at state and regional levels, but also serve as inputs to
model-based approaches for characterizing forest carbon stocks and
stock-changes at finer resolutions. Although NFI tree and plot-level data are
often treated as truth in these models, they are in fact estimates based on
regional species-group models known collectively as the Component Ratio Method
(CRM). In late 2023 the Forest Inventory and Analysis (FIA) program introduced
a new National Scale Volume and Biomass Estimators (NSVB) system to replace CRM
nationwide and offer more precise and accurate representations of forest AGB
and carbon. Given the prevalence of model-based AGB studies relying on FIA,
there is concern about the transferability of methods from CRM to NSVB models,
as well as the comparability of existing CRM AGB products (e.g. maps) to new
and forthcoming NSVB AGB products. To begin addressing these concerns we
compared previously published CRM AGB maps to new maps produced using identical
methods with NSVB AGB reference data. Our results suggest that models relying
on passive satellite imagery (e.g. Landsat) provide acceptable estimates of
point-in-time NSVB AGB and carbon stocks, but fail to accurately quantify
growth in mature closed-canopy forests. We highlight that existing estimates,
models, and maps based on FIA reference data are no longer compatible with
NSVB, and recommend new methods as well as updated models and maps for
accommodating this step-change. Our collective ability to adopt NSVB in our
modeling and mapping workflows will help us provide the most accurate spatial
forest carbon data possible in order to better inform local management and
decision making.
