Addressing the potentially widespread underestimation of carbon uptake in undisturbed forests

About This Grant

Forests are responsible for approximately 90% of all terrestrial carbon storage and are key regulators of the global carbon cycle. Moreover, strategies like forest conservation, reforestation, and improved forest management are widely viewed as promising avenues for natural carbon removal that confer a host of environmental and economic additional benefits. Yet, at scales ranging from individual sites to the entire globe, estimates of forest carbon uptake and storage vary by considerably. This uncertainty stymies efforts to confirm regional and global carbon budget estimates, and prevents robust evaluations of the potential of forest-based carbon removal strategies. Much of this uncertainty stems from a misalignment between our state-of-the-art understanding of forest carbon removal and the decades-old tools used to estimate it in practice. The overall goal of this project is to address these discrepancies using the best-available science, testing the central prediction that conventional monitoring approaches systematically underestimate how much carbon is removed from the atmosphere by undisturbed forests. This project will blend state-of-the-art field observations and synthesis of environmental network data to understand why measurement approaches give different results. The PI and her team will also develop novel techniques for more accurate forest carbon quantification that bridge field monitoring and regional to global-scale policy setting. To accelerate the transition of research findings into actionable information, the project will strengthen existing relationships with forest managers and policy-makers across the public and civic sectors, and emphasize the training of a workforce equipped to measure forest carbon removals using the best-available scientific tools. Most operational protocols for forest carbon monitoring rely on ‘stock-change’ approaches, which infer forest carbon uptake and storage from changes in woody biomass estimated from allometric equations and forest inventory data. While this approach is highly scalable, it has many limitations, including the omission or imprecise calculation of carbon changes in branches, roots, and the soil. Rapidly growing networks of eddy covariance flux towers have opened new opportunities to develop flux-based approaches for quantifying forest carbon uptake and storage. Although flux towers are the gold standard for measuring land-atmosphere carbon exchanges, they have not yet been leveraged for policy-relevant forest carbon quantification. This project integrates several independent but complementary activities to perform a robust comparison of stock versus flux-based monitoring approaches. These activities include: (1) a comprehensive synthesis of information from environmental observation networks including NSF’s National Ecological Observatory Network (NEON), the FLUXNET tower network, and the USDA Forest Inventory and Analysis (FIA) network; (2) an intensive, paired-site field study that will compare measurement approaches in undisturbed and commercially harvested stands, with tests of terrestrial laser scanning and tree-ring data for more representative quantification of aboveground biomass carbon stocks; and (3) the development of a novel, theoretically grounded approach to parameterizing allometric equations that surmounts key limitations of empirical methods. The research efforts will enable NEON, FLUXNET and the U.S. Forest Service to synthesize protocols amd relate overall inventories to individual flux tower sites. while providing training opportunities at the undergraduate, graduate student and postdoctoral levels. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.