Wu et al. (2026): Forest carbon protocols underestimate climate-driven carbon loss risks
Chao Wu, Grayson Badgley, Michael L. Goulden, James T. Randerson, Anna T. Trugman, Jonathan A. Wang, Linqing Yang, Nezha Acil, Susan C. Cook-Patton, Danny Cullenward, Steven J. Davis, Christopher A. Williams and William R. L. Anderegg, IN: Nature, https://doi.org/10.1038/s41586-026-10571-y
Although the reduction of fossil fuel emissions remains of the utmost importance to mitigate climate change, maintaining and enhancing carbon sinks in forests have been widely promoted as nature-based climate solutions1,2,3,4. However, disturbances that could result in losses of forest carbon stocks are poorly accounted for when estimating the potential role of forests in climate mitigation5,6,7. This makes it difficult to appropriately size ‘buffer pools’: a mechanism designed to compensate for unintended carbon losses in carbon crediting projects8,9. Here the authors use forest inventory, satellite data, disturbance modelling and machine learning to map reversal (carbon loss) risk in the contiguous United States (CONUS) from natural disturbance.