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Uncertainty in US forest carbon storage potential due to climate risks

Forests have considerable potential to mitigate anthropogenic climate change through carbon sequestration, as well as provide society with substantial co-benefits. However, climate change risks may fundamentally compromise the permanence of forest carbon storage. Here, we conduct a multi-method synt...

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Bibliographic Details
Published in:Nature geoscience 2023-05, Vol.16 (5), p.422-429
Main Authors: Wu, Chao, Coffield, Shane R., Goulden, Michael L., Randerson, James T., Trugman, Anna T., Anderegg, William R. L.
Format: Article
Language:English
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Summary:Forests have considerable potential to mitigate anthropogenic climate change through carbon sequestration, as well as provide society with substantial co-benefits. However, climate change risks may fundamentally compromise the permanence of forest carbon storage. Here, we conduct a multi-method synthesis of contiguous US forest aboveground carbon storage potential at both regional and species levels through a fusion of historical and future climate projections, extensive forest inventory plots datasets, machine learning/niche models, and mechanistic land surface model ensemble outputs. We find diverging signs and magnitudes of projected future forest aboveground carbon storage potential across contrasting approaches, ranging from an average total gain of 6.7 Pg C to a loss of 0.9 Pg C, in a moderate-emissions scenario. The Great Lakes region and the northeastern United States showed consistent signs of carbon gains across approaches and future scenarios. Substantial risks of carbon losses were found in regions where forest carbon offset projects are currently located. This multi-method assessment highlights the current striking uncertainty in US forest carbon storage potential estimates and provides a critical foundation to guide forest conservation, restoration and nature-based climate solutions. Projections of forest aboveground carbon storage potential in the United States show divergent results across different modelling approaches due to uncertainties in the estimated impact of climate risks, according to a comparison of modelling results.
ISSN:1752-0894
1752-0908
DOI:10.1038/s41561-023-01166-7