Abstract
extreme drought events are predicted to increase with climate change, yet their impacts on ecosystem carbon dynamics under warming and elevated carbon dioxide (ecO2) remain unclear. In a peatland experiment with five warming treatments each under ambient carbon dioxide (acO2) and ecO2 (+500 parts per million), a 2-month extreme drought in 2021 reduced net ecosystem productivity by 444.0 ± 65.8 and 736.6 ± 57.8 grams of carbon per square meter at +9°c under acO2 and ecO2, respectively—228.6 ± 56.8% and 381.9 ± 83.4% of the reduction at +0°c under acO2. this exacerbation was driven by warming-induced water table decline, prolonged low water tables, and cO2-enhanced substrate availability through increased plant carbon inputs. Findings indicate that future climate will greatly amplify carbon loss during extreme drought, reinforcing positive carbon-climate feedbacks.
| Original language | English |
|---|---|
| Pages (from-to) | 367-370 |
| Number of pages | 4 |
| Journal | Science |
| Volume | 390 |
| Issue number | 6771 |
| DOIs | |
| State | Published - Oct 23 2025 |
Funding
We thank the SPRUCE program and team for supporting this study. We thank the many researchers who contributed data to the SPRUCE project database. This research was conducted under the Terrestrial Ecosystem Sciences Scientific Focus Area at Oak Ridge National Laboratory (ORNL), a program funded by the US Department of Energy (DOE), Office of Science, and the Office of Biological and Environmental Research. ORNL operates under the management of UT-Battelle for the DOE under contract DE-AC05-1008 00OR22725. The contributions from Y.L. EcoLab at Cornell University were supported in part by funding from the US National Science Foundation (NSF; grants DEB 2242034, DEB 2406930, and DEB 2425290), as well as by the DOE’s Terrestrial Ecosystem Sciences Grant (DESC0023514). Additional support was provided through the “NYS Connects: Climate Smart Farms & Forestry” project, funded collaboratively by the US Department of Agriculture (USDA), the New York State Department of Environmental Conservation, and the New York State Department of Agriculture and Markets. This work is also part of the AI Institute for Land, Economy, Agriculture and Forestry (AI-LEAF), supported by the USDA National Institute of Food and Agriculture (NIFA) and the NSF National AI Research Institutes Competitive Award (2023-67021-39829). Contributions by J.E.K., J.P.C., and R.M.W. were supported in part by the Office of Biological and Environmental Research, Genomic Science Program, under DOE contract DE-SC0023297). Contributions and long-term monitoring by S.D.S. at the Marcell Experimental Forest were supported by the USDA Forest Service, Northern Research Station. Contributions by D.W. were supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) Strategic Project Grant STPGP 521445-18. We thank the SPRUCE program and team for supporting this study.We thank the many researchers who contributed data to the SPRUCE project database. Funding: This research was conducted under the Terrestrial Ecosystem Sciences Scientific Focus Area at Oak Ridge National Laboratory (ORNL), a program funded by the US Department of Energy (DOE), Office of Science, and the Office of Biological and Environmental Research. ORNL operates under the management of UT-Battelle for the DOE under contract DE-AC05-1008 00OR22725.The contributions from Y.L. EcoLab at Cornell University were supported in part by funding from the US National Science Foundation (NSF; grants DEB 2242034, DEB 2406930, and DEB 2425290), as well as by the DOE’s Terrestrial Ecosystem Sciences Grant (DESC0023514). Additional support was provided through the “NYS Connects: Climate Smart Farms & Forestry”project, funded collaboratively by the US Department of Agriculture (USDA), the New York State Department of Environmental Conservation, and the New York State Department of Agriculture and Markets.This work is also part of the AI Institute for Land, Economy,Agriculture and Forestry (AI-LEAF), supported by the USDA National Institute of Food and Agriculture (NIFA) and the NSF National AI Research Institutes Competitive Award (2023-67021-39829). Contributions by J.E.K.,J.P.C., and R.M.W. were supported in part by the Office of Biological and Environmental Research, Genomic Science Program, under DOE contract DE-SC0023297). Contributions and long-term monitoring by S.D.S. at the Marcell Experimental Forest were supported by the USDA Forest Service, Northern Research Station. Contributions by D.W. were supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) Strategic Project Grant STPGP 521445-18. Author contributions: Conceptualization: Y.L. and Q.Q. Project administration: P.J.H. Data curation: P.J.H. Investigation: P.J.H., S.D.S., D.J.W.,J.P.C., R.M.W.,J.E.K., M.A.M.,J.M.S.,A.D.R., M.E.D., D.W., and J.M.W.Visualization: Q.Q.,J.Z., and Y.L.Writing – original draft: Q.Q.,J.Z., and Y.L.Writing – review & editing: Q.Q., P.J.H., D.R., S.D.S., D.J.W.,J.P.C., R.M.W.,J.E.K.,J.M.W.,J.Z.,Y.Z., N.W., L.J., M.A.M.,J.M.S.,A.D.R., M.E.D., D.W., and Y.L. Competing interests: The authors declare that they have no competing interests. Data and materials availability: All data and code used in this paper have been deposited in figshare (https://doi.org/10.6084/m9. figshare.27857655) (76).All the datasets are also cited in the materials and methods and publicly available in the online SPRUCE project archive at http://mnspruce.ornl.gov (77). License information: Copyright © 2025 the authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original US government works. https://www.science.org/about/science-licenses-journal-article-reuse