Net CO2 emissions from dry inland waters persist in the presence of vegetation
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2026
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Wiley
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Sharma, K., Brothers, S., Bernal, S., Catalán, N., Keller, P., Koschorreck, M., et al. (2026). Net CO2 emissions from dry inland waters persist in the presence of vegetation. Global Biogeochemical Cycles, 40, e2025GB008801. https://doi.org/10.1029/2025GB008801
Abstract
Many inland waters are shrinking due to shifts in climate and water diversion for human uses. As they dry out, their exposed sediments emit large amounts of carbon dioxide (CO2) to the atmosphere. However, current global estimates of CO2 emissions from dry inland waters are derived exclusively from bare sediment dark-chamber measurements that do not account for the colonization of desiccated areas by vegetation. To understand the impact of vegetation on CO2 emissions from dry sediments, we analyzed 164 dry inland water bodies across five climatic regions and five inland water body types (lakes, ponds, reservoirs, streams and wetlands). On average, within vegetated zones, vegetation occupied 47 ± 35% in measured biomass quadrants. Light-induced decreases in instantaneous CO2 emissions in vegetated dry sediments were lower (mean ± SD = −3.7 ± 12.9 mmol CO2 m−2 hr−1) than increases during dark conditions (14.7 ± 20.1 mmol CO2 m−2 hr−1). Diel (24-hr) CO2 emissions from dry, vegetated sediments (mean ± SD = 100 ± 261 mmol CO2 m−2 d−1) were 25% lower than in bare sediments (133 ± 245 mmol CO2 m−2 d−1). These results indicate that vegetation can partially off-set sediment respiration, although the magnitude of this effect is insufficient to switch dry beds from net sources to net sinks of carbon.
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This study was made possible thanks to a large collective effort of a global research network called DryFlux (www.ufz.de/dryflux). This work is the result of an international team science effort facilitated by the Global Lake Ecological Observatory Network (GLEON). KS holds a predoctoral fellowship from AGAUR FI ajuts (2023 FI-1 00295), Joan Oró of the Secretariat of Universities and Research of the Department of Research and Universities of the Generalitat of Catalonia, and the European Social Plus Fund. The work of SBe was supported by the projects EVASIONA (PID2021-122817-NB-100) and RIPAMED (CNS2023-144737) funded by MICIU/AEI/FEDER-Next Generation. AP is currently supported by a “Ramón y Cajal” Fellowship (RYC2022-036661-I) of the Spanish Ministry of Science, Innovation and Universities. RM participation was funded by the Spanish Agencia Estatal de Investigación Grant PID2024-161534NB-C31/MICIU/AEI/10.13039/501100011033/FEDER,UE. BDE and JY were supported by ARC Grant DP220100918. LR was supported by Hong Kong RGC Grant 17306224. SBa was funded by the USGS Ecosystems Land Change Science Program and U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research (Grant DE-SC0023084). Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. USGS data can be found at Bansal et al. (2022). SS and SK were supported by the Department of Space, Government of India. Special thanks to D. Mercado (CEAB-CSIC) for their assistance with R coding, which greatly contributed to the analysis in this study. Lastly, KS appreciates the support and insights from her colleagues and mentors who have helped refine this work. NC was supported by Spanish Agencia Estatal de Investigacion Grant—PID2022-140848NA-C32.







