Abstract
Rewetting peatlands is required to limit carbon dioxide (CO2) emissions, however, raising the groundwater level (GWL) will strongly increase the chance of methane (CH4) emissions which has a higher radiative forcing than CO2. Data sets of CH4 from different rewetting strategies and natural systems are scarce, and quantification and an understanding of the main drivers of CH4 emissions are needed to make effective peatland rewetting decisions. We present a large data set of CH4 fluxes (FCH4) measured across 16 sites with eddy covariance on Dutch peatlands. Sites were classified into six land uses, which also determined their vegetation and GWL range. We investigated the principal drivers of emissions and gapfilled the data using machine learning (ML) to derive annual totals. In addition, Shapley values were used to understand the importance of drivers to ML model predictions. The data showed the typical controls of FCH4 where temperature and the GWL were the dominant factors, however, some relationships were dependent on land use and the vegetation present. There was a clear average increase in FCH4 with increasing GWLs, with the highest emissions occurring at GWLs near the surface. Soil temperature was the single most important predictor for ML gapfilling but the Shapley values revealed the multi-driver dependency of FCH4. Mean annual FCH4 totals across all land uses ranged from 90 ± 11 to 632 ± 65 kg CH4 ha−1 year−1 and were on average highest for semi-natural land uses, followed by paludiculture, lake, wet grassland and pasture with water infiltration system. The mean annual flux was strongly correlated with the mean annual GWL (R2 = 0.80). The greenhouse gas balance of our sites still needs to be estimated to determine the net climate impact, however, our results indicate that considerable rates of CO2 uptake and long-term storage are required to fully offset the emissions of CH4 from land uses with high GWLs.
Original language | English |
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Article number | e17590 |
Pages (from-to) | 1-22 |
Number of pages | 22 |
Journal | Global Change Biology |
Volume | 30 |
Issue number | 12 |
Early online date | 6 Dec 2024 |
DOIs | |
Publication status | Published - Dec 2024 |
Bibliographical note
Publisher Copyright:© 2024 The Author(s). Global Change Biology published by John Wiley & Sons Ltd.
Funding
This work was supported by Ministerie van Landbouw, Natuur en Voedselkwaliteit, Stichting Toegepast Onderzoek Waterbeheer, Natuurmonumenten and Provincie Frysl\u00E2n. Funding: We kindly thank two anonymous reviewers for their insightful comments and suggestions that helped improve this manuscript. This study was conducted as part of the Netherlands Research Programme on Greenhouse Gas Dynamics in Peatlands and Organic Soils [in Dutch: Nationaal onderzoeksprogramma broeikasgassen veenweiden (NOBV)] that was funded by the Dutch government [Ministry of Agriculture, Nature, and Food Quality (LNV)]. The Frisian measurement sites (Hommerts, Lytse Deelen, De Burd) are part of research financed by the province of Frysl\u00E2n. Onlanden and Camphuys were co\u2010financed and managed by Natuurmonumenten and their local staff and volunteers. We would like to thank the support of field workers and technical support staff: Jan Biermann, Wietse Franssen, Hanne Berghuis, Wilma Jans, Corine van Huissteden, Ron Lootens and Arie Bikker.
Funders | Funder number |
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Natuur en Voedselkwaliteit | |
Stichting Toegepast Onderzoek Waterbeheer | |
Dutch Government | |
Nationaal onderzoeksprogramma broeikasgassen veenweiden | |
Ministerie van Landbouw | |
Ministry of Agriculture of the People's Republic of China | |
Netherlands Research Programme on Greenhouse Gas Dynamics in Peatlands and Organic Soils |
Keywords
- CH
- eddy covariance
- flux driver
- greenhouse gas
- land use change
- machine learning
- rewet