Drivers and Annual Totals of Methane Emissions From Dutch Peatlands

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.

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Main Authors: Buzacott, Alexander J.V., Kruijt, Bart, Bataille, Laurent, van Giersbergen, Quint, Heuts, Tom S., Fritz, Christian, Nouta, Reinder, Erkens, Gilles, Boonman, Jim, van den Berg, Merit, van Huissteden, Jacobus, van der Velde, Ype
Format: Article/Letter to editor biblioteca
Language:English
Subjects:CH, eddy covariance, flux driver, greenhouse gas, land use change, machine learning, rewet,
Online Access:https://research.wur.nl/en/publications/drivers-and-annual-totals-of-methane-emissions-from-dutch-peatlan
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spelling dig-wur-nl-wurpubs-6389102024-12-20 Buzacott, Alexander J.V. Kruijt, Bart Bataille, Laurent van Giersbergen, Quint Heuts, Tom S. Fritz, Christian Nouta, Reinder Erkens, Gilles Boonman, Jim van den Berg, Merit van Huissteden, Jacobus van der Velde, Ype Article/Letter to editor Global Change Biology 30 (2024) 12 ISSN: 1354-1013 Drivers and Annual Totals of Methane Emissions From Dutch Peatlands 2024 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. en application/pdf https://research.wur.nl/en/publications/drivers-and-annual-totals-of-methane-emissions-from-dutch-peatlan 10.1111/gcb.17590 https://edepot.wur.nl/683506 CH eddy covariance flux driver greenhouse gas land use change machine learning rewet https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/ Wageningen University & Research
institution WUR NL
collection DSpace
country Países bajos
countrycode NL
component Bibliográfico
access En linea
databasecode dig-wur-nl
tag biblioteca
region Europa del Oeste
libraryname WUR Library Netherlands
language English
topic CH
eddy covariance
flux driver
greenhouse gas
land use change
machine learning
rewet
CH
eddy covariance
flux driver
greenhouse gas
land use change
machine learning
rewet
spellingShingle CH
eddy covariance
flux driver
greenhouse gas
land use change
machine learning
rewet
CH
eddy covariance
flux driver
greenhouse gas
land use change
machine learning
rewet
Buzacott, Alexander J.V.
Kruijt, Bart
Bataille, Laurent
van Giersbergen, Quint
Heuts, Tom S.
Fritz, Christian
Nouta, Reinder
Erkens, Gilles
Boonman, Jim
van den Berg, Merit
van Huissteden, Jacobus
van der Velde, Ype
Drivers and Annual Totals of Methane Emissions From Dutch Peatlands
description 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.
format Article/Letter to editor
topic_facet CH
eddy covariance
flux driver
greenhouse gas
land use change
machine learning
rewet
author Buzacott, Alexander J.V.
Kruijt, Bart
Bataille, Laurent
van Giersbergen, Quint
Heuts, Tom S.
Fritz, Christian
Nouta, Reinder
Erkens, Gilles
Boonman, Jim
van den Berg, Merit
van Huissteden, Jacobus
van der Velde, Ype
author_facet Buzacott, Alexander J.V.
Kruijt, Bart
Bataille, Laurent
van Giersbergen, Quint
Heuts, Tom S.
Fritz, Christian
Nouta, Reinder
Erkens, Gilles
Boonman, Jim
van den Berg, Merit
van Huissteden, Jacobus
van der Velde, Ype
author_sort Buzacott, Alexander J.V.
title Drivers and Annual Totals of Methane Emissions From Dutch Peatlands
title_short Drivers and Annual Totals of Methane Emissions From Dutch Peatlands
title_full Drivers and Annual Totals of Methane Emissions From Dutch Peatlands
title_fullStr Drivers and Annual Totals of Methane Emissions From Dutch Peatlands
title_full_unstemmed Drivers and Annual Totals of Methane Emissions From Dutch Peatlands
title_sort drivers and annual totals of methane emissions from dutch peatlands
url https://research.wur.nl/en/publications/drivers-and-annual-totals-of-methane-emissions-from-dutch-peatlan
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