Alexander J. V. Buzacott, Bart Kruijt, Laurent Bataille, Quint van Giersbergen, Tom S. Heuts, Christian Fritz, Reinder Nouta, Gilles Erkens, Jim Boonman, Merit van den Berg, Jacobus van Huissteden, Ype van der Velde
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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 FCH<sub>4</sub> 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 FCH<sub>4</sub> 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 FCH<sub>4</sub>. Mean annual FCH<sub>4</sub> totals across all land uses ranged from 90 <sub>±</sub> 11 to 632 <sub>±</sub> 65 kg CH<sub>4</sub> ha<sup>−1</sup> year<sup>−1</sup> 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 (<i>R</i><sup>2</sup> = 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 CO<sub>2</sub> uptake and long-term storage are required to fully offset the emissions of CH<sub>4</sub> from land uses with high GWLs.</p>","PeriodicalId":175,"journal":{"name":"Global Change Biology","volume":"30 12","pages":""},"PeriodicalIF":10.8000,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gcb.17590","citationCount":"0","resultStr":"{\"title\":\"Drivers and Annual Totals of Methane Emissions From Dutch Peatlands\",\"authors\":\"Alexander J. V. Buzacott, Bart Kruijt, Laurent Bataille, Quint van Giersbergen, Tom S. 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引用次数: 0
摘要
为了限制二氧化碳(CO2)的排放,泥炭地需要重新湿润,然而,提高地下水位(GWL)将大大增加甲烷(CH4)排放的机会,而甲烷(CH4)的辐射强迫高于二氧化碳。来自不同复湿策略和自然系统的CH4数据集很少,需要对CH4排放的主要驱动因素进行量化和理解,以制定有效的泥炭地复湿决策。我们提供了荷兰泥炭地16个地点测量的CH4通量(FCH4)的大型数据集。这些地点被划分为六种土地用途,这也决定了它们的植被和GWL范围。我们调查了排放的主要驱动因素,并使用机器学习(ML)对数据进行填补,以得出年度总量。此外,Shapley值用于理解驱动程序对ML模型预测的重要性。结果表明,FCH4的典型控制因子以温度和GWL为主导因子,但某些关系依赖于土地利用和植被。随着gwl的增加,FCH4的平均排放量明显增加,其中地表附近的gwl排放最高。土壤温度是最重要的预测因子,但Shapley值揭示了FCH4的多驱动依赖性。所有土地利用的年平均CH4总量在90±11 ~ 632±65 kg CH4 ha - 1 - 1年之间,半自然土地利用的平均CH4总量最高,其次是古牧、湖泊、湿草地和有水渗透系统的牧场。年平均通量与年平均GWL呈极显著相关(R2 = 0.80)。为了确定净气候影响,我们仍然需要估算这些地点的温室气体平衡,然而,我们的研究结果表明,要完全抵消高gwl土地利用产生的CH4排放,需要相当大的CO2吸收和长期储存速率。
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.
期刊介绍:
Global Change Biology is an environmental change journal committed to shaping the future and addressing the world's most pressing challenges, including sustainability, climate change, environmental protection, food and water safety, and global health.
Dedicated to fostering a profound understanding of the impacts of global change on biological systems and offering innovative solutions, the journal publishes a diverse range of content, including primary research articles, technical advances, research reviews, reports, opinions, perspectives, commentaries, and letters. Starting with the 2024 volume, Global Change Biology will transition to an online-only format, enhancing accessibility and contributing to the evolution of scholarly communication.