Guo Haonan, Cui Shihao, Nielsen Claudia Kalla, Pullens Johannes Wilhelmus Maria, Qiu Chunjing, Wu Shubiao
Department of Agroecology, Aarhus University, Tjele 8830, Denmark.
Research Center for Global Change and Complex Ecosystems, School of Ecological and Environmental Sciences, East China Normal University, Shanghai 200241, China.
Environ Sci Technol. 2024 Aug 12;58(34):15052-65. doi: 10.1021/acs.est.4c06057.
Methane fluxes (FCH) vary significantly across wetland ecosystems due to complex mechanisms, challenging accurate estimations. The interactions among environmental drivers, while crucial in regulating FCH, have not been well understood. Here, the interactive effects of six environmental drivers on FCH were first analyzed using 396,322 half-hourly measurements from 22 sites across various wetland types and climate zones. Results reveal that soil temperature, latent heat turbulent flux, and ecosystem respiration primarily exerted direct effects on FCH, while air temperature and gross primary productivity mainly exerted indirect effects by interacting with other drivers. Significant spatial variability in FCH regulatory mechanisms was highlighted, with different drivers demonstrated varying direct, indirect, and total effects among sites. This spatial variability was then linked to site-specific annual-average air temperature (17.7%) and water table (9.0%) conditions, allowing the categorization of CH sources into four groups with identified critical drivers. An improved estimation approach using a random forest model with three critical drivers was consequently proposed, offering accurate FCH predictions with fewer input requirements. By explicitly accounting for environmental interactions and interpreting spatial variability, this study enhances our understanding of the mechanisms regulating CH emissions, contributing to more efficient modeling and estimation of wetland FCH.
由于机制复杂，甲烷通量（FCH）在不同湿地生态系统中差异显著，这给准确估算带来了挑战。环境驱动因素之间的相互作用虽然在调节FCH方面至关重要，但尚未得到很好的理解。在此，首先利用来自不同湿地类型和气候区的22个站点的396322个半小时测量数据，分析了六种环境驱动因素对FCH的交互作用。结果表明，土壤温度、潜热湍流通量和生态系统呼吸主要对FCH产生直接影响，而气温和总初级生产力主要通过与其他驱动因素相互作用产生间接影响。研究突出了FCH调节机制的显著空间变异性，不同驱动因素在各站点间表现出不同的直接、间接和总效应。然后将这种空间变异性与特定站点的年平均气温（17.7%）和地下水位（9.0%）条件联系起来，从而将CH源分为四组，并确定了关键驱动因素。因此，提出了一种使用具有三个关键驱动因素的随机森林模型的改进估算方法，该方法以较少的输入要求提供了准确的FCH预测。通过明确考虑环境相互作用并解释空间变异性，本研究增进了我们对CH排放调节机制的理解，有助于更有效地对湿地FCH进行建模和估算。
