Mechanistic Modeling of Microtopographic Impacts on CO 2 and CH 4 Fluxes in an Alaskan Tundra Ecosystem Using the CLM‐Microbe Model
Mechanistic Modeling of Microtopographic Impacts on CO 2 and CH 4 Fluxes in an Alaskan Tundra Ecosystem Using the CLM‐Microbe Model
复制标题
使用 CLM–微生物模型建立阿拉斯加苔原生态系统中微地形对 CO 2 和 CH 4 通量影响的机制模型
DOI：
10.1029/2019ms001771
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发表时间：
2019
影响因子：
6.8
通讯作者：
Zona, Donatella
中科院分区：
文献类型：
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作者：
Wang, Yihui;Yuan, Fengming;Yuan, Fenghui;Gu, Baohua;Hahn, Melanie S.;Torn, Margaret S.;Ricciuto, Daniel M.;Kumar, Jitendra;He, Liyuan;Zona, Donatella
土壤水文的空间异质性是北极冻原生态系统CO2和CH 4通量的重要控制因素。在这项研究中，我们应用了一个机械生态系统模型，CLM-Microbe，研究微地形对CO2和CH 4通量的影响，在Utqiavik，阿拉斯加7种景观类型：槽，低中心多边形（LCP）中心，LCP过渡，LCP边缘，高中心多边形（HCP）中心，HCP过渡和HCP边缘。我们首先验证了CLM-Microbe模型对静态室测量的CO2和CH 4通量在2013年为三种景观类型：槽，LCP中心，LCP边缘。模型应用表明，低海拔，因此更潮湿的景观类型（即，槽，过渡，和LCP中心）有较大的CH 4排放率更大的季节变化比高海拔和干燥的景观类型（边缘和HCP中心）。敏感性分析表明，甲烷生成的基质有效性（乙酸盐、CO2+ H2）是决定北极冻原生态系统CH 4排放的最重要因素，植被生理特性对北极冻原生态系统的净碳交换和生态系统呼吸具有重要影响。模拟不同微地形特征的CH 4排放量在与EC测量的CH 4通量进行验证之前，使用面积加权方法将其放大到涡度相关（EC）域。该模型在每日和每小时的时间步长上分别低估了20%和25%的EC测量的CH 4通量，这表明了时间步长在报告CH 4通量中的重要性。强烈的微地形对CO2和CH 4通量的影响需要一个模型-数据集成框架，以更好地理解和预测高度异质性的北极景观中的碳通量。
Spatial heterogeneities in soil hydrology have been confirmed as a key control on CO2and CH4fluxes in the Arctic tundra ecosystem. In this study, we applied a mechanistic ecosystem model, CLM‐Microbe, to examine the microtopographic impacts on CO2and CH4fluxes across seven landscape types in Utqiaġvik, Alaska: trough, low‐centered polygon (LCP) center, LCP transition, LCP rim, high‐centered polygon (HCP) center, HCP transition, and HCP rim. We first validated the CLM‐Microbe model against static‐chamber measured CO2and CH4fluxes in 2013 for three landscape types: trough, LCP center, and LCP rim. Model application showed that low‐elevation and thus wetter landscape types (i.e., trough, transitions, and LCP center) had larger CH4emissions rates with greater seasonal variations than high‐elevation and drier landscape types (rims and HCP center). Sensitivity analysis indicated that substrate availability for methanogenesis (acetate, CO2+ H2) is the most important factor determining CH4emission, and vegetation physiological properties largely affect the net ecosystem carbon exchange and ecosystem respiration in Arctic tundra ecosystems. Modeled CH4emissions for different microtopographic features were upscaled to the eddy covariance (EC) domain with an area‐weighted approach before validation against EC‐measured CH4fluxes. The model underestimated the EC‐measured CH4flux by 20% and 25% at daily and hourly time steps, suggesting the importance of the time step in reporting CH4flux. The strong microtopographic impacts on CO2and CH4fluxes call for a model‐data integration framework for better understanding and predicting carbon flux in the highly heterogeneous Arctic landscape.