Partitioning methane flux by the eddy covariance method in a cool temperate bog based on a Bayesian framework
Partitioning methane flux by the eddy covariance method in a cool temperate bog based on a Bayesian framework
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基于贝叶斯框架的寒温带沼泽涡流协方差法划分甲烷通量
DOI：
10.1016/j.agrformet.2022.108852
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发表时间：
2022
影响因子：
6.2
通讯作者：
R.
中科院分区：
文献类型：
--
作者：
Ueyama;M.;Yazaki;T.;Hirano;T.;Endo;R.
湿地CH4通量对环境驱动因子的响应是复杂的，由于其非线性性质，不容易解释。为了更好地了解所观察到的CH4通量，我们开发了一种方法来划分此通量为CH4生产，氧化，和三个运输途径。基于贝叶斯方法与六年涡度相关测量从一个凉爽的温带沼泽在日本北方，我们估计了一个简单的两层模型的参数，它认为在表面的氧化和深缺氧层的过程。约束模型解释了87%的变化，在观测到的CH4通量在每日到季节的时间尺度。该模型估计，64%的CH4是由沸腾运输相比，36%的植物介导的运输在无雪期间。该模型预测，CH4主要是从深缺氧层，而不是从表层排放。该模型解释了56%的CH4通量年际变化，这主要是由CH4生产控制。参数的后验分布取决于约束模型的数据覆盖范围，这强烈表明长期数据对于约束过程模型是不可或缺的。即使使用六年数据，所有参数也没有得到很好的约束，这可能是因为数据中没有包含足够的信息来约束这些过程。因此，该方法必须在各种湿地进行测试，并提供额外的长期数据，以评估其适用性和局限性。
The responses of CH4fluxes to environmental drivers are known to be complex in wetlands and are not easily interpreted due to their nonlinear nature. To better understand the observed CH4flux, we developed a method to partition this flux into CH4production, oxidation, and three transport pathways. Based on a Bayesian method with six-year eddy covariance measurements from a cool temperate bog in northern Japan, we estimated the parameters of a simple two-layer model, which considered the processes in surface oxic and deep anoxic layers. The constrained model explained 87% of the variation in the observed CH4flux at the daily to seasonal timescales. The model estimated that 64% of CH4was transported by ebullition compared with 36% by plant-mediated transport during snow-free periods. The model predicted that CH4was mostly emitted from the deep anoxic layer rather than from the surface layer. The model explained 56% of the interannual variations in the annual CH4flux, which was mostly controlled by CH4production. Posterior distributions of the parameters depended on the data coverage that constrained the model, strongly indicating that long-term data are indispensable for constraining process models. Even when using the six-year data, all parameters were not well constrained probably because the data did not contain enough information to constrain the processes. Thus, the method must be tested in various wetlands with additional long-term data to evaluate its applicability and limitations.
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影响因子：
5
作者：
D. Nadeau;A. Rousseau;C. Coursolle;H. Margolis;M. Parlange
通讯作者：
D. Nadeau;A. Rousseau;C. Coursolle;H. Margolis;M. Parlange
沼泽池底部地形的时空变化——温度效应及其对池发育的影响：以爱沙尼亚凸起沼泽为例
DOI：
--
发表时间：
2014
期刊：
影响因子：
--
作者：
E. Karofeld;H. Tõnisson
通讯作者：
H. Tõnisson
影响因子：
11.6
作者：
M. Turetsky;A. Kotowska;J. Bubier;N. Dise;P. Crill;E. Hornibrook;K. Minkkinen;T. Moore;I. Myers-Smith
通讯作者：
M. Turetsky;A. Kotowska;J. Bubier;N. Dise;P. Crill;E. Hornibrook;K. Minkkinen;T. Moore;I. Myers-Smith
影响因子：
5.1
作者：
J. Susiluoto;M. Raivonen;L. Backman;M. Laine;J. Mäkelä;O. Peltola;T. Vesala;T. Aalto
通讯作者：
J. Susiluoto;M. Raivonen;L. Backman;M. Laine;J. Mäkelä;O. Peltola;T. Vesala;T. Aalto
影响因子：
5.2
作者：
T. Tokida;T. Miyazaki;M. Mizoguchi;O. Nagata;F. Takakai;A. Kagemoto;R. Hatano
通讯作者：
T. Tokida;T. Miyazaki;M. Mizoguchi;O. Nagata;F. Takakai;A. Kagemoto;R. Hatano