首页> 外文期刊>Journal of Advances in Modeling Earth Systems >Transient Traceability Analysis of Land Carbon Storage Dynamics: Procedures and Its Application to Two Forest Ecosystems
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Transient Traceability Analysis of Land Carbon Storage Dynamics: Procedures and Its Application to Two Forest Ecosystems

机译:土地碳储量动态的瞬态可溯性分析:程序及其在两个森林生态系统中的应用

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Uptake of anthropogenically emitted carbon (C) dioxide by terrestrial ecosystem is critical for determining future climate. However, Earth system models project large uncertainties in future C storage. To help identify sources of uncertainties in model predictions, this study develops a transient traceability framework to trace components of C storage dynamics. Transient C storage ( X ) can be decomposed into two components, C storage capacity ( X c ) and C storage potential ( X p ). X c is the maximum C amount that an ecosystem can potentially store and X p represents the internal capacity of an ecosystem to equilibrate C input and output for a network of pools. X c is codetermined by net primary production (NPP) and residence time (???? N ), with the latter being determined by allocation coefficients, transfer coefficients, environmental scalar, and exit rate. X p is the product of redistribution matrix (???? ch ) and net ecosystem exchange. We applied this framework to two contrasting ecosystems, Duke Forest and Harvard Forest with an ecosystem model. This framework helps identify the mechanisms underlying the responses of carbon cycling in the two forests to climate change. The temporal trajectories of X are similar between the two ecosystems. Using this framework, we found that different mechanisms lead to a similar trajectory between the two ecosystems. This framework has potential to reveal mechanisms behind transient C storage in response to various global change factors. It can also identify sources of uncertainties in predicted transient C storage across models and can therefore be useful for model intercomparison.
机译:陆地生态系统对人为排放的二氧化碳的吸收对于确定未来的气候至关重要。但是,地球系统模型预测未来的C存储存在很大的不确定性。为了帮助确定模型预测中的不确定性来源,本研究开发了一个瞬态可跟踪性框架来跟踪C存储动态的组成部分。瞬态C存储器(X)可以分解为两个部分,C存储器容量(X c)和C存储器电位(X p)。 X c是生态系统可以存储的最大C量,X p表示生态系统为池网络平衡C输入和输出的内部能力。 X c由净初级生产(NPP)和停留时间(ΔεN)决定,后者由分配系数,转移系数,环境标量和出口率确定。 X p是再分配矩阵(???? ch)与净生态系统交换的乘积。我们将此框架应用于具有生态系统模型的两个截然不同的生态系统,杜克森林和哈佛森林。该框架有助于确定两种森林中碳循环对气候变化的响应所依据的机制。 X的时间轨迹在两个生态系统之间是相似的。使用此框架,我们发现不同的机制导致两个生态系统之间的轨迹相似。该框架有潜力揭示瞬态C存储背后响应各种全局变化因素的机制。它还可以在模型间的预测瞬态C存储中识别不确定性来源,因此对于模型间的比较很有用。

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