Across‐model spread and shrinking in predicting peatland carbon dynamics under global change
Across‐model spread and shrinking in predicting peatland carbon dynamics under global change
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DOI：
10.1111/gcb.16643
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发表时间：
2023-02
影响因子：
11.6
通讯作者：
E. Hou;Shuang Ma;Yuanyuan Huang;Yu Zhou;Hyung-Sub Kim;E. López-Blanco;Lifen Jiang;J. Xia;F. Tao;Christopher Williams;M. Williams;D. Ricciuto;P. Hanson;Yiqi Luo
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作者：
E. Hou;Shuang Ma;Yuanyuan Huang;Yu Zhou;Hyung-Sub Kim;E. López-Blanco;Lifen Jiang;J. Xia;F. Tao;Christopher Williams;M. Williams;D. Ricciuto;P. Hanson;Yiqi Luo
在模式比较项目（MIPs）中，模拟土地碳(C)动态的大跨模式差异已被普遍证明，并成为推进气候变化预测的主要障碍。因此，必须确定这种蔓延的潜在来源。在这里，我们使用了一种新的矩阵方法来分析确定瞬态泥炭地碳动态中跨模型传播的来源，以响应两种大气二氧化碳水平和五种温度水平的析因组合。通过将8个土地模型（TEM、CENTURY4、DALEC2、TECO、FBDC、CASA、CLM4.5和ORCHIDEE）的C循环模块转换为8个矩阵模型，构建了基于矩阵的MIP模型。虽然生态系统碳储量的模型平均值与测量值相当，但模型之间的模拟差异很大，主要是由于模型间基线碳停留时间的差异。模型普遍高估了净生态系统产量（NEP），且差异较大，这主要归因于模型间环境标量的差异。根据确定的扩散来源，我们依次标准化模型参数，将模拟生态系统C存储和NEP缩小到几乎为零。模式总体上捕获了观测到的NEP对变暖的负响应，但由于基线C停留时间和分解的温度敏感性的差异，在响应幅度上存在很大差异。虽然在测量中缺乏NEP对升高的CO2 （eCO2）浓度的响应，但在大多数模型中，模拟的NEP对eCO2浓度的响应是正的，这是由于模拟的净初级生产量的正响应。我们的研究使用了明尼苏达州泥炭地的一个案例研究来证明，在模拟瞬态碳动力学时，跨模型传播的来源可以精确地追溯到模型结构和参数，而不管它们的复杂性如何，因为所有矩阵模型都是由相同的初级生产总量和环境变量驱动的。
Large across‐model spread in simulating land carbon (C) dynamics has been ubiquitously demonstrated in model intercomparison projects (MIPs), and became a major impediment in advancing climate change prediction. Thus, it is imperative to identify underlying sources of the spread. Here, we used a novel matrix approach to analytically pin down the sources of across‐model spread in transient peatland C dynamics in response to a factorial combination of two atmospheric CO2 levels and five temperature levels. We developed a matrix‐based MIP by converting the C cycle module of eight land models (i.e., TEM, CENTURY4, DALEC2, TECO, FBDC, CASA, CLM4.5 and ORCHIDEE) into eight matrix models. While the model average of ecosystem C storage was comparable to the measurement, the simulation differed largely among models, mainly due to inter‐model difference in baseline C residence time. Models generally overestimated net ecosystem production (NEP), with a large spread that was mainly attributed to inter‐model difference in environmental scalar. Based on the sources of spreads identified, we sequentially standardized model parameters to shrink simulated ecosystem C storage and NEP to almost none. Models generally captured the observed negative response of NEP to warming, but differed largely in the magnitude of response, due to differences in baseline C residence time and temperature sensitivity of decomposition. While there was a lack of response of NEP to elevated CO2 (eCO2) concentrations in the measurements, simulated NEP responded positively to eCO2 concentrations in most models, due to the positive responses of simulated net primary production. Our study used one case study in Minnesota peatland to demonstrate that the sources of across‐model spreads in simulating transient C dynamics can be precisely traced to model structures and parameters, regardless of their complexity, given the protocol that all the matrix models were driven by the same gross primary production and environmental variables.