Microbial dynamics and soil physicochemical properties explain large‐scale variations in soil organic carbon
Microbial dynamics and soil physicochemical properties explain large‐scale variations in soil organic carbon
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DOI：
10.1111/gcb.14994
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发表时间：
2020-01
影响因子：
11.6
通讯作者：
Haicheng Zhang;D. Goll;Ying‐ping Wang;P. Ciais;W. Wieder;R. Abramoff;Yuanyuan Huang;B. Guenet
中科院分区：
文献类型：
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作者：
Haicheng Zhang;D. Goll;Ying‐ping Wang;P. Ciais;W. Wieder;R. Abramoff;Yuanyuan Huang;B. Guenet
大多数地球系统模型（ESM）都使用一阶有机物分解模型来预测未来的全球碳循环；这些模型因无法准确反映土壤有机碳 (SOC) 稳定机制和 SOC 对气候变化的响应而受到批评。新的土壤生物地球化学模型已经开发出来，但其评估仅限于实验室孵化或少量现场实验的观察。考虑到 ESM 的全球范围，在将其引入 ESM 之前，必须利用对大空间范围内各种 SOC 库的现场观测来对此类模型进行综合评估。在这项研究中，我们收集了来自欧洲和中国不同森林和土壤类型的 206 个地点的 SOC、凋落物和土壤特性的一组现场观测数据。这些数据用于校准模型 MIMICS（微生物-矿物碳稳定模型），我们将其与广泛使用的一阶模型 CENTURY 进行比较。我们表明，与 CENTURY 相比，MIMICS 可以更准确地估计森林 SOC 浓度以及 SOC 对土壤温度、粘土含量和凋落物输入变化的敏感性。 MIMICS 预测的微生物生物量与总 SOC 的比率与全球分布森林站点的独立观测结果非常吻合。通过测试有关（使用替代过程表示）MIMICS 中 SOC 脱保护和微生物周转的物理化学限制的不同假设，跨站点模拟 SOC 浓度的误差进一步减小。我们表明，MIMICS 可以解决 SOC 分解和稳定的主导机制，并且可以成为预测未来气候变化下陆地 SOC 动态的可靠工具。它还使我们能够根据实验室和有限现场观察大规模评估对 SOC 形成和稳定的快速发展的理解。
First‐order organic matter decomposition models are used within most Earth System Models (ESMs) to project future global carbon cycling; these models have been criticized for not accurately representing mechanisms of soil organic carbon (SOC) stabilization and SOC response to climate change. New soil biogeochemical models have been developed, but their evaluation is limited to observations from laboratory incubations or few field experiments. Given the global scope of ESMs, a comprehensive evaluation of such models is essential using in situ observations of a wide range of SOC stocks over large spatial scales before their introduction to ESMs. In this study, we collected a set of in situ observations of SOC, litterfall and soil properties from 206 sites covering different forest and soil types in Europe and China. These data were used to calibrate the model MIMICS (The MIcrobial‐MIneral Carbon Stabilization model), which we compared to the widely used first‐order model CENTURY. We show that, compared to CENTURY, MIMICS more accurately estimates forest SOC concentrations and the sensitivities of SOC to variation in soil temperature, clay content and litter input. The ratios of microbial biomass to total SOC predicted by MIMICS agree well with independent observations from globally distributed forest sites. By testing different hypotheses regarding (using alternative process representations) the physicochemical constraints on SOC deprotection and microbial turnover in MIMICS, the errors of simulated SOC concentrations across sites were further decreased. We show that MIMICS can resolve the dominant mechanisms of SOC decomposition and stabilization and that it can be a reliable tool for predictions of terrestrial SOC dynamics under future climate change. It also allows us to evaluate at large scale the rapidly evolving understanding of SOC formation and stabilization based on laboratory and limited filed observation.