Zhang Haicheng, Goll Daniel S, Wang Ying-Ping, Ciais Philippe, Wieder William R, Abramoff Rose, Huang Yuanyuan, Guenet Bertrand, Prescher Anne-Katrin, Viscarra Rossel Raphael A, Barré Pierre, Chenu Claire, Zhou Guoyi, Tang Xuli
Le Laboratoire des Sciences du Climat et de l'Environnement, IPSL-LSCECEA/CNRS/UVSQ Saclay, Gif-sur-Yvette, France.
Department Geoscience, Environment & Society, Université Libre de Bruxelles, Bruxelles, Belgium.
Glob Chang Biol. 2020 Apr;26(4):2668-2685. doi: 10.1111/gcb.14994. Epub 2020 Feb 12.
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.
大多数地球系统模型(ESM)都使用一阶有机物质分解模型来预测未来全球碳循环;这些模型因未能准确描述土壤有机碳(SOC)稳定机制以及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培养或少数野外实验的观测结果。鉴于ESM的全球范围,在将此类模型引入ESM之前,使用大空间尺度上广泛的SOC储量原位观测对其进行全面评估至关重要。在本研究中,我们收集了来自欧洲和中国206个覆盖不同森林和土壤类型地点的SOC、凋落物和土壤性质的一组原位观测数据。这些数据用于校准模型MIMICS(微生物-矿物碳稳定模型),并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能更准确地估计森林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地点的独立观测结果吻合良好。通过在MIMICS中测试关于SOC脱保护和微生物周转的物理化学约束的不同假设(使用替代过程表示),各地点模拟SOC浓度的误差进一步降低。我们表明,MIMICS能够解析SOC分解和稳定的主导机制,并且它可以成为预测未来气候变化下陆地SOC动态的可靠工具。它还使我们能够基于实验室和有限的实地观测,在大尺度上评估对SOC形成和稳定的快速发展的理解。