Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma.
Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, Tennessee.
Glob Chang Biol. 2018 Oct;24(10):4946-4959. doi: 10.1111/gcb.14325. Epub 2018 Jun 12.
Climate warming can result in both abiotic (e.g., permafrost thaw) and biotic (e.g., microbial functional genes) changes in Arctic tundra. Recent research has incorporated dynamic permafrost thaw in Earth system models (ESMs) and indicates that Arctic tundra could be a significant future carbon (C) source due to the enhanced decomposition of thawed deep soil C. However, warming-induced biotic changes may influence biologically related parameters and the consequent projections in ESMs. How model parameters associated with biotic responses will change under warming and to what extent these changes affect projected C budgets have not been carefully examined. In this study, we synthesized six data sets over 5 years from a soil warming experiment at the Eight Mile Lake, Alaska, into the Terrestrial ECOsystem (TECO) model with a probabilistic inversion approach. The TECO model used multiple soil layers to track dynamics of thawed soil under different treatments. Our results show that warming increased light use efficiency of vegetation photosynthesis but decreased baseline (i.e., environment-corrected) turnover rates of SOC in both the fast and slow pools in comparison with those under control. Moreover, the parameter changes generally amplified over time, suggesting processes of gradual physiological acclimation and functional gene shifts of both plants and microbes. The TECO model predicted that field warming from 2009 to 2013 resulted in cumulative C losses of 224 or 87 g/m , respectively, without or with changes in those parameters. Thus, warming-induced parameter changes reduced predicted soil C loss by 61%. Our study suggests that it is critical to incorporate biotic changes in ESMs to improve the model performance in predicting C dynamics in permafrost regions.
气候变暖会导致北极苔原发生非生物（如永冻层解冻）和生物变化（如微生物功能基因）。最近的研究已经将动态永冻层解冻纳入地球系统模型（ESMs）中，并表明由于解冻深层土壤 C 的分解增强，北极苔原可能成为未来重要的碳（C）源。然而，变暖引起的生物变化可能会影响与生物相关的参数和 ESMs 中的后续预测。在变暖条件下与生物响应相关的模型参数将如何变化，以及这些变化对预测的 C 预算的影响程度，尚未得到仔细研究。在这项研究中，我们使用概率反演方法将阿拉斯加八英里湖的一项土壤增温实验的六个数据集在陆地生态系统（TECO）模型中进行了五年的综合分析。TECO 模型使用多个土壤层来跟踪不同处理下解冻土壤的动态变化。研究结果表明，与对照相比，增温增加了植被光合作用的光利用效率，但降低了快和慢库中 SOC 的基线（即经环境校正的周转速率）。此外，参数变化随着时间的推移普遍放大，表明植物和微生物的生理逐渐适应和功能基因的转变过程。TECO 模型预测，2009 年至 2013 年田间增温分别导致 224 或 87 g/m 的累积 C 损失，而不考虑或考虑这些参数的变化。因此，变暖引起的参数变化使预测的土壤 C 损失减少了 61%。本研究表明，在 ESMs 中纳入生物变化对于提高模型在预测永久冻土区 C 动态方面的性能至关重要。
