Mineral and Climatic Controls Over Soil Organic Matter Stability Across the Tibetan Alpine Permafrost Region

永久冻土 自然地理学 土壤有机质 环境科学 气候变化 土壤学 地质学 土壤碳 土壤水分 高原(数学) 土壤科学 空间变异性 空间生态学 地球科学 大气科学 生态学 地理 海洋学 统计 生物 数学分析 数学
作者
Kai Fang,Leiyi Chen,Shuqi Qin,Qiwen Zhang,Xuning Liu,Pengdong Chen,Yuanhe Yang
出处
期刊:Global Biogeochemical Cycles [Wiley]
卷期号:35 (12) 被引量:8
标识
DOI:10.1029/2021gb007118
摘要

Abstract Permafrost thaw could accelerate microbial decomposition, lead to greenhouse gases emissions into the atmosphere, and thus trigger a positive feedback to climate warming. As a key parameter reflecting the resistance of soil organic matter (SOM) to be decomposed by microorganisms, SOM stability may determine the strength of permafrost carbon (C)‐climate feedback. Adequate understanding of patterns and drivers of SOM stability can thus contribute to predicting permafrost C cycle and its feedback to climate change. However, due to limited observations, it remains unknown whether biochemical selectivity or physico‐chemical protection dominates SOM stability in permafrost regions. By combining large‐scale soil sampling, thermal analysis and random forest model, we quantified SOM stability in the top 10 cm using thermogravimetry and differential scanning calorimetry, and explored its spatial patterns across the Tibetan alpine permafrost region. We then constructed structural equation model to evaluate the relative importance of climatic variables, edaphic properties, substrate quality, and mineral variables in regulating SOM stability over a broad geographic scale. Our results indicated that SOM stability exhibited an increasing tendency from the southeastern to northwestern plateau. The stronger SOM stability was associated with higher mineral‐organic associations and more arid conditions. By contrast, substrate quality had limited effects on SOM stability. Overall, these results provide large‐scale evidence for the physico‐chemical protection hypothesis, highlighting the importance of considering mineral variables in Earth system models to better predict soil C dynamics across permafrost regions.
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