亚热带常绿阔叶林土壤碳库的深度变化格局及其调控机制

Variation of carbon pool along soil profile in a subtropical forest and regulation mechanism

  • 摘要: 土壤碳库是陆地生态系统最大的碳库,准确评估土壤碳库的大小和分布格局是土壤生态学研究亟待解决的关键科学问题之一.已有研究表明土壤碳密度沿土壤剖面呈现出自上而下的递减趋势,但是该递减过程的调控机制仍不清楚.本研究基于广东车八岭亚热带常绿阔叶林80个样点的实测数据,系统评估了0~100 cm土壤碳库及其沿深度变化的递减系数β的空间变化格局.结果显示,车八岭亚热带常绿阔叶林土壤碳储量平均为11.09 kg (C)·m−2,土壤碳密度沿深度的递减系数β值平均为0.961 1.通过最小方差回归与结构方程模型分析发现:1)在该亚热带常绿阔叶林中影响β最主要的因素是表层细根生物量,表现为表层细根生物量越大,β越小,意味着土壤碳在表层土壤的富集程度越高;2)表层土壤碳氮比、辐射总量和地上生物量也是影响β的主要因素,这些因子累积共解释了β空间变化的66%.将基于这些因素模拟的β和表层土壤碳库相结合,亦能够有效预测亚热带常绿阔叶林0~100 cm土壤碳库.综上,通过表层植物和土壤特征可以有效预测亚热带常绿阔叶林的β和0~100 cm碳库.这一研究发现可用于将仅有表层土壤碳库的数据外推至100 cm的碳储量,为亚热带常绿阔叶林缺乏深层土壤采样的区域提供全剖面土壤碳库估算的路径.

     

    Abstract: Soil stores the largest carbon pool in terrestrial ecosystems, and thus accurately assessing its size and spatial distribution pattern is a critical scientific question in soil ecology study. Previous studies have shown that soil carbon density generally decreases along the soil profile from top to bottom; however, the regulatory mechanisms controlling this attenuation process are still not well understood. Based on field measurements from 80 sampling sites in a subtropical evergreen broadleaf forest of Chebaling, Guangdong province, this study systematically evaluated the spatial variation of the 0–100 cm soil carbon pool and its decay coefficient β along the soil depth. Results show that the average soil carbon storage in the Chebaling subtropical evergreen broadleaf forest is 11.09 kg C m−2, and the mean decay coefficient β for soil carbon density along soil profile is 0.9611. By using the least subsets square regression and structural equation modeling analyses, we found that β was dominantly determined by surface soil fine root biomass in this subtropical evergreen broadleaf forest. Specifically, greater fine root biomass in the surface soil contributed to a smaller β, indicating greater carbon accumulation in the surface soil. Other factors, including surface soil carbon-to-nitrogen ratio, total ambient radiation, and aboveground biomass, are also contributed to the variation of β. These factors totally explain 66% of the spatial variation in β. By combining the simulated β values based on these factors with surface soil carbon pool can effectively predict the 0-100 cm soil carbon pool in the subtropical evergreen broad-leaved forests. In conclusion, β and whole-profile soil carbon storage could be well predicted using plant and surface soil characteristics. This approach has great potential in extrapolating the abundant surface soil carbon data to estimate soil carbon stocks down to deep soil layer, thereby providing an efficient pathway for estimating whole-profile soil carbon storage in in subtropical evergreen broad-leaved forests lacking deep soil samplings.

     

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