竹林土壤碳储量的空间变异分析:以四川长宁县为例

Spatial variation of soil organic carbon in bamboo forests:A case study in Changning County,Sichuan Province

竹林在我国视为一种特殊的森林类型,固碳潜力大;然而竹林碳储量的估算具有较大的不确定性,这在一定程度上与竹林的异质性分布有关。与竹林植被碳储量的研究相比,关于竹林土壤碳储量空间异质性的研究较少。本文以四川长宁县竹林土壤为对象,基于实测数据采用地统计法(克里金插值法)开展竹林土壤碳储量的空间变异研究。四川长宁的竹林土壤碳密度在0~20 cm土层空间自相关程度低,在20~40和40~60 cm土层为中等强度空间自相关;空间自相关性随着土层深度的增加逐渐增大。竹林土壤碳密度克里金插值的最优插值邻域为1.5 km。随着土壤深度的增加,土壤碳储量不断减小,全县竹林0~60 cm土壤碳储量为2.45 Tg。空间分布显示,长宁南部土壤碳密度高值区呈片状分布,北部为块状镶嵌分布,总体呈现从南向北减少的趋势。相关分析表明,全氮、土壤湿度和植被指数是长宁县土壤碳密度的主要影响因子。本研究结果可为提高竹林土壤碳储量的估算精度以及竹林抽样设计、森林经营管理决策等提供重要依据。

Bamboo forest,as a special forest type in China,has a great carbon sequestration potential.However,there are large uncertainties in the estimation of its carbon pools,which is likely related to the heterogeneous distribution of bamboo forest.Few studies were conducted on the spatial heterogeneity of soil carbon,compared with the estimation of vegetation carbon pool of bamboo forests.In this study,we examined the spatial variation of soil organic carbon(SOC)of bamboo forests in Changning County,Sichuan Province using geostatistics(Kriging interpolation method).The spatial autocorrelation of SOC density was low in 0-20 cm soil layer,and medium both in 20-40 cm and 40-60 cm soil layers,showing that spatial autocorrelation gradually increased with increasing soil depth.The optimal Kriging interpolation neighborhood of SOC density was 1.5 km.The SOC pool(0-60 cm depth)of bamboo forests in this county was 2.45 Tg,showing a decreasing trend with increasing soil depth.Spatially,SOC density with high values showed a patchy distribution in southern Changning,and a mosaic distribution in the northern part,thus showing a decreasing trend from south to north.Correlation analysis indicated that spatial variation of SOC was more likely attributed to total nitrogen,soil moisture and vegetation index(a reflection of vegetation growth).Our results can provide an important basis for improving the accurate estimation of SOC,as well as sampling design and forest management for bamboo forests.