Spatial distribution of soil organic carbon stocks in Masson pine (Pinus massoniana) forests in subtropical China

被引:47
|
作者
Yao, Xiong [1 ,2 ]
Yu, Kunyong [1 ,2 ]
Deng, Yangbo [1 ]
Zeng, Qi [1 ]
Lai, Zhuangjie [1 ]
Liu, Jian [1 ,2 ]
机构
[1] Fujian Agr & Forestry Univ, Coll Forestry, Fuzhou 350002, Fujian, Peoples R China
[2] Univ Key Lab Geomat Technol & Optimize Resources, Fuzhou 350002, Fujian, Peoples R China
基金
中国国家自然科学基金;
关键词
Soil organic carbon stock; Ordinary kriging; Inverse distance weighting; Spatial variability; Pinus massoniana; MOSO BAMBOO FORESTS; NITROGEN DYNAMICS; VARIABILITY; SCALE; PLANTATIONS; STORAGE; BIOMASS; PHOSPHORUS; VEGETATION; POTASSIUM;
D O I
10.1016/j.catena.2019.03.004
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Masson pine (Pinus massoniana) is a typical reforestation species in subtropical China, which plays a key role in soil and water conservation. Site-specific forest management requires an accurate estimation of the soil organic carbon (SOC) stocks, and information about the spatial distribution of SOC stocks is essential for improving the soil quality and ecosystem productivity. We examined the spatial distribution of SOC stocks using 91 soil samples from Masson pine forests in subtropical China. Ordinary kriging (OK) and inverse distance weighting (IDW) methods were used to compare the spatial patterns of the SOC stocks. A moderate spatial dependence of the SOC stocks suggested that extrinsic and intrinsic factors affected the SOC stocks. Similar spatial distributions but different cross-validation accuracies indicated that OK outperformed IDW. The soil pools at a depth of 0-60 cm were 774.06 Gg and 761.61 Gg as determined by the OK and IDW methods, respectively, which were higher than that measured by the conventional method (CM, 734.22 Gg). This highlights the need to apply different methods when studying the regional SOC pools. On the basis of the comparison of OK, IDW, and CM methods, OK is recommended for determining nonhomogeneous sampling point distributions. The present results enhance our understanding of method selection when studying the spatial distribution of SOC stocks.
引用
收藏
页码:189 / 198
页数:10
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