Temporal and spatial changes in soil organic carbon and soil inorganic carbon stocks in the semi-arid area of northeast China

被引:5
|
作者
Wang, Shuai [1 ,2 ,3 ,4 ]
Zhuang, Qianlai [4 ]
Zhou, Mingyi [1 ]
Jin, Xinxin [1 ]
Yu, Na [1 ]
Yuan, Ting [5 ]
机构
[1] Shenyang Agr Univ, Coll Land & Environm, 120 Dongling Rd, Shenyang 110866, Liaoning, Peoples R China
[2] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R China
[3] Forschungszentrum Julich, Inst Bio & Geosci Agrosphere IBG 3, Wilhelm Johnen Str, D-52428 Julich, Germany
[4] Purdue Univ, Dept Earth Atmospher & Planetary Sci, W Lafayette, IN USA
[5] Chinese Acad Agr Sci CAAS, Agr Informat Inst, Beijing 100081, Peoples R China
基金
国家重点研发计划; 中国博士后科学基金; 中国国家自然科学基金;
关键词
Soil organic carbon; Soil inorganic carbon; Digital soil mapping; Boosted regression trees; LAND-USE; REGRESSION; NITROGEN; STORAGE; CLIMATE; VARIABLES; FOREST;
D O I
10.1016/j.ecolind.2022.109776
中图分类号
X176 [生物多样性保护];
学科分类号
090705 ;
摘要
Soil organic carbon (SOC) and soil inorganic carbon (SIC) has important effects on soil physical, chemical and biological properties. They play an important role in coordinating the relationship between soil water and air, increasing soil water holding capacity and improving plant productivity. In this study, a boosted regression trees (BRT) model was developed to map the spatial distribution carbon stocks in the semi-arid region of Northeast China in 1990 and 2015. During the two periods, 10-fold cross-validation technology was used to test the performance and uncertainty of BRT model. In order to construct the model, 9 environmental variables (derived from climate, topography and biology) and 173 (1990) and 223 (2015) topsoil (0-30 cm) samples were used. The comparison between estimated and observed data shows that the RMSE of SOC and SIC stocks were 0.53 kgm(-2) and 0.19 kgm(-2) in 1990, and 0.65 kgm(-2) and 0.20 kgm(-2) in 2015, respectively. Elevation, normalized difference vegetation index, mean annual precipitation and Landsat band 3 were identifies as critical environmental factors for simulating the spatial distribution of SOC, accounting for 76.6 % and 70.3 % of the total relative importance in 1990 and 2015, respectively. Mean annual precipitation, mean annual temperature and topographic wetness index were the critical environmental factors for simulating the spatial variation of SIC during the two periods. Land use change also played an important role in the spatial variability of SOC and SIC stocks. In the past 25 years, soil carbon stocks decreased from 6.2 kg m(-2) in 1990 to 5.9 kg m(-2) in 2015. The spatial distribution pattern of SOC was high in northeastern area and low in southwestern area during the two periods, while the spatial distribution pattern of SIC was opposite to that of SOC stocks. The mapped soil carbon stock distribution is fundamental to future study of soil carbon cycle and regional carbon balance in semi-arid regions.
引用
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页数:12
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