标题: Unraveling the threshold and interaction effects of environmental variables on soil organic carbon mapping in plateau watershed

作者: Zhang, C (Zhang, Chi); Chen, YY (Chen, Yiyun); Wei, YJ (Wei, Yujiao); Yu, PH (Yu, Peiheng); Hong, YS (Hong, Yongsheng); Hu, YZ (Hu, Yazhen); Wang, JX (Wang, Jiaxue); Shi, Z (Shi, Zhou)

来源出版物: GEODERMA 卷: 450 文献号: 117032 DOI: 10.1016/j.geoderma.2024.117032 Published Date: 2024 OCT

摘要: Understanding the spatial distribution and mechanisms driving soil organic carbon (SOC) is crucial for assessing soil carbon stocks and implementing effective carbon sequestration strategies in agricultural landscapes. The linear and nonlinear relationships between environmental variables and SOC have been extensively documented, but the threshold and interaction effects among multiple covariates on SOC remain underexplored. This study focused on farmland within the Qilu Lake watershed in Yunnan Province, China, which is characterized by complex surface conditions shaped by both climate change and anthropogenic activities. Utilizing 216 soil samples from the watershed, this research aimed to investigate the threshold and interaction effects of environmental variables on SOC. To achieve this, gradient boosted decision tree (GBDT) combined with partial dependence analysis were employed to elucidate the spatial distribution of SOC and the intricate relationships between environmental factors and SOC. In order to enhance the accuracy of SOC prediction, we employed the landscape metrics as environmental variables, thereby facilitating a more comprehensive description of the landscape. The results indicated that GBDT (R-2= 0.47) outperformed random forest (R-2 = 0.38), achieving higher accuracy and lower uncertainty, indicated by a narrower 90% prediction interval. The SOC distribution was predominantly influenced by soil moisture, elevation, and the contagion index (CONTAG), with threshold effects observed at relatively high soil moisture levels (>50%), CONTAG levels (>85%), and relatively low elevations (<1812 m). Moreover, the nonlinear relationship between one environmental variable and SOC could be influenced by another, suggesting interaction effects rather than a simple additive effect. Our findings suggest that combining GBDT modeling with partial dependence analysis provides an efficient and interpretable approach for SOC mapping. Knowledge of the threshold and interaction effects is critical for understanding the complex relationships between environmental variables and SOC, which has important implications for soil carbon management.

作者关键词: Soil organic carbon; Gradient boosting decision tree; Threshold effect; Interaction effect; Plateau watershed; Landscape metrics

地址: [Zhang, Chi; Chen, Yiyun; Wei, Yujiao; Wang, Jiaxue] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

[Chen, Yiyun] Minist Nat Resources, Key Lab Digital Cartog & Land Informat Applicat En, Wuhan 430079, Peoples R China.

[Chen, Yiyun] Hubei Luojia Lab, Wuhan 430079, Peoples R China.

[Yu, Peiheng] Hong Kong Polytech Univ, Res Inst Sustainable Urban Dev, Dept Bldg & Real Estate, Hong Kong 999077, Peoples R China.

[Yu, Peiheng] Natl Univ Singapore, Saw Swee Hock Sch Publ Hlth, Singapore 117549, Singapore.

[Yu, Peiheng] Natl Univ Singapore, Dept Geog, GeoSpatialX Lab, Singapore 117568, Singapore.

[Hong, Yongsheng] Chinese Acad Sci, Inst Soil Sci, State Key Lab Soil & Sustainable Agr, Nanjing 210008, Peoples R China.

[Hong, Yongsheng] Univ Chinese Acad Sci, Beijing 100049, Peoples R China.

[Hu, Yazhen] Guangzhou Urban Planning & Design Survey Res Inst, Guangzhou 510060, Peoples R China.

[Shi, Zhou] Zhejiang Univ, Coll Environm & Resource Sci, Hangzhou 310058, Peoples R China.

通讯作者地址: Chen, YY (通讯作者)，Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

电子邮件地址: chenyy@whu.edu.cn

影响因子：5.6