干旱区生态环境知识资源中心(Arid): Mapping sub-surface distribution of soil organic carbon stocks in South Africa's arid and semi-arid landscapes: Implications for land management and climate change mitigation

Arid

DOI	10.1016/j.geodrs.2024.e00817
	Mapping sub-surface distribution of soil organic carbon stocks in South Africa's arid and semi-arid landscapes: Implications for land management and climate change mitigation
	Odebiri, Omosalewa; Mutanga, Onisimo; Odindi, John; Slotow, Rob; Mafongoya, Paramu; Lottering, Romano; Naicker, Rowan; Matongera, Trylee Nyasha; Mngadi, Mthembeni
通讯作者	Odebiri, O
来源期刊	GEODERMA REGIONAL
ISSN	2352-0094
出版年	2024
卷号	37
英文摘要	Soil organic carbon (SOC) stocks are critical for land management strategies and climate change mitigation. However, understanding SOC distribution in South Africa's arid and semi-arid regions remains a challenge due to data limitations, and the complex spatial and sub-surface variability in SOC stocks driven by desertification and land degradation. Thus, to support soil and land-use management practices as well as advance climate change mitigation efforts, there is an urgent need to provide more precise SOC stock estimates within South Africa's arid and semi-arid regions. Hence, this study adopted remote-sensing approaches to determine the spatial sub-surface distribution of SOC stocks and the influence of environmental co-variates at four soil depths (i.e., 0-30 cm, 30-60 cm, 60-100 cm, and 100-200 cm). Using two regression-based algorithms, i.e., Extreme Gradient Boosting (XGBoost) and Random Forest (RF), the study found the former (RMSE values ranging from 7.12 t/ha to 29.55 t/ ha) to be a superior predictor of SOC in comparison to the latter (RMSE values ranging from 7.36 t/ha to 31.10 t/ ha). Nonetheless, both models achieved satisfactory accuracy (R2 >= 0.52) for regional-scale SOC predictions at the studied soil depths. Thereafter, using a variable importance analysis, the study demonstrated the influence of climatic variables like rainfall and temperature on SOC stocks at different depths. Furthermore, the study revealed significant spatial variability in SOC stocks, and an increase in SOC stocks with soil depth. Overall, these findings enhance the understanding of SOC dynamics in South Africa's arid and semi-arid landscapes and emphasizes the importance of considering site specific topo-climatic characteristics for sustainable land management and climate change mitigation. Furthermore, the study offers valuable insights into sub-surface SOC distribution, crucial for informing carbon sequestration strategies, guiding land management practices, and informing environmental policies within arid and semi-arid environments.
英文关键词	Soil organic carbon Arid and semi-arid regions Climate action Machine learning Soil management
类型	Article
语种	英语
开放获取类型	hybrid, Green Accepted
收录类别	SCI-E
WOS记录号	WOS:001249965700001
WOS关键词	SYNTHETIC-APERTURE RADAR ; CONSERVATION AGRICULTURE ; REDUCED TILLAGE ; NORTHERN CAPE ; SEQUESTRATION ; MATTER ; REDISTRIBUTION ; ACCUMULATION ; GROUNDWATER ; CATCHMENT
WOS类目	Soil Science
WOS研究方向	Agriculture
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/403929
推荐引用方式 GB/T 7714	Odebiri, Omosalewa,Mutanga, Onisimo,Odindi, John,et al. Mapping sub-surface distribution of soil organic carbon stocks in South Africa's arid and semi-arid landscapes: Implications for land management and climate change mitigation[J],2024,37.
APA	Odebiri, Omosalewa.,Mutanga, Onisimo.,Odindi, John.,Slotow, Rob.,Mafongoya, Paramu.,...&Mngadi, Mthembeni.(2024).Mapping sub-surface distribution of soil organic carbon stocks in South Africa's arid and semi-arid landscapes: Implications for land management and climate change mitigation.GEODERMA REGIONAL,37.
MLA	Odebiri, Omosalewa,et al."Mapping sub-surface distribution of soil organic carbon stocks in South Africa's arid and semi-arid landscapes: Implications for land management and climate change mitigation".GEODERMA REGIONAL 37(2024).