绘制南非干旱和半干旱地区土壤有机碳储量地下分布图:对土地管理和减缓气候变化的影响

IF 3.1 2区 农林科学 Q2 SOIL SCIENCE
Omosalewa Odebiri , Onisimo Mutanga , John Odindi , Rob Slotow , Paramu Mafongoya , Romano Lottering , Rowan Naicker , Trylee Nyasha Matongera , Mthembeni Mngadi
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引用次数: 0

摘要

土壤有机碳(SOC)储量对于土地管理战略和减缓气候变化至关重要。然而,由于数据的局限性,以及荒漠化和土地退化导致的土壤有机碳储量在空间和地表下的复杂变化,了解南非干旱和半干旱地区的土壤有机碳分布仍然是一项挑战。因此,为了支持土壤和土地利用管理实践以及推进气候变化减缓工作,迫切需要对南非干旱和半干旱地区的 SOC 储量进行更精确的估算。因此,本研究采用遥感方法确定了四种土壤深度(即 0-30 厘米、30-60 厘米、60-100 厘米和 100-200 厘米)的 SOC 储量空间次表层分布以及环境共变量的影响。研究使用了两种基于回归的算法,即极端梯度提升算法(XGBoost)和随机森林算法(RF),发现前者(均方根误差值从 7.12 吨/公顷到 29.55 吨/公顷不等)与后者(均方根误差值从 7.36 吨/公顷到 31.10 吨/公顷不等)相比,前者更能预测 SOC。尽管如此,这两个模型对所研究土壤深度的区域尺度 SOC 预测都达到了令人满意的精度(R2 ≥ 0.52)。随后,研究利用变量重要性分析,证明了降雨量和温度等气候变量对不同深度 SOC 储量的影响。此外,研究还揭示了 SOC 储量的显著空间变异性,以及 SOC 储量随土壤深度的增加而增加。总之,这些研究结果加深了人们对南非干旱和半干旱地貌中 SOC 动态的了解,并强调了考虑特定地点的地貌-气候特征对于可持续土地管理和减缓气候变化的重要性。此外,该研究还提供了有关地表下 SOC 分布的宝贵见解,这对于制定碳固存战略、指导土地管理实践以及为干旱和半干旱环境中的环境政策提供信息至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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

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.

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来源期刊
Geoderma Regional
Geoderma Regional Agricultural and Biological Sciences-Soil Science
CiteScore
6.10
自引率
7.30%
发文量
122
审稿时长
76 days
期刊介绍: Global issues require studies and solutions on national and regional levels. Geoderma Regional focuses on studies that increase understanding and advance our scientific knowledge of soils in all regions of the world. The journal embraces every aspect of soil science and welcomes reviews of regional progress.
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