Soil organic carbon accumulation in dry tropical mountainous zone of Cameroon

Atourakai, Michael Roi Apiniel; Tsozué, Désiré; Basga, Simon Djakba; Nzeukou, Aubin Nzeugang; Kagonbé, Bertin Pagna; Bitom, Dieudonné

doi:10.1007/s12517-023-11248-w

Cited by 2 publications

(1 citation statement)

References 85 publications

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“…Numerous large-scale studies found that under natural conditions, SOC is significantly positively correlated with precipitation and negatively correlated with temperature [45][46][47][48]. Increasing the temperatures can enhance microbial activity, thereby accelerating the mineralization rate of SOC [49,50]. However, this result contrasts our study findings, which could be attributed to the relatively small scope of our study area (predominantly consists of cultivated land with welldeveloped irrigation facilities).…”

Section: Relationship Between Soc and Environmental Variablescontrasting

confidence: 94%

Improving soil organic carbon mapping in farmlands using machine learning models and complex cropping system information

Ou,

Wu,

Yan

et al. 2024

Environ Sci Eur

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Obtaining accurate spatial maps of soil organic carbon (SOC) in farmlands is crucial for assessing soil quality and achieving precision agriculture. The cropping system is an important factor that affects the soil carbon cycle in farmlands, and different agricultural managements under different cropping systems lead to spatial heterogeneity of SOC. However, current research often ignores differences in the main controlling factors of SOC under different cropping systems, especially when the cropping pattern is complex, which is not conducive to farmland zoning management. This study aims to (i) obtain the spatial distribution map of six cropping systems by using multi-phase HJ-CCD satellite images; (ii) explore the stratified heterogeneous relationship between SOC and environmental variables under different cropping systems by using the Cubist model; and (iii) predict the spatial map of SOC. The Xiantao, Tianmen, and Qianjiang cities, which are the core agricultural areas of the Jianghan Plain, were selected as the study area. Results showed that the SOC content in rice–wheat rotation was the highest among the six cropping systems. The Cubist model outperformed random forest, ordinary kriging, and multiple linear regression in SOC mapping. The results of the Cubist model showed that cropping system, climate, soil attributes, and vegetation index were important influencing factors of SOC in farmlands. The main controlling factors of SOC under different cropping systems were different. Specifically, summer crop types had a greater influence on spatial variations in SOC than winter crops. Paddy–upland rotation was more affected by river distance and NDVI, while upland–upland rotation was more affected by irrigation-related factors. This work highlights the differentiated main controlling factors of SOC under different cropping systems and provides data support for farmland zoning management. The Cubist model can improve the prediction accuracy of SOC under complex cropping systems.

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Section: Relationship Between Soc and Environmental Variablescontrasting

confidence: 94%

Improving soil organic carbon mapping in farmlands using machine learning models and complex cropping system information

Ou,

Wu,

Yan

et al. 2024

Environ Sci Eur

View full text Add to dashboard Cite

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Soil organic carbon sequestration under Araucaria angustifolia plantations but not under exotic tree species on a mountain range

Zinn,

Cardoso,

Silva

2024

Revista Brasileira De Ciência Do Solo

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Plantation forests can be efficient C sinks in biomass and soil organic carbon (SOC), but the latter depends on many factors, including climate. Tropical humid, mountain areas have cooler temperatures, slowing microbial decomposition, and thus can store considerable SOC. However, the effects of forest plantations on SOC of these montane areas are still poorly studied. Here, we aimed to assess changes in SOC, and related soil properties, after conversion of native rainforest to plantations of five tree species, with rotation cycles varying from 7 to 30 years, on the Mantiqueira Range, Minas Gerais, Brazil. We measured SOC contents and stocks (0.00-0.40 m layer) under a native montane rainforest (control) and plantations of Eucalyptus, Pinus, Cunninghamia, Cupressus and Araucaria, all planted in 3 × 3 m spacing, at an altitude of ca. 1,300 m, marked by humid and cool climate, where SOC contents are naturally high. Soil organic carbon varied from 55 g kg -1 under Eucalyptus to 105 g kg -1 under Araucaria (0.00-0.05 m layer), decreasing in depth (0.20-0.40 m) to the still high values of 20-40 g kg -1 . Soil organic carbon stocks for the top 0.20 m were also high, reaching ca. 140 Mg ha -1 under Araucaria, significantly higher value than the native forest (ca. 90 Mg ha -1 , p<0.05), which did not differ from the other species. Soil organic carbon stocks were not affected in the 0.20-0.40 m soil layer, whereas soil structure patterns changed under some species, without however resulting in bulk density changes, and pH decreased under Araucaria. Such data showed large SOC stocks under montane native forests can not only be preserved upon conversion to forest plantations, but considerable SOC sequestration can be achieved in 30-years rotation cycles plantations of indigenous Araucaria angustifolia, marked by more open canopies and greater understory biomass.

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Soil organic carbon accumulation in dry tropical mountainous zone of Cameroon

Cited by 2 publications

References 85 publications

Improving soil organic carbon mapping in farmlands using machine learning models and complex cropping system information

Improving soil organic carbon mapping in farmlands using machine learning models and complex cropping system information

Soil organic carbon sequestration under Araucaria angustifolia plantations but not under exotic tree species on a mountain range

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