Spatial variability of soil organic carbon fractions and aggregate stability along an elevation gradient in the alpine meadow grasslands of the Qilian Mountains, China

Abalori, Theophilus Atio; Cao, Wenxia; Weobong, Conrad Atogi-Akwoa; Wang, Shilin; Anning, Dominic Kwadwo; Sam, Faisal Eudes; Liu, Wanting; Wang, Wenhu

doi:10.4067/s0718-58392022000100052

Cited by 5 publications

(3 citation statements)

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“…The influences of auxiliary variables on SOC content have been noted by previous research (Calvo de Anta et al, 2020). Our study confirmed the same conclusions about the influences of environmental variables on SOC maps as had been drawn from those previous studies (Abalori et al, 2022). The map created by RF method is shown clearly.…”

Section: Discussionsupporting

confidence: 92%

Application GIS and remote sensing for soil organic carbon mapping in a farm-scale in the hilly area of central Vietnam

Chương

Pham

Nguyen

et al. 2022

Air, Soil and Water Research

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Soil Organic Carbon (SOC) influences many soil properties including nutrient and water holding capacity, nutrient cycling and stability, improved water infiltration and aeration. It also is an essential parameter in the assessment of soil quality, especially for agricultural production. However, SOC mapping is a complicated process that is costly and time-consuming due to the physical challenges of the natural conditions that is being surveyed. The best model for SOC mapping is still in debate among many researchers. Recently, the development of machine learning and Geographical Information Systems (GIS) has provided the potential for more accurate spatial prediction of SOC content. This research was conducted in a relatively small-scale capacity in the Central Vietnam region. The aim of this study is to compare the accuracy of Inverse Distance Weighting (IDW), Ordinary Kriging (OK), and Random Forest (RF) methods for SOC interpolation, with a dataset of 47 soil samples for an area of 145 hectares. Three environmental variables including elevation, slope, and the Normalized Difference Vegetation Index (NDVI) were used for the RF model. In the RF model, the values of the number of variables randomly sampled as candidates at each split, (mtry), and the number of bootstrap replicates, (ntree), were determined in terms of 1 and 1,000 respectively The results at our research site showed that using IDW is the most accurate method for SOC mapping, followed by the methods of RF and OK respectively. Concerning SOC mapping based-on auxiliary variables, in areas where there is human activity, the selection of auxiliary variables should be carefully considered because the variation in the SOC may not only be due to environmental variables but also by farming technologies.

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Section: Discussionsupporting

confidence: 92%

Application GIS and remote sensing for soil organic carbon mapping in a farm-scale in the hilly area of central Vietnam

Chương

Pham

Nguyen

et al. 2022

Air, Soil and Water Research

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“…Likewise, Dieleman et al (2013) found that SOC in tropical forests varied in a predictable manner with altitude, ranging from 4.8 to 19.4 kg C m -2 and increasing by 5.1 kg C m -2 for every 1000 m increase in altitude. Also, it has been shown that SOC and the stability of recalcitrant and labile soil aggregates increased with altitude (Abalori et al, 2022). Tashi et al (2016) indicated that C content was similarly correlated with altitude, with temperature apparently being the driver of soil C content along the altitudinal gradient.…”

Section: Relationship Between Soc and Altitudementioning

confidence: 99%

Soil organic carbon balance across contrasting plant cover ecosystems in the Peruvian Amazon

Vallejos-Torres,

Gaona-Jimenez,

Lozano

et al. 2023

Chil. j. agric. res.

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The Peruvian Amazon has been significantly affected by land use and climate change, decreasing decomposition processes, which cause a significant depletion of soil C stocks. In this study, we estimated soil organic C (SOC) mediated by different plant covers in coffee (Coffea arabica L.) plantations and secondary forests in several districts of the San Martín Region, Peru. We calculated the critical threshold, saturation point, and the organic C deficit of these Amazonian soils. The association between geography, soil physical-chemical characteristics, and SOC was estimated through principal component analysis. Across all sites of the study, SOC stock had an average value of 69.19 t ha -1 , with 48.95 t ha -1 constituting inorganic C. The highest SOC stock (225.28 t ha -1 ) was observed under secondary forest in the Jepelacio district. The SOC stocks were positively correlated with altitude and CaCO3 content only in secondary forests. The current measured amount of organic C within 15 cm soil depth was 28.5 g C kg -1 , which is very low and close to the critical threshold (20.6 g C kg -1 ) -estimated based on its clay and silt contents. Our SOC stocks measurements indicated a worrisome situation, as they are close to the critical threshold, which exposes this area to a greater and stronger degradation.

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“…Figure 1 presents a map showing the description and altitude of the study area. SO, SA, RC, and PF dominate the shrubby grassland ecosystem, with heights of 50-120 cm [22]. All these alpine shrub species play important roles in maintaining the biodiversity and stability of their respective ecosystems.…”

Section: Study Areamentioning

confidence: 99%

Assessing Shrub Patch Characteristics and Soil Nutrient Distribution Patterns of Four Typical Alpine Shrub Plants in the Eastern Qilian Mountains

Zhao,

Adu,

Wang

et al. 2024

Sustainability

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Shrub patches have an impact on soil fertility and vegetation, influencing species composition and diversity. The unique context of the Eastern Qilian Mountains provides insights into alpine ecosystems’ responses to environmental challenges. This study aimed to evaluate the physical characteristics and soil nutrient contents of shrub patches for four different shrub species (Salix oritrepha (SO), Spiraea alpina (SA), Rhododendron capitatum (RC), and Potentilla fruticosa (PF)). We assessed their patch characteristics and soil nutrients at different depths within three patch microsites (the center (CS), the edge (ES), and the midpoint between the center and the edge of the shrub patch (BC)). Soil samples were collected and analyzed for organic matter, nitrogen, phosphorus, and potassium content. Statistical analyses were conducted to evaluate differences among shrub species and locations within the shrub patches. Our results showed that the shrub species exhibited variations in patch characteristics and soil nutrient distribution. Soil nutrient content varied by depth and location within the shrub patches, with higher concentrations at the center. The relative interaction intensity (RII) revealed nutrient aggregation or dispersion trends. The study highlighted the complex interactions between shrub characteristics and soil nutrients, emphasizing their influence on nutrient cycling, vegetation dynamics, and soil properties. These findings contribute to our understanding of alpine ecosystem dynamics and inform conservation, sustainability, and management strategies.

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Spatial variability of soil organic carbon fractions and aggregate stability along an elevation gradient in the alpine meadow grasslands of the Qilian Mountains, China

Cited by 5 publications

References 0 publications

Application GIS and remote sensing for soil organic carbon mapping in a farm-scale in the hilly area of central Vietnam

Application GIS and remote sensing for soil organic carbon mapping in a farm-scale in the hilly area of central Vietnam

Soil organic carbon balance across contrasting plant cover ecosystems in the Peruvian Amazon

Assessing Shrub Patch Characteristics and Soil Nutrient Distribution Patterns of Four Typical Alpine Shrub Plants in the Eastern Qilian Mountains

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