Spatial variability in soil pH and land use as the main influential factor in the red beds of the Nanxiong Basin, China

Yan, Ping; Hua, Peng; Yan, Lei; Zhang, Shaoyun; Chen, Aimin; Lin, Kairong

doi:10.7717/peerj.6342

Cited by 15 publications

(11 citation statements)

References 62 publications

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“…The pH change trend was similar to that of the BD. Significantly lower pH values were observed in the M and GW systems than in the W system, which was probably attributed to higher organic matter inputs of plantations and acidifying effects of coniferous trees (Yan et al, ). The pH values at our study site ranged from 7.82 to 8.58, which were classified as weakly alkaline (7.5–8.5) and moderately alkaline (8.5–9.5; Guo et al, ).…”

Section: Discussionmentioning

confidence: 99%

Afforestation and agroforestry enhance soil nutrient status and carbon sequestration capacity in eastern China

Guo

Wang

et al. 2019

Land Degrad Dev

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Afforestation and agroforestry both sequester atmospheric carbon (C) and store C in the soil. However, the response of soil nutrients and soil organic carbon (SOC) to these practices has not been fully examined, especially in deep soil layers. We therefore investigated the effects of afforestation and agroforestry on the nutrient contents and organic carbon (OC) stocks within a 100-cm depth in eastern China. The soil nutrient contents and stoichiometry as well as the SOC contents and stocks exhibited different vertical patterns and varied among the five planting systems.The total nitrogen (TN), total phosphorus (TP), and SOC contents decreased dramatically at a 20-cm depth, and the total potassium (TK) content exhibited a different pattern. Compared with adjacent croplands and nurseries, the forest plantation and agroforestry systems had higher SOC stocks, ranging from 42.9 to 111.6 t·hm −2 in the whole soil profile. The SOC distribution among the depth gradient varied among planting systems, and the topsoil SOC stocks played crucial roles in total SOC storage within a depth of 100 cm in the cropland and nursery systems. The soil pH and bulk density (BD) were negatively correlated with the SOC content, and a significant positive linear relationship occurred between the TN and SOC contents and between the TP and SOC contents. We recommend that combinations of nitrogen (N) and phosphorus (P) fertilizers would benefit SOC storage and improve stabilization in agroforestry and plantation systems.

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Section: Discussionmentioning

confidence: 99%

Afforestation and agroforestry enhance soil nutrient status and carbon sequestration capacity in eastern China

Guo

Wang

et al. 2019

Land Degrad Dev

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“…The increasingly serious land degradation poses a great threat to cultivated land use, soil and water conservation, and has become one of the major global environmental problems [36][37][38]. The Nanxiong basin is an ecologically fragile red bed area in South China with complex topography [16][17][18]31]. If the vegetation and soil layer on the surface of the red bed soil is destroyed, the soft rock of the base red bed will be rapidly weathered and form surface clasts.…”

Section: Discussionmentioning

confidence: 99%

“…The Nanxiong basin is a typical red bed ecosystem with special material, energy, structure and function, which is formed based on red sandstone and glutenite and under the interaction of the atmosphere, water, rocks and organisms [16,17]. In recent years, the aggravation of human activities has exacerbated the land degradation of red bed ecology, generating severe ecological problems such as deserts in the red bed area of southern China [18].…”

Section: Introductionmentioning

confidence: 99%

Assessment of Influencing Factors on the Spatial Variability of SOM in the Red Beds of the Nanxiong Basin of China, Using GIS and Geo-Statistical Methods

Yan

Lin

Wang

et al. 2021

IJGI

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Understanding the spatial variability of soil organic matter (SOM) is crucial for implementing precise land degradation control and fertilization to improve crop productivity. Studying spatial variability provides a scientific basis for precision fertilization and land degradation control. In this study, geostatistics and classical statistical methods were used to analyze the spatial variability of SOM and its influencing factors under various degrees of land degradation in the red bed area of southern China. The results demonstrate a declining trend for SOM content with increasing land degradation. The SOM content differs profoundly under different land degradation degrees. The coefficient of variation ranges from 13.61% for extreme land degradation to 8.98% for mild land degradation, 7.96% for moderate land degradation, and 5.64% for severe land degradation. A significant positive correlation is displayed between the altitude and the SOM (p < 0.01) under mild and moderate land degradation conditions. Bulk density and pH value have a significant negative correlation with SOM (p < 0.01). It can be observed that terrain factors, as well as physical and chemical soil parameters, have a great influence on SOM.

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“…The level of decision coe cient represented the effect of tting variogram by the model. The higher the decision coe cient, the better the effect of tting variogram by the model 22 . The determination coe cients of different sampling points were between 0.39 and 0.69, indicating that the model can better re ect the spatial structure characteristics of soil pH.…”

Section: Resultsmentioning

confidence: 99%

Rational sampling numbers of soil pH for spatial variation: A case study from Yellow River Delta

Zhang

Duan

Zhang

2022

Preprint

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Spatial variation of soil pH is important for the evaluation of environmental quality. A reasonable number of sampling points has an important meaning for accurate quantitative expression on spatial distribution of soil pH and resource savings. Based on the grid distribution point method, 797, 700, 594, 499, 398, 299, 200, 149, 100, 75 and 50 sampling points, which were randomly se-lected from 908 sampling points, constituted 12 sample sets. Semi-variance structure analysis was carried out for different point sets, and ordinary Kriging was used for spatial prediction and ac-curacy verification, and the influence of different sampling points on spatial variation of soil pH was discussed. The results showed that the pH value in Kenli County was generally between 7.8 and 8.1, and the soil was alkaline. Semi-variance models fitted by different point sets could well reflect the spatial structure characteristics of soil pH. With the decrease of the number of sampling points, the Sill value of sample set increased, and the spatial autocorrelation gradually weakened. Considering the prediction accuracy, spatial distribution and investigation cost, the number of sampling points greater than or equal to 150 could satisfy the spatial variation expression of soil pH at the county level in the Yellow River Delta. This was equivalent to taking at least 107 sam-pling points per 1 000 km2. The results in this study are applicable to areas with similar environ-mental and soil conditions as the Yellow River Delta, and have certain reference significance for them.

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Spatial variability in soil pH and land use as the main influential factor in the red beds of the Nanxiong Basin, China

Cited by 15 publications

References 62 publications

Afforestation and agroforestry enhance soil nutrient status and carbon sequestration capacity in eastern China

Afforestation and agroforestry enhance soil nutrient status and carbon sequestration capacity in eastern China

Assessment of Influencing Factors on the Spatial Variability of SOM in the Red Beds of the Nanxiong Basin of China, Using GIS and Geo-Statistical Methods

Rational sampling numbers of soil pH for spatial variation: A case study from Yellow River Delta

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