ArticleScientific reports2025
Evaluation of soil quality and analysis of drivers of different vegetation patterns in the loess region of Northern Shaanxi.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Analysis of Soil Quality Characteristics and Driving Factors of Micro-Landforms in Loess Hilly Areas.Plants (Basel, Switzerland) · 2026Article
- Article
- Mechanical behavior and microstructural investigation of loess sustainable stabilization using nanosilica and GGBS.Scientific reports · 2025Article
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6 authors.
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Abstract
Evaluating the effects of different vegetation patterns on soil quality and clarifying the soil quality drivers in the loess area of northern Shaanxi are highly important for the future land use and vegetation optimization in this area. In this work, eight typical vegetation patterns in the loess area of northern Shaanxi were used as research objects, and the main soil physicochemical indicators were screened out using principal component analysis, the soil quality evaluation model was established using fuzzy comprehensive evaluation method, and the soil quality (SQ) was comprehensively evaluated. Finally, structural equation modeling (SEM) was used to explore the key factors affecting soil quality. The results revealed that (1) the maximum water holding capacity (MWHC), capillary water holding capacity (CWHC), total porosity (TCP), soil organic carbon (SOC), quick acting phosphorus (AP), C/P, and C/N of the PTF sample were significantly greater than those of the other vegetation models, and the maximum water holding capacity (MWHC), capillary water holding capacity (CWHC), soil organic carbon (SOC), total nitrogen (TN), and total phosphorus (TP) of the MAF sample site were significantly lower than those of the other sample sites, while soil bulk density (BD) was significantly higher than other sample sites. (2) According to the principal component analysis of the 16 physical and chemical indicators, the eigenvalues of the first four principal components were 1, and the cumulative contribution rate reached 77.482%, which effectively included the information of the original variables. (3) The soil qualities of the different vegetation types in the loess area of northern Shaanxi were ranked as follows: PTF (0.534) > SLP (0.494) > SF (0.462) > MF1 (0.430) > HPF (0.423) > BLF (0.420) MF2 > (0.415) > MAF (0.389). (4) SEM revealed that soil quality drivers varied among vegetation patterns, but soil organic carbon (SOC), as the main influencing factor, positively affected all vegetation. Therefore, this study suggests that in the future, when forestry ecological construction is carried out in similar areas, vegetation such as Pinus tabuliformissmall-leaf poplars, and sea buckthorn can be created to improve soil quality and ecological benefits.
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