Forests (Jun 2023)

Soil Quality Evaluation and Dominant Factor Analysis of Economic Forest in Loess Area of Northern Shaanxi

  • Ting Xiang,
  • Fangfang Qiang,
  • Guangquan Liu,
  • Changhai Liu,
  • Ning Ai

DOI
https://doi.org/10.3390/f14061179
Journal volume & issue
Vol. 14, no. 6
p. 1179

Abstract

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Choosing economically important trees and establishing planting patterns can improve soil quality in economic forests. To clarify the soil quality status of the main economic forest land distributed in northern Shaanxi, the research object in this study was jujube and apple economic forests, and the control was grassland. By evaluating 17 soil indicators, the minimum data set (MDS) and structural equation model (SEM) were used to analyze the soil quality status and its dominant factors under different economic forests and land preparation methods. The results showed that (1) compared with grassland, the economic forest has a certain improvement and promotion in soil’s properties, mainly in the water-holding capacity and available nutrients. Compared to the undisturbed slope, the level bench had better physical and chemical properties. (2) Six indicators were identified as the minimum data set for assessing soil quality, including the soil organic carbon, saturated water content, bulk density, alkaline nitrogen, sand, and total capillary porosity. In addition, structural equation model analysis showed that the soil organic carbon, saturated water content, alkaline nitrogen, and capillary porosity were the dominant factors affecting soil quality in the study area. (3) Jujube trees exhibited the highest soil quality and the best restoration effect, followed by apple trees, while grassland had the poorest restoration effect. The soil quality of undisturbed slopes under different land preparation methods was lower than that of the level bench land preparation. The outcomes of this study are to provide data support and a theoretical basis for improving soil quality, enhancing ecological benefits, and selecting and managing economic forest species, in the study area and similar regions in the future.

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