Quality evaluation of the soil-root composites layer of Leymus chinensis grassland based on different degradation degrees

• Published in: Catena (Giessen) 2022-08, Vol.215, p.106330, Article 106330
• Main Authors: Zhang, Xuening, You, Yong, Wang, Decheng, Zhu, Lu
• Format: Article
• Language: English
• Subjects: Membership function; Minimum data set; Obstacle factors; Quality evaluation; Soil-root composites
• ISSN: 0341-8162; 1872-6887
• DOI: 10.1016/j.catena.2022.106330

•The minimum data set consisted of forage biomass, bulk density, and pH.•The non-linear scoring method is best suited for assessing this work.•The soil-root composites quality increased as grassland coverage increased.•The main obstacle factors of degraded Leymus chinensis grassland were determined. Soil quality index (SQI) is widely used to assess the status and use potential of soils, and it is also an important prerequisite for taking effective remedial measures for degraded land. The objectives of this study are as follows: (1) to construct a soil-root composites quality index (SRCQI) by selecting the minimum data set (MDS) and membership function that are most suitable for evaluating degraded Leymus chinensis grassland, and to analyze the relationship between the SRCQI and degraded environment; and (2) to determine the main obstacle factors of degraded Leymus chinensis grassland and propose corresponding control measures. In this study, 15 evaluation indicators representing the physical, chemical, and biological properties of the soil-root composites layer (SRCL) of Leymus chinensis grassland were measured. The MDS was determined by principal component analysis (PCA), and the accuracy of MDS was verified by Pearson correlation analysis. The suitability of three membership functions (linear membership function, nonlinear membership function, and three-effect membership function) was compared by the coefficient of variation (CV) and ANOVA. The SRCQI was constructed to evaluate the quality of Leymus chinensis grassland SRCL with different degradation degrees. An obstacle factor model was introduced to determine the dominant obstacle factors affecting degraded Leymus chinensis grassland. The results showed the following: (1) for the SRCL of Leymus chinensis grassland, the MDS could be constructed by forage biomass, bulk density, and pH; (2) based on the highest F value (102.800) and CV value (23.35%), the non-linear membership function was determined to be the optimal membership function for the quality evaluation of SRCL of Leymus chinensis grassland; (3) the average SRCQI of Leymus chinensis grassland with coverages of 70–80%, 60–70%, 50–60%, and 40–50% were 0.617, 0.532, 0.406, and 0.398, respectively, where the SRCQI gradually decreased with the aggravation of grassland degradation (coverage reduction); and (4) the main obstacle factors of degraded Leymus chinensis grassland were determined as follows: the available potassium, forage biomass, moisture