Comprehensive Evaluation of Soil Substrate Improvement Based on the Minimum Data Set Method

Dong Tang, Jianjun Yang and Ping Cheng
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Dong Tang: Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830017, China
Jianjun Yang: Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830017, China
Ping Cheng: Xinjiang Academy of Forestry Sciences, Urumqi 830018, China

Sustainability, 2022, vol. 14, issue 7, 1-15

Abstract: Long-term transitional grazing on the northern slopes of the Tianshan Mountains in Xinjiang has led to severe vegetation degradation, loss of self-renewal capacity and regional ecological degradation in the region. This study was conducted to improve the soil quality and vegetation restoration efficiency in the foreland zone of the northern slope of the Tianshan Mountains (Xiangyataizi slope) using xanthic acid, bentonite, a green plant growth regulator (GGR) and high amounts of mulch as improvement materials, and eight sets of experiments were conducted. Fifteen physical and chemical indicators were selected as the total data set (TDS), and the minimum data set (MDS) was constructed using principal component analysis (PCA) combined with norm values to evaluate the soils in the study area by nonlinear (NL) and linear (L) evaluation methods. The results showed that the soil quality evaluation indexes of the MDS included effective phosphorus, organic matter, percentage of powder, total potassium and total salt for the Xiangyataizi slope of the Tianshan Mountains. The SQI was ( p < 0.05). The Ⅵ treatment significantly improved soil quality; that is, plastic mulch applied to soil with 250 g of fulvic acid, 1000 g of bentonite and 15 g of GGR (mixed with 100 kg of water) was the best treatment. Additionally, since the nonlinear soil quality evaluation method (SQI-NL) had a smaller variation interval and coefficient of variation of the soil quality index compared with linear soil quality evaluation method (SQI-L), the coefficient of determination between the MDS and TDS was 0.873 and 0.811 under the SQI-NL and SQI-L evaluation methods, respectively. The nonlinear soil quality evaluation method had better applicability in this region, and the minimum data set was more accurate for soil quality evaluation.

Keywords: the northern slope of the Tianshan Mountains; vegetation; soil quality evaluation methods; principal component analysis; minimum data set (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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