Application of soil quality index to determine the effects of different vegetation types on soil quality in the Yellow River Delta wetland. (August 2022)

• Record Type: Journal Article
• Authors: Zhang, Yinghu; Wang, Lu; Jiang, Jiang; Zhang, Jinchi; Zhang, Zhenming; Zhang, Mingxiang
• Is Part Of: Ecological indicators. Volume 141(2022)
• Publication Date: 2022-08
• Subjects: ISWC initial soil water content -- SBD soil bulk density -- TSP total soil porosity -- SCP soil capillary porosity -- SNCP soil non-capillary porosity -- SOC soil organic carbon -- STN soil total nitrogen -- STP soil total phosphorus -- SAP soil available phosphorus -- SEC soil electronic conductivity -- RLD root length density; Soil properties -- Soil quality index -- Indicator -- Yellow River Delta wetland; Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2022.109116
• Languages: English
• ISSNs: 1470-160X

Abstract

Highlights: Variation in soil properties at tree, bush, and grass sites in wetlands was examined. Soil quality index (SQI) was characterized to assess soil quality at the three sites. SQI in surface soils (0–10 cm) was higher at tree/grass site than that at bush site. SQI in deeper soils (10–60 cm) was significantly lower than that in surface soils. Soil organic carbon and total soil porosity were the key soil quality indicators. Abstract: Assessment of soil quality in different vegetation types of wetland ecosystems is essential for soil functioning, such as nutrient cycling and vegetation growth, particularly the maintenance of wetland ecosystem sustainability. Wetland degradation can extremely influence soil quality. However, prediction of soil quality in terms of soil quality index in wetland soils remains obscure. In this study with the fundamental goal to assess soil quality, we have intended to assemble a range of soil quality indicators to characterize the soil quality index (SQI). The minimum data set (MDS) from the Principal component analysis (PCA) was used to determine the SQI. With such objectives, three vegetation types: Robinia pseudoacacia community (tree), Tamarix chinensis community (bush), and Suaeda salsa community (grass) were selected in the Yellow River Delta wetland, eastern of China. A total of 108 soil samples [3 sites (tree, bush and grass)—3 field plots—3 replicates—4 soil depth layers: 0–10 cm, 10–20 cm, 20–40 cm, and 40–60 cm] were collected for laboratory analyses. This study showed that there were high variations in soil physical and chemical properties among the three sites. Soil organic carbon (SOC), silt, clay, and pH at tree site, total soil porosity (TSP), soil organic carbon (SOC), pH, and soil bulk density (SBD) at bush site, and total soil porosity (TSP), silt, and soil electronic conductivity (SEC) at grass site were retained in the MDS. SOC and TSP were the key soil quality indicators. The values of the SQI at 0–10 cm soil depth at all three sites (2.236, 0.895, and 2.573 respectively) were the highest compared with other soil depths, indicating the best soil quality in the upper soil layers (0–10 cm). The values of the SQI at 0–10 cm soil depth at both tree site and grass site were similar, and they were higher than those at bush site. At tree site, the values of the SQI decreased with increasing soil depth, which indicated that soil quality became worse with depth. At bush site, the values of the SQI decreased with increasing soil depth (0–40 cm), while the values increased at 40–60 cm depth, indicating better soil quality in the deeper soil layers (40–60 cm). At grass site, the values of the SQI at 10–20 cm and 40–60 cm soil depth were lower than those at 20–40 cm soil depth, indicating better soil quality at 20–40 cm soil depth. It is concluded that the SQI can be compared more accurately in different vegetation types of wetland ecosystems based on its simplicity and quantitative flexibility. These findings are of importance because the assessment of the SQI allows to quantify different vegetation effects on soil quality.