Agents Affecting the Plant Functional Traits in National Soil and Water Conservation Demonstration Park (China)

• Published in: Plants (Basel) Vol. 11; no. 21; p. 2891
• Main Authors: Duan, Gaohui, Wen, Zhongming, Xue, Wei, Bu, Yuankun, Lu, Jinxin, Wen, Bojin, Wang, Boheng, Chen, Sihui
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 28-10-2022; MDPI
• Subjects: Abiotic factors; Adaptability; Altitude; Analysis; Chemical elements; China; Ecosystem components; Ecosystems; Environmental aspects; Grasslands; Herbs; Humidity; Laboratories; Leaves; Methods; Moisture content; Multivariate statistical analysis; Parks; Physiological aspects; plant functional traits; Plants; plants diversity; PLS-SEM; random forest algorithm; Resource utilization; Soil conditions; Soil conservation; Soil moisture; Soil properties; Soil structure; Soil water; Structural equation modeling; Topography; Variables; Vegetation; Water conservation; Water content; Water shortages; China
• ISSN: 2223-7747; 2223-7747
• DOI: 10.3390/plants11212891

Plant functional traits (PFTs) can reflect the response of plants to environment, objectively expressing the adaptability of plants to the external environment. In previous studies, various relationships between various abiotic factors and PFTs have been reported. However, how these factors work together to influence PFTs is not clear. This study attempted to quantify the effects of topographic conditions, soil factors and vegetation structure on PFTs. Four categories of variables were represented using 29 variables collected from 171 herb plots of 57 sites (from different topographic and various herb types) in Xindian SWDP. The partial least squares structural equation modeling showed that the topographic conditions and soil properties also have a direct effect on plant functional traits. Among the topographic conditions, slope (SLO) has the biggest weight of 0.629, indicating that SLO contributed the most to plant functional traits and vegetation structure. Among soil properties, maximum water capacity (MWC) contributes the most and is followed by soil water content (SWC), weighted at 0.588 and 0.416, respectively. In a word, the research provides new points into the quantification of the correlation between different drivers that may be important for understanding the mechanisms of resource utilization, competition and adaptation to the environment during plant recovery.