Interspecific Integration of Chemical Traits in Desert Plant Leaves with Variations in Soil Water and Salinity Habitats

Abstract

Understanding the relationship between soil environmental conditions and the interspecific integration of plant traits might shed light on how plants adapt to their environment. In order to clarify the adaptation strategies of desert plants in the various habitats, this study calculated interspecific trait integration (ITI) and plant trait networks (PTN) by selecting plants from high water-salinity habitat (HSM) with salt stress and low water-salinity habitat (LSM) with drought stress in the Ebinur Lake region. Eight different phytochemical traits were taken into consideration, including carbon (C), nitrogen (N), phosphorus (P), sulfur (S), potassium (K), calcium (Ca), sodium (Na), and magnesium (Mg). Six soil factors were chosen, including soil pH, water content (SVWC), electrical conductivity (EC), soil nitrogen (N), phosphorus (P), and potassium (K). The results obtained are shown below: (1) the relationship between plant leaf chemical traits was closer in HSM than in LSM, and the correlation between C and other leaf chemical traits was significant in HSM and insignificant in LSM; (2) the correlations between soil factors and ITI were not statistically significant; however, in both soil water-salinity habitats, the strength of fit between SVWC and ITI was the greatest, while the strength of fit between EC and ITI was the smallest; and (3) according to the PTN, C and Ca are the two most central traits for the growth of desert leaf chemical plants in Ebinur Lake, which is consistent with the results of the PCA. Coordination of plant leaf traits along water-salinity gradients involves many different combinations of traits, and the use of ITI and PTN can quantify the complex relationships between multiple traits to a greater extent, highlighting the multivariate mechanisms of plant response and adaptation to soil habitats. This information will help expand and optimize our ability to observe and predict desert plant responses to habitat change, providing powerful insights for assessing desert plant survival strategies.