Ecological Indicators (Feb 2021)
A novel characterization on the interaction of soil and vegetation in a reclaimed area of opencast coalmine based on joint multi-fractal method
Abstract
Soil and vegetation, as the basic structural unit of artificial ecosystems, play an important role in ecological restoration in opencast coal mining areas, and both exhibit a complex interaction. However, the traditional method cannot well characterize the inter action between the soil and vegetation. In order to reveal the interaction between soil and vegetation in the reclaimed area of opencast coalmine, and explore the interaction mechanism between soil and vegetation, the soil and vegetation data from 70 reclaimed points in Antaibao and Anjialing opencast coal mines in Shanxi province of China were selected to conduct an investigation study. Ten soil and three vegetation indicators were determined, and the joint multifractal method was innovatively introduced to characterize the relationships of soil and vegetation on multiple scales using joint multifractal spectra and grayscale images. The interaction between soil and vegetation can be clearly obtained using the joint multifractal method. The canopy density was negatively correlated with soil bulk density, silt content, and pH; whereas, it was positively correlated with rock content, sand content, total nitrogen, soil organic matter, available phosphorus, and available potassium content. The average diameter at breast height was negatively correlated with soil bulk density, clay content, and pH; however, it was positively correlated with silt content, sand content, total nitrogen, soil organic matter, available phosphorus, and available potassium content. The herb coverage was negatively correlated with rock content, silt content, clay content, pH, soil organic matter, available phosphorus and available potassium content. Soil bulk density and clay content showed negative correlation with herb coverage. Compared to the traditional method, the novel joint multifractal method can more accurately charecterize the correlations from multiple scales. This novel method can be used to study the interaction between soil and vegetation.
