Using PLE-SEM to Quantify the Impacts of Natural and Human Factors on Vegetation Change: A Case Study of the Jialing River Basin

Abstract

Vegetation cover is an important indicator reflecting changes in terrestrial ecosystems and plays an important role in regulating and maintaining ecosystem stability. To investigate the spatial and temporal variations in the NDVI (normalized difference vegetation index) and their intrinsic driving influences, this paper uses trend analysis and a barycentric model to study the temporal and spatial variation characteristics of vegetation in the Jialing River Basin from 2000 to 2020, constructs PLS-SEMs (partial least squares structural equation models), analyzes the indirect and direct effects of latent and observable variables of surface, human activities, and climate on vegetation growth, and explores the driving processes of different levels of NDVI. The vegetation center gradually migrates northwards. The impact of surface factors on the NDVI is mainly direct and positive. The impact of human activities on the NDVI is mainly direct and negative. The impact of climate factors on the NDVI is mainly positive. The driving mechanisms of low and medium NDVI are relatively similar but tend to be opposite to those of high NDVI. Medium and high NDVI values are more influenced by observable variables. The research on vegetation change and its driving factors, through indirect and direct paths, illustrates the driving processes of different latent and observable variables of the NDVI in more detail and provides a theoretical basis for the implementation of ecological restoration projects and construction of ecological civilizations in the future.