Spatiotemporal evolution and driving factors of tourism ecological adaptation in the Dongting Lake Area, China

Abstract

Tourism ecological adaptation (TEA) offers a novel research framework and practical tool for analyzing sustainable regional development. This facilitates high-quality tourism development, safeguards the ecosystem, and enhances risk resilience. However, existing TEA research has shortcomings regarding methodology and research scales. This study constructed a TEA index system to address these deficiencies. The index system comprises two subsystems, tourism industry adaptation (TIA) and ecological environment adaptation (EEA), including three dimensions: sensitivity, stability, and response. The entropy-weighted TOPSIS method, adaptation assessment model, standard deviation ellipse, and geographic detector were used to analyze the spatiotemporal evolution and driving factors of TEA in the Dongting Lake area, China, from 2012 to 2021. The TIA index displays a rise-fall-rise pattern, whereas the EEA index demonstrates a fluctuating upward trend. Additionally, the TEA index exhibits a distinctive basin-type spatial distribution pattern, with lower values in the central region and higher values in the surrounding areas. Over the past decade, standard deviation ellipses of adaptability have shown minimal changes in shape, position, and center. Both the clustering and center positions reached a state of basic equilibrium. The predominant TEA type was characterized by low adaptation, including 41.18% of the counties. The spatiotemporal evolution of TEA is driven by tourism resource endowment, government regulatory efforts, level of economic development, and environmental governance capacity