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<p>Ecosystem service value (ESV) constitutes the ecological value foundation for enhancing tourism economic resilience (TER), serving as the central catalytic mechanism that drives the synergistic evolution of system disturbance resistance, recovery efficiency, and transformative adaptability. This study conducts a comprehensive evaluation of the interrelation between ESV and TER while exploring the key influencing factors to optimize human-environment interactions within the tourism system. The Coupling Coordination Degree (CCD) model is utilized to examine the association between ESs and TER across China. Additionally, spatial evolution patterns and key driving factors are explored using Exploratory Spatial Data Analysis (ESDA) and Geographically Weighted Regression (GWR). The key findings are as follows: (1) ESV displayed an inverted “N” trend, declining from southeast to northwest. (2) The spatial distribution of TER showed a persistent pattern of “high in the south, low in the north,” indicating a sustained stage of coordination. (3) The CCD of TER revealed positive spatial clustering, characterized by a distinct “two poles” pattern. (4) Economic and tourism-related factors were the dominant forces enhancing the CCD of TER, while social factors imposed constraints. These insights can support regional tourism economic planning and ecosystem management strategies.</p>

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The co-evolution and driving mechanism analysis of ecosystem services value and tourism economic resilience from 286 cities in China

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年5月10日

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  • Shuang Zhao,
  • Zhengyong Yu,
  • Wei Liu

摘要

Ecosystem service value (ESV) constitutes the ecological value foundation for enhancing tourism economic resilience (TER), serving as the central catalytic mechanism that drives the synergistic evolution of system disturbance resistance, recovery efficiency, and transformative adaptability. This study conducts a comprehensive evaluation of the interrelation between ESV and TER while exploring the key influencing factors to optimize human-environment interactions within the tourism system. The Coupling Coordination Degree (CCD) model is utilized to examine the association between ESs and TER across China. Additionally, spatial evolution patterns and key driving factors are explored using Exploratory Spatial Data Analysis (ESDA) and Geographically Weighted Regression (GWR). The key findings are as follows: (1) ESV displayed an inverted “N” trend, declining from southeast to northwest. (2) The spatial distribution of TER showed a persistent pattern of “high in the south, low in the north,” indicating a sustained stage of coordination. (3) The CCD of TER revealed positive spatial clustering, characterized by a distinct “two poles” pattern. (4) Economic and tourism-related factors were the dominant forces enhancing the CCD of TER, while social factors imposed constraints. These insights can support regional tourism economic planning and ecosystem management strategies.