Scholarlink

<p>Differences in geographical location influence hydrology, vegetation, and other environmental conditions, thereby affecting ecosystem service value (ESV). However, how ESV patterns and their nonlinear association mechanisms vary among cities with distinct climatic backgrounds remains insufficiently quantified under a unified valuation framework. We selected representative cities across China’s five major climate zones and adjusted ESV from natural, social, and economic perspectives to characterize its spatiotemporal dynamics. We then identified climate-related natural indicators and applied the XGBoost–SHAP model to quantify the nonlinear effects of climate-related natural indicators on ESV. Finally, statistical models were used to assess inter-city ESV differences, revealing three key findings: (1) Lhasa and Urumqi showed high ESV but fluctuated markedly due to plateau ecology and oasis water resources, while Shanghai and Haikou remained at low ESV levels under high-intensity urbanization. High values in Lhasa were homogeneously and stably distributed, low values in Shanghai and Haikou were diffuse, and those in Beijing and Urumqi were patchy. (2) ESV differed significantly among the five selected cities with distinct climatic backgrounds (ANOVA: <i>p</i> &lt; 0.001), indicating substantial cross-city heterogeneity in ESV patterns. (3) The nonlinear association mechanisms of ESV showed clear regional heterogeneity. Vegetation structure was more influential in Beijing, Haikou, Lhasa, and Urumqi, whereas hydrological conditions played a more prominent role in Shanghai. These differences indicate that ESV responses are shaped by city-specific combinations of vegetation, water availability, thermal conditions, and land-use structure. The results provide a more refined assessment framework for land-use evaluation and large-scale ecological management across typical cities with distinct climatic backgrounds, supporting future policy formulation, spatial planning, and sustainable urban governance.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Spatiotemporal patterns and nonlinear drivers of urban ecosystem service value across cities in different climate zones

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月6日

查看全文
  • Xiqian Wang,
  • Chenfeng Xu

摘要

Differences in geographical location influence hydrology, vegetation, and other environmental conditions, thereby affecting ecosystem service value (ESV). However, how ESV patterns and their nonlinear association mechanisms vary among cities with distinct climatic backgrounds remains insufficiently quantified under a unified valuation framework. We selected representative cities across China’s five major climate zones and adjusted ESV from natural, social, and economic perspectives to characterize its spatiotemporal dynamics. We then identified climate-related natural indicators and applied the XGBoost–SHAP model to quantify the nonlinear effects of climate-related natural indicators on ESV. Finally, statistical models were used to assess inter-city ESV differences, revealing three key findings: (1) Lhasa and Urumqi showed high ESV but fluctuated markedly due to plateau ecology and oasis water resources, while Shanghai and Haikou remained at low ESV levels under high-intensity urbanization. High values in Lhasa were homogeneously and stably distributed, low values in Shanghai and Haikou were diffuse, and those in Beijing and Urumqi were patchy. (2) ESV differed significantly among the five selected cities with distinct climatic backgrounds (ANOVA: p < 0.001), indicating substantial cross-city heterogeneity in ESV patterns. (3) The nonlinear association mechanisms of ESV showed clear regional heterogeneity. Vegetation structure was more influential in Beijing, Haikou, Lhasa, and Urumqi, whereas hydrological conditions played a more prominent role in Shanghai. These differences indicate that ESV responses are shaped by city-specific combinations of vegetation, water availability, thermal conditions, and land-use structure. The results provide a more refined assessment framework for land-use evaluation and large-scale ecological management across typical cities with distinct climatic backgrounds, supporting future policy formulation, spatial planning, and sustainable urban governance.