Exploring the coupling of ecosystem services and human well-being: evidence from Chinese cities through interpretable machine learning

• Multiple machine learning models to analyze the factors influencing. • The ESV-HDI coupling harmonization in China increased significantly. • Per capita forest area is the most important driving factor. • The driving factors exhibit nonlinear characteristics. • Climate change profoundly affects regional ecosystem services and human well-being. To achieve the development goal of harmonious coexistence within urban human–land systems, it is essential to conduct an in-depth exploration of the coupling coordination between human well-being and ecosystems. This study first constructs a human–land coupling system model to measure the coupling coordination degree between ecosystem service value and human well-being in Chinese cities. Second, box plots, kernel density analysis, and other methods are employed to investigate the spatiotemporal evolution characteristics of the coupling coordination degree. In addition, interpretable machine learning was applied to identify the feature importance, threshold effects, and interactions among variables affecting the coupling coordination degree. The results show that from 2000 to 2022, the coupling coordination degree between ESV and HDI in Chinese cities increased slowly, rising from 0.254 to 0.326. This improvement was mainly driven by the rapid growth of human well-being, with the HDI increasing from 0.526 to 0.784. The findings further confirm that both natural factors and human activities exert significant influences on the human–land coupling system, particularly variables such as per capita forest area, total land area, total population, per capita arable land, and precipitation. Moreover, the impact pathways of these variables exhibit nonlinear characteristics, with evident threshold effects. Precipitation, temperature, and sunshine duration show significant interaction effects with other variables. The findings contribute to monitoring the coordinated evolution of urban ecosystems and human well-being, and to promoting harmonious coexistence between humans and nature.

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Publication Details

Journal
Ecological Indicators
Published
2025-10-22
DOI
https://doi.org/10.1016/j.ecolind.2025.114315
Citations
4
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
4.42
Controls
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article

Exploring the coupling of ecosystem services and human well-being: evidence from Chinese cities through interpretable machine learning

Xingren Yao, Fang Shi-jiao
4 citations
Ecological Indicators
Land Use and Ecosystem Services
4.42
article

Exploring the coupling of ecosystem services and human well-being: evidence from Chinese cities through interpretable machine learning

Xingren Yao, Fang Shi-jiao
article en
4 citations

Abstract

• Multiple machine learning models to analyze the factors influencing. • The ESV-HDI coupling harmonization in China increased significantly. • Per capita forest area is the most important driving factor. • The driving factors exhibit nonlinear characteristics. • Climate change profoundly affects regional ecosystem services and human well-being. To achieve the development goal of harmonious coexistence within urban human–land systems, it is essential to conduct an in-depth exploration of the coupling coordination between human well-being and ecosystems. This study first constructs a human–land coupling system model to measure the coupling coordination degree between ecosystem service value and human well-being in Chinese cities. Second, box plots, kernel density analysis, and other methods are employed to investigate the spatiotemporal evolution characteristics of the coupling coordination degree. In addition, interpretable machine learning was applied to identify the feature importance, threshold effects, and interactions among variables affecting the coupling coordination degree. The results show that from 2000 to 2022, the coupling coordination degree between ESV and HDI in Chinese cities increased slowly, rising from 0.254 to 0.326. This improvement was mainly driven by the rapid growth of human well-being, with the HDI increasing from 0.526 to 0.784. The findings further confirm that both natural factors and human activities exert significant influences on the human–land coupling system, particularly variables such as per capita forest area, total land area, total population, per capita arable land, and precipitation. Moreover, the impact pathways of these variables exhibit nonlinear characteristics, with evident threshold effects. Precipitation, temperature, and sunshine duration show significant interaction effects with other variables. The findings contribute to monitoring the coordinated evolution of urban ecosystems and human well-being, and to promoting harmonious coexistence between humans and nature.

Ecological IndicatorsVol. 180
Zhongnan University of Economics and Law (CN)
Openalex Percentile: Top 5%
Land Use and Ecosystem Services
4.42
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Exploring the coupling of ecosystem services and human well-being: evidence from Chinese cities through interpretable machine learning — Xingren Yao, Fang Shi-jiao · Ecological Indicators (2025) | TGRS Research Map | TGRS