Abstract

ContextThe relationships between ecosystem services (ES) and human well-being (HWB) have been found to be influenced by geographic locations and socioeconomic development, and vary from local to global scales. However, there is a lack of comparative analyses at fine administrative scales such as town and village scales.ObjectiveThis study took the core region of the Yangtze River Delta (YRD) of China as the study area to examine the spatial characteristics of the values of ES and the subjective satisfaction scores of HWB and then compare their relationships at the town and village scales.MethodsThe values of 9 ES indicators were quantified using the ecosystem service equivalent factor method, and the subjective satisfaction scores of 11 HWB indicators were investigated using the questionnaire survey. The ES-HWB relationships between 9 ES and 11 HWB measures in the study area were investigated using Spearman's correlation analysis.ResultsThe value of ES per unit area in the study area in 2020 was about 15,202.90 USD/ha, nearly three times the average level in China, but the per capita value was relatively low, at 322.11 USD/person. The satisfaction score of HWB was relatively high, especially for the dimensions of social relations (4.46), health (4.26), and safety (4.22), based on a 5-point Likert scale. As spatial scales decreased from town to village scales and thematic scales increased from secondary to primary indicators, the strength of the ES-HWB correlations diminished and their direction changed as well. According to secondary indicators, most of the ES-HWB relationships were positive at the town scale but became negative or nonexistent at the village scale (e.g. the Spearman correlation coefficient between the value of raw material supply and the satisfaction score of leisure and entertainment shifted from 0.9 at the town scale to -0.51 at the village scale).ConclusionsThe correlation strength and direction of the ES-HWB relationships still changed with spatial and thematic scales at the town and village scales. Thus, better understanding the relationships requires studies at multiple and broader scales and calls for caution when using the aggregating indicators, because they can also lead to different ES-HWB relationships.

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