Abstract

A clear understanding of the relationship between ecosystem services (ESs) and urbanization provides new insight into urban landscape planning and decision making. Although a considerable amount of literature has focused on this topic, few studies address the spatial interactions between ESs and urbanization, especially at the local scale. Various models and multisource data were integrated to estimate ESs and urbanization in Wuhan City, China. The bivariate Moran's I methods were employed to test and visualize the spatial correlations between ESs and urbanization. Spatial regression models were used to describe the spatial dependence of ESs on urbanization. Our results showed that all ESs have globally negative spatial correlations with urbanization, but focusing on local scale allowed spatial correlations to be categorized into four types: high ESs and high urbanization, high ESs and low urbanization, low ESs and high urbanization, and low ESs and low urbanization. Spatial regression models were identified as more suitable to measure the spatial dependence of ESs on urbanization, as they account for the effects of spatial autocorrelation. Among ESs, biodiversity conservation was the one most sensitive to increased urbanization, followed by outdoor recreation, water yield, grain productivity, carbon storage, and erosion prevention. The spatial exploration of the relationship between ESs and urbanization provides practical guidance for urban development planning and environmental protection.

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