Journal
JOURNAL OF CLEANER PRODUCTION
Volume 257, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2020.120454
Keywords
Ecosystem services; Synergy and tradeoff; Geographically weighted logistic regression; Spatial correlation; Land use types; Fujian
Categories
Funding
- National Key Research and Development Program, China [2017YFB0503500]
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Determining what factors affect the relationship between ecosystem services (benefits people derive from ecosystems) and how the impact distributed, is conducive to strengthening ecological governance and improving the sustainable development of the ecological environment. However, previous studies remained difficulties in directly regressing with potential impact factors after spatializing the relationship between ecosystem services (ESs) and neglected the impact of urbanization. Therefore, we asked the following: (i) Whether the relationship between ecosystem services is spatially heterogeneous? (ii) Whether the relationship between ecosystem services is only related to the natural environment or is also affected by urbanization? (iii) Are the correlations between such relationship and latent influencing factors consistent in space? In this study, we mapped the relationships between four ESs (grain productivity, carbon storage, outdoor recreation, and biodiversity conservation), and analyzed the spatial correlation between such relationships and ecological factors and urbanization factors, using geographically weighted logical regression (GWLR). The relationship between ESs is spatially heterogeneous, and a refined mechanism for the relationship between ESs was proposed in this study to explain it. The occurrence of the synergy and tradeoff between ESs is not only related to the natural environment but also affected by urbanization, that the relationships are robustly correlated to landform factor, meteorological factors, and urbanization factors; and the properties and intensity of the correlations varied with space. This study allows generalization, that the data, models, and software used in this study are universal in the field; the relevant factors selected in this study are also universal and meaningful in other study areas; research in other regions or larger scale regions can refer to the method and mechanism proposed in this study. (C) 2020 Elsevier Ltd. All rights reserved.
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