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https://doi.org/10.1016/j.ecolind.2021.108299
Title: | The spatial relationship between ecosystem service scarcity value and urbanization from the perspective of heterogeneity in typical arid and semiarid regions of China | Authors: | Li, Rong Shi, Yu Feng, Chen-Chieh Guo, Luo |
Keywords: | Ecosystem services scarcity value Geographically weighted regression model Urbanization |
Issue Date: | 1-Dec-2021 | Publisher: | Elsevier B.V. | Citation: | Li, Rong, Shi, Yu, Feng, Chen-Chieh, Guo, Luo (2021-12-01). The spatial relationship between ecosystem service scarcity value and urbanization from the perspective of heterogeneity in typical arid and semiarid regions of China. Ecological Indicators 132 : 108299. ScholarBank@NUS Repository. https://doi.org/10.1016/j.ecolind.2021.108299 | Rights: | Attribution-NonCommercial-NoDerivatives 4.0 International | Abstract: | Rapid expansions of urban areas and the intensification of human activities have severely impacted ecosystems and ecosystem service provisions. Considering limited availability of ecosystem services, the evaluation of ecosystem service value should consider its fluctuations supply and demand due to urbanization, i.e., the ecosystem service scarcity value (ESSV). Taking typical arid and semiarid regions of China and the Ningxia Hui Autonomous Region as an example, the effects of different scarcity factors on the scarcity value of ecosystem services were compared. At the same time, a geographically weighted regression model (GWR) was developed to analyze the spatial relationships between urbanization and the scarcity value of ecosystem services. The results suggest that demand-driven scarcity is the most important factor affecting the ESSV in Ningxia, and between 1990 and 2015, the ESSV in Ningxia increased significantly, with increase being more evident from 2005 to 2015. Among the different types of ecosystem services, the scarcity values of ecosystem services such as air quality, waste treatment, soil retention, biodiversity services, and recreation and culture increased significantly from 1990 to 2015. Spatially, the total ESSV and the ESSV of different ecosystem service types exhibited evident spatial heterogeneity due, to spatial distribution characteristics of land-use type, population density and per capita GDP. The GWR modeling result shows, that the impact of urbanization on ESSV was positively correlated overall. The ESSV of food production, raw material, air quality, climate regulation and water supply are greatly affected by urbanization, while the ESSV of biodiversity services and recreation and culture are less affected by urbanization. Meanwhile, the High-Low type and Low-High type had significant aggregation effects in the study area. © 2021 The Authors | Source Title: | Ecological Indicators | URI: | https://scholarbank.nus.edu.sg/handle/10635/231907 | ISSN: | 1470-160X | DOI: | 10.1016/j.ecolind.2021.108299 | Rights: | Attribution-NonCommercial-NoDerivatives 4.0 International |
Appears in Collections: | Elements Staff Publications |
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