4.7 Article

Assessment of ecosystem service flow and optimization of spatial pattern of supply and demand matching in Pearl River Delta, China

期刊

ECOLOGICAL INDICATORS
卷 153, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.ecolind.2023.110452

关键词

Ecosystem service flow; Supply and demand matching; Drivers; Spatial pattern optimization; Urban agglomeration; The Pearl River Delta

向作者/读者索取更多资源

This paper explores the spatial flow pattern of ecosystem services and clarifies the transmission path between the supply area and the demand area, aiming to formulate more scientific and reasonable ecological protection policies. Using the Pearl River Delta urban agglomeration as an example, the Invest model is used to assess the supply and demand of carbon sequestration services and water ecosystem services from 2000 to 2020. A spatial flow model of ecosystem services is constructed to clarify the regional spatial flow pattern. The Geo-detector model is used to explore the driving factors of the supply and demand relationship, and the spatiotemporal geographic weighted regression model is further used to analyze the impact degree. Based on the Bayesian belief network, the optimal state factor configuration is selected to optimize the spatial pattern, and the corresponding optimization strategy is given. The main conclusions are as follows: (1) The supply of carbon sequestration services in the Pearl River Delta decreased gradually during 2000-2020, while the demand increased gradually. The supply of water ecosystem services increased first and then decreased, while the demand showed a downward trend. (2) The main driving factors of carbon sequestration services include night light brightness value, temperature, and vegetation index. The main driving factors of water ecosystem services include night light brightness value, land use type, and vegetation index. (3) The optimal areas for supply and demand matching of carbon sequestration services are mainly distributed in Zhaoqing, Huizhou, and Jiangmen. The optimal matching areas of water ecosystem service supply and demand are mainly distributed in Zhaoqing, Guangzhou, Huizhou, and other cities.
Exploring the spatial flow pattern of ecosystem services and clarifying the transmission path between the supply area and the demand area will help to formulate more scientific and reasonable ecological protection policies. This paper takes the rapid urbanization area representing the Pearl River Delta urban agglomeration as an example. Using Invest model to quantitative the assessment of the supply and demand of carbon sequestration services and water ecosystem services from 2000 to 2020, a spatial flow model of ecosystem services is constructed to clarify the spatial flow of regional ecosystem services pattern. In addition, the Geo-detector model is used to explore the driving factors of the supply and demand relationship of ecosystem services, and the spatiotemporal geographic weighted regression model is further used to analyze the temporal and spatial differentiation of the impact degree. Finally, based on the Bayesian belief network, the optimal state factor configuration is selected to optimize the spatial pattern, and the corresponding optimization strategy is given. The main conclusions are as follows: (1) The supply of carbon sequestration services in the Pearl River Delta decreased gradually during 2000-2020, while the demand increased gradually. The supply of water ecosystem services increased first and then decreased, while the demand showed a downward trend. (2) In terms of spatial heterogeneity of supply and demand matching, the main driving factors of carbon sequestration services included night light brightness value, temperature and vegetation index; The main driving factors of water ecosystem services include night light brightness value, land use type and vegetation index. (3) In terms of optimal areas for supply and demand matching, carbon sequestration services were mainly distributed in Zhaoqing, Huizhou and Jiangmen; The optimal matching areas of water ecosystem service supply and demand were mainly distributed in Zhaoqing, Guangzhou, Huizhou and other cities.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据