Spatiotemporal Evolution of Ecosystem Health of China's Provinces Based on SDGs

基于可持续发展目标的中国各省生态系统健康时空演变

阅读:1

Abstract

In the context of increasing ecological scarcity, maintaining the balance between natural and artificial capital has become a popular research topic in the field of ecosystem health. From the perspective of coordinating natural and artificial capital and maintaining the balance between human systems and the Earth's ecosystem, the Ecosystem Health Index (EHI) was developed on the basis of the Sustainable Development Goals (SDGs). The EHI consists of the Social Progress Index (SPI), Economic Development Index (EDI), Natural Environment Index (NEI), and a pressure adjustment coefficient. Comprehensive indicator assessment models were used to analyze the spatial and temporal evolution of the EHIs in 30 of China's provinces from 2013 to 2019. A three-dimensional judgment matrix was used to classify the 30 provinces into four basic types. The results show the following: (1) From 2013 to 2019, the EHIs of all provinces improved to different degrees, with 19 provinces achieving a healthy state. (2) Spatially, the EHI showed some regional aggregation in 2013. Provinces with high EHIs were concentrated in the west, followed by those in the east, and those in the central provinces had the lowest EHIs. However, the differences between regions had narrowed by 2019. (3) The spatial distribution patterns of the NEI and the EDI varied widely, and most provinces did not reach a high level of coordination between natural and artificial capital. (4) The environmental pressure in all provinces, except Liaoning, decreased over time. In some cases, excessive pressure decreased the pressure-adjusted EHI, regardless of the EHI value. (5) According to the results of the ecosystem health classification in each province, the factors that hinder ecosystem health vary from place to place.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。