Spatial and temporal patterns of ecosystem health in the Yangtze River Economic Zone and their influencing factors
To promote the healthy management and sustainable development of regional ecosystems,the Yangtze River Economic Belt was taken as the study area to construct an ecosystem health assessment system based on the concept of"Vitality-Organization-Resilience-Ecosystem Services",and analyze the spatial and temporal evolution of ecosystem health in 2000,2010 and 2020,We analyzed the spatial and temporal evolution of ecosystem health in the Yangtze River Economic Zone in 2000,2010 and 2020,and analyzed the main influencing factors and their spatial differentiation characteristics by using geodetectors and geographically weighted regression models.The results showed that:1)From 2000 to 2020,the ecosystem health of the Yangtze River Economic Zone displayed a decreasing trend,which was from 0.588 in 2000 to 0.569 in 2020;2)On the whole,the ecosystem health of the Yangtze River Economic Zone had a strong spatial correlation,and its spatial agglomeration effect shows the basic trend of"high in the south and low in the north".The high-high agglomeration mainly distributed in the southern region of the middle and lower reaches,low-low agglomeration mainly distributed in the northern region of the lower reaches,and low-high agglomeration and high-low agglomeration distributed in a piecemeal manner.3)The main influencing factors on ecosystem health in the Yangtze River Economic Zone were manifested as follows:vegetation cover＞urbanization＞population density＞elevation,and there was obvious spatial heterogeneity in the influence of each driving factor on ecosystem health.This study reveals the spatial and temporal patterns of ecosystem health and its influencing factors in the Yangtze River Economic Belt from 2000 to 2020,which can provide a basis for formulating differentiated and refined ecological management strategies in the Yangtze River Economic Belt.
ecosystem healthspatial and temporal patternsGeodetectorgeo-weighted regression modelYangtze River Economic Belt
国家科技期刊平台
NSTL
万方数据
