Analyses of driving factors on the spatial variations in regional eco-environmental quality using two types of species distribution models: A case study of Minjiang River Basin, China

Li, Yudong1; Li, Zhijian1; Wang, Junjian2; Zeng, Hui1

2022-06-01

10.1016/j.ecolind.2022.108980

ECOLOGICAL INDICATORS   影响因子和分区

1470-160X

1872-7034

Understanding the spatial variations in regional eco-environmental quality and their driving factors is essential for environmental management and protection. However, the lack of quantitative analyses in relevant studies has often hindered the formulation and implementation of effective eco-environmental policies. Taking Minjiang River Basin as an example, we used the remote sensing ecological indices (RSEI) to objectively and quantitatively characterize the eco-environmental quality. We also introduced and compared the maximum entropy (MaxEnt) and the random forest models to identify the critical driving factors. Results showed that the eco-environmental quality of Minjiang River Basin in 2020 was good overall, and the areas with good or excellent ecoenvironmental quality accounted for 58%. The areas with poor eco-environmental quality were mainly distributed in the periphery of the basin and the riverine areas. Both the MaxEnt and the random forest models were applicable to identify the critical driving factors and indicated that the degrees of landscape fragmentation and drastic land use were the main factors causing spatial variation of eco-environmental quality in the Minjiang River Basin. This study provides a new perspective and method for quantitative analysis of the driving factors of the spatial variations in regional eco-environmental quality for future eco-environmental management and protection.

Remote sensing ecological indices MaxEnt model Random forest model Minjiang River Basin Ecological and environmental quality

SCI ; EI

英语

其他

Shenzhen Fundamental Research Program[GXWD20201231165807007-20200812142216001]

Biodiversity & Conservation ; Environmental Sciences & Ecology

Biodiversity Conservation ; Environmental Sciences

WOS:000805241400004

ELSEVIER

20222212178366

Chemical analysis ; Decision trees ; Ecology ; Environmental management ; Factor analysis ; Land use ; Rivers ; Watersheds

Urban and Regional Planning and Development:403 ; Surface Water:444.1 ; Environmental Engineering, General:454.1 ; Environmental Impact and Protection:454.2 ; Ecology and Ecosystems:454.3 ; Combinatorial Mathematics, Includes Graph Theory, Set Theory:921.4 ; Mathematical Statistics:922.2 ; Systems Science:961

ENVIRONMENT/ECOLOGY

Web of Science

1.Peking Univ, Sch Urban Planning & Design, Shenzhen 518055, Guangdong, Peoples R China
2.Southern Univ Sci & Technol, Sch Environm Sci & Engn, State Environm Protect Key Lab Integrated Surface, Shenzhen 518055, Guangdong, Peoples R China

Li, Yudong,Li, Zhijian,Wang, Junjian,et al. Analyses of driving factors on the spatial variations in regional eco-environmental quality using two types of species distribution models: A case study of Minjiang River Basin, China[J]. ECOLOGICAL INDICATORS,2022,139.

Li, Yudong,Li, Zhijian,Wang, Junjian,&Zeng, Hui.(2022).Analyses of driving factors on the spatial variations in regional eco-environmental quality using two types of species distribution models: A case study of Minjiang River Basin, China.ECOLOGICAL INDICATORS,139.

Li, Yudong,et al."Analyses of driving factors on the spatial variations in regional eco-environmental quality using two types of species distribution models: A case study of Minjiang River Basin, China".ECOLOGICAL INDICATORS 139(2022).