Back to Search Start Over

Dynamic prediction and impact factors analysis of ecological risk in Chinese farming-pastoral ecotone.

Authors :
Yan, Jixuan
Li, Guang
Qi, Guangping
Yao, Xiangdong
Qiao, Hongqiang
Song, Miao
Gao, Pengcheng
Huang, Caixia
Li, Jie
Da, Qihong
Source :
Human & Ecological Risk Assessment; 2023, Vol. 29 Issue 1, p123-143, 21p
Publication Year :
2023

Abstract

Chinese Farming-pastoral Ecotones (CFPE) is the largest ecologically fragile zone in China. The dynamic prediction and impact factors analysis of landscape ecological risk based on LUCC have an important significance for effectively resolving ecological and environmental risk. In this paper, CA-Markov and BRT models were used to quantitatively analyze dynamic change, evolution characteristics, and influencing factors of landscape ecological risk.The results showed that: (1) LUCC types significantly changed from 2000 to 2040, especially in the bareland regions, which decreased by 1.64 times from 2000 to 2020, mainly transferred out to grassland and farmland. (2) The overall ecological risk showed a trend of increasing first and then decreasing. The highest ecological risk regions reached an area of 192,000 km<superscript>2</superscript> in 2020 and decreased by 1.78 times from 2020 to 2040, these areas showed high spatial correlation and aggregation. (3) Topographical, climate, and socioeconomic factors had certain impacts on landscape ecological risk. Elevation (24.4%) was the most important factor affecting ecological risk, followed by temperature (19.1%), precipitation (15.7%), slope (13.6%) and GDP (8.4%). The study not only proposes a novel method regarding prediction and quantitative assessment of ecological risk based on influencing factors, but also provides a more precise and specific decision-making basis for sustainable development of ecological safety and social economic in the CFPE. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10807039
Volume :
29
Issue :
1
Database :
Complementary Index
Journal :
Human & Ecological Risk Assessment
Publication Type :
Academic Journal
Accession number :
161545579
Full Text :
https://doi.org/10.1080/10807039.2022.2143318