Ecological risk assessment and influencing factor analysis of the Yellow River basin based on LUCC and boosted regression tree

The Yellow River basin is an important ecological security barrier and ecologically vulnerable region in China. Landscape ecological risk assessment and influencing factor analysis based on land-use/land-cover change (LUCC) and boosted regression tree (BRT) models are of great significance to the coordinated and sustainable development of regional ecological environment and social economy. Based on LUCC and driving factor data from 1980 to 2020, the ecological risk index (ERI) model was constructed to evaluate the spatiotemporal evolution characteristics of ecological risk in the past 40 years. Especially, a new method of influencing factor analysis based on the BRT model is proposed. The final index size of the influencing factors was further quantitatively evaluated. The results showed that the spatial distribution pattern of landscape ecological risk in the Yellow River basin was “highest in the north and lowest in the south, highest in the west and lowest in the east.” During the periods, the overall ecological risk and high risk increased first and then decreased. Elevation (24.8%) was the most important factor affecting landscape ecological risk, followed by precipitation (17.8%), GDP (15.2%), and temperature (14.6%). It showed that the particularity of the geographical location of the Yellow River basin eventually led to the stronger influence of natural factors on the change in landscape ecological risk under the interference of human activities. This study will provide a new perspective for quantitative assessment of the final contribution rate of landscape ecological risk factors.

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Publication Details

Journal
Frontiers in Environmental Science
Published
2024-09-26
DOI
https://doi.org/10.3389/fenvs.2024.1465475
Citations
3
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
0.85

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article

Ecological risk assessment and influencing factor analysis of the Yellow River basin based on LUCC and boosted regression tree

Miao Song, Xiangdong Yao, Guangping Qi, Hongqiang Qiao et al.
3 citations
Frontiers in Environmental Science
Land Use and Ecosystem Services
0.85
article

Ecological risk assessment and influencing factor analysis of the Yellow River basin based on LUCC and boosted regression tree

Miao Song, Xiangdong Yao, Guangping Qi, Hongqiang Qiao, Guang Li, Jie Li, Qiang Li, Jixuan Yan, Meihua Zhang, Pengcheng Gao
article en
3 citations

Abstract

The Yellow River basin is an important ecological security barrier and ecologically vulnerable region in China. Landscape ecological risk assessment and influencing factor analysis based on land-use/land-cover change (LUCC) and boosted regression tree (BRT) models are of great significance to the coordinated and sustainable development of regional ecological environment and social economy. Based on LUCC and driving factor data from 1980 to 2020, the ecological risk index (ERI) model was constructed to evaluate the spatiotemporal evolution characteristics of ecological risk in the past 40 years. Especially, a new method of influencing factor analysis based on the BRT model is proposed. The final index size of the influencing factors was further quantitatively evaluated. The results showed that the spatial distribution pattern of landscape ecological risk in the Yellow River basin was “highest in the north and lowest in the south, highest in the west and lowest in the east.” During the periods, the overall ecological risk and high risk increased first and then decreased. Elevation (24.8%) was the most important factor affecting landscape ecological risk, followed by precipitation (17.8%), GDP (15.2%), and temperature (14.6%). It showed that the particularity of the geographical location of the Yellow River basin eventually led to the stronger influence of natural factors on the change in landscape ecological risk under the interference of human activities. This study will provide a new perspective for quantitative assessment of the final contribution rate of landscape ecological risk factors.

Frontiers in Environmental ScienceVol. 12
Gansu Agricultural University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 27%
Land Use and Ecosystem Services
0.85
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