Exploring ecosystem sensitivity patterns in China: A quantitative analysis using the Importance-Vulnerability-Sensitivity framework and neighborhood effects method

• Developed sensitivity evaluation framework based on importance and vulnerability. • Constructed a land use neighborhood matrix based on the neighborhood effect method. • The ecological sensitivity corrected by neighborhood effect is more reasonable. • We found significant spatial variation in China’s ecological sensitivity in 2020. In tandem with societal and economic progress, ecological and environmental issues have emerged as pivotal constraints to the sustainable development of China’s economy and society. While the impacts of land use are widely acknowledged as a significant factor in ecological changes, studies on ecological sensitivity often overlook the effects of land use edge dynamics in rapidly urbanizing, fragmented landscapes, leading to inadequate evaluation frameworks. This paper establishes an evaluation framework encompassing ecosystem importance-vulnerability-sensitivity to assess China’s ecological sensitivity in 2020 amid various external disturbances. The neighborhood effect method was employed to formulate a neighborhood matrix capturing interactions among various land use categories. This enabled the quantification of the impacts of interactions between different land use types on ecological sensitivity, subsequently leading to the correction of ecological sensitivity results in China. The findings indicate that the ecological sensitivity, when adjusted for the neighborhood effects method, offers more nuanced and reasonable details. The spatial variation of ecological sensitivity in China is noteworthy, with areas of extreme sensitivity and high sensitivity concentrated in the southeastern hills, northwestern mountains, Yunnan-Guizhou Plateau-Hengduan Mountains, northeastern mountains, and the Qinghai-Tibetan Plateau. The comprehensive evaluation results of ecological sensitivity revealed a trend of spatial distribution fragmentation, with extremely sensitive and highly sensitive areas primarily distributed in woodland and grassland, and less sensitivity observed in artificial land, water, and cropland. Further factor analysis of ecological sensitivity results identified that the significance of wind and sand fixation and soil conservation are crucial factors influencing ecological sensitivity, and the superposition of these factors enhances the explanatory power of ecological sensitivity. This study provides a scientific basis for preserving natural resources and managing ecological environments in China.

Authors

Institutions

Publication Details

Journal
Ecological Indicators
Published
2024-09-19
DOI
https://doi.org/10.1016/j.ecolind.2024.112623
Citations
10
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
2.83

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Exploring ecosystem sensitivity patterns in China: A quantitative analysis using the Importance-Vulnerability-Sensitivity framework and neighborhood effects method

Junfeng Kang, Tao Liu, Lei Fang, Wenqian Dong
10 citations
Ecological Indicators
Land Use and Ecosystem Services
2.83
article

Exploring ecosystem sensitivity patterns in China: A quantitative analysis using the Importance-Vulnerability-Sensitivity framework and neighborhood effects method

Junfeng Kang, Tao Liu, Lei Fang, Wenqian Dong
article en
10 citations

Abstract

• Developed sensitivity evaluation framework based on importance and vulnerability. • Constructed a land use neighborhood matrix based on the neighborhood effect method. • The ecological sensitivity corrected by neighborhood effect is more reasonable. • We found significant spatial variation in China’s ecological sensitivity in 2020. In tandem with societal and economic progress, ecological and environmental issues have emerged as pivotal constraints to the sustainable development of China’s economy and society. While the impacts of land use are widely acknowledged as a significant factor in ecological changes, studies on ecological sensitivity often overlook the effects of land use edge dynamics in rapidly urbanizing, fragmented landscapes, leading to inadequate evaluation frameworks. This paper establishes an evaluation framework encompassing ecosystem importance-vulnerability-sensitivity to assess China’s ecological sensitivity in 2020 amid various external disturbances. The neighborhood effect method was employed to formulate a neighborhood matrix capturing interactions among various land use categories. This enabled the quantification of the impacts of interactions between different land use types on ecological sensitivity, subsequently leading to the correction of ecological sensitivity results in China. The findings indicate that the ecological sensitivity, when adjusted for the neighborhood effects method, offers more nuanced and reasonable details. The spatial variation of ecological sensitivity in China is noteworthy, with areas of extreme sensitivity and high sensitivity concentrated in the southeastern hills, northwestern mountains, Yunnan-Guizhou Plateau-Hengduan Mountains, northeastern mountains, and the Qinghai-Tibetan Plateau. The comprehensive evaluation results of ecological sensitivity revealed a trend of spatial distribution fragmentation, with extremely sensitive and highly sensitive areas primarily distributed in woodland and grassland, and less sensitivity observed in artificial land, water, and cropland. Further factor analysis of ecological sensitivity results identified that the significance of wind and sand fixation and soil conservation are crucial factors influencing ecological sensitivity, and the superposition of these factors enhances the explanatory power of ecological sensitivity. This study provides a scientific basis for preserving natural resources and managing ecological environments in China.

Ecological IndicatorsVol. 167
Peking University (CN), Ministry of Natural Resources (CN), Fudan University (CN), Jiangxi University of Science and Technology (CN)
National Natural Science Foundation of China
Climate action
Openalex Percentile: Top 9%
Land Use and Ecosystem Services
2.83
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.