Regional Ecological Risk Assessment Based on Relative Risk Model

Jia-bing ZHU , Jian-ting WU , Hua ZHANG , Yan-hui CUI , Jia-di LIANG , Xi-chun LI

Science Technology and Engineering ›› 2024, Vol. 24 ›› Issue (7) : 3020 -3033.

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Science Technology and Engineering ›› 2024, Vol. 24 ›› Issue (7) : 3020-3033 DOI: 10.12404/j.issn.1671-1815.2303994
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Regional Ecological Risk Assessment Based on Relative Risk Model
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Abstract

A part of ecosystems have been damaged to varying degrees in the process of modern socio-economic development, and ecological risk assessment is one of the most important methods for measuring the health status of ecosystems. Taking Yunnan Province as the research area, four main risk sources, divides the area into five types of habitats, and considers the ecosystem as the risk receptor, and four types of ecosystem services as the assessment endpoints. The relative risk model (RRM) was used to calculate the ecological risk values of each habitat, risk source, assessment endpoint, and assessment unit in Yunnan Province, and the risk levels are divided by the assessment results. Subsequently, the Monte Carlo simulation method was used for uncertainty analysis, and risk management analysis is carried out on the basis of the risk calculation results. The results show that the overall ecological risk situation in Yunnan Province is good, with small spatial differences; Zhaotong city has the highest relative risk level, but the result error is the largest; The suffered risk of urban ecosystem habitat, the risk of population load risk source to the ecosystem, and the risk response of regulatory services were all the highest; uncertainty analysis indicates the impacting of risk sources to risk results is underestimated, and its evolution simulation results tend to converge.

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Jia-bing ZHU, Jian-ting WU, Hua ZHANG, Yan-hui CUI, Jia-di LIANG, Xi-chun LI. Regional Ecological Risk Assessment Based on Relative Risk Model. Science Technology and Engineering, 2024, 24(7): 3020-3033 DOI:10.12404/j.issn.1671-1815.2303994

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