Regional ecological risk assessment and transfer mechanism based on improved gravity and social network analysis model: A case study of Northwest China

IF 7 2区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Ecological Indicators Pub Date : 2025-02-22 DOI:10.1016/j.ecolind.2025.113243
Ruiyang Li , Zhaocai Wang , Yanyu Li , Tunhua Wu
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Abstract

With the acceleration of industrialization and urbanization, regional ecological risk issues have become increasingly prominent. Scientifically assessing and analyzing ecological risks is crucial for implementing effective ecological protection measures. Currently, most studies primarily focus on the isolated ecological risk conditions of individual regions, while the interactive transfer relationships of ecological risks among these regions have received little attention. This limitation hinders a comprehensive and scientific reflection of the overall trends in regional ecological risks. Therefore, it is necessary to construct relevant models for an in-depth investigation of this issue. This study employs an improved gravity model to simulate the interactive transfer of ecological risks between different regions within the ecosystem framework, considering soil pollution, air pollution, and economic transmission pathways. Additionally, a social network analysis (SNA) model is applied to further dissect the mechanisms of ecological risk transfer among regions. Furthermore, by integrating ecological risk indices based on land use types and landscape patterns, a comprehensive ecological risk assessment method is proposed. Finally, a comprehensive assessment and analysis of ecological risks in five provinces of Northwest China from 2003 to 2022 is conducted. The results indicate that during the period from 2003 to 2022, the comprehensive ecological risk index of the region exhibited a fluctuating trend, remaining within an alert range overall. The spatial relative differences in ecological risk first increased and then decreased, showing a peak pattern. The transfer of pollution among regions through different pathways significantly increased the share of regional comprehensive risks, particularly in Gansu (88.87%), Qinghai (79.35%), and Shaanxi (70.91%). Moreover, the findings also indicate that Gansu is a significant transmitter of regional comprehensive ecological risks, warranting substantial attention. This research provides a scientific basis for risk assessment and governance in ecologically fragile areas.

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基于改进重力和社会网络分析模型的区域生态风险评价及转移机制——以西北地区为例
随着工业化和城镇化进程的加快,区域生态风险问题日益突出。科学评估和分析生态风险是实施有效生态保护措施的关键。目前,大多数研究主要集中在单个区域孤立的生态风险状况,而生态风险在各个区域之间的相互传递关系很少受到关注。这种局限性阻碍了全面、科学地反映区域生态风险的总体趋势。因此,有必要构建相关模型,对这一问题进行深入研究。本研究采用改进的重力模型,在生态系统框架下,考虑土壤污染、大气污染和经济传递途径,模拟不同区域间生态风险的交互传递。在此基础上,应用社会网络分析(SNA)模型进一步剖析了区域间生态风险转移的机制。在此基础上,提出了基于土地利用类型和景观格局的综合生态风险评价方法。最后,对2003 - 2022年西北五省的生态风险进行了综合评价和分析。结果表明:2003 - 2022年,该地区综合生态风险指数呈波动趋势,总体处于警戒区间;生态风险空间相对差异先增大后减小,呈峰值型。不同途径的区域间污染转移显著增加了区域综合风险占比,其中以甘肃(88.87%)、青海(79.35%)和陕西(70.91%)最为显著。此外,研究结果还表明,甘肃是区域综合生态风险的重要传播者,值得重视。本研究为生态脆弱地区的风险评估和治理提供了科学依据。
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来源期刊
Ecological Indicators
Ecological Indicators 环境科学-环境科学
CiteScore
11.80
自引率
8.70%
发文量
1163
审稿时长
78 days
期刊介绍: The ultimate aim of Ecological Indicators is to integrate the monitoring and assessment of ecological and environmental indicators with management practices. The journal provides a forum for the discussion of the applied scientific development and review of traditional indicator approaches as well as for theoretical, modelling and quantitative applications such as index development. Research into the following areas will be published. • All aspects of ecological and environmental indicators and indices. • New indicators, and new approaches and methods for indicator development, testing and use. • Development and modelling of indices, e.g. application of indicator suites across multiple scales and resources. • Analysis and research of resource, system- and scale-specific indicators. • Methods for integration of social and other valuation metrics for the production of scientifically rigorous and politically-relevant assessments using indicator-based monitoring and assessment programs. • How research indicators can be transformed into direct application for management purposes. • Broader assessment objectives and methods, e.g. biodiversity, biological integrity, and sustainability, through the use of indicators. • Resource-specific indicators such as landscape, agroecosystems, forests, wetlands, etc.
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