| 引用本文: | 徐灵芝,潘继征,李勇,华跃洲,李清濯,阳振,何尚卫,杜成栋.1980—2020年滇池生态脆弱性评价及主要驱动因子.湖泊科学,2023,35(5):1682-1693. DOI:10.18307/2023.0528 |
| Xu Lingzhi,Pan Jizheng,Li Yong,Hua Yuezhou,Li Qingzhuo,Yang Zhen,He Shangwei,Du Chengdong.The ecological vulnerability evaluation and its driving force in Lake Dianchi, 1980-2020. J. Lake Sci.2023,35(5):1682-1693. DOI:10.18307/2023.0528 |
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| 1980—2020年滇池生态脆弱性评价及主要驱动因子 |
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徐灵芝1,2, 潘继征3,4, 李勇1,2,5, 华跃洲1,2, 李清濯3,6, 阳振3, 何尚卫3,6, 杜成栋1,2
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1.苏州科技大学环境科学与工程学院, 苏州 215011;2.江苏省环境科学与工程重点实验室, 苏州 215011;3.中国科学院南京地理与湖泊研究所, 湖泊与环境国家重点实验室, 南京 210008;4.滇池湖泊生态系统云南省野外科学观测研究站, 昆明 650228;5.广东省佛山市南海区苏州科技大学环境研究院, 佛山 528200;6.中国科学院大学, 北京 100049
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| 摘要: |
| 人类活动的加剧和经济社会的发展导致滇池开发强度持续增加,滇池生态系统结构与功能受到严重影响,评估滇池的生态脆弱性程度与主要驱动因子是明晰滇池生态系统现状和问题、实现其精准治理和可持续发展的首要任务。基于“暴露程度-敏感程度-适应程度”模型(VSD模型),选取3个准则7个要素24个指标构建滇池生态系统脆弱性评估指标体系,利用逼近理想解排序法(TOPSIS)进行权重方案比选,并通过鲁棒性检验分析,确定计算权重的最优方案。通过分析1980—1989、1990—2009、2010—2020年这3个时间段滇池的生态脆弱性,识别出影响滇池生态系统的主要驱动因子,以期为滇池未来生态保护与修复方向的确定提供参考。结果显示, 1980—2020年滇池生态脆弱性呈现先增加后降低的趋势,生态脆弱度最高的是1990—2009年(0.502),属于中度脆弱。影响滇池生态系统的主要因素为敏感程度指标,其次为暴露程度指标。在暴露程度方面,影响生态系统的主要驱动因子逐渐从单一的工业污染向工农业的复合污染转变,1980—1989年工业废水排放量为主要驱动因子,1990—2009年建设用地面积是主要胁迫因素,2010—2020年化肥施用量(折纯)为影响滇池生态系统的主要因素;在敏感程度方面,影响生态系统的主要驱动因子逐渐从水质指标向水生态指标转变,1980—1989年水体恢复能力是主要因素,1990—2009年与2010—2020年土著鱼类种数为主要驱动因子。基于上述分析,为提升滇池生态系统健康水平,应采取改善湖区生境条件、修复水生生物种群、建设农业面源污染控制体系等对策。 |
| 关键词: 滇池 生态脆弱性评价 VSD模型 逼近理想解排序法 鲁棒性检验 驱动因子分析 |
| DOI：10.18307/2023.0528 |
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| 基金项目:江苏省高校水处理技术与材料协同创新中心项目和滇池湖泊生态系统云南省野外科学研究观测站项目联合资助。 |
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| The ecological vulnerability evaluation and its driving force in Lake Dianchi, 1980-2020 |
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Xu Lingzhi1,2, Pan Jizheng3,4, Li Yong1,2,5, Hua Yuezhou1,2, Li Qingzhuo3,6, Yang Zhen3, He Shangwei3,6, Du Chengdong1,2
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1.School of Environmental Science and Engineering, Suzhou University of Science and Technology, Suzhou 215011, P.R. China;2.Key Laboratory of Environmental Science and Engineering of Jiangsu Province, Suzhou 215011, P.R. China;3.State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, P.R. China;4.Lake Dianchi Ecosystem Observation and Research Station of Yunnan Province, Kunming 650228, P.R. China;5.Foshan Nanhai Suzhou University of Science and Technology Environmental Research Institute, Foshan 528200, P.R. China;6.University of Chinese Academy of Sciences, Beijing 100049, P.R. China
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| Abstract: |
| The intensification of human activities and the development of the economy and society have led to a continuous increase in the intensity of development in Lake Dianchi. The structure and function of the Lake Dianchi ecosystem have been seriously affected. According to the degree of ecological vulnerability and the main driving factors of Lake Dianchi, the main task is to clarify the current situation and problems of Lake Dianchi ecosystem for its precise management and sustainable development. Based on the "exposure sensitivity adaptation" model (VSD model), 3 criteria, 7 elements and 24 indicators were selected to construct the vulnerability assessment index system of Lake Dianchi ecosystem in this paper. The TOPSIS method was used to compare and select the weighting schemes. The robust test analysis was used to determine the optimal weight calculation scheme. The ecological vulnerability of Lake Dianchi in the three periods of 1980-1989, 1990-2009 and 2010-2020 was analysed, and the main driving factors affecting the Lake Dianchi ecosystem were identified to provide a reference for determining the ecological protection and restoration of Lake Dianchi in the future. The results showed that: (1) From 1980 to 2020, the ecological vulnerability of Lake Dianchi showed a trend of increasing and then decreasing. The highest ecological vulnerability was from 1990 to 2009, which was 0.502, which belongs to moderate vulnerability. (2) The main factor affecting the Lake Dianchi ecosystem was the sensitivity index, followed by the exposure index. In terms of exposure index, the main driving factor affecting the ecosystem had gradually changed from single industrial pollution to combined industrial and agricultural pollution. The industrial effluent discharge from 1980 to 1989 was the main driving factor, the construction land area from 1990 to 2009 was the main stress factor, and the chemical fertiliser application amount (converted into pure) from 2010 to 2020 was the main factor affecting the ecosystem of Lake Dianchi; in terms of sensitivity, the main driving factor affecting the ecosystem had gradually changed from water quality indicators to water ecological indicators. The water restoration capacity was the main driving factor from 1980 to 1989, and the number of native fish species was the main driving factor from 1990 to 2009 and 2010 to 2020. (3) Based on the above analysis, the main countermeasures to improve the health level of Lake Dianchi ecosystem are to improve the habitat conditions in the lake area, restore the population of aquatic organisms, and build an agricultural non-point source pollution control system. |
| Key words: Lake Dianchi ecological vulnerability assessment VSD model TOPSIS Robustness check the analysis of drivers |
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