基于可变模糊评价模型的东山湾生态系统健康评价

Abstract

PDF HTML阅读 XML下载 导出引用 引用提醒 基于可变模糊评价模型的东山湾生态系统健康评价 DOI: 10.5846/stxb201312052899 作者: 作者单位: 集美大学水产学院,集美大学水产学院,集美大学水产学院,国家海洋局第三海洋研究所 作者简介: 通讯作者: 中图分类号: 基金项目: 中国海洋生物多样性保护研究(海洋生态影响评价方法研究)HD130701-13(6) Ecosystem health assessment based on variable fuzzy evaluation model in Dongshan Bay, Fujian, China Author: Affiliation: Fisheries College of Jimei University,,,The Third Institute of Oceanography of the State Oceanic Administration Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:根据东山湾海域环境污染现状和生态系统的特点,从水质环境、沉积物环境、生物残毒以及海洋生物方面构建了东山湾生态系统健康评价指标体系,提出了基于可变模糊评价模型的海湾生态系统健康评价方法,并利用该方法对东山湾生态系统健康状况进行了评价。结果表明:东山湾春季生态系统健康指数为2.36,秋季为2.44,均处于"良与中之间,偏良"水平,春季略优于秋季。影响东山湾生态系统健康状况的主要负面指标因子为鱼卵及仔鱼密度(春秋季健康指数均值为4.95)、营养水平(秋季健康指数为4.47)和底栖生物生物量(春季健康指数为3.59)。实例研究表明该方法通过准则参数α和距离参数p的不同组合变化,以线性与非线性相结合,能够较客观系统、标准量化地评价海湾生态系统健康状况的优劣。 Abstract:Human activities such as overfishing, coastal development and pollution have altered bay ecosystems and eroded their capacity to provide benefits now and in the future. A systematic diagnosis of bay ecosystem health for sustainable ecological management is urgently needed. Sustainable management aims at maintaining the flow of a broad range of benefits from the bay and also requires a comprehensive and quantitative method to measure and monitor the health of bay at the level of ecosystem. A variable fuzzy evaluation model is introduced for the comprehensive evaluation of bay ecosystem health. According to the environmental pollution conditions and ecosystem characteristics in Dongshan Bay, Fujian, China, an integrated index system comprising water, sediment environment, residual toxicity in organisms and marine biota were created for evaluation of bay ecosystem health. The judgment criteria regarding the level of bay ecosystem health could be roughly classified as "excellent, good, moderate, poor, and bad". The five levels could be further sub-classified into 13 ranks. Ecosystem health assessment of Dongshan Bay in spring and autumn based on variable fuzzy evaluation model was presented in this paper. The results showed that the score of ecosystem health index for Dongshan bay was 2.36 in spring and 2.44 in autumn, respectively. The status of Dongshan bay ecosystem health could be generally classified as "between good and moderate, mostly good", with better level in spring than in autumn. In more detail, the scores of ecosystem health index ranged from 2.31 to 2.47 and all stations were classified as "between good and moderate, mostly good" in spring. In autumn, the scores of ecosystem health index ranged from 2.29 to 2.74. Only three stations (D11、D13 and D14) were classified as "between good and moderate, mostly good" and the other stations were classified as "between good and moderate, mostly moderate". Several factors showed their positive effects on the ecosystem heath status, such as heavy metals in seawater, sediment and organism, oil in seawater and sediment, zooplankton biomass, phytoplankton cells density and diversity as well as benthos diversity. The scores of health index for these indicators were all lower than 1.5 in spring and autumn. However, the health status of the ecosystem was potentially made to change to "between good and moderate, mostly moderate" by the negative factors including fish eggs and larva density (average score of heath index in spring and autumn was 4.95), nutrition level (the score of heath index in autumn was 4.47), and benthos biomass (the score of heath index in spring was 3.59). The scores of health index for these three indicators were all higher than 3.5. Case study indicates that the ecosystem health assessment based on variable fuzzy evaluation model also provides a standardized and quantitative approach for measuring overall health condition of bay ecosystems, which can perform well and accurately evaluate the comprehensive status of the bay ecosystem heath through the change of variable model parameters (the criterion and distance parameter, α and p), combining the linear and nonlinear models. Therefore, the model result is more reliable than before. 参考文献 相似文献 引证文献