研究报告
王影,柴立和.生态承载力水平评价的动态模型及其应用——以洞庭湖生态经济区为例[J].环境科学学报,2016,36(5):1859-1865
生态承载力水平评价的动态模型及其应用——以洞庭湖生态经济区为例
- The dynamic evaluation model of ecological carrying capacity and its application:A case study of Dongting Lake Ecological Economic Zone
- 基金项目:国家自然科学基金(No.71071110)
- 王影
- 天津大学环境科学与工程学院, 天津 300072
- 柴立和
- 天津大学环境科学与工程学院, 天津 300072
- 摘要:生态承载力是可持续发展研究的核心.本文基于生态承载力的内涵,从4个方面构建了生态承载力的评价指标体系,并以最大信息熵原理(MIEP)为基础,自组织特征映射神经网络(SOFM)为算法,借助MATLAB数学软件为计算平台,从复杂系统结构演化的角度提出了生态承载力评价模型,并用MIEP模型对洞庭湖生态经济区2008-2012年的生态承载力进行评价,以指导当地生态建设.结果表明,5年间该地区的生态承载力呈总体上升的趋势,其中,2008年和2009年两年生态承载力水平基本一致,2010年呈现较明显的上升,2011年的生态承载力剧烈下降后在2012年呈现大幅回升.ξ值各分量的雷达图揭示出各指标逐年贡献程度的变化,结合准则层面的分析发现,水资源发展状况对该地生态承载力整体水平影响较大.与主成分分析法的比较表明了MIEP模型对生态承载力评价的可行性,同时其能更好地体现生态承载力发展演变的动力学特性,连接权值的获取避免了人为设定的主观性,在评价中有明显优势,且在预测上有一定潜力.
- Abstract:Ecological carrying capacity (ECC) is the core of sustainable development. Based on the connotation of ECC, assessment of ECC is established from four aspects. ECC assessment model is proposed from structural evolution of complex systems based on maximum information entropy principle (MIEP), self-organizing feature map neural network (SOFM) algorithm and MATLAB workshop. The ECC of Dongting Lake Ecological Economic Zone from 2008 to 2012 is assessed with the model. The results show that the ECC of this zone has an upward trend. The ECC in 2008 and 2009 were approximately the same, and significantly increased in 2010, while the ECC of 2011 showed a severe downward trend and then greatly rose in 2012. The radar chart of ξ value reveals the yearly changes of each indicator's contributions to ECC. With the criteria analysis, it is found that the water resources development has more important influence on the ECC. Compared with principal component analysis, result indicates the feasibility of the ECC assessment model, which can better reflect the temporal-spatial evolutionary dynamic behavior of ECC, and connection weights obtained avoid the subjectivity of artificial assumption. The model not only has obvious advantages in ECC's evaluation, but also is potential for trend prediction.
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