地理研究 ›› 2015, Vol. 34 ›› Issue (10): 1824-1838.doi: 10.11821/dlyj201510002

• 研究论文 • 上一篇    下一篇

中国沿海地区人海关系地域系统评价及协同演化研究

孙才志(), 张坤领, 邹玮, 王泽宇   

  1. 辽宁师范大学海洋经济与可持续发展研究中心,大连 116029
  • 收稿日期:2015-01-16 修回日期:2015-06-08 出版日期:2015-10-15 发布日期:2015-10-30
  • 作者简介:

    作者简介:孙才志(1970- ),男,山东烟台人,教授,博士生导师,主要从事水资源与海洋经济地理研究。E-mail: suncaizhi@lnnu.edu.cn

  • 基金资助:
    国家自然科学基金项目(41301129),教育部人文社会科学重点研究基地项目(12JJD790032),辽宁省创新团队课题(WT2014005)

Study on regional system of man-sea relationship and its synergetic development in the coastal regions of China

Caizhi SUN(), Kunling ZHANG, Wei Zou, Zeyu WNAG   

  1. Center for Studies of Marine Economy and Sustainable Development, Liaoning Normal University, Dalian 116029, China
  • Received:2015-01-16 Revised:2015-06-08 Online:2015-10-15 Published:2015-10-30

摘要:

借鉴信息熵、协同学相关理论,在分析人海关系地域系统协同演化机制基础上,构建综合评价指标体系,利用AHP-PP模型测算沿海地区1996-2012年11个省份人类社会与海洋资源环境子系统综合评价值;通过信息熵模型对人海关系地域系统信息熵值及有序度进行测算,发现沿海地区各省份人海关系地域系统信息熵呈逐年下降,有序度呈逐年上升趋势,但区域差异显著。进一步构建人海关系地域系统协同演化模型,并采用加速遗传算法进行模型参数估计,辨识其协同演化类型,结果显示:天津、辽宁、江苏、浙江、福建表现为冲突型,河北、广西、海南表现为掠夺型,上海、山东、广东则表现为协同型。最后对各种类型进行分析,并简要提出人海关系协同发展的对策与建议。

关键词: 沿海地区, 人海关系地域系统, AHP-PP模型, 加速遗传算法, 协同演化

Abstract:

The oceans have long been recognized as increasingly important natural resources for humans. Humans, especially coastal residents, depend on ocean systems for essential and valuable life-supporting provisions, such as ocean resources, ocean traffic, seashore tourism, etc. Oceans are extremely sensitive and vulnerable, regardless of their substantial productivity. Long-term of ocean- and land-based human activities have increasingly threatened the oceans through direct and indirect means and caused the degradation of structure, function and provision service of ocean systems. Recently, theoretical and practical studies on man-land relationship have already become a research hotspot both at home and abroad. However, there are relatively few studies on man-sea relationship. Furthermore, regional system of man-sea relationship is a complex system that constitutes two relatively independent, but interactional subsystems, human and ocean. Yet, few studies have focused on the perspective of complex system. For decades, marine economy has been rapidly developing in China, and human impact on marine is gradually deepened. In this context, studies on regional system of man-sea relationship will be of important theoretical and practical significance to the coastal regions of China. Referring information entropy and synergetic theory, this study proposes a general concept of synergetic development mechanism of regional system of man-sea relationship, and sets up the index system of development level assessment. Then, the development levels of human-society and marine resources-environment subsystems were calculated by AHP-PP model from 1996 to 2012 in coastal regions of China. Information entropy scores and order degrees of regional system of man-sea relationship are calculated by using information entropy model in the article. The results indicate that information entropy scores of regional system of man-sea relationship go down with each passing year and order degrees show an upward trend, but regional differences are noticeable in coastal regions of China. Furthermore, the synergetic development model of regional system of man-sea relationship was established for recognizing the synergetic development classification of regional systems and parameters of the model are estimated by accelerating genetic algorithm. The findings confirm that three man-sea relationship patterns are recognized in the eleven coastal provinces. The man-sea relationship of Hubei, Guangxi and Hainan are conflicting; Tianjin, Liaoning, Jiangsu, Zhejiang, and Fujian are predatory; and Shanghai, Shandong, and Guangdong are cooperative. The causes for these different synergetic development patterns are analyzed and countermeasures for enhancing synergetic development are briefly put forward in this study.

Key words: coastal region, regional system of man-sea relationship, AHP-PP model, synergetic development, accelerating genetic algorithm