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杭州湾滨海湿地生态安全动态变化及趋势预测

Ecological security dynamics and trend forecast of coastal wetlands in Hangzhou Bay

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【作者】 李楠李龙伟陆灯盛张银龙吴明

【Author】 LI Nan;LI Longwei;LU Dengsheng;ZHANG Yinlong;WU Ming;Co-Innovation Center for the Sustainable Forestry in Southern China, College of Biology and the Environment, Nanjing Forestry University;Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province, Zhejiang Agriculture and Forestry University;School of Geographical Sciences, Fujian Normal University;Institute of Subtropical Forestry Research, Chinese Academy of Forestry;

【通讯作者】 张银龙;

【机构】 南京林业大学南方现代林业协同创新中心南京林业大学生物与环境学院浙江农林大学浙江省森林生态系统碳循环与固碳减排重点实验室福建师范大学地理科学学院中国林业科学研究院亚热带林业研究所

【摘要】 【目的】受人类活动干扰,滨海湿地日益突出的生态问题已经对区域可持续发展构成了严重威胁,明确滨海湿地的生态安全状态及变化趋势至关重要。笔者对杭州湾滨海湿地的生态安全状况进行评估和发展趋势分析预测,为湿地的有效管理、区域可持续发展,以及滨海湿地生态安全趋势的准确预测提供参考。【方法】基于DPSIR概念模型,从驱动力、压力、状态、影响和响应等5个层面选取46个相关指标构建杭州湾滨海湿地生态安全评价体系。基于遥感数据、湿地监测数据、地理辅助数据、社会经济等统计数据获取各指标数据。分别对正负向指标进行标准化处理,使用熵值法计算各指标的权重,建立加权判断矩阵,确定各指标的正负理想解。根据各指标与理想解之间的距离,计算贴近度,即生态安全值,并划分为安全、比较安全、预警、脆弱、极度脆弱等5个等级。分别计算2000、2005、2010及2015年的生态安全值,使用灰色预测模型GM(1,1)对2020年杭州湾滨海湿地的生态安全值进行预测分析。【结果】根据熵值法改进的TOPSIS模型计算得到杭州湾滨海湿地在2000、2005、2010和2015年的生态安全指数分别为0.413、0.382、0.287和0.582,安全等级由预警等级恶化到脆弱等级,又恢复到预警等级,呈下降后上升趋势。熵值法计算的指标权重表明,湿地保护率、景观多样性指数、生活污水排放量、大气调节、长效机制构建、固碳、文教科研、人口增长率、旅游休闲、人均GDP、工业废气排放量和水源涵养是影响杭州湾滨海湿地生态安全的主要因素。杭州湾滨海湿地的DPSIR模型中,"驱动力"一直处于预警状况,但其面临的"压力"越来越大,从安全状态恶化到极度脆弱状态,"状态"不容乐观,从比较安全恶化到极度脆弱后好转,处于脆弱状态,"影响"基本处于预警状态,当地对湿地生态安全的"响应"从无到有,并稳步提高,有效地改善了滨海湿地整体生态安全状况。通过灰色预测模型GM(1, 1)预测得到2020年杭州湾滨海湿地生态安全值为0.697,处于"比较安全"的状态。【结论】经济快速发展,城市化加快和污染负荷加剧,导致杭州湾滨海湿地生态安全恶化;随着政府及民众对湿地的广泛关注和重视,环保投入资金增加,构建了湿地保护长效机制,杭州湾滨海湿地生态安全状况逐渐改善,但仍处于安全预警状态。随着湿地保护力度增加,预计2020年杭州湾滨海湿地的生态安全状况将进一步好转,提升到比较安全状态。

【Abstract】 【Objective】 Due to constant anthropogenic disturbance, coastal wetlands of China have been suffering from increasing ecological problems, posing a serious threat to regional sustainable development. It is crucial to clarify the ecological security status and trends of coastal wetlands. For effective management of wetlands and regional sustainable development, the ecological security status of the coastal wetlands in Hangzhou Bay was evaluated and predicted. 【Method】Based on the driving force-pressure-state-impact-response(DPSIR) conceptual model, 46 indicators reflecting the ecological security of the Hangzhou Bay coastal wetlands were selected to develop the ecological security assessment system. Then, these indicators were quantified by remote sensing data, wetland observational data, geographic ancillary data, and socioeconomic statistics. The indicators were normalized as appropriate and the weight of indicators was calculated by entropy methods. A weighted judgment matrix was established to calculate the positive and negative ideal solutions of each indicator. According to the distance between an indicator and the ideal solution, the closeness C_i(i.e., the ecological security value) was calculated and classified into five levels: extremely vulnerable, vulnerable, warning, relatively safe, and safe. The ecological safety values of 2000, 2005, 2010 and 2015 were calculated separately, and the value of 2020 was predicted by the grey prediction model GM(1, 1). 【Result】The ecological security values in 2000, 2005, 2010 and 2015 were 0.413, 0.382, 0.287 and 0.582, respectively. The security level deteriorated from the warning level to the vulnerable level, and returned to the warning level, showing an upward trend after the decline. From 2000 to 2005, large areas of coastal wetlands were occupied due to rapid urban expansion, coupled with increased pollution loads on wetlands, causing the ecological security value to reach the level of vulnerability. From 2005 to 2010, the region maintained rapid economic development under the guidance of policies. As development of the Hangzhou Bay New District intensified, the wetland area was continuously reduced, along with the ecological security value. From 2010 to 2015, the ecological value of wetlands was widely recognized, and a number of wetland protection policies were promulgated by the central and local governments. As environmental protection investment increased, and the pollution load decreased, the ecological security of wetlands has improved. The weights of indicators calculated by the entropy method showed that wetland protection rate, landscape diversity index, domestic sewage discharge, atmospheric regulation, long-term mechanism construction, carbon sequestration, cultural and educational research, population growth rate, tourism and leisure, per capita GDP, industrial emissions, and water conservation were the main factors affecting the ecological safety of coastal wetlands in Hangzhou Bay. In the DPSIR model of the Hangzhou Bay coastal wetlands, the "driving force" has always been in a warning situation, while "pressure" increases from a safe to extremely vulnerable state. Its "state" is not optimistic and the "impact" is basically in a warning state. The local "response" for wetland ecological has grown from scratch and has steadily improved, effectively improving the overall ecological security of coastal wetlands. The gray prediction model GM(1, 1) predicted that the ecological security value of the coastal wetland in 2020 will be 0.697, which is a "relatively safe" state. 【Conclusion】The deterioration of ecological safety of coastal wetlands mainly resulted from rapid economic development, urbanization, and pollution. With extensive attention of the government and the public to the wetlands, the investment in environmental protection has increased, and a long-term mechanism for wetland protection has been established. However, although the ecological security of the wetland has gradually improved, it is still in a security alert state. Overall, with the increased wetland protection, it is predicted that the ecological security status of the coastal wetlands in Hangzhou Bay will further improve in 2020 and will be upgraded to a safe state.

【基金】 浙江省省院合作林业科技项目(2018SY03);江苏省研究生科研与实践创新计划项目(KYCX17_0819);江苏高校优势学科建设工程资助项目(PAPD);南京林业大学博士学位论文创新基金项目
  • 【文献出处】 南京林业大学学报(自然科学版) ,Journal of Nanjing Forestry University(Natural Sciences Edition) , 编辑部邮箱 ,2019年03期
  • 【分类号】X826;X37
  • 【网络出版时间】2018-09-28 13:16
  • 【被引频次】7
  • 【下载频次】592
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