杭州湾滨海湿地生态安全动态变化及趋势预测
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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。
【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.
【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.
引文
[1] 牟晓杰,刘兴土,阎百兴,等.中国滨海湿地分类系统[J].湿地科学,2015,13(1):19-26.DOI:10.13248/j.cnki.wetlandsci.2015.01.004.MOU X J,LIU X T,YAN B X,et al.Classification system of coastal wetlands in China [J].Wetland Science,2015,13(1):19-26.
[2] BARBIER E B,HACKER S D,KENNEDY C,et al.The value of estuarine and coastal ecosystem services [J].Ecological Monographs,2011,81(2):169-193.DOI:10.1890/10-1510.1.
[3] 谢高地,鲁春霞,冷允法,等.青藏高原生态资产的价值评估[J].自然资源学报,2003,18(2):189-196.DOI:10.3321/j.issn:1000-3037.2003.02.010.XIE G D,LU C X,LENG Y F,et al.Ecological assets valuation of the Tibetan Plateau [J].Journal of Natural Resources,2003,18(2):189-196.
[4] 吴明.杭州湾滨海湿地现状与保护对策[J].林业资源管理,2004(6):44-47.DOI :10.13466/j.cnki.lyzyg l.2004.06.011.WU M.Current situation and conservation countermeasures of Hangzhou Bay wetland [J].Forest Resources Management,2004(6):44-47.
[5] 梁晨,李晓文,崔保山,等.中国滨海湿地优先保护格局构建[J].湿地科学,2015,13(6):660-666.DOI:10.13248/j.cnki.wetlandsci.2015.06.002.LIANG C,LI X W,CUI B S,et al.The pattern construction of priority protection for coastal wetlands in China [J].Wetland Science,2015,13(6):660-666.
[6] 卢奇.基于DPSIR模型的新疆艾里克湖生态安全评价研究[D].乌鲁木齐:新疆农业大学,2015.LU Q.The ecological security assessment of Eric Lake based on DPSIR model [D].Urumqi:Xinjiang Agricultural University,2015.
[7] 杜培军,陈宇,谭琨.湿地景观格局与生态安全遥感监测分析——以江苏滨海湿地为例[J].国土资源遥感,2014,26(1):158-166.DOI:10.6046/gtzyyg.2014.01.27.Du P J,CHEN Y,TAN K.Monitoring and analyzing wetland landscape pattern change and ecological security using remote sensing images:a case study of Jiangsu coastal wetland [J].Remote Sensing for Land & Resources,2014,26(1):158-166.
[8] 周云鹏,胡忠行,张曼,等.基于PSR模型的浙江望东垟亚高山湿地生态安全评价[J].湿地科学与管理,2017,13(2):20-24.DOI:10.3969/j.issn.1673-3290.2017.02.04.ZHOU Y P,HU Z X,ZHANG M,et al.PSR-based eco-security evaluation of Wangdongyang subalpine wetland in Zhejiang province [J].Wetland Science & Management,2017,13(2):20-24.
[9] 庄伟,廖和平,潘卓,等.基于变权TOPSIS模型的三峡库区土地生态安全评估——以巫山县为例[J].西南大学学报(自然科学版),2014,34(8):106-112.DOI:10.13718/cnki.xdzk.2014.08.019.ZHUANG W,LIAO H P,PAN Z,et al.Evaluation of land eco-security in the three gores reservoir region based on the variable weight TOPSIS model:a case study of Wushan [J].Journal of Southwest University (Natural Science Edition),2014,36(8):106-112.
[10] 劳燕玲.滨海湿地生态安全评价研究[D].北京:中国地质大学,2013.LAO Y L.Research on ecological security evaluation of coastal wetland [D].Beijing:China University of Geosciences,2013.
[11] 陈丽欣.河北省滨海湿地生态安全评价与保护研究[D].石家庄:河北师范大学,2010.CHEN L X.Protection and ecological security evaluation on coastal wetlands in Hebei Province [D].Shijiazhuang:Hebei Normal University,2010.
[12] 宁潇,胡咪咪,邵学新,等.杭州湾南岸滨海湿地生态服务功能价值评估[J].生态科学,2017,36(4):166-175,184.DOI:10.14108/j.cnki.1008-8873.2017.04.023.NING X,HU M M,SHAO X X,et al.Assessment of coastal wetland ecosystem services in the south of Hangzhou Bay [J].Ecological Science,2017,36(4):166-175.
[13] 高欣.杭州湾湿地生物多样性及其保护[J].沈阳师范大学学报(自然科学版),2006,24(1):92-95.DOI:10.3969/j.issn.1673-5862.2006.01.027.GAO X.Biodiversity and conservation of wetland of Hangzhou Bay [J].Journal of Shenyang Normal University (Natural Science Edition),2006,24(1):92-95.
[14] SUNT T,LIN W P,CHEN G S,et al.Wetland ecosystem health assessment through integrating remote sensing and inventory data with an assessment model for the Hangzhou Bay,China [J].Science of the Total Environment,2016,566-567:627-640.DOI:10.1016/j.scitotenv.2016.05.028.
[15] GARI S R,NEWTON A,ICELY J D.A review of the application and evolution of the DPSIR framework with an emphasis on coastal social-ecological systems [J].Ocean & Coastal Management,2015,103:63-77.DOI:10.1016/j.ocecoaman.2014.11.013.
[16] HAZARIKA N,NITIVATTANANON V.Strategic assessment of groundwater resource exploitation using DPSIR framework in Guwahati City,India [J].Habitat International,2016,51:79-89.DOI:10.1016/j.habitatint.2015.10.003.
[17] 宁波市统计局.宁波统计年鉴[M].北京:中国统计出版社,2001.Ningbo Municipal Statistics Bureau.Ningbo statistical yearbook [M].Beijing:China Statistics Press,2001.
[18] 宁波市统计局.宁波统计年鉴[M].北京:中国统计出版社,2006.Ningbo Municipal Statistics Bureau.Ningbo statistical yearbook [M].Beijing:China Statistics Press,2006.
[19] 宁波市统计局.宁波统计年鉴[M].北京:中国统计出版社,2011.Ningbo Municipal Statistics Bureau.Ningbo statistical yearbook [M].Beijing:China Statistics Press,2011.
[20] 宁波市统计局.宁波统计年鉴[M].北京:中国统计出版社,2016.Ningbo Municipal Statistics Bureau.Ningbo statistical yearbook [M].Beijing:China Statistics Press,2016.
[21] 张国钢,陈丽霞,陈水华,等.杭州湾大桥周边鸟类资源现状调查[J].动物学杂志,2014,49(5):672-685.DOI:10.13859 / j.cjz.201405006.ZHANG G G,CHEN L X,CHEN S H,et al.The survey on the bird community around the Hangzhou Bay Bridge in China [J].Chinese Journal of Zoology,2014,49(5):672-685.
[22] 刘世栋,薛东前,高峻.上海杭州湾北岸滨海地区生态安全评价[J].安全与环境学报,2012,12(6):124-130.DOI:10.3969/ j.issn.1009-6094.2012.06.02.LIU S D,XUE D Q,GAO J.Coastal eco-environmental security assessment of the northern shore of Shanghai-Hangzhou Bay [J].Journal of Safety and Environment,2012,12(6):124-130.
[23] 邹长新,陈金林,李海东.基于模糊综合评价的若尔盖湿地生态安全评价[J].南京林业大学学报(自然科学版),2012,36(3):53-58.ZOU C X,CHEN J L,LI H D.Fuzzy comprehensive assessment of ecological security evaluation in Zoige wetland [J].Journal of Nanjing Forestry University(Natural Sciences Edition),2012,36(3):53-58.
[24] LI N,LU D S,WU M,et al.Coastal wetland classification with multiseasonal high-spatial resolution satellite imagery [J].International Journal of Remote Sensing,2018:1-21.DOI:10.1080/01431161.2018.1500731.
[25] 朱卫红,苗承玉,郑小军,等.基于3S技术的图们江流域湿地生态安全评价与预警研究[J].生态学报,2014,34(6):1379-1390.DOI:10.5846/stxb201211241666.ZHU W H,MIAO C Y,ZHENG X J,et al.Study on ecological safety evaluation and warning of wetlands in Tumen River watershed based on 3S technology [J].Acta Ecologica Sinica,2014,34(6):1379-1390.
[26] 廖柳文,秦建新.环长株潭城市群湿地生态安全研究[J].地球信息科学学报,2016,18(9):1217-1226.DOI:10.3724/SP.J.1047.2016.01217.LIAO L W,QIN J X.Ecological security of wetland in Chang-Zhu-Tan urban agglomeration [J].Journal of Geo-information Science,18(9):1217-1226.
[27] 王荣军,谢余初,张影,等.基于PSR模型的旱区城市湿地生态安全评估[J].生态科学,2015,34(3):133-138.DOI:10.14108/j.cnki.1008-8873.2015.03.023.WANG R J,XIE Y C,ZHANG Y,et al.Ecological security evaluation of urban wetland in arid China based on PSR model [J].Ecological Science,2015,34(3):133-138.
[28] 吴健生,张茜,曹祺文.快速城市化地区湿地生态安全评价——以深圳市为例[J].湿地科学,2017,15(3):321-328.DOI:10.13248/j.cnki.wetlandsci.2017.03.001.WU J S,ZHANG X,CAO Q W.Ecological security assessment of wetlands in rapidly urbanizing areas:a case study of Shenzhen,China [J].Wetland Science,2017,15(3):321-328.
[29] 李悦,张合兵,张小虎,等.基于熵值法和灰色预测模型的城市土地生态安全评价[J].环境科学与技术,2014,38(12):242-247.DOI:10.3969/j.issn.1003-6504.2015.12.043.LI Y,ZHANG H B,ZHANG X H,et al.Evaluation on ecological security of urban land based on entropy method and grey prediction model [J].Environmental Science & Technology,2014,38(12):242-247.
[2] BARBIER E B,HACKER S D,KENNEDY C,et al.The value of estuarine and coastal ecosystem services [J].Ecological Monographs,2011,81(2):169-193.DOI:10.1890/10-1510.1.
[3] 谢高地,鲁春霞,冷允法,等.青藏高原生态资产的价值评估[J].自然资源学报,2003,18(2):189-196.DOI:10.3321/j.issn:1000-3037.2003.02.010.XIE G D,LU C X,LENG Y F,et al.Ecological assets valuation of the Tibetan Plateau [J].Journal of Natural Resources,2003,18(2):189-196.
[4] 吴明.杭州湾滨海湿地现状与保护对策[J].林业资源管理,2004(6):44-47.DOI :10.13466/j.cnki.lyzyg l.2004.06.011.WU M.Current situation and conservation countermeasures of Hangzhou Bay wetland [J].Forest Resources Management,2004(6):44-47.
[5] 梁晨,李晓文,崔保山,等.中国滨海湿地优先保护格局构建[J].湿地科学,2015,13(6):660-666.DOI:10.13248/j.cnki.wetlandsci.2015.06.002.LIANG C,LI X W,CUI B S,et al.The pattern construction of priority protection for coastal wetlands in China [J].Wetland Science,2015,13(6):660-666.
[6] 卢奇.基于DPSIR模型的新疆艾里克湖生态安全评价研究[D].乌鲁木齐:新疆农业大学,2015.LU Q.The ecological security assessment of Eric Lake based on DPSIR model [D].Urumqi:Xinjiang Agricultural University,2015.
[7] 杜培军,陈宇,谭琨.湿地景观格局与生态安全遥感监测分析——以江苏滨海湿地为例[J].国土资源遥感,2014,26(1):158-166.DOI:10.6046/gtzyyg.2014.01.27.Du P J,CHEN Y,TAN K.Monitoring and analyzing wetland landscape pattern change and ecological security using remote sensing images:a case study of Jiangsu coastal wetland [J].Remote Sensing for Land & Resources,2014,26(1):158-166.
[8] 周云鹏,胡忠行,张曼,等.基于PSR模型的浙江望东垟亚高山湿地生态安全评价[J].湿地科学与管理,2017,13(2):20-24.DOI:10.3969/j.issn.1673-3290.2017.02.04.ZHOU Y P,HU Z X,ZHANG M,et al.PSR-based eco-security evaluation of Wangdongyang subalpine wetland in Zhejiang province [J].Wetland Science & Management,2017,13(2):20-24.
[9] 庄伟,廖和平,潘卓,等.基于变权TOPSIS模型的三峡库区土地生态安全评估——以巫山县为例[J].西南大学学报(自然科学版),2014,34(8):106-112.DOI:10.13718/cnki.xdzk.2014.08.019.ZHUANG W,LIAO H P,PAN Z,et al.Evaluation of land eco-security in the three gores reservoir region based on the variable weight TOPSIS model:a case study of Wushan [J].Journal of Southwest University (Natural Science Edition),2014,36(8):106-112.
[10] 劳燕玲.滨海湿地生态安全评价研究[D].北京:中国地质大学,2013.LAO Y L.Research on ecological security evaluation of coastal wetland [D].Beijing:China University of Geosciences,2013.
[11] 陈丽欣.河北省滨海湿地生态安全评价与保护研究[D].石家庄:河北师范大学,2010.CHEN L X.Protection and ecological security evaluation on coastal wetlands in Hebei Province [D].Shijiazhuang:Hebei Normal University,2010.
[12] 宁潇,胡咪咪,邵学新,等.杭州湾南岸滨海湿地生态服务功能价值评估[J].生态科学,2017,36(4):166-175,184.DOI:10.14108/j.cnki.1008-8873.2017.04.023.NING X,HU M M,SHAO X X,et al.Assessment of coastal wetland ecosystem services in the south of Hangzhou Bay [J].Ecological Science,2017,36(4):166-175.
[13] 高欣.杭州湾湿地生物多样性及其保护[J].沈阳师范大学学报(自然科学版),2006,24(1):92-95.DOI:10.3969/j.issn.1673-5862.2006.01.027.GAO X.Biodiversity and conservation of wetland of Hangzhou Bay [J].Journal of Shenyang Normal University (Natural Science Edition),2006,24(1):92-95.
[14] SUNT T,LIN W P,CHEN G S,et al.Wetland ecosystem health assessment through integrating remote sensing and inventory data with an assessment model for the Hangzhou Bay,China [J].Science of the Total Environment,2016,566-567:627-640.DOI:10.1016/j.scitotenv.2016.05.028.
[15] GARI S R,NEWTON A,ICELY J D.A review of the application and evolution of the DPSIR framework with an emphasis on coastal social-ecological systems [J].Ocean & Coastal Management,2015,103:63-77.DOI:10.1016/j.ocecoaman.2014.11.013.
[16] HAZARIKA N,NITIVATTANANON V.Strategic assessment of groundwater resource exploitation using DPSIR framework in Guwahati City,India [J].Habitat International,2016,51:79-89.DOI:10.1016/j.habitatint.2015.10.003.
[17] 宁波市统计局.宁波统计年鉴[M].北京:中国统计出版社,2001.Ningbo Municipal Statistics Bureau.Ningbo statistical yearbook [M].Beijing:China Statistics Press,2001.
[18] 宁波市统计局.宁波统计年鉴[M].北京:中国统计出版社,2006.Ningbo Municipal Statistics Bureau.Ningbo statistical yearbook [M].Beijing:China Statistics Press,2006.
[19] 宁波市统计局.宁波统计年鉴[M].北京:中国统计出版社,2011.Ningbo Municipal Statistics Bureau.Ningbo statistical yearbook [M].Beijing:China Statistics Press,2011.
[20] 宁波市统计局.宁波统计年鉴[M].北京:中国统计出版社,2016.Ningbo Municipal Statistics Bureau.Ningbo statistical yearbook [M].Beijing:China Statistics Press,2016.
[21] 张国钢,陈丽霞,陈水华,等.杭州湾大桥周边鸟类资源现状调查[J].动物学杂志,2014,49(5):672-685.DOI:10.13859 / j.cjz.201405006.ZHANG G G,CHEN L X,CHEN S H,et al.The survey on the bird community around the Hangzhou Bay Bridge in China [J].Chinese Journal of Zoology,2014,49(5):672-685.
[22] 刘世栋,薛东前,高峻.上海杭州湾北岸滨海地区生态安全评价[J].安全与环境学报,2012,12(6):124-130.DOI:10.3969/ j.issn.1009-6094.2012.06.02.LIU S D,XUE D Q,GAO J.Coastal eco-environmental security assessment of the northern shore of Shanghai-Hangzhou Bay [J].Journal of Safety and Environment,2012,12(6):124-130.
[23] 邹长新,陈金林,李海东.基于模糊综合评价的若尔盖湿地生态安全评价[J].南京林业大学学报(自然科学版),2012,36(3):53-58.ZOU C X,CHEN J L,LI H D.Fuzzy comprehensive assessment of ecological security evaluation in Zoige wetland [J].Journal of Nanjing Forestry University(Natural Sciences Edition),2012,36(3):53-58.
[24] LI N,LU D S,WU M,et al.Coastal wetland classification with multiseasonal high-spatial resolution satellite imagery [J].International Journal of Remote Sensing,2018:1-21.DOI:10.1080/01431161.2018.1500731.
[25] 朱卫红,苗承玉,郑小军,等.基于3S技术的图们江流域湿地生态安全评价与预警研究[J].生态学报,2014,34(6):1379-1390.DOI:10.5846/stxb201211241666.ZHU W H,MIAO C Y,ZHENG X J,et al.Study on ecological safety evaluation and warning of wetlands in Tumen River watershed based on 3S technology [J].Acta Ecologica Sinica,2014,34(6):1379-1390.
[26] 廖柳文,秦建新.环长株潭城市群湿地生态安全研究[J].地球信息科学学报,2016,18(9):1217-1226.DOI:10.3724/SP.J.1047.2016.01217.LIAO L W,QIN J X.Ecological security of wetland in Chang-Zhu-Tan urban agglomeration [J].Journal of Geo-information Science,18(9):1217-1226.
[27] 王荣军,谢余初,张影,等.基于PSR模型的旱区城市湿地生态安全评估[J].生态科学,2015,34(3):133-138.DOI:10.14108/j.cnki.1008-8873.2015.03.023.WANG R J,XIE Y C,ZHANG Y,et al.Ecological security evaluation of urban wetland in arid China based on PSR model [J].Ecological Science,2015,34(3):133-138.
[28] 吴健生,张茜,曹祺文.快速城市化地区湿地生态安全评价——以深圳市为例[J].湿地科学,2017,15(3):321-328.DOI:10.13248/j.cnki.wetlandsci.2017.03.001.WU J S,ZHANG X,CAO Q W.Ecological security assessment of wetlands in rapidly urbanizing areas:a case study of Shenzhen,China [J].Wetland Science,2017,15(3):321-328.
[29] 李悦,张合兵,张小虎,等.基于熵值法和灰色预测模型的城市土地生态安全评价[J].环境科学与技术,2014,38(12):242-247.DOI:10.3969/j.issn.1003-6504.2015.12.043.LI Y,ZHANG H B,ZHANG X H,et al.Evaluation on ecological security of urban land based on entropy method and grey prediction model [J].Environmental Science & Technology,2014,38(12):242-247.