The purpose is to analyze the situation of ecological security in Gansu from 2005 to 2015 and predict its development trend, thus to provide reference for improving the ecological environment situation. Based on the driving force-pressure-state-response (DPSR) model, an evaluation index system of ecologicalsecurity early warning of Gansu was established. Then, entropy method was used to analyze the ecological security situation from 2005 to 2015. Finally, the evolution trend of ecological security from 2018 to 2022 was predicted by grey GM (1,1) model. The results indicated that: the ecological security index of Gansu increased from 0.4103 to 0.5967 from 2005 to 2015 with a fluctuating increase trend, and the ecological security level was from Grade III to Grade II, and then turn to grade III, showing a“U”type trend, which indicated that the ecological environment of Gansu was improved to some extent after experiencing a deterioration. According to the results of the grey GM (1,1) model, the ecological safety index of 2018 to 2022 was 0.6344, 0.6592, 0.6859, 0.7148 and 0.7458, respectively, indicating that the ecological security situation in Gansu maintains a good
momentum.
Key words
ecological security early warning; D-P-S-R model；GM(1,1) gray prediction model；Gansu Province
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References
[1]舒帮荣,刘友兆,徐进亮,等.基于BP—ANN的生态安全预警研究——以苏州市为例[J].长江流域资源与环境,2010,19(09):1080-1085.
[2]胡和兵.生态敏感型地区生态安全评价与预警研究——以安徽省池州市为例[D].华东师范大学,2006.
[3]Brent Tegler,Mirek Sharp,Mary Ann Johnson.Ecological Monitoring and Assessment Network’s Proposed Core Monitoring Variables:An Early Warning of Environmental Change[J].Environmental Monitoring and Assessment:An International Journal, 2001(1/2) : 29-56.
[4]Ioannis M.Dokas,John Feehan,Syed Imran et al.EWaSAP: An early warning sign identification approach based on a systemic hazard analysis[J].Safety science,2013(1),58:11-26.
[5]Chris A.Boulton,Peter Good,Timothy M.Lenton.Early warning signals of simulated Amazon rainforest dieback[J].Theoretical Ecology, 2013, 6(3):373-384.
[6]Dan S, Oaie G, Radulescu V, et al.The Black Sea Security System—A New Early Warning and Environmental Monitoring System[M].Sustainable Development of Sea-Corridors and Coastal Waters. Springer International Publishing, 2015.
[7]马利邦,牛叔文,李永华,等.甘肃省生态安全评价及驱动因素分析[J].干旱区资源与环境,2009,23(5):30-36.
[8]陈国阶.对环境预警的探讨[J].重庆环境科学,1996,18(005):1-4.
[9]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.
[10]徐成龙,程钰,任建兰.黄河三角洲地区生态安全预警测度及时空格局[J].经济地理,2014,34(3):149-155.
[11]高家骥,李雪铭,张峰,等.南四湖湖泊湿地生态环境预警研究[J]. 地理科学,2016,36(08):1219-1226.
[12]王让虎,李晓燕,张树文,等. 东北农牧交错带景观生态安全格局构建及预警研究——以吉林省通榆县为例[J]. 地理与地理信息科学,2014,30(2):111-115.
[13]王治和,黄坤,张强.基于可拓云模型的区域生态安全预警模型及应用——以祁连山冰川与水源涵养生态功能区张掖段为例[J].安全与环境学报,2017,17(2):768-774.
[14]赵雪雁.产业结构生态预警研究——以甘肃省为例[J].干旱区地理,2007,30(1):128-134.
[15]李杨帆,林静玉,孙翔.城市区域生态风险预警方法及其在景观生态安全格局调控中的应用[J].地理研究,2017,36(3):485-494.
[16]徐美,朱翔,刘春腊. 基于RBF的湖南省土地生态安全动态预警[J].地理学报,2012,67(10):1411-1422.
[17]闫云平.西藏景区旅游承载力评估与生态安全预警系统设计与实现[D].中国地质大学(北京),2013.
[18]HAN Yiwen,LIU Zhong,YU Xueqian,et al.Desertification monitoring and early warning in context of sandy land consolidation[J].Transactions of the Chinese Society of Agricultural Engineering, 2017(10):271-277.
[19]尹亚.生态城市研究方法探讨[D].兰州:兰州大学,2012.
[20]张玉泽,任建兰,刘凯,等.山东省生态安全预警测度及时空格局[J].经济地理,2015,35(11):166-171.
[21]李玉照,刘永,颜小品.基于DPSIR模型的流域生态安全评价指标体系研究[J].北京大学学报(自然科学版), 2012, 48(6):971-981.
[22]郭锐利,郑钦玉,刘娟,等.基于熵值法和GM(1,1)模型的重庆城市生态系统健康评价[J].中国环境科学, 2012, 32(6):1148-1152.
[23]邬万江,张连富,卢伟.用Excel建立灰色数列预测模型的研究[J].佳木斯大学学报(自然科学版),2005,23(3):378-380.
[24] 周健,刘占才.基于GM(1,1)预测模型的兰州市生态安全预警与调控研究[J].干旱区资源与环境,2011,25(1):15-19.
[25]袁瑞萍,李俊韬,田志勇.基于GM(1,1)残差模型的科技园区财政收入预测[J].数学的实践与认识,2016,46(18):109-114.
[26]吴林红,汪国梁.着力完善生态保护红线制度[EB/OL].http://news.ifeng.com/a/20180304/56454952_0.shtml,2018-03-04.
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