江苏省县域森林生态安全评价及空间计量分析
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摘要
通过考察生态区位因素对森林生态安全的影响,建立评价指标体系,研究其空间相关性的内在效应机制,从而实现森林生态安全的评价与监测。以江苏省80个区县为研究对象,基于2000—2015年面板数据,运用熵权法、专家法及模糊物元法计算森林生态安全指数,然后结合气象类指标及地形类指标计算生态区位系数,再用该系数修正森林ESI,同时结合Arc GIS技术、空间相关性分析、SLM与SEM模型得出如下结论:(1)人口密度、单位面积能源消耗量、退耕还林面积占比等指标权重最大;(2)生态区位系数高值区主要分布在江苏南部少数地区,低值区主要分布在江苏东北部;(3)苏南地区森林生态安全状况整体好于苏北及中东部地区;(4) 2000—2015年,江苏省67.5%的区县森林ESI呈现出较明显下降趋势,反映出江苏省森林生态安全发展状况不容乐观;(5)江苏省县域森林ESI整体空间相关性显著(P≤0.01),但2000—2015年空间聚集程度有所下降,且Low-Low聚类显著性更强;(6)森林ESI在江苏省县域间为扩散效应与回流效应并存。
The aim of the present study was to examine the impact of ecological location factors on forest ecological security,establish an evaluation index system and study the internal effect mechanism of its spatial correlation to evaluate and monitor forest ecological security.Based on 80 counties in Jiangsu Province forest panel data from 2000 to 2015 were analyzed in this study using the entropy,expert,and fuzzy matter element methods to calculate the forest ecological security index,which was adjusted according to the ecological location model obtained from the meteorological and terrain indexes.Moreover,the combined use of Arc GIS software,ESDA and CSDA models in the present study revealed that( 1) population density,unit area energy consumption and proportion of reforestation area are the most important measures;( 2) the area with the highest ecological location coefficient was mainly distributed in southern Jiangsu Province. Further,the area with the lowest ecological location coefficient was mainly distributed in the northeast;( 3) the forest ecological security status in southern Jiangsu was better than that in northern and mideastern Jiangsu;( 4) regarding forest cover change from 2000 to 2015,65%of the ESI index of all counties in Jiangsu Province showed an obvious declining trend;( 5) the overall spatial correlation ofthe forest ESI index in counties of the Jiangsu Province was significant,but the spatial aggregation in 2000—2015 decreased and Low-Low clustering was more significant( P≤0.01); and( 6) the diffusion and reflux effects between the forest ESI index in the counties of Jiangsu Province were concomitant.
The aim of the present study was to examine the impact of ecological location factors on forest ecological security,establish an evaluation index system and study the internal effect mechanism of its spatial correlation to evaluate and monitor forest ecological security.Based on 80 counties in Jiangsu Province forest panel data from 2000 to 2015 were analyzed in this study using the entropy,expert,and fuzzy matter element methods to calculate the forest ecological security index,which was adjusted according to the ecological location model obtained from the meteorological and terrain indexes.Moreover,the combined use of Arc GIS software,ESDA and CSDA models in the present study revealed that( 1) population density,unit area energy consumption and proportion of reforestation area are the most important measures;( 2) the area with the highest ecological location coefficient was mainly distributed in southern Jiangsu Province. Further,the area with the lowest ecological location coefficient was mainly distributed in the northeast;( 3) the forest ecological security status in southern Jiangsu was better than that in northern and mideastern Jiangsu;( 4) regarding forest cover change from 2000 to 2015,65%of the ESI index of all counties in Jiangsu Province showed an obvious declining trend;( 5) the overall spatial correlation ofthe forest ESI index in counties of the Jiangsu Province was significant,but the spatial aggregation in 2000—2015 decreased and Low-Low clustering was more significant( P≤0.01); and( 6) the diffusion and reflux effects between the forest ESI index in the counties of Jiangsu Province were concomitant.
引文
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[2]顾艳红,张大红.省域森林生态安全评价——基于5省的经验数据.生态学报,2017,37(18):6229-6239.
[3] Mathews JT. Redefining security. Foreign Affairs,1989,68(2):162-177.
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[8] Hayes E H,Landis W G. Regional ecological risk assessment of a near shore marine environment:cherry point,WA. Human and Ecological Risk Assessment:An International Journal,2004,10(2):299-325.
[9] Costanza R,Norton BG,Haskell BD. Ecosystem Health:New Goals for Environmental Management. Washington,DC:IslandPress,1992:234-246.
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[12]米锋,谭曾豪迪,顾艳红,鲁莎莎,张大红.我国森林生态安全评价及其差异化分析.林业科学,2015,51(7):107-115.
[13]张智光.基于生态-产业共生关系的林业生态安全测度方法构想.生态学报,2013,33(4):1326-1336.
[14]赵宏波,马延吉.东北粮食主产区耕地生态安全的时空格局及障碍因子——以吉林省为例.应用生态学报,2014,25(2):515-524.
[15]吕建树,吴泉源,张祖陆,刘洋.基于RS和GIS的济宁市土地利用变化及生态安全研究.地理科学,2012,32(8):928-935.
[16]杨振姣,姜自福,罗玲云.海洋生态安全研究综述.海洋环境科学,2011,30(2):287-291.
[17]刘良明,魏然,周正.利用动态阈值的森林草原火灾火点检测算法.武汉大学学报:信息科学版,2011,36(12):1434-1437.
[18]刘心竹,米锋,张爽,苏立娟,顾艳红,张大红.基于有害干扰的中国省域森林生态安全评价.生态学报,2014,34(11):3115-3127.
[19]张智光.林业生态安全的共生耦合测度模型与判据.中国人口·资源与环境,2014,24(8):90-99.
[20]汤旭,冯彦,王慧,张大红.湖南省县域森林生态安全评价与时空分析.南京林业大学学报:自然科学版,2017,41:1-22.
[21]韩智霞,张江山.基于熵权的模糊物元法对福建省大气环境质量的综合评价.安全与环境工程,2009,16(5):30-33.
[22]蔡文.物元模型及其应用.北京:科学技术文献出版社,1994.
[23]张斌,雍歧东,肖芳淳.模糊物元分析.北京:石油工业出版社,1997.
[24]赵海凤,刘川源,鲁莎莎,张大红.基于区位模型的四川森林生态服务价值核算研究.河南农业大学学报,2015,49(6):831-837.
[25]李婧,谭清美,白俊红.中国区域创新生产的空间计量分析——基于静态与动态空间面板模型的实证研究.管理世界,2010,(7):43-55,65-65.
[26]何键芳,张虹鸥,叶玉瑶,吴旗韬.广东省区域创新产出的空间相关性研究.经济地理,2013,33(2):117-121.
[27]张贵,李涛.京津冀省域创新效率差异演化与空间计量分析.地域研究与开发,2017,36(4):13-18.
[28]薛达元,蒋明康,王献溥.我国自然保护区级别划分标准的研究.生态与农村环境学报,1993,9(2):1-4,66-66.
[29]高守荣,洪林.深化国有林场改革推进林场经济发展——贵州省毕节市国有林场改革发展的经验与成效.林业经济,2014,36(11):6-9.
[30]李英,齐丹坤.基于生态区位测度的伊春林区森林生态服务功能价值评估.林业科学,2013,49(8):140-147.
[31]陈昕,彭建,刘焱序,杨旸,李贵才.基于“重要性—敏感性—连通性”框架的云浮市生态安全格局构建.地理研究,2017,36(3):471-484.
[32]陈磊,田双清,张宽,陈文宽.基于耗散结构理论的四川省耕地生态安全测度分析.水土保持研究,2017,24(2):307-313.
[33]郭跃,程晓昀,朱芳,姜瑞华.基于生态足迹的江苏省生态安全动态研究.长江流域资源与环境,2010,19(11):1327-1332.
[34]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.北京大学学报:自然科学版,2012,48(6):971-981.
[35]周彬,钟林生,陈田,周睿.基于变权模型的舟山群岛生态安全预警.应用生态学报,2015,26(6):1854-1862.
[36]任继勤,夏景阳,殷悦.基于改进的BP神经网络和马尔科夫模型的一次能源消费预测——以北京市为例.生态经济,2017,33(11):28-33.
[37]张家其,吴宜进,葛咏,王程昊,Kung H.基于灰色关联模型的贫困地区生态安全综合评价——以恩施贫困地区为例.地理研究,2014,33(8):1457-1466.
[38]朱卫红,苗承玉,郑小军,曹光兰,王凡凡.基于3S技术的图们江流域湿地生态安全评价与预警研究.生态学报,2014,34(6):1379-1390.
[39]王耕,王嘉丽,龚丽妍,苏柏灵,刘秋波.基于GIS-Markov区域生态安全时空演变研究——以大连市甘井子区为例.地理科学,2013,33(8):957-964.
[40]欧定华,夏建国,欧晓芳.基于GIS和RBF的城郊区生态安全评价及变化趋势预测——以成都市龙泉驿区为例.地理与地理信息科学,2017,33(1):49-58.
[2]顾艳红,张大红.省域森林生态安全评价——基于5省的经验数据.生态学报,2017,37(18):6229-6239.
[3] Mathews JT. Redefining security. Foreign Affairs,1989,68(2):162-177.
[4] Rogers K S. Ecological Security and Multinational Corporations.Environmental Change and Security Project(ECSP)Report. Washington,DC:Woodrow Wilson Center,1997:29-36.
[5] Helman GB,Ratner SR. Saving failed states. Foreign Policy,1992-1993,89:3-20.
[6]邹长新,沈渭寿.生态安全研究进展.农村生态环境,2003,19(1):56-59.
[7] Moraes R,Landis W G,Molander S. Regional risk assessment of a Brazilian rain forest reserve. Human and Ecological Risk Assessment:An International Journal,2002,8(7):1779-1803.
[8] Hayes E H,Landis W G. Regional ecological risk assessment of a near shore marine environment:cherry point,WA. Human and Ecological Risk Assessment:An International Journal,2004,10(2):299-325.
[9] Costanza R,Norton BG,Haskell BD. Ecosystem Health:New Goals for Environmental Management. Washington,DC:IslandPress,1992:234-246.
[10] Hunsaker C T,Graham R L,Suter II G W,O'Neill R V,Barnthouse L W,Gardner R H. Assessing ecological risk on a regional scale.Environmental Management,1990,14(3):325-332.
[11]刘婷婷,孔越,吴叶,祝凌云,张大红.基于熵权模糊物元模型的我国省域森林生态安全研究.生态学报,2017,37(15):4946-4955.
[12]米锋,谭曾豪迪,顾艳红,鲁莎莎,张大红.我国森林生态安全评价及其差异化分析.林业科学,2015,51(7):107-115.
[13]张智光.基于生态-产业共生关系的林业生态安全测度方法构想.生态学报,2013,33(4):1326-1336.
[14]赵宏波,马延吉.东北粮食主产区耕地生态安全的时空格局及障碍因子——以吉林省为例.应用生态学报,2014,25(2):515-524.
[15]吕建树,吴泉源,张祖陆,刘洋.基于RS和GIS的济宁市土地利用变化及生态安全研究.地理科学,2012,32(8):928-935.
[16]杨振姣,姜自福,罗玲云.海洋生态安全研究综述.海洋环境科学,2011,30(2):287-291.
[17]刘良明,魏然,周正.利用动态阈值的森林草原火灾火点检测算法.武汉大学学报:信息科学版,2011,36(12):1434-1437.
[18]刘心竹,米锋,张爽,苏立娟,顾艳红,张大红.基于有害干扰的中国省域森林生态安全评价.生态学报,2014,34(11):3115-3127.
[19]张智光.林业生态安全的共生耦合测度模型与判据.中国人口·资源与环境,2014,24(8):90-99.
[20]汤旭,冯彦,王慧,张大红.湖南省县域森林生态安全评价与时空分析.南京林业大学学报:自然科学版,2017,41:1-22.
[21]韩智霞,张江山.基于熵权的模糊物元法对福建省大气环境质量的综合评价.安全与环境工程,2009,16(5):30-33.
[22]蔡文.物元模型及其应用.北京:科学技术文献出版社,1994.
[23]张斌,雍歧东,肖芳淳.模糊物元分析.北京:石油工业出版社,1997.
[24]赵海凤,刘川源,鲁莎莎,张大红.基于区位模型的四川森林生态服务价值核算研究.河南农业大学学报,2015,49(6):831-837.
[25]李婧,谭清美,白俊红.中国区域创新生产的空间计量分析——基于静态与动态空间面板模型的实证研究.管理世界,2010,(7):43-55,65-65.
[26]何键芳,张虹鸥,叶玉瑶,吴旗韬.广东省区域创新产出的空间相关性研究.经济地理,2013,33(2):117-121.
[27]张贵,李涛.京津冀省域创新效率差异演化与空间计量分析.地域研究与开发,2017,36(4):13-18.
[28]薛达元,蒋明康,王献溥.我国自然保护区级别划分标准的研究.生态与农村环境学报,1993,9(2):1-4,66-66.
[29]高守荣,洪林.深化国有林场改革推进林场经济发展——贵州省毕节市国有林场改革发展的经验与成效.林业经济,2014,36(11):6-9.
[30]李英,齐丹坤.基于生态区位测度的伊春林区森林生态服务功能价值评估.林业科学,2013,49(8):140-147.
[31]陈昕,彭建,刘焱序,杨旸,李贵才.基于“重要性—敏感性—连通性”框架的云浮市生态安全格局构建.地理研究,2017,36(3):471-484.
[32]陈磊,田双清,张宽,陈文宽.基于耗散结构理论的四川省耕地生态安全测度分析.水土保持研究,2017,24(2):307-313.
[33]郭跃,程晓昀,朱芳,姜瑞华.基于生态足迹的江苏省生态安全动态研究.长江流域资源与环境,2010,19(11):1327-1332.
[34]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.北京大学学报:自然科学版,2012,48(6):971-981.
[35]周彬,钟林生,陈田,周睿.基于变权模型的舟山群岛生态安全预警.应用生态学报,2015,26(6):1854-1862.
[36]任继勤,夏景阳,殷悦.基于改进的BP神经网络和马尔科夫模型的一次能源消费预测——以北京市为例.生态经济,2017,33(11):28-33.
[37]张家其,吴宜进,葛咏,王程昊,Kung H.基于灰色关联模型的贫困地区生态安全综合评价——以恩施贫困地区为例.地理研究,2014,33(8):1457-1466.
[38]朱卫红,苗承玉,郑小军,曹光兰,王凡凡.基于3S技术的图们江流域湿地生态安全评价与预警研究.生态学报,2014,34(6):1379-1390.
[39]王耕,王嘉丽,龚丽妍,苏柏灵,刘秋波.基于GIS-Markov区域生态安全时空演变研究——以大连市甘井子区为例.地理科学,2013,33(8):957-964.
[40]欧定华,夏建国,欧晓芳.基于GIS和RBF的城郊区生态安全评价及变化趋势预测——以成都市龙泉驿区为例.地理与地理信息科学,2017,33(1):49-58.