新疆土地生态安全时空变化
|
摘要
土地生态安全评价能高效引导土地合理利用,协调生态保护与区域经济发展之间的矛盾。以核密度估算法及克里金空间插值为技术支撑,构建基于突变级数法的土地生态安全评价指标体系,并采用空间变异系数法及灰色预测模型对新疆土地生态安全进行探索性测度分析。结果表明:(1)新疆土地生态安全总体水平不断提高。土地生态安全指数由2004年的0.76上升到2017年0.94,安全等级呈现"不安全→较不安全→临界安全→较安全"的发展趋势。(2)新疆各县市土地生态安全的不均衡性得到改善,空间差异缩小。新疆土地生态安全空间变异系数由2004年的0.51上升为2017年的0.84,呈持续上升趋势,其中2009年到2014年期间最快增加了0.29。(3)研究区人口增加了27.59%,同时未利用地和草地面积的减少量分别占到整个新疆面积的7.51‰和9.45‰。自然资源分布不均、社会经济发展对未利用地和草地的大量占用以及区域人口的急剧增加可能是新疆土地生态安全面临的主要问题。(4)通过灰色模型预测,2020年新疆土地生态安全将进一步得到改善,土地生态安全空间差异将进一步缩小。与2005年相比, 2020年空间变异系数将上升到0.85;安全区和临界安全区将分别增加2.06%和11.24%;较安全区、较不安全区、不安全区将分别下降2.98%、9.16%、1.15%。
Land ecological security assessment can guide rational land use efficiently and coordinate the contradiction between ecological protection and regional economic development. Supported by the kernel density estimation method and Kriging spatial interpolation, the index system of land ecological security evaluation based on catastrophe progression method has been constructed, and the spatial variation coefficient method and grey prediction model have been used to analyze the land ecological security in Xinjiang. The results indicated that:(1) the overall level of land ecological security in Xinjiang has continuously improved. The land ecological security index increased from 0.76 in 2004 to 0.94 in 2017; the development trend of "unsafe→less safe→critical safety→safer" is apparent at the ecological security level;(2) the disequilibrium of land ecological security has been improved and spatial differences have been reduced in all counties and cities of Xinjiang. The spatial variation coefficient of land ecological security in Xinjiang increased from 0.51 in 2004 to 0.84 in 2017. There has been a sustained upward trend, with the fastest increase of 0.29 between 2009 and 2014;(3) the population of the research area increased by 27.59%, whereas the area of unused land and grassland decreased by 7.51‰ and 9.45‰, respectively. The uneven distribution of natural resources, extensive occupation of unused land and grassland for socio-economic development, and sharp increase in regional population may be the main problems of land ecological security in Xinjiang;(4) through the gray model prediction, the land ecological security of Xinjiang will be further improved in 2020, and the spatial difference of land ecological security will be further reduced. Compared with the scenario in 2005, the spatial variation coefficient will increase to 0.85 in 2020; the safety and critical safety zones will be increased by 2.06% and 11.24%, respectively; and the safer, less safe and unsafe zones will be reduced by 2.98%, 9.16%, and 1.15%, respectively.
Land ecological security assessment can guide rational land use efficiently and coordinate the contradiction between ecological protection and regional economic development. Supported by the kernel density estimation method and Kriging spatial interpolation, the index system of land ecological security evaluation based on catastrophe progression method has been constructed, and the spatial variation coefficient method and grey prediction model have been used to analyze the land ecological security in Xinjiang. The results indicated that:(1) the overall level of land ecological security in Xinjiang has continuously improved. The land ecological security index increased from 0.76 in 2004 to 0.94 in 2017; the development trend of "unsafe→less safe→critical safety→safer" is apparent at the ecological security level;(2) the disequilibrium of land ecological security has been improved and spatial differences have been reduced in all counties and cities of Xinjiang. The spatial variation coefficient of land ecological security in Xinjiang increased from 0.51 in 2004 to 0.84 in 2017. There has been a sustained upward trend, with the fastest increase of 0.29 between 2009 and 2014;(3) the population of the research area increased by 27.59%, whereas the area of unused land and grassland decreased by 7.51‰ and 9.45‰, respectively. The uneven distribution of natural resources, extensive occupation of unused land and grassland for socio-economic development, and sharp increase in regional population may be the main problems of land ecological security in Xinjiang;(4) through the gray model prediction, the land ecological security of Xinjiang will be further improved in 2020, and the spatial difference of land ecological security will be further reduced. Compared with the scenario in 2005, the spatial variation coefficient will increase to 0.85 in 2020; the safety and critical safety zones will be increased by 2.06% and 11.24%, respectively; and the safer, less safe and unsafe zones will be reduced by 2.98%, 9.16%, and 1.15%, respectively.
引文
[1] 黄晓东.新疆土地生态安全动态评价及障碍因子诊断[D].乌鲁木齐:新疆农业大学,2016.
[2] 刘雯波,郑华伟,刘友兆.基于物元模型的苏南地区土地生态安全评价.水土保持通报,2013,33(6):175- 180.
[3] Wang H,Long H L,Li X B,Yu F.Evaluation of changes in ecological security in China′s Qinghai Lake Basin from 2000 to 2013 and the relationship to land use and climate change.Environmental Earth Sciences,2014,72(2):341- 354.
[4] Zhang J S,Gao J Q.Lake ecological security assessment based on SSWSSC framework from 2005 to 2013 in an interior lake basin,China.Environmental Earth Sciences,2016,75(10):888.
[5] Li X B,Tian M R,Wang H,Wang H,Yu J J.Development of an ecological security evaluation method based on the ecological footprint and application to a typical steppe region in China.Ecological Indicators,2014,39:153- 159.
[6] Zhou K H,Liu Y L,Tan R H,Song Y.Urban dynamics,landscape ecological security,and policy implications:a case study from the Wuhan area of central China.Cities,2014,41:141- 153.
[7] 李强,刘云庆,陈望香,王兴磊,周晓花,冯伟莹.新疆地表水体重金属生态风险评估.中国环境科学,2018,38(5):1913- 1922.
[8] Xu X B,Yang G S,Tan Y,Zhuang Q L,Li H P,Wan R R,Su W Z,Zhang J.Ecological risk assessment of ecosystem services in the Taihu Lake Basin of China from 1985 to 2020.Science of the Total Environment,2016,554- 555:7- 16.
[9] 于潇,吴克宁,郧文聚,魏洪斌,刘玲,宋英赫,高星.三江平原现代农业区景观生态安全时空分异分析.农业工程学报,2016,32(8):253- 259.
[10] 李彩惠,霍海鹰,李雅洁,侯玮.基于突变级数模型的城市低碳竞争力评价及障碍因子诊断分析.资源科学,2015,37(7):1474- 1481.
[11] 秦伟霞,王新闯,马守臣,张合兵,陈宁丽,宋香平.基于功能分区的土地生态质量障碍因子诊断——以新乡市为例.水土保持研究,2015,22(4):148- 154.
[12] 周磊,黄秋昊.基于灰色关联TOPSIS的城市土地效益评价及障碍因子诊断.水土保持研究,2014,21(4):39- 44.
[13] 李春燕,南灵.陕西省土地生态安全动态评价及障碍因子诊断.中国土地科学,2015,29(4):72- 81.
[14] 王鹏,况福民,邓育武,田亚平,易锋.基于主成分分析的衡阳市土地生态安全评价.经济地理,2015,35(1):168- 172.
[15] 张宇,游和远.基于P-S-R的土地资源生态环境安全评价——以湖北省为例.生态经济,2015,31(8):125- 128.
[16] 李明月,赖笑娟.基于BP神经网络方法的城市土地生态安全评价——以广州市为例.经济地理,2011,31(2):289- 293.
[17] Huang L,Yan L J,Wu J G.Assessing urban sustainability of Chinese megacities:35 years after the economic reform and open-door policy.Landscape and Urban Planning,2016,145:57- 70.
[18] 刘莎莎.新疆植被覆盖变化及其对气候的敏感性分析[D].泰安:山东农业大学,2017:3- 5.
[19] 刘凌冰.甘肃省土地生态安全评价研究[D].杨凌:西北农林科技大学,2014:2- 6.
[20] 秦晓楠,卢小丽,武春友.国内生态安全研究知识图谱——基于Citespace的计量分析.生态学报,2014,34(13):3693- 3703.
[21] 李鹏山,吕雅慧,张超,郧文聚,杨建宇,朱德海.基于核密度估计的京津冀地区耕地破碎化分析.农业机械学报,2016,47(5):281- 287.
[22] 李黎,王会豪,任平.基于核密度估算的都江堰耕地破碎化趋势及特征分析.信阳师范学院学报:自然科学版,2017,30(1):72- 76.
[23] Han B L,Liu H X,Wang R S.Urban ecological security assessment for cities in the Beijing-Tianjin-Hebei metropolitan region based on fuzzy and entropy methods.Ecological Modelling,2015,318:217- 225.
[24] 谢余初,巩杰,张玲玲.基于PSR模型的白龙江流域景观生态安全时空变化.地理科学,2015,35(6):790- 797.
[25] 潘竟虎,刘晓.疏勒河流域景观生态风险评价与生态安全格局优化构建.生态学杂志,2016,35(3):791- 799.
[26] 孟祥凤,王冬艳,李红.东北老工业城市建设占用耕地驱动力分析.农业工程学报,2018,34(11):225- 233.
[27] 于海洋,张飞,曹雷,王娟,杨胜天.基于乡镇尺度的土地生态安全时空格局评价研究——以博尔塔拉蒙古自治州为例.生态学报,2017,37(19):6355- 6369.
[28] 胡源.武汉市耕地资源安全评价研究[D].武汉:华中农业大学,2014:31- 55.
[29] 邓维强.基于DPSIR模型的罗平县耕地资源安全评价研究[D].昆明:云南大学,2015.
[30] 赵杰,刘雪佳,杜自强,武志涛,徐小明.昼夜增温速率的不对称性对新疆地区植被动态的影响.中国环境科学,2017,37(6):2316- 2321.
[31] 高原.基于遥感的新疆NPP时空变化特征及其影响因素分析[D].兰州:西北师范大学,2015.
[32] 李魁明,帅红,姚罗兰.基于物元模型的岳阳市土地生态安全评价.湖南农业科学,2013,(21):44- 48.
[33] 邓文叶,贾尔恒·阿哈提,魏明娜,马俊英,牛婷,祝婕,蔺尾燕,都伟新.新疆准噶尔盆地南缘一次典型沙尘污染特征分析.新疆环境保护,2017,39(02):1- 6,17- 17.
[34] 张月,张飞,王娟,任岩,Ghulam A,Kung H.基于LUCC的艾比湖区域生态风险评价及预测研究.中国环境科学,2016,36(11):3465- 3474.
[35] 邵玲.新疆土地利用总体规划的生态足迹评价研究[D].乌鲁木齐:新疆农业大学,2011.
[36] 洪惠坤,廖和平,魏朝富,李涛,谢德体.基于改进TOPSIS方法的三峡库区生态敏感区土地利用系统健康评价.生态学报,2015,35(24):8016- 8027.
[37] 高星.耕地质量等级提升的土地整治项目设计关键技术研究[D].北京:中国地质大学,2016.
[38] 王波,王夏晖,张笑千.“山水林田湖草生命共同体”的内涵、特征与实践路径——以承德市为例.环境保护,2018,46(7):60- 63.
[2] 刘雯波,郑华伟,刘友兆.基于物元模型的苏南地区土地生态安全评价.水土保持通报,2013,33(6):175- 180.
[3] Wang H,Long H L,Li X B,Yu F.Evaluation of changes in ecological security in China′s Qinghai Lake Basin from 2000 to 2013 and the relationship to land use and climate change.Environmental Earth Sciences,2014,72(2):341- 354.
[4] Zhang J S,Gao J Q.Lake ecological security assessment based on SSWSSC framework from 2005 to 2013 in an interior lake basin,China.Environmental Earth Sciences,2016,75(10):888.
[5] Li X B,Tian M R,Wang H,Wang H,Yu J J.Development of an ecological security evaluation method based on the ecological footprint and application to a typical steppe region in China.Ecological Indicators,2014,39:153- 159.
[6] Zhou K H,Liu Y L,Tan R H,Song Y.Urban dynamics,landscape ecological security,and policy implications:a case study from the Wuhan area of central China.Cities,2014,41:141- 153.
[7] 李强,刘云庆,陈望香,王兴磊,周晓花,冯伟莹.新疆地表水体重金属生态风险评估.中国环境科学,2018,38(5):1913- 1922.
[8] Xu X B,Yang G S,Tan Y,Zhuang Q L,Li H P,Wan R R,Su W Z,Zhang J.Ecological risk assessment of ecosystem services in the Taihu Lake Basin of China from 1985 to 2020.Science of the Total Environment,2016,554- 555:7- 16.
[9] 于潇,吴克宁,郧文聚,魏洪斌,刘玲,宋英赫,高星.三江平原现代农业区景观生态安全时空分异分析.农业工程学报,2016,32(8):253- 259.
[10] 李彩惠,霍海鹰,李雅洁,侯玮.基于突变级数模型的城市低碳竞争力评价及障碍因子诊断分析.资源科学,2015,37(7):1474- 1481.
[11] 秦伟霞,王新闯,马守臣,张合兵,陈宁丽,宋香平.基于功能分区的土地生态质量障碍因子诊断——以新乡市为例.水土保持研究,2015,22(4):148- 154.
[12] 周磊,黄秋昊.基于灰色关联TOPSIS的城市土地效益评价及障碍因子诊断.水土保持研究,2014,21(4):39- 44.
[13] 李春燕,南灵.陕西省土地生态安全动态评价及障碍因子诊断.中国土地科学,2015,29(4):72- 81.
[14] 王鹏,况福民,邓育武,田亚平,易锋.基于主成分分析的衡阳市土地生态安全评价.经济地理,2015,35(1):168- 172.
[15] 张宇,游和远.基于P-S-R的土地资源生态环境安全评价——以湖北省为例.生态经济,2015,31(8):125- 128.
[16] 李明月,赖笑娟.基于BP神经网络方法的城市土地生态安全评价——以广州市为例.经济地理,2011,31(2):289- 293.
[17] Huang L,Yan L J,Wu J G.Assessing urban sustainability of Chinese megacities:35 years after the economic reform and open-door policy.Landscape and Urban Planning,2016,145:57- 70.
[18] 刘莎莎.新疆植被覆盖变化及其对气候的敏感性分析[D].泰安:山东农业大学,2017:3- 5.
[19] 刘凌冰.甘肃省土地生态安全评价研究[D].杨凌:西北农林科技大学,2014:2- 6.
[20] 秦晓楠,卢小丽,武春友.国内生态安全研究知识图谱——基于Citespace的计量分析.生态学报,2014,34(13):3693- 3703.
[21] 李鹏山,吕雅慧,张超,郧文聚,杨建宇,朱德海.基于核密度估计的京津冀地区耕地破碎化分析.农业机械学报,2016,47(5):281- 287.
[22] 李黎,王会豪,任平.基于核密度估算的都江堰耕地破碎化趋势及特征分析.信阳师范学院学报:自然科学版,2017,30(1):72- 76.
[23] Han B L,Liu H X,Wang R S.Urban ecological security assessment for cities in the Beijing-Tianjin-Hebei metropolitan region based on fuzzy and entropy methods.Ecological Modelling,2015,318:217- 225.
[24] 谢余初,巩杰,张玲玲.基于PSR模型的白龙江流域景观生态安全时空变化.地理科学,2015,35(6):790- 797.
[25] 潘竟虎,刘晓.疏勒河流域景观生态风险评价与生态安全格局优化构建.生态学杂志,2016,35(3):791- 799.
[26] 孟祥凤,王冬艳,李红.东北老工业城市建设占用耕地驱动力分析.农业工程学报,2018,34(11):225- 233.
[27] 于海洋,张飞,曹雷,王娟,杨胜天.基于乡镇尺度的土地生态安全时空格局评价研究——以博尔塔拉蒙古自治州为例.生态学报,2017,37(19):6355- 6369.
[28] 胡源.武汉市耕地资源安全评价研究[D].武汉:华中农业大学,2014:31- 55.
[29] 邓维强.基于DPSIR模型的罗平县耕地资源安全评价研究[D].昆明:云南大学,2015.
[30] 赵杰,刘雪佳,杜自强,武志涛,徐小明.昼夜增温速率的不对称性对新疆地区植被动态的影响.中国环境科学,2017,37(6):2316- 2321.
[31] 高原.基于遥感的新疆NPP时空变化特征及其影响因素分析[D].兰州:西北师范大学,2015.
[32] 李魁明,帅红,姚罗兰.基于物元模型的岳阳市土地生态安全评价.湖南农业科学,2013,(21):44- 48.
[33] 邓文叶,贾尔恒·阿哈提,魏明娜,马俊英,牛婷,祝婕,蔺尾燕,都伟新.新疆准噶尔盆地南缘一次典型沙尘污染特征分析.新疆环境保护,2017,39(02):1- 6,17- 17.
[34] 张月,张飞,王娟,任岩,Ghulam A,Kung H.基于LUCC的艾比湖区域生态风险评价及预测研究.中国环境科学,2016,36(11):3465- 3474.
[35] 邵玲.新疆土地利用总体规划的生态足迹评价研究[D].乌鲁木齐:新疆农业大学,2011.
[36] 洪惠坤,廖和平,魏朝富,李涛,谢德体.基于改进TOPSIS方法的三峡库区生态敏感区土地利用系统健康评价.生态学报,2015,35(24):8016- 8027.
[37] 高星.耕地质量等级提升的土地整治项目设计关键技术研究[D].北京:中国地质大学,2016.
[38] 王波,王夏晖,张笑千.“山水林田湖草生命共同体”的内涵、特征与实践路径——以承德市为例.环境保护,2018,46(7):60- 63.