Volume 34 Issue 6
Nov.  2017
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WEN Guojing, LIU Yungen, WANG Yan, HOU Lei, WANG Yanxia, GUO Yujing. Temporal and spatial evolution of landscape patterns and ecological risk in the Puzhehei Lake basin[J]. Journal of Zhejiang A&F University, 2017, 34(6): 1095-1103. doi: 10.11833/j.issn.2095-0756.2017.06.018
Citation: WEN Guojing, LIU Yungen, WANG Yan, HOU Lei, WANG Yanxia, GUO Yujing. Temporal and spatial evolution of landscape patterns and ecological risk in the Puzhehei Lake basin[J]. Journal of Zhejiang A&F University, 2017, 34(6): 1095-1103. doi: 10.11833/j.issn.2095-0756.2017.06.018

Temporal and spatial evolution of landscape patterns and ecological risk in the Puzhehei Lake basin

doi: 10.11833/j.issn.2095-0756.2017.06.018
  • Received Date: 2016-11-29
  • Rev Recd Date: 2017-02-28
  • Publish Date: 2017-12-20
  • To analyze temporal and spatial evolution for ecological risk and landscape patterns in a lake basin so as to further improve the ecological environment, Puzhehei Lake basin in Yunnan Province was studied over(1990, 1995, 2000, 2005, 2010, and 2015). Analysis included using the spatial analysis function of ArcGIS based on the landscape disturbance index and the landscape loss index to constructed a landscape ecological risk index. Results showed that:(1) For landscape patterns from 1990 to 2015, the degree of disturbance for agricultural land and woodlands was the most intense, while that of building land, gardens, and wetlands was slightly weaker, and that of unused land was the weakest with the interference degree index ranged from 0.208 7 to 0.218 0. In addition, the variation range of disturbance index for agricultural land was quite narrow (from 0.375 8 to 0.379 6), whereas that for construction land fluctuated largely with a changing rate of -14.10%. (2) For twenty years (from 2005 to 2015), the degree of landscape loss for different land-use varied markedly. The index of landscape loss for farmland and unused land was the largest with the values of 0.542 2 and 0.551 4, respectively, whereas that for wetland, construction land, and forest land take the second place, and that for garden land was the smallest (0.119 7). (3) From 1990 to 2015, the spatial distribution of ecological risk changed largely, and it showed a low level of ecological risk between 1990 and 2005 whereas a middle level from 2005 to 2015. In addition, the ecological risk was slowly increasing in the range of research period. The spatial and temporal distribution of ecological risk was closely related to the intensity of land use and human activities; therefore, regional sustainable development could be realized by strengthening the integrated management of land and human activities and by promoting a synergistic effect among social, economic, and ecological protection activities.
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  • [1]
    GAO Yongnian, GAO Junfeng, XU Yan. Response of landscape ecological risk to land use change in level aquatic eco-functional regions in Taihu Lake Watershed[J]. J Nat Resour, 2010, 25(5):1088-1096.
    [2]
    WU Jiang. Landscape sustainability science:ecosystem services and human well-being in changing landscapes[J]. Landscape Ecol, 2013, 28(6):999-1023.
    [3]
    LIU Yinge. Ecological risk analysis based on land use in Shaanxi Province[J]. Bull Soil Water Conserv, 2011, 31(3):180-184.
    [4]
    ZHANG Yue, ZHANG Fei, ZHOU Mei, et al. Landscape ecological risk assessment and its spatio-temporal variations in Ebinur Lake region of inland arid area[J]. Chin J Appl Ecol, 2016, 27(1):233-242.
    [5]
    WU Li, HOU Xiyong, DI Xianghong. Assessment of regional ecological risk in coastal zone of Shandong Province[J]. Chin J Ecol, 2014, 33(1):214-220.
    [6]
    PAN Jinghu, LIU Xiao. Landscape ecological risk assessment and landscape security pattern optimization in Shule River Basin[J]. Chin J Ecol, 2016, 35(3):791-799.
    [7]
    ZHANG Xuebin, SHI Peiji, LUO Jun, et al. The ecological risk assessment of arid inland river basin at the landscape scale:a case study on Shiyang River Basin[J]. J Nat Resour, 2014, 29(3):410-417.
    [8]
    GONG Jie, XIE Yuchu, ZHAO Caixia, et al. Landscape ecological risk assessment and its spatiotemporal variation of the Bailongjiang watershed, Gansu[J]. China Environ Sci, 2014, 34(8):2153-2160.
    [9]
    HUANG Muyi, HE Xiang. Study on landscape pattern changes and driving forces of ecological risk in Chaohu lake basin[J]. Resour Environ Yangtza Basin, 2016, 25(5):743-750.
    [10]
    WANG Yan, LIU Yungen, LIANG Qibin, et al. Variation of Puzhehei lake area in dry season from 1977 to 2014[J]. Wetland Sci, 2016, 14(4):471-476.
    [11]
    WANG Shijie, ZHANG Xinbao, BAI Xiaoyong. An outline of karst geomorphology zoning in the karst areas of Southern China[J]. J Mt Sci, 2015, 33(6):641-648.
    [12]
    FAN Feide, WANG Kelin, XUAN Yong, et al. Eco-environmental sensitivity and its spatial distribution in karst regions, Southwest China[J]. Resour Environ Yangtza Basin, 2011, 20(11):1394-1399.
    [13]
    HUANG Muyi, HE Xiang. Landscape ecological risk assessment and its mechanism in Chaohu Basin during the past almost 20 years[J]. J Lake Sci, 2016, 28(4):785-793.
    [14]
    FENG Yuansong, YANG Qingyuan, QIU Conghao. A study of influence of landscape pattern evolution on river water quality in the Nanming River Basin[J]. Res Environ Sci, 2015, 28(12):1852-1861.
    [15]
    FORBES V E, CALOW P. Developing predictive systems models to address complexity and relevance for ecological risk assessment[J]. Integr Environ Assess Manage, 2013, 9(3):e75-e80.
    [16]
    MALEKMOHAMMADI B, BLOUCHI L R. Ecological risk assessment of wetland ecosystems using multi criteria decision making and geographic information system[J]. Ecol Indic, 2014, 41(1):133-144.
    [17]
    LI Weiping, CHEN Ahui, YU Linghong, et al. Pollutant influx from the main river (Kherlen River) of Lake Hulun in wet seasons, 2010-2014[J]. J Lake Sci, 2016, 28(2):281-286.
    [18]
    GUO Hong, GONG Wenfeng, DONG Jun, et al. RS-and-GIS-based analysis of variation of landscape of land desertification in the lower reaches of Nenjiang River[J]. J Ecol Rural Environ, 2009, 25(3):99-103.
    [19]
    DUAN Hanchen, WANG Tao, XUE Xian, et al. Spatial-temporal evolution of aeolian desertification and landscape pattern in Horqin sandy land:a case study of Naiman Banner in Inner Mongolia[J]. Acta Geogr Sin, 2012, 67(7):917-928.
    [20]
    WANG Juan, CUI Baoshan, LIU Jie, et al. The effect of land use and its change on ecological risk in the Lancang River Watershed of Yunnan Province at the landscape scale[J]. Acta Sci Circumst, 2008, 28(2):269-277.
    [21]
    LI Liqing, SHAN Baoqing, YIN Chenqing. Stormwater runoff pollution loads from an urban catchment with rainy climate in China[J]. Front Envion Sci Eng, 2012, 6(5):672-677.
    [22]
    PENG Jian, DANG Weixiong, LIU Yanxu, et al. Review on landscape ecological risk assessment[J]. Acta Geogr Sin, 2015, 70(4):664-677.
    [23]
    XIE Yuchu, GONG Jie, ZHAO Caixia. Evaluation of landscape ecological risk of soil and water erosion in the Bailongjiang watershed in Southern Gansu, China[J]. Chin J Ecol, 2014, 33(3):702-708.
    [24]
    WANG Yizhe, YAN Zhenguang, ZHANG Yahui, et al. Preliminary aquatic life criteria development and ecological risk assessment of ammonia in seven major basins in China[J]. Res Environ Sci, 2016, 29(1):77-83.
    [25]
    ZHANG Yazhou, XIE Xiaoping. Regional ecological risk assessment in Nansi Lake based on RS and GIS[J]. Acta Ecol Sin, 2015, 35(5):1371-1377.
    [26]
    HU Hebing, LIU Hongyu, HAO Jingfeng, et al. Influence of spatial difference on water quality in Jiuxiang River Watershed, Nanjing[J]. Environ Sci, 2012, 33(3):794-801.
    [27]
    LI Xianping, FENG Zhongke, YOU Xianxiang, et al. Remote sensing dynamic monitoring and driving force analysis county-cities expansion[J]. J Zhejiang A & F Univ, 2016, 33(5):798-806.
    [28]
    WANG Mengxi, TANG Fanglin, MA Guoqiang, et al. Exploration and thinking of returning pond to lake in wetland protection:a case study of Qiubei Puzhehei Wetland Project in Yunnan[J]. Wetland Sci, 2015, 11(1):32-35.
    [29]
    ZHANG Wei, CHEN Shurong, HOU Ping. Heavy metal contamination and potential ecological risk for sediments in the Puyang River Basin prior to and post dredging[J]. J Zhejiang A & F Univ, 2016, 33(1):33-41.
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Temporal and spatial evolution of landscape patterns and ecological risk in the Puzhehei Lake basin

doi: 10.11833/j.issn.2095-0756.2017.06.018

Abstract: To analyze temporal and spatial evolution for ecological risk and landscape patterns in a lake basin so as to further improve the ecological environment, Puzhehei Lake basin in Yunnan Province was studied over(1990, 1995, 2000, 2005, 2010, and 2015). Analysis included using the spatial analysis function of ArcGIS based on the landscape disturbance index and the landscape loss index to constructed a landscape ecological risk index. Results showed that:(1) For landscape patterns from 1990 to 2015, the degree of disturbance for agricultural land and woodlands was the most intense, while that of building land, gardens, and wetlands was slightly weaker, and that of unused land was the weakest with the interference degree index ranged from 0.208 7 to 0.218 0. In addition, the variation range of disturbance index for agricultural land was quite narrow (from 0.375 8 to 0.379 6), whereas that for construction land fluctuated largely with a changing rate of -14.10%. (2) For twenty years (from 2005 to 2015), the degree of landscape loss for different land-use varied markedly. The index of landscape loss for farmland and unused land was the largest with the values of 0.542 2 and 0.551 4, respectively, whereas that for wetland, construction land, and forest land take the second place, and that for garden land was the smallest (0.119 7). (3) From 1990 to 2015, the spatial distribution of ecological risk changed largely, and it showed a low level of ecological risk between 1990 and 2005 whereas a middle level from 2005 to 2015. In addition, the ecological risk was slowly increasing in the range of research period. The spatial and temporal distribution of ecological risk was closely related to the intensity of land use and human activities; therefore, regional sustainable development could be realized by strengthening the integrated management of land and human activities and by promoting a synergistic effect among social, economic, and ecological protection activities.

WEN Guojing, LIU Yungen, WANG Yan, HOU Lei, WANG Yanxia, GUO Yujing. Temporal and spatial evolution of landscape patterns and ecological risk in the Puzhehei Lake basin[J]. Journal of Zhejiang A&F University, 2017, 34(6): 1095-1103. doi: 10.11833/j.issn.2095-0756.2017.06.018
Citation: WEN Guojing, LIU Yungen, WANG Yan, HOU Lei, WANG Yanxia, GUO Yujing. Temporal and spatial evolution of landscape patterns and ecological risk in the Puzhehei Lake basin[J]. Journal of Zhejiang A&F University, 2017, 34(6): 1095-1103. doi: 10.11833/j.issn.2095-0756.2017.06.018
  • 景观生态风险评价是区域生态风险评价的主要内容[1],它对建立生态风险预警机制,降低生态风险概率,以及促进流域景观格局优化具有重要意义[2]。目前,生态系统评价主要以区域生态系统为主,主要涉及范围包括自然因素、人为干扰及流域等方面[3],张月等[4]、吴莉等[5]和潘竟虎等[6]对区域景观生态风险的研究表明:海岸带景观以低和较低等级生态风险区为主,与传统的区域生态风险评价相比,景观生态风险评价不仅关注生态环境整体的风险评价,也注重生态风险对整体景观格局破碎度、脆弱性以及多样性的影响。张学斌等[7]、巩杰等[8]和黄木易等[9]等对流域景观生态风险进行分析,结果表明:低生态风险向流域上游不断迁移,高生态风险逐渐向流域下游延伸,生态风险呈现增高趋势。也有部分学者分别对普者黑湖面积变化及旅游活动对水质的影响进行研究,表明湖泊面积缩减主要受人类活动影响,且旅游开发是造成总磷和总氮超标的主要原因[10]。以上研究结果在研究区域上缺乏对岩溶湖泊流域景观生态风险的分析并且从研究内容上缺乏对景观格局干扰指数与生态风险的关系分析及相应管理对策。普者黑湖流域地处滇东南岩溶高原的西北部,属于喀斯特湖泊湿地生态系统,是生态和环境变化敏感的区域之一,是湿地生态退化敏感区的典型代表[11]。近年来,在当地旅游业发展及生态系统自身脆弱性影响之下,普者黑湖流域景观格局及生态风险时空发生较大变化,生态环境遭到严重破坏,研究和解决普者黑湖流域生态环境问题刻不容缓。笔者以1990-2015年研究区的遥感影像数据为基础,从景观格局角度出发,运用景观格局指数及空间插值法对该流域景观格局和生态风险时空演变进行分析,从而揭示景观生态风险时空演变规律,以期为普者黑湖流域开发利用过程提供理论依据和技术参考。

  • 普者黑湖流域(24°05′~24°12′N,103°55′~104°13′E)位于云南省丘北县境内,距丘北县城约为11 km,流域面积为33.17×103 km2,地处珠江源头和长江、红河上游,是典型的岩溶地区。该流域的气候属于低纬度季风气候,具有终年温和湿润的中亚热带气候特征,多年平均气温为16.4 ℃,极端高温35.7 ℃,极端低温-7.6 ℃,7月气温高,1月气温低,多年平均降水量为1 206.8 mm。普者黑湖水质稳定达Ⅲ类标准。研究区特殊的水文地质条件在云贵高原湖泊湿地及西南部滇黔桂喀斯特地貌中都极具代表性,属于典型的生态敏感区。普者黑作为国家湿地公园(试点),主要景点有湖泊群、孤峰群和溶洞群,“十二五”期间累计接待游客1 041.60万人次,旅游综合收入达53.10亿元。

  • 本研究以卫星传感器TM(1990年,1995年,2000年,2005年和2010年)和陆地成像仪OLI(2015年)6期10月中旬遥感影像为数据源,在Erdas 19.0软件支持下,结合野外地面控制点调查和地形资料,对6期遥感影像进行几何校正、图形配准和拼接处理,并根据研究区范围大小进行裁剪,以Arc GIS 10.2和Fragstas 3.4为数据处理平台,空间分辨率统一为30 m,所选用的投影为WGS-1984-UTM-Zone-49N。在此基础上,根据普者黑的土地资源特征和景观变化差异以及影像数据的特点,基于光谱特征及地物纹理特征等信息,参考GB/T 21010-2007《土地利用现状分类》对6期影像进行手工分类和解译,将普者黑湖流域景观划分为林地、农地、湿地、建筑用地、园地、未利用地等6种类型。

  • 生态风险指数空间化可以解释生态风险空间特征及内在形成机制,对探究景观格局结构特征具有重要意义[11]。本研究基于前人[12]研究经验及风险方格划分方法,采用等间距系统采样法,将研究区按12 km × 12 km大小划分为83个风险方格,一个风险方格代表一个风险小区,以每个风险小区的综合生态风险指数作为其风险值。

  • 景观生态风险指数是区域生态安全状况的一个评价指数,可以反映流域内潜在的综合生态损失相对大小[7]。本研究以破碎度指数、分离度指数和优势度指数为自变量,建立生态风险指数计算模型。景观生态风险指数可以表示为:

    式(1)中:IER是生态风险指数,m为景观组分类型的数量,Akik个风险小区i类景观组分的面积,Ak为第k个风险小区总面积,Li是第i类风险小区的生态损失度,可由下式给出:

    式(2)中:Ei为景观干扰度指数,Fi为景观脆弱度指数。同时各参数的计算公式及生态学意义如表 1

    指数名称 意义 计算方法
    景观干扰度指数(Ei) 表示遭遇干扰时各类型景观所受到的生态损失的差别, 其自然属性损失的程度, 是某一景观类型的景观结构指数和脆弱度指数的综合 Ei=aCi+bNi+cDi
    景观破碎度指数(Ci) 指由于受到自然或人为因素干扰使景观由单一、均质和连续的整体趋向于复杂、异质或不连续的斑块镶嵌过程, 同时也是生物多样性丧失的重要原因之一 Ci=ni/Ai
    景观分离度指数(Ni) 指某一景观类型中不同斑块数个体分布的分离度 ${N_i} = \frac{A}{{2{A_i}}}\sqrt {\frac{{{n_i}}}{A}} $
    景观优势度指数(Di) 反映斑块在景观中占有的地位及其对景观格局形成和变化的影响 Di=(Ri+Mi)/4+Li/2
    景观脆弱度指数(Fi) 表示不同生态系统的易损失性, 生态系统的脆弱性与其在景观自然演替过程中所处的阶段有关 由专家咨询法且归一化获得
      说明:a为破碎度权重,b为分离度权重,c为优势度权重,且a+b+c=1。根据分析权衡,并结合前人[8-9]研究结果,得出脆弱度指数最为重要,其次为分离度指数和优势度指数,以上3种指数分别赋以0.5, 0.3和0.2的权值。ni为景观类型i的斑块数,Ai为景观类型i的总面积,A为景观总面积,Ri=斑块i出现的样方数/总样方数,Mi=斑块i的数目/斑块总数,Li-斑块i的面积/样方的总面积。

    Table 1.  Calculation methods of landscape pattern indices

  • 在流域各生态风险网格单元IER的范围[8-9]基础上采用下限排除法,对风险小区的生态风险指数进行自然断点区间间隔为0.079的等距划分为5个等级:0.002~<0.080为低生态风险,0.080~<0.160为较低生态风险,0.160~<0.239为中生态风险,0.239~<0.318为较高生态风险,≥0.318为高生态风险。

  • 流域生态风险指数作为一种空间变量,可以描述和识别景观格局的空间结构,对空间局部进行最优化插值。基于Arc GIS地统计学中的空间分析法,采用统计学中半方差方法对景观生态风险空间进行分析,从而进行理论半变异函数拟合。在此基础上,利用克里金插值法进行流域生态风险空间分析。具体计算公式:

    式(3)中:γ(h)为变异函数;Z(xi)和Z(xi+h)分别为景观生态风险指数在空间位置xixi+h处的值;N(h)为样本对数;h为空间距离。

  • 景观干扰度表示遭遇干扰时各类型景观所受到的生态损失程度,由景观破碎度指数、分离度指数和优势度指数计算得出。1990-2015年间,普者黑湖流域建筑用地、农地景观类型面积在不断增加,林地、湿地和未利用地景观类型面积在不断减少,不同土地利用类型的景观干扰演变特征差异较大,即农地和林地的干扰度较高,最大干扰度指数分别达到0.379 6和0.373 5,其次是园地、建筑用地和湿地最大干扰度指数分别为0.260 1,0.229 1和0.229 0,未利用地干扰度最小,其最大干扰指数仅为0.218 0;在各种土地利用类型变化中,农地干扰度波动较小,变化范围在0.375 8~0.379 6,建筑用地干扰度指数从0.267 4下降到0.229 7,变化率为-14.10%,波动最大。具体如表 2所示。

    土地类型 指数名称 1990-2015年景观结构指数值
    1990 1995 2000 2005 2010 2015
    农地 破碎度Ci 0.054 4 0.052 0 0.050 9 0.045 9 0.042 8 0.055 9
    分离度Ni 0.937 4 0.939 8 0.936 5 0.930 7 0.936 5 0.940 3
    优势度Di 0.373 5 0.374 2 0.373 4 0.380 3 0.377 2 0.380 3
    干扰度Ei 0.375 8 0.376 6 0.375 5 0.377 6 0.377 2 0.379 6
    林地 破碎度Ci 0.058 7 0.056 6 0.066 8 0.063 0 0.065 2 0.063 0
    分离度Ni 0.888 7 0.893 9 0.883 6 0.883 7 0.883 6 0.883 7
    优势度Di 0.339 2 0.338 3 0.346 2 0.355 7 0.353 4 0.355 7
    干扰度Ei 0.365 0 0.364 9 0.369 9 0.373 5 0.373 0 0.373 5
    建筑用地 破碎度Ci 0.165 7 0.143 1 0.163 1 0.089 1 0.079 3 0.089 1
    分离度Ni 0.882 5 0.844 6 0.853 7 0.857 1 0.853 7 0.859 8
    优势度Di 0.082 4 0.083 0 0.097 4 0.061 9 0.090 3 0.091 9
    干扰度Ei 0.267 4 0.253 4 0.268 4 0.229 1 0.224 7 0.229 7
    湿地 破碎度Ci 0.025 4 0.025 9 0.027 4 0.039 4 0.035 2 0.039 4
    分离度Ni 0.852 9 0.824 9 0.879 3 0.867 5 0.879 3 0.889 5
    优势度Di 0.092 1 0.090 8 0.089 9 0.083 8 0.090 9 0.083 8
    干扰度Ei 0.224 3 0.218 1 0.229 0 0.227 2 0.231 8 0.231 6
    园地 破碎度Ci 0.198 6 0.183 4 0.191 9 0.201 2 0.208 6 0.201 2
    分离度Ni 0.8146 0.884 7 0.825 0 0.816 6 0.825 0 0.806 0
    优势度Di 0.057 9 0.056 3 0.055 8 0.059 1 0.062 6 0.059 1
    干扰度Ei 0.251 4 0.260 1 0.250 5 0.253 2 0.258 9 0.251 1
    未利用地 破碎度Ci 0.006 8 0.006 7 0.006 0 0.013 2 0.016 0 0.013 2
    分离度Ni 0.927 9 0.927 1 0.931 0 0.938 5 0.931 0 0.891 9
    优势度Di 0.060 1 0.051 9 0.044 5 0.052 7 0.044 0 0.052 7
    干扰度Ei 0.217 7 0.213 4 0.210 2 0.218 0 0.213 0 0.208 7

    Table 2.  Weight evaluation of factors influencing the selection of tree species in urban green space by different participants

    表 2可知:普者黑湖流域景观干扰度演变特征:农地分离度和优势度分别从0.937 4和0.373 5上升到0.940 3和0.380 3,破碎度上升,景观干扰度增加,其作为研究区内的主要景观类型,且农地面积占研究区总面积的3/5,对景观格局的变化产生了重要影响;随着城镇化进程的推进,建筑用地景观破碎度、分离度和优势度均呈现先下降后上升的趋势。此外,由于受自然、社会和经济等人为因素的影响,加上建筑用地景观格局变化的机制相对复杂,破碎度变化最为激烈,变化率达到46.23%,干扰度指数显著增加;湿地破碎度和分离度在不断增加,优势度由0.092 1在缓慢减小到0.083 8,景观类型在区域上趋于集中分布,作为生态敏感性较强区域,湿地交错带的干扰度整体上在增加且达到0.227 2;而林地受人类活动影响较小,分离度范围仅介于0.883 7~0.888 7,但(林地)其在生态系统中具有重要作用[13-17],景观破碎化程度的加剧将会对流域生态系统的过程、功能及其所提供的生态服务功能产生显著的影响。另外,园地景观所占面积较少,仅占流域总面积的0.74%,景观干扰度指数变化不明显,受干扰性较小。

  • 景观生态损失度指数(Li)可以反映土地利用变化对生态环境造成的潜在生态损失和风险,其变化过程对生态环境的干扰和影响将体现在景观格局结构和功能变化上[18-20]。20 a来,普者黑湖流域不同土地利用景观损失度变化显著,农地和未利用地损失度较大,依次达到0.542 2和0.551 4,湿地、建筑用地和林地次之,园地损失度最小,仅为0.119 7,其中建筑用地损失度指数为0.437 5~0.509 4,变化率达到14.11%,变化趋势显著(P<0.05),对生态环境造成的潜在风险较大(图 1)。

    Figure 1.  Loss degree indices of landscape pattern of Puzhehei river basin

    图 1可知:建筑用地和未利用地景观损失度指数总体呈现减少趋势,湿地景观损失度则逐渐增加,当地住房建设逐步集中连片发展使得建筑用地损失度从0.509 4减小到0.437 5,景观生态风险趋于下降,但由于近年来当地大力发展旅游业导致生态系统受到破坏,湿地和农地景观损失度分别达到0.551 4和0.512 2,景观干扰程度增强,且湿地抗干扰性较弱,湿地和农地损失度逐渐增加趋势需要引起高度关注。景观损失度演化特点表现为农地作为研究区内所占比例较大的景观类型,景观损失度较大,但其变化幅度较小为0.99%,对生态环境造成的潜在风险依然较大。由于森林覆盖率上升及国家实施退耕还林政策,生态系统得到改善,林地景观损失度为0.347 6~0.355 7,趋于稳定状态。2000年以前建筑用地损失度较严重,从0.509 4上升到0.521 2,2005年后相应房屋建设措施的制定,景观损失度逐渐下降到0.437 5。湿地损失度变化与区域社会经济发展紧密相关,旅游人口的增加会加剧流域生态风险,为了保护湿地生态功能,2009年普者黑湖流域下游修建湿地公园,与1990-2010年这20 a间湿地损失度变化率3.37%相比,2010-2015年湿地损失度变化率大幅度减少,仅为0.11%。整体上,土地利用受到了政策驱动下的强烈人为活动干扰,普者黑湖流域景观生态潜在风险有所缓解。

  • 根据式(1)计算出1990-2015年普者黑湖流域划分的各风险小区景观生态风险指数(IER),如图 2所示:1990年生态风险指数值为0.002 8~0.314 2,1995年生态风险指数值介于0.001 9~0.321 5,2000年生态风险指数值介于0.001 8~0.324 2,2005年生态风险指数值介于0.002 1~0.336 6,2010年生态风险指数值介于0.002 5~0.339 6,2015年生态风险指数值介于0.002 7~0.351 4。从景观类型来看,农地和林地生态风险最大,园地生态风险最小;从景观生态风险最小值和最大值来看,2015年较1990年生态风险指数最小值在下降,最大值趋于上升,其中增加幅度较大,从1990年的0.314 2上升为2015年的0.351 4,增长11.84%,显示出较为明显的增长趋势。

    Figure 2.  Landscape ecological risk index of the Puzhehei river basin

    1990-2015年普者黑湖流域生态风险空间分布差异较大,主要体现在流域湖泊水域及水库周边,普者黑湖流域生态风险演变趋势与当地区域特征和社会经济发展基本符合[19-21],流域生态风险时空分布及差异如图 3所示。

    Figure 3.  Distribution map of landscape ecological risk level of the Puzhehei river basin

    图 3可以看出:在空间上,研究区生态风险空间分布规律在一定程度上体现了当地土地利用的特点,1990年和1995年流域生态风险主要集中在西南部,其中1990年流域生态风险面积分布较散乱,2005年生态风险有所改善,2010年和2015年流域生态风险差异变化不大。流域生态风险分布可分为3个阶段来描述:1990-2000年为第1阶段,该阶段普者黑湖流域生态风险主要集中在日者乡和八道哨乡,这些区域主要以耕地为主,人口较集中,生态风险高;2000-2005年为第2个阶段,流域生态风险面积分布较散乱,在此期间经济发展较领先,人口密度增大,村庄和水域区域生态风险较高,2004年丘北县实施退耕还林政策,开始大力造林,流域生态风险有所降低;第3阶段是2005-2015年,流域生态风险差异变化不大,2008年丘北县实施退塘还湖、退房还湖以及退村还湖工程,湖泊流域生态风险得到缓减,2009年在普者黑湖流域下游湿地公园的修建,游客大量增加,该区域生态风险较高。

    表 2所示:从时间变化上来看,1990-2000年普者黑湖流域主要表现为较低生态风险等级,所占面积比例为32.13%~43.99%,低生态风险面积由3 436.41 hm2减少到2 362.57 hm2,高生态风险面积由3 066.63 hm2增加到3 286.32 hm2;2000-2005年流域生态风险逐渐改善,高生态风险面积比例从9.91%急剧下降到0.95%,低生态风险面积比例由7.12%上升到15.29%,该时间段以较低生态风险等级为主;2005-2015年生态风险等级发生了较大变化,高生态风险面积和低生态风险面积分别增加了1 542.04 hm2和1 691.45 hm2,流域生态风险等级主要处于中生态风险等级。

    风险等级 1990 1995 2000 2005 2010 2015
    面积/hm2 比例/% 面积/hm2 比例/% 面积/hm2 比例/% 面积/hm2 比例/% 面积/hm2 比例/% 面积/hm2 比例/%
    低生态风险 3 436.41 10.36 1 575.45 4.75 2 362.57 7.12 5 071.97 15.29 4 538.34 13.68 6 763.42 20.39
    较低生态风险 10 656.76 32.13 12 839.04 38.71 14 589.66 43.99 12 444.00 37.52 9 917.62 29.9 6 162.09 18.58
    中生态风险 11 180.97 33.71 10 312.06 31.09 9 403.04 28.35 8 747.07 26.37 10 559.85 31.84 11 632.42 35.07
    较高生态风险 4 828.06 14.56 5 307.08 16.00 3 527.24 10.63 6 592.09 19.87 6 370.18 19.21 6 755.13 20.37
    高生态风险 3 066.63 9.25 3 135.21 9.45 3 286.32 9.91 313.73 0.95 1 782.84 5.38 1 855.77 5.59

    Table 3.  The areas of ecological risk grade of the Puzhehei river basin

  • 本研究通过对普者黑湖流域景观格局及生态风险时空演变规律进行分析,结果表明:研究区的景观干扰度指数发生了较大变化,农地和林地的干扰度较高,分别达到0.379 6和0.373 5,其次是建筑用地、园地和湿地干扰度,未利用地干扰度最小,干扰度指数仅为0.218 0,建筑用地干扰度指数波动较大,变化率达到-14.10%。此外,受到政策驱动下的人为活动干扰,建筑用地和湿地损失度有所改善,但由于研究区具有较大的景观干扰和损失,对生态环境造成较大的潜在风险,其中农地和未利用地损失度较大,依次达到0.542 2和0.551 4;1990-2015年普者黑湖流域景观生态风险等级由较低生态风险转化为中生态风险,生态风险在缓慢增加,高生态风险和较高生态风险区分别在日者乡和八道哨镇往水域周围扩散,主要分布在流域下游的国家湿地公园区域,流域较低生态风险区面积由32.13%下降到18.58%,中生态风险区面积从33.71%上升到35.07%。

    1990-2015年普者黑湖流域景观生态风险的时空分布呈现出以下趋势:高生态风险和较高生态风险区空间差异较大,由西北、西南部向东北部延伸,且主要分布在人口集中及生态脆弱性较高的地区,湖泊水周围及水库周边是高生态风险和较高生态风险的主要受体;而大多数林地及部分农地等景观类型主要属于低生态风险区或较低生态风险区。随着普者黑国家湿地公园的修建,旅游业带动当地社会经济显著增加[22-28]。相关研究表明普者黑湖流域中的湖泊面积减少收到人类活动干扰,且与当地国内生产总值和农地生产总值增长呈现显著负相关[29],而发展旅游业带来社会经济增长的同时,对各景观类型产生了强烈干扰,其次湖泊和湿地生态系统功能退化,外加岩溶地貌属于生态敏感区,加剧了流域景观生态风险恶化的趋势。

  • 基于普者黑湖流域景观生态风险空间分布特征,针对不同风险等级的区域具体实施相应的对策措施如下:①高风险区和较高风险区的管理对策。高风险和较高风险区主要分布在流域的西南部,以及人口较集中的乡镇和旅游区,这些区域主要以耕地为主,人口较集中,生态脆弱性高。该类区域应采取的措施是合理规划土地利用,禁止大规模、无序地开垦土地,有效控制人类活动,应严格依照国家自然保护区条例,不在核心区和缓冲区内修建房屋及开展旅游活动,同时可对旅游人口集中的地方采取游客分流,制定生态重建标准,提高生态系统调控能力。②中风险区的管理对策。中风险区主要分布在较高风险区的外围及林地和水库景观类型中,人类活动的干扰相对较弱。为了降低未来生态风险及其危害,在该区域内应本着因地制宜,合理规划和建设生产活动,实施退耕还林,加强生态环境治理;此外,对于位于流域中部的低风险区和较低风险区,由于处于平地与山地的交界处,这一区域人类活动较少,林地面积较广,植被覆盖度较高,但这些区域一旦遭到破坏,其恢复难度较大。植被破坏会引发滑坡泥石流等自然灾害,加之该区域的地势陡峭特点,开垦耕地及发展旅游业存在一定难度。需要针对研究区的特点因地制宜采取相应措施。因此,应加强该区域的保护力度,合理配置土地资源使用,促进多种经济经营发展,既考虑增加农民收入又要考虑生态环境保护,同时还要兼顾生态风险等级的降低和危害。

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