Volume 39 Issue 5
Sep.  2022
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ZHU Ying, GU Chunwang, LI Xin, ZHOU Tingting, FENG Yuqing. Evaluation of wetland ecological security in Wujiang District of Suzhou based on DPSIRM model[J]. Journal of Zhejiang A&F University, 2022, 39(5): 1114-1123. doi: 10.11833/j.issn.2095-0756.20210758
Citation: ZHU Ying, GU Chunwang, LI Xin, ZHOU Tingting, FENG Yuqing. Evaluation of wetland ecological security in Wujiang District of Suzhou based on DPSIRM model[J]. Journal of Zhejiang A&F University, 2022, 39(5): 1114-1123. doi: 10.11833/j.issn.2095-0756.20210758

Evaluation of wetland ecological security in Wujiang District of Suzhou based on DPSIRM model

doi: 10.11833/j.issn.2095-0756.20210758
  • Received Date: 2021-11-23
  • Accepted Date: 2022-05-23
  • Rev Recd Date: 2022-04-25
  • Available Online: 2022-09-22
  • Publish Date: 2022-10-20
  •   Objective  This study is aimed to conduct a scientific evaluation of wetland ecological security in water network area so as to provide basis for regional ecological security and high-quality development.   Method  With Wujiang District of Suzhou as the research object, on the basis of the threats faced by the wetland in the water network area in the process of urban development, first, an evaluation index system was constructed employing the DPSIRM model (driving-force-pressure-stae-impact-response-management) after which the combined weighting method was used to give the index weight; then some indexes were spatially quantified in combination with Geographic Information System (GIS) grid technology; finally, the comprehensive evaluation method was adopted to evaluate the wetland ecological security of Wujiang District from 2012 to 2020.   Result  In 2012, 2016 and 2020, the ecological security values of wetlands in Wujiang District were 0.394 4, 0.455 2 and 0.516 4 respectively, which evolved from low security and medium security to high security. The high value areas in each period were mainly concentrated along the coast of Taihu Lake, Zhenze area, Beimayang area, Tongli Lake area, Sanbaidang area and Yuandang area. Based on the analysis of DPSIRM model, the safety value of management, impact and driving force subsystem had increased significantly, that of the pressure subsystem had decreased, whereas that of the state and response subsystem had first decreased and then increased.   Conclusion  During the study period, the ecological security values of wetlands in Wujiang District showed an overall upward state. However, in the future ecological protection of wetlands, devoted efforts should be made to the regulate pressure indicators, strengthen the control of areas with low ecological security level, and maintain high-intensity management measures. [Ch, 8 fig. 1 tab. 31 ref.]
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Evaluation of wetland ecological security in Wujiang District of Suzhou based on DPSIRM model

doi: 10.11833/j.issn.2095-0756.20210758

Abstract:   Objective  This study is aimed to conduct a scientific evaluation of wetland ecological security in water network area so as to provide basis for regional ecological security and high-quality development.   Method  With Wujiang District of Suzhou as the research object, on the basis of the threats faced by the wetland in the water network area in the process of urban development, first, an evaluation index system was constructed employing the DPSIRM model (driving-force-pressure-stae-impact-response-management) after which the combined weighting method was used to give the index weight; then some indexes were spatially quantified in combination with Geographic Information System (GIS) grid technology; finally, the comprehensive evaluation method was adopted to evaluate the wetland ecological security of Wujiang District from 2012 to 2020.   Result  In 2012, 2016 and 2020, the ecological security values of wetlands in Wujiang District were 0.394 4, 0.455 2 and 0.516 4 respectively, which evolved from low security and medium security to high security. The high value areas in each period were mainly concentrated along the coast of Taihu Lake, Zhenze area, Beimayang area, Tongli Lake area, Sanbaidang area and Yuandang area. Based on the analysis of DPSIRM model, the safety value of management, impact and driving force subsystem had increased significantly, that of the pressure subsystem had decreased, whereas that of the state and response subsystem had first decreased and then increased.   Conclusion  During the study period, the ecological security values of wetlands in Wujiang District showed an overall upward state. However, in the future ecological protection of wetlands, devoted efforts should be made to the regulate pressure indicators, strengthen the control of areas with low ecological security level, and maintain high-intensity management measures. [Ch, 8 fig. 1 tab. 31 ref.]

ZHU Ying, GU Chunwang, LI Xin, ZHOU Tingting, FENG Yuqing. Evaluation of wetland ecological security in Wujiang District of Suzhou based on DPSIRM model[J]. Journal of Zhejiang A&F University, 2022, 39(5): 1114-1123. doi: 10.11833/j.issn.2095-0756.20210758
Citation: ZHU Ying, GU Chunwang, LI Xin, ZHOU Tingting, FENG Yuqing. Evaluation of wetland ecological security in Wujiang District of Suzhou based on DPSIRM model[J]. Journal of Zhejiang A&F University, 2022, 39(5): 1114-1123. doi: 10.11833/j.issn.2095-0756.20210758
  • 湿地是水网地区最重要的生态资源,湿地的生态安全关系着地区生态健康与可持续发展。在高强度的城镇建设、农业发展、水运开发过程中,湿地往往成为各类建设用地的来源[1],结果给地区内湿地造成特殊的生态风险[2-3]。由此,对湿地进行生态安全评价,不仅可以反映湿地生态质量状况,还能够为湿地保护政策制定提供量化支撑,促进地区生态安全建设[4]。目前,关于湿地生态安全的研究以区域安全状况评价、发展预测以及影响因素探究等方面研究居多,主要运用综合指数法[5]、生态足迹法[6]、景观格局指数[7]、生境质量模型[7]等方法对湿地生态安全进行评价分析,以及通过灰色关联模型[8]、景观模拟演化[9]等对安全趋势进行影响因素探究和模拟预测。相关研究主要以区域或行政区单元生态安全为对象进行评价,对湿地生态安全的空间分异化研究相对缺乏,且针对湿地生态安全的研究多集中于干旱区[5]、高原[10]、滨海[11]等地域特色鲜明区域,对湿地资源丰富的水网地区生态安全评价指导有待提升。长江三角洲是中国水网最密集、社会经济发展最快的地区之一。2018年,长江三角洲一体化发展上升为国家战略,苏州市吴江区是长江三角洲区域一体化发展示范区之一,在高质量发展的背景下面临湿地生态系统优先保护的压力[12]。本研究以吴江区为例,构建基于驱动力-压力-状态-影响-响应-管理(DPSIRM)模型的湿地生态安全评价指标体系,突出水网地区人与环境之间的相互关系,通过地理信息系统(GIS)格网技术将生态安全值进行空间量化,探析吴江区湿地生态安全状况,以期为吴江区湿地生态保护管理提供依据。

    • 吴江区位于苏州市最南部,是苏州主城区面积最大的板块,东接上海市青浦区,南连浙江省嘉兴市,西临太湖,北靠苏州市吴中区。吴江区既是苏、浙、沪两省一市的地理交界处,又是长江三角洲区域一体化发展国家战略的中心区域,具有重要的地理、经济、生态地位。吴江区总面积为1 176.68 km2,下辖7个乡镇和4个街道(本研究为方便数据统计,按照2012年下辖的8个乡镇进行分析),2020年常住人口131.26万,城镇化率超过70%。吴江区内河道纵横交错,湖泊星罗棋布,湿地总面积(保有量)为431.09 km²,占全区总面积的36.64%,自然湿地保护率达71.10%。吴江区湿地分布见图1

      Figure 1.  Distribution map of wetland in Wujiang District

    • 本研究数据包括以下3类:①土地利用/覆被类型数据。通过2012、2016、2020年SPOT-5遥感卫星影像经ENVI 5.3解译获取,借助ArcGIS 10.8和Fragstats 4.2处理获得景观格局指数。②社会统计数据、资源调查数据和环境保护规划数据。来源于《吴江年鉴(2013—2020年)》《苏州市湿地保护年报(2015—2020年)》《苏州市水土保持规划(2016—2030年)》《苏州市鸟类物种调查与统计(2012—2020年)》《吴江区湿地保护规划(2018—2030年)》等。③其他数据。年度归一化植被指数来自资源环境科学与数据中心(https://www.resdc.cn),路网数据来自开放街道地图OpenStreetMap平台(https://www.openstreetmap.org)。

    • DPSIRM模型是基于压力-状态-响应(PSR)模型演变而来,是一种被广泛运用于环境质量评价中,生态系统健康评价的因果关系模型[13]。框架内各子系统具体含义参照王欣等[14]的相关研究,针对湿地生态系统对模型各子系统进行如下界定:①“驱动力”是驱使湿地生态系统自然演替或退化的根本因素和原始动力,分为自然和社会2个方面;②“压力”可理解为驱动力作用于湿地生态系统,对湿地资源产生的需求和作用,表现为征占湿地、用水需求、污染排放等;③“状态”即湿地生态系统在压力作用下所发生的最直接变化,包括湿地生态系统的物理化学特征和景观状态特征;④“影响”为湿地生态系统状态发生改变之后对人类生存发展产生的影响;⑤“响应”和“管理”都是湿地生态系统中的人类社会在感应到系统影响之后采取的各种弥补及治理措施,有所区别的是响应指标代表生态系统受到安全威胁后较为被动的补救性举措,管理指标是人类为了提升系统的安全性,通过法律、政策,提高人类社会生态保护意识,进行全过程的管理措施,更能体现人在湿地生态安全过程中的主观能动性。这6个因子具有因果作用关系,它们共同表达着影响湿地生态安全的信息耦合关系。

    • 根据DPSIRM框架模型,参考相关研究[15-16]和吴江区湿地实际状况,遵循指标数据的代表性、独立性、易获得性、可操作性和系统性原则[17],从驱动力、压力、状态、影响、响应和管理6个方面建立了吴江区湿地生态安全评价指标体系(表1)。

      目标层准则层指标层正负性数据来源综合权重
      湿地生态安全 驱动力 人口密度/(人·km−2) 各镇人口/镇域面积 0.022 5
      国内生产总值(GDP)/万元 + 《吴江年鉴(2013—2021年)》 0.018 9
      城市化水平/% 各镇非农业人口/各镇总人口 0.030 7
      降水/m3 + 《吴江年鉴(2013—2021年)》 0.019 1
      压力 区域开发指数/% (建设用地面积+耕地面积)/国土面积 0.035 1
      万元GDP耗水量/(t·万元−1) 《吴江年鉴(2013—2021年)》 0.016 4
      公路密度/% 公路面积/国土面积 0.020 4
      航道密度/% 航道等级缓冲区分析 0.017 5
      农药、化肥施用强度/t 《吴江年鉴(2013—2021年)》 0.027 3
      企业生产污水排放/t 苏州市重点排污企业名单 0.030 3
      城镇生活污水排放/t 《吴江年鉴(2013—2021年)》 0.029 6
      状态 水域面积占比/% + 水域面积/国土面积 0.035 6
      水环境质量/% + 吴江区重要断面水环境质量状况 0.038 5
      水土流失等级/% 《苏州市水土保持规划》 0.035 6
      植被覆盖度/% + 资源环境科学与数据中心 0.019 5
      景观结构指数/% 景观破碎度、分离度和分维数加权函数式[21] 0.022 5
      湿地连通性指数*/% + 景观形态空间格局分析(MSPA)结合Conefor2.6[22] 0.036 4
      生境质量/% + 生境质量(Invest)模型[23] 0.022 3
      影响 人均水资源量/(m3·人−1) + 《吴江年鉴(2013—2021年)》 0.030 8
      农业产值占比/% + 0.027 6
      环境调节服务/% + 生态系统服务价值计算[24] 0.034 6
      鸟类多样性*/种 + 《苏州市鸟类物种调查与统计》 0.042 1
      响应 污水处理率/% + 《吴江年鉴(2013—2021年)》 0.026 3
      无害化垃圾处理率/% + 0.023 3
      水功能区达标率/% + 0.034 3
      河道治理/% + 0.040 6
      地区生产总值能耗下降比率/% + 0.023 7
      查处环境违法案件数/件 + 0.030 4
      管理 湿地保护等级*/% + 《苏州市湿地保护年报(2015—2020年)》 0.043 6
      自然湿地保护率*/% + 0.037 8
      湿地执法巡查次数 + 《吴江年鉴(2013—2021年)》 0.026 7
      退渔还湖及池塘标准化改造* + 0.020 4
      高标准农田建设 + 0.028 4
      湿地科普宣教情况*/万元 + 《苏州市湿地保护年报(2015—2020年)》 0.049 1
      环保投资占GDP比重/% + 《吴江年鉴(2013—2021年)》 0.047 9
        说明:*表示反映吴江区湿地特质的指标。+表示对湿地生态安全起促进作用;−表示对湿地生态安全起抑制作用

      Table 1.  Evaluation index system and meaning of wetland ecological security in Wujiang District

    • 组合赋权法是将专家理论知识和丰富经验的主观赋权法与充分挖掘数据组合信息的客观赋权法相结合的赋权方法,可以减少系统误差和随机误差[18]。本研究分别通过yahhp1.03和Excel计算层次分析法和熵权法的结果,选择将两者结果相结合,综合考虑主客观因素的指标权重。

    • 结合相关研究[19],充分考虑研究区面积和范围特征,本研究确定基础网格的尺度为1 km×1 km。通过空间插值和数据链接方法将各指标数据链接至各格网,采用综合评价法对研究区各格网的湿地生态安全状况进行计算:

      其中:CEI表示某时段各格网区域的综合湿地生态安全值,Pi为第i个指标的标准化值,Wi为第i个指标的综合权重,n为评价指标的个数。根据相关研究[20],将研究区湿地生态安全等级划为5级,即高度安全(CEI>0.8)、较高安全(0.8≥CEI0.6)、中等安全(0.6≥CEI>0.4)、低度安全(0.4≥CEI>0.2)、不安全(CEI≤0.2)。通过综合评价法计算研究区各格网湿地生态安全值,并在ArcGIS中通过空间插值法绘制吴江区湿地生态安全定量空间分布图。

    • 吴江区2012、2016和2020年湿地生态安全指数平均值分别为0.394 4、0.455 2和0.516 4,湿地生态安全指数逐步攀升,增长较为平稳,说明吴江区的湿地生态状况呈现稳步提升的趋势。湿地生态安全指数极值区域分布基本一致(图2),高值区域主要位于吴江区东部沿太湖区,包括中部偏南的震泽-雪落漾-长漾片区、北麻漾-庄西漾片区、东北部同里湖-九里湖-沐庄湖片区以及东部的三白荡、元荡片区。上述区域湿地保护安全等级高,湿地斑块面积较大,水面开阔,河网密布,支流众多,连通性较好,有利于水体之间的水文交换,同时远离建设区域,污染排放影响较小。低值区域分布于同里镇、太湖新城镇、黎里镇和桃源镇建设用地密集区域,湿地面积较小,城市开发、污染排放等对湿地造成的压力较大,故相对湿地密集区域而言安全值较低。

      Figure 2.  Evaluation value of wetland ecological security in Wujiang District in 2012, 2016 and 2020

    • 图3可知:驱动力子系统安全值由0.032 8增长至0.050 1,呈逐年升高的趋势,增长幅度平缓,说明驱动力子系统总体情况稳中向好。2012年驱动力安全值较高的区域集中于同里镇、盛泽镇和平望镇,2016年安全值高值区域主要位于平望镇、七都镇、震泽镇和桃源镇,2020年安全值高值分布与2016年分布相仿,原因在于上述几镇人口总数略有减少,对环境的压力有所降低,而由于吴江经济开发区的高速发展,使得同里镇的城市化快速提升,农业人口占比降低26%,GDP增长近7倍,同时也伴随着人口的急剧增长,仅2012—2016年,同里镇总人口数由4.3万增至10.4万,使得其驱动力安全值提升幅度相对较低。

      Figure 3.  Spatial distribution of safety value of driving force subsystem

    • 图4可知:压力子系统安全值由0.125 3降低至0.103 4,说明近年来湿地生态系统受人为扰动压力逐渐升高,对地区生态安全造成了压力。城市扩张以及生活、生产污水排放等问题给湿地生态安全带来一定的压力。2012—2020年,吴江区建设用地面积占比增加了10%,城镇生活污水排放年均增长150万 t,市重点排污企业增长50余家。但另一方面,生态农业的推广使得农药、化肥的施用量分别减少了128和3 438 t,减轻了对湿地生态系统的干扰。压力安全值较高的区域主要位于开发程度较低的区域,如沿太湖区、震泽镇、桃源镇湖荡区域、同里湖、白蚬湖、三白荡及元荡片区、北麻漾片区,而城区、乡村、路网密布、航运发达等区域压力安全值较低。从整体看来,高值区域分布未发生明显改变,但随着城市扩张的影响,高值区域面积有所减少。

      Figure 4.  Spatial distribution of safety value of pressure subsystem

    • 图5可知:状态子系统安全值由0.092 2降至0.089 7,经历了先降低后升高的变化过程。该变化趋势反映了在负面影响和正向提升的双重作用下,湿地状态整体上有所下降,但2016—2020年有好转的趋势。原因在于,虽然湿地受到城市扩张的侵占,部分地区湿地的连通性受阻,景观破碎化加剧,但由于整体水环境质量有所好转,水质综合污染指数由0.64降低至0.59,导致状态子系统变化幅度较小。状态子系统安全值的高低值分布与水域空间分布关系紧密,高值分布区主要为水域周边,建设区安全值较低;此外,由于水质较好、景观结构较为稳定,故盛泽镇状态安全值相对较高,而震泽、北麻漾片区、太浦河沿岸、同里湖、白蚬湖、元荡、三白荡片区的湿地连通性较高导致区域内状态安全值较高。

      Figure 5.  Spatial distribution of safety value of state subsystem

    • 图6可知:影响子系统安全值由0.026 0升高至0.074 9,呈明显升高趋势。影响子系统反映了湿地生态系统的扰动与人类活动之间的紧密联系,湿地生态系统的变化影响着人们的生产生活,反映从自然生态系统获益情况。3个时段,影响子系统安全值的极值区域分布大致相同,高值区域集中在吴江区沿太湖区域、西南与东北之间的湖荡群区域。从镇域分布上看,震泽镇的影响子系统安全值较高,得益于农业产值占比相较于其他镇处于较高水平,震泽镇农业产值占生产总值比例约10%,而其他镇的农业产值占比仅5%。低值区域集中在太湖新城和同里镇、盛泽镇的城区附近,主要是受生态系统服务价值的影响,沿太湖和湖荡片区的湿地区域所创造的环境调节服务价值较高,因此成为了影响子系统的高值分布区。总体上,建设用地的扩张使得城区生态系统服务价值降低,进一步导致高值区域呈现减少趋势,但由于受到鸟类物种多样性和人均水资源量提升等影响,总体系统安全值呈现升高趋势。

      Figure 6.  Spatial distribution of safety value of affected subsystem

    • 图7可知:响应子系统安全值由0.081 5提升至0.085 7,总体变化幅度较小。2012—2016年安全值有所下降,即当地对于湿地状态变化响应有所减弱,原因为河道疏浚距离以及地区生产总值能耗下降比率的减少,2016—2020年安全值有所提升,主要得益于无害化垃圾处理率、查处环境违法案件数以及水功能区达标率的提升,其中无害化垃圾处理率提升22%,环境违法案件查处数量增加380余件,水功能达标率提升25%。空间分布上,3个时段的响应子系统安全值空间分布情况一致,受污水处理能力的影响较大,低值区域分布在太湖新城西南部和黎里镇北部,其余区域为高值区域,因为吴江芦墟、盛泽桥北、七都、盛泽以及汾湖南部几座污水处理厂相较于其余处理厂对周边的污水处理能力相对较弱。

      Figure 7.  Spatial distribution of safety value of response subsystem

    • 图8可知:管理子系统安全值在所研究时段内由0.036 6升高至0.112 6,增长幅度明显。管理子系统的变化反映了吴江区对湿地的保护管理工作日益加强,着重体现在湿地保护率的提升、环保投入增加、生态农业的推广以及湿地公园的科普宣教等。其中,随着湿地保护管理制度的完善,吴江区自然湿地保护率提升了49%,越来越多的湿地被纳入保护管理区域,形成了湿地公园-湿地保护小区-水源地保护小区-水产种质资源保护区多类型、省级重要湿地-市级重要湿地-一般湿地多层级的保护体系;当地政府更加重视生态文明的建设,环保投入占GDP比例增长了1.2%,不断推进鱼塘标准化改造、高标准农田建设和重点湿地公园科普宣教课程研发推广,湿地管理工作成效提升明显。空间分布上,受湿地保护等级的影响,管理子系统安全值呈现一定的空间分异规律。高值区域大多集中在省级重要湿地,如太湖、震泽湿地公园周边和同里湿地公园,其次为市级重要湿地及其周边,一般湿地和非湿地区域次之。总体看来,管理子系统增长趋势相对于其他系统最为明显,增长幅度最高。

      Figure 8.  spatial distribution of safety value of management subsystem

    • 吴江湿地生态高安全值的空间分布,与戈弋[25]研究的吴江高敏感区域分布相似,生态安全格局的核心源地区域的空间分布与陈琪[26]的研究相符。此外,杜健[27]从景观生态风险的角度对于吴江区开展了相应的评价,表明2012—2016年吴江区的演变趋势与本研究结果存在差异,可能是研究方法及数据的差异性所致。杜健[27]采用景观格局指数法进行景观生态风险分析,这种方法是以自然因素相关数据为基础,社会经济类因素涉及不多,故2种研究结论不同。吴江区湿地在景观格局上确实存在日渐破碎化趋势,导致景观生态风险日趋严重,但是在综合自然、经济、社会等多系统指标后,湿地生态安全更加侧重于全面反映湿地生态系统面临的多重威胁与应对挑战的能力,因此,在综合因素影响下区域湿地生态安全呈现逐渐好转的趋势,这与崔馨月等[28]的研究结果相似。此外,本研究中,湿地管理对生态安全的贡献逐渐占据较为重要的地位,这也与秦趣等[10]的研究结果相同。

      目前针对湿地生态安全的评价,以PSR[29]、驱动力-压力-状态-影响-响应(DPSIR)模型[30]为依据构建评价指标体系的研究居多,在湿地管理重要性日渐提升的背景下,将改进后的DPSIRM框架模型应用于湿地生态安全评价研究中,有利于更全面系统地分析湿地生态安全发生变化的全过程[13]。其次,通过GIS格网方法将评价指标数据进行空间量化,能够较为直观地反映湿地生态安全空间差异和演变特征,有利于管理者针对性地对区域采取相应措施[31]。最后,本研究对于格网尺度的选择主要借鉴以往学者的经验,尚未考虑到格网尺度差异对安全值大小分布的影响,未来的研究可进一步探寻生态安全值的尺度效应。

    • 2012—2020年,研究区湿地生态安全综合指数由0.394 4提升至0.516 4,呈明显提升趋势。空间分布上,各时期的高低值分布区域发生较大变化,高值区域集中于吴江区东部的沿太湖片区、中部的震泽片区、北麻漾片区、东北部的元荡片区、三白荡片区以及同里湖片区,低值区域集中分布于同里镇、太湖新城镇、黎里镇和桃源镇建设用地密集区域。从影响湿地生态安全的6个子系统分析来看,管理、影响、驱动力子系统安全值提升相对显著,压力子系统安全值有所降低,而状态和响应子系统安全值呈现波动上升趋势。因此,在未来的湿地保护管理工作中,应当注重加强对湿地面临的压力因素的调节,降低经济发展对湿地的影响,关注生态安全较低等级的区域,着力提升防范生态风险的能力。

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