Article(id=1241116643384938829, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1241116641321350143, articleNumber=null, orderNo=null, doi=null, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1723132800000, receivedDateStr=2024-08-09, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773834866615, onlineDateStr=2026-03-18, pubDate=1742400000000, pubDateStr=2025-03-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773834866615, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773834866615, creator=13701087609, updateTime=1773834866615, updator=13701087609, issue=Issue{id=1241116641321350143, tenantId=1146029695717560320, journalId=1234093305789726721, year='2025', volume='45', issue='3', pageStart='1185', pageEnd='1776', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773834866123, creator=13701087609, updateTime=1773881366030, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241311676130193619, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1241116641321350143, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241311676130193620, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1241116641321350143, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1587, endPage=1600, ext={EN=ArticleExt(id=1241116645003940182, articleId=1241116643384938829, tenantId=1146029695717560320, journalId=1234093305789726721, language=EN, title=Regional prioritization of territorial spatial ecological restoration based on ecological degradation riskA case study of the Shandong Section of the Yellow River Basin., columnId=1234106388083954308, journalTitle=China Environmental Science, columnName=Environmental Ecology, runingTitle=null, highlight=null, articleAbstract=

Ecological restoration of territorial space is a critical measure for advancing the construction of ecological civilization. Precise identification of areas requiring ecological restoration and rational delineation of restoration priorities are fundamental prerequisites for the scientific and orderly promotion of territorial ecological restoration. This paper selected the Shandong Section of the Yellow River Basin as the research area and quantitatively evaluated the risk of ecosystem degradation using the "ecological resilience and human disturbance" framework. An ecological security pattern was constructed through Morphological Spatial Pattern Analysis(MSPA), landscape connectivity assessment, and circuit theory models, identifying key ecological factors such as source areas, corridors, pinch points, and barrier points. By overlaying these factors with ecological degradation risks, the priority levels of restoration areas were determined, and corresponding restoration strategies were formulated. The results indicated that the overall risk of ecological degradation in the study area was high, with high-risk areas exhibiting a zonal radiation distribution centered around each city. The influence of rapid urbanization and the expansion of transportation networks on ecological degradation cannot be overlooked. A total of 27 ecological sources, 71 ecological corridors, 71 ecological pinch points, and 51 ecological barrier points were identified as ecological restoration areas. Overlapping ecological degradation risks, ecological restoration areas were divided into priority restoration, general restoration and ecological conservation, and restoration strategies were proposed in conjunction with the characteristics of different ecological elements and their priority order.

, correspAuthors=Yong YANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Jin-hua LIU, Yong-xing ZHENG, Wei LI, Yong YANG), CN=ArticleExt(id=1241116656466972688, articleId=1241116643384938829, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=基于生态退化风险的国土空间生态修复区域优先序划定——以黄河流域山东段为例, columnId=1234106388268503686, journalTitle=中国环境科学, columnName=环境生态, runingTitle=null, highlight=null, articleAbstract=

国土空间生态修复是落实生态文明建设的重要举措,精准识别生态修复区域以及合理划定修复的优先序,是科学有序推进国土空间生态修复的前提,因此,本文以黄河流域山东段为研究区,通过“生态韧性-人类干扰”定量评估生态系统退化风险,采用形态学空间格局分析(MSPA)、景观连通性评价和电路理论模型等方法构建生态安全格局,识别生态源地、廊道、夹点、障碍点等生态要素作为生态修复区域,叠加退化风险等级对修复区域进行优先序划定,并提出相应修复策略.结果表明:研究区总体生态退化风险较高,高退化风险区以各城市为中心呈带状辐射分布,快速城镇化以及交通网络的发展对生态退化的影响不容忽视;识别生态修复区域,包括27个生态源地、71条生态廊道、71处生态夹点和51处生态障碍点;叠加生态退化风险,将生态修复区域划分为优先修复、一般修复以及生态保育三类,并结合不同生态要素特征以及优先序提出修复策略.

, correspAuthors=杨勇, authorNote=null, correspAuthorsNote=
* 责任作者,高级经济师,
, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=yE1L0MgvmdUaKPxvAJuuDQ==, magXml=4PSnMT0jXnSgopK4z3akWA==, pdfUrl=null, pdf=kOvQPqrcbEfFrU4LHEmqyw==, pdfFileSize=4479517, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=5IZ+QFuwdlTNraFI8Rry0w==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=hZvoWchs22z+TMW6yrFAmA==, mapNumber=null, authorCompany=null, fund=null, authors=

刘金花(1979-),女,山东潍坊人,教授,博士,主要从事国土空间规划与评价、土地信息建模研究.发表论文20余篇..

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刘金花(1979-),女,山东潍坊人,教授,博士,主要从事国土空间规划与评价、土地信息建模研究.发表论文20余篇..

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刘金花(1979-),女,山东潍坊人,教授,博士,主要从事国土空间规划与评价、土地信息建模研究.发表论文20余篇..

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Journal of Central South University of Forestry & Technology202444(2):98-107., articleTitle=Construction of Lushan ecological network based on MSPA and MCR model, refAbstract=null), Reference(id=1241116681918009988, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116643384938829, doi=null, pmid=null, pmcid=null, year=2023, volume=43, issue=4, pageStart=1824, pageEnd=1833, url=null, language=null, rfNumber=[40], rfOrder=66, authorNames=杨帅琦, 何文, 王金叶, journalName=中国环境科学, refType=null, unstructuredReference=杨帅琦,何文,王金叶,等. 基于MCR模型的漓江流域生态安全格局构建 [J]. 中国环境科学202343(4):1824-1833., articleTitle=基于MCR模型的漓江流域生态安全格局构建, refAbstract=null), Reference(id=1241116681997701771, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116643384938829, doi=null, pmid=null, pmcid=null, year=2023, volume=43, issue=4, pageStart=1824, pageEnd=1833, url=null, language=null, rfNumber=[40], rfOrder=67, authorNames=Yang S Q, He W, Wang J Y, journalName=China Environmental Science, refType=null, unstructuredReference=Yang S QHe WWang J Y,et al. Ecological security pattern construction in Lijiang River basin based on MCR model [J]. 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Data information table

, figureFileSmall=null, figureFileBig=null, tableContent=
数据用途来源
土地利用数据适应力计算、恢复力计算、人类干扰指数计算、生态源地识别、阻力面构建中国科学院资源环境科学数据中心(https://www.resdc.cn)
道路数据阻力面构建、人类干扰指数计算中国科学院资源环境科学数据中心(https://www.resdc.cn)
人口密度数据人类干扰指数计算中国科学院资源环境科学数据中心(https://www.resdc.cn)
夜间灯光数据人类干扰指数计算中国科学院资源环境科学数据中心(https://www.resdc.cn)
NPP数据抵抗力计算EarthData官网(https://www.earthdata.nasa.gov)
气象数据抵抗力计算中国地面气候资料日值数据集V3.0
土壤数据抵抗力计算全球土壤数据集(Harmonized World Soil Database version 1.2)
DEM数据抵抗力计算、阻力面构建地理空间数据云(https://www.gscloud.cn)
), ArticleFig(id=1241116667602850690, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116643384938829, language=CN, label=表1, caption=

数据信息表

, figureFileSmall=null, figureFileBig=null, tableContent=
数据用途来源
土地利用数据适应力计算、恢复力计算、人类干扰指数计算、生态源地识别、阻力面构建中国科学院资源环境科学数据中心(https://www.resdc.cn)
道路数据阻力面构建、人类干扰指数计算中国科学院资源环境科学数据中心(https://www.resdc.cn)
人口密度数据人类干扰指数计算中国科学院资源环境科学数据中心(https://www.resdc.cn)
夜间灯光数据人类干扰指数计算中国科学院资源环境科学数据中心(https://www.resdc.cn)
NPP数据抵抗力计算EarthData官网(https://www.earthdata.nasa.gov)
气象数据抵抗力计算中国地面气候资料日值数据集V3.0
土壤数据抵抗力计算全球土壤数据集(Harmonized World Soil Database version 1.2)
DEM数据抵抗力计算、阻力面构建地理空间数据云(https://www.gscloud.cn)
), ArticleFig(id=1241116667728679826, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116643384938829, language=EN, label=Table 2, caption=

Meaning of landscape pattern index

, figureFileSmall=null, figureFileBig=null, tableContent=
景观格局指数生态含义
香农多样性指数(SHDI)反映景观异质性,特别对景观中各拼块类型非均衡分布状况较为敏感,即强调稀有拼块类型对信息的贡献.
香农均匀度指数(SHEI)与SHDI指数一样,也是比较不同景观或同一景观不同时期多样性变化的一个有力手段.
斑块密度(PD)表现某种斑块在景观中的密度,可反映出景观整体的异质性与破碎度以及某一类型的破碎化程度.
蔓延度指数(CONTAG)描述景观里不同斑块类型的团聚程度或延展趋势,高蔓延度指数说明景观中的某种优势斑块类型形成了良好的连接性.
凝聚度指数(COHESION)描述斑块在景观中的聚集和分散状态,反映自然景观连接性程度.
), ArticleFig(id=1241116668018086822, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116643384938829, language=CN, label=表2, caption=

景观格局指数含义

, figureFileSmall=null, figureFileBig=null, tableContent=
景观格局指数生态含义
香农多样性指数(SHDI)反映景观异质性,特别对景观中各拼块类型非均衡分布状况较为敏感,即强调稀有拼块类型对信息的贡献.
香农均匀度指数(SHEI)与SHDI指数一样,也是比较不同景观或同一景观不同时期多样性变化的一个有力手段.
斑块密度(PD)表现某种斑块在景观中的密度,可反映出景观整体的异质性与破碎度以及某一类型的破碎化程度.
蔓延度指数(CONTAG)描述景观里不同斑块类型的团聚程度或延展趋势,高蔓延度指数说明景观中的某种优势斑块类型形成了良好的连接性.
凝聚度指数(COHESION)描述斑块在景观中的聚集和分散状态,反映自然景观连接性程度.
), ArticleFig(id=1241116668143915950, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116643384938829, language=EN, label=Table 3, caption=

Calculation factors and explanation of human footprint index

, figureFileSmall=null, figureFileBig=null, tableContent=
HII因子因子含义说明参考文献
IPop人口密度影响指数随着人口密度(pd)增加,该指数呈对数增长.当pd<1000人/km2时,IPop=3.333×lg(pd+1);当pd≥1000人/km2时,IPop=10[35]
ILanduse土地利用影响指数按照研究区土地利用类型赋值,未利用地为0分,湖泊、滩涂、草地、河渠1分,有林地、灌木林、疏林地2分,其他林地4分,耕地7分,水库、坑塘、农村居民点8分,城镇建设用地10分[36]
INightlight夜间灯光影响指数使用分位法,将夜间灯光数据的辐射强度重新缩放至0~10分
将高速公路和铁路、国道、省道和其他道路的影响距离分别设定为2、1.6、1.2和1km.随着景
[37]
IAccess区域交通影响指数观单元与道路的距离增加,交通影响指数从10分递减至0分,不同类型的交通影响重叠时,取最大值[38]
), ArticleFig(id=1241116668252967868, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116643384938829, language=CN, label=表3, caption=

人类足迹指数计算因子及说明

, figureFileSmall=null, figureFileBig=null, tableContent=
HII因子因子含义说明参考文献
IPop人口密度影响指数随着人口密度(pd)增加,该指数呈对数增长.当pd<1000人/km2时,IPop=3.333×lg(pd+1);当pd≥1000人/km2时,IPop=10[35]
ILanduse土地利用影响指数按照研究区土地利用类型赋值,未利用地为0分,湖泊、滩涂、草地、河渠1分,有林地、灌木林、疏林地2分,其他林地4分,耕地7分,水库、坑塘、农村居民点8分,城镇建设用地10分[36]
INightlight夜间灯光影响指数使用分位法,将夜间灯光数据的辐射强度重新缩放至0~10分
将高速公路和铁路、国道、省道和其他道路的影响距离分别设定为2、1.6、1.2和1km.随着景
[37]
IAccess区域交通影响指数观单元与道路的距离增加,交通影响指数从10分递减至0分,不同类型的交通影响重叠时,取最大值[38]
), ArticleFig(id=1241116668366214083, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116643384938829, language=EN, label=Table 4, caption=

Resistance factors and coefficient of ecological resistance surface

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阻力因子赋值权重
土地利用类型林地(1)、草地(10)、耕地(30)、水域(60)、未利用地(80)、建设用地(100)0.5
坡度<8°(1)、8°~15°(20)、15°~25°(50)、25°~35°(75)、>35°(100)0.15
起伏度<25m(1)、25~50m(20)、50~70m(50)、70~100m(75)、>100m(100)0.15
高速公路/铁路>2km(1)、1.5~2km(20)、1~1.5km(50)、0.5~1km(75)、<0.5km(100)0.08
国道>1.6km(1)、1.2~1.6km(20)、0.8~1.2km(50)、0.4~0.8km(75)、<0.4km(100)0.06
省道>1.2km(1)、0.9~1.2km(20)、0.6~0.9km(50)、0.3~0.6km(75)、<0.3km(100)0.04
其他道路>1km(1)、0.75~1km(20)、0.5~0.75km(50)、0.25~0.5km(75)、<0.25km(100)0.02
), ArticleFig(id=1241116668454294482, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116643384938829, language=CN, label=表4, caption=

生态阻力面阻力因子及阻力系数

, figureFileSmall=null, figureFileBig=null, tableContent=
阻力因子赋值权重
土地利用类型林地(1)、草地(10)、耕地(30)、水域(60)、未利用地(80)、建设用地(100)0.5
坡度<8°(1)、8°~15°(20)、15°~25°(50)、25°~35°(75)、>35°(100)0.15
起伏度<25m(1)、25~50m(20)、50~70m(50)、70~100m(75)、>100m(100)0.15
高速公路/铁路>2km(1)、1.5~2km(20)、1~1.5km(50)、0.5~1km(75)、<0.5km(100)0.08
国道>1.6km(1)、1.2~1.6km(20)、0.8~1.2km(50)、0.4~0.8km(75)、<0.4km(100)0.06
省道>1.2km(1)、0.9~1.2km(20)、0.6~0.9km(50)、0.3~0.6km(75)、<0.3km(100)0.04
其他道路>1km(1)、0.75~1km(20)、0.5~0.75km(50)、0.25~0.5km(75)、<0.25km(100)0.02
), ArticleFig(id=1241116668554957787, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116643384938829, language=EN, label=Table 5, caption=

Delineation method of regional priority for territorial ecological restoration

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生态要素低退化风险区中退化风险区高退化风险区
生态源地生态保育源地一般修复源地优先修复源地
生态廊道生态保育廊道一般修复廊道优先修复廊道
生态夹点生态保育夹点一般修复夹点优先修复夹点
生态障碍点生态保育障碍点一般修复障碍点优先修复障碍点
), ArticleFig(id=1241116668676592616, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116643384938829, language=CN, label=表5, caption=

国土空间生态修复区域优先序划定方法

, figureFileSmall=null, figureFileBig=null, tableContent=
生态要素低退化风险区中退化风险区高退化风险区
生态源地生态保育源地一般修复源地优先修复源地
生态廊道生态保育廊道一般修复廊道优先修复廊道
生态夹点生态保育夹点一般修复夹点优先修复夹点
生态障碍点生态保育障碍点一般修复障碍点优先修复障碍点
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基于生态退化风险的国土空间生态修复区域优先序划定——以黄河流域山东段为例
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刘金花 1 , 郑永兴 1 , 李威 2 , 杨勇 2, *
中国环境科学 | 环境生态 2025,45(3): 1587-1600
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中国环境科学 | 环境生态 2025, 45(3): 1587-1600
基于生态退化风险的国土空间生态修复区域优先序划定——以黄河流域山东段为例
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刘金花1 , 郑永兴1, 李威2, 杨勇2, *
作者信息
  • 1.山东建筑大学管理工程学院,山东 济南 250101
  • 2.山东省国土空间生态修复中心,山东 济南 250014
  • 刘金花(1979-),女,山东潍坊人,教授,博士,主要从事国土空间规划与评价、土地信息建模研究.发表论文20余篇..

通讯作者:

* 责任作者,高级经济师,
Regional prioritization of territorial spatial ecological restoration based on ecological degradation riskA case study of the Shandong Section of the Yellow River Basin.
Jin-hua LIU1 , Yong-xing ZHENG1, Wei LI2, Yong YANG2, *
Affiliations
  • 1.School of Management Engineering, Shandong Jianzhu University, Jinan 250101, China
  • 2.Shandong Provincial Territorial Spatial Ecological Restoration Center, Jinan 250014, China
出版时间: 2025-03-20
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国土空间生态修复是落实生态文明建设的重要举措,精准识别生态修复区域以及合理划定修复的优先序,是科学有序推进国土空间生态修复的前提,因此,本文以黄河流域山东段为研究区,通过“生态韧性-人类干扰”定量评估生态系统退化风险,采用形态学空间格局分析(MSPA)、景观连通性评价和电路理论模型等方法构建生态安全格局,识别生态源地、廊道、夹点、障碍点等生态要素作为生态修复区域,叠加退化风险等级对修复区域进行优先序划定,并提出相应修复策略.结果表明:研究区总体生态退化风险较高,高退化风险区以各城市为中心呈带状辐射分布,快速城镇化以及交通网络的发展对生态退化的影响不容忽视;识别生态修复区域,包括27个生态源地、71条生态廊道、71处生态夹点和51处生态障碍点;叠加生态退化风险,将生态修复区域划分为优先修复、一般修复以及生态保育三类,并结合不同生态要素特征以及优先序提出修复策略.

生态韧性  /  人类干扰  /  生态安全格局  /  优先序  /  黄河流域山东段

Ecological restoration of territorial space is a critical measure for advancing the construction of ecological civilization. Precise identification of areas requiring ecological restoration and rational delineation of restoration priorities are fundamental prerequisites for the scientific and orderly promotion of territorial ecological restoration. This paper selected the Shandong Section of the Yellow River Basin as the research area and quantitatively evaluated the risk of ecosystem degradation using the "ecological resilience and human disturbance" framework. An ecological security pattern was constructed through Morphological Spatial Pattern Analysis(MSPA), landscape connectivity assessment, and circuit theory models, identifying key ecological factors such as source areas, corridors, pinch points, and barrier points. By overlaying these factors with ecological degradation risks, the priority levels of restoration areas were determined, and corresponding restoration strategies were formulated. The results indicated that the overall risk of ecological degradation in the study area was high, with high-risk areas exhibiting a zonal radiation distribution centered around each city. The influence of rapid urbanization and the expansion of transportation networks on ecological degradation cannot be overlooked. A total of 27 ecological sources, 71 ecological corridors, 71 ecological pinch points, and 51 ecological barrier points were identified as ecological restoration areas. Overlapping ecological degradation risks, ecological restoration areas were divided into priority restoration, general restoration and ecological conservation, and restoration strategies were proposed in conjunction with the characteristics of different ecological elements and their priority order.

ecological resilience  /  human disturbance  /  ecological security pattern  /  priority order  /  the Shandong Section of the Yellow River Basin
刘金花, 郑永兴, 李威, 杨勇. 基于生态退化风险的国土空间生态修复区域优先序划定——以黄河流域山东段为例. 中国环境科学, 2025 , 45 (3) : 1587 -1600 .
Jin-hua LIU, Yong-xing ZHENG, Wei LI, Yong YANG. Regional prioritization of territorial spatial ecological restoration based on ecological degradation riskA case study of the Shandong Section of the Yellow River Basin.[J]. China Environmental Science, 2025 , 45 (3) : 1587 -1600 .
黄河流域作为我国重要的生态屏障及经济地带,党中央多次强调黄河流域生态保护和高质量发展,提倡生态优先,绿色发展[1-2].但近年来,随着城市化与工业化快速推进,人类活动干扰生态系统的状况日益加剧,导致生态系统发生退化,生态系统服务功能降低,严重威胁了黄河流域生态安全[3-5].国土空间生态修复作为恢复和重建退化生态系统的重要手段[6],可为区域生态安全问题提供解决方案[7].生态修复区域的识别是开展国土空间生态修复的基础,对修复区域进行优先序划定,合理安排近远期修复工程,能高效缓解区域生态问题、提高生态系统质量和稳定性.然而,如何落实山水林田湖草沙生命共同体理念、科学合理地划定修复区域优先序,仍是目前国土空间生态修复工作亟需解决的关键问题.
中国生态修复工作起源于20世纪70年代,先后部署了三北防护林体系建设工程、黄河中上游水土流失重点治理工程等一系列大规模的生态修复工程[8].自党的十八大以来,国家更加重视生态文明建设[9],开展了一系列生态修复工作.起初,相关的研究主要针对单一要素或单一生境进行修复治理,缺乏对生态要素关联性的考虑,出现局部效果好而整体收益低的现象[10].为强化国土空间生态修复的整体性和系统性,研究开始关注多要素综合治理,其中通过“源地识别-阻力面构建-廊道提取-节点识别”构建生态安全格局的研究范式应用最为广泛,为国土空间系统性和针对性修复提供了理论支持[11-12].生态安全格局研究方法日益完善,相关研究主要通过直接与间接两种方式识别生态源地,直接识别是将生态保护红线、自然保护区等直接作为生态源地[13-14],间接识别则是采用综合评价法通过生态系统服务评估与权衡(InVEST)模型[15]、生态系统服务功能重要性评价[16]等筛选综合指数高的区域作为生态源地,或通过形态学空间格局分析(MSPA)[17]与景观连通性指数相结合,将景观连通性高的核心区作为生态源地.比较而言,间接识别更加客观.利用最小累积阻力(MCR)模型[18-19]、电路理论模型[20]等识别生态廊道,其中电路理论模型利用了电子在电路中随机游走的特性[21],更接近实际生物的迁徙,且基于电路理论可以识别生态修复的关键节点,即生态夹点与生态障碍点.这些研究仅侧重于识别生态安全格局中的生态要素,并将其组合进行修复,视角较为单一[22].目前已有学者将人类干扰[23-24]、景观生态风险[25-27]等与生态安全格局相结合识别生态修复的优先区,但人类干扰和生态系统之间并非简单的干扰与被干扰关系[25],生态系统对外界干扰有自组织、自适应的能力,仅站在威胁生态安全的角度提取生态修复优先区存在一定局限性.鉴于此,本文从“自然生态—人类社会”两个视角出发,引入在生态系统受到外界干扰时,能维持空间结构功能稳定的生态韧性这一概念[28],结合人类干扰研判生态退化风险.以生态退化风险作为优先序划定的依据,从而对生态修复区域进行精准划分.
黄河流域山东段作为黄河流域唯一的河海交汇区以及黄河三角洲所在地,是黄河下游湿地保护和生态治理的主战场,由于在过去几十年以牺牲生态为代价发展经济,致其生态脆弱、环境污染积重较深、易发生退化,亟需开展生态修复研究.鉴于此,本文以黄河流域山东段为研究区,首先,综合生态韧性与人类干扰研判生态退化风险;然后,通过形态学空间格局分析(MSPA)结合景观连通性评价识别生态源地,基于电路理论识别生态廊道、夹点以及障碍点,将四类生态要素作为修复区域;最后,根据退化风险对修复区域进行优先序划定,并结合各生态要素特征以及优先序提出具有针对性的修复策略,以期为促进黄河流域山东段生态系统稳定性、连通性以及可持续发展提供参考借鉴.
黄河流域山东段(图1)位于黄河下游,黄河从菏泽市入鲁,流经济宁市、泰安市、聊城市、济南市、德州市、滨州市、淄博市,最后从东营市流入渤海,是黄河流域重要的下游生态廊道.气候属于暖温带季风气候,冬季北风盛行,夏季以东南风为主、降雨集中在7~9月,年降雨量大于480mm,年平均温度在11.7~14.2℃.土地利用类型以耕地为主,地势较为平坦,87.6%为平原洼地区,属于鲁西平原、鲁北平原和黄河三角洲冲积平原;12.4%为低山丘陵区,主要分布在东平、长清、历城和章丘等区县,属于泰山山区余脉.区域最高点位于济南长清区,最低点位于东营入海口.黄河流域山东段的生态问题复杂多样,且黄河三角洲极易发生退化,恢复难度极大、过程缓慢,亟需开展生态修复工作,解决区域突出问题.
研究数据主要包括土地利用、交通、人口、夜间灯光、NPP、气象、土壤等数据(表1),数据时间为2020年.将土地利用数据划分为耕地、林地、草地、水域、建设用地以及未利用地六类,为方便空间数据的分析处理,本研究所有数据投影统一为GCS_Krasovsky_1940坐标系,将各数据分辨率统一重采样为100m×100m.
研究方法由三部分组成,首先基于生态韧性评价以及人类干扰评估识别生态退化风险,然后通过构建生态安全格局识别重要生态要素作为待修复区域,最后将生态退化风险等级与各生态要素进行叠加,从而完成修复区域优先序的划定,技术路线如图2所示.
生态系统具有一定的韧性,主要体现在其受到外界干扰时首先能够抵抗外界扰动产生的消极作用,保持原来的结构不会被完全破坏;同时又能适应外界干扰带来的变化,在多变的环境中保持自身的存在和运作;最后在受到外界干扰的影响后,又能恢复其原有结构和功能.因此,本研究从生态系统抵抗力、适应力以及恢复力三个维度选取指标[29],构建生态韧性评价模型.
(1)生态系统抵抗力
生态系统的抵抗能力(P)是生态系统抵抗干扰的能力,与生态系统服务功能有着密切关系,生态系统服务功能越强,表明其抵抗外界干扰的能力越强.研究区拥有我国最年轻河口湿地黄河三角洲、山东省最大淡水湖微山湖、山东省第二大淡水湖东平湖以及泰山、沂山等鲁中南山地,这些生态资源在黄河流域山东段发挥着重要的水源涵养、水土保持以及生物多样性功能,故本研究参考生态环境部颁布的《生态保护红线划定指南》中生态系统服务功能重要性NPP定量指标评估方法,对这三种生态系统服务功能进行评价[30],作为表征生态系统抵抗能力的指标.该方法虽然适用于大尺度研究区的评估,但考虑到准确性以及与实地的相符性,评估所用的参数选取可在评估过程进行适当调整与细化,尽可能采用权威、分辨率高的基础数据.
水源涵养服务能力指数计算式如下:
式中:WR为水源涵养服务能力指数;NPPmean为多年植被净初级生产力平均值;Fsic为土壤渗流因子;Fpre为多年平均降水量因子;Fslo为坡度因子.
水土保持服务能力指数计算公式如下:
式中:Spro为水土保持服务能力指数;K为土壤可蚀性因子;Fslo为坡度因子.
生物多样性服务能力指数计算公式如下:
式中:Sbio为生物多样性服务能力指数;NPPmean为多年植被净初级生产力平均值;Fpre为多年平均降水量因子;Ftem为多年平均气温因子;Falt为海拔因子.
考虑到三种服务功能在黄河流域山东段的重要程度相当,因此对三种功能的服务能力指数标准化处理后进行等权加和处理,计算得到生态系统抵抗力,公式如下:
式中:P为抵抗力;WR为水源涵养服务能力指数;Spro为水土保持服务能力指数;Sbio为生物多样性服务能力指数.
(2)生态系统适应力
生态系统的适应能力(A)是生态系统迅速适应外界环境变化并做出调整以维持稳定的能力,与生态系统的景观结构稳定性相关,一个越稳定的生态系统,其适应性越高[31].生态系统的结构稳定性主要取决于景观异质性和景观连通性[29].景观异质性和景观连通性越高,则生境越复杂,生态系统稳定性越高.衡量景观异质性的重要指标包括景观多样性以及破碎化程度,本研究选取香农多样性指数(SHDI)、香农均匀性指数(SHEI)描述景观多样性,选取斑块密度(PD)表示景观破碎化程度.景观连通性则通过蔓延度指数(CONTAG)以及凝聚度指数(COHESION)来表示,指标具体含义见表2.
式中:SHDI为香农多样性指数;n为景观中斑块类型的总数;Pi为每一种斑块类型所占景观总面积的比例.SHDI=0表明该单元仅由一个用地类型组成,SHDI指数越高,单元内用地类型越多.
式中:SHEI为香农均匀性指数;m是指景观中斑块类型的总数.当指数值为0时代表景观中不存在多样性,值为1时是指景观中不同斑块类型所占总体面积比一致,呈现完全均匀状态,在范围内指数值越大代表景观中不同斑块类型所占面积比越接近,均匀程度越高.
式中:PD为斑块密度指数;NP为斑块数量;A为斑块的总面积.
式中:CONTAG为蔓延度指数;Pi表示i类斑块所占面积百分比;gik表示i类斑块和k类斑块毗邻的数目;m是景观种的斑块类型总数目,其中0<CONTAG<100.
式中:COHESION为凝聚度指数;aij为每一种景观中每个斑块的面积;Pij为每一种景观中每个斑块的周长;A为景观的总面积.
将各指标计算结果进行标准化处理,通过层次分析法确定权重,加权求和计算得到生态系统适应力,公式如下:
式中:A为适应力;SHDI为香农多样性指数;SHEI为香农均匀性指数;PD为斑块密度指数;CONTAG为蔓延度指数;COHESION凝聚度指数.
(3)生态系统恢复力
生态系统的恢复能力(R)是指生态系统在受到外界干扰后恢复其原有结构和功能的能力,表现为生态系统的可调节能力.当受到外界压力时,接近自然生态系统的土地利用类型更容易恢复,而人类利用强度高的土地利用类型在面对外部干扰时恢复能力较差.生态系统的自我调节恢复能力又叫生态弹性力[32],因此本研究采用生态弹性力来表示生态系统的恢复力(R).参考生态弹性力的相关研究成果,选取Peng等[33]提出的生态弹性模型与系数测算生态系统的恢复力.具体公式如下:
式中:R为恢复力;Ai为第i种土地利用类型的总面积;RCi为第i种土地利用类型的生态系统恢复力系数.
最后,将抵抗力、适应力和恢复力三者的计算结果进行标准化,计算生态韧性指数,具体公式如下:
式中:Resilience为生态韧性指数;P为抵抗能力;A为适应能力;R为恢复能力.
人类足迹指数(Human Footprint Index,HFI)可以用来作为量化人类干扰对生态环境影响的常用指标,在自然保护区的生态功能区划和人类活动强度定量评价[34]中得到广泛应用.本研究为表征人类活动对生态系统的影响,基于前人提出的人类足迹体系研究架构,考虑区域特征以及数据的可用性,选取人口、土地利用、夜间灯光和交通四类典型人类活动影响因素评估人类干扰强度[24],计算公式如下:
式中:HF为人类足迹;HII为人类影响指数;HIImax与HIImin分别取研究区内人类影响指数的最大值、最小值,计算公式如下:
式中:IPopILanduseINightlight、和IAccess的含义及说明见表3所示.
随着城市化、工业化的快速推进,生态系统不断遭受人类活动产生的压力与干扰,这些影响将会给生态系统带来不同程度的损害,由于生态系统具有韧性,当生态系统在受到干扰时会自发进行抵抗、适应以及恢复,使得生态系统能够维持其空间结构功能的稳定[28].但生态系统的韧性是有一定限度的,当人类干扰强度高而生态韧性低时生态系统发生退化的风险高,反之生态系统发生退化的风险则低.因此,本研究将通过自然断点法将生态韧性评价与人类干扰评估结果各分为五级,通过等级的对比划定风险区(图3).
生态安全格局构建是国土空间生态修复工作中的重要一环,其有效构建及维护有利于促进生态系统连通性与完整性,从而实现生态系统结构与功能稳定.目前生态安全格局构建范式已日益成熟,其构建过程主要包括生态源地识别、生态阻力面构建、生态廊道提取、生态夹点以及生态障碍点识别,主要研究如下.
生态源地是生物生存、繁衍的重要栖息地,在维持景观完整性和维护生态系统稳定上发挥着重要生态作用.本研究通过形态学空间格局分析(MSPA)识别核心区,筛除面积较小的斑块作为备选源地,最后结合景观连通性评价对备选源地进行进一步的筛选从而得到生态源地[39].
对土地利用栅格数据进行重分类处理,将发挥生态功能的林地、草地、水域作为前景,其他用地作为背景,基于八邻域分析法,利用GuidosToolbox软件识别核心区、连接桥、孤岛、边缘区、孔隙、支线和环岛.选取核心区面积大于5km2的生态区域作为备选生态源地,进行后续景观连通性评价.
景观连通性可以代表各景观要素之间连通性的强弱,是物种能否顺利迁徙以及实现物质能量流通的重要因素.常用的景观连接度指数包括概率连通性指数(PC)和斑块重要性指数(dPC),以此分析景观连通水平,从而识别出对景观格局的连接具有较大影响的生态斑块.具体公式如下:
式中:PC为概率连通性指数;dPC为斑块重要性指数;n为生态斑块数量;aiaj分别表示斑块ij的面积;表示斑块ij之间所有路径的最大乘积概率扩散的最大可能性;ij;PCremove表示斑块剔除后剩余斑块的概率连通性指数;dPC通过移除某斑块后PC的变化衡量各斑块的重要程度.
采用Conefor 2.6软件对备选源地进行定量评价,结合相关文献,设置生态斑块的连通概率为0.5,连通距离阈值为3500m.最终剔除dpc<0.2的斑块,考虑到面积较大的生态斑块对生态系统发挥的重要作用,保留dPC<0.2但面积较大的斑块.
生态阻力是物种在各生态源地之间迁徙所要克服的阻力,构建生态阻力面是识别生态廊道的基础.本研究选取土地利用类型、地形、距离因子三个方面指标作为阻力因子.参考前人关于生态阻力面构建的研究确定阻力系数[40],并结合层次分析法来确定各因子在评价体系中的权重,最终对各评价指标采用赋值加权求和的方法来构建生态阻力面,结果见表4.
生态廊道是物种迁徙、信息传递以及能量流动的主要通道,是维持生态过程、改善景观连通性的关键,对于维持生态系统的稳定性具有极其重要的作用.电路理论模型利用了电子在电路中随机游走的特性[21],更接近实际生物的迁徙.因此本研究采用电路理论,以生态源地作为节点,将生态阻力面视为导电面,利用Linkage Mapper工具箱中的Linkage pathway tool工具,提取出源地间累积阻力最小的廊道作为生态廊道.
生态节点主要包括生态夹点与生态障碍点,对其进行保护修复有利于物种迁徙以及能量流通,从而维持生态系统连通性与功能完整性.生态夹点是生态廊道中电流密度较高的区域,反映物种在各生态源地之间迁徙、流动经过该区域的可能性较大以及缺少其他可以替代的路径,其退化或损失极大可能切断生态系统连通性.本研究基于电路理论的Circuitscape程序,运用Pinchpoint Mapper模块的“all to one”模式识别生态夹点,廊道成本加权距离设为20km.计算电路中的电流密度,提取高密度区域作为生态夹点.生态障碍点是指物种在源地斑块间运动受到阻碍的区域,移除这些区域可以提高生态系统连通性.运用Circuitscape中的Barrier Mapper模块识别生态障碍点,设置500m为最小搜索半径,以100m为步长,1000m为最大搜索半径进行迭代运算,最终选取600m为最合理的迭代半径,提取累积电流恢复高值区作为生态障碍点.
抵抗力与适应力整体上表现为“中部高,南北低”的空间特征(图4a、4b),中部高值区主要分布在济南市与淄博市南部、泰安市中部以及济宁市东北部,该区域位于南部山区、泰山山脉等林草资源丰富的地区,良好的自然本底条件使其具有较强的抵抗力,同时由于该区域内的景观类型复杂多样,景观异质性与连通性较高,从而使得该区域具有较强的生态适应能力.恢复力呈现“中部以及南北两端高,其余地方低”的空间分布特征(图4c),由于恢复力与土地利用类型有着密切关联,所以恢复力高值区一般分布在林、草、水等生态用地聚集的区域.
黄河流域山东段生态韧性的空间分布情况也呈现出“中部高,南北低”的特征(图5),生态韧性等级总体上处于中等偏低水平,其中低韧性和较低韧性区占研究区面积的56.51%,表明研究区整体上生态本底较差.其中,低韧性的区域集中分布在北部河流入海的滨海湿地以及南部的微山湖,北部滨海湿地生态系统较为敏感,自我调节能力较弱,土地盐碱化严重,而微山湖的景观类型、功能单一,抗干扰的能力较差.其他低韧性区零散分布在城镇化发展较为迅速的区域.
研究区人口、土地利用、夜间灯光和交通四类人类活动影响指数评估结果如图所示,研究区绝大部分处于人口密度影响中高值区,少数人口密度影响低值区主要分布在东营市与滨州市的北部,此处为黄河入海口,人口较为稀疏(图6a);土地利用影响低值区主要分布在研究区的中部以及济宁市南部微山湖附近,该区域主要是森林、湖泊,受人类干扰较小.高值区在研究区的分布较为零散,城镇建设用地是该区域土地利用干扰效应的主要来源(图6b);夜间灯光影响高值区分布与土地利用影响高值区的空间分布类似,主要聚集在中心城市,而中高值区零星分布在高值区边缘(图6c);交通影响高值区以研究区各城市为核心向外呈网状辐射(图6d).
总体上,黄河流域山东段对生态环境的干扰强度较低,人类活动高、较高、中、较低和低干扰区面积分别为4508.65km2、19215.76km2、16628.60km2、36111.2km2和6540.21km2,其中低和较低干扰区面积占研究区总面积的51.38%.具体而言,高干扰区集中分布在城市群中部以及各县中心城区;较高干扰区主要沿交通要道呈带状分布;中干扰区分布在较高干扰区的外侧;较低干扰区主要是耕地,该区域面积占比最大;低干扰区主要分布在研究区的中部以及南北两端,该区域主要是受人类干扰较低的林地、山体以及湖泊,生态系统相对稳定(图7).
将生态韧性与人类干扰评价结果叠加得到的生态退化风险情况如图8所示,高退化风险区以各城市为中心呈带状辐射分布,中退化风险区主要分布在研究区的北部,低退化风险区主要分布在研究区的中部以及南部.其中,高退化风险区面积占比最高为45.17%,说明研究区整体生态本底较差,加之人类活动的干扰,导致研究区具有较高的退化风险.
提取通过形态学空间格局分析(MSPA)识别出来的核心区(图9a),剔除面积较小的零碎板块后进行景观连通性评价,选择景观连通性高的核心区作为生态源地,黄河流域山东段生态源地识别情况如(图9b)所示.本研究共识别出27个生态源地,总面积为4889.52km2,土地利用类型主要为林地、草地以及水域,人口密度低,其中最大的源地面积为1411.88km2.生态源地主要分布在滨州市与东营市的北部、淄博市与济南市的南部、泰安市的北部与西部以及济宁市的南部,其中德州市、聊城市以及菏泽市没有生态源地,表明该区域生态自然本底较差.
将土地利用类型、地形以及距离因子三类指标加权求和得到研究区综合阻力值情况(图10a).阻力高值区主要分布在研究区各地市的城市中心,人类生活生产活动较多,对生态环境的干扰强度较大,阻碍了物种迁徙,不利于物质流通、能量传递.低阻力区生态本底相对较好,受人类活动影响较少,能促进生态系统的连通,有利于维持良好的生态系统结构与功能.
以生态源地与综合阻力面为基础,通过电路理论模型,共提取71条生态廊道(图10b),总长度为3177.27km.生态廊道多呈纵向分布,最长生态廊道为286.74km,连接北部与西南部生态源地,生态廊道分布情况与研究区生态源地分布以及生态阻力大小有着直接关系.在未来的土地开发利用过程中应避免破坏生态廊道,保护生态系统稳定性与连通性.
本研究生态节点由生态夹点与生态障碍点共同组成,取电流密度高值区作为生态夹点(图11a).结果表明,共识别生态夹点71处,面积共计293.92km2,其中最大的夹点面积为34.75km2,最小的面积为1.02km2.空间分布上看,生态夹点主要位于中部地区,其中济南市的生态夹点面积最大,为124.63km2,位于济宁市、泰安市以及淄博市的夹点面积也较大,在德州市与菏泽市则无夹点分布.结合综合阻力面显示,生态夹点所处位置阻力较小,表明物种在迁徙过程中易于通过阻力低值区,其承担着重要的生态连通功能,是维持生态系统稳定性的重要区域.叠加土地利用数据分析可知,生态夹点的土地利用类型以林地、草地以及耕地为主.
累积电流恢复高值区为生态障碍点(图11b).研究区共识别生态障碍点51处,面积共计242.93km2,其中最大的障碍点面积为17.41km2,最小的面积为1.14km2.从空间分布上看,生态障碍点也主要分布在研究区的中部,其中济南市的生态障碍点面积最大,为58.82km2.其次为淄博市与济宁市,面积分别为50.55km2、40.69km2.结合阻力面分析得知,障碍点所处位置的阻力相对较高,对物种沿生态廊道迁徙过程中存在一定阻碍作用,对生态系统的连通性存在一定的割裂行为.叠加土地利用数据分析可知,生态障碍点的土地利用类型主要为耕地与建设用地,受人类活动的影响较为严重.
结合生态退化风险评估结果,对黄河流域山东段生态修复区域进行优先序的划定(图12).
优先修复源地面积最大,为1894.60km2,占生态源地总面积的38.75%,主要分布在滨州市无棣县北部、沾化区北部,东营市河口区北部、垦利区东部、东营区东部,该区域主要是河流入海的滨海湿地.近年来,海水倒灌导致湿地萎缩的同时也加剧了土壤盐渍化、降低了土壤有机质含量,使植被发生逆向演替,导致生物多样性降低的同时也削弱了其保水能力,使得该区域韧性低,易发生退化,所以亟需开展生态修复工程提高该区域的生态韧性.一般修复源地面积为1270.00km2,占生态源地总面积的25.97%,主要分布在东营市垦利区东部,泰安市东平县西部以及济宁市微山县,多为滩涂、湖泊,生态系统结构较为单一,存在退化风险,需采取措施提高其抗干扰能力.生态保育源地面积为1724.93km2,占生态源地总面积的35.28%,主要分布在济南市长清区东部、历城区南部、章丘区东部、莱芜区北部、钢城区北部,淄博市淄川区中部、博山区西部与南部、沂源县北部以及泰安市的泰山区西部、岱岳区中部、新泰市北部,该区域林草资源丰富,受人类活动干扰的程度低、本底状况好(图12a).
优先修复廊道长度为715.48km,占廊道总长度的22.52%,相对集中的分布于中部源地的边缘地带,其余优先修复的廊道分布较为零碎,此区域亟需采取修复措施,保障廊道的稳定性与连通性.一般修复廊道长度为427.97km,长度占比最低,仅为13.47%,大部分一般修复廊道与优先修复廊道相接,修复的急迫程度稍缓.生态保育廊道最长,长度为2033.81km,占廊道总长度的64.01%,该生态廊道较为稳固.总体来说,生态廊道的生态本底较好,受人类活动的影响较小(图12b).
优先修复夹点是具有较大退化风险的生态夹点区,其面积为84.21km2,占生态夹点总面积的28.77%,主要位于济南市章丘区东部、历城区南部、平阴市中部、长清区南部、莱芜区北部、钢城区西部,泰安市泰山区中部、岱岳区中部、宁阳县北部,淄博市博山区中部、临淄区中部,分布较为分散,该区域作为物种迁徙的重要区域,应优先采取修复措施防止其退化.一般修复夹点面积最小,为14.69km2,仅占夹点总面积的5.02%,主要位于济南市章丘区东部、莱芜区西部,处于优先修复夹点的边缘,存在一定的退化风险.生态保育夹点面积最大,为193.78km2,占夹点总面积的66.21%,主要位于济南市章丘区南部、莱芜区北部、钢城区北部,淄博市临淄区南部、淄川区南部、博山区北部、沂源县北部,济宁市邹城市南部、泗水县北部,该区域植被覆盖稳定人类开发利用强度低(图12c).
大部分生态障碍点的退化风险程度较高,优先修复障碍点面积为196.92km2,占生态障碍点总面积的81.06%,主要位于济南市槐荫区北部、天桥区中部、长清区东部、章丘区东部、莱芜区西南部,淄博市临淄区中部,滨州市邹平市中部、滨城区西部,泰安市泰山区中部、新泰市中部、东平县西部、宁阳县北部,济宁市任城区中部、兖州区西部、泗水县西部、邹城市中部,该区域本就在物种迁徙过程中就起着阻碍作用,如继续退化可能会切断廊道的流通,严重影响生态系统的连通性,所以应优先修复退化风险高的生态障碍点.一般修复障碍点面积为7.28km2,占障碍点总面积的3.00%,主要分布在优先修复区的边缘.生态保育障碍点面积为38.72km2,占障碍点总面积的15.94%,零散分布于东营市河口区北部、垦利区北部,济南市槐荫区北部,淄博市博山区西部、沂源县东部,滨州市邹平市西部以及泰安市东平县北部,该区域退化风险较小(图12d).
根据不同生态要素的特征,提出点线面结合、生态功能互为支撑的生态修复措施,结合修复优先序的划定安排近远期修复工程,以保障生态系统结构完整、提高区域生态系统服务功能、完善“源地—廊道—节点”的生态安全格局.
(1)生态源地修复策略.生态源地的生态本底较好,应以“自然恢复为主,人工修复为辅”的方式进行保护与修复.优先修复源地主要位于北部河口湿地,对其修复首先应对河口区沿岸产业布局进行合理规划调整,将严重污染产业调出河口区;合理布局滩涂养殖,实施围垦养殖以及浅海养殖.其次,对于部分敏感、受损严重或重要栖息地的河口湿地进行保护,建立保护区制度,给予适当的恢复和保护空间,恢复鸟类栖息觅食场所;对受阻行洪通道实施必要的疏浚,疏导水沙流向、调整滩涂格局,同时根据流域不同鱼类的洄游习性增设辅助设施,助其完成洄游,从而促进生物多样性保护和恢复.优先修复源地的生态退化风险高,应安排近期生态修复工程解决区域突出问题.一般修复源地主要位于南部河湖湿地,对其生态修复则可以通过退养还滩、生态补水等措施,恢复原有湿地;对功能退化的自然湿地,通过清淤疏浚、地形地貌恢复、自然湿地岸线维护、河湖水系连通、水生植被恢复、栖息地营造和外来入侵物种防控等手段,逐步恢复湿地生态功能;开展湿地恢复与综合治理,提高湿地水体净化能力,改善湿地动植物生境.一般修复源地的生态退化风险适中,修复的急迫程度相对较缓,可安排远期生态修复工程.生态保育源地主要位于中部山区,生态本底好,退化风险低.对于该区域应减少人为干扰,主要可通过开展封山禁牧和育林育草等措施对其进行保护,加强原生林草植被和生物多样性保护,禁止开垦利用荒山荒坡.
(2)生态廊道修复策略.生态廊道是源地之间连接的桥梁,对其保护修复可以保障生态系统的连通性与系统性.优先修复廊道与一般修复廊道多贯穿建设用地密集、人口密度较大的区域,应避免城镇空间对生态空间的过度侵占,需建设并完善廊道两侧绿化带和缓冲带,减少人类活动对生态廊道的影响,并对交通运输通道进行合理规划,避免交通道路对生态廊道的阻碍,可根据修复优先序安排近远期工程.生态保育廊道多分布在生态用地,其生态状况较好,应禁止建设用地侵占廊道,保障物种迁徙和廊道流通.
(3)生态节点修复策略.生态夹点对维持生态廊道的流通性起到重要的作用,多位于被中高阻力区域包围的低阻力区域,如建成区内的绿地以及被耕地包围的林草地,由于其位置的特殊性,易受到周围环境的干扰而发生退化.建议重视城区绿地的扩增及养护工作,对基本农田保护区外的耕地采取生态退耕或在耕地周围构建缓冲带,预防生态夹点区域被建设用地、耕地侵占.生态障碍点多位于交通道路上,应设立综合交通廊道防护设施,完善道路两侧绿化带,设置警示牌以限制车辆行驶速度,减少噪声、扬尘、尾气等对生境的影响.此外,应加强生态空间的保留塑造,必要时则修建相关改良设施,如野生动物迁徙专用通道、天桥或隧道等,并定期监测此处野生动物的流动情况.对于生态夹点与生态障碍点的修复,应按照其优先序合理安排生态修复工程.
确定生态修复优先序可以根据修复的轻重缓急以近远期结合的方式合理部署各项生态修复任务,为生态修复工程合理安排提供科学依据.而生态修复优先序的科学划分则需要在“整体保护、系统修复、综合治理”理念指导下,结合生态系统退化受损程度以及修复潜力进行.以往的研究中多考虑通过人类活动干扰强度识别生态修复优先区,忽略了生态系统本身的自组织、自适应能力.为了充分考虑国土空间中“生态—社会”两大系统间博弈关系与系统内各组分的关联性,本研究在前人研究的基础上引入了生态韧性这一概念,用其表示生态系统对外界干扰的抵抗、适应以及恢复能力.综合生态韧性与人类干扰情况判别生态系统退化风险,通过退化风险高低表征生态修复迫切程度,这样既考虑人类干扰对生态系统造成的影响,又考虑生态系统自身应对干扰的能力,有效避免了单一视角评价对生态修复急迫程度表征不准确的问题.在生态修复区域修复策略的制定上,针对不同生态要素提出了具有针对性的修复治理措施,结合修复优先序的划定科学安排近远期修复工程,能够高效提升生态系统连通性与生态功能完整性.
本研究仍然存在一些不足.首先,在生态退化风险评估过程中,虽然综合了自然与人类两个视角,用人类活动表征了对生态系统的干扰,用生态韧性代表生态系统对外界干扰的抵抗.但生态系统所受到的干扰除人类活动带来的干扰外还应有大自然本身的干扰,比如洪涝灾害、台风、地震等自然灾害都会对生态系统产生严重影响.本研究未将自然灾害对生态系统的干扰考虑在内,后续研究中可以充分考虑研究区自然灾害情况,将其带来的干扰定量化表达并纳入到退化风险评估体系中去.其次,本研究主要根据源地、廊道、夹点以及障碍点等生态要素在生态安全格局中的作用以及空间分布特征,提出了针对不同生态要素的修复措施.但同种生态要素内部仍存在较大差异,目前仅在较浅层面上针对要素内部差异粗略提出了相应修复措施,未来需对要素内部差异进行进一步细化研究,提出更为精准、科学的修复方案.
5.1 黄河流域山东段总体生态退化风险较高.高退化风险区面积最大,占研究区总面积的45.17%,空间格局以各城市为中心呈带状辐射分布,快速城镇化以及交通网络的发展对生态退化的影响不容忽视.
5.2 识别出27个生态源地,总面积4889.52km2.提取71条生态廊道,总长度3177.27km.识别71处生态夹点,总面积293.92km2,多位于被中高阻力区域包围的低阻力区域.识别51处生态障碍点,总面积242.93km2,多位于交通道路上.
5.3 叠加生态退化风险评估结果,对各生态要素进行了优先序划定,最终划分了优先修复、一般修复以及生态保育三个等级.优先修复区的急迫程度较高,应安排近期修复工程,一般修复区的急迫程度适中,可安排远期修复工程,而生态保育区的急迫程度较低主要以保护为主.其中优先修复源地面积为1894.60km2,占生态源地总面积的38.75%,主要分布在生态敏感的河流入海区域.优先修复廊道长度为715.48km,占廊道总长度的22.52%.优先修复夹点面积为84.21km2,占生态夹点总面积的28.77%.优先修复障碍点面积为196.92km2,占生态障碍点总面积的81.06%,大部分的生态障碍点修复的急迫程度较高.结合不同生态要素的特征提出修复措施,根据优先序的划定安排近远期工程,能高效提升生态系统连通性、完整性.
  • 教育部产学合作协同育人项目(S2022315)
  • 山东省人文社会科学基金(24BGL212)
  • 山东省重点研发计划(软科学项目)一般项目(2023RKY02005)
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2025年第45卷第3期
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  • 接收时间:2024-08-09
  • 首发时间:2026-03-18
  • 出版时间:2025-03-20
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  • 收稿日期:2024-08-09
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教育部产学合作协同育人项目(S2022315)
山东省人文社会科学基金(24BGL212)
山东省重点研发计划(软科学项目)一般项目(2023RKY02005)
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    1.山东建筑大学管理工程学院,山东 济南 250101
    2.山东省国土空间生态修复中心,山东 济南 250014

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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
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