基于生态系统服务与生态恢复力的国土生态修复分区 -pg电子娱乐平台

doi:10.12357/cjea.20230010中国生态农业学报(中英文),2023,31(9):14961510menglandspaceecologicalrestorationzoningbasedecosystemservicesupplyecologicalresilience:casestudybeijing-tianjin-hebeiregion[j].chinesejournaleco-ag-riculture,2023,31(9):14961510基于生态系统服务供需与生态恢复力的国土空间生态修复分区中央农业广播学校保定分校　保定　071000)探究生态系统服务供需匹配特征与生态恢复力属性的耦合关系,科学划分国土空间生态修复分区,对生态安全与区域可持续发展具有重要意义。本研究以京津冀区县为研究单元,基于多源数据,运用食物产量模型、in-vest模型、csle模型等方法测算食物供给、产水、碳固持、土壤保持、休闲游憩等5项生态系统服务的供需构建生态恢复力评价指标体系测算县(区)生态恢复力;基于“生态系统服务供需 生态恢复力”划定生态修复分京津冀生态系统服务供给高值区主要分布在承德市北部、秦皇岛市和唐山市区县,中部县(区)有零星分布;需求高值区主要集中在发展较好的京津冀中部及东南部城市,而北部山区及高原生态系统服务需求较低;研究区供需关系表现为空间负相关。2)各区县生态恢复力区域性差异明显,高值区主要聚集在京津冀的东北部。3)研究区生态系统服务综合供需无高度盈余区域,赤字区域占总面积的42.26%,主要原因为城市与工业的发展导致系统功能衰退,生态服务需求难以得到满足。结合生态系统服务供需匹配特征和生态恢复力空间分布格局,将研究区划分为高供给-高需求-高恢复力区(13.68%)、低供给-高需求-低恢复力区(0.51%)、低供给-高需求-高恢复力区(10.54%)、低供给-低需求-低恢复力区(12.07%)、低供给-低需求-高恢复力区(20.22%)、高供给-低需求-高恢复力区(42.98%)同时针对不同分区提出差异化的生态修复策略,为生态修复工程的系统布局提供指引,为国土空间综合整理方案的科学编制提供方法参考。关键词:生态系统服务供需;生态恢复力;生态修复分区;京津冀中图分类号:tu982.2;x171.4开放科学码(资源服务)标识码(osid):landspaceecologicalrestorationzoningbasedecosystemservicesupplyde-mandecologicalresilience:casestudybeijing-tianjin-hebeiregionmengfandizhouzhi1,2**zhangguijunjiaocuilikanyaochuanzhaoliresourcescollege,hebeiagriculturaluniversity,baoding071000,china;hebeiprovincialkeylaboratoryfarmlandecologicalenvironment,baoding071000,china;baodingbranchcentralagriculturalbroadcastingschool,baoding071000,china)河北省社会科学发展研究课题(20210201298)资助主要从事土地整治工程与土地利用规划研究。e-mail:zhouzhi797825@163.com主要从事国土空间综合整治与生态修复研究。e-mail:mfd1997@foxmail.com收稿日期:2023-01-05　接受日期:2023-05-11hebeisocialsciencedevelopmentresearchproject(20210201298).correspondingauthor,e-mail:zhouzhi797825@163.comreceivedjan.2023;acceptedmay11,2023中国生态农业学报(中英文)　2023chinesejournalofeco-agriculture,sep.2023,31(9):14961510http://www.ecoagri.ac.cnabstract:couplingrelationshipbetweendemandcharacteristicsecosystemservicesecologicalresilience,scientificallydelineateecologicalrestorationzonesnationallandspaceecologicalsecurityregionalsustainabledevelopment.studytookdistrictsbeijing,tianjin,studyunit.basedmulti-sourcedata,foodproductionmodel,investmodel,cslemodel,othermethodswereusedfiveecosystemservices,includingfoodsupply,wateryield,carbonstorage,soilconservation,recreationsupply.ecologicalresilienceevaluationindexsystemecologicalresiliencecounties(districts).basedecosystemservicesupplyecologicalresilience,ecologicalrestorationzonesweredelineated,correspondingoptimizationstrategieswereproposedaccordingsocio-economicstatusde-velopmentcharacteristicswithinresultsshowedhigh-valueareasecosystemservicesupplybeijing-tianjin-hebeiregionweremainlydistributednorthernpartchengdecity,qinhuangdaocity,tangshancity,centralcounties(districts)high-valueareasecosystemservicedemandweremainlyconcen-tratedwell-developedcitiessoutheasternbeijing-tianjin-hebei region, whereas ecosystemservices mountainousareas northernbeijing-tianjin-hebei region eco-system services studyarea were spatially negatively correlated. ecologicalresilience eachdistrict countyhad ticeableregional differences, high-valueareas were mainly concentrated beijing-tianjin-hebeiregion. highsurplus area comprehensivesupply ecosystemservices studyarea. deficitarea accounted totalarea, mainly resulting from systemfunction caused industrialdevelop- ment, ecologicalservices matchingcharacteristics de-mand ecosystemservices spatialdistribution pattern ecologicalresilience, studyarea highsupply- high demand-high resilience (13.68%), low supply-high demand-low resilience (0.51%), low supply-high demand-high resilience