基于PLUS模型的图们江流域生态系统服务价值情景模拟及驱动因素研究  

Research on scenario simulation and driving factors of ecosystem service value in Tumen River Basin based on PLUS model

作　　者：宋心馨 张守志[1,2] 王淑琪 邓嘉琪 SONG Xinxin;ZHANG Shouzhi;WANG Shuqi;DENG Jiaqi(College of Geography and Ocean Sciences,Yanbian University,Yanji 133000,Jilin,China;Key Laboratory of Wetland Ecological Function and Ecological Security,Yanji 133000,Jilin,China)

机构地区：[1]延边大学地理与海洋科学学院,吉林延吉133000 [2]湿地生态功能与生态安全重点实验室,吉林延吉133000

出　　处：《水利水电技术(中英文)》2025年第3期186-201,共16页Water Resources and Hydropower Engineering

基　　金：国家自然科学基金重点基金项目(41830643);国家自然科学基金项目(41461036)。

摘　　要：【目的】揭示生态功能区土地利用(LULC)与生态系统服务价值(ESV)之间的内在关系,对于科学发挥生态系统效益和推进区域生态文明建设具有重要意义。【方法】文章利用修正后的标准等效因子,对图们江流域的ESV进行了评估,并采用地理探测器分析了ESV与温度(TEM)、降水(PRE)、归一化植被指数(NDVI)、高程(DEM)、土壤有机质含量(SOMC)和陆地表层人类活动强度(HAILS)等潜在因素的关系及其驱动下的ESV时空演变。基于《吉林省国土空间规划(2021—2035年)》和《延边朝鲜族自治州国土空间总体规划(2021—2035年)》,利用PLUS模型进行了空间约束的多情景设置,探讨在自然发展情景(S1)和目标导向情景(S2)下2030年图们江流域ESV的空间变化。【结果】结果表明,2000—2020年,研究区总ESV虽有波动但整体呈上升趋势,其中2005—2010年期间增幅最大,五年内增加了0.87×10^(10)元。林地的ESV最高,占总价值的近94%;调节服务价值(RSV)和支持服务价值(SSV)是主要的生态系统服务。因子探测结果显示,HAILS(q=0.678)是影响ESV空间分异的主要因子,其次是TEM(q=0.470)和NDVI(q=0.435),而DEM和SOMC的影响较小。相关性分析表明,ESV与景观形状指数(SI)呈负相关(-0.65),与香农多样性指数(SHDI)(0.72)和聚合指数(AI)(0.60)呈正相关。PLUS模拟结果显示,2030年林地的ESV仍将最高。灰色模型GM(1,1)预测的2030年各土地利用类型的单位ESV分别为:耕地3394.79元/hm^(2)、草地10367.71元/hm^(2)、水域107954.26元/hm^(2)、未利用地558.64元/hm^(2)、湿地44708.07元/hm^(2)。【结论】不同情景下ESV高值区和低值区的变化进一步验证了《规划》的科学性和实施的必要性。本研究通过预测不同土地资源管理策略下的ESV空间演变,为实现规划目标提供了空间可视化分析和数据支持,并为土地资源与环境保护综合规划及东北边疆生态功能区的可持续发展提供了参考[Objective]This study aims to reveal the intrinsic relationship between land use and land cover(LULC)in ecological function zones and ecosystem service value(ESV),which is crucial for effectively maximizing ecosystem benefits and advancing regional ecological civilization.[Methods]The ESV of the Tumen River Basin was assessed using modified standard equivalent factors.Geodetector was used to analyze the relationships between ESV and potential influencing factors,including temperature(TEM),precipitation(PRE),normalized difference vegetation index(NDVI),elevation(DEM),soil organic matter content(SOMC),and human activity intensity on land surfaces(HAILS),as well as their influence on the spatiotemporal evolution of ESV.Furthermore,based on the Territorial Spatial Plan of Jilin Province(2021—2035)and the Overall Territorial Spatial Plan of Yanbian Korean Autonomous Prefecture(2021—2035),the PLUS model was used for spatially constrained multi-scenario settings to explore the spatial changes of ESV in the Tumen River Basin under the natural development scenario(S1)and the target-oriented scenario(S2)in 2030.[Results]The result indicated that from 2000 to 2020,the total ESV of the study area fluctuated but showed an overall upward trend,with the largest increase observed between 2005 and 2010,where the ESV increased by 0.87×10^(10) yuan within five years.Forestland contributed the highest ESV,accounting for nearly 94%of the total value.Regulating service value(RSV)and supporting service value(SSV)were the dominant ecosystem services.Geodetector result showed that HAILS(q=0.678)was the primary factor influencing the spatial variation of ESV,followed by TEM(q=0.470)and NDVI(q=0.435),while DEM and SOMC had relatively minor impacts.Correlation analysis revealed that ESV was negatively correlated with the landscape shape index(SI)(-0.65)but positively correlated with the Shannon diversity index(SHDI)(0.72)and aggregation index(AI)(0.60).The PLUS simulation result indicated that,by 2030,forestland would still have the hi

关 键 词：ESV 情景模拟 LULC PLUS模型 驱动因素 影响因素 

分 类 号：X171.1[环境科学与工程—环境科学]