张紫怡, 刘艳芳, 张扬, 刘耀林, 陆砚池, 任其然. 生态系统服务协同权衡对影响因子的空间响应——以福建省生态功能区为例[J]. 武汉大学学报 ( 信息科学版), 2022, 47(1): 111-125. DOI: 10.13203/j.whugis20200700
引用本文: 张紫怡, 刘艳芳, 张扬, 刘耀林, 陆砚池, 任其然. 生态系统服务协同权衡对影响因子的空间响应——以福建省生态功能区为例[J]. 武汉大学学报 ( 信息科学版), 2022, 47(1): 111-125. DOI: 10.13203/j.whugis20200700
ZHANG Ziyi, LIU Yanfang, ZHANG Yang, LIU Yaolin, LU Yanchi, REN Qiran. Spatial Non-Stationary Response of the Ecosystem Services Synergy and Tradeoff to Influencing Factors: A Case Study of Ecological Function Area in Fujian Province[J]. Geomatics and Information Science of Wuhan University, 2022, 47(1): 111-125. DOI: 10.13203/j.whugis20200700
Citation: ZHANG Ziyi, LIU Yanfang, ZHANG Yang, LIU Yaolin, LU Yanchi, REN Qiran. Spatial Non-Stationary Response of the Ecosystem Services Synergy and Tradeoff to Influencing Factors: A Case Study of Ecological Function Area in Fujian Province[J]. Geomatics and Information Science of Wuhan University, 2022, 47(1): 111-125. DOI: 10.13203/j.whugis20200700

生态系统服务协同权衡对影响因子的空间响应——以福建省生态功能区为例

Spatial Non-Stationary Response of the Ecosystem Services Synergy and Tradeoff to Influencing Factors: A Case Study of Ecological Function Area in Fujian Province

  • 摘要: 全球生态系统服务(ecosystem services, ESs)大幅衰退,迫切需要正确的环境治理政策。为解决当前中国生态环境治理存在的缺少以生态功能区为单位的统筹规划和缺乏对ESs协同权衡的深入理解两个问题,以生态功能区为研究单元,测定4项ESs(粮食生产(grain production, GP)、植物固碳(carbon sequestration, CS)、户外休憩(outdoor recreation, OR)和生物多样性维护(biodiversity conservation, BC))的时空变化,探究ESs协同权衡的形成机制及其对温度、降水、日照、海拔和城市化程度这5项影响因子的空间非平稳性响应。提出用差异比较法来确定ESs协同权衡的空间分布,通过主成分分析法选取影响因子,并通过地理加权逻辑回归(geographical weighted logistic regression, GWLR)确定ESs协同权衡对影响因子的空间响应。结果表明,ESs协同权衡具有显著的空间自相关性。每两项服务在空间上并非只是单一关系,而是同时存在协同与权衡关系。其中, BC与OR在整个研究区内表现出高度协同关系,且其二者与其他两项服务GP、CS之间协同权衡的空间分布也十分相似。ESs协同权衡对所有影响因子均表现出显著响应,该响应具有空间异质性,其正负性和强度随空间变化。研究通过总结ESs协同权衡发生的规律,对已有的协同权衡形成机制进行细化:在一定的区域范围内,支持性和非支持性土地利用类型的面积比例,以及它们对各项服务的支持程度会使得两项服务在该区域范围内区分出优势服务和劣势服务。优势服务和劣势服务之间存在动态差距,当该差距处于增加状态时可能导致权衡发生。

     

    Abstract:
      Objectives  Due to the sharp decline of global ecosystem services (ESs), there is an urgent need for correct environmental governance policies. The two problems in the current ecological environment gov‍ernance in China need to be solved: (1) The lack of overall planning based on ecological function areas, (2) The shortage of in-depth synergy and tradeoff understanding among ESs. This study takes ecological function areas as the research units to measure the spatio temporal changes of four ESs (grain production (GP), carbon sequestration (CS), outdoor recreation (OR), and biodiversity conservation (BC)). It also explores the formation mechanism of the synergy and tradeoff among ESs and its spatially non-stationary response of the synergy and tradeoff to the five influencing factors of temperature, precipitation, sunshine, altitude, and urbanization.
      Methods   V arious models and multisource data are integrated to estimate the yield distribution of ESs in Fujian Province. A difference comparison method is proposed to determine the spatial distribution of the synergy and tradeoff among ESs. The Moran's I applied is to determine the spatial autocorrelation of the synergy and tradeoff among ESs. The influencing factors are select‍ed by principal component analysis, and the geographical weighted logistic regression (GWLR) determined the spatial response of the synergy and tradeoff to the influencing factors.
      Results  The main results are as follows: (1) The four ESs selected in the study (GP, CS, OR, And BC) have spatial heterogeneity. Among them, the yield distribution of GP is significantly related to the administrative region, and the highest values of BC, OR and CS appear in the ecological functional areas of biodiversity and water conservation. (2) All the Moran's I values applied are greater than 0, which means the synergy and tradeoff among ESs have significant spatial autocorrelation and are spatially clustered. (3) In space, there are synergy and tradeoff, instead of a single relationship between two ESs. (4) When the yield spatial distribution of two services is similar, such as BC and OR, the spatial distribution of synergies and tradeoffs of other services is also very similar. (5) The synergy and tradeoff among ESs showed significant responses to climate, topography, and urbanization. (6) The responses of the synergy and tradeoff among ESs to the influencing factors are spatially heterogeneous, and their positivity, negativity, and intensity varied with space.
      Conclusions  The diagnosis results of the model show that GWLR is superior to the global regression model in explaining the correlation of synergy and tradeoff among ESs with the influencing factors. By summarizing the law of the occurrence of synergy and tradeoff among ESs, this paper refines the existing formation mechanism of the synergy and tradeoff among ESs: In a certain area, the area proportion of supporting type of land and non-supporting type of land, and the degree of their support effect for each service will divide the two services into superior service and inferior service within the region. Due to the changes in land use, there are a dynamic gap between the superior service and the inferior service, and the increase in the gap may lead to tradeoff.

     

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