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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
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
作者姓名:张紫怡  刘艳芳  张扬  刘耀林  陆砚池  任其然
作者单位:1.武汉大学资源与环境科学学院,湖北 武汉,430079
基金项目:国家重点研发计划2017YFB0503500
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(carbo...

关 键 词:生态系统服务  协同权衡  地理加权逻辑回归  生态功能区  影响因子
收稿时间:2021-04-19

Spatial Non-Stationary Response of the Ecosystem Services Synergy and Tradeoff to Influencing Factors: A Case Study of Ecological Function Area in Fujian Province
Affiliation:1.School of Resources and Environmental Sciences, Wuhan University, Wuhan 430079, China
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 gov?ernance 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 select?ed 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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