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Dynamic Study On Regional Ecological Carrying Capacity And Its Driving Factors In China

Posted on:2018-08-29Degree:MasterType:Thesis
Country:ChinaCandidate:X WangFull Text:PDF
GTID:2311330512973760Subject:Statistics
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Over the past decade,many aspects such as economic and society have made a breakthrough development in China.But in the meantime,desertification,fog and haze,resource depletion and a lot of other resource and environmental problems are exposed to us gradually.Of course,we can't completely deny the achievements of economic development.So that,the key point is to measure whether the ecological carrying capacity can satisfy the growing demands from people.The demands always can be measured by some objects,but the carrying capacity is relatively abstract.So what is the ecological carrying capacity?And how to improve the regional ecological carrying capacity?Therefore,it is necessary to carry out the relevant research of ecological carrying capacity in the whole country and different areas,and give the connotation,calculation method and driving factors of regional ecological carrying capacity,in order to provide the necessary conditions for the future sustainable development of our country.This article absorbs the excellent ecological carrying capacity research at home and abroad to give the definition and connotation of the ecological carrying capacity from the point of bearer body and bearer object.In particular,it points out that human being as an important component of ecosystem plays a useful feedback role in the process of ecosystem evolution.So that it is necessary to integrate human support into the ecological carrying capacity.At the same time,according to the theory of emergy analysis and ecological footprint model,a reasonable improvement method is put forward to integrate this human support into the calculation method of regional ecological carrying capacity.Based on this method,this article measured the regional ecological carrying capacity of 31 areas in China from 2000 to 2014.In the meantime,making use of basic descriptive statistical methods,and combining with K-means clustering algorithm,spatial autocorrelation coefficient and scattergram of Moran's I,this article analyzes the overall pattern,the trend and the spatial correlation of the ecological carrying capacity in China.The result of spatial pattern is "West areas>east areas>central areas",and there are two different trends,one is growing and the other is stable.And because these two regions are geographically distinct,they can be divided into "eastern" and "western" regions in the sense of carrying capacity.In addition,the regional ecological carrying capacity of China has significant spatial correlation.And the main accumulation characteristics of the local areas are:the southwest regions are high-high aggregation,the central areas are low-low aggregation,while the eastern coastal areas gradually changes from low-low aggregation to high-high aggregation.An then this article absorbs the research results of some scholars to choose the appropriate driving forces,and make use of panel regression and spatial panel regression model to carry out empirical analysis on the driving factors of carrying capacity in the "eastern","western" and nationwide areas respectively.The results are that in nationwide and"western" regions,increasing levels of economic development and population growth will have a significant negative impact on carrying capacity,while the efficiency of economic development is conducive to the improvement of the regional ecological carrying capacity.And in"eastern" regions,besides the inhibitory effect of economic development and the promoting effect of the efficiency of economic development,scientific and technological progress and promotion of society is also conducive to enhance the carrying capacity,but the driving force is relatively weak.In addition,the spatial spillover effect of regional ecological carrying capacity can't be neglected in China.
Keywords/Search Tags:Regional Ecological Carrying Capacity, Emergy-based Ecological Footprint Model, Spatial Correlation, Spatial Panel Regression
PDF Full Text Request
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