中国资源再生利用的生态效率演变特征与空间分异格局

doi:10.13287/j.1001-9332.202103.014

摘要/Abstract

摘要： 解析资源生态效率演变特征和分异格局,可为我国实现资源再生利用区域均衡发展和提高生态利用效率水平提供参考。本研究以26个省(市、区)的资源再生利用面板为对象,采用超效率DEA模型测算了2004—2017年其产业生态效率水平,并基于地理区划,分析该产业生态效率演变特征和空间分异格局。结果表明: 2004—2017年,研究区的资源再生利用产业生态效率逐年提高,约有年均1.5%的增长势能,整体表现为由内陆逐渐向沿海递增的演变态势。该产业生态效率全局空间相关性显著,且省(市、区)之间存在明显的空间集聚特征;随着年份推移,区域差异性减弱,高水平省(市、区)辐射带动力较强。研究期间,我国资源再生利用的生态效率空间分异趋于缓和,主要因为华北、东北、华东、华南、华中和西北地区的空间分异减弱,而西南地区的分异不断增强,从而弱化了整体降低趋势。

关键词: 资源再生利用, 生态效率, 时空演变, 空间分异

Abstract: Analyzing the evolution and heterogeneity patterns of resources’ ecological efficiency in China could provide reference for balancing regional development and improving the ecological efficiency of resource recycling. With the panel data of resource recycling in 26 provinces (cities, regions), we measured the ecological efficiency during 2004 to 2017 by the super efficiency DEA model, and analyzed the evolution of ecological efficiency and heterogeneity patterns based on the regionalization. The results showed that, from 2004 to 2017, the ecological efficiency of resource recycling was increasing yearly, with a mean annual growth potential of 1.5%, showing an spatially increasing trend from inland to coast. The ecological efficiency in China showed significant spatial correlation, with clustering character among provinces. During 2004 to 2017, the overall correlation decreased yearly due to the strong radiation effect of high level provinces. Because of the decrease of differentiation in the north, northeast, east, central, south, southwest and northwest in China, the spatial heterogeneity of ecological efficiency of resource recycling in China turned to relieve, which was weakened by the increasing heterogeneity in the southwest region.

Key words: resource recycling, ecological efficiency, spatial-temporal evaluation, spatial heterogeneity

唐燕, 孟繁玥. 中国资源再生利用的生态效率演变特征与空间分异格局[J]. 应用生态学报, 2021, 32(3): 983-992.

TANG Yan, MENG Fan-yue. Evolution and spatial heterogeneity patterns of ecological efficiency of resource recycling in China[J]. Chinese Journal of Applied Ecology, 2021, 32(3): 983-992.

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