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经济差异化增长下生态系统服务价值的时空演变特征——以珠江—西江经济带为例
引用本文:赵泳春,苏方林.经济差异化增长下生态系统服务价值的时空演变特征——以珠江—西江经济带为例[J].自然资源学报,2022,37(7):1782-1798.
作者姓名:赵泳春  苏方林
作者单位:广西师范大学经济管理学院,桂林 541004
基金项目:广西壮族自治区哲学社会科学规划专题重点项目(17AZT20);
摘    要:为了应对经济增长与生态保护双重压力,使用生物量与植被覆盖度修正后的当量因子法测度珠江—西江经济带的生态系统服务价值(ESV);基于STIRPAT模型构建地理加权回归模型,实证研究人文因素对ESV影响的空间异质性,并着重将经济增长因子的回归系数以表格形式展示。结论认为:(1)珠江—西江经济带的ESV在研究年份截面中呈现先下降、后上升、再下降的变动趋势;(2)人均GDP对地均ESV在研究区域东部表现为持续负向影响、中部和北部地区表现为由负转正的影响态势、西北部和西南部的回归结果不显著。基于上述结论,针对避免东部地区ESV进一步下降、鼓励中部和北部经济追赶,以及提高西北和西南部对经济与生态环境协调发展问题的重视方面提出政策建议。

关 键 词:珠江—西江经济带  生态系统服务价值  经济增长  STIRPAT模型  地理加权回归  
收稿时间:2021-08-28
修稿时间:2022-03-18

Spatio-temporal dynamic characteristics of the ecosystem service values under differential economic growth: A case study of the Pearl River-West River Economic Belt
ZHAO Yong-chun,SU Fang-lin.Spatio-temporal dynamic characteristics of the ecosystem service values under differential economic growth: A case study of the Pearl River-West River Economic Belt[J].Journal of Natural Resources,2022,37(7):1782-1798.
Authors:ZHAO Yong-chun  SU Fang-lin
Institution:School of Economics and Management, Guangxi Normal University, Guilin 541004, Guangxi, China
Abstract:Promoting the construction of ecological civilization is conductive to alleviate the contradiction between ecosystem degradation and the people's high-level requirements for a better life, which leads the regions to achieve a win-win situation between ecological value enhancement and economic growth. This paper quantitatively analyzes the spatial and temporal patterns of ecosystem service values (ESV) in the Pearl River-West River Economic Belt in 2005, 2010, 2015, and 2018 by using the method of the value equivalent factor in unit area, which is modified by biomass and vegetation coverage. Further, this paper constructs a geographically weighted regression (GWR) model based on the STIRPAT model to empirically analyze the spatial heterogeneity and spatial non-stationarity of county economic growth affecting unit area ESV. The results shows that: (1) From the perspective of spatio-temporal variation pattern, the ESV of the study area was 4783.391 billion yuan, 4597.193 billion yuan, 5231.360 billion yuan, and 5074.459 billion yuan in 2005, 2010, 2015, and 2018, respectively, documenting a time-varying trend of decreasing, then increasing, and decreasing again. The contribution of the first classification of land-use types to ESV was ranked as forest land > watershed > grassland > cropland > wetland > desert. From the perspective of spatial trends, the ESV showed an alternative distribution of high and low value areas, and presented a spatial pattern of "low in the west, but high in the east". Some districts and counties located at the border between Guangdong and Guangxi have higher ESV per unit area, which appeared a trend of spreading from east to west. However, ESV in the Pearl River Delta region was hardly affected by the diffusion trend. (2) The number of counties with a significant effect of GDP per capita on ESV per unit area was increasing and concentrated in the eastern, central and northern parts. Among them, the Guangdong section of the Pearl River-West River Economic Belt showed a continuous and significant negative effect. In contrast, the central and northern parts of Guangxi showed a change from negative to positive effect, which is in accordance with the EKC hypothesis. Based on the above results, this paper proposes targeted recommendations. First, further declines in ESV in the Pearl River Delta and its western contiguous parts should be avoided. Second, the central and northern parts of the Pearl River-West River Economic Belt should be given more preferential policies to speed up regional development. Third, the northwestern and southwestern parts should pay more attention to the coordination of economic growth and ecological environment. The results of this paper have important implications to the localized development that balances economic growth and ecological environment.
Keywords:Pearl River-West River Economic Belt  ecosystem service value  economic growth  STIRPAT model  geographically weighted regression  
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