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基于三维生态足迹的中国自然资本利用时空演变及驱动力分析
引用本文:郑德凤,刘晓星,王燕燕,吕乐婷.基于三维生态足迹的中国自然资本利用时空演变及驱动力分析[J].地理科学进展,2018,37(10):1328-1339.
作者姓名:郑德凤  刘晓星  王燕燕  吕乐婷
作者单位:辽宁师范大学城市与环境学院,辽宁 大连 116029
基金项目:国家社会科学基金项目(17BJL105)
摘    要:目前基于三维生态足迹的中国省际自然资本利用研究,仅从生产视角测度评价了区域自然资本存量、流量利用的空间格局。本文以消费视角对2006-2015年中国30个省(市、自治区)及不同地类足迹深度、足迹广度进行动态评估,进而通过存量流量利用比和资本流量占用率刻画了中国自然资本利用可持续性现状,并利用全局和局部回归模型量化其驱动因素及因素效应的空间差异性。结果显示:①中国足迹深度从3.04升至4.17又降至4.06,存量资本消耗有减弱趋势;足迹深度大致表现为:东部>中部>西部,其中上海最高达30.69,青海最低为1.70;②中国足迹广度在0.36~0.39 ghm2/人之间波动;足迹广度总体表现为:西部>中部>东部,其中最大值为新疆0.81 ghm2/人,最小值为上海0.09 ghm2/人;③从组分构成看,化石能源用地和草地是存量资本消耗的主要方式,耕地和建设用地是流量资本占用的主要方式;④中国自然资本利用可持续性呈现变好趋势,省际呈东弱西强的格局;通过回归分析发现,生态足迹强度、城市化率、生态承载力是导致自然资本利用可持续性空间差异的显著因素,且这些因素的效应特征表现出不同的空间模式。生产视角和消费视角的测算结果相结合,可提供全面丰富的生态足迹信息,为相关实际应用提供一定的借鉴。

关 键 词:三维生态足迹  自然资本  可持续性  最小二乘法  地理加权回归  时空演变  中国  
收稿时间:2018-04-20
修稿时间:2018-06-14

Spatiotemporal evolution and driving forces of natural capital utilization in China based on three-dimensional ecological footprint
Defeng ZHENG,Xiaoxing LIU,Yanyan WANG,Leting LV.Spatiotemporal evolution and driving forces of natural capital utilization in China based on three-dimensional ecological footprint[J].Progress in Geography,2018,37(10):1328-1339.
Authors:Defeng ZHENG  Xiaoxing LIU  Yanyan WANG  Leting LV
Institution:School of Urban and Environmental Sciences, Liaoning Normal University, Dalian 116029, Liaoning, China
Abstract:Dynamic assessment of natural capital utilization can help to track consumption demand of residents and ecological sustainability of regions. To date, studies on natural capital utilization in China's provinces based on the three-dimensional ecological footprint has only measured and evaluated the spatial patterns of regional natural capital stock and flow from the perspective of production. In this study, the footprint depth and size of regions and different land use types in 30 provinces (municipalities, autonomous regions) of China from 2006 to 2015 were first calculated from the consumption perspective. Then the regional sustainability of natural capital utilization was characterized by utilization ratio of stock to flow and occupancy rate of capital flows. Lastly, the driving factors and effects of natural capital utilization were quantified by the methods of ordinary least squares (OLS) and geographically weighted regression (GWR). The results are as follows: (1) China's footprint depth was highly consistent with the changing trend of ecological footprint and ecological deficit—it showed a trend of first growing and then decreasing during 2006 to 2015, and the value changed from 3.04 to 4.06. The main reason is that the continuous rising trend of ecological pressure was reversed due to the reduced contribution of fossil energy land. Ecological footprint depth presented significant differences from east to west—in Shanghai it is up to 30.69 and in Qinghai it is a minimum of 1.70. (2) Ecological footprint size in China was influenced by resource endowments and showed a small fluctuation through time, with an overall pattern of western region > central region > eastern region in space, and the maximum and minimum footprint sizes were respectively 0.81 ghm2 in Xinjiang and 0.09 ghm2 in Shanghai. Natural capital flow can be improved greatly in the central and western regions. (3) The main components of footprint depth in Chinese provinces were fossil energy land and grassland, and the utilization degrees of other lands varied in different regions. The main components of footprint size in Chinese provinces were cultivated land and construction land, followed by woodland, grassland and water area accounting for a small proportion. (4) The sustainability of natural capital utilization has become better in China, and it showed the spatial pattern of "weak east and strong west". By using OLS regression and GWR, we found that the significant factors that affected the sustainability of natural capital utilization were the intensity of ecological footprint, urbanization rate, and ecological carrying capacity. The influence degree of these factors in different geographical locations showed spatial differences.
Keywords:three-dimensional ecological footprint  natural capital  sustainability  ordinary least squares analysis  geographical weighted regression  spatiotemporal evolution  China  
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