大别山贫困区旅游地社会—生态系统脆弱性时空演变与影响机理

旅游地社会—生态系统脆弱性主要由社会、经济、生态子系统要素和旅游发展所带来的相关变化要素构成,是社会脆弱性、经济脆弱性和生态环境脆弱性的综合体现。以大别山区9县（市）为例,基于SEE-PSR模型构建理论研究框架和综合评价体系,探讨贫困山区旅游地社会—生态系统脆弱性时空演变及影响机理。结果表明：① 2009-2016年,区域系统脆弱性综合指数由0.52波动降至0.41,其中经济子系统脆弱性指数呈持续下降趋势,社会子系统与生态子系统呈稳定态势且对区域系统脆弱性综合指数贡献率达到76%,目前区域整体属于较低脆弱并朝着利好方向发展。② 空间差异上,2009-2016年脆弱性综合指数低值县域随时间变化呈波动下降且变异系数较小,脆弱性综合指数高值县域于2013年开始下降逐步演变为较低脆弱等级且变异系数较大;县域间脆弱性空间差异呈现连续波动上升趋势,县域间差异有所增大。③ 阻碍旅游地社会—生态系统脆弱性降低的主要因素由旅游收入增长率、工业增加值占GDP比重、城乡收入差距、旅游总收入占GDP比重及耕地面积比率转变为旅游经济密度、游客密度及城镇化率,区域整体由状态主导型脆弱演化为压力主导型脆弱。

Spatio-temporal evolution and impact mechanism of socio-ecological system vulnerability in poor mountainous tourist distinations: Taking Dabie Mountain Area as example

Tourism's socio-ecological vulnerability is mainly composed of social, economic, and ecological subsystems and the related changing elements from tourism development. It is an integrated manifestation of social vulnerability, economic vulnerability and ecological vulnerability. The paper, taking nine counties in the Dabie Mountain Area as case studies, proposes a socio-ecological vulnerability theoretical framework and comprehensive evaluation index combining the Social-Economic-Environment (SEE) model and the Pressure-State-Response (PSR) model. It explores the spatio-temporal evolution and mechanism that influences vulnerability in impoverished mountainous areas. Conclusions are drawn as follows: (1) During the period 2009-2016, the regional system vulnerability composite index fluctuated, declining from 0.52 to 0.41. The index for the economic subsystem continued to decline, and the index for the social and ecological subsystem kept stable. The contribution to a composite index for a regional system reached 76%, and the regional system had a relatively low degree of vulnerability and tended toward a positive direction. (2) The value of low vulnerability counties fluctuated and declined, and the coefficient of variation is lower, while the value of high vulnerability counties in 2013 began to decrease gradually and evolved into a lower degree of vulnerability; the coefficient of variation is larger. For the entire region, the spatial differences of vulnerability in the county experienced a wave-shaped dynamic change. Finally, the differences reached the minimum in 2013, which led to an aggravation of regional differences. (3) The main factors affecting tourism socio-ecological vulnerability have already changed from the growth of tourism income, the proportion of industrial added value in GDP, the urban-rural income gap, the proportion of tourism income to GDP, and the ratio of agricultural acreage to the density of the tourism economy and tourists, and the population urbanization rate. Entire regional vulnerability has already evolved from state-dominated to pressure-dominated.