College of Land and Tourism, Luoyang Normal University, Luoyang 471022, China.
College of Geography and Environmental Science, Henan University, Kaifeng 475004, China.
Int J Environ Res Public Health. 2022 Dec 2;19(23):16144. doi: 10.3390/ijerph192316144.
Exploring the assessment methods and multi-scale spatiotemporal interaction characteristics of ecosystem health is of great significance for current ecosystem health theory and application research. Based on the regional differentiation theory and ecosystem service flow theory, the spatial weight coefficient and the modified coefficient of spatial proximity effect were introduced to improve the regional ecosystem health assessment model. Then, the improved VORS model was used to evaluate the ecosystem health level in the Middle Reaches of the Yellow River (MRYR) in China at multiple scales, and the ESTDA method was used to reveal the multi-scale spatiotemporal interaction characteristics of ecosystem health. The results show that: (1) From 1990 to 2018, the ecosystem health level at grid and county scale in the MRYR showed a trend of first decline and then increase, and experienced a slow decline and a steady rise from 1990 to 2005 and 2005 to 2018, respectively. The ecosystem health level at the grid and county scale presented a spatially hierarchical structure with alternating low-value and high-value zones. (2) Compared with the county scale, the grid scale can describe the spatial distribution characteristics of ecosystem health more refined, indicating the existence of spatial scale effects in ecosystem health assessment. (3) The rapid urbanization areas, the ecologically fragile areas in the central and western regions and the transitional zone between mountain and basin have more dynamic spatial structure, and stronger spatio-temporal interaction process. (4) In terms of LISA spatio-temporal transition, the regional system as a whole had strong path-dependent and lock-in characteristics, and the local spatial correlation structure of ecosystem health gradually tended to be stable during the study period. (5) In terms of spatio-temporal interaction network, there were strong spatio-temporal competition in the process of time evolution in six typical regions, such as the surrounding cities of provincial capitals, the fringe areas of cities, the transitional zone between mountain and basin, the transitional zone of ecologically fragile regions, the mountainous areas of western Henan Province, and the areas along rivers.
探索生态系统健康的评估方法和多尺度时空相互作用特征,对当前的生态系统健康理论和应用研究具有重要意义。基于区域分异理论和生态系统服务流动理论,引入空间权重系数和空间邻近效应修正系数,改进区域生态系统健康评估模型。然后,采用改进的 VORS 模型对中国黄河中游(MRYR)多尺度的生态系统健康水平进行评价,并采用 ESTDA 方法揭示生态系统健康的多尺度时空相互作用特征。结果表明:(1)1990—2018 年,MRYR 网格和县域尺度的生态系统健康水平呈先降后升的趋势,分别于 1990—2005 年和 2005—2018 年经历缓慢下降和稳步上升阶段。生态系统健康水平在网格和县域尺度上呈现低值区和高值区交替出现的空间层次结构。(2)与县域尺度相比,网格尺度能够更加精细地描述生态系统健康的空间分布特征,表明生态系统健康评估中存在空间尺度效应。(3)快速城市化地区、中西部生态脆弱区和山地-盆地过渡区的空间结构动态性更强,时空相互作用过程更强。(4)从 LISA 时空跃迁来看,区域系统整体具有较强的路径依赖和锁定特征,研究期间生态系统健康的局部空间相关结构逐渐趋于稳定。(5)从时空相互作用网络来看,六个典型区域(省会城市周边地区、城市边缘区、山地-盆地过渡区、生态脆弱区过渡区、豫西山区和沿江地区)在时间演化过程中存在较强的时空竞争。