State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China.
State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China.
Sci Total Environ. 2020 Oct 15;739:139622. doi: 10.1016/j.scitotenv.2020.139622. Epub 2020 May 22.
Land cover change (LCC) is a major part of environmental change. Exploring the spatiotemporal differences in LCC and the driving factors is the basis for comprehensive research on landscape planning, and it is of great significance for future effective and sustainable landscape management. In this respect, cross-scale research with integrated methods is worthy of more attention, although some studies have discussed the driving forces of LCCs at either regional or local scale. We combined a structural equation model and a mixed-effects model for quantifying the driving forces of LCCs across different scales in the Loess Plateau (China), which is a typical region that has experienced significant LCCs over recent decades. The impacts of biophysical and socioeconomic factors on different change trajectories (agricultural intensification, urbanization and ecological restoration) were found to be inconsistent at different temporal and spatial scales. We found that topography had a negative effect on agricultural intensification during 1990-2010 and on urbanization during 1990-2000, but it had a positive effect on ecological restoration during 2000-2015 at the regional scale. Moreover, although there was no significant impact from economic development on any type of LCCs at the regional scale, its important influence could be seen in some of the township categories. Therefore, the path and scale dependence of driving forces is an important consideration in landscape planning and management to accommodate local conditions and fine-tuned analysis as decision-making supports.
土地覆被变化（LCC）是环境变化的主要组成部分。探索 LCC 的时空差异及其驱动因素是进行景观规划综合研究的基础，对未来进行有效和可持续的景观管理具有重要意义。在这方面，采用综合方法的跨尺度研究值得更多关注，尽管一些研究已经讨论了区域或局部尺度的 LCC 驱动因素。我们结合结构方程模型和混合效应模型，在黄土高原（中国）不同尺度上量化了 LCC 的驱动因素，该地区是近几十年来经历了显著 LCC 的典型区域。在不同的时空尺度上，生物物理和社会经济因素对不同变化轨迹（农业集约化、城市化和生态恢复）的影响是不一致的。我们发现，在区域尺度上，地形对 1990-2010 年的农业集约化和 1990-2000 年的城市化有负面影响，但对 2000-2015 年的生态恢复有积极影响。此外，尽管经济发展对任何类型的 LCC 在区域尺度上都没有显著影响，但在一些乡镇类别中可以看到其重要影响。因此，驱动力的路径和尺度依赖性是景观规划和管理中需要考虑的一个重要因素，以适应当地条件和微调分析作为决策支持。
