基于无人机影像的草方格生态恢复区植被空间格局演化研究

理解植物群落组成结构的演化对于阐明荒漠化的过程与驱动机制、制定有效的干旱区生态系统恢复措施具有重要价值。研究干旱区植物群落的空间格局的演化过程有助于深入理解荒漠化和生态恢复的过程与机理。目前大量研究关注于植被退化过程中的群落组成结构变化,而对于生态恢复过程中的植物群落空间格局演化的研究尚不多见。干旱区生态系统中植物通常较为稀疏且个体较小,准确提取植物的分布往往需要分辨率极高的遥感数据。近年来,低空无人机遥感技术的快速发展为精细尺度上植被空间格局的研究提供重要技术支持。利用2 cm空间分辨率的低空无人机遥感数据结合地面群落调查,在精细尺度上研究了宁夏沙坡头草方格生态恢复区内植物群落的空间格局变化。研究结果表明,沙坡头地区草方格生态恢复工程实验区域,相对于未实施生态恢复工程的裸露沙丘区域,植物物种多样性和植被盖度显著提高。恢复工程实施4年后,平均植被盖度增加3倍,物种丰富度增加1倍。在植被恢复过程中,随着植被盖度的增加,植被斑块表现出规模上升、破碎化程度下降、形状复杂化、空间自相关减弱等格局特征变化。这些空间格局特征的变化表明大型植被斑块趋于恢复,整体微环境的改善有利于单独生长的植物个体存活,整体上生态系统退化为裸地的风险降低。利用低空无人机遥感手段,对草方格生态恢复工程的植被恢复过程进行了详细、高分辨率的空间格局调查及分析,结合地面群落调查,从多个方面证明了草方格生态恢复措施的有效性。基于无人机的系统格局连续长期监测有助于深入理解干旱区生态恢复机理,对于科学开展荒漠化生态恢复措施也具有重要价值。

The spatial dynamics of vegetation revealed by unmanned aerial vehicles images in a straw-checkerboards-based ecological restoration area

Understanding the temporal variation of plant community composition is one of the prerequisites to address desertification process and its driving factors and to further develop the effective measures for ecosystem restoration in arid region. Investigating the spatial pattern dynamics of plant communities may help to improve our understandings of vegetation degradation and restoration processes. Till now numerous studies have focused on the changes of community composition during vegetation degradation processes, whereas few studies paid concern to the spatial pattern dynamics of plant communities during the ecological restoration processes. Plants in arid ecosystems are usually sparse with relatively small individual size, which require high-resolution remote sensing data to accurately extract the plant distribution pattern. Recently, the rapid development of unmanned aerial vehicles (UAVs) remote sensing technology has allowed an opportunity for the studies on vegetation spatial pattern variation at fine-scale. In this study, we investigated the spatial pattern changes of plant communities in the ecological restoration sites in the Shapotou area, Ningxia Hui Autonomous Region using both high-resolution remote sensing data of UAVs with 2 cm spatial resolution and ground community survey. The results showed that the implementation of the straw checkerboards in Shapotou has significantly improved the plant species diversity and vegetation coverage compared to those of un-restored areas. After four years of implementation, the average vegetation coverage increased by three times and the species richness increased by one time. During the vegetation restoration process, the vegetation patches have shown a significant transformation in pattern features such as increased patch size, decreased fragmentation rate, complicated shape, and weakened spatial autocorrelation. The changes in these spatial pattern characteristics indicate that (1) The large-scale vegetation patches were in a recovery process. (2) The improvement of microenvironment was conducive to the survival of individual plants. (3) The risk of ecosystem degradation to bare land has been reduced. In this study, we assessed the vegetation spatial pattern variation during the restoration processes in detail using UAV remote sensing technology. Combined with thoroughly ground community survey, the effectiveness of straw checkerboards has been proven in multiple perspectives. The continuous long-term monitoring of the system pattern based on UAVs is valuable and necessary for understanding the ecological restoration mechanism in arid region and for future science-based ecological restoration measures in desertification control.