植物生态学报 ›› 2021, Vol. 45 ›› Issue (5): 467-475.DOI: 10.17521/cjpe.2020.0288

• 研究论文 • 上一篇    下一篇

黄河首曲玛曲县高寒湿地景观格局演变

薛鹏飞1,2, 李文龙1,2,*(), 朱高峰3, 周华坤4, 刘陈立1,2, 晏和飘1,2   

  1. 1草地农业生态系统国家重点实验室, 兰州大学草地农业科技学院, 兰州 730000
    2兰州大学农业农村部草牧业创新重点实验室, 兰州大学草地农业教育部工程研究中心, 兰州 730000
    3兰州大学资源环境学院, 兰州 730000
    4中国科学院西北高原生物研究所, 西宁 810008
  • 收稿日期:2020-08-21 接受日期:2021-01-12 出版日期:2021-05-20 发布日期:2021-03-09
  • 通讯作者: 李文龙
  • 作者简介:*薛鹏飞:ORCID: 0000-0002-4617-3404(wllee@lzu.edu.cn)
  • 基金资助:
    国家重点研发计划(2018YFC0406602);国家自然科学基金(41471450);中央高校基本科研业务费学科交叉创新团队建设项目(lzujbky-2021);现代农业产业技术体系建设专项资金(CARS-34);青海省自然科学基金(2019-ZJ-908)

Changes in the pattern of an alpine wetland landscape in Maqu County in the first meander of the Yellow River

XUE Peng-Fei1,2, LI Wen-Long1,2,*(), ZHU Gao-Feng3, ZHOU Hua-Kun4, LIU Chen-Li1,2, YAN He-Piao1,2   

  1. 1State Key Laboratory of Grassland Agro-ecosystems, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730000, China
    2Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Lanzhou University; Engineering Research Center of Grassland Industry, Ministry of Education, Lanzhou University, Lanzhou 730000, China
    3College of Earth and Environment Sciences, Lanzhou University, Lanzhou 730000, China
    4Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810008, China
  • Received:2020-08-21 Accepted:2021-01-12 Online:2021-05-20 Published:2021-03-09
  • Contact: LI Wen-Long
  • Supported by:
    the National Key R&D Program of China(2018YFC0406602);the National Natural Science Foundation of China(41471450);the Fundamental Research Fund for the Central Universities(lzujbky-2021);the Earmarked Fund for China Agriculture Research System(CARS-34);the Natural Science Foundation of Qinghai Province(2019-ZJ-908)

摘要:

高寒湿地是青藏高原地区最重要的生态水源涵养区之一, 也是局部气候的有效调节者, 其动态变化与成因亟待深入研究。该研究基于遥感图像分析、地理信息系统空间分析和景观生态指数分析结合的方法, 以黄河首曲玛曲县高寒湿地为研究对象, 对1995-2018年6期湿地的动态变化进行研究。结果表明, 研究区湿地在1995-2010年间不断退化, 1995-2010年湿地面积总共减少了18 680.31 hm2。在2010-2018年间黄河首曲高寒湿地面积有所增加, 但与20世纪90年代相比, 21世纪初开始湿地的面积普遍呈现下降趋势; 1995-2010年湿地斑块数不断增加, 斑块密度不断增大, 平均斑块面积下降, 景观的破碎度升高; 2010-2015年湿地斑块数和斑块密度减少, 2015-2018年湿地斑块数和斑块密度增加, 平均斑块面积先增大后减小, 景观的破碎度先降低后升高。1995-2010年研究区高寒湿地景观Shannon多样性指数和Shannon均匀度指数均呈现下降的趋势, 湿地的景观结构趋于简单, 景观类型分布更加集中。2010-2018年湿地景观Shannon多样性指数和Shannon均匀度指数均呈现上升趋势, 湿地的景观结构趋于复杂, 景观类型增加且分布更加分散。进一步的驱动力分析表明, 引起黄河首曲高寒湿地景观格局演变的主要因素是蒸发量和降水量, 其次是人口数量和大牲畜数量等人类活动影响。气候因子是影响黄河首曲高寒湿地面积变化的主要原因, 过度的人类经济活动在一定程度上加剧了湿地的变化。

关键词: 高寒湿地, 景观格局, 随机森林算法, 驱动力分析, 湿地变化

Abstract:

Aims The alpine wetland is one of the most important sites for ecological and water conservation in Qingzang Plateau, and also an effective regulator of the local climate. Research is needed to understand the dynamics and drivers of changes in this alpine wetland landscape.
Methods This study was conducted with combination of methods in remote sensing image analysis, GIS spatial analysis and landscape attributes analysis. Changes in the alpine wetland patterns in Maqu County, which is located in the first meander of the Yellow River, was determined for six periodic samplings from 1995 to 2018.
Important findings The alpine wetland area in Maqu County continuously degraded from 1995 to 2010, and decreased by 18 680.31 hm2 over the period. From 2010 to 2018, the wetland area increased. Compared with the level in 1990s, the wetland area has generally declined since the beginning of the 21st century. From 1995 to 2010, the patch number and density of the wetland increased continuously, but the average patch size decreased, with increased degree of landscape fragmentation. In contrast, from 2010 to 2015, the patch number and density of wetland decreased. From 2015 to 2018, the patch number and density of wetland increased, and the average patch size first increased and then decreased, with the landscape fragmentation first decreased and then increased. Both the Shannon diversity index and evenness index showed a downward trend from 1995 to 2010; the landscape structure tended to be simpler and the distribution of landscape types became more clustered. From 2010 to 2018, the Shannon diversity and evenness indices showed an upward trend; the landscape structure tended to be more complex, and the landscape types became more diverse and dispersed. Further analyses revealed that the main factors driving the changes in the alpine wetland landscape patterns in the first meander of the Yellow River are evaporation and precipitation, followed by human activities such as the population and the quantity of large livestock. Climate is the main factor driving the changes in the alpine wetland area in the first meander of the Yellow River. Intensive human economic activities have aggravated the wetland changes to some extent.

Key words: alpine wetland, landscape pattern, random forest algorithm, driving force analysis, wetland change