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草业学报 ›› 2020, Vol. 29 ›› Issue (1): 13-27.DOI: 10.11686/cyxb2019148

• 研究论文 • 上一篇    下一篇

青藏高原东部高寒沼泽湿地动态变化及其驱动因素研究

侯蒙京, 高金龙, 葛静, 李元春, 刘洁, 殷建鹏, 冯琦胜, 梁天刚*   

  1. 兰州大学草地农业生态系统国家重点实验室,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,兰州大学草地农业科技学院,甘肃 兰州 730020
  • 收稿日期:2019-03-05 修回日期:2019-04-17 出版日期:2020-01-20 发布日期:2020-01-20
  • 通讯作者: *E-mail: tgliang@lzu.edu.cn
  • 作者简介:侯蒙京(1994-), 男, 北京平谷人, 在读博士。E-mail: houmj17@lzu.edu.cn
  • 基金资助:
    国家“十三五”重点研发计划项目 (2017YFC0504801),国家自然科学基金项目(31672484、31702175、41801191、41805086、41671330),长江学者和创新团队发展计划(IRT17R50)和中央高校基本科研业务费(lzujbky-2018-it17,lzujbky-2019-kb28)资助

An analysis of dynamic changes and their driving factors in marsh wetlands in the eastern Qinghai-Tibet Plateau

HOU Meng-jing, GAO Jin-long, GE Jing, LI Yuan-chun, LIU Jie, YIN Jian-peng, FENG Qi-sheng, LIANG Tian-gang*   

  1. State Key Laboratory of Grassland Agro-ecosystem, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730020, China
  • Received:2019-03-05 Revised:2019-04-17 Online:2020-01-20 Published:2020-01-20
  • Contact: *E-mail: tgliang@lzu.edu.cn

摘要: 20世纪中后期以来,在全球气候变化和人类活动的影响下,青藏高原湿地生态系统变的极其敏感和脆弱。运用遥感与地理信息系统技术,以Landsat TM/ETM+/OLI遥感影像为主要数据源,解译了青藏高原东部甘南和川西北地区1991、2000、2010和2016年4个时期的沼泽湿地;利用转移矩阵和湿地动态度,分析了沼泽湿地的空间变化、转移方向和变化速率;采用景观指数,分析了沼泽湿地景观格局变化;结合气象数据和相关统计资料并利用灰色关联度法,分析了沼泽湿地变化的驱动因素。结果表明: 1)研究区沼泽湿地主要分布在东北部,1991-2016年4个时期的面积分别为6739.89、6231.39、5849.59和5649.35 km2,处于持续减少的状态,26年间面积共减少了1090.54 km2。2)26年来,研究区沼泽湿地的动态度从-7.54%减小至-3.42%,面积变化速率持续减慢,高寒草地是沼泽湿地转出和转入的主要类型。3)沼泽湿地的斑块数量先增加后减少,斑块密度持续增大,反映了沼泽湿地的破碎程度增高;最大斑块指数先降低后小幅升高,斑块形状指数先升高后小幅下降,反映了沼泽湿地的优势度降低,景观形状趋于复杂化;分离度指数先增大后小幅减小,聚集度持续降低,反映了沼泽湿地从单独紧凑的状态趋向离散化发展。4)人为因素是影响青藏高原东部沼泽湿地面积变化的首要原因,其次受到气候因素的影响,各因子影响力大小依次是牧业生产总值>国民生产总值(GDP)>人口数量>温度>蒸发量。沼泽湿地面积与各因子呈明显的负相关关系,面积随牧业生产总值、GDP、人口数量、温度和蒸发量的增加而减小。

关键词: 沼泽湿地, 青藏高原, 遥感, 景观格局, 动态变化, 驱动因素

Abstract: Wetland degradation and ecosystem structural degeneration caused by climate change and unsustainable human activity have become more common since the middle of the 20th century. It is difficult to carry out a ground-based investigation because of complex spatial mosaic of grassland interspersed with bodies of water and marsh wetlands in the eastern part of the Qinghai-Tibet Plateau. We therefore used remote sensing technology to monitor real-time dynamic change in wetland distribution, to enhance understanding of the changes in the ecological environment of the Qinghai-Tibet Plateau. Using Landsat TM/ETM+/OLI images, the areas of marsh wetlands in the eastern Qinghai-Tibet Plateau were extracted by visual interpretation from 1991, 2000, 2010, and 2016 records. The area change of marsh wetlands, and direction and rate of movement were analyzed based on a dynamic transfer matrix methodology. Landscape indices at the patch level were used to quantify the spatial and temporal dynamics of the marsh wetlands. We also used the grey correlation method together with meteorological data and statistical information to analyze the factors driving marsh wetland change. It was found that: 1) The marsh wetlands are mainly distributed in the northeast of the study region. For the 1991, 2000, 2010 and 2016 analyses, the total marsh wetland areas were 6739.89, 6231.39, 5849.59 and 5649.35 km2, respectively, meaning that a reduction in total area of 1090.54 km2 was recorded during the 26 year study period; 2) The annual rate of wetland loss decreased gradually during the 26 years from -7.54% to -3.42%, and the lost marsh wetlands were mainly transformed into alpine grassland; 3) The number of patches increased initially and then decreased, while patch density continued to increase, indicating an increasing degree of fragmentation of the marsh wetlands. The largest patch index decreased initially and then increased slightly, while the landscape shape index increased initially and then decreased slightly, reflecting the decreasing dominance of marsh wetlands and the complexity of landscape shape. The splitting index increased initially and then decreased slightly, while the aggregation index decreased throughout the study period, reflecting a tendency for marsh wetlands to be fragmented and discrete; 4) Human factors are the primary reason for reduction of marsh wetland area in the eastern Qinghai-Tibet Plateau, followed by climatic factors. Specifically, the factors in order of influence were: Gross output value of animal product, gross domestic product, population increase, temperature and precipitation.

Key words: marsh wetlands, Qinghai-Tibetan Plateau, remote sensing, landscape pattern, dynamic change, driving factors