An Improved Method for Monitoring Multiscale Plant Species Diversity of Alpine Grassland Using UAV: A Case Study in the Source Region of the Yellow River, China

被引:3
|
作者
Sun, Yi [1 ]
Yuan, Yaxin [1 ]
Luo, Yifei [1 ]
Ji, Wenxiang [1 ]
Bian, Qingyao [1 ]
Zhu, Zequn [1 ]
Wang, Jingru [1 ]
Qin, Yu [2 ]
He, Xiong Zhao [3 ]
Li, Meng [1 ]
Yi, Shuhua [1 ]
机构
[1] Nantong Univ, Inst Fragile Eco Environm, Sch Geog Sci, Nantong, Peoples R China
[2] Chinese Acad Sci, Northwest Inst Eco Environm & Resources, State Key Lab Cryospher Sci, Lanzhou, Peoples R China
[3] Massey Univ, Coll Sci, Sch Agr & Environm, Palmerston North, New Zealand
来源
基金
中国国家自然科学基金;
关键词
species diversity; diversity monitoring; unmanned aerial vehicle; FragMAP; multiscale diversity; TIBETAN PLATEAU; GRAZING EXCLUSION; CLIMATE-CHANGE; BIODIVERSITY; RICHNESS; PRODUCTIVITY; CLASSIFICATION; REGRESSION; GRADIENTS; RESPONSES;
D O I
10.3389/fpls.2022.905715
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
Plant species diversity (PSD) is essential in evaluating the function and developing the management and conservation strategies of grassland. However, over a large region, an efficient and high precision method to monitor multiscale PSD (alpha-, beta-, and gamma-diversity) is lacking. In this study, we proposed and improved an unmanned aerial vehicle (UAV)-based PSD monitoring method (UAV(B)) and tested the feasibility, and meanwhile, explored the potential relationship between multiscale PSD and precipitation on the alpine grassland of the source region of the Yellow River (SRYR), China. Our findings showed that: (1) UAV(B) was more representative (larger monitoring areas and more species identified with higher alpha- and gamma-diversity) than the traditional ground-based monitoring method, though a few specific species (small in size) were difficult to identify; (2) UAV(B) is suitable for monitoring the multiscale PSD over a large region (the SRYR in this study), and the improvement by weighing the dominance of species improved the precision of alpha-diversity (higher R-2 and lower P values of the linear regressions); and (3) the species diversity indices (alpha- and beta-diversity) increased first and then they tended to be stable with the increase of precipitation in SRYR. These findings conclude that UAV(B) is suitable for monitoring multiscale PSD of an alpine grassland community over a large region, which will be useful for revealing the relationship of diversity-function, and helpful for conservation and sustainable management of the alpine grassland.
引用
收藏
页数:12
相关论文
共 34 条
  • [1] Soil and plant responses to degradation of alpine grassland in source region of the Yellow River
    Peng, Fei
    Wang, Tao
    Xue, Xian
    Zhang, Fang
    SCIENCES IN COLD AND ARID REGIONS, 2010, 2 (04): : 364 - 370
  • [2] Plant Species Diversity Assessment in the Temperate Grassland Region of China Using UAV Hyperspectral Remote Sensing
    Wang, Hong
    Feng, Chunyong
    Li, Xiaobing
    Yang, Yalei
    Zhang, Yao
    Su, Jingru
    Luo, Dingsheng
    Wei, Dandan
    He, Yixiao
    DIVERSITY-BASEL, 2024, 16 (12):
  • [3] Human activities dominant the distribution of Kobresia pygmaea community in alpine meadow grassland in the east source region of Yellow River, China
    Lv, Yanyan
    Sun, Yi
    Yi, Shuhua
    Meng, Baoping
    FRONTIERS IN ECOLOGY AND EVOLUTION, 2023, 11
  • [4] Impacts of climate change and human activities on the aboveground production in alpine grasslands: a case study of the source region of the Yellow River, China
    Xu, Hao-jie
    Wang, Xin-ping
    Zhang, Xiao-xiao
    ARABIAN JOURNAL OF GEOSCIENCES, 2017, 10 (01)
  • [5] Impacts of climate change and human activities on the aboveground production in alpine grasslands: a case study of the source region of the Yellow River, China
    Hao-jie Xu
    Xin-ping Wang
    Xiao-xiao Zhang
    Arabian Journal of Geosciences, 2017, 10
  • [6] Evaluation of multisource precipitation input for hydrological modeling in an Alpine basin: a case study from the Yellow River Source Region (China)
    Gu, Pengfei
    Wang, Gaoxu
    Liu, Guodong
    Wu, Yongxiang
    Liu, Hongwei
    Jiang, Xi
    Liu, Tao
    HYDROLOGY RESEARCH, 2022, 53 (02): : 314 - 335
  • [7] Comprehensive Research on Remote Sensing Monitoring of Grassland Degradation: A Case Study in the Three-River Source Region, China
    Zhang, Ying
    Zhang, Chaobin
    Wang, Zhaoqi
    An, Ru
    Li, Jianlong
    SUSTAINABILITY, 2019, 11 (07)
  • [8] Retrieval of the surface evapotranspiration patterns in the alpine grassland-wetland ecosystem applying SEBAL model in the source region of the Yellow River, China
    Li, Zhouyuan
    Liu, Xuehua
    Ma, Tianxiao
    Kejia, De
    Zhou, Qingping
    Yao, Bingquan
    Niu, Tianlin
    ECOLOGICAL MODELLING, 2013, 270 : 64 - 75
  • [9] A framework for dynamic assessment of soil erosion and detection of driving factors in alpine grassland ecosystems using the RUSLE-InVEST (SDR) model and Geodetector: A case study of the source region of the Yellow River
    Li, Hucheng
    Chen, Jianjun
    Ling, Ming
    Chen, Zizhen
    Lan, Yanping
    Huang, Qinyi
    Li, Xinhong
    You, Haotian
    Wang, Feng
    Han, Xiaowen
    Zhou, Guoqing
    ECOLOGICAL INFORMATICS, 2025, 85
  • [10] Predicting the Distribution of Oxytropis ochrocephala Bunge in the Source Region of the Yellow River (China) Based on UAV Sampling Data and Species Distribution Model
    Zhang, Xinyu
    Yuan, Yaxin
    Zhu, Zequn
    Ma, Qingshan
    Yu, Hongyan
    Li, Meng
    Ma, Jianhai
    Yi, Shuhua
    He, Xiongzhao
    Sun, Yi
    REMOTE SENSING, 2021, 13 (24)