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Plant Diversity Dataset of Five Typical Vegetation Types in the Qinghai Area of Qilian Mountains National Park (2023)


BAI Lili1,2WANG Wenying2,3DIAO Erlong1,4CHEN Zhirong1,4
1 College of Resources and Environment,Ningxia Normal University,Guyuan 756099,Ningxia,China2 College of Geographical Science,Qinghai Normal University,Xining 810008,China3 College of Life Science,Qinghai Normal University,Xining 810008,China4 Key Laboratory of Soil Ecological Health and Microbial Regulation,Ningxia Normal University,Guyuan 756099,Ningxia,China

DOI:10.3974/geodb.2026.04.09.V1

Published:Apr. 2026

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Key Words:

Qilian Mountains National Park,Qinghai Area,vegetation types,vegetation diversity,2023

Abstract:

The Qilian Mountains National Park has a unique ecosystem and diverse natural landscape. It is one of the 32 priority areas for biodiversity conservation in China and an important gene pool for plateau organisms. The plant diversity dataset of five typical vegetation types in Qinghai area of Qilian Mountains National Park (2023) was developed based on the in situ survey on 5 typical vegetation types (coniferous forests, meadow grasslands, alpine shrubs, alpine meadows, and sparse vegetation of limestone flats) along the vertical belts of the Qilian Mountains in the Qinghai. The dataset includes: (1) geo-location of samples; (2) statistics on dominant species, vegetation coverage, and aboveground biomass of each vegetation type; (3) statistics on the number of plant families, genera, and species in the vertical belt spectrum of the mountain (Xianmi Forest Farm - Lenglongling); (4) species composition and diversity statistics of the five typical vegetation communities. The dataset is archived in .shp and .xlsx formats, and consists of 8 data files with data size of 819 KB (compressed to one file with 300 KB).

Foundation Item:

Ningxia Natural Science Foundation (2026A2647); Ningxia Science and Technology Department (2024BEH04062);

Data Citation:

BAI Lili, WANG Wenying, DIAO Erlong, CHEN Zhirong. Plant Diversity Dataset of Five Typical Vegetation Types in the Qinghai Area of Qilian Mountains National Park (2023)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2026. https://doi.org/10.3974/geodb.2026.04.09.V1.
.

References:


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     [2] Zhang, Y., Xie, Y., Ma, H., et al. The influence of climate warming and humidity on plant diversity and soil bacteria and fungi diversity in desert grassland [J]. Plants, 2021, 10(12): 2580.
     [3] Li, Z. X., Dao, Z. G., Zhao, G. J., et al. Plant community composition and diversity pattern along the altitude gradient in the hand arid river valley of Yuanjiang River [J]. Guangxi Botany, 2024, 44(11): 2141-2151.
     [4] Zhou, B., Li, S., Li, F. U., et al. Plant functional groups asynchrony keep the community biomass stability along with the climate change: a 20-year experimental observation of alpine meadow in eastern Qinghai-Tibet Plateau [J]. Agriculture, Ecosystems & Environment, 2019, 282: 49-57.
     [5] Klein, J. A., Harte, J., Zhao, X. Q., et al. Experimental warming causes large and rapid species loss, dampened by simulated grazing, on the Tibetan Plateau [J]. Ecology Letters, 2004, 7(12): 1170-1179.
     [6] Bai, L. L., Wang, W. Y., De, C., et al. Vertical changes of soil carbon, nitrogen, phosphorus contents and ecological chemical composition characteristics of typical vegetation in the Qilian Mountains [J]. Arid Zone Research, 2024, 41(3): 444-455.
     [7] Wen, J., Qin, R., Zhang, S., et al. Effects of long-term warming on the aboveground biomass and species diversity in an alpine meadow on the Qinghai-Tibetan Plateau of China [J]. Journal of Arid Land, 2020, 12: 252-266.
     [8] Zhou, G. Y., Yin, G. C., Tang, X. L., et al. Biomass Equation for Carbon Storage of Forest Ecosystems in China [M]. Beijing: Science Press, 2000.
     [9] Liu, L. Study on biomass and carbon storage of two shrub communities in the Loess Hilly Region of Qinghai [D]. Xi’an: Shaanxi University of Science and Technology, 2014.

Data Product:

ID Data Name Data Size Operation
1 PlantDiversityQilianMt.2023.rar 300.23KB
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