In Situ Vegetation Dataset from 28 Plots in Qinghai
Lake Basin (2019)
Wang,
X.1,3
Wang, X. Y.2*
Yang, X. Y.1,4 Li,
L.1,3 He, Y. B.5 Sun, J. Q.5
Shi, Q. Q.5
1. Qinghai Provincial Key Laboratory of Geospatial
Information Technology and Application, Xining 810001, China;
2. Qinghai Lake Wetland
Ecosystem National Research Station, Gangcha 812300, China;
3. Qinghai Geographic
Information Industry Development Co., LTD., Xining 810001, China;
4. Qinghai Remote Sensing
Center for Natural Resources, Xining 810001, China;
5. Qinghai Lake National Nature
Reserve Administration, Xining 810001, China
Abstract: The Qinghai
Lake basin,
located northeast of the Qinghai-Tibet Plateau, is a significant natural
and geographical ecological protection area. It forms a crucial component
of the ecological security pattern known as the ??two screens and three regions?? in Qinghai province.
Being a comprehensive
natural and social complex ecosystem with diverse ecological and geographical
elements, the
Qinghai Lake basin is among the 35 priority areas in China for
biodiversity conservation. Additionally, it serves as an
important gene
bank for plateau biological resources. In 2019, this paper??s
authors and other
researchers conducted a vegetation monitoring study
in the basin, focusing
on 28 sample locations. The study collected various data, such as vegetation type,
height, coverage, and biomass, and information on plant families, genera, and species.
This paper presents the 2019 vegetation monitoring dataset for the Qinghai
Lake basin,
which includes the following components: (1) profiles of the monitoring
samples,
including geographic information system data for their locations;
(2) vegetation type structure, covering temperate steppe, temperate desert
steppe, alpine steppe, temperate desert, mountain meadow, lowland meadow, and alpine
meadow; (3) quantitative statistics on 16 major plant families, genera, and species
that represent
zonal vegetation; (4) statistics on vegetation biomass and available biomass in the Qinghai
Lake Nature Reserve and the active area of the Przewalski
gazelle; and (5) annual comparisons of plant structure and biomass among
temperate steppe, temperate desert steppe, alpine steppe, and
temperate desert. The dataset consists of 9 data files with data size of
86.6 KB.
Keywords: Qinghai
Lake basin; vegetation monitoring; 2019
DOI: https://doi.org/10.3974/geodp.2023.01.12
CSTR: https://cstr.escience.org.cn/CSTR:20146.14.2023.01.12
Dataset Availability Statement:
The dataset supporting this paper
was published and is accessible through the Digital
Journal of Global Change Data Repository at: https://doi.org/10.3974/geodb.2021.10.04.V1 or
https://cstr.escience.org.cn/CSTR:20146.11.2021.10.04.V1.
1 Introduction
The Qinghai
Lake basin, situated in the semi-arid plateau area on the northeast margin of the Qinghai-Tibet Plateau, represents a
significant geographical ecotone in China[1]. The basin??s flowing water system possesses complex and diverse characteristics[2], playing a crucial role in curbing desertification and safeguarding the ecological security of the Hehuang Valley agricultural area[3]. Moreover, the species richness within the Qinghai Lake basin surpasses that of the Qinghai-Tibet Plateau, with
775 identified seed plant species accounting for
32.60% of the province??s total[4]. The topography of the Qinghai Lake area is characterized by high altitude and substantial relative elevation differences. Additionally, the presence of the vast Qinghai Lake and diverse landforms contribute to the regulation of the
local climate, resulting in pronounced variations in natural environmental factors such as water,
heat, and soil within the basin. The natural vegetation in the area encompasses five types,
namely shrubland, steppe, desert, intergrass, and marsh and aquatic vegetation, primarily consisting of warm steppe, warm desert steppe, and
alpine marsh meadow near the lake shore[5,6]. The basin holds significant ecological value and serves as a crucial
grassland animal husbandry production base on
the Qinghai-Tibet Plateau[7], supporting the region??s economic development in this sector. Therefore, monitoring and
investigating the status of the
grassland ecosystem in the Qinghai Lake basin is of utmost
importance for ecological environment protection, sustainable grassland
utilization, and the advancement of animal husbandry on the plateau.
This dataset is derived from the vegetation monitoring sample points[8] of the Qinghai Lake National Nature Reserve
Administration (Figure 1), spanning multiple years. The monitoring period
for this specific dataset ranges from August 2 to August 12, 2019. Monitoring
was conducted at 28 fixed points, including locations such as Daotang River wetland, Ganzi River,
Anhuan Lake, Ganzi River wetland, Hada Tan, Hargai, Haixin Mountain slope,
Heima River wetland, Heima River towards Hu village, Hudong sheep farm, Jiermeng, Jiangxi
Gulxiashe village, Ketu, Kuerma, Cormorant island summit, Qingbaya Huo, Quanwan wetland, Shadao
East, Shadao wetland, Shaliu River, Shengge, Talexuan Guo, Xianggong village, and Xiao Bohu and Yuanzhe.
2 Metadata of the Dataset
Table 1 presents the metadata information for the In situ dataset on vegetation from 28 sample sites in Qinghai Lake
basin (2019) [9].
3 Vegetation Monitoring Methods
Figure 1 In situ monitoring
map of Qinghai Lake basin in 2019
|
The vegetation monitoring points primarily consist of ground
monitoring points established in accordance with the objectives of vegetation investigation
and monitoring within the Qinghai Lake Nature Reserve. These monitoring points are strategically positioned based on the technical requirements for point layout, resulting in the establishment of a comprehensive vegetation monitoring
network within the Qinghai Lake area.
3.1 Rules for Setting
Monitoring Points
(1)
The selected plots were chosen to exhibit typical environmental and vegetation
charac teristics representative of their respective distribution types. The
vegetation composition and taxonomy were carefully assessed to ensure accurate
type classification.
Table 1 Metadata summary of In situ
dataset on vegetation from 28 sample sites in Qinghai Lake basin (2019)
Article
|
description
|
Dataset
name
|
In situ
dataset on vegetation from 28 sample sites in Qinghai Lake basin (2019)
|
Dataset
short name
|
VegetationQinghaiLakeBasin2019
|
Authors
|
Wang, X. Y.,
Qinghai Lake Wetland Ecosystem National Positioning Observation and Research
Station, Qinghai Province, 245003744@qq.com
Sun, J. Q.,
Qinghai Lake National Nature Reserve Administration, 625764587@qq.com
Chen, K. L., Qinghai Normal
University, ckl7813@163.com
Chen, Z. R., Qinghai Normal
University, 2776246502@qq.com
Ma, Y. X., Qinghai Normal University, 346404980@qq.com
|
Geographical
area
|
Qinghai
Lake basin
|
Data year
|
2019
|
|
Data format
|
.shp, .xlsx
|
Data sizes
|
86.6 KB
|
Data files
|
Consists of
nine data files
|
Foundations
|
Qinghai
Province (2020-ZJ-Y06); Ministry of Science and Technology of P. R. China
(2019QZKK0405); National Natural Science Foundation of China (41661023)
|
Data
publisher
|
Global
Change scientific research data publishing System http://www.geodoi.ac.cn
|
Address
|
No.
11A, Datun Road, Chaoyang District, Beijing 100101, China
|
Data
sharing policy
|
Data from the Global Change
Research Data Publishing & Repository includes metadata, datasets
(in the Digital Journal of Global Change Data Repository), and
publications (in the Journal of Global Change Data & Discovery). Data sharing policy includes: (1) Data
are openly available and can be free downloaded via the Internet; (2) End
users are encouraged to use Data subject to citation; (3)
Users, who are by definition also value-added service providers, are welcome
to redistribute Data subject to written permission from the GCdataPR Editorial
Office and the issuance of a Data redistribution license; and (4)
If Data
are used to compile new datasets, the ??ten per cent principal?? should be
followed such that Data records utilized should not
surpass 10% of the new dataset contents, while sources should be clearly
noted in suitable places in the new dataset[10]
|
Communication and searchable system
|
DOI, CSTR, Crossref, DCI, CSCD,
CNKI, SciEngine, WDS/ISC, GEOSS
|
|
|
|
|
|
|
|
|
(2) During the plot selection process,
particular attention was given to capturing the various patterns and trends of dominant species and community-building species within the main vegetation
types.
(3) For the various vegetation types distributed along
the vertical spectrum of the mountains, sample plots were
established in the middle of each vertical distribution
belt, maintaining relative consistency in slope, slope direction, and slope position. In flat areas, plots were
positioned on the flattest sections. For plots within shrublands, the selection was made in areas with moderate shrubland coverage.
(4) In sections with concealed or obscured regional
vegetation distributions, sample plots were placed in areas with relatively uniform
environmental conditions within that section.
(5) Sample plots were
distributed across different geomorphic types to comprehensively
represent the various vegetation types found under distinct terrain and topographic conditions.
3.2 Field Monitoring
The investigation encompassed
vegetation types, bird populations, and Przewalski??s
antelope populations at the sites mentioned above. For the vegetation type survey and
monitoring, representative sample sites were selected within each region as the focus of vegetation assessment. Detailed records
were made, including the administrative region of the sample sites, vegetation type, altitude, geographic location, landform characteristics,
soil
properties, hydrological conditions, hydrogeological
conditions, utilization methods, and utilization status. Random selection
was employed to establish one vegetation structure
sample and ten plant frequency samples. Aboveground
vegetation biomass was measured in Przewalski??s
antelope habitats and breeding sites. Bird and Przewalski??s antelope populations were
surveyed and recorded using
single and binocular observations. Additionally, plant
specimens were collected during the investigation.
Following sample selection principles, 28 vegetation survey and monitoring points were established within
the Qinghai Lake Nature Reserve. The primary focus
of these points was on the habitats and breeding grounds of birds within the reserve. Accordingly, the vegetation types selected for surveying were primarily those closely associated with bird habitats
and breeding grounds, such as the wetlands surrounding Qinghai Lake. Most of the samples consisted of marshes and salt meadows, while a smaller portion
represented warm grassland vegetation types.
4 Data Results
4.1 Dataset Composition
The
dataset includes the following: (1) monitoring plot profile and plot location
data; (2) vegetation types (temperate steppe, temperate desert steppe, alpine steppe, temperate
desert, mountain meadow, lowland meadow, and alpine meadow); (3) quantitative statistics of 16 major plant families, genera, and species of zonal vegetation; (4)
statistics of vegetation biomass and available biomass in Qinghai Lake Nature
Reserve and Przewalski gazelle active area. (5) annual comparison of plant structure
and biomass in temperate steppe, temperate desert steppe, alpine steppe, and temperate desert. The dataset was archived in .shp and .xlsx formats and consists of
nine data files totaling 86.6 KB (compressed into two files of 74.9 KB).
4.2 Data Results
(1)
In this survey, a total of 28 sample sites were established across
25 regions, including Egg island,
Cormorant island, and
Haixinshan island (Figure 1). These sample sites consisted of seven sites categorized as warm steppe, one site as
warm desert steppe, two sites as
alpine steppe, two sites as
warm desert, one site as
mountain meadow, one site as
lowland meadow, and 14 sites as alpine meadow.
(2) The vegetation monitoring results are as follows: the average
height of the reproductive branches of plants was 22.2 cm, while the height of the dominant species was 29.9 cm. The height of vegetative branches measured 12.0 cm, with the dominant species reaching a height of 13.9 cm.
The total vegetation coverage was 76%, and the coverage of dominant species was
29%, which is 4% higher than that of
2018. The vegetation biomass recorded was 2,117.12 kg/hm2, with grasses and Cyperaceae
accounting for 54.79% of the total. Notably, the vegetation
biomass experienced a decrease of 33.76% compared to 2018, which could be
attributed to the low rainfall observed in 2019.
(3) In 2019, the
vegetated livestock carrying capacity in the active area of Przewalski showed
a significant increase of 47.54% compared to 2018, reaching a total of 134,821 sheep units. Among the active
areas, the Hudong active area exhibited the highest carrying capacity, capable of supporting 91,418 sheep units. This marked an increase of
57,932 sheep units compared to the previous year. On the other hand, the Cormorant island activity area had the lowest carrying
capacity, accommodating only 1,509 sheep units.
(4) When comparing the vegetation biomass of the seven different vegetation types with the average values observed over the years, certain types, such as Achnatherum, Stipa, and Stipa with golden dew, displayed an
increasing trend. However, the biomass of other vegetation
types exhibited a decreasing trend. Considering the vegetation growth across the entire region, it was still considered a favorable year. Nevertheless,
specific areas, like the Ganzi River area, have experienced drought and
water scarcity, resulting in sparse vegetation growth and consistently low biomass yield. Furthermore, the vegetation on Haixinshan Island has been subject to long-term
restrictions, leading to the accumulation of a substantial layer of dead vegetation that hinders the normal
growth and development of plants. Consequently, the height,
coverage, and biomass of vegetation on the island have
experienced varying degrees of decline.
(5) The average
total ground biomass of the ten vegetation types in Qinghai
Lake Nature Reserve was recorded at 2,153.3 kg/hm2. Among these, grasses contributed significantly, with a biomass of 1,128.3 kg/hm2, accounting for
52.04% of the total biomass. Seperaceae accounted for 96.7 kg/hm2, making up 4.46% of the total. Legumes
registered a biomass of 162.9 kg/hm2, representing 7.51% of the total, while other plants had a biomass of 780.4 kg/hm2, constituting 35.99% of the total
biomass.
5 Discussion
According
to the vegetation monitoring sample points of the Qinghai
Lake National Nature Reserve Administration over the years, 28 sample sites
were established in 25 regions, such as Guandao island,
Cormorant island, and Haixinshan island, for a period of 11 days from August 2, 2019,
to August 12, 2019 (Figure 1). Among these sites, seven were temperate grasslands, one was a temperate desert
grassland, and two were alpine grasslands.
Additionally, there were two
warm desert samples, one mountain meadow sample, one lowland meadow sample, and 14 alpine meadow samples. Plant
classification and identification are crucial aspects of the vegetation survey and monitoring process. Accurate identification of vegetation species and names is a significant technical challenge. Therefore, the expertise of vegetation monitoring workers in plant classification and identification is of
utmost
importance.
Furthermore, vegetation
monitoring should be integrated with the ecological environment
protection and comprehensive treatment project of Qinghai Lake to collectively
accomplish the ecological monitoring of vegetation. This will provide a scientific foundation for the protection and comprehensive
treatment project of Qinghai Lake??s ecological
environment. Serving as the fundamental dataset for
vegetation research in the Qinghai Lake basin, this dataset can serve as a reference for studying ecological remote
sensing and other related subjects in the basin. It can also provide a data basis for the Qinghai Lake basin??s response model to global changes and offer a scientific groundwork for the ecological construction, vegetation restoration, and sustainable development of the Qinghai Lake basin.
Author Contributions
Wang, X. and Wang, X. Y. did the overall design
for the development of the dataset; Yang, X. Y., Li, L., Sun, J. Q., Shi, Q. Q.
and He, Y. B. collected and processed all the data. Wang, X. wrote the data
paper.
Conflicts of Interest
The
authors declare no conflicts of interest.
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