The data set was obtained from the background survey of wildlife diversity in Three River Source National Park by Northwest Institute of Plateau Biology, Chinese Academy of Sciences. The time range of the data set is 2017, and the survey area is Three River Source National Park. The survey species include a variety of rare wildlife such as Equus kiang, Canis lupus, Vulpes vulpes, Cervus elaphus, Accipiter nisus, Phoenicurus erythrogastrus, Prionailurus bengalensis, Buteo hemilasius, Procapra picticaudata, Tetraogallus tibetanus, Perdix hodgsoniae, Falco cherrug, etc.
ZHANG Tongzuo
Taking Landsat series data as the main data source, including KH in 1965 (only including Gurinai and Guaizi Lake), MSS in 1975, TM in 1990, 1995, 2006 and 2010, and ETM in 2000. Before information extraction, remote sensing images are preprocessed by image synthesis, mosaic, fusion, geometric correction and image enhancement. In the process of correction, ETM + image in 2000 is corrected by 1:100000 topographic map and used as reference image. The 4, 3 and 2 band standard pseudocolor synthesis scheme is selected for image synthesis; during correction, 7 × 8 control points are evenly selected on each image, and the average positioning error is less than 1 pixel, that is, the ground distance is less than 30m. In other years, the datum image of 2000 is used as the reference image for image registration, so that the pixels with the same name on different images have the same geographical coordinates. After correction and registration, the whole image maintains the 30 m spatial resolution of TM. Through field correction, the accuracy of qualitative analysis can be ensured to be over 95%.
XIAO Shengchun
The data set contains the rare animal survey data for the Sanjiangyuan area from 2016 to 2017, including the latitude and longitude of the survey site, the length of the sample line, animal discovery time, animal names, quantity, location of the occurrence, type of habitat, affiliated families, etc.
HU Linyong, ZHANG Tongzuo, ZHANG Tongzuo,
The global land surface characteristic parameter (LAI) product was used with a spatial resolution of 5 km. The product uses generalized regression neural network method to retrieve Lai from AVHRR surface reflectance data. In this study, 12 issues of Lai data products from June to August of each year in five Central Asian countries, Mongolia and Northern China from 1981 to 2017 were downloaded from the national science and technology infrastructure platform National Earth System Science Data Center. These images are cropped by ArcGIS software, and the maximum value is calculated to obtain the spatiotemporal data set of the largest Lai. Among them, five Central Asian countries include Turkmenistan, Kyrgyzstan, Kazakhstan, Tajikistan and Uzbekistan; northern China refers to the area north of the Yangtze River in China.
ZHANG Na
The global land surface characteristic parameter (LAI) product was used with a spatial resolution of 5 km. The product uses generalized regression neural network method to retrieve Lai from AVHRR surface reflectance data. In this study, 12 issues of Lai data products from June to August of each year in five Central Asian countries, Mongolia and Northern China from 1981 to 2017 were downloaded from the national science and technology infrastructure platform National Earth System Science Data Center. These images are cropped by ArcGIS software, and the maximum value is calculated to obtain the spatiotemporal data set of the largest Lai. Among them, five Central Asian countries include Turkmenistan, Kyrgyzstan, Kazakhstan, Tajikistan and Uzbekistan; northern China refers to the area north of the Yangtze River in China.
ZHANG Na
This data is the hydrological data of kuzhan hydrological station in the middle reaches of the Xier river. The station is jointly built by Urumqi Institute of desert meteorology of China Meteorological Administration, Institute of water energy and ecology of Tajik National Academy of Sciences and Tajik hydrometeorological Bureau. The data can be used for scientific research such as water resources assessment and water conservancy projects in Central Asia. Data period: November 2, 2019 to December 5, 2020. Data elements: Hourly velocity (M / s), hourly water level (m) and hourly rainfall (m) Site location: 40 ° 17 ′ 38 ″ n, 69 ° 40 ′ 18 ″ e, 320m
ZHANG Na
The global land surface characteristic parameter (LAI) product was used with a spatial resolution of 5 km. The product uses generalized regression neural network method to retrieve Lai from AVHRR surface reflectance data. In this study, 12 issues of Lai data products from June to August of each year in five Central Asian countries, Mongolia and Northern China from 1981 to 2017 were downloaded from the national science and technology infrastructure platform National Earth System Science Data Center. These images are cropped by ArcGIS software, and the maximum value is calculated to obtain the spatiotemporal data set of the largest Lai. Among them, five Central Asian countries include Turkmenistan, Kyrgyzstan, Kazakhstan, Tajikistan and Uzbekistan; northern China refers to the area north of the Yangtze River in China.
ZHANG Na
This data set contains 2018 global forest fire case data for the whole year and 2019, including the forest fire in California in November 2018, the forest fire in Attica, Greece in July 2018, and the forest fire in Shanxi Province in March 2019. Case data. Specific data include: fire intensity data of the monitoring range and data of vegetation index changes before and after the disaster. The data set is mainly used to describe the occurrence, development, impact and recovery of major global forest fire events in the first half of 2018-2019. The data mainly comes from NASA official website and EM-DAT database, it was processed by statistical and spatial analysis methods using EXCEL and ArcGIS tools. The data source is reliable, the processing method is scientific and rigorous, and it can be effectively applied to global (forest fire) disaster case analysis research.
YANG Yuqing, GONG Adu, WU Jianjun, ZHOU Hongmin
1. The grassland animal husbandry production and management policies in the study area from 1954 to 2012 mainly include: 1) the time series of the formation and evolution of various policies; 2) the key policies related to herdsman's livestock activities and grassland management and utilization. 2. Residents' perception and response to pastoral socio-economic development policies, grassland management systems, ecological compensation policies, ecological restoration projects, and ecological environment status quo.
ZHAO Chengzhang
The data set includes the spatial distribution of grass yield in the Qinghai-Tibetan Plateau in 1980, 1990, 2000, 2010, and 2017. The gross primary productivity (GPP) of grassland in the Qinghai-Tibetan Plateau was simulated based on the ecological hydrological dynamic model VIP (vegetation interface process) with independent intellectual property of Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences. The net primary productivity (NPP) was estimated by empirical coefficient, and converted it into dry matter, and then the hay yield was estimated by root-shoot ratio. The spatial resolution is 1km. The data set will provide the basis for grassland resource management, development, utilization and the formulation of the strategy of "grass for livestock".
MO Xingguo
The data includes the county-level data of characteristic agriculture distribution in the Qinghai Tibet Plateau, which lays the foundation for the spatial distribution and development of characteristic agriculture in the Qinghai Tibet Plateau. The data comes from the planning documents of each province in the Tibetan Plateau region, such as the development plan of the characteristic agricultural products base of the Tibetan Plateau (2015-2020). The data is the distribution of characteristic agriculture at the county level, including four kinds of agricultural products: highland barley, yak, sheep and wolfberry. The spatialization of main agricultural products of characteristic agriculture at the county level is realized. The time range is set to 2015-2020, referring to the planning and construction time of characteristic agriculture in each province in the data source. The data can be applied to the research on the spatial distribution of characteristic agriculture and the development of characteristic agriculture in the future.
SHI Wenjiao
The content of this data set is the measurements of body weight and body size (body height, body length, chest circumference, tube circumference) of 11 representative yak populations in Qinghai pastoral area at 2018. All the metadata comes from the work of body weight monitoring of yaks in Qinghai pastoral area at 2018, by the Northwest Institute of Plateau Biology, Chinese Academy of Sciences and Qinghai Academy of Animal Husbandry and Veterinary Sciences. The data set is named by “Monitoring Data Set of Body Weights of Traditional Grazing Yaks in Qinghai Pastoral Area (2018)”, consisting of 11 worksheets. The names and contents of worksheets are as follows: 1. Haiyan-Halejing (167 yaks in halejing Mongolian Town, Haiyan County, Haibei Tibetan Autonomous Prefecture); 2. Qilian-Mole (69 yaks in Mole Town, Qilian County, Haibei Tibetan Autonomous Prefecture); 3. Qilian-Yeniugou (42 yaks in Yeniugou Town, Qilian County, Haibei Tibetan Autonomous Prefecture); 4. Qilian-Yanglong (104 yaks in Yanglong Town, Qilian County, Haibei Tibetan Autonomous Prefecture); 5. Qilian-Ebao (28 yaks in Ebao Town, Qilian County, Haibei Tibetan Autonomous Prefecture); 6. Tianjun-Xinyuan (38 yaks in Xinyuan Town, Tianjun County, Haixi Mongolian and Tibetan Autonomous Prefecture); 7. Tianjun-Longmen (100 yaks in Longmen Town, Tianjun County, Haixi Mongolian and Tibetan Autonomous Prefecture); 8. Gande-Ganlong (36 yaks in Ganglong Town, Gande County, Guoluo Tibetan Autonomous Prefecture); 9. Guinan-Taxiu (70 yaks in Taxiu Town, Guinan County, Hainan Tibetan Autonomous Prefecture); 10. Henan-Kesheng (73 yaks in Kesheng Town, Henan Mongolian Autonomous Country, Huangnan Tibetan Autonomous Prefecture); 11. Ledu-Dala (50 yaks in Dala Town, Ledu District, Haidong City). This data set comprehensively evaluates the growth performance of yaks grazing in alpine meadow under the current ecological environment through the measurement of weight and body size data in the representative areas of Qinghai pastoral area. The data set can be compared with the growth characteristics of representative populations of Qinghai yaks measured in 1981 and 2008 recorded in 1983 and 2013, and the degradation index of growth performance of yaks grazing in Qinghai pastoral area can be obtained, which is helpful to assess the impact of ecological environment changes on the growth and production performance of grazing livestock.
JIA Gongxue, YANG Qien, Tianwei XU
The data set of prokaryotic microorganism distribution in the snow and ice of the Arctic Antarctic and the Tibetan Plateau provides the bacterial 16S ribosomal RNA gene sequence collected by the experimental group led by Yongqin Liu from the NCBI database during 2010 to 2018. The keywords for NCBI database search are Antarctic, Arctic Tibetan, and Glacier. The collected sequences were calculated using the DOTOUR software to obtain the similarities between sequences, the sequences with similarities above 97% were clustered into one OTU, and the OTU representative sequence was defined. The OTU representative sequence was compared with the RDP database by the "Classifier" software and was identified as level one when the reliability exceeded 80%. After acquiring the sequence, the GPS coordinates of the sample were obtained by reading the sample information in the sequence file. These data contain the sequence of 16S ribosomal RNA gene fragments for each sequence, evolutionary classification, and sample GPS coordinates. Compared with sequences based on high-throughput sequencing, these data have a longer sequence and more accurate classification. It is significant for comparing the evolutionary information of three-pole microorganisms and understanding the evolution of psychrophilic microorganisms.
JI Mukan
This data is the spatial distribution map of ecological shelters in Nursultan, the capital of Kazakhstan in 2018. The types of features in the map mainly include shelter forests, roads, buildings, lakes and rivers. The data source is four sentinel images in August 2018, with a resolution of 10 meters. At the same time, overlay the vector map of OSM global features. The data set is more accurate after correction. Through visual interpretation and field investigation, the extraction of shelter forest spot has high precision. The data reflects the spatial distribution of urban ecological shelters in Nursultan, the capital of Kazakhstan. At the same time, it has an important reference value for the long-term monitoring of the spatial and temporal pattern of shelter forests.
WANG Yongdong
This dataset subsumes sustainable livestock carrying capacity in 2000, 2010, and 2018 and overgrazing rate in 1980, 1990, 2000, 2010, and 2017 at county level over Qinghai Tibet Plateau. Based on the NPP data simulated by VIP (vehicle interface process), an eco hydrological model with independent intellectual property of the institute of geographic sciences and nature resources research(IGSNRR), Chinese academy of Sciences(CAS), the grass yield data (1km resolution) is obtained. Grass yield is then calculated at county level, and corresponding sustainable livestock carring capacity is calculated according to the sustainable livestock capacity calculation standard of China(NY / T 635-2015). Overgrazing rate is calculated based on actual livestock carring capacity at county level.The dataset will provide reference for grassland restoration, management and utilization strategies.
MO Xingguo
The glacial bacterial resource database of the Tibetan Plateau provides the bacterial 16S ribosomal RNA gene sequences of several glaciers, which are seven glaciers of the Tibetan Plateau separated by an experimental group led by Yongqin Liu during 2010 to 2018 (East Rongbuk Glacier of Mt. Qomolangma, Tianshan Glacier No.1, Guliya Glacier, Laohugou Glacier, Muztagh Ata Glacier, Qiyi Glacier and Yuzhufeng Glacier), the Malan Glacier separated by Shurong Xiang and the Puruogangri Glacier separated by Xinfang Zhang. After the glacier samples were collected, they were taken to the Ecological Laboratory of the Institute of Tibetan Plateau Research of the Chinese Academy of Sciences in Beijing and the National Cryosphere Laboratory in Lanzhou. After applying the spread plate method, the samples were cultured at different temperatures (4-25 °C) for 20 days to 90 days, and single colonies were picked out for purification. After the DNA was extracted from the isolated bacteria, the 16S ribosomal RNA gene fragment was amplified with 27F/1492R primer and sequenced using the Sanger method. The 16S ribosomal RNA gene sequence was compared with the RDP database using the "Classifier" software and identified as level one when the reliability exceeded 80%. These data contain the 16S ribosomal RNA gene fragment sequence and glacier sources of each sequence. Compared with sequences based on high-throughput sequencing, these data have a longer sequence and more accurate classification and can better serve in glacier microbiology research.
JI Mukan
To investigate the paternal genetic structure of Tibetans from Lhasa, 1029 male samples were collected from Lhasa, Tibet. Firstly, SNP genotyping was performed to allocate samples into haplogroups. To further evaluate the genetic diversity of the major Y-chromosomal haplogroup in Tibetan populations from Lhasa, eight commonly used Y-chromosomal STR (short tandem repeat) loci (DYS19, DYS388, DYS389I, DYS389II, DYS390, DYS391, DYS392, and DYS393) were genotyped using fluorescence-labeled primers with an ABI 3130XL Genetic Analyzer (Applied Biosystems, USA). The results indicated that haplogroup D-M174 displayed highest frequency in Lhasa Tibetans (56.56%, the majority of its sublineages were D3*-P99), followed by haplogroups O-M175 (30.71%, with most of the samples belonging to O3a3c1-M117). Another relatively rare lineages in Lhasa Tibetans were N-M231 (5.15%, especially its sublineage N1*-LLY22G), C-M130 (2.62%), R-M207 (2.53%), Q (1.55%), J (0.68%), K-M, and T. Further analysis indicated that the Lhasa Tibetans’ Y chromosome haplogroups have ages within different periods, including >30 kya, LGM, post-LGM, Holocene, indicating occupation of modern humans in different periods.
KONG Qingpeng, QI Xuebin
The data set of bacterial diversity in Tibetan soil provides the microbial distribution characteristics of the soil surface (0-2 cm) of the Tibetan Plateau. The samples were collected from July 1st to July 15th, 2015, from three types of ecosystems: meadows, grasslands and desert. The soil samples were stored in ice packs and transported to the Ecological Laboratory of the Institute of Tibetan Plateau Research in Beijing. The DNA from the soil was extracted using an MO BIO Power Soil DNA kit. The soil surface samples were stored in liquid nitrogen after collection, shipped to the Sydney laboratory, and then extracted using a Fast Prep DNA kit. The extracted DNA samples adopted 515F (5'-GTGCCAGCMGCCGCGGTAA-3') and 909r (5'-GGACTACHVGGGTWTCTAAT-3') to amplify the 16S rRNA gene fragments. The amplified fragments were sequenced by the Illumina Miseq PE250 method, and the raw data were analyzed using Mothur software. The sequences with poor sequencing quality were first removed; the sequences were sorted, and the chimeric sequences were removed. The similarities between the sequences were then calculated, the sequences with similarities above 97% were clustered into one OTU, and the OTU representative sequence was defined. The OTU representative sequence was compared with the Silva database and identified as level one when the reliability exceeded 80%. The microbial diversities in these data on the Tibetan Plateau were systematically compared, which made them significant to the study of the microbial distribution on the Tibetan Plateau.
JI Mukan
From April 2020 to August 2020, sub project 3 collected 51 ear tissue samples of Qinghai fine wool sheep distributed in Haiyan County, Haixi Mongolian and Tibetan Autonomous Prefecture, Qinghai Province, 50 blood samples of Oula sheep in Tongde County, Hainan Tibetan Autonomous Prefecture, 50 blood samples of yak in Tongde County, Hainan Tibetan Autonomous Prefecture, 60 blood samples of Haidong donkey in Datong Hui and Tu Autonomous County, Xining City, and tissue samples A total of 211 copies. At the same time, the information of body length, body height, weight, age and gender, as well as the data of economic traits such as litter size, wool fineness and wool length were recorded. The individual photos were taken, and the information of feeding mode and epidemic situation were obtained through questionnaire survey.
TIAN Fei
To analyzing the distribution pattern and genetic background of domain domestic animals in Qinghai-Tibet Plateau and surrounding regions and building a genetic resources bank of animals and plants in Pan-Third Pole, we collected 343 domain domestic animal samples in 2018, including Tibet pigs, Tibet dogs, Tibet sheep and Tibet chickens in Yunnan, Sichuan and Tibet Province. By applying mitochondrial DNA sequencing on 159 chickens from northwest Yunnan and southeast Tibet, genome resequencing on 11 wild and domestic pigs and GBS sequencing on 193 domestic cattle, a batch of genetic and genome data were generated. It provides basic genetic data to analysis on domestication, immigration and expansion of domestic animals in Qinghai-Tibet Plateau. Meanwhile it helps better understand the adaption of domestic animals to Qinghai-Tibet Plateau environment.
YIN Tingting, PENG Minsheng
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