The data set is the measured data, which is obtained through the three-year field survey from 2019 to 2021. There are 59 sample points and 590 quadrats in total. It includes the grassland growth status of different grassland types in 14 typical counties in Qilian Mountain Area (Aksai, Dachaidan, Delingha, Dulan, Gangcha, Gaotai, Golmud, Huangcheng Town, Mangya City, Menyuan County, Qilian County, Shandan County, Sunan County and Wulan county). The indicators include species diversity, dominant species, edible forages, poisonous weeds Dry weight of edible forage and dry weight of poisonous weeds. This data set investigates edible forage and poisonous weeds separately, which can provide accurate data support for calculating effective livestock carrying capacity.
PENG Zechen
Using the quadrat survey method, natural grassland, fenced natural grassland and artificial grassland are arranged in the source area of rivers and lakes in Tibet to investigate grassland type, coverage, species composition, aboveground biomass, soil temperature, soil bulk density, soil water content, soil texture, soil pH, soil organic matter, soil total P and soil total K, The characteristics of vegetation community and soil quality under different grassland utilization modes were compared and analyzed to study the impact of grassland utilization on vegetation and soil environment. The data collection year is from August 2019 to August 2021, and the collection location is the source area of Jianghu and surrounding areas. The altitude of the sample point is the GPS recorded data, the vegetation type is the mapping of the sample point in the vegetation map of China, the soil temperature and humidity is the soil 4 parameter speedometer data, the soil bulk density is the measured data of the sample point, the number of herbaceous species, grassland coverage and aboveground biomass are the sample survey data, and the soil particle size, organic matter and nutrient content are the sample laboratory analysis data.
XU Zengrang, JIN Mingming , QIAO Tian
The data were collected from the sample plot of Haibei Alpine Meadow Ecosystem Research Station (101°19′E，37°36′N，3250m above sea level), which is located in the east section of Lenglongling, the North Branch of Qilian Mountain in the northeast corner of Qinghai Tibet Plateau. Alpine meadow is the main vegetation type in this area. The data recorded the light, air temperature and humidity, wind temperature and wind speed above the alpine plant canopy. The radiation intensity above the alpine plant canopy was recorded by LI-190R photosynthetic effective radiation sensor (LI-COR, Lincoln NE, USA) and LR8515 data collector (Hioki E. E. Co., Nagano, Japan), and the recording interval was once per second. S580-EX temperature and humidity recorder (Shenzhen Huatu) and universal anemometer are used (Beijing Tianjianhuayi) record the daily dynamics of air temperature and humidity, wind temperature and wind speed every three seconds. The recording time is from 10:00 on July 13 to 21:00 on August 17, Beijing time. Due to the need to use USB storage time and replace the battery every day, 3-5min of data is missing every day, and the missing time period is not fixed. At present, the data has not been published. Through research on the data The data can further explore the microenvironment of alpine plant leaves and its possible impact on leaf physiological response.
TANG Yanhong, ZHENG Tianyu
1) Data content: data set of soil physical and chemical properties compared inside and outside the grassland fence project, including quadrat number, grassland type, survey County, survey location, project type, sampling time, project start time, duration, "longitude (° E)", "latitude (° n)", "altitude (m)", "pH (0-15cm)", "pH (15-30cm)", "SOM (0-15cm (‰))," SOM 15-30cm (‰)) "TN(0-15（‰）)"、"TN(15-30（‰）)"、"TP(0-15（‰）)"、"TP(15-30（‰）)" 2) Data source: field sampling data 3) Data quality: high quality 4) Data application prospect: the grassland fence project on the Qinghai Tibet Plateau will achieve remarkable results in protecting grassland and restoring regional vegetation productivity. The implementation of the project provides a broader space for the development of regional animal husbandry and ensures the stable growth of local farmers' and herdsmen's income and regional economy. In addition, the implementation of the project ensures and supports the normal production and life of herdsmen in Tibet, and realizes the grassland protection in the pastoral area and the stable development of herdsmen's animal husbandry production, which is of great significance to maintaining the overall stability of Tibetan society and promoting the sound and rapid development of Tibet
HONG Jiangtao, WANG Xiaodan
The gridded desertification risk data of The Arabian Peninsula in 2021 was calculated based on the environmentally sensitive area index (ESAI) methodology. The ESAI approach incorporates soil, vegetation, climate and management quality and is one of the most widely used approaches for monitoring desertification risk. Based on the ESAI framework, fourteen indicators were chosen to consider four quality domains. Each quality index was calculated from several indicator parameters. The value of each parameter was categorized into several classes, the thresholds of which were determined according to previous studies. Then, sensitivity scores between 1 (lowest sensitivity) and 2 (highest sensitivity) were assigned to each class based on the importance of the class’ role in land sensitivity to desertification and the relationships of each class to the onset of the desertification process or irreversible degradation. A more comprehensive description of how the indicators are related to desertification risk and scores is provided in the studies of Kosmas (Kosmas et al., 2013; Kosmas et al., 1999). The main indicator datasets were acquired from the Harmonized World Soil Database of the Food and Agriculture Organization, Climate Change Initiative (CCI) land cover of the European Space Agency and NOAA’s Advanced Very High Resolution Radiometer (AVHRR) data. The raster datasets of all parameters were resampled to 500m and temporally assembled to the yearly values. Despite the difficulty of validating a composite index, two indirect validations of desertification risk were conducted according to the spatial and temporal comparison of ESAI values, including a quantitative analysis of the relationship between the ESAI and land use change between sparse vegetation and grasslands and a quantitative analysis of the relationship between the ESAI and net primary production (NPP). The verification results indicated that the desertification risk data is reliable in the Arabian Peninsula in 2021.
XU Wenqiang
This data set includes the PM2.5 mass concentration of atmospheric aerosol particles at Southeast Tibet station, Ali station, mostag station, Everest station and Namuco station (unit: mm) μ g/m3）。 Aerosol PM2.5 fine particles refer to particles with aerodynamic equivalent diameter less than or equal to 2.5 microns in the ambient air. It can be suspended in the air for a long time, which has an important impact on air quality and visibility. The higher its concentration in the air, the more serious the air pollution. The concentration characteristic data of PM2.5 is output at the frequency of obtaining a set of data every 5 minutes, which can realize the analysis of aerosol mass concentration at different time scales such as hour, day and night, season and interannual, which provides the analysis of changes and influencing factors of aerosol mass concentration at different locations in the Qinghai Tibet plateau at different time scales, as well as the evaluation of local air quality, It provides important data support. This data is an update of the published data set of PM2.5 concentration of aerosol particles at different stations on the Qinghai Tibet Plateau (2018 and 2019).
WU Guangjian
This data set includes two infrared cameras and environmental parameter data sets of three terrestrial vertebrates deployed in Qilian Mountain reserve. The equipment is deployed near Sidalong in Qilian Mountain reserve, with a time span of (2020.8-2021.10). Due to equipment maintenance and insufficient illumination, some data are discontinuous, but the data of the two equipment can complement each other and reconstruct all the information of observation points in Qilian Mountain reserve from August 2020 to October 2021. One of the two devices is equipped with an infrared camera, which collects 4994 photos, which can be matched with the above sensor photos, or the ecological factor information before and after taking photos. 1. Wild animals and temperature, humidity, light, pressure and network signal strength information in Qilian Mountain reserve. The acquisition interval is once every half an hour 2. Data source: "development of terrestrial vertebrate monitoring equipment", 2016yfc0500104, completed by: Institute of zoology, Chinese Academy of Sciences, raw data, unprocessed 3. The sensor data acquisition interval is every half an hour. The temperature accuracy is plus or minus 0.1 degrees and the humidity accuracy is plus or minus 0.5%. The photo data is divided into trigger and timing. The trigger data is generally triggered by wild animals in the field of vision of the infrared camera; the timing photo data is dynamically adjusted according to the battery power, and the acquisition interval is between 1-12 hours. 4. This data can be used to record the ambient temperature in the reserve. Combined with the infrared camera data, it can be used to analyze the activity rhythm of wild animals, coexistence analysis and distribution limiting factors.
QIAO Huijie
The demonstration data set of automatic plant phenology observer at Heihe Daman station is the corn phenology observation data set collected by the plant phenology observer at Heihe Daman station. The plant phenology observer can collect phenology images through the phenology observation hardware system based on multispectral imager and wireless transmission module, and through online calculation and visual image management Phenological information processing and system control software can realize the automatic identification of key phenological periods at individual and community scales. Through the data collected by the automatic plant phenology observer, the indexes such as vegetation greenness index and NDVI index can be calculated, the change process of key plant phenology can be monitored, and the change law of vegetation phenology can be reflected.
SONG Chuangye, GAO Liyao, WU Dongxiu
This data includes the image data of the second comprehensive field scientific investigation of the Qinghai Tibet Plateau. The image data includes the sample plot photos of the quadrats collected in the nature reserve during the scientific research, the images of forest ecosystem, grassland ecosystem and lake ecosystem in the nature reserve in Northwest Yunnan and Western Sichuan, the vegetation situation, wildlife habitat, and the data of animals, plants and fungi in the reserve. In addition, the image data also includes the sample collection process of the scientific research, the household survey of the scientific research team in the community survey and the image data of the interview with the local protection department. The data comes from UAV and camera shooting, which can provide evidence and reference for scientific research.
SU Xukun
This vegetation water content data set is derived from the ground synchronous observation in the Luanhe River Basin soil moisture remote sensing experiment, including 55 sampled plots.The vegetation types involved in these sampled plots include grass, corn, potatoes, naked oats and carrots. The data measurement time is from September 13, 2018 to September 26, 2018.
ZHENG Xingming, JIANG Tao
This data is derived from the Supplementary Tables of the paper: Chen, F. H., Welker, F., Shen, C. C., Bailey, S. E., Bergmann, I., Davis, S., Xia, H., Wang, H., Fischer, R., Freidline, S. E., Yu, T. L., Skinner, M. M., Stelzer, S., Dong, G. R., Fu, Q. M., Dong, G. H., Wang, J., Zhang, D. J., & Hublin, J. J. (2019). A late Middle Pleistocene Denisovan mandible from the Tibetan Plateau. Nature, 569, 409-412. This research is another breakthrough made by academician Fahu Chen and his team over the years research of human activities and environmental adaptation on the Tibetan Plateau. The research team analyzed the newly discovered hominid mandible fossils in Xiahe County, Gansu Province, China, and identified it belongs to Denisovan of the Tibetan Plateau, which suggested to call Xiahe Denisovan. The team conducted a multidisciplinary analysis of the fossil, including chronology, physique morphology, molecular archaeology, living environment and human adaptation. It is the first Denisovan fossil found outside the Denisova Cave in the Altai Mountains and the earliest evidence of human activity on the Tibetan Plateau (160 kyr BP). This study provides key evidence for further study of Denisovans' physical characteristics and distribution in East Asia, it also provides evidence of a deep evolutionary history of these archaic hominins within the challenging environment of the Tibetan Plateau. This data contains 6 tables, table name and contents are as follows: t1: Distances in mm between meshes generated from CT versus photoscans (PS). t2: Measurements of the Xiahe mandible after reconstruction. t3: Comparative Dental metrics. t4: Comparative crown morphology. t5: Uniprot accession numbers for protein sequences of extant primates used in the phylogenetic analyses. t6: Specimen names and numbers.
CHEN Fahu
Reasonable carrying capacity, also known as theoretical carrying capacity, refers to the maximum number of domestic animals that can be carried by a certain grassland area in a certain period of time under the premise of moderate grazing (or mowing) and maintaining sustainable production of grassland to meet the needs of normal growth, reproduction and production of livestock. Based on the MODIS inversion data of forage yield (fresh weight, kg / hm2), the reasonable carrying capacity of grassland (sheep unit, mu / km2) was evaluated according to the code for calculation of grassland carrying capacity and grass livestock balance (DB 51 / t1480-2012) and calculation of reasonable carrying capacity of natural grassland (NY / T 635-2015), The time series is 2000-2019, and the spatial resolution is 250m. This data set can analyze the temporal and spatial variation characteristics of the theoretical carrying capacity under the condition of rational utilization of grassland in the Qinghai Tibet Plateau, evaluate the carrying capacity characteristics of grassland in the Qinghai Tibet Plateau, and extract the overgrazing areas, which has important application value for ecological protection, monitoring and early warning of the Qinghai Tibet Plateau.
LIU Bintao
Grassland yield is an important ecological parameter of grassland, which is an important basis for monitoring grassland productivity, Estimating Grassland reasonable carrying capacity and evaluating grassland carrying status. Based on the grassland data collected in July and August, MODIS NDVI, precipitation and terrain parameters, multivariate statistical equations were established to invert the total grass yield (kg / hm2) and edible grass yield (kg / hm2). The time series is 2000-2019, and the spatial resolution is 250 meters. Based on the data of 50 quadrats distributed in Sichuan, Tibet, Qinghai, Gansu and other regions, the results show that the average absolute error of total grass yield is 734.75kg/hm2, and the average relative error is 24.85%. The average absolute error of edible grass yield is 715.81kg/hm2, and the average relative error is 30.52%. Due to the complexity of grassland types, high spatial heterogeneity and scale mismatch between the measured grassland quadrats and MODIS image pixels, this accuracy can meet the requirements of remote sensing monitoring of grassland in large areas. This data set can analyze the spatiotemporal variation characteristics of grassland productivity in the Qinghai Tibet Plateau, evaluate the carrying capacity characteristics of grassland in the Qinghai Tibet Plateau, and extract the overgrazing areas, which has important application value for ecological protection, monitoring and early warning of the Qinghai Tibet Plateau.
LIU Bintao
The actual carrying capacity refers to the number of livestock in a certain area of grassland in a certain period of time. The actual carrying capacity is obtained from the statistical yearbooks of the provinces (autonomous regions) and cities (prefectures) of the Qinghai Tibet Plateau and the statistical data provided by the animal husbandry management departments. In the statistical data, there are a variety of statistical dimensions, such as the number of stocks on hand, the number of stocks on hand, the ratio of stocks on hand, and the number of livestock at the end of the year, etc. Based on the multivariate linear regression between the actual livestock carrying capacity and population density, NPP and topographic relief in the statistical yearbook, the spatial model of actual livestock carrying capacity was established, and the grid data of actual livestock carrying capacity (sheep unit, mu / km2) was obtained. The time series was from 2000 to 2019, and the spatial resolution was 250 meters. Using the statistical data of Guoluo, Yushu, Changdu, Naqu, ABA, Ganzi and Gannan in the core pastoral areas of the Qinghai Tibet Plateau, the results show that the average absolute error of spatialization is 27.48 mu / km2, and the average relative error is 13.79%. This data set can analyze the temporal and spatial variation characteristics of the actual livestock carrying capacity of the Qinghai Tibet Plateau, evaluate the grassland carrying capacity characteristics of the Qinghai Tibet Plateau, and extract the overgrazing areas, which has important application value for ecological protection, monitoring and early warning of the Qinghai Tibet Plateau.
LIU Bintao
Carrying capacity refers to the carrying capacity of grassland calculated by actual carrying capacity and reasonable carrying capacity, that is, all overloading, balanced and non overloading. This data set includes two products: Grassland carrying capacity pressure index and grassland livestock balance index. Grassland carrying capacity pressure index = actual carrying capacity / reasonable carrying capacity, and grassland livestock balance index = (actual carrying capacity - reasonable carrying capacity) × 100% / reasonable carrying capacity, the actual carrying capacity data comes from the Qinghai Tibet Plateau actual carrying capacity data set (2000-2019), and the reasonable carrying capacity data comes from the Qinghai Tibet Plateau reasonable carrying capacity data set (2000-2019). This data set can analyze the temporal and spatial variation characteristics of livestock carrying status in the Qinghai Tibet Plateau, extract overgrazing areas, and evaluate the overload intensity of the Qinghai Tibet Plateau, which has important application value for ecological protection, monitoring and early warning of the Qinghai Tibet Plateau.
LIU Bintao
1) Data content: the data are field sampling data of fence project, including sample number, grassland type, survey County, survey location, project type, project start time, "longitude (° E)", "latitude (° n)", "altitude (m)", "total coverage (%)," average height (CM) ", aboveground biomass (g / m2), underground biomass (g / m2), and total biomass (g / m2), 2) Data source: field sampling data 3) Data quality: high quality. 4) Data application prospects: it will be of great significance for promoting the development of local animal husbandry and improving the local economic benefits by deeply exploring the grassland fence project on the Qinghai Tibet Plateau. In terms of the expected results, the Qinghai Tibet Plateau grassland fencing project will achieve remarkable results in protecting grassland and restoring regional vegetation productivity. The implementation of the project provides a broader space for the development of regional animal husbandry, and ensures the stable growth of local farmers and herdsmen's income and regional economy. In addition, the implementation of the project ensures and supports the normal production and life of Tibetan herdsmen, and realizes the stable development of grassland protection and animal husbandry production of herdsmen in the pastoral areas, which is of great significance for maintaining the overall stability of Tibet society and promoting the sound and rapid development of Tibet.
HONG Jiangtao, WANG Xiaodan
Dataset of biodiversity survey in the urbanized area of Tibetan Plateau mainly includes the survey datasets of waterbird diversity and vegetation diversity in the Qinghai Lake Basin. From July to August in 2020, 24 waterbird observation sites were set up around Qinghai Lake, such as sites located in Ganzi River wetland and Buha River estuary, etc., and the species and population of waterbirds were recorded by telescope observations and drones. Besides, 28 plots (1m×1m) were selected based on the local vegetation types, and elements of vegetation types, frequency and biomass were recorded. Our dataset will support the study of optimizing the ecological security barrier system in the key urbanized areas of the Tibetan Plateau.
CHEN Kelong, CHEN Zhirong
According to the characteristics of the Qinghai Tibet Plateau and the principles of scientificity, systematization, integrity, operability, measurability, conciseness and independence, the human activity intensity evaluation index system suitable for the Qinghai Tibet Plateau has been constructed, which mainly includes the main human activities such as agricultural and animal husbandry activities, industrial and mining development, urbanization development, tourism activities, major ecological engineering construction, pollutant discharge, etc, On the basis of remote sensing data, ground observation data, meteorological data and social statistical yearbook data, the positive and negative effects of human activities are quantitatively evaluated by AHP, and the intensity and change characteristics of human activities are comprehensively evaluated. The data can not only help to enhance the understanding of the role of human activities in the vegetation change in the sensitive areas of global change, but also provide theoretical basis for the sustainable development of social economy in the Qinghai Tibet Plateau, and provide scientific basis for protecting the ecological environment of the plateau and building a national ecological security barrier.
ZHANG Haiyan, XIN Liangjie, FAN Jiangwen, YUAN Xiu
This data is the data of automatic weather station (AWS, Campbell company) set up at the top of the mountain in the west slope of Sejila by the comprehensive observation and research station of Southeast Tibet alpine environment of Chinese Academy of Sciences in 2016. The geographical coordinates are 29.5919 n, 94.6102 e, with an altitude of 4640 m, and the underlying surface is alpine grassland. The data include daily arithmetic mean data of air temperature (℃), relative humidity (%), wind speed (M / s) and air pressure (MB) and daily accumulated value of precipitation. The original data is an average of 30 minutes before October 2018, and an average of 10 minutes after that. The temperature and humidity are measured by hmp155a temperature and humidity probe. The rainfall instrument model is rg3-m, the atmospheric pressure sensor probe is ptb210, and the wind speed sensor is 05103. These probes are 2 m above the ground. In terms of data quality: the obvious abnormal values are eliminated, the battery is damaged due to snow in the first half of 2019, and the data is missing. The missing temperature data is corrected by using the temperature fitting regression of 43900 m at nearby stations, and the data is yellow. Please pay attention when using it; the monitoring of precipitation starts from August 2019. The data station is a high altitude meteorological station in Southeast Tibet, which will be updated from time to time. It can be used by scientific researchers studying ecology, climate, hydrology, glaciers, etc.
Luo Lun
Based on a large number of measured aboveground biomass data of grassland, the temperate grassland types were divided according to the vegetation type map of China in 1980s Based on the Landsat remote sensing data of engine platform, the random forest model of grassland aboveground biomass and remote sensing data was constructed for different grassland types. On the basis of reliable verification, the annual aboveground biomass of grassland from 1993 to 2019 was estimated, and the annual spatial data set of aboveground biomass of temperate grassland in Northern China from 1993 to 2019 was formed. Aboveground biomass is defined as the total amount of organic matter of vegetation living above the ground in unit area. The original grid value has been multiplied by a factor of 100, unit: 0.01 g / m2 (g / m2). This data set can provide a scientific basis for the dynamic monitoring and evaluation of temperate grassland resources and ecological environment in northern China.
ZHANG Na
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