This phenological data is based on the MOD13A2 data of the Qinghai Tibet Plateau from 2000 to 2015 (with a temporal resolution of 16 days and a spatial resolution of 1km). The NDVI curve is fitted using the segmented Gaussian function in the TIMESAT software. The spring phenology, autumn phenology and the length of the growth season are extracted using the dynamic threshold method. The thresholds of spring phenology and autumn phenology are set to 0.2 and 0.7 respectively. The phenological data were masked. Among them, the mask rules are: 1) The maximum value of NDVI must be met between June and September; 2) The average value of NDVI from June to September shall not be less than 0.2; 3) The average NDVI in winter shall not exceed 0.3.
ZU Jiaxing , ZHANG Yangjian
Vegetation survey data is essential for the study of ecosystem structure and function. The Qinghai Tibet Plateau contains a vast grassland ecosystem, mainly including alpine meadow, alpine grassland, and alpine desertification grassland. Due to the unique geographical location and high altitude anoxic environmental conditions, the community survey data in the northern Tibetan Plateau is relatively scarce. This data set includes the aboveground biomass and coverage data of 47 sampling points on the northern Tibet transect in 2019, and the sampling time is from July to August. The sample size is 50cm × 50cm, dry weight of the plant is weighed after drying. This data set can be used for spatial analysis of productivity and calibration of models.
ZHANG Yangjian, ZHU Juntao
This dataset is the growing season NDVI and vegetation phenology dataset of the Tibetan Plateau during during the past 20 years (2001-2020). The data source is MODIS (MOD13A2, Collection 6) products, and the spatial resolution is 1km. The dataset includes: the average NDVI during the growing season (May-September), the start date of the growing season (SOS), the end date of the growing season (EOS) and the duration of the growing season (DOS) for each year from 2001 to 2020. Two methods were used to extract vegetation phenology: dynamic threshold approach and double logistic function method. The data format is TIFF and the projection is Sphere_ ARC_ INFO_ Lambert_ Azimuthal_ Equal_ Area.
WANG Taihua, YANG Dawen
The normalized difference vegetation index (NDVI) can accurately reflect the surface vegetation coverage. At present, NDVI time series data based on spot / vegetation and MODIS satellite remote sensing images have been widely used in the research of vegetation dynamic change monitoring, land use / cover change detection, macro vegetation cover classification and net primary productivity estimation at various scales. Evi is similar to the normalized difference vegetation index (NDVI) and can be used to quantify vegetation greenness. However, evi corrects for some atmospheric conditions and canopy background noise and is more sensitive in areas with dense vegetation. It contains an "L" value to adjust the canopy background, a "C" value as the atmospheric drag coefficient, and a value from the blue band (b). These enhancements allow the ratio between R and NIR values to be calculated exponentially while reducing background noise, atmospheric noise and saturation in most cases. This research work mainly focuses on post-processing NDVI and evi data, and gives a more reliable vegetation situation of the Qinghai Tibet Plateau in 2013 and 2018 through transformation of projection coordinate system, data fusion, maximum value synthesis method, elimination of outliers and clipping. The spatial resolution of the data is 0.05 °, and the temporal resolution is month.
YE Aizhong
Normalized Difference Vegetation Index (NDVI) has been widely used for monitoring vegetation. This dataset employed all available Landsat 5/7/8 data on the Qinghai-Tibetan Plateau (QTP) (> 100,000 scenes), and reconstructed high spatiotemporal NDVI time-series data (30-m and 8-d) during 2000-2020 on the TP (QTP-NDVI30) by using the MODIS-Landsat fusion algorithm (gap filling and Savitzky–Golay filtering；GF-SG). For the details of GF-SG, please refer to Chen et al. (2021). This dataset has been evaluated carefully. The quantitative assessments show that the reconstructed NDVI images have an average MAE value of 0.02, correlation coefficient of 0.96, and SSIM value of 0.94. We compared the reconstructed images in some typical areas with the PlanetScope 3-m images and found that the spatial details were well preserved by QTP-NDVI30. The geographic coordinate system of this dataset is GCS_WGS_84. The spatial range covers the vegetation area of the QTP, which is defined as the areas with average NDVI during July- September larger than 0.15.
CAO Ruyin , XU Zichao , CHEN Yang , SHEN Miaogen , CHEN Jin
The rich habitat polymorphism of Qinghai Tibet Plateau makes it a treasure house of natural resources. There are special gene resources in plateau plants, such as cold resistance, drought resistance, salt resistance, UV radiation resistance, high light efficiency, etc. How to tap, utilize and establish functional gene resources with independent property rights has important potential application value for modern crop breeding in China. High quality chromosome level genomes provide a solid molecular basis for the analysis of plant adaptation mechanism, stress resistance gene mining and other related research. The contents of this data collection are: the genome data set of Euphorbiaceae Euphorbiaceae, Qinghai Xizang Euphorbiaceae, including chromosome level genome sequences and annotation files; The genome data set of the scions of Euphorbiaceae, including chromosome level genome sequences and annotation files; Genome data set of Euphorbiaceae single tree, including chromosome level genome sequence and annotation file; Genome data set of Sophora pseudoacacia in Leguminosae, including chromosome and genome sequence, annotation file.
YANG Yongping
The Qinghai-Tibet Plateau and its surrounding alpine areas have bred a high degree of plant diversity, and their composition sources are complex. The Qinghai-Tibet Plateau is not only the distribution center of modern alpine plants, but also inextricably linked with plants in other areas. The plants growing in this area have unique gene resources to adapt to the plateau environment. Due to the limit of technology, the mining and utilization of plant gene resources in this area is still in its infancy. Through comparative genomics research on two species of Gentianaceae, we can analyze the genomic effect of plant mating system evolution, discover the key genes related to selfing, and explore the maintenance mechanism of plant hybrid mating system. The content of this data collection is listed as follows: the original genome data of the Halenia elliptica and the Halenia grandiflora , including the third-generation pacbio sequencing data of Halenia elliptica and the Halenia grandiflora, and the second-generation Illumina sequencing data of the Halenia elliptica and the Halenia grandiflora.
DUAN Yuanwen
Vegetation primary productivity (Net Primary Production, NPP) dataset, source data from MODIS product (MOD17A3H), after data format conversion, projection, resampling and other preprocessing. The existing format is TIFF format, the projection is Krasovsky_1940_Albers projection, the unit is kg C/m2/year, and the spatial range is the entire Qinghai-Tibet Plateau. The spatial resolution of the data is 500 meters, the temporal resolution is every 5 years, and the time range is from 2001 to 2020. The NPP of the Qinghai-Tibet Plateau showed a trend of increasing gradually from northwest to southeast.
ZHU Juntao
In this study，a vegetation classification system for the vegetation types in the Qinghai-Tibet Plateau was designed. The integrated classification method，taken into account of multi-source vegetation classification / land cover classification products， was used to produce the actual vegetation map. This integrated classification method followed the principle of data consistency，and the resultant vegetation map was superior over other vegetation maps in terms of reflection of current situation， classification system， and classification accuracy. This vegetation map is timely and could better reflect current vegetation distribution than earlier ones. This vegetation map could be conducive to fully extract vegetation information from multi-source data products with high reliability and consistency. Compared with previous data products，the overall accuracy （78.09%，kappa coefficient is 0.75） of this new vegetation map was found to increase by 18.84%-37.17%，especially for grassland and shrub.
ZHANG Hui, ZHAO Cenliang, ZHU Wenquan
Mapping scope: the scope of Qinghai Tibet Plateau (2002 Edition) by Zhang Yili, etc. Data source: vegetation map of Qinghai Tibet Plateau in 1980s, climate, terrain, landform, soil data, etc. Mapping method: the restored vegetation map is a vegetation map that reflects the distribution of the original vegetation before it was damaged by human economic activities. Due to the lack of early vegetation distribution map of the Qinghai Tibet Plateau, based on the vegetation map of the Qinghai Tibet Plateau in the 1980s prepared by the project team, the approximate Restored Vegetation Map is prepared through the following methods. Based on the vegetation map of the Qinghai Tibet Plateau in the 1980s and the worldclim19 bioclimatic data in 1980, the relationship between bioclimatic data and natural vegetation is analyzed to determine the climate data change range corresponding to the distribution of various natural vegetation. For the artificial vegetation in the 1980's vegetation map, the earliest 1960 worldclim19 biological climate data are used to judge the corresponding natural vegetation according to the climate data of the artificial vegetation distribution area and the relationship between the vegetation distribution and climate, and replace the artificial vegetation in this area with natural vegetation. On this basis, further consider the zonal law of vegetation distribution and its relationship with terrain, landform and soil, analyze the previous judgment results according to the remaining natural vegetation around the artificial vegetation and the surrounding zonal vegetation, cross verify the accuracy of the artificial vegetation replacement results, and make appropriate corrections. The natural vegetation in the 1980's vegetation map, such as coniferous forest, broad-leaved forest, shrub, desert, grassland and meadow, remains unchanged. Based on the above analysis results, an approximate Restored Vegetation Map is obtained. The vegetation classification unit is the same as the vegetation map of Qinghai Tibet Plateau in 1980s. Based on the accuracy of the data used in the mapping, the maximum mapping scale of this drawing is 1:500000.
ZHOU Jihua, ZHENG Yuanrun, SONG Changqing , CHENG Changxiu , GAO Peichao , SHEN Shi, YE Sijing
Vegetation map of Qinghai Tibet Plateau in 1980s: Region: Zhang Yili, etc. 2021 edition of Qinghai Tibet Plateau. Data sources: Landsat 4-5 TM images from 1980 to 1988 (spatial resolution of about 30m), field survey data, 1:1 million vegetation map, Google Earth image, climate, terrain, landform, soil, land cover data, etc. Mapping methods: (1) preliminary patch segmentation, using object-oriented method to preliminarily segment remote sensing images to form preliminary cartographic patches; (2) Visual interpretation: integrate the field survey data, 1:1 million vegetation map, Google Earth image, climate, terrain, landform, soil and land cover data to visually interpret and map the preliminary mapping patches; (3) Cross validation, using topographic map, 1:1 million vegetation map and land use map for logical verification; (4) The legend system adopts the classification standard, legend unit and system of vegetation map of the people's Republic of China (1:1, 000, 000), 2007, including vegetation type group and vegetation type 2 units. There are 11 vegetation type groups, 46 vegetation types and 10 non vegetation sections in the mapping area; (5) Vegetation map decoration adopts the method of combining map spots and numbers to represent different vegetation types and mapping units; (6) Based on the accuracy of the data used in the mapping, the maximum drawing scale of this drawing is 1:500000.
ZHOU Jihua, ZHENG Yuanrun, SONG Changqing , CHENG Changxiu , GAO Peichao , SHEN Shi, YE Sijing
The dataset based on synthesized data from 1114 sites across the Tibetan permafrost region which report that paleoclimate is more important than modern climate in shaping current permafrost carbon distribution.A new estimate of modern soil carbon stock to 3m depth on Tibetan permafrost region was derived by machine learning algorithm, including factors such as climate (paleoclimate and modern climate), vegetation, soil (soil thickness and soil physical and chemical properties, etc.) and topography. This dataset shows that ecosystem models clearly underestimated the Tibetan soil carbon stock, due to the absence of paleoclimate effects in the model. Future modelling of soil carbon cycling should include paleoclimate .
DING Jinzhi
This dataset is the biome change data of the Tibetan Plateau since the last glacial maximum which was reconstructed by using a new method. Firstly, a random forest algorithm was applied to establish a pollen-biome classification model for reconstructing past vegetation changes of the Tibetan Plateau, and 1802 modern pollen assemblages from 17 vegetation zones in and around the Tibetan Plateau were used as the training set for the model development. The random forest model showed a reliable performance (accuracy > 76%) in predicting modern biomes from modern pollen assemblages based on a comparison with the observed biomes. Moreover, the random forest model had a significantly higher accuracy than the traditional biomization method. Then, the newly established random forest model is applied to the paleovegetation reconstruction of 51 fossil pollen sequences of the Tibetan Plateau. New age-depth models were developed for these fossil pollen records using the Bayesian method, and all fossil pollen records were linearly interpolated to 500-year time slices. Finally, the spatiotemporal changes of biomes on the Tibetan plateau over the past 22,000 years at an interval of 500 years were reconstructed by using the random forest model. This dataset can provide evidence for understanding the past variation of alpine vegetation and its mechanism; provide the basis for studying the impact of past climate change on vegetation on the Tibetan Plateau; and provide boundary conditions for climate simulation.
QIN Feng , ZHAO Yan, CAO Xianyong
Dataset of plant community quadrats in Tibetan Plateau (2019) was obtained from the field survey of The Second Tibetan Plateau Scientific Expedition and Research Task 3 Topic 6 in August 2019. The spatial span is N36.02° -38.07 °, and E91.45° -100.84 °. The dataset consisted 48 plots including forest, shrub, grassland, desert and cropland. And the dataset consisted of four parts, including plot information, tree layer plot, shrub layer plot and herb layer plot. Among them, there are 2 data of tree layer, 63 data of shrub layer and 101 data of herb layer. The survey items included species composition, species coverage, average species height, average area of shrub canopy and total community coverage.
HUANG Yongmei , HUO Jiaxuan , REN Liang
Based on the distribution locations of the Qinghai toad-headed lizard (Phrynocephalus vlangalii) collected by field investigation and literature investigation, combined with five climate factors from WorldClim database, the current (1960-1990) and future (2061-2080) climate data were input into the trained species distribution model to predict the current and future suitable habitats. The prediction results shows that the lizard will lose a lot of original habitats under the climate change, and the protection measures for the lizard species should focus on the eastern margin of Qinghai-Tibet Plateau, the northern and eastern parts of Qaidam Basin. The model also predicts that after the climate change, new suitable habitats will appear in areas that were not suitable for the Qinghai toad-headed lizard. However, due to the very limited diffusion ability of reptiles (the maximum annual diffusion distance recorded in the literature is less than 500m), the newly emerging suitable habitats may not be used by the Qinghai toad-headed lizard. Meanwhile, based on the physiological, life history, behavior and morphological data of three altitudinal populations of the Qinghai toad-headed lizard collected by field work, and combined with microclimate data, the physiological consequences of climate change on the Qinghai toad-headed lizard in the current suitable distribution area were predicted by using the mechanism niche model. The prediction results of the model show that, whether in the SSP245 or SSP585 climate change scenarios, the activity time of the lizard will increase in most areas (> 93%) of the current suitable distribution area, and the thermal safety threshold will decrease in all places of the current suitable distribution area. The increase of activity time of high-altitude populations is less than that of low-altitude populations, but the decrease of thermal safety threshold is greater than that of low-altitude populations. The results reveal that climate change may have a greater impact on lizard populations in high altitude areas.
ZENG Zhigao
This data set is the spectral reflectance data of typical features in Ali during August to September in 2017, using ASD FieldSpec 4. The day of spectral data obtaining was sunny, we recorded the cloud condition during measuring. The white board was calibrated before measurement; The longitude and latitude coordinates are recorded by GPS. We measured the spectral reflectance data of different vegetation types and soil surrounding them. The DN value (.asd format) recorded by instrument can be read by ViewSpecPro, then converted into reflectance using EXCEL with the white board data. Spectral reflectance data is used to extract spectral characteristics of different vegetation types, vegetation classification, inversion of vegetation coverage and so on.
LIU Linshan, ZHANG Binghua
1) Data content: the data are the ancient DNA data generated by studying the cultural layer of Klu lding site in Nyingchi region, Tibetan Plateau, including the hiseqx metagenomics data of 10 ancient DNA samples from 4 layers. It can be used to preliminarily analyze the changes of species composition recorded by ancient DNA in the sediments, and reveal the process of local agricultural development. 2) Data source and processing method: the research group has its ownership. the data were obtained by using pair-end library building and Illumina hiseqx sequencing platform. 3) Data quality: 20.3 MB, Q30 > 85%. 4) Application: The data will be used to explore the potential of the ancient DNA from archaeological sediments in revealing the development of ancient agriculture on the Tibetan Plateau.
YANG Xiaoyan
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
In this paper, we review evidence for a major biotic turnover across the Oligocene/Miocene in the Tibetan Plateau region. Based on the recent study of six well-preserved fossil sites from the Cenozoic Lunpola and Nima basins in the central Tibetan Plateau, we report a regional changeover from tropical/subtropical ecosystems in the Late Oligocene ecosystem (26–24 Ma) to a cooler, alpine biota of the Early Miocene (23–18 Ma). The Late Oligocene fossil biota, comprising of fish (climbing perch), insects and plants (palms), shows that the hinterland of the Tibetan Plateau was a warm lowland influenced by tropical humidity from the Indian Ocean. In the Early Miocene, the regional biota became transformed, with the evolution and diversification of the endemic primitive snow carp. Early Miocene vegetation was dominated by temperate broad-leaved forest with abundant conifers and herbs under a cool climate, and mammals included the hornless rhinoceros, Plesiaceratherium, a warm temperate taxon. This dramatic ecosystem change is due to a cooling linked to the uplift of Tibetan region, from a Late Oligocene paleo-elevation of no greater than 2300 m a.s.l. in the sedimentary basin to a paleo-elevation of about 3000 m a.s.l. Another factor was the Cenozoic global climatic deterioration toward to an ice-house world.
DENG Tao
The data include raw sequencing result of plant DNA in surface sediments of 33 lakes in the Qinghai-Tibetan Plateau and arid northwestern China. We used PowerMax Soil Kit of Qiagen company in Germany to extract DNA, then used universal plant primer g-h (Taberlet et et al., 2007) to amplify P6 loop of chloroplast trnL (UAA) intron in the sample. The PCR products were then sent to Fasteris company in Switzerland for the next-generation paired-end sequencing. The sequencing instrument is Illumina Nextseq 550. The data quality score (Q30) is 81.97.
LIU Xingqi, JIA Weihan
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