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
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
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
This dataset is derived from the paper: Tang, H. et al. (2020). Early Oligocene vegetation and climate of southwestern China inferred from palynology. Palaeogeography, Palaeoclimatology, Palaeoecology, 560, 109988. doi:10.1016/j.palaeo.2020.109988 This data is part of Supplementary data of the paper, maily contains: Supplementary table 1) Pollen percentages, which were calculated using the collected pollen samples. Supplementary table 2) Plant functional types (PFTs) for the reconstructed paleovegetation of three sites : Wenshan (Early Oligocene), Jianchuan (Early Oligocene) and Lühe (Late Eocene). Recently, in the town of Lühe, central Yunnan, SW China, a new fossil-bearing section was found and dated as early Oligocene (~33–32 Ma) according to U-Pb isotope of volcanic tuff. The fossil-bearing section totals about 18 m in thickness. Fifty-five pollen samples were collected vertically throughout this Lühe town section. For each sample, 2–2.5 g of sediment were treated with KOH (10%,) HCl (10%) and HF (39%), then sample residues were sieved through a 5 μm nylon mesh in an ultrasonic tank. Spore and pollen grains were identified using both a light microscope (LM, Leica DM1000 microscope) and a scanning electronic microscope (SEM). Single grains were picked up by a capillary tube and then transferred to a copper stub, coated with gold and observed with a Zeiss EVO LS10 SEM. At least 300 pollen grains were counted for each sample under the LM at ×400 magnification. Then the pollen percentages were calculated using the sum of total terrestrial pollen. The paleovegetation was reconstructed following the method described by Prentice et al., 1996, Prentice and Jolly, 2000 and Ni et al. (2010). The paleobiomes were reconstructed by comparing the similarity of the palaeoflora with modern plant functional types (PFTs), according to the data published by Ni et al. (2010). The similarity between the palaeoflora and modern PFTs data was explored using Euclidean distances (Prentice et al., 1996) and the Jaccard Index Coefficient (Pound and Salzmann, 2017). The Jaccard Index Coefficient in the R package “clusteval” was used here to calculate the similarity. The palaeoflora was assigned to the biome with the highest similarity scores, taking into account dominant or key taxa.
TANG He
The data include the Cenozoic plant fossils collected from Gansu, Qinghai and Yunnan by the Department of paleontology, School of Geological Sciences and mineral resources, Lanzhou University from 2019 to 2020. All the fossils were collected by the team members in the field and processed in the laboratory by conventional fossil restoration methods and cuticle experiment methods. The fossils are basically well preserved, some of which are horned The study of these plant fossils is helpful to understand the Cenozoic paleoenvironment, paleoclimate, paleogeographic changes and vegetation features of the eastern Qinghai Tibet Plateau.
YANG Tao
This dataset is derived from the paper: Deng, W. et al. (2020). Sharp changes in plant diversity and plant-herbivore interactions during the Eocene–Oligocene transition on the southeastern Qinghai-Tibetan Plateau. Global and Planetary Change, 194, 103293. doi:10.1016/j.gloplacha.2020.103293 This data contains herbivore damage patterns on fossil leaves of plant assemblages from the latest Eocene layer and the earliest Oligocene layer in Kajun Village, Markam County, southeastern margin of the Qinghai-Tibetan Plateau. Herbivore damage patterns on fossil leaves are essential to explore the evolution of plant-herbivore interactions under paleoenvironmental changes and to better understand the evolutionary history of terrestrial ecosystems. The Eocene–Oligocene transition (EOT) is a period of dramatic paleoclimate changes that significantly impacted global ecosystems, Researchers identified taxonomic composition of the flora, and investigated well-preserved herbivore damage on fossil leaves from two layers(the latest Eocene layer (MK-3, ~34.6 Ma) and the earliest Oligocene layer (MK-1, ~33.4 Ma)) of the Lawula Formation in Markam County, southeastern Qinghai-Tibetan Plateau (QTP), China. The data contains tables of the records of the leaves fossil, the fileds of the tables are as following: Basic Code; Database RFID; Family code; Genera code; Species code; Marks; Plant-herbivore; Leaves for damage; FFGs & DTs; Code marks; Hole feeding; Margin feeding; Skeletonization; Surface feeding; Piercing & Sucking; Oviposition; Mining; Galling; Fungal; Incertae Sedis; Boring; Undefined This dataset also contains some figures in the article.
DENG Weiyudong, SU Tao
Airborne pollen is mainly produced and disseminated during the process of plant flowering, controlled by plant phenology and climatic conditions. As an important bioindicator of plant behavior, airborne pollen can supply information about reproductive phenology, climate and atmospheric circulations. From 2011 to 2013, airborne pollen samples were collected using a volumetric Burkard pollen trap at the Qomolangma Station for Atmospheric and Environmental Observation and Research, Chinese Academy of Sciences (QOMS, 28.21°N, 86.56°E; 4276 m a.s.l.), on the northern slope of the Himalayas. The sampler is a volumetric air-suction device capable of continuously gathering pollen and spore particles. Air is drawn in at a speed of 10 l/min, and airborne particles are deposited on a sticky tape mounted on a drum that makes one complete rotation per week. The tape is changed weekly after a complete rotation. Then, the tape is removed and cut into seven pieces, with each piece representing one day of sampling. The pieces are mounted on slides using glycerin and safranin. Identification and counting of pollen grains were performed under an Olympus BX41 microscope at 400× magnification; all pollen grains on each slide were counted . Pollen concentration was expressed as the daily pollen grains per cubic meter of air using a constant air intake speed of 10 l/min. The pollen concentration and percentage of each pollen taxon in each year were calculated. The pollen sampling and lab process were followed the standard methods to ensure the authenticity and reliability of the data. The pollen data can provides insights into vegetation response to climate change and has significance for interpreting fossil pollen records.
LÜ Xinmiao
This dataset is collected from the Supplementary Materials part of the paper: Gao, S., Zhou, T., Yi, C., Shi, P., Fang, W., Liu, R., Liang, E., & Julio Camarero, J. (2020). Asymmetric impacts of dryness and wetness on tree growth and forest coverage. Agricultural and Forest Meteorology, 288-289, 107980. doi:10.1016/j.agrformet.2020.107980. In this paper the researchers took forests in the semi-arid area of the Colorado Plateau in the southwest USA as the research object, comprehensively applied a large amount of tree ring width data, combined with remote sensing forest coverage data, they explored the legacy effect under the influence of the interannual water deficit by designing "natural experiments" at the regional scale, and compared the similarities and differences of the effect of the interannual water status changes on the tree ring width and forest coverage. The study found that the water status in the year when the tree ring was formed can significantly affect the duration and intensity of the legacy effect, and the response of the tree ring width and forest coverage to the interannual water status is different. This data contains ring-width indices (RWI) of 357 sample sites in 111-hydrological year (i.e., for 1902–2012) and annual water deficit anomaly (Dya) that matched to RWI. The tree-ring database used in this research was composed of 357 standard chronologies of three major species (Pinus edulis Engelm., Pinus ponderosa Douglas ex C. Lawson and Pseudotsuga menziesii (Mirb.) Franco) in the study region, spanning from 1902 to 2012, resulting in a total of 29,969 site-years. A total of 357 tree-ring width chronologies of three major tree species were obtained from the International Tree-Ring Data Bank (https://www.ncdc.noaa.gov/data-access/paleoclimatology-data/datasets/tree-ring). To transform tree-ring width data into ring-width indices (RWI), long-term trends caused by aging and increasing trunk diameter were mostly removed by negative exponential curves using the ARSTAN program (Cook, 1985). After performing standardization, all chronologies were scaled to a standard mean (RWI = 1000) with a comparable variance to reduce the spatial heterogeneity among these tree-ring sites. In this research, researchers used annual water deficit anomaly (Dya) to explore the impact of water deficit variability on tree radial growth and growth legacies. They matched gridded Dya to RWIs. For tree-ring chronologies within the same grid, they averaged them for each year to reduce bias caused by the rough resolution of climate data. The data is 1 Excel workbooks, Ring-width indices and annual water deficit anomaly (1902-2012), which contains 3 worksheets as follows: raw_data processed_data variables The data contains the following fields: sitename: the name of tree-ring sampled site Year: the tree-ring formation year RWI: ring-width indices latitude: the latitude of tree-ring sampled site lontitude: the lontitude of tree-ring sampled site altitude: the altitude of tree-ring sampled site lon Grid no.: the lontitude grid number of tree-ring sampled site lat Grid no.: the latitude grid number of tree-ring sampled site Dya_3: water deficit anomaly of the 3rd year before the tree-ring formation year (i.e. "Year" column) Dya_2: water deficit anomaly of the 2nd year before the tree-ring formation year (i.e. "Year" column) Dya_1: water deficit anomaly of the 1st year before the tree-ring formation year (i.e. "Year" column) Dya_curr: water deficit anomaly of the tree-ring formation year (i.e. "Year" column) Dya_std: the standard deviation of 111-hydrological year (i.e., for 1902–2012) averaged annual water deficit of the grid
GAO Shan
Data set contains tree age of trees growing at different glacier moraines in the central Himalayas. The data were obtained using tree ring samples. Cores samples were collected (almost near to the ground level to estimate the minimum age of the related moraine) using an increment borer. Samples were processed by using standard dendrochronological techniques.
SIGDEL Shalik Ram, ZHNAG Hui, ZHU Haifeng, SHER Muhammad, LIANG Eryuan
By archaeological investigation and excavation in Tibetan Plateau and Hexi corridor, we discovered more than 40 Neolithic and Bronze Age sites, including Zongri, Sanjiaocheng, Huoshiliang, Ganggangwa, Yigediwonan, Shaguoliang, Guandi, Maolinshan, Dongjicuona, Nuomuhong, Qugong, Liding and so on. In this dataset, there are some basic informations about these sites, such as location, longitude, latitude, altitude, material culture and so on. On this Basis, we identified animal remains, plant fossil, selected some samples for radiocarbon dating, optically stimulated luminescence dating, stable carbon, nitrogen isotopes, polle, fungal sporen and environmental proxies. This dataset provide important basic data for understanding when and how prehistoric human lived in the Tibetan Plateau during the Neolithic and Bronze Age.
YANG Xiaoyan, Lü Hongliang, LIU Xiangjun, HOU Guangliang
This dataset is provided by the author of the paper: Huang, R., Zhu, H.F., Liang, E.Y., Liu, B., Shi, J.F., Zhang, R.B., Yuan, Y.J., & Grießinger, J. (2019). A tree ring-based winter temperature reconstruction for the southeastern Tibetan Plateau since 1340 CE. Climate Dynamics, 53(5-6), 3221-3233. In this paper, in order to understand the past few hundred years of winter temperature change history and its driving factors, the researcher of Key Laboratory of Alpine Ecology, Institute of Tibetan Plateau Research, Chinese Academy of Sciences and CAS Center for Excellence in Tibetan Plateau Earth Sciences. Prof. Eryuan Liang and his research team, reconstructed the minimum winter (November – February) temperature since 1340 A.D. on southeastern Tibetan Plateau based on the tree-ring samples taken from 2007-2016. The dataset contains minimum winter temperature reconstruction data of Changdu on the southeastern TP during 1340-2007. The data contains fileds as follows: year Tmin.recon (℃) See attachments for data details: A tree ring-based winter temperature reconstruction for the southeasternTibetan Plateau since 1340 CE.pdf
HUANG Ru, ZHU Haifeng, LIANG Eryuan
By archaeological investigation and excavation in Tibetan Plateau, we discovered 14 historic period sites, including Meinuo, Sariguo, Rongwaguo, Kaze, Jiha, Yarigei, Bami, Barongbadang, Qingtu, Labu ,Maisong Petroglyph, Gala, Yezere 1 and Yezere 4 . In this dataset, there are some basic informations about these sites, such as location, longitude, latitude, altitude, material culture and so on. On this Basis, we identified animal remains, plant macrofossil, selected some samples for radiocarbon dating and stable carbon and nitrogen isotopes. This dataset provide important basic data for understanding when and how prehistoric human lived in the Tibetan Plateau during the historic period.
DONG Guanghui , HOU Guangliang
By archaeological investigation and excavation in Tibetan Plateau, we discovered 8 Neolithic and Bronze Age sites, including Gaomuxudi, Duojialiang, Shuikou, Qipanshan, Xinzhai, Canxionggasu, Niaodao, Bangga, Baiyangcun and so on. In this dataset, there are some basic informations about these sites, such as location, longitude, latitude, altitude, material culture and so on. On this Basis, we identified animal remains, plant macrofossil, selected some samples for radiocarbon dating and stable carbon and nitrogen isotopes. This dataset provide important basic data for understanding when and how prehistoric human lived in the Tibetan Plateau during the Neolithic and Bronze Age.
DONG Guanghui , YANG Xiaoyan, Lü Hongliang
This data set contains Chen Co fossil diatoms, Chen Co conductivity reconstruction, Nam Co fossil diatoms, and Nam Co conductivity reconstruction. It can be used to study the characteristics of the living diatom species and for quantitative reconstruction of the paleoenvironments of the lakes of the Tibetan Plateau. The diatom data are obtained on the basis of the sample identification statistics, the water environment data are measured by the instrument, and the reconstructed conductivity is calculated from the diatom-salinity conversion function. This data set is obtained from laboratory measurements. The data are obtained immediately after the completion of the instrument or experiment. The samples and data are collected in strict accordance with relevant operating procedures at all stages. There are 6 subtables in this dataset: Subtable 1 is for a lake environment and has 18 fields, which are the lake name, number, lake number, latitude, longitude, water depth, altitude and water environment indicators; Subtable 2 is for the diatoms in surface sediments and has 4 fields, which are the lake serial number, the diatom abbreviation, the diatom name and its content; Subtable 3 is for the Chen Co diatoms and has 6 fields, which are sample number, analysis number and depth, diatom abbreviation, diatom name and its content; Subtable 4 is for the Chen Co conductivity reconstruction and has 3 fields, which are the depth, age, and conductivity of diatom reconstruction; Subtable 5 is for Nam Co fossil diatoms and has 5 fields. The first two fields are depth and age, and the other fields are the contents of diatoms of different species; and Subtable 6 is for the Nam Co conductivity reconstruction and has 3 fields, which are the depth, age, and conductivity of the diatom reconstruction. The dimension of diatom content in each subtable is the percentage of percent. The units of sample depth, water depth, age, longitude, latitude, altitude, ion content and conductivity are cm, m, AD, ° east longitude, ° north latitude, m, mg/L, and μS/cm, respectively. The diatom samples are collected from approximately 90 lakes on the Tibetan Plateau within a longitude range of 84.528 -102.360 °E and a latitude range of 28.148-38.897 °N; altitude: 2797-5180 m.
YANG Xiangdong
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