The data file is in 7z compressed package format, which can be unzipped and opened with 7-Zip software. The internal is divided into 2 compressed packages, including 47 samples in Lhasa and Nagqu in 2019, and 49 samples in Ali and Nagqu in 2020. Survey photos. The photos of each sample point are placed in a separate folder. The folder is named the sample number. The photos of each sample point include photos of the landscape around the sample point, photos of the plant community in the sample square, and Close-up photos of the dominant species, you can observe the status of the vegetation community in the plot, the condition of the soil surface, the slope of the surrounding sampling area, human interference, etc. The photos are all original images, jpg format, taken with mobile phones or cameras, sampling The specific longitude and latitude information of the points can be viewed in a separate Excel table in the compressed package.
TIAN Dashuan
The dataset includes FPAR, GPP, NPP, evapotranspiration product and LAI product. FPAR product is and LAI product are obtained from the MODIS Terra MOD15A2H dataset, GPP and NPP product are obtained from the MOD15A2H dataset and evapotranspiration product is obtained from MODIS Terra MOD16A2 dataset from 2000 to 2019 over the Tibetan Plateau,which is downloaded from USGS, and their formats are converted from .hdf to .tif by GDAL.The quality assessment files are also included for aboved products,and they are stored in an efficient bit-encoded manner.The MODIS products play an important role in forest, agriculture, ecology.
GONG Chengjuan
This data set contains the biological property data of soil samples from several scientific research routes in the Qinghai Tibet Plateau from 2019 to 2021, including the information of the collector, collection time, collection location, longitude and latitude, altitude, vegetation type, sampling depth, phosphatase activity, microbial respiration, nitrogen transformation characteristics, functional gene abundance, fungi, bacteria, protobiotic diversity, etc. The analysis of various soil properties refers to the requirements of "technical specification for soil environmental quality monitoring", and the first-hand data obtained through laboratory analysis. The data quality is controlled by determining blank samples, duplicate samples and standard samples. The data set can be used to evaluate soil quality and function under the influence of climate change and human activities.
ZHANG Limei
This dataset includes data recorded by the Cold and Arid Research Network of Lanzhou university obtained from an observation system of Meteorological elements gradient of Dunhuang Station from January 1 to December 31, 2020. The site (93.708° E, 40.348° N) was located on a wetland in the Dunhuang west lake, Gansu Province. The elevation is 990 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (4m and 8 m, towards north), wind speed and direction profile (windsonic; 4m and 8 m, towards north), air pressure (1 m), rain gauge (4 m), infrared temperature sensors (4 m, towards south, vertically downward), soil heat flux (-0.05 and -0.1m ), soil soil temperature/ moisture/ electrical conductivity profile (below the vegetation in the south of tower, -0.05 and -0.2 m), photosynthetically active radiation (4 m, towards south), four-component radiometer (4 m, towards south), sunshine duration sensor(4 m, towards south). The observations included the following: air temperature and humidity (Ta_4 m, Ta_8 m; RH_2 m, RH_4 m, RH_8 m) (℃ and %, respectively), wind speed (Ws_4 m, Ws_8 m) (m/s), wind direction (WD_4 m, WD_8 m) (°), air pressure (press) (hpa), precipitation (rain) (mm), four-component radiation (DR, incoming shortwave radiation; UR, outgoing shortwave radiation; DLR_Cor, incoming longwave radiation; ULR_Cor, outgoing longwave radiation; Rn, net radiation) (W/m^2), infrared temperature (IRT) (℃), photosynthetically active radiation (PAR) (μmol/ (s m-2)), soil heat flux (Gs_0.05m, Gs_0.1m) (W/m^2), soil temperature (Ts_0.05m, Ts_0.2m) (℃), soil moisture (Ms_0.05m, Ms_0.2m) (%, volumetric water content), soil conductivity (Ec_0.05m, Ec_0.2m)(μs/cm), sun time(h). The data processing and quality control steps were as follows: (1) The AWS data were averaged over intervals of 10 min for a total of 144 records per day and missing records were denoted by -6999.. (3) Unphysical data were rejected. (4) The data marked in red are problematic data. (5) The format of the date and time was unified, and the date and time were collected in the same column.
ZHAO Changming, ZHANG Renyi
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 contains the survey information of the sample community species of 5 samples at each sampling site, including species name, coverage, height (5 plants) and number of plants. A total of 28 samples (28 Excel forms) are named from QZKK- 03-001 to QZKK-03-028, in a compressed file package, the other three files are the aboveground biomass, underground biomass and the longitude and latitude information of the sampling point of the species, which need to be compared with each other (species height, coverage , Number of plants, aboveground/underground biomass collection and survey plot area is 1m*1m, each sample point has 10 plots, of which 2, 4, 6, 8, 10 and other plots are collected for different species. P2, P4, P6, P8, P10 are expressed, the coverage is expressed as a percentage, the height is cmcm, and the number of plants is expressed by the number of species. The root biomass of each plot is divided into 3 layers, each layer 10cm, each item The units of the indicators are marked in the title). The data are all collected and measured on the spot, the height is measured by a tape measure, and the coverage is obtained by the estimation method. The data is of good quality and can be used to calculate biodiversity and species distribution.
SHANG Zhanhuan
From July to August 2019, taking Hongyuan County on the eastern edge of the Zoige Plateau as the scientific research site, select alpine grasslands with typical land use types and typical slopes to set up transects, and set up transects every 50m from the top to the foot of the mountain. The characteristics of the plant community were investigated. The plot size was 50cm×50cm, with 3 replicates, a total of 63 plant plots were investigated, and the number of plant species, quantity, above-ground biomass, diversity index, etc. were obtained. Provide reliable data for the study of plant productivity and community changes in different altitude gradients and different grassland types.Accurately quantifying the effects of alpine grass and shrub vegetation changes on plant communities and vegetation evolution will help optimize multi-objective management of grassland ecosystems on the Qinghai-Tibet Plateau.
HU Jian
Data content: the data set product contains the 30-meter resolution product of suspended solids concentration in the water body of the Qinghai-Tibet Plateau, which can be used as the key parameters for ecosystem-related research in Qinghai-Tibet Plateau. Data sources and processing methods: Product inversion is mainly based on the Landsat series data, by extracting the effective aquatic reflectance, to obtain the water composition information. This product is the preliminary result of extracting the concentration information of suspended solids in water using the empirical / semi-empirical method. Data quality: the overall accuracy is high, and the product will be further optimized in combination with the measured data of scientific research. Results and prospects of data application: the data set will be continuously updated and can be used for the study and analysis of ecosystem change in the Qinghai-Tibet Plateau.
LIU Huichan
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 contains experimentally measured soil nutrient data collected in typical small watersheds in Sichuan Province, Tibet Autonomous Region and Qinghai Province. The data comes from the survey of grassland, cultivated land, and woodland in Minhe County, Menyuan County and the east area of Qinghai Lake in the second Qinghai-Tibet Plateau scientific expedition, and recorded detailed soil parameters (including organic carbon, ph, soil Cation exchange capacity, water content, etc.) can provide important values for tracing the source of soil water erosion in small watershed areas and understanding the soil environment.
SU Zhengan
Leaf area index is an important structural parameter of ecosystem, which is used to reflect the number of plant leaves, changes in canopy structure, life vitality of plant community and its environmental effects, provide structured quantitative information for the description of material and energy exchange on the surface of plant canopy, and balance the energy of carbon accumulation, vegetation productivity and interaction between soil, plant and atmosphere in ecosystem, Vegetation remote sensing plays an important role. The data comes from the distributed leaf area index instrument independently developed by the project (based on hemispheric image), which takes hemispheric images of forest canopy at fixed time, fixed point and from bottom to top, and uploads them through wireless network. This data acquisition is the original hemispherical image, which needs further processing to calculate the leaf area index, which can be processed by hemiview and other software.
SU Hongxin
The data set is the vegetation sample survey photos of Qilian County in Qinghai Province during the second comprehensive scientific expedition to the Qinghai-Tibet Plateau. Iincluding the survey photos of 28 sample points in Qilian County in 2020. The photos of each sample point are placed in a separate In a folder, the folder is named the sample number. The photos of each sample point include photos of the landscape around the sample point, photos of the plant community in the sample square and close-up photos of the dominant species. The vegetation in the sample can be observed The status of the community, the status of the soil surface and the slope of the surrounding sampling area, human interference, etc. The photos are all original images, in jpg format, taken with a mobile phone or camera, and the specific latitude and longitude information of the sampling points are in a separate Excel table in the compressed package In, you can compare and view.
SHANG Zhanhuan
Collect daily meteorological data from 1980 to 2018 from the Meteorological Data Sharing Center of China Meteorological Administration. Humidity Index (HI) is calculated by the ratio of annual precipitation to potential evapotranspiration. Anusplin interpolation software is used to obtain a spatial dataset of HI 1km resolution.Through spatial data collection, model simulation of the spatiotemporal pattern of typical water and soil ecosystem services such as ecosystem production, carbon fixation, hydrological regulation, and soil conservation, revealing the spatiotemporal change pattern of water and soil ecosystem services in the watershed, combining climate change, socioeconomic data and ecological environmental protection policies Implementation, land use conversion and other factors, combined with trade-off analysis and structural equation modeling to quantify the trade-offs and synergies of these water and soil ecosystem services and their main driving forces, to provide more effective and scientific ecological protection and multi-purpose land use for Ruoergai Wetland Optimal management provides theoretical support.
HU Jian
The effective energy and material transfer (EEMT) data set (1980-2018) for 1km on the Zoige Plateau. Effective energy and matter transfer (EEMT) is closely related to the structure and function of the earth's key zones. The unit of effective energy and matter transfer (EEMT) is (Jm-2 s-1or W m-2). The heat energy (EPPT) related to the effective rain energy material transfer, the net primary production energy material transfer (EBIO), and the effective energy and material transfer (EEMT) (which is the sum of both EPPT and EBIO) are used as comprehensive climate indicators, The EEMTMODEL model simulation method is used to evaluate these three indicators, and the Anusplin interpolation software is used to obtain a spatial data set with a resolution of EEMT 1km.
HU Jian
From July to August 2019, take Hongyuan County on the Qinghai-Tibet Plateau as the scientific research site, select typical land use types of grassland and typical slopes to set up transects. After plant sample surveys, the soil profiles of grassland, shrubs, and wetland ecosystems (0-10 cm, 10-20 cm, 20-40 cm, 40-60 cm and 60-100 cm) soil samples were collected, 3 replicates for each soil layer, 104 soil samples were collected, and the soil was measured The bulk density and water content.Through the sampling of various lines to form the surface sampling points and spatial data sets of the Baihe River Basin, it simulates the spatiotemporal pattern of typical water and soil ecosystem services such as ecosystem production, carbon fixation, hydrological regulation and soil conservation, and reveals the spatiotemporal changes of water and soil ecosystem services at the basin scale Pattern, combined with factors such as climate change, socio-economic data, implementation of ecological and environmental protection policies, and land use change.
HU Jian
1) Data content: species list and distribution data of sand lizard and hemp lizard in the Qaidam Basin, including class, order, family Chinese name, family Latin name, genus Chinese name, genus Latin name, species Latin name, species Chinese name, country, province, city, county, town and township, etc; 2) Data source and processing method: Based on the field investigation of amphibians and reptiles in the arid desert area of the Qaidam Basin from 2007 to 2021, the species composition and distribution range of toad-headed agamas and racerunners in this area are recorded; 3) Data quality description: the investigation, collection and identification personnel of samples are professionals. The collection information of samples is checked to ensure the quality of distribution data; 4) Data application achievements and prospects: comprehensive analysis of species diversity and distribution data of toad-headed agamas and racerunners in the Qaidam Basin can provide important data for biodiversity cataloguing in northwest desert region and arid Central Asia, and provide scientific basis for assessing biodiversity situation and formulating conservation strategies.
GUO Xianguang
The dataset is the normalized burnt ratio (NBR) products from 1980s to 2019 over the Tibetan Plateau。The dataset is producted based on Landsat surface reflectance dataset. It is calculated by the NBR equation which use the difference ratio between the NIR band and SWIR1 band to enhance the feature of the burned area.And the corresponding production of quality identification documents (QA) is also generated to identify the cloud, ice and snow.NBR is usually used to extract burned area information effectively, and to monitor the vegetation restoration in burned area .
PENG Yan
The dataset is the normalized difference moisture index (NDMI) products from 1980s to 2019 over the Tibetan Plateau。The dataset is producted based on Landsat surface reflectance dataset. It is calculated by the NDMI equation which use the difference ratio between the NIR band and SWIR2 band to quantitatively reflect the water content of vegetation canopy .And the corresponding production of quality identification documents (QA) is also generated to identify the cloud, ice and snow.NDMI is highly correlated with canopy water content and can be used to estimate vegetation water content, and it is also used to analyze the change of land surface temperature because it is strongly correlated with land surface temperature.
PENG Yan
The dataset is the modified soil adjusted vegetation index (MSAVI) products from 1980s to 2019 over the Tibetan Plateau。The dataset is producted based on Landsat surface reflectance dataset. It is calculated by the MSAVI equation which modifies the problem that SAVI is not sensitive in the dense vegetation area.And the corresponding production of quality identification documents (QA) is also generated to identify the cloud, ice and snow.MSAVI is stable in the dense vegetation area, but is not sensitive in the sparse vegetation area .
PENG Yan
The data set is based on the field observation and survey along the roads in Sichuan, Qinghai and Tibet. 100 * 100m sample plots are selected along the roads, and 1m * 1m or 2m * 2m sample plots are selected according to the vegetation distribution. The survey content involves the weather, geographical location, geomorphic characteristics, slope direction, slope position, soil type, vegetation type, plant community name, surface characteristics, human activity mode and vegetation status in the sample plot. For the investigation of basic information and vegetation status of the sample plot, the methods of artificial observation and tool measurement are adopted. In the vegetation status, the vegetation name refers to "herb species in Qinghai Province", mainly investigating its height, coverage, life form and other information. The summary of the survey results of the data set can be used as a reference to supplement the herb diversity of the Qinghai Tibet Plateau. The data set is the vegetation survey content of the actual sample plot, one file per day, and the file naming method is: year + day. For example, 20200712 represents the questionnaire content on July 12, 2020, and 202007023 represents the questionnaire content on July 23, 2020.
LI Jingji
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