In the previous project, three different types of desert investigation and observation sites in the lower reaches of Heihe River were set up. Different kinds of desert plants with the same average growth and size as the observation site were selected for the above ground biomass and underground biomass total root survey. The dry weight was the dry weight at 80 ℃, and the root shoot ratio was the dry weight ratio of the underground biomass to the aboveground biomass. Species: Elaeagnus angustifolia, red sand, black fruit wolfberry, bubble thorn, bitter beans, Peganum, Tamarix and so on.
SU Peixi
Net Primary Productivity (NPP) reflects the efficiency of plant fixation and conversion of light energy as a compound. It refers to the amount of organic matter accumulated per unit time and unit area of green plants. It is the organic matter produced by plant photosynthesis. The remainder of the Gross Primary Productivity (GPP) minus Autotrophic Respiration (RA), also known as net primary productivity. As an important part of the surface carbon cycle, NPP not only directly reflects the production capacity of vegetation communities under natural environmental conditions, but also is an important component to measure regional land use/cover change. The net primary productivity data product uses the light energy utilization (GLOPEM) model algorithm to invert multiple scale raster data products obtained from various satellite remote sensing data (Landsat, MODIS, etc.), which is also the main factor for determining and regulating ecological processes.
LIU Tie
1) data content: distribution map of Amphipoda in the Tibetan Plateau; 2) data source and processing method: based on the list of Amphipoda in Tibetan and its basic database of distribution, including longitude and latitude, altitude, and the ArcView software has been used to make the distribution map of Amphipoda in the Tibetan Plateau; 3) data quality description: sample collection, longitude and latitude, altitude information are checked to ensure the quality of distribution data, all analysts have received strict training in the laboratory; 4) data application achievements and prospects: comprehensively analyze the distribution data, species diversity and genetic diversity of Amphipoda in Tibetan Plateau, discuss the impact of climate change on Amphipoda diversity and the response of Amphipoda to environmental change from the perspective of evolution and genetics, and provide scientific basis for biodiversity assessment and ecological protection in the Tibetan Plateau; 5) legend: brown circles for samples from Tian Shan, pink circles for samples at north side of the Yarlung Zangbo River with diversification age of 2-4 Ma, greeen triangles for samples at south side of the Yarlung Zangbo River with diversification age of 4-6 Ma, yellow circles for samples from Himalayas with diversification age around 3 Ma, orange square for samples from Hengduan Mt. with diversificaiton age of 5-7 Ma, blue circles for samples from east of the Tibetan Plateau.
HOU Zhonge
This data set is a three-level classification map of Eurasian grassland remote sensing in 2009. The data is in TIF grid format, with a spatial resolution of 1km. The three-level grassland is classified as: temperate meadow grassland, temperate typical grassland, temperate desertification grassland, temperate grassland desertification, and temperate desert. The data is processed according to the ESA global cover 2009 Product global cover map, combined with the historical meteorological data (precipitation, annual accumulated temperature, humidity coefficient, evaporation) and DEM data of ECMWF website. The data can be used to provide the basis for the distribution information and temporal and spatial variation analysis of warm grassland in Eurasia.
TANG Jiakui
This data set is a spatiotemporal variation map of temperate grassland types in Eurasia - three level classification of Inner Mongolia region of China (2009). The data is in TIF grid format with a spatial resolution of 1km. The data is processed on the basis of the existing grass type map of Inner Mongolia grassland. The grassland type map of Inner Mongolia grassland is based on the field survey data, neimengqi County as the unit, the grassland type classification system, on the basis of prediction, the field sample data, remote sensing image and other information data are superposed, and the local historical grassland survey data and relevant data are referred to, and the field plot is modified. We select 2000-2009 historical meteorological data, further analyze and modify the satellite data, and carry out spatial interpolation calculation. The classification of temperate grassland in Inner Mongolia was obtained. The data can be used to provide the basis for the distribution information and temporal and spatial variation analysis of warm grassland in Eurasia.
TANG Jiakui
By applying Supply-demand Balance Analysis, the water resource supply and demand of the whole river basin and each county or district were calculated, based on which the vulnerability of the water resources system of the basin was evaluated. The IPAT equation was used to set a future water resource demand scenario, setting variables such as future population growth rate, economic growth rate, and unit GDP water consumption to establish the scenario. By taking 2005 as the base year and using assorted forecasting data of population size and economic scale, the future water demand scenarios of various counties and cities from 2010 to 2050 were forecast. By applying the basic structure of the HBV conceptual hydrological model of the Swedish Hydrometeorological Institute, a model of the variation tendency of the basin under climate change was designed. The glacial melting scenario was used as the model input to construct the runoff scenario under climate change. According to the national regulations of the water resources allocation of the basin, a water distribution plan was set up to calculate the water supply comprehensively. Considering of the supply and demand situation, the water resource system vulnerability was evaluated by the water shortage rate. By calculating the (grain production) land pressure index of the major counties and cities in the basin, the balance of supply and demand of land resources under the climate change, glacial melt and population growth scenarios was analyzed, and the vulnerability of the agricultural system was evaluated. The Miami formula and HANPP model were used to calculate the human appropriation of net primary biomass and primary biomass in the major counties and cities for the future, and the vulnerability of ecosystems from the perspective of supply and demand balance was assessed.
YANG Linsheng, ZHONG Fanglei
Desertification is a kind of land degradation with aeolian sands as the main symbol caused by the uncoordinated human-land relationship in arid, semi-arid and some semi-humid regions of northern China. Data source: edited by the China Institute of Glacial and Frozen Desert and coordinated by the Institute of Geography of the Chinese Academy of Sciences. Based on aerial photographs from the 1970s and field research, a 1: 2 million desert map was drawn. Mapping of the 14 million "Map of the People's Republic of China" published in 1971. First, the data set content 1.Desert_Ch_2009 (desert distribution) 2.Dune_hight_Ch_200 (dune height) 3.Gobi_Ch_200 (Gobi) 4.Wind_eroded_land_Ch_200 (wind erosion data) The fields of the desertification attribute table are as follows: (1) Semifixed (semi-fixed dunes): undulating sandy land (2-1), thicket dunes (2-2), parabolic dunes (2-3), beam nest dunes (2-4), sand ridges And dendritic sand ridge (2-5), honeycomb sand dune (2-6), honeycomb sand ridge (2-7), composite sand ridge (2-8) (2) Fixation (fixed dune): flat sandy land (3-1), grassland bush (3-2), sand ridge (3-3), honeycomb sand dune (3-4) (3) Migratory: Crescent sand dunes and dune chains (1-1), Crescent sand ridges and dunes (1-2), Lattice dunes and Lattice dune chains (1-3), Fish scales Sand dunes (1-4), feathery dunes (1-5), pyramid dunes (1-6), composite dunes and dune chains (1-7), composite dunes (1-8), composite Dome-shaped dunes (1-9), chain-shaped sand hills (sand dunes) (1-10), stacked chain-shaped sand hills (1-11), compound ridge-shaped sand hills (1-12), composite chain-shaped Sand Mountain (1-13), Pyramid Sand Mountain (1-14) (4) class_id: encoding of desertification attributes Projection information PROJCS ["Albers", GEOGCS ["GCS_Beijing_1954", DATUM ["Beijing_1954", SPHEROID ["Krasovsky_1940", 6378245.0,298.3]], PRIMEM ["Greenwich", 0.0], UNIT ["Degree", 0.0174532925199433]], PROJECTION ["Albers_Conic_Equal_Area"], PARAMETER ["False_Easting", 0.0], PARAMETER ["False_Northing", 0.0], PARAMETER ["longitude_of_center", 105.0], PARAMETER ["Standard_Parallel_1", 25.0], PARAMETER ["Standard_Parallel_2", 47.0], PARAMETER ["latitude_of_center", 0.0], UNIT ["Meter", 1.0]]
WANG Jianhua
Data for 100000 desert map qaidam river basin, cutting since China 1:100000 desert sand data set, the data of TM images in 2000 data sources, to interpret, extraction, revision, using remote sensing and geographic information system technology combining 1:100000 scale mapping, the desert, sand and gravel gobi for thematic mapping.The desert codes are as follows: mobile sandy land 2341010, semi-mobile sandy land 2341020, semi-fixed sandy land 2341030, gobi desert 2342000, saline alkaline land 2343000.
WANG Jianhua
The vegetation regulation mechanism project of soil water cycle in arid desert areas belongs to the national natural science foundation "environment and ecological science in western China" major research plan, led by li xinrong, a researcher of the institute of environment and engineering in dry and cold areas, Chinese academy of sciences, with the running time of 2003.1-2005.12. Remittance data of the project: 1. Dataset of observation field of shapotou railway vegetation sand fixation protection system (excel) Plant and soil information in the vegetation-sand fixation zone established in 1956, 1964, 1981 and 1987.Since the establishment of the observation field, long-term soil moisture and vegetation surveys have been conducted. This database records the soil moisture data after the neutron tube installation in August 2002, the vegetation data from 2003 to 2005 (vegetation structure, herb structure, shrub structure, etc.), and the soil physical and chemical properties data (particle size, total N,P2O5,K2O, hydrolyzed N) of the irregular surveys. 2. Physiological data set of desert plant stress (excel) From 2003 to 2005, the physiological and biochemical characteristics of typical plant communities and their dominant species in steppe desert under natural and simulated environmental conditions were analyzed.(including photosynthetic transpiration, fluorescence, biochemistry and other indicators) 3. Soil infiltration and evapotranspiration data set (excel) Precipitation infiltration process, soil water dynamics and evapotranspiration of fixed sand dunes monitored by desert artificial vegetation using TDR and Lysimeters from 2002 to 2005. 4. Data set of comprehensive survey on soil and vegetation in the southeastern margin of tengger desert (excel) In 2003-2004, silver (sichuan), yan (latour) highway, silver (sichuan) (state) highway through the tengger desert area, set up along the road of eight samples, 449 samples of soil conductivity, Ph, organic matter, total nitrogen (content) and vegetation (plants, coverage, average height, biomass, strains, coverage, high average, biomass).
LI Xinrong
The data is the distribution map of 100,000 deserts in Qinghai Lake Basin. This data uses 2000 TM image as the data source for interpretation, extraction and revision. Remote sensing and geographic information system technology are combined with the mapping requirements of a scale of 1: 100,000 to carry out thematic mapping of deserts, sands and gravelly Gobi. Data attribute table: area (area), perimeter (perimeter), ashm_ (sequence code), class (desert code) and ashm_id (desert code), of which the desert code is as follows: mobile sand 2341010, semi-mobile sand 2341020, semi-fixed sand 2341030, Gobi desert 2342000 and saline-alkali land 2343000.
WANG Jianhua, YAN Changzhen
The compilation basis of frozen soil map includes: (1) frozen soil field survey, exploration and measurement data; (2) aerial photo and satellite image interpretation; (3) topo300 1km resolution ground elevation data; (4) temperature and ground temperature data. Among them, the distribution of permafrost in the Qinghai Tibet Plateau adopts the research results of nanzhuo Tong et al. (2002). Using the measured annual average ground temperature data of 76 boreholes along the Qinghai Tibet highway, regression statistical analysis is carried out to obtain the relationship between the annual average ground temperature and latitude, elevation, and based on this relationship, combined with the gtopo30 elevation data (developed under the leadership of the center for earth resources observation and science and technology, USGS) Global 1 km DEM data) to simulate the annual mean ground temperature distribution over the whole Tibetan Plateau. Taking the annual average ground temperature of 0.5 ℃ as the boundary between permafrost and seasonal permafrost, the boundary between discontinuous Permafrost on the plateau and island Permafrost on the plateau is delimited by referring to the map of ice and snow permafrost in China (1:4 million) (Shi Yafeng et al., 1988); in addition, the division map of Permafrost on the big and small Xing'an Mountains in the Northeast (Guo Dongxin et al., 1981), the distribution map of permafrost and underground ice around the Arctic (b According to rown et al. 1997) and the latest field survey data, the Permafrost Boundary in Northeast China has been revised; the Permafrost Boundary in Northwest mountains mostly uses the boundary defined in the map of ice and snow permafrost in China (1:4 million) (Shi Yafeng et al., 1988). According to the data, the area of permafrost in China is about 1.75 × 106km2, accounting for about 18.25% of China's territory. Among them, alpine permafrost is 0.29 × 106km2, accounting for about 3.03% of China's territory. For more information, please refer to the specification of "1:4 million map of glacial and frozen deserts in China" (Institute of environment and Engineering in cold and dry areas, Chinese Academy of Sciences, 2006)
WANG Tao
This dataset is the first 1: 100,000 desert spatial database in China based on the graphic data of desert thematic maps. It mainly reflects the geographical distribution, area size, and mobility of sand dunes in China. According to the system design requirements and relevant standards, the input data is standardized and uniformly converted into a standard format for various types of data input. Build a library to run the delivery system. This project uses the TM image in 2000 as the information source, and interprets, extracts, and edits the coverage of the national land use map and TM digital image information in 2000. It uses remote sensing and geographic information system technology to 1: 100,000 Thematic mapping requirements for scale bar maps were made on the desert, sandy land and gravel Gobi in China. The 1: 100,000 desert map across the country can save users a lot of data entry and editing work when they are engaged in research on resources and the environment. Digital maps can be easily converted into layout maps The dataset properties are as follows: Divided into two folders e00 and shp: Desert map name and province comparison table in each folder 01 Ahsm Anhui 02 Bjsm Beijing 03 Fjsm Fujian 04 Gdsm Guangdong 05 Gssm Gansu 06 Gxsm Guangxi Zhuang Autonomous Region 07 Gzsm Guizhou 08 Hebsm Hebei 09 Hensm Henan 10 Hljsm Heilongjiang 11 Hndsm Hainan 12 Hubsm Hubei 13 Jlsm Jilin Province 14 Jssm Jiangsu 15 Jxsm Jiangxi 16 Lnsm Liaoning 17 Nmsm Inner Mongolia Gu Autonomous Region 18 Nxsm Ningxia Hui Autonomous Region 19 Qhsm Qinghai 20 Scsm Sichuan 21 Sdsm Shandong 22 Sxsm Shaanxi Province 23 Tjsm Tianjin 24 Twsm Taiwan Province 25 Xjsm Xinjiang Uygur Autonomous Region 26 Xzsm Tibet Autonomous Region 27 Zjsm Zhejiang 28 Shxsm Shanxi 1. Data projection: Projection: Albers False_Easting: 0.000000 False_Northing: 0.000000 Central_Meridian: 105.000000 Standard_Parallel_1: 25.000000 Standard_Parallel_2: 47.000000 Latitude_Of_Origin: 0.000000 Linear Unit: Meter (1.000000) 2. Data attribute table: area (area) perimeter ashm_ (sequence code) class (desert encoding) ashm_id (desert encoding) 3. Desert coding: mobile sandy land 2341010 Semi-mobile sandy land Semi-fixed sandy land 2341030 Gobi 2342000 Saline land 2343000 4: File format: National, sub-provincial and county-level desert map data types are vector shapefiles and E00 5: File naming: Data organization based on the National Basic Resources and Environmental Remote Sensing Dynamic Information Service System is performed on the file management layer of Windows NT. The file and directory names are compound names of English characters and numbers. Pinyin + SM composition, such as the desert map of Gansu Province is GSSM. The flag and county desert map is the pinyin + xxxx of the province name, and xxxx is the last four digits of the flag and county code. The division of provinces, districts, flags and counties is based on the administrative division data files in the national basic resources and environmental remote sensing dynamic information service operation system.
WANG Jianhua, WANG Yimou, YAN Changzhen, QI Yuan
From April to June 2019, we used both live traps and camera traps to collect mammal diversity and distributions along the elevational gradients at the Yarlung Zangbo Grand Canyon National Nature Reserve. We set 64 trap lines for small mammals inventory, with a total of 11456 live trap nights. We collected 1061 individuals and 2394 tissue samples of small mammals during the field sampling. We also retrived images of 60 camera traps placed between October 2018 and April 2019. We obtained 4638 pictures of wild animals and 654 captures of anthopogenic activities. The camera traps were reset in the same locations after renew batteries and memory cards. Small mammal data consist of richness, abundance, traits, environmental gradients etc, and could be used to model relationship between environmental gradients and traits concatenated by richness matrix. Camera trap data could inventory endangered species in the region, and provide information to identify biodiversity hotspots and conservation priorities.
LI Xueyou
At the end of September and the beginning of October, 2013, desert plants in typical areas of heihe basin stopped their growth period to conduct year-end ecological survey. There are altogether 8 survey and observation fields, which are: piedmont desert, piedmont gobi, middle reaches desert, middle reaches gobi, middle reaches desert, lower reaches desert, lower reaches gobi and lower reaches desert, with a size of 40m×40m. Three 20m×20m large quadrats were fixed in each observation field, named S1, S2 and S3, and regular shrub surveys were conducted.Each large quadrat was fixed with 4 5m x 5m small quadrats, named A, B, C, D, for the herbal survey.
SU Peixi
As determined in mid-august 2013, planting species: bubbly spines (different habitats are mid-range intermountain lowland and gobi), red sand (different habitats are mid-range gobi and downstream gobi). Using the brother company of LI - 6400 Portable Photosynthesis System (Portable Photosynthesis System, LI - COR, USA) and LI - 3100 leaf area meter, etc., to the desert plant photosynthetic physiological characteristics were observed. The symbolic meaning of the observed data is as follows: Obs，observation frequency ； Photo ，net photosynthetic rate，μmol CO2•m–2•s–1； Cond stomatal conductance，mol H2O•m–2•s–1 ; Ci, Intercellular CO2 concentration, μmol CO2•mol-1； Trmmol，transpiration rate，mmol H2O•m–2•s–1； Vpdl，Vapor pressure deficit，kPa； Area，leaf area，cm2； Tair，free air temperature ，℃； Tleaf，Leaf temperature，℃； CO2R，Reference chamber CO2 concentration，μmol CO2•mol-1； CO2S，Sample chamber CO2 concentration，μmol CO2•mol-1； H2OR，Reference chamber moisture，mmol H2O•mol-1； H2OS，Sample chamber moisture，mmol H2O•mol-1； PARo，photon flux density，μmol•m–2•s–1； RH-R，Reference room air relative humidity，%； RH-S，Relative humidity of air in sample room，%； PARi，Photosynthetic effective radiation，μmol•m–2•s–1； Press，barometric pressure，kPa； Others are the state parameters of the instrument at the time of measurement.
SU Peixi
1. The data is digitized in the map of the development degree of desertification in daqintara (1958) from the drawing. The specific information of the map is as follows: * chief editor: zhu zhenda, qiu xingmin * editor: wang yimou * drawing: feng yu-sun, yao fa-fen, wu wei, wang jianhua, wang zhou-long * cartographic unit: desert laboratory, Chinese academy of sciences * publishing house: xi 'an map publishing house, unified isbn: 12461.26 二. The data is stored in ESRI Shapefile format, including the following layers: 1, * desertification development degree map (1958) : desertification1958.shp 2, * double river: river_double-shp 3, * single river: river_single-shp 4, Road: SHP 5, Lake: lake.shp 6, street: Stree. SHP 7, Railway: Railway. SHP 8, forest belt: Tree_networks 9. Residential land: residential. SHP 10. Map: map_margin.shp 三, desertification development degree figure property fields and encoding attribute: (1) desertification degree (Type) : a flow of sand (Semi - shifting Sandy Land), sand form class (Shapes), grass (Grassland), forest Land, Woodland and forest density (W_density), the cultivated Land (Farmland) (2) sand Shapes: Barchan Dunes, Flat Sandy Land, undulated Sandy Land, Vegetated Dunes (3) the grass (Grassland) (4) Woodland: Woodland. (5) woodland density (W_density): Sparse Woodlot (6) Farmland: Dryfarming and Abandoned Farmland, Irrigated Fields
WANG Jianhua, ZHU Zhenda, QIU Xingmin, YAO Fafen, FENG Yusun
1. The data is digitized in the map of the development degree of desertification in daqintara (1974) from the drawing. The specific information of the map is as follows: * chief editor: zhu zhenda, qiu xingmin * editor: wang yimou * drawing: feng yu-sun, yao fa-fen, wu wei, wang jianhua, wang zhou-long * cartographic unit: desert laboratory, Chinese academy of sciences * publishing house: xi 'an map publishing house, unified isbn: 12461.26 二. The data is stored in ESRI Shapefile format, including the following layers: 1, * desertification development degree map (1974) : desertification1974.shp 2, * double river: river_double-shp 3, * single river: river_single-shp 4, Road: SHP 5, Lake: lake.shp 6, street: Stree. SHP 7, Railway: Railway. SHP 8, forest belt: Tree_networks 9. Residential land: residential. SHP 10. Map: map_margin.shp 三, desertification development degree figure property fields and encoding attribute: (1) desertification degree (Type) : a flow of sand (Semi - shifting Sandy Land), sand form class (Shapes), grass (Grassland), forest Land, Woodland and forest density (W_density), the cultivated Land (Farmland) (2) sand Shapes: Barchan Dunes, Flat Sandy Land, undulated Sandy Land, Vegetated Dunes (3) the grass (Grassland) (4) Woodland: Woodland. (5) woodland density (W_density): Sparse Woodlot (6) Farmland: Dryfarming and Abandoned Farmland, Irrigated Fields
WANG Jianhua, ZHU Zhenda, QIU Xingmin, FENG Yusun, YAO Fafen
Background: this data interchange is the first data interchange of the key project of "integrated study of eco-hydrological processes in heihe basin", "genomics research on drought tolerance mechanism of typical desert plants in heihe basin".The main research targets of the key projects is a typical sand desert plants are Holly, using the current international advanced a new generation of gene sequencing technology to the whole genome sequence and gene transcription of Holly group sequence decoding, so as to explore related to drought resistance gene and gene groups, and transgenic technology in model to verify their drought resistance in plants. Process and content: as genome sequencing requires special sequencing equipment, the project is huge and the process is complex (mainly including genome library construction, sequencing, data analysis and genome assembly), so it needs to be completed by a professional sequencing company.After contacting with sequencing companies, we learned that before sequencing an unknown genome, the size and complexity of the genome should be predicted, which is a necessary prerequisite for designing sequencing schemes and strategies.Therefore, in 2013, we mainly predicted the chromosome composition, genome size and complexity of sand Holly, and successfully established the extraction and purification method of its genomic DNA.The results showed that the plant was diploid, the genome was composed of 9 staining lines (18 lines of diploid), and the genome size was 1.07G.The quality test results of the genomic DNA indicated that the requirements of the obtained DNA complex sequencing have been sent to the sequencing company for library construction and sequencing, which is now in progress.In addition, in order to obtain a large number of uniform plant materials, we have discussed the induction of callus, which has been successful.Due to these reasons, we were unable to complete the genome sequencing and submit the relevant data of sand Holly in accordance with the original plan of the project this year, mainly because we did not count the predicted contents of the genome before. Data usage: the data obtained in this year on ploidy, karyotype composition and genome size of lycopodium SPP.The success of the callus induction provides a high-quality material guarantee for the subsequent transcriptome sequencing and drought-resistance mechanism research experiments, and it is also a new contribution to the cytological and physiological research of the plant.
HE Junxian, GU Lifei
In mid-july 2011, photosynthetic organs (leaves or assimilating branches) of typical desert plants were collected and brought back to the laboratory in a liquid nitrogen tank for determination. The analysis indexes mainly include soluble protein unit: mg/g;Free amino acid unit: g/g;Chlorophyll content unit: mg/g;Superoxide dismutase (SOD) unit: U/g FW;Catalase (CAT) unit: U/(g•min);POD unit: U/(g•min);Proline (Pro) unit: g/g; Soluble sugar unit: g/g;Malondialdehyde (MDA) is given in moles per liter.
SU Peixi
On the basis of physiological and biochemical analysis of photosynthetic organs (leaves or assimilating branches) of typical desert plants in heihe river basin collected in mid-july 2011, some photosynthetic organs of desert plants were collected in mid-july 2012 and put into a liquid nitrogen tank and brought back to the laboratory for determination. Physiological analysis indexes mainly include: soluble protein unit: mg/g;Free amino acid unit: g/g;Chlorophyll content unit: mg/g;Superoxide dismutase (SOD) unit: U/g FW;Catalase (CAT) unit: U/(g•min);POD unit: U/(g•min);Proline (Pro) unit: g/g; Soluble sugar unit: g/g;Malondialdehyde (MDA) is given in moles per liter.
SU Peixi
Contact Support
Northwest Institute of Eco-Environment and Resources, CAS
0931-4967287
poles@itpcas.ac.cn
Links
National Tibetan Plateau Data CenterFollow Us
A Big Earth Data Platform for Three Poles © 2018-2020 No.05000491 | All Rights Reserved
｜ 
No.11010502040845
Tech Support: westdc.cn
