Through the observation of tissue sections of root system, stem and leaf of Ammopiptanthus mongolicus, it is found that Ammopiptanthus mongolicus has morphological characteristics of efficient absorption, transportation and storage of water. Through the study of physiology and biochemistry of Ammopiptanthus mongolicus, the physiological and molecular mechanism of Ammopiptanthus mongolicus adapting to water stress through osmotic adjustment under drought stress was preliminarily confirmed. Through the study of physiological characteristics of Ammopiptanthus mongolicus under drought conditions, the change rule of proline accumulation with the process of drought stress was found, which may participate in the regulation mechanism of Ammopiptanthus mongolicus adapting to water stress as an important osmotic regulator. Furthermore, 7 full-length genes involved in proline synthesis, metabolism and transport of Ammopiptanthus mongolicus were cloned and obtained.
SU Yanhua
This dataset is the FPAR observation in the artificial oasis experimental region of the middle stream of the Heihe River Basin. The observation period is from 24 May to 19 July, 2012 (UTC+8). Measurement instruments: AccuPAR (Beijing Normal University) Measurement positions: Core Experimental Area of Flux Observation Matrix 18 corn samples, 1 orchard sample, 1 artificial white poplar sample Measurement methods: For corn, to measure the incoming PAR on the canopy, transmission PAR under the canopy, reflected PAR on the canopy, reflected PAR under the canopy. For orchard and white poplar forest, to measure the incoming PAR outside of the canopy, transmission PAR under the canopy. Corresponding data: Land cover, plant height, crop rows identification
MA Mingguo
From May 2008 to July 2008, several synchronous observation quadrats were set up in the intensive observation area of Linze grassland. According to the spatial resolution of transit sensing, a 1.8km × 1.8km quadrat h and five 360m × 360m quadrats a, B, C, D and E are set up within 2km × 2km around Linze grassland station. There are 64 sampling points in sample h, numbered H01 to H64, and the distance between two adjacent points is 250m, mainly for MODIS synchronization. The sample a, B, C, D and e of 360m × 360m contains 49 sample points, the sample spacing is 60m, and the sample number is 01-49 (for example, sample a is a01-a49). The surface type of sample a is Phragmites australis, the surface type of sample B is saline alkali, and there are sparse Phragmites australis. The surface type of sample C is saline alkali, and Phragmites australis is more sparse than that of sample a. the surface type of sample D is alfalfa, and the surface type of sample e is alfalfa The type of table is barley field. A small sample of 120m × 120m is nested in each sample of a, B, C, D and e. the spacing of sample points in the small sample is 30m (see "sample distribution. PDF" in the data folder). Quadrats a, B, C, D, e and their nested small quadrats are mainly for ASAR, PALSAR, aster and airborne OMIS, widas synchronization. In addition, there are 7 microwave synchronous transects with 25 sampling points in each transect. The interval between the transects is 200m, and the interval between the sampling points on the transect is 100m. The No. l3-11 indicates the No. 11 sampling point on the No. 3 transect. PR2 is a 3 grid × 3 grid quadrat, and the distance between sampling points is 30 m. The number is pr11. There are also two PR2 transects, a total of 11 transects. The coordinates of all sample points are in Excel.
WANG Xufeng, WU Lizong, Qu Yonghua, LI Hongxing, ZHOU Hongmin, HUANG Chunlin
All data in this data set are original data, including meteorological and soil moisture content, stem sap flow, water potential of plant tissue, isotope characteristics of atmospheric and humidified water vapor, fluorescence tracer image, plant photosynthetic fluorescence, and basic data of five desert plants, Tamarix chinensis, Haloxylon ammodendron, Bawang, Nitraria tangutorum and red sand, which are related to field and indoor control experiments Because of the data of expression regulation. 1. Isotopic data of Tamarix chinensis. After humidifying for 1 hour, 2 hours and 3 hours, the tissue samples of indoor and outdoor plants of plexiglass were collected at the same time. The samples were put forward and processed by low-temperature vacuum distillation glass water extraction system, and then used euro The isotopic data were measured by ea3000 element analyzer and isoprime gas stability mass spectrometer. Tamarix Tamarix samples were collected from Sitan village, Jingtai County, including humidification and control samples. The variation data of isotopic composition can be used to determine the way and amount of water vapor absorbed by plant leaves. 2. Fluorescence section photo data: all the data in this data set are original data, including the structural photos under high-power microscope of Tamarix, Haloxylon ammodendron, Nitraria, Bawang, Hongsha and other desert plant leaves in Sitan village of Jingtai County and Ejin Banner. The specific method is as follows: apply fluorescent dye to the surface of desert plant leaves before humidification, collect plant leaves and stems after humidification for 1 hour, 2 hours and 3 hours, put them in liquid nitrogen, take them back to the laboratory, observe and take photos with fluorescence microscope. It can be used to analyze the tissue and organs of water absorption by desert plant leaves and the direction and path of water migration in plants. 3: Gene transcription and expression data: transcription and expression data of Tamarix chinensis, data collection time: May 25, 2014, location: Sitan village, Jingtai County, Gansu Province, data analysis platform: lllumina hisep TM 2000 platform, obtained by transcriptome analysis of baimaike company. 4. Photosynthetic and fluorescence data: photosynthetic and fluorescence parameters measured by photosynthetic apparatus in the field (Sitan village and Ejin Banner, Jingtai County). 5. Sap flow and environmental data: all data are original data. Sap flow data of desert plants measured by stem flow meter, including Tamarix chinensis, Haloxylon ammodendron, Nitraria tangutorum, red sand and other desert plants (Sitan village, Jingtai County and Ejin Banner), and environmental data monitored by automatic weather station, including temperature and humidity.
XIAO Honglang
The experimental data of Yingke Daman in Heihe River Basin is supported by the key fund project of Heihe River plan, "eco hydrological effect of agricultural water saving in Heihe River Basin and multi-scale water use efficiency evaluation". Including: soil bulk density, soil water content, soil texture, corn sample biomass, cross-section flow, etc Data Description: 1. Sampling location of Lai and aboveground biomass: Yingke irrigation district; sampling time: May 2012 to September 2012; Lai and aboveground biomass of maize were measured by canopy analyzer (lp-80), and aboveground biomass was measured by sampling drying method; sample number: 16. 2. Soil texture: Sampling location: Yingke irrigation district and Shiqiao Wudou Er Nongqu farmland in Yingke irrigation district; soil sampling depth is 140 cm, sampling levels are 0-20 cm every 10 cm, 20-80 cm every 20 cm, 80-140 cm every 30 cm; sampling time: 2012; measurement method: laboratory laser particle size analyzer; sample number: 38. 3. Soil bulk density: Sampling location: Yingke irrigation district and Daman irrigation district; sampling depth of soil bulk density is 100 cm, sampling levels are 0-50 cm and 50-100 cm respectively; sampling time: 2012; measurement method: ring knife method; number of sample points: 34. 4. Soil moisture content: this data is part of the monitoring content of hydrological elements in Yingke irrigation district. The specific sampling location is: Shiqiao Wudou Er Nongqu farmland in Yingke Irrigation District, planting corn for seed production; soil moisture sampling depth is 140 cm, sampling levels are 0-20 cm every 10 cm, 20-80 cm every 20 cm, 80-140 cm every 30 cm Methods: soil drying method and TDR measurement; sample number: 17. 5. Cross section flow: Sampling location: the farmland of Wudou Er Nong canal in Shiqiao, Yingke irrigation district; measure the flow velocity, water level and water temperature of different canal system sections during each irrigation, record the time and calculated flow, monitor once every 3 hours until the end of irrigation; sampling time: 2012.5-2012.9; measurement method: Doppler ultrasonic flow velocity meter (hoh-l-01, Measurement times: Yingke irrigation data of four times.
HUANG Guanhua, JIANG Yao
The ground sample data was collected by LAI-2000 canopy analyzer, and the collection area was located in Dayekou, Wuxing Village (2012) and other areas. The main measure of vegetation is corn. The LAI value of the corn was obtained using the LAI2000, and the observation was repeated twice in a pattern of “one up and four down”. The leaf area of each leaf of the corn plant was obtained using CD202, and a total of three corns were collected.
FAN Wenjie
The forest hydrology experimental area of Heihe River integrated remote sensing experiment includes the dense observation area of Dayekou basin and the dense observation area of Pailugou basin. Due to the concentrated distribution of the fixed sample plots in the drainage ditch basin, these sample plots lack of representativeness to the forest of the whole dayokou basin, so in June 2008, 43 temporary forest sample plots were set up in the whole dayokou basin. The data set is the ground observation data of the 43 temporary plots. In addition to the measurement and recording of stand status and site factors, Lai was also observed. The instruments used to measure each wood in the sample plot are mainly tape, DBH, flower pole, tree measuring instrument and compass. The DBH, tree height, height under branch, crown width in cross slope direction, crown width along slope direction and single tree growth were measured for each tree. WGS84 latitude and longitude coordinates of the center point of the sample plot were measured with different hand-held GPS, and the positioning error was about 5-30m. Other observation factors include: Forest Farm, slope direction, slope position, slope, soil thickness, canopy density, etc. The implementation time of these temporary sample plots is from 2 to 30 June 2008. The data set can provide ground data for the development of remote sensing inversion algorithm of forest structure parameters.
LING Feilong, HE Qisheng, ZHANG Xuelong, WANG Shunli, ZHAO Ming, LEI Jun, NIU Yun, LUO Longfa, CHEN Erxue
The data set mainly includes observation data of each tree in the super site, and the observation time is from June 2, 2008 to June 10, 2008. The super site is set around the Dayekou Guantan Forest Station. Since the size of the super site is 100m×100m, in order to facilitate the forest structure parameter survey, the super site is divided into 16 sub-sample sites, and tally forest measurement is performed in units of sub-samples. The tally forest measurement factors include: diameter, tree height, height under branch, crown width in transversal slope direction, crown width in up and down slope direction, and tindividual tree growth status. The measuring instruments are mainly: tape, diameter scale, laser altimeter, ultrasonic altimeter, range pole and compass. The data set also records the center point latitude and longitude coordinates of 16 sub-samples (measured by Z-MAX DGPS). The data set can be used for verification of remote sensing forest structure parameter extraction algorithm. The data set, together with other observation data of the super site, can be used for reconstruction of forest 3D scenes, establishment of active and passive remote sensing mechanism models, and simulation of remote sensing images,etc.
CHEN Erxue, BAI Lina, WANG Bengyu, TIAN Xin, LIU Qingwang, CAO Bin, Yang Yongtian, Zhihai Gao, Bingxiang Tan, GUO Zhifeng, WANG Xinyun, FU Anmin, ZHANG Zhiyu, NI Wenjian, WANG Qiang, BAO Yunfei, WANG Dianzhong, ZHANG Yang, ZHAO Liqiong, LIANG Dashuang, WANG Shunli, ZHAO Ming, LEI Jun, NIU Yun, LUO Longfa
The data set is the meteorological and observational data of hulugou shrub experimental area in the upper reaches of Heihe River, including meteorological data, albedo data and evapotranspiration data under shrubs. 1. Meteorological data: Qilian station longitude: 99 ° 52 ′ E; latitude: 38 ° 15 ′ n; altitude: 3232.3m, scale meteorological data from January 1, 2012 to December 31, 2013. Observation items include: temperature, humidity, vapor pressure, net radiation, four component radiation, etc. The data are daily scale data, and the calculation period is 0:00-24:00 2. Albedo: daily surface albedo data from January 1, 2012 to July 3, 2014, including snow and non snow periods. The measuring instrument is the radiation instrument on the 10m gradient tower in hulugou watershed. Among them, the data from August 4 to October 2, 2012 was missing due to instrument circuit problems, and the rest data quality was good 3. Evapotranspiration: surface evapotranspiration data of Four Typical Shrub Communities in hulugou watershed. The observation period is from July 18 to August 5, 2014, which is the daily scale data. The data include precipitation data, evaporation and infiltration data observed by lysimeter. The data set can be used to analyze the evapotranspiration data of alpine shrubs and forests. The evapotranspiration of grassland under canopy was measured by a small lysimeter with a diameter of 25 cm and a depth of 30 cm. Two lysimeters were set up in each shrub plot, and one lysimeter was set for each shrub in transplanting experiment. The undisturbed undisturbed soil column with the same height as the barrel is placed in the inner bucket, and the outer bucket is buried in the soil. During the embedding, the outer bucket shall be 0.5-1.0 cm higher than the ground, and the outer edge of the inner barrel shall be designed with a rainproof board about 2.0 cm wide to prevent surface runoff from entering the lysimeter. Lysimeter was set up in the nearby meteorological stations to measure grassland evapotranspiration, and a small lysimeter with an inner diameter of 25 cm and a depth of 30 cm was also set up in the sample plot of Picea crassifolia forest to measure the evaporation under the forest. All lysimeters are weighed at 20:00 every day (the electronic balance has a sensing capacity of 1.0 g, which is equivalent to 0.013 mm evaporation). Wind proof treatment should be taken to ensure the accuracy of measurement. Data processing method: evapotranspiration is mainly calculated by mass conservation in lysimeter method. According to the design principle of lysimeter lysimeter, evapotranspiration is mainly determined by the quality difference in two consecutive days. Since it is weighed every day, it is calculated by water balance.
SONG Yaoxuan, LIU Zhangwen
The data set of atmospheric water vapor absorption and utilization of desert plants, all of which are original data, including the liquid flow and environmental data of wild desert plants (Sitan village and Ejina Banner, Jingtai County), such as Tamarix, Bawang, Baici, Hongsha, etc., including the data of meteorology, photosynthesis, fluorescence and leaf surface humidity, as well as the data of gene transcriptome and expression regulation.
XIAO Honglang
The dataset is Lai data of ground sample points in Heihe River Basin, collected by LAI-2000 canopy analyzer. The collection area is located in Zhangye rural demonstration base, Ejina Banner, Jiuquan Satellite Center (2011) and other areas. The main measured vegetation is corn. The Lai value of maize was obtained by using lai2000, and the observation was repeated twice in the mode of one up four down. Cd202 was used to obtain the leaf area of each leaf of maize plant, and three maize plants were collected.
FAN Wenjie
This data includes three parts of data, namely shrub water holding experiment, shrub interception experiment and shrub transpiration experiment data. Shrub water holding experiment: select the two shrub types of Caragana jubata and Potentilla fruticosa, respectively pick the branches and leaves of the two vegetation types, weigh their fresh weight, carry out water holding experiment, measure the saturated weight of branches and leaves, dry weight of branches and leaves, dry weight of branches and leaves after completion, and finally obtain the data of branches, leaves and total water holding capacity. Shrub interception experiment: two shrubs, Caragana jubata and Potentilla fruticosa, were also selected and investigated. 30 rain-bearing cups were respectively arranged under the two shrubs. after each rainfall, penetration rainfall was measured and observed from June 1, 2012 to September 10, 2012. Shrub Transpiration Experiment: Potentilla fruticosa on July 14, Caragana jubata on August 5, Salix gilashanica on August 15, 2012. The measurement is made every hour according to the daily weather conditions.
ZHAO Chuanyan, MA Wenying
The leaf cross-sectional structure of constructive species in arid area of the middle and lower reaches of Heihe River Basin. The material number is consistent with the sampling table. Refer to the sampling table number to determine the material and its distribution position. A semi thin section of 65 dominant plants. The mesophyll structure of C3 and C4 plants, the characteristics of palisade tissue and sponge tissue, as well as the special structure including crystalloid cells can be reflected.
LIU Yubing
The survey data of vegetation quadrat in the middle reaches of Heihe River consists of the field survey data in 2013 and 2014, including the vegetation and soil data of the survey quadrat. The data of each survey sample includes the following information: sample longitude and latitude, sample size, elevation, sample overview, plant name, plant height, crown width, coverage, total coverage, number of trees, plant spacing, row spacing, large row spacing, DBH. The soil is divided into 6 layers according to 0-100cm below the ground, which are 0-10cm, 10-20cm, 20-40cm, 40-60cm, 60-80cm and 80-100cm respectively.
WANG Zifeng, XU Zongxue, ZHANG Shurong
一. Data overview This data interchange is the second data interchange of "genomics research on drought tolerance mechanism of typical desert plants in heihe basin", a key project of the major research program of "integrated research on eco-hydrological processes in heihe basin".The main research goal of this project is a typical desert sand Holly plants as materials, 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 plants such as arabidopsis and rice) verify its drought resistance. 二, data content 1.Sequencing of the genome and transcriptome of lycophylla SPP. The genome size of Mongolian Holly was about 926 Mb, GC content 36.88%, repeat sequence proportion 66%, genome heterozygosity rate 0.56%, which indicated that the genome has many repeat sequences, high heterozygosity and belongs to a complex genome.Based on the predicted sequence results, we subsequently carried out in-depth sequencing of the genome of lysiopsis SPP. The obtained data were assembled to obtain a 937 Mb genome sequence (table 1), which was basically the same as the predicted genome size.Through to the sand Holly transcriptome sequencing and sequence assembly (table 2), received more than 77000 genes coding sequence (Unigene), these sequences are comments found that most of the gene sequence and legumes and soybean, garbanzo beans and bean has a higher similarity (figure 1), consistent with the fact of sand ilex leguminous plants. 一), and the sand Holly is a leguminous plants consistent with the fact. 2.Discovery of simple repeat sequence (SSR) molecular markers of sand Holly: There is a transcriptome data set of sand Holly in the network public database, and the sample collection site is zhongwei city, ningxia.But this is the location of the project team samples in minqin county, gansu province, in order to study whether this sand in different areas of the Holly sequence has sequence polymorphism, we first identify the minqin county plant samples in the genomes of simple sequence repeat (SSR) markers (table 3), and then, compares the transcriptome sequences of plant sample, found in part of SSR molecular marker polymorphism (table 4), these molecular markers could be used for the species of plant genetic map construction, QTL mapping and genetic diversity analysis in the study. 三, data processing instructions Sample collection place: minqin county, gansu province, latitude and longitude: N38 ° 34 '25.93 "E103 ° 08' 36.77".Genome sequencing: a total of 8 genomic DNA libraries of different sizes were constructed and determined by Illumina HiSeq 2500 instrument.Transcriptome sequencing: a library of 24 transcriptome mrnas was constructed and determined by Illumina HiSeq 4000. 四, the use of data and meaning We selected a typical desert plant as the research object, from the Angle of genomics, parse the desert plant genome and transcriptome sequences, excavated its precious drought-resistant gene resources, and to study their drought resistance mechanism of favorable sand Holly this ancient and important to the utilization of plant resources, as well as the heihe river basin of drought-resistant plant genetic breeding, ecological restoration and sustainable development.
HE Junxian, FENG Lei
This dataset contains the LAI measurements from the Daman superstation in the middle reaches of the Heihe integrated observatory network from June 11 to September 18 in 2018. The site (100.372° E, 38.856°N) was located in the maize surface, near Zhangye city in Gansu Province. The elevation is 1556 m. There are 3 observation samples, each of which is about 30m×30m in size, and the latitude and longitude ranges are (100.373297°E~100.374205°E, 38.857871°N~38.858390°N), (100.373918°E~100.373897°E, 38.854025°). N~38.854941°N), (100.368007°E~100.369044°E, 38.850678°N~38.851580°N). Five sub-canopy nodes and one above-canopy node are arranged in each sample. The LAI data is obtained from LAINet measurements following four steps: (1) the raw data is light quantum (level 0); (2) the daily LAI can be obtained using the software LAInet (level 1); (3) the invalid and null values are screened and using the 7 days moving averaged method to obtain the processed LAI (level 2); (4) for the multi LAINet nodes observation, the averaged LAI of the nodes area is the final LAI (level 3). The released data are the post processed LAI products and stored using *.xls format. For more information, please refer to Liu et al. (2018) (for sites information), Qu et al. (2014) for data processing) in the Citation section.
LIU Shaomin, Qu Yonghua, XU Ziwei, LI Xin
This dataset contains the LAI measurements from the Sidaoqiao in the downstream of the Heihe integrated observatory network from June 16 to October 18 in 2018. The site was located in Ejina Banner in Inner Mongolia Autonomous Region. The elevation is 870 m. There are 2 observation samples, around Sidaoqiao superstation (101.1374E, 42.0012N) and Mixed forest station (101.1335E, 41.9903N), each of which is about 30m×30m in size. Five sub-canopy nodes and one above-canopy node are arranged in each sample. The LAI data is obtained from LAINet measurements following four steps: (1) the raw data is light quantum (level 0); (2) the daily LAI can be obtained using the software LAInet (level 1); (3) the invalid and null values are screened and using the 7 days moving averaged method to obtain the processed LAI (level 2); (4) for the multi LAINet nodes observation, the averaged LAI of the nodes area is the final LAI (level 3). The released data are the post processed LAI products and stored using *.xls format. For more information, please refer to Liu et al. (2018) (for sites information), Qu et al. (2014) for data processing) in the Citation section.
Qu Yonghua, XU Ziwei, LI Xin
The dataset contains phenological camera observation data collected at the Arou Superstation in the midstream of the Heihe integrated observatory network from June 13 to November 16, 2018. The instrument was developed with data processed by Beijing Normal University. The phenomenon camera integrates data acquisition and data transmission functions. The camera captures high-quality data with a resolution of 1280×720 by looking-downward. The calculation of the greenness index and phenology are following 3 steps: (1) calculate the relative greenness index (GCC, Green Chromatic Coordinate, calculated by GCC=G/(R+G+B)) according to the region of interest, (2) perform gap-filling for the invalid values, filtering and smoothing, and (3) determine the key phenological parameters according to the growth curve fitting (such as the growth season start date, Peak, growth season end, etc.) There are also 3 steps for coverage data processing: (1) select images with less intense illumination, (2) divide the image into vegetation and soil, and (3) calculate the proportion of vegetation pixels in each image in the calculation area. After the time series data is extracted, the original coverage data is smoothed and filtered according to the time window specified by the user, and the filtered result is the final time series coverage. This data set includes relative greenness index (Gcc). Please refer to Liu et al. (2018) for sites information in the Citation section.
Qu Yonghua, XU Ziwei, LI Xin
The dataset contains phenological camera observation data collected at the Arou Superstation in the midstream of the Heihe integrated observatory network from June 13 to November 16, 2018. The instrument was developed with data processed by Beijing Normal University. The phenomenon camera integrates data acquisition and data transmission functions. The camera captures high-quality data with a resolution of 1280×720 by looking-downward. The calculation of the greenness index and phenology are following 3 steps: (1) calculate the relative greenness index (GCC, Green Chromatic Coordinate, calculated by GCC=G/(R+G+B)) according to the region of interest, (2) perform gap-filling for the invalid values, filtering and smoothing, and (3) determine the key phenological parameters according to the growth curve fitting (such as the growth season start date, Peak, growth season end, etc.) There are also 3 steps for coverage data processing: (1) select images with less intense illumination, (2) divide the image into vegetation and soil, and (3) calculate the proportion of vegetation pixels in each image in the calculation area. After the time series data is extracted, the original coverage data is smoothed and filtered according to the time window specified by the user, and the filtered result is the final time series coverage. This data set includes relative greenness index (GCC), phenological phase and fractional cover (FC). Please refer to Liu et al. (2018) for sites information in the Citation section.
Qu Yonghua, XU Ziwei, LI Xin
The dataset contains phenological camera observation data collected at the Arou Superstation in the midstream of the Heihe integrated observatory network from June 13 to November 16, 2018. The instrument was developed with data processed by Beijing Normal University. The phenomenon camera integrates data acquisition and data transmission functions. The camera captures high-quality data with a resolution of 1280×720 by looking-downward. The calculation of the greenness index and phenology are following 3 steps: (1) calculate the relative greenness index (GCC, Green Chromatic Coordinate, calculated by GCC=G/(R+G+B)) according to the region of interest, (2) perform gap-filling for the invalid values, filtering and smoothing, and (3) determine the key phenological parameters according to the growth curve fitting (such as the growth season start date, Peak, growth season end, etc.) There are also 3 steps for coverage data processing: (1) select images with less intense illumination, (2) divide the image into vegetation and soil, and (3) calculate the proportion of vegetation pixels in each image in the calculation area. After the time series data is extracted, the original coverage data is smoothed and filtered according to the time window specified by the user, and the filtered result is the final time series coverage. This data set includes relative greenness index (Gcc). Please refer to Liu et al. (2018) for sites information in the Citation section.
Qu Yonghua, XU Ziwei, LI Xin
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
