This data includes the coverage data set of vegetation in one growth cycle in five stations of Daman super station, wetland, desert, desert and Gobi, and the biomass data set of maize and wetland reed in one growth cycle in Daman super station. The observation time starts from May 10, 2014 and ends on September 11, 2014. 1 coverage observation 1.1 observation time 1.1.1 super station: the observation period is from May 10 to September 11, 2014. Before July 20, the observation is once every five days. After July 20, the observation is once every 10 days. A total of 17 observations are made. The specific observation time is as follows:; Super stations: May 10, 15, 20, 25, 30, 10, 15, 20, 20, 30, 30, 30, 30, 30, 7, 10, 10, 10, 10, 10, 15 1.1.2 other four stations: the observation period is from May 20 to September 15, 2014, once every 10 days, and 11 observations have been made in total. The specific observation time is as follows:; Other four stations: May 10, 2014, May 20, 2014, May 30, 2014, June 10, 2014, June 20, 2014, June 30, July 10, 2014, July 20, August 5, 2014, August 17, 2014, September 11, 2014 1.2 observation method 1.2.1 measuring instruments and principles: The digital camera is placed on the instrument platform at the front end of the simple support pole to keep the shooting vertical and downward and remotely control the camera measurement data. The observation frame can be used to change the shooting height of the camera and realize targeted measurement for different types of vegetation. 1.2.2 design of sample Super station: take 3 plots in total, the sample size of each plot is 10 × 10 meters, take photos along two diagonal lines in turn each time, take 9-10 photos in total; Wetland station: take 2 sample plots, each plot is 10 × 10 meters in size, and take 9-10 photos for each survey; 3 other stations: select 1 sample plot, each sample plot is 10 × 10 meters in size, and take 9-10 photos for each survey; 1.2.3 shooting method For the super station corn and wetland station reed, the observation frame is directly used to ensure that the camera on the observation frame is far higher than the vegetation crown height. Samples are taken along the diagonal in the square quadrat, and then the arithmetic average is made. In the case of a small field angle (< 30 °), the field of view includes more than 2 ridges with a full cycle, and the side length of the photo is parallel to the ridge; in the other three sites, due to the relatively low vegetation, the camera is directly used to take pictures vertically downward (without using the bracket). 1.2.4 coverage calculation The coverage calculation is completed by Beijing Normal University, and an automatic classification method is adopted. For details, see article 1 of "recommended references". By transforming RGB color space to lab space which is easier to distinguish green vegetation, the histogram of green component A is clustered to separate green vegetation and non green background, and the vegetation coverage of a single photo is obtained. The advantage of this method lies in its simple algorithm, easy to implement and high degree of automation and precision. In the future, more rapid, automatic and accurate classification methods are needed to maximize the advantages of digital camera methods. 2 biomass observation 2.1 observation time 2.1.1 corn: the observation period is from May 10 to September 11, 2014, once every 5 days before July 20, and once every 10 days after July 20. A total of 17 observations have been made. The specific observation time is as follows:; Super stations: May 10, 15, 20, 25, 30, 10, 15, 20, 20, 30, 30, 30, 30, 30, 7, 10, 10, 10, 10, 10, 15 2.1.2 Reed: the observation period is from May 20 to September 15, 2014, once every 10 days, and 11 observations have been made in total. The specific observation time is as follows:; 2014-5-10、2014-5-20、2014-5-30、2014-6-10、2014-6-20、2014-6-30、2014-7-10、2014-7-20、2014-8-5、2014-8-17、2014-9-11 2.2 observation method Corn: select three sample plots, and select three corn plants that represent the average level of each sample plot for each observation, respectively weigh the fresh weight (aboveground biomass + underground biomass) and the corresponding dry weight (85 ℃ constant temperature drying), and calculate the biomass of unit area corn according to the plant spacing and row spacing; Reed: set two 0.5m × 0.5m quadrats, cut them in the same place, and weigh the fresh weight (stem and leaf) and dry weight (constant temperature drying at 85 ℃) of reed respectively. 2.3 observation instruments Balance (accuracy 0.01g), oven. 3 data storage All the observation data were recorded in the excel table first, and then stored in the excel table. At the same time, the data of corn planting structure was sorted out, including the plant spacing, row spacing, planting time, irrigation time, except for the parent time, harvesting time and other relevant information.
YU Wenping, GENG Liying, Li Yimeng, TAN Junlei, MA Mingguo
The data set include crop leaf chlorophyll content observed at four sample regions, that is the soil moisture control experimental field at Daman county, and the EC plots, the super station, and Shiqiao sample plots at Wuxing village in Zhangye city. 1) Objective Crop leaf chlorophyll content, a key biophysical parameter, was observed as model parameter or a priori knowledge for canopy radiative transfer model or eco-hydrological models. 2) Measuring instruments SPAD. 3) Measuring site a. the soil moisture control experimental field at Daman county, Twelve soil water treatments are set. The wheat leaf chlorophyll content for each treatment is measured on 17, 23 and 29 May, and 3, 9, 14 and 24 June, and 5 and 12 July. b. the EC site The maize leaf chlorophyll content at 14 EC site (EC-2,EC-3,EC-5,EC-6,EC-7,EC-8,EC-9, EC-10, EC-11, EC-12, EC-13, EC-14, EC-15, EC-16) are measured on 14, 21, 25 and 31 May, 7, 13, 23 and 28 June, 3, 13, 18 and 23 July, 3, 12 and 28 August. c. the Super Station The maize chlorophyll content at the super station is measured on 22 and 28 May, 5, 11, 18, and 25 June, and 1, 8, 15, 22 and 31 July, 9, 15 and 22 August, and 3 and 11 September. d. the Shiqiao sample site The maize chlorophyll content at the Shiqiao village is measured on 17, 22 and 28 May, 4, 11, 17 and 25 June, 1, 8, 15, 22, and 30 July, 8, 16 and 27 August, and 9 September. 4) Data processing The observational data was recorded in the sheets and reorganized in the EXCEL sheets. The time used in this dataset is in UTC+8 Time.
Xu Fengying, Wang Jing, Huang Yongsheng, LI Xin, MA Mingguo
The dataset include the planting structure and area information of major crops in 11 districts and counties of the Heihe River Basin from 2000 to 2012 (grain, wheat, corn, potato, soybean, cotton, oil, vegetables, etc.)
DENG XiangZheng
We produced surface photosynthetic effective radiation (PAR), solar radiation (SSR) and net radiation (NR) products with 1KM resolution in the heihe basin in 2012.The temporal resolution ranges from instantaneous to hourly and daily.Day-by-day ancillary data were also produced, including aerosol optical thickness, moisture content, NDVI, snow cover, and surface albedo.Among them, PAR and SSR use the method of lookup table to directly invert by combining the stationary weather satellite and polar orbit satellite MODIS product.NR was calculated by analyzing the relationship between net short-wave and net surface radiation.Hourly instantaneous products are weighted by average and integral to obtain hourly and daily cumulative products.
HUANG Guanghui
A typical Shaker type potassium ion absorption channel gene AmKAT1 was cloned from the leaves of Ammopiptanthus mongolicus. Electrophysiological studies of AmKAT1 show that AmKAT1 is a K+ absorption channel regulated by potassium ion concentration. the system can only input K+ into guard cells when the extracellular potassium ion concentration is high (above 10 mmol/L). This distinctive feature has important physiological significance for xerophytes such as Ammopiptanthus mongolicus: under the condition of low concentration of extracellular potassium ions (no matter how high the concentration of sodium ions), AmKAT1 is difficult to open, potassium ions cannot enter guard cells, the guard cells will not absorb water and expand, and stomata will be difficult to open, thus reducing the transpiration and loss of water in Ammopiptanthus mongolicus and enhancing the viability of Ammopiptanthus mongolicus in arid environment. We have further studied the mechanism of extracellular potassium ion regulating the activity of AmKAT1 and found that at least two sites in AmKAT1 are involved in potassium ion induction, and now one site has been determined to be located in the channel pore region. In addition, we cloned a guard cell export-oriented K+ channel AmGORK and a slow anion channel AmSLAC1. Fluorescence quantitative PCR results showed that AmGORK was mainly expressed in the upper part of the ground, and its transcription level was affected by PEG simulated water stress, ABA, NaCl and osmotic stress treatments to varying degrees. Electrophysiological studies in xenogeneic system of Xenopus laevis oocytes show that AmGORK channel of Mongolian Ammopiptanthus mongolicus guard cells can mediate efficient efflux of K+ when membrane potential is depolarized. The activation of this channel has typical voltage dependence and potassium ion concentration dependence, and is inhibited by potassium ion channel inhibitors TEA and Ba2+; In addition, the activity of AmGORK is regulated by extracellular pH, but not by extracellular calcium concentration. These results show that although Ammopiptanthus mongolicus is an ancient drought-resistant leguminous shrub originated millions of years ago, it is highly similar to the existing common model plant Arabidopsis thaliana in the stomatal closure mechanism dominated by K+. These results provide evidence to preliminarily reveal the functional conservatism of GORK-like stomatal regulatory channels in different species and long-term evolution.
SU Yanhua
The data set contains the data of thermal diffusion fluid flow meter in the hydrometeorological observation network from January 1 to December 31, 2015. The study area is located in huyang forest, ejin banner, alxa league, lower reaches of heihe, Inner Mongolia autonomous region.According to the different height and diameter at breast height of iminqak, choose install Thermal diffusion flow meter sample tree (Thermal Dissipation SAP flow velocity Probe, TDP), domestic TDP pin type Thermal diffusion plant flow meter, model for TDP30.The TDP1 point and TDP2 point of sample plots were set in the vicinity of mixed forest station and populus populus station, respectively.Sample tree height from high to low in turn for TDP2 (16.4 meters, 18.3 meters, 16.9 meters), TDP1 (12.5 meters, 13 meters, 14 meters), diameter at breast height order from large to small is TDP1 (48 cm, 41.6 cm, 46.6 cm), TDP2 (33.8 cm, 38.5 cm, 42.3 cm), density of TDP1 respectively (0.0158 per square meter) tree, TDP2 (0.0116 per square meter), to represent the whole area of populus euphratica transpiration measurement.Two sets of probes are installed in each sample tree, with a height of 1.3 meters and a direction of east and west of the sample tree. The original observation data of TDP is the temperature difference between the probes, and the collection frequency is 10s, with an average output of 10 minutes.The published data are calculated and processed trunk flow data, including flow rate V (cm/h), flux Fs (cm3/h) and daily transpiration Q (mm/d) per 10 minutes.Firstly, the liquid flow rate and liquid flux were calculated according to the temperature difference between the probes, and then the transpiration Q per unit area of the forest zone was calculated according to the area of Euphrates poplar forest and the distance between trees at the observation points.At the same time, post-processing was carried out on the calculated rate and flux value :(1) data that obviously exceeded the physical significance or the instrument range were removed;(2) the missing data is marked with -6999;(3) suspicious data caused by probe fault or other reasons shall be identified in red, and the data confirmed to have problems shall be removed. Please refer to Li et al. (2013) for hydrometeorological network or site information, and Qiao et al. (2015) for observation data processing.
LIU Shaomin, LI Xin, CHE Tao, XU Ziwei, REN Zhiguo, TAN Junlei
This dataset includes observational data of sap flow from 14 June to 21 September, 2012. The study area was located in the irrigation area within the middle reaches of the Heihe River Basin, China. Sample trees were selected for installing TDP (thermal dissipation sap flow velocity probe) instruments according to their height and diameter at breast height (DBH); only Popolusgansuensis trees were selected in this study. The TDP instrument is made in China; the model type was TDP30. There were 3 TDP observation sites, i.e., TDP-1, TDP-2 and TDP-3, which were located near the LAS4_S, EC6 and EC8 sites, respectively. The order of tree heights was TDP-2 > TDP-1 > TDP-3, and the order of DBH was TDP-2 > TDP-3 > TDP-1. At each site, 3 representative trees were selected to measure the sap flow. Three TDPs were mounted on the stem of each tree, one each for the southeast, southwest and north directions; the mounting height is 1.3 meters. Each TDP had two probes. The raw TDP data included the temperature difference between the two probes at a frequency of 30 s. The released data include the 10 minute-averaged sap flow rate (cm/h), sap flow flux (cm^3/h), and daily transpiration (mm/d). The sap flow rate and the sap flow flux were calculated according to the temperature difference between the two probes; the shelter-forest transpiration per unit area (Q) was calculated based on the area of shelterbelts and density of Popolusgansuensis trees at each site. The data preprocessing steps included the following. (1) Unphysical data were excluded. (2) Missing data were filled with -6999. (3) Suspicious data, which were most likely caused by probe failure, were marked in red; confirmed bad data were excluded. For more information, please refer to Liu et al. (2016) (for multi-scale observation experiment or sites information), Qiao et al. (2015) (for data processing) in the Citation section.
LIU Shaomin, LI Xin
This dataset includes 5 sub-datasets obtained from measurements in the flux observing matrix at observing site No.15 (the Daman superstation) and 13. Specifically, the sub-datasets include the following: (1) a dataset that contains atmospheric water vapor D/H and 18O/16O isotopic and flux ratio measurements from site No.15 from 27 May to 21 September in 2012, (2) a dataset that contains D/H and 18O/16O isotopic ratios of water in soil and in corn xylem at site No.15 from 27 May to 21 September 2012, (3) a dataset that contains atmospheric water vapor D/H and 18O/16O isotopic ratios at site No.13 when airborne surveys occurred, and (4) a dataset that contains D/H and 18O/16O isotopic ratios of water in soil and in corn xylem at sites No.13 and 15 when airborne surveys occurred, (5) a dataset that contains the ratios of evaporation and transpiration to evapotranpiration at site No.15. The experiment area was located in a corn cropland in the Daman irrigation district of Zhangye, Gansu Province, China. The positions of observing sites No.15 and 13 were 100.3722° E, 38.8555° N and 100.3785° E, 38.8607° N, respectively, with an elevation of 1552.75 m above sea level. The atmospheric water vapor D/H and 18O/16O isotopic and flux ratios at site No.15 were continuously measured using an in situ observation system. The system consisted of an H218O, HDO and H2O analyzer (Model L1102-i, Picarro Inc.), a CTC HTC-Pal liquid auto sampler (LEAP Technologies) and a multichannel solenoid valve (Model EMT2SD8 MWE, Valco Instruments CO. Inc.). The heights of the two intakes were 0.5 and 1.5 m above the corn canopy. The water vapor D/H and 18O/16O isotopic ratio analyzer recorded signals at 0.2 Hz; data were recorded for 2 minutes per intake. The data were block-averaged to hourly intervals. The sampling frequency of soil and xylem at site No. 15 was 1-3 days. The atmospheric water vapor D/H and 18O/16O isotopic and flux ratios at site No.13 were measured using a cold traps/mass spectrometer. The sampling frequency of atmospheric water vapor, soil water and xylem water at site No.13 was the same as that of the airborne surveys. Briefly, the Picarro analyzer measurements were calibrated during every 3 h switching cycle using a two-point concentration interpolation procedure in which the water vapor mixing ratio was dynamically controlled to track the ambient water vapor mixing ratio. Possible delta stretching effects were not considered. A schematic diagram of the Picarro analyzer and its operation principles and calibration procedure are described elsewhere in the literature (Huang et al., 2014; Wen et al. 2008, 2012). The dataset of atmospheric water vapor D/H and 18O/16O isotopic and flux ratios at site No.15 includes the following variables: Timestamp (time, timestamp without time zone), Number (available record number), δD for r1 (δD for the lower intake, ‰), δD for r2 (δD for the higher intake, ‰), δ18O for r1 (δ18O for the lower intake, ‰), δ18O for r2 (δ18O for the higher intake, ‰), vapor mixing ratio for r1 (vapor mixing ratio for the lower intake, mmol/mol), vapor mixing ratio for r2 (vapor mixing ratio for the higher intake, mmol/mol), δET_D (δD of evapotranspiration, ‰), and δET_18O (δ18O of evapotranspiration, ‰). The dataset of D/H and 18O/16O isotopic ratios of water in soil and in corn xylem at site No.15 includes the following variables: Timestamp (time, timestamp without time zone), Remark (treatment: soil without mulch (Ld)=1; soil with mulch (Fm)=2; soil with male corns (F)=3; Xylem=4), δD (‰), and δ18O (‰). The dataset for the ratio of soil evaporation and transpiration to the evapotranspiration at site 15 includes the following variables: Timestamp (time, timestamp without time zone), E/ET (ratio of soil evaporation to the evapotranspiration, %), and T/ET (ratio of transpiration to the evapotranspiration, %). The mean (±one standard deviation) ratio of transpiration to evapotranspiration was 86.7±5.2% (the range was 71.3 to 96.0%). The mean (±one standard deviation) ratio of soil evaporation to the evapotranspiration was 13.3 ±5.2% (the range was 4.0 to 28.7%). The dataset of atmospheric water vapor D/H and 18O/16O isotopic ratio at site No. 13 when airborne surveys occurred includes the following variables: Timestamp1 (start time, timestamp without time zone), Timetamp2 (end time, timestamp without time zone), Height (observation height, cm), δD (‰), and δ18O (‰). The dataset of D/H and 18O/16O isotopic ratios of water in soil and in corn xylem at sites No. 13 and 15 when airborne surveys occurred include the following variables, Timestamp (time, timestamp without time zone), Remark (treatment: soil without mulch (Ld)=1; soil with mulch (Fm)=2; Xylem=4), δD (‰), δ18O (‰), and Location (observing site 13 or 15) . The missing measurements were replaced with -6999. For more information, please refer to Liu et al. (2016) (for multi-scale observation experiment or sites information), Wen et al. (2016) (for data processing) in the Citation section.
WEN Xuefa, LIU Shaomin, LI Xin
The data set contains the observation data of thermal diffusion fluid flow meters at the downstream mixed forest station and eupoplar forest station of the hydrometeorological observation network from January 1 to December 31, 2014. La shan au in the study area is located in the Inner Mongolia autonomous region of mesozoic-cenozoic in iminqak, according to the different height and diameter at breast height of iminqak, choose sampling tree installation TDP (Thermal Dissipation SAP flow velocity Probe, Thermal diffusion flow meter), domestic TDP pin type Thermal diffusion stem flow meter, the model for TDP30.The sample sites are TDP1 point and TDP2 point respectively, which are located near the mixed forest station and populus populus station.The height of the sample tree is TDP2 and TDP1 from high to low, and the diameter of the chest is TDP1 and TDP2 from large to small, so as to measure the trunk fluid flow on behalf of the whole area.The installation height of the probe is 1.3 meters and the installation orientation is due east and west of the sample tree. The original observation data of TDP is the temperature difference between probes, which is collected once for 10s and the average output period is 10 minutes.The published data are calculated and processed trunk flow data, including flow rate (cm/h), flux (cm3/h) and daily transpiration (mm/d) per 10 minutes.Firstly, the liquid flow rate and liquid flux were calculated according to the temperature difference between the probes, and then the transpiration Q per unit area of the forest zone was calculated according to the area of Euphrates poplar forest and the distance between trees at the observation points.At the same time, post-processing was carried out on the calculated rate and flux value :(1) data that obviously exceeded the physical significance or the instrument range were removed;(2) the missing data is marked with -6999;Among them, the data of TDP2 was missing due to power supply problems from 1.1-2.8 days, and the data of the third group of probes was missing from 2.8-3.13 days due to the problems of the third group of probes.(3) suspicious data caused by probe fault or other reasons shall be identified in red, and the data confirmed to have problems shall be removed. Please refer to Li et al.(2013) for hydrometeorological network or site information, and Qiao et al.(2015) for observation data processing.
LIU Shaomin, LI Xin, CHE Tao, XU Ziwei, REN Zhiguo, TAN Junlei
The EC150 open circuit eddy covariance observation system was set up in the typical Populus euphratica community near ulantuge of Ejina oasis in the lower reaches of Heihe River. The water and heat fluxes of Populus euphratica community from July 2013 to September 2014 were systematically observed.
CHEN Yaning
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
According to the sample survey data, in August 2013, 30 forest plots were set up in the Tianlaochi watershed, with a plot size of 10 m×20 m. The long side of the plot was parallel to the slope of the hillside, including 26 blocks of Picea crassifolia forest. 2 blocks of Sabina Przewalsskii forest and 2 mixed forests of Picea and Sabina. In the plot, the diameter of the breast of each tree (the diameter of the trunk at a height of 1.3 m) is measured by a diameter tape, and the height of each tree and the height under the branches (the height of the first live branch at the lower end of the canopy) is measured by a hand-held ultrasonic altimeter. The north-south direction and the east-west crown width are measured with a tape measure, and the sample site is positioned by differential GPS. The parallel version of HASM-AD algorithm is used to simulate the classified LIDAR point cloud data. DEM is generated from ground points, DSM is generated from all points, and the height of surface features is obtained by differential operation between DSM and DEM. In forest area, it is called Canopy Height Model (CHM). A circular window with a given search radius is used to find the local maximum value on CHM. If the central pixel value is the maximum value, it is determined as the crown vertex. The pixel attribute value of the tree vertex is the tree height, and the spatial resolution is 1m.
YUE Tianxiang, WANG Yifu
This data is the ASTER fractional vegetation cover in a growth cycle observed in the Yingke Oasis Crop land. Data observations began on May 30, 2012 and ended on September 12. Original data: 1.15m resolution L1B reflectivity product of ASTER 2.Vegetation coverage data set of the artificial oasis experimental area in the middle reaches Data processing: 1.Preprocessing of ASTER reflectance products to obtain ASTER NDVI; 2.Through the NDVI-FVC nonlinear transformation form, the ASTER NDVI and the ground measured FVC are used to obtain the conversion coefficients of NDVI to FVC at different ASTER scales. 3.Apply this coefficient to the ASTER image to obtain a vegetation coverage of 15m resolution; 4.Aggregate 15m resolution ASTER FVC to get 1km ASTER FVC product
HUANG Shuai, MA Mingguo
The evapotranspiration and soil evapotranspiration of lycium rubra and red sand of small shrubs in typical desert weather were observed by using infrared gas analyzer to measure water vapor flux. The measurement system consists of li-8100 closed-circuit automatic measurement of soil carbon flux (li-cor, USA) and an assimilation box designed and manufactured by Beijing ligotai technology co., LTD. Li-8100 is an instrument produced by li-cor for soil carbon flux measurement. It USES an infrared gas analyzer to measure the concentration of CO2 and H2O.The length, width and height of the assimilation box are all 50cm.The assimilation box is controlled by li-8100. After setting up the measurement parameters, the instrument can run automatically.
SU Peixi
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
In the late June and early July of 2014, the dominant species of desert plants in the lower reaches of Heihe River, Lycium barbarum and Sophora alopecuroides, were selected. Using the LI-6400 portable photosynthesis system (LI-COR, USA), the photosynthetic and water physiological characteristics of desert plants were measured and analyzed.
SU Peixi
The leaf area of five typical species of jinjier, jilialu, jinlumei, huangxiaoba and Ganqing jinjier in Dayekou watershed of Qilian Mountain was measured by LAI-2200 canopy analyzer.
LIU Xiande
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
Vegetation index (NDVI) can be used to detect vegetation growth state, vegetation coverage and eliminate some radiation errors. The data set is the NDVI product data synthesized by MODIS in 500 meters and 16 days in the black river basin from 2000 to 2010 after graphic processing, and the no-value zone is -32768.The coordinate system is the longitude and latitude projection, and the spatial range is 96.5E -- 102.5E, 37.5N -- 43N.The data format is GEOTIFF.
WANG Zhongjing
In this project, Ammopiptanthus mongolicus, a typical desert plant, is taken as the research object. Through optimizing the protein extraction and purification system of Ammopiptanthus mongolicus, IEF and 2-D two-dimensional electrophoresis techniques are used to obtain soluble protein electrophoresis maps of Ammopiptanthus mongolicus, and protein spots differentially expressed under drought stress are analyzed and obtained, which provides technical guarantee for subsequent mass spectrometry to identify protein functions and construct Ammopiptanthus mongolicus water stress response network.
SU Yanhua
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
