WATER: Dataset of forest structure parameter survey at the super site around the Dayekou Guantan Forest Station

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.

2020-08-20

Potassium transporter in ammopiptanthus mongolicus (2015-2016)

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.

2020-07-28

The investigation data on the ground and underground biomass and distribution characteristics of the desert plant communities (2014)

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.

2020-06-01

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2020-03-27

HiWATER: Dataset of fractional vegetation cover and biomass observed in the middle reaches of the Heihe River Basin (2014)

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.

2020-03-14

Experimental observation data of water consumption and law of water consumption of different life type desert plants in Heihe River basin (2014)

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.

2020-03-10

WATER: Dataset of forest structure parameter survey at the fixed sampling plot in the Pailugou watershed and Dayekou watershed foci experiment area (2003)

The main contents of this data set are forest, shrub and grassland sample plot survey data.The fixed samples are located in the drainage ditch valley of qilian mountain and the dayaokou valley where the hydrology observation and test site of the water source conservation forest research institute of gansu province is located. The information of the sample is as follows: Number elevation quadrat size longitude latitude surface type G1 2715 20 × 20 100 ° 17 '12 "38 ° 33' 29" qinghai spruce forest G2 2800 20×36 100°17 '07 "38°33' 27" moss spruce forest G3 2840 20×20 100°17 '37 "38°33' 05" moss spruce forest G4 2952 20 × 20 100 ° 17 '59 "38 ° 32' 47" qinghai spruce forest G5 3015 20 × 20 100 ° 18 '06 "38 ° 32' 42" qinghai spruce forest G6 3100 20 × 20 100 ° 18 '13 "38 ° 32' 31" thicket qinghai spruce forest G7 3300 23.5 × 20 thickets qinghai spruce forest G8 2800 20×20 100°13 '30 "38°33' 29" moss spruce forest B1 2700 12.8×25 moss spruce forest B2 2800 20×20 100°17 '38 "38°32' 59" moss spruce forest B3 2900 20×20 100°17 '59 "38°32' 51" grass spruce forest B4 3028 20×20 100°17 '59 "38°32' 39" moss spruce forest B5 3097 20×20 100°18 '02 "38°32' 32" moss spruce forest B6 3195 20 × 20 100 ° 18 '06 "38 ° 32' 25" qinghai spruce forest B7 2762 20 × 20 100 ° 17 '08 "38 ° 33' 21" qinghai spruce forest B8 2730 20×20 100°17 '06 "38°33' 27" moss spruce forest GM1 3690 5×5 100°18 '02 "38°32' 02" caragana scrub (middle) GM2 3690 5×5 100°18 '02 "38°32' 02" caragana scrub (rare) GM3 3700 5×5 100°18 '03 "38°32' 03" caragana + jilaliu shrub (dense) GM4 3600 5×5 100°18 '10 "38°32' 06" caragana + jila willow thicket (middle) GM5 3600 5×5 100°18 '10 "38°32' 06" caragana + jila willow shrub (sparse) GM6 3600 5×5 100°18 '10 "38°32' 06" caragana + jila willow thicket (dense) GM7 3500 5×5 100°18 '14 "38°32' 08" caragana + jila willow thicket (middle) GM8 3500 5×5 100°18 '14 "38°32' 08" caragana + jila willow thicket (dense) GM9 3500 5×5 100°18 '14 "38°32' 08" caragana + jila willow thicket (rare) GM10 3400 5×5 100°18 '18 "38°32' 12" golden pheasant scrub (rare) GM11 3400 5×5 100°18 '18 "38°32' 12" golden pheasant + golden raspberry shrub (dense) GM12 3400 5×5 100°18 '18 "38°32' 12" golden pheasant scrub (rare) GM13 3300 5 × 5 100 ° 18 '21 "38 ° 32' 21" giraliu thicket GM14 3300 5 × 5 100 ° 18 '21 "38 ° 32' 21" caragana + jila shrub GM15 3300 5 × 5 100 ° 18 '21 "38 ° 32' 21" caragana + jila shrub YC3 2700 1×1 100°17 '14 "38°33' 33" needle thatch field YC4 2750 1×1 100°17 '18 "38°33' 32" needle thatch field YC5 2800 1×1 100°17 '21 "38°33' 33" needle thatch field YC6 2850 1×1 100°17 '25 "38°33' 33" needle thatch field YC7 2900 1×1 100°17 '31 "38°33' 32" aster + needle thatch field YC8 2950 1×1 100°17 '44 "38°33' 23" needle thatch field YC9 2980 1×1 100°17 '48 "38°33' 25" needle thatch field The sample geodesic tree data were surveyed from July to August 2007.The survey included: 1. Basic survey of sample plots in drainage ditch basin: A) sample land setting: sample land number, elevation, slope direction, slope position, slope, soil layer thickness, sample land size, longitude and latitude, community type, soil type, operation status, age B) survey of each wood in the sample plots: sample plot number, tree number, tree species, tree classification, chest diameter, tree height, undershoot height, crown radius 2. Soil profile survey record sheet Including forest/vegetation status, major tree species, forest age, soil name, surface soil erosion, parent rock and material, drainage conditions, land use history, soil profile (soil layer, moisture, color, texture, structure, root system, gravel content) 3. Standard ground cover factor Standard land area, dominant tree species, stand/vegetation origin, elevation, slope direction, slope position, slope, cutting and utilization method, afforestation land preparation type, survey method, canopy coverage, living ground cover, dead cover cover, litter thickness (undivided strata, semi-decomposed layer, decomposed layer) 4. Canopy survey: 5. Draft quadrat (1m×1m) survey record sheet Including species name, number, coverage, average height 6. Results of determination of soil physical properties in source forest of qilian mountain (land sample survey) Contains the soil physical properties measurement process (+ wet mud weight aluminum box, aluminum box, soil moisture content, suddenly bulk density, etc.), bringing biomass measurement (total fresh weight of shrub and herb, fresh weight of sample, sample dry weight, etc.), litter dry weight (including mosses) layer and the largest capacity calculation process (of moss and litter thickness, total fresh weight, fresh weight of samples, the dry weight of the sample, soaking for 24 h after heavy, maximum water holding capacity, the largest water depth, the biggest hold water rate, maximum moisture capacity) 7. Bush sample survey: Including species name, number, coverage, average height 8. Standard sample land setting and questionnaire for each wooden inspection ruler Including tree species, tree classification, age, chest diameter, number of height, undershoot height, crown radius 9. Litter layer survey record sheet Including litter (decomposed layer, semi-decomposed layer, decomposed layer) thickness 10. Update survey records: Including tree species, natural regeneration (height <30cm, height 31-50cm, height >51cm), artificial regeneration (height <30cm, height 31-50cm, height >51cm) This data set can provide ground measured data for remote sensing inversion of forest structure parameters.

2020-03-10

WATER: Dataset of forest structure parameter measurements for the fixed forest sampling plots in the Dayekou and Pailugou watershed foci experimental areas (2003-3007)

The fixed forest sample plot is located in the drainage ditch of Dayekou, Qilian Mountain, where the hydrological observation field of Gansu Water Conservation Forest Research Institute is located. From July 2003 to August 2003 and from July 2007 to August 2007, the tree survey of the sample plot was completed by technicians from Gansu Water Conservation Forest Research Institute and Institute of environment and Engineering in cold and dry areas of Chinese Academy of Sciences. A total of 17 fixed forest samples were observed, including the survey of sample plot factors and the survey of each tree. The observation factors of sample plots mainly include forest farm, longitude and latitude coordinates, slope direction, slope position, slope, soil thickness, canopy density of arbor layer, leaf area index, etc. The main instruments used in the measurement are tape, DBH, flower pole, tree measuring instrument, compass and fish eye camera. The measurement factors of each tree include DBH, height of tree, height under branch, crown width in cross slope direction, crown width along slope direction, growth status of single tree, etc. For details, please refer to the metadata of "Heihe River Integrated Remote Sensing joint test: fixed sample plot tree survey data set (2003)" and "Heihe River Integrated Remote Sensing joint test: fixed sample plot tree survey data set (2007)". The Lai in this data set is the supplementary measurement data during the joint remote sensing experiment of Heihe River in 2008. That is to say, the supplementary measurement of Lai has been done in these fixed plots. The supplementary observation time of Lai was from June 1 to 13, 2008. 15 of the 17 fixed plots were investigated. Four instruments were used to observe each plot. In addition to the commercial instruments such as hemiview fish eye camera, LAI-2000 and trac, these instruments also use the canopy analysis instrument made by Beijing Normal University. In each 20 m × 20 m plot, trac measures along two parallel routes perpendicular to the direction of sunlight incidence, which can basically represent the entire quadrat; hemiview fisheye camera and LAI-2000 measure the same points, that is, take three points on the trac line, plus the center point of the quadrat, a total of 7 measuring points. This set of data set can provide ground data for the study of remote sensing inversion method of forest structure parameters.

2020-03-10

WATER: Dataset of forest structure parameter survey at the forest sampling strip around the Dayekou Guantan forest station

Observation time: 2008-06-05 ~ 2008-06-15.A sample strip with a length of 1Km and a width of 20m was set up to cross the super sample plot from the starting point of the super sample plot at the geantan forest station in ohnoguchi.The compass was used to determine the direction of the sample, and the azimuth was 115 degrees north by east, which was basically consistent with the flight route.20 meters ×20 meters of sample land shall be arranged every 50 meters in the sample belt, a total of 20 pieces of sample land.There is some overlap between the sample belt and the super sample land. The center of the no.1 sample land of the sample belt is located at the center of the super sample land. The observation data is shown in the measurement data set per wood of the super sample land.This data set records the observation data of sample 2 ~ 20.These data include the following three parts: 1) tree data of sample plots: each wood of 2 ~ 20 plots was measured: chest diameter, tree height, crown width and undershoot height.Laser altimeter and ultrasonic altimeter were used to measure the height of big trees and under branches, flower rod was used to measure the height of small trees and under branches, chest diameter was used to measure the chest diameter of trees, and crown width was measured with a leather tape measure. 2) sample location data: the sample location is roughly determined by using a tape measure and compass. The coordinates of the center point of the sample are accurately measured using the French THALES DGPS measurement system (model z-max).The observation method is to use two GPS receivers to conduct synchronous static measurement, one in the reference station and the other in the mobile station. The observation lasts 30 minutes. The data processing software provided by the system is used for post-processing difference. 3) LAI observation data: LAI area index (LAI) of each sample plot was measured by lai-2000 and HemiView.

2020-03-10

HiWATER: Dataset of fractional vegetation cover and biomass observed in the middle of Heihe River Basin (2013)

The dataset includes the fractional vegetation cover data generated from the stations of crop land, wetland, Gebi desert and desert steppe in Yingke Oasis and biomass data generated from the stations of crop land (corn) and wetland. The observations lasted for a vegetation growth cycle from 19 May, 2012 to 15 September, 2012. 1. Fractional vegetation cover observation 1.1 Observation time 1.1.1 Station of the crop land: The observations lasted from 20 May, 2012 to 15 September, 2012, and in five-day periods for each observation before 31 July and in ten-day periods for each observation after 31 July. The observation time for the station of crop land (corn) are 2013-5-20, 2013-5-25, 2013-5-30, 2013-6-5, 2013-6-10, 2013-6-16, 2013-6-22, 2013-6-27, 2013-7-2, 2013-7-7, 2013-7-12, 2013-7-17, 2013-7-27, 2013-8-3, 2013-8-13, 2013-8-25, 2013-9-5 and 2013-9-15. 1.1.2 The other four stations: The observations lasted from 20 May, 2012 to 15 September, 2012 and in ten-day periods for each observation. The observation time for the crop land are 2013-5-20, 2013-6-5, 2013-6-16, 2013-6-27, 2013-7-7, 2013-7-17, 2013-7-27, 2013-8-3, 2013-8-13, 2013-8-25, 2013-9-5 and 2013-9-15. 1.2 method 1.2.1 Instruments and measurement method Digital photography measurement is implemented to measure the FVC. Plot positions, photographic method and data processing method are dedicatedly designed. In field measurements, a long stick with the camera mounted on one end is beneficial to conveniently measure various species of vegetation, enabling a larger area to be photographed with a smaller field of view. The stick can be used to change the camera height; a fixed-focus camera can be placed at the end of the instrument platform at the front end of the support bar, and the camera can be operated by remote control. 1.2.2 Design of the samples Three and two plots with the area of 10×10 m^2 were measured for the station of the crop land and wetland, respectively. One plot with the area of 10×10 m^2 was measured for the other three stations. Shoot 9 times along two perpendicularly crossed rectangular-belt transects. The picture generated of each time is used to calculate a FVC value. “True FVC” of the plot is then acquired as the average of these 9 FVC values. 1.2.3 Photographic method The photographic method used depends on the species of vegetation and planting pattern. A long stick with the camera mounted on one end is used for the stations of crop land and wetland. For the station of the crop land, rows of more than two cycles should be included in the field of view (<30), and the side length of the image should be parallel to the row. If there are no more than two complete cycles, then information regarding row spacing and plant spacing are required. The FVC of the entire cycle, that is, the FVC of the quadrat, can be obtained from the number of rows included in the field of view. For other three stations, the photos of FVC were obtained by directly photographing for the lower heights of the vegetation. 1.2.4 Method for calculating the FVC The FVC calculation was implemented by the Beijing Normal University. The detail method can be found in the reference below. Many methods are available to extract the FVC from digital images, and the degree of automation and the precision of identification are important factors that affect the efficiency of field measurements. This method, which is proposed by the authors, has the advantages of a simple algorithm, a high degree of automation and high precision, as well as ease of operation (see the reference). 2. Biomass observation 2.1. Observation time 2.1.1 Station of the crop land: The observations lasted from 20 May 2012 to 15 September 2012, and in five-day periods for each observation before 31 July and in ten-day periods for each observation after 31 July. The observation time for the crop land are 2013-5-25, 2013-5-30, 2013-6-5, 2013-6-10, 2013-6-16, 2013-6-22, 2013-6-27, 2013-7-2, 2013-7-7, 2013-7-12, 2013-7-17, 2013-7-27, 2013-8-3, 2013-8-13, 2013-8-25, 2013-9-5 and 2013-9-15. 2.1.2 The station of wetland: The observations lasted from 20 May 2012 to 15 September 2012, and in ten-day periods for each observation. The observation time for the crop land are 2013-6-5, 2013-6-16, 2013-6-27, 2013-7-7, 2013-7-17, 2013-7-27, 2013-8-3, 2013-8-13, 2013-8-25, 2013-9-5 and 2013-9-15. 2.2. Method Station of the crop land: Three plots were selected and three strains of corn for each observation were random selected for each plot to measure the fresh weight (the aboveground biomass and underground biomass) and dry weight. Per unit biomass can be obtained according to the planting structure. Station of the wetland: Two plots of reed with the area of 0.5 m × 0.5 m were random selected for each observation. The reed of the two plots was cut to measure the fresh weight (the aboveground biomass) and dry weight. 2.3. Instruments Balance (accuracy 0.01 g); drying oven 3. Data storage All observation data were stored in excel. Other data including plant spacing, row spacing, seeding time, irrigation time, the time of cutting male parent and the harvest time of the corn for the station of cropland were also stored in the excel.

2019-09-15