Analysis data of plant carbon and nitrogen cycle (2019-2020)

The data were collected from the sample plot of Haibei Alpine Meadow Ecosystem Research Station (101°19′E,37°36′N,3250m above sea level), which is located in the east section of Lenglongling, the North Branch of Qilian Mountain in the northeast corner of Qinghai Tibet Plateau. Alpine meadow is the main vegetation type in this area. The data recorded the light, air temperature and humidity, wind temperature and wind speed above the alpine plant canopy. The radiation intensity above the alpine plant canopy was recorded by LI-190R photosynthetic effective radiation sensor (LI-COR, Lincoln NE, USA) and LR8515 data collector (Hioki E. E. Co., Nagano, Japan), and the recording interval was once per second. S580-EX temperature and humidity recorder (Shenzhen Huatu) and universal anemometer are used (Beijing Tianjianhuayi) record the daily dynamics of air temperature and humidity, wind temperature and wind speed every three seconds. The recording time is from 10:00 on July 13 to 21:00 on August 17, Beijing time. Due to the need to use USB storage time and replace the battery every day, 3-5min of data is missing every day, and the missing time period is not fixed. At present, the data has not been published. Through research on the data The data can further explore the microenvironment of alpine plant leaves and its possible impact on leaf physiological response.

0 2022-01-18

Data set of vegetation investigation of in river and lake source (2020)

A standardized field survey was carried out from August to September 2020 in the source areas of rivers and lakes in Tibet Autonomous Region. A total of 25 samples and 75 quadrats were investigated. The data set includes sample number, plot number, latitude and longitude, altitude, aboveground biomass, species number and coverage of the plot, and the data format is Excel. The area volume of collected and investigated samples was 100cm*100cm, and each sample site had 3 quadrats named Plot1, Plot2 and Plot3. All data were collected and measured in the field, and the quality of data was ensured in the field survey according to the vegetation survey specifications. This dataset provides theoretical basis for rational utilization of grassland resources and data support for comprehensive evaluation of environmental effects of typical land use change.

0 2021-12-28

Demonstration in situ data set of three-dimensional canopy micro structure imaging system(2019-2021)

The demonstration data set of canopy micro structure imaging system (CanoMIS) demonstration data set contains the standard branch data of representative plants such as corn, sunflower, Yunsong, Ulmus pumila, Fraxinus mandshurica, Juglans mandshurica, peach tree and chicken tree strip collected by CanoMIS in Zhangye Daman station, Qilian Mountain Ecological Station, Shenyang Qingyuan Ecological Station and Beijing urban area. CanoMIS is installed on the pan-tilt, and placed on the ground or ecological observation tower. One can access CanoMIS through the operating terminal computer to conduct in-situ sampling of the standard branches of interest, and obtain the two-dimensional intensity images and depth images (three-dimensional images) of the standard branches without background interference, ,which solves the problem that the traditional imaging technology is vulnerable to background interference and the loss of distance information. It provides a novel technique for in-situ analysis of standard branches.

0 2021-12-01

Ancient DNA sequencing data of archaeological sediments from Klu lding site in Nyingchi region

1) Data content: the data are the ancient DNA data generated by studying the cultural layer of Klu lding site in Nyingchi region, Tibetan Plateau, including the hiseqx metagenomics data of 10 ancient DNA samples from 4 layers. It can be used to preliminarily analyze the changes of species composition recorded by ancient DNA in the sediments, and reveal the process of local agricultural development. 2) Data source and processing method: the research group has its ownership. the data were obtained by using pair-end library building and Illumina hiseqx sequencing platform. 3) Data quality: 20.3 MB, Q30 > 85%. 4) Application: The data will be used to explore the potential of the ancient DNA from archaeological sediments in revealing the development of ancient agriculture on the Tibetan Plateau.

0 2021-11-29

Demonstration data set of automatic plant phenology observer at Heihe Daman station (2019-2021)

The demonstration data set of automatic plant phenology observer at Heihe Daman station is the corn phenology observation data set collected by the plant phenology observer at Heihe Daman station. The plant phenology observer can collect phenology images through the phenology observation hardware system based on multispectral imager and wireless transmission module, and through online calculation and visual image management Phenological information processing and system control software can realize the automatic identification of key phenological periods at individual and community scales. Through the data collected by the automatic plant phenology observer, the indexes such as vegetation greenness index and NDVI index can be calculated, the change process of key plant phenology can be monitored, and the change law of vegetation phenology can be reflected.

0 2021-11-16

Southeast Tibet station of Chinese Academy of Sciences: basic meteorological data of forest line on the east slope of Sejila Mountain (2019-2020)

1) Data content (including elements and significance): the data includes the daily values of air temperature (℃), precipitation (mm), relative humidity (%), wind speed (M / s) and radiation (w / m2) 2) Data source and processing method; Air temperature, relative humidity, radiation and wind speed are daily mean values, and precipitation is daily cumulative value; Data collection location: 29 ° 39 ′ 25.2 ″ n near the forest line on the east slope of Sejila Mountain; 94°42′25.62″E; 4390m; The underlying surface is natural grassland; Collector model Campbell Co CR1000, acquisition time: 10 minutes. Digital automatic data acquisition. The temperature and relative humidity instrument probe is hmp155a; The wind speed sensor is 05103; The precipitation is te525mm; The radiation is li200x; 3) Data quality description; The original data of air temperature, relative humidity and wind speed are the average value of 10 minutes, and the precipitation is the cumulative value of 10 minutes; The daily average temperature, relative humidity, precipitation and wind speed are obtained by arithmetic average or summation. Due to the limitation of the sensor, the precipitation in winter may have a certain error. 4) Data application achievements and prospects: this data is the update of the existing data "Sejila Mountain meteorological data (2007-2017)" and "basic meteorological data of Sejila east slope forest line of South Tibet station of Chinese Academy of Sciences (2018)". The data time scale span is large, which is convenient for scientists or graduate students in Atmospheric Physics, ecology and atmospheric environment. This data will be updated from time to time every year.

0 2021-11-05

Dataset of growing season average NDVI changing trends in Three River Source National Park (2000-2018)

Based on the average NDVI (spatial resolution 250m) of MODIS during the growing season from 2000 to 2018, the trend of NDVI was calculated by using Mann-Kendall trend detection method. Three parks of Three River Source National Park are calculated (CJYQ: Yangtze River Park; HHYYQ: Yellow River Park; LCJYQ: Lancang River Park). CJYQ_NDVI_trend_2000_2018_ok.tif: Changjiang Source Park NDVI trend. CJYQ_NDVI_trend_2000_2018_ok_significant.tif: Changjiang Source Park NDVI change trend, excluding the area that is not significant (p > 0.05). CJYYQ_gs_avg_NDVI_2000.tif: The average NDVI of the Yangtze River Source Park in 2000 growing season. Unit NDVI changes every year.

0 2021-11-02

Continuous observation data set of leaf area index (based on hemispheric image) in Zhangye City (2019-2021)

Leaf area index is an important structural parameter of ecosystem, which is used to reflect the number of plant leaves, changes in canopy structure, life vitality of plant community and its environmental effects, provide structured quantitative information for the description of material and energy exchange on the surface of plant canopy, and balance the energy of carbon accumulation, vegetation productivity and interaction between soil, plant and atmosphere in ecosystem, Vegetation remote sensing plays an important role. The data comes from the distributed leaf area index instrument independently developed by the project (based on hemispheric image), which takes hemispheric images of forest canopy at fixed time, fixed point and from bottom to top, and uploads them through wireless network. This data acquisition is the original hemispherical image, which needs further processing to calculate the leaf area index, which can be processed by hemiview and other software.

0 2021-11-01

Test and demonstration data set of automatic recording meter for tree diameter at breast height at field stations (2019-2020)

We develop a DBH recording meter that can automatically record DBH at high frequencies and high precision in the field by designing a high-precision displacement sensor and temperature compensation algorithm. With the developed software, tree growth dynamics can be evaluated online in real time through remote computers or smartphones。The data set is collected through field test and demonstration at Qilian mountain station in Gansu Province and Beijing forest station by using the DBH recording meter. The data table includes the control values measured manually and the measured values of VI (displacement), RI (tree perimeter) and CI (tree diameter) collected by different tree species at different stations. The development of this automatic DBH recording meter promote the automation, intelligent level and independent innovation of vegetation ecological monitoring in China. The dynamic changes of DBH of trees serve the national ecosystem monitoring network, the construction of national "two screens and three belts" ecological security barrier and the demand for large-scale, all-weather and three-dimensional monitoring of vulnerable ecological areas. It plays an important supporting role in promoting the construction of ecological civilization in China.

0 2021-11-01

Data of green wood density of trees at field stations (2020)

Data collection sites include Qilian mountain forest station and Dangzhai forest farm in Gansu Province (August 2020), northwest ditch and east side of northeast tiger and leopard National Forest Park (October 2020). Data collection elements include tree species, DBH (CM), core mass (g), core length (CM) and green wood density (g / cm ^ 3). The core was drilled and sampled with a growth cone at 1.3m of the tree. The mass of the tree core was measured by electronic balance, the length of the tree core was measured by vernier caliper, and the data of tree green wood density were measured and calculated. The transceiver antenna of the living tree density observer is placed on both sides of the tree. After inputting the tree species and DBH, each tree collects data five times, averages the five measurement results of each tree, and then saves the measurement results.

0 2021-11-01