Phenotypic data of main domestic animals in Xinjiang and its surrounding areas (2021)

In order to describe the distribution pattern of genetic diversity of main domesticated animals in the Qinghai Tibet Plateau and its surrounding areas, clarify their related genetic background, and establish the corresponding genetic resource bank. In 2021, the investigation and collection of genetic resources of domestic animals will be carried out in yinguoling Mongolian Autonomous Prefecture, Xinjiang. A total of 209 blood samples of 500 local domesticated animals such as sheep, pigeons, cattle, goats and chickens were collected. This data set contains basic sample information such as species, variety, detailed sampling place, sample type, collection time, collector and storage method, which are stored in Excel form. This data set also contains the appearance photos of sampled individuals, which are stored in JPG format.

0 2021-10-19

Camera-trapping survey of the mammal diversity in the Qilian Mountain:Camera-trapping data of Lanzhou university in the Sidalong of Qilian Mountain (2020)

This dataset contains infrared camera data from January 2020 to October 2020 for the Sidalong sample area in the Qilian Mountains region of Lanzhou University. The typical habitats in the sample area of Teradalong are forests, the main tree species are Qilian round cypress and Qinghai spruce, and the typical mammals are red deer, musk deer, roe deer and blue eared-pheasant.. The main steps of infrared camera data processing include. 1. data storage, setting up directories to store photos and video files on computers, mobile hard disks or other storage media. 2. Processing of mistaken or invalid photos. Delete wind-blown, exposure, no animal presence or arbitrary form of invalid photos. 3. species identification. (1) Animal identification image library construction, each survey unit to establish a library of animal identification images, the library is mainly used for the training of species identification personnel, to facilitate their rapid grasp of species identification characteristics, accurate identification of species. (2) Processing of effective photos: for photos (videos) that can accurately identify species, fill in the name, number and environmental information of the animals in the automatic camera (video) recording form; if there are two or more animals on a photo, fill in one line each; for photos that cannot accurately identify species, fill in the column of the name of the animal that cannot be identified, and fill in the number and environmental information, and fill in the photo processing For poultry and livestock, fill in the name and number of animals and poultry and livestock; for people, fill in the name of the animal as "herder, tourist, forest ranger", etc. (3) other information: environmental information records, according to the photos (video), fill in the following environmental information: temperature: according to the temperature shown on the photos to fill in. Weather: sunny, cloudy, rain, snow. Need to judge carefully. Snow: with or without. Behavior: foraging, drinking, hunting, mating, fighting, fighting for food, repelling, playing, running, resting, walking, alerting, etc. Animal age: young, subspecies, female, male, unknown. Published observation data include: file number, file format, folder number, camera number, deployment point number, shooting date, shooting time, working days (days), element, species name, young, sub, female, male, unknown, total, behavior, temperature (℃), weather, snow.

0 2021-07-15

Camera-trapping survey of the mammal diversity in the Qilian Mountain:Camera-trapping data of Lanzhou university in the Haxi of Qilian Mountain (2019-2020)

This dataset contains infrared camera data from July 2019 to October 2020 for the Haxi sample area in the Qilian Mountains region of Lanzhou University. The typical habitat in the Haxi sample area is forest, the main tree species are Qilian round cypress and Qinghai spruce, and the typical mammals are red deer, musk deer, roe deer and blue eared-pheasant.. The area is heavily grazed and has frequent human activities. The main steps of infrared camera data processing include. 1. data storage, setting up directories to store photos and video files on computers, mobile hard disks or other storage media. 2. Processing of mistaken or invalid photos. Delete wind-blown, exposure, no animal presence or arbitrary form of invalid photos. 3. species identification. (1) Animal identification image library construction, each survey unit to establish a library of animal identification images, the library is mainly used for the training of species identification personnel, to facilitate their rapid grasp of species identification characteristics, accurate identification of species. (2) Processing of effective photos: for photos (videos) that can accurately identify species, fill in the name, number and environmental information of the animals in the automatic camera (video) recording form; if there are two or more animals on a photo, fill in one line each; for photos that cannot accurately identify species, fill in the column of the name of the animal that cannot be identified, and fill in the number and environmental information, and fill in the photo processing For poultry and livestock, fill in the name and number of animals and poultry and livestock; for people, fill in the name of the animal as "herder, tourist, forest ranger", etc. (3) other information: environmental information records, according to the photos (video), fill in the following environmental information: temperature: according to the temperature shown on the photos to fill in. Weather: sunny, cloudy, rain, snow. Need to judge carefully. Snow: with or without. Behavior: foraging, drinking, hunting, mating, fighting, fighting for food, repelling, playing, running, resting, walking, alerting, etc. Animal age: young, subspecies, female, male, unknown. Published observation data include: file number, file format, folder number, camera number, deployment point number, shooting date, shooting time, working days (days), element, species name, young, sub, female, male, unknown, total, behavior, temperature (℃), weather, snow.

0 2021-07-15

Camera-trapping survey of the mammal diversity in the Qilian Mountain:Camera-trapping data of Lanzhou university in the Qifeng of Qilian Mountain (2019-2020)

This dataset contains infrared camera data from January 2020 to November 2020 from Qifeng sample area in Qilian Mountains region of Lanzhou University. It belongs to the Sunan Yugu Autonomous County, Zhangye City, Gansu Province, in the northwest of the Sunan Yugu Autonomous County, the western part of the Western Corridor and the northern foot of the Qilian Mountains, east of Daxiang, south of Qilian County and Tianjun County, Qinghai Province, west of Subei County, Jiuquan City, and north of Jiuquan Suzhou District, Jiayuguan City and Yumen City. The typical habitats in the Qifeng sample area are desert and alpine bare rock, and typical mammals include snow leopard, lynx, white-lipped deer and blue sheep. The main steps of infrared camera data processing include. 1. data storage, setting up directories to store photos and video files on computers, mobile hard disks or other storage media. 2. Processing of mistaken or invalid photos. Delete wind-blown, exposure, no animal presence or arbitrary form of invalid photos. 3. species identification. (1) Animal identification image library construction, each survey unit to establish a library of animal identification images, the library is mainly used for the training of species identification personnel, to facilitate their rapid grasp of species identification characteristics, accurate identification of species. (2) Processing of effective photos: for photos (videos) that can accurately identify species, fill in the name, number and environmental information of the animals in the automatic camera (video) recording form; if there are two or more animals on a photo, fill in one line each; for photos that cannot accurately identify species, fill in the column of the name of the animal that cannot be identified, and fill in the number and environmental information, and fill in the photo processing For poultry and livestock, fill in the name and number of animals and poultry and livestock; for people, fill in the name of the animal as "herder, tourist, forest ranger", etc. (3) other information: environmental information records, according to the photos (video), fill in the following environmental information: temperature: according to the temperature shown on the photos to fill in. Weather: sunny, cloudy, rain, snow. Need to judge carefully. Snow: with or without. Behavior: foraging, drinking, hunting, mating, fighting, fighting for food, repelling, playing, running, resting, walking, alerting, etc. Animal age: young, subspecies, female, male, unknown. Published observation data include: file number, file format, folder number, camera number, deployment point number, shooting date, shooting time, working days (days), element, species name, young, sub, female, male, unknown, total, behavior, temperature (℃), weather, snow.

0 2021-07-14

Aquatic zooplankton of lakes in Selin co Namco area, Qinghai Tibet Plateau (August September, 2019)

The data includes: zooplankton species list; zooplankton density; microscopy; high-throughput sequencing; complete data; constructing an original data set for lakes on the Qinghai-Tibet Plateau. Zooplankton is an indispensable link in lake water ecological investigation, and it is a link between the system The location of the food web is an important carrier for the material circulation and energy flow of the food web. The systematic investigation and study of the composition and biodiversity of the zooplankton in the lakes on the Qinghai-Tibet Plateau is particularly important for understanding the stability and resilience of the lake ecosystem on the Qinghai-Tibet Plateau. In addition, Zooplankton are very sensitive to environmental changes, and changes in their structure and functional groups can indicate the intensity and magnitude of environmental pressure.

0 2021-06-08

Gross Primary Productivity (GPP) dataset of Tibetan Plateau (1980-2018)

The data set is based on the GPP simulated by 16 dynamic global vegetation models (TRENDY v8) under S2 Scenario (CO2+Climate) and represents the gross primary productivity of the ecosystem. Data was derived from Le Qu é r é Et al. (2019). The range of source data is global, and the Qinghai Tibet plateau region is selected in this data set. Original data is interpolated into 0.5*0.5 degree by the nearest neighbor method in space, and the original monthly scale is maintained in time. The data set is the standard model output data, which is often used to evaluate the temporal and spatial patterns of gross primary productivity, and compared with other remote sensing observations, flux observations and other data.

0 2021-05-18

Information of animal specimens and tissue samples in the second comprehensive scientific expedition of Qinghai Tibet Plateau (2019-2020)

In the first year (from the end of 2019 to the beginning of 2020), a total of 110 scientific research teams were organized, focusing on more than 60 field scientific investigations in Motuo area, Qilian Mountain and West Tianshan Mountain of the Qinghai Tibet Plateau, covering the whole Qinghai Tibet Plateau. By means of infrared camera, transect and sampling point, the authors investigated the vertebrates (birds, mammals, reptiles, amphibians and fishes) in the Qinghai Tibet Plateau and the agro pastoral insects in the ecotone between agriculture and animal husbandry in the Asian water tower region and Himalaya region. We have completed the first round of field investigation of exotic fish in typical water bodies such as Yarlung Zangbo River, exotic amphibians and reptiles in Lhasa, Nyingchi and Xining city of Qinghai Province, rodents in northern Sichuan Tibet line, and Przewalski gazelle, and carried out and completed the collection of genetic (or histological) samples of some species. This data set contains the information of tissue samples collected during the first year of the scientific expedition. Each folder contains one data set specification table and one or more tissue sample information tables. The information report includes the sub subject number, species, collection place, collection time, collector, sample type, storage method and other information.

0 2021-04-16

Genome sequencing data of equine (2020)

In order to study the population evolution history and local adaptive genetic mechanism of main domesticated equine animals in Qinghai Tibet Plateau and its surrounding areas, and to establish the corresponding germplasm genetic resource bank. We have sequenced 236 horse samples collected in Qinghai Province, Tibet Autonomous Region and Xinjiang Autonomous Region by the end of 2018, including Tibetan horse, Tibetan donkey, plain domestic donkey and Jiama plain local breed. Seventy five samples (including 73 donkey samples and two horse samples) were sequenced for mitochondrial genome and D-loop sequencing. A number of genomic data were generated by sequencing, which provided data for tracing the domestication, migration, expansion and other historical events of horse domesticated animals in this area, and further exploring the adaptation mechanism of equine animals to the harsh environment such as hypoxia, high temperature and dryness.

0 2021-01-04

WATER: Dataset of forest structure parameter survey at the temporary forest sampling plot in the Dayekou watershed foci experimental area (2008)

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.

0 2020-08-20

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.

0 2020-08-20