Plateau pika is a key species of the Qinghai Tibet Plateau and an indigenous species formed with the uplift of the Qinghai Tibet Plateau. During the long-term evolution, it has evolved a unique life history strategy to adapt to the extreme environment of the plateau. This sub project (2019QZKK05010410) investigates the distribution area of plateau pika, analyzes its population fluctuation rule and its influencing factors in the context of global climate change, and discusses the ecological significance of plateau pika in the alpine meadow ecosystem. This data set contains the information table of 213 plateau zokor tissue samples collected in Gonghe County, Guinan County, Hainan Prefecture, and Maqin County, Golog Prefecture, Qinghai Province in 2020, including species, collection place, collection time, collection person, sample type and other information. The information table is named after the sub subject number - year - group and opened in excel
QU Jiapeng
This dataset is based on the Tibet Statistical Yearbook and Qinghai Statistical Yearbook (2020). The two books contain statistical data on the economic and social development of the Tibet Autonomous Region and Qinghai Province since 2019, mainly from 1951 to 2020. Extract the agricultural aspects, from the basic situation of rural areas and agriculture, the basic situation of rural areas, rural employees, the total output value of agriculture, forestry, animal husbandry and fishery in sub-regional cities, the sown area of main crops, the output of main agricultural products, the output per unit area of main agricultural products, and the sown area of crops It is an important statistical data for people from all walks of life at home and abroad to understand the Qinghai-Tibet Plateau and the Qinghai-Tibet Plateau.
TANG Yawei TANG Yawei
In order to describe the distribution pattern of genetic diversity of important livestock and poultry germplasm resources in the Qinghai Tibet Plateau, clarify their related genetic background, and establish a corresponding genetic resource bank. During 2019-2022, 2167, 1056 and 516 tissue samples of local Tibetan sheep and fine wool sheep were collected in Gangca County, Haibei Tibetan Autonomous Prefecture, Qinghai Province, and 2074 and 1548 lambing records were recorded. This data set includes 3 tissue sample information tables and 2 lambing record information tables. The organization sample information table records the variety, collection place, collection time, sample type and other information. The lambing record information table records the variety, detailed sampling place, sex, date of birth, birth weight and other information. The information table is stored in excel form.
ZHAO Kai
The dataset includes climate suitability zonation, climate and soil suitability zonation and climate and soil terrain suitability zonation dataset of 8 forages. The dataset can provide important data support for artificial grassland construction. Based on the climate index model and maximum entropy model, the climate suitability index of each pasture was constructed by using the temperature, precipitation data of the last 40 years and elevation data, and considering the soil type, soil organic matter content and topographic factors, the planting zonation of eight pasture species was established in Qinghai. Eight forages are important forage resources in alpine areas. The accuracy of climate suitability index was ensured by field investigation, and the practicability of dataset of pasture planting zonation was ensured by comprehensive consideration of climate factors and soil topographic factors. Artificial grassland planting is not only the main means of ecological restoration of degraded grassland, but also an important part of grassland production structure adjustment. Reasonable and scientific grass planting is the foundation. The dataset of forage planting zonation has an important application prospect in the implementation of major ecological projects and the scientific management of grassland.
ZHOU Huakun , SU Wenjiang , ZHOU Bingrong , SHI Mingming , ZHAO Huifang
In order to describe the distribution pattern of genetic diversity of important rodents in the Qinghai Tibet Plateau, clarify their related genetic background, and establish the corresponding genetic resource bank. In 2021, this sub project (2019QZKK05010410) focused on the investigation of plateau pika in Haixi Mongolian and Tibetan Autonomous Prefecture, Golog Prefecture and Hainan prefecture, Qinghai. A total of 200 plateau pika samples were collected, and the solid samples were spleen and lung tissues. This data set contains a sample information table and habitat photos, work photos and work videos. The sample information table contains basic sample information such as species, gender, detailed sampling place, altitude, sample type, collection time, collector and storage method, which are stored in the form of Excel.
QU Jiapeng
In order to describe the distribution pattern of genetic diversity of pika germplasm resources in Qinghai Tibet Plateau, clarify its related genetic background, and establish the corresponding genetic resource bank. In 2021, this sub project (2019QZKK05010209) focused on Qinghai Province (Haixi Mongolian and Tibetan Autonomous Prefecture, Golmud City, Kunlun mountain pass; Haixi Mongolian and Tibetan Autonomous Prefecture, Dulan County, Xiangride Town, Gouli township; Golog Tibetan Autonomous Prefecture, Maduo County; Golog Tibetan Autonomous Prefecture, Maqin County, Dawu town; Huangnan Tibetan Autonomous Prefecture, Zeku County; Hainan Tibetan Autonomous Prefecture, Guinan County, Taxiu township) 93 plateau pika germplasm resources were collected at different altitudes, and the solid samples included blood or tissue, feces and so on. This data set contains 1 sample information table. The sample information table contains basic sample information such as species, variety, detailed sampling place, sample type, collection time, collector and storage method, which is stored in the form of Excel.
ZHANG Liangzhi
The Qaidam Basin is a key area for understanding the paleoenvironmental and faunal history of the Tibetan Plateau. The fossil schizothoracine fish, Hsianwenia wui, evolved extraordinarily thickened bones to adapt to the aridification of the Qaidam Basin during the Pliocene. However, the nature of the bone thickening itself remains elusive. To promote the further investigation of the physiological mechanism of the pachyostosis and the phylogenetic interrelationships of Hsianwenia and all relevant cyprinids, here we present a comprehensive morphological study of Hsianwenia. We have new information on the anterior part of the cranial cavity, a large supraneural 3 in the Weberian apparatus, numerous procurrent caudal fin rays supported by the preural centrum (Pu) 5, and a neural arch on Pu2. We also find the differentiated pattern of the bone-thickening: the pachyostosis exists in the endoskeleton but not in the dermal skeleton; it is more obvious in ventral bones than in dorsal ones, when the thickening is present in the dorsally and ventrally grouped endoskeletal bones (e.g., the epineural and epipleural intermuscular bones). Considering the integrity of musculoskeletal system manipulating the chewing activities, we suspect that the thickened pharyngeal jaws and the hard food processing might be associated with the unique hind protrusion (cleithral “humeral” process) of the dermal pectoral girdle of Hsianwenia.
WU Feixiang
This data set includes the original Landsat satellite image data TM and ETM+ data of Salt Lake area in Qinghai Province from January to December 2020, including 4 bands of MSS sensor (spatial resolution 78m), 7 bands of TM sensor and 8 bands of ETM+ sensor (spatial resolution 15m and 30m). The data is based on MSS, TM and ETM+ remote sensing image data of Salt Lake area collected and sorted on USGS official website. Strict quality assurance measures are taken in the data processing process. The data is warehoused after quality inspection, which can ensure the data quality. The data size is about 22.3gb.
CHEN Liang, WANG Jianping
This data set includes the original Landsat satellite image data TM and ETM+ data of Salt Lake area in Qinghai Province from January to December 2013, including 4 bands of MSS sensor (spatial resolution 78m), 7 bands of TM sensor and 8 bands of ETM+ sensor (spatial resolution 15m and 30m). The data is based on MSS, TM and ETM+ remote sensing image data of Salt Lake area collected and sorted on USGS official website. Strict quality assurance measures are taken in the data processing process. The data is warehoused after quality inspection, which can ensure the data quality. The data size is about 20.6gb.
CHEN Liang, WANG Jianping
This data set includes the original Landsat satellite image data TM and ETM+ data of Salt Lake area in Qinghai Province from January to December 2002, including 4 bands of MSS sensor (spatial resolution 78m), 7 bands of TM sensor and 8 bands of ETM+ sensor (spatial resolution 15m and 30m). The data is based on MSS, TM and ETM+ remote sensing image data of Salt Lake area collected and sorted on USGS official website. Strict quality assurance measures are taken in the data processing process. The data is warehoused after quality inspection, which can ensure the data quality. The data size is about 3.18GB.
CHEN Liang, WANG Jianping
1. The data content includes: year, month, day, hour, longitude, latitude, altitude, meridional (UQ) and latitudinal (VQ) components of water vapor flux; 2. Data source and processing method: GPS meteorological sounding data of voyages in the eastern Indian Ocean, and calculate water vapor flux through relative humidity, wind field, air pressure and altitude; 3. Data quality description: vertical continuous observation with 1 second vertical resolution; 4. Data application achievements and prospects: Study on the changes of water vapor transport in the tropical Indian Ocean;
LIU Zhaofei, YAO Zhijun
In order to collect the special germplasm resources of Qinghai Tibet Plateau and excavate the molecular markers affecting the special germplasm resources, individual sheep with excellent ectopic spots were selected for marker assisted selection, propagation and generation breeding according to the genetic marker information, so as to cultivate the families of special germplasm resources. In 2021, this sub project (2019QZKK05010704) widely collected samples of Qinghai Tibetan sheep and Qinghai fine wool sheep in Haibei, Qinghai, and continued to establish and expand the first and second core groups in Ledu agricultural experimental station and Qinghai Sanjiaocheng sheep breeding farm. This data set contains the basic information of 1050 tissue samples, including variety, collection place, collection time, gender, tissue type, preservation method, etc.
ZHAO Kai
This sub project (2019qzkk05010411) focuses on the population investigation and monitoring of wild yak, Tibetan antelope and brown bear, carries out systematic and continuous field investigation, finds out their geographical distribution, population number and population structure, and carries out appropriate habitat assessment. The distribution area and potential distribution area are selected and divided into multiple sub areas. Stratified random sampling is adopted according to habitat type, climate, altitude and other factors, and the population counting method, variable distance spline method or fixed width spline method are used for investigation respectively. At the same time, in view of the extremely low encounter rate of brown bears, combined with the interview method. The investigation area mainly includes the distribution areas and potential distribution areas of the three animals in Yushu Tibetan Autonomous Prefecture, Haixi Mongolian Tibetan Autonomous Prefecture, Haibei Tibetan Autonomous Prefecture and other prefectures and counties in Qinghai Province, in order to master the distribution and five-year population dynamics of wild yak, Tibetan antelope and brown bear in Qinghai Province. This data set contains photos of yaks, Tibetan antelopes and brown bears investigated in Qinghai in 2021.
CHEN Zhenning
This sub project (2019QZKK05010217) plans to select Qinghai sand lizard, an exothermic vertebrate that is very sensitive to environmental changes, as the representative. Through field investigation, we will compare the differences in morphology, physiology and life history of Qinghai sand lizard populations at different altitudes in the Qinghai Tibet Plateau and adjacent areas, and analyze the response and adaptation characteristics of Qinghai sand lizard to environmental changes in the Qinghai Tibet Plateau, Combined with species distribution model (SDM) and mechanism model, this paper predicts the threatened degree of Qinghai sand lizard in the future, and puts forward the Protection Countermeasures of Qinghai sand lizard diversity on the Qinghai Tibet Plateau under the background of climate warming, so as to provide a theoretical basis for the protection of Reptile Diversity on the Qinghai Tibet Plateau under the background of environmental change. This data includes ecological photos and habitat photos of Qinghai sand lizard in Gonghe County, Haiyan County and Maduo County of Qinghai Province.
DU Weiguo
In order to determine the distribution points and habitat types of plateau forest frog along the latitudinal gradient in Qinghai, in 2021, a total of 8 distribution points of plateau forest frog were collected in Minhe County of Haidong, Qinghai, Gonghe County of Hainan Tibetan Autonomous Prefecture and Maqin County of Golog Prefecture, covering an altitude of 2000-3800m. This dataset contains 1 coordinate information table and 57 habitat photos. The coordinate information table contains information such as number, recording date, time, weather, coordinate longitude and latitude, altitude sample, habitat type and photo number of representative habitat, which are stored in the form of Excel. Photos are stored in JPG format. In order to reveal the impact of climate change on the diversity of plateau forest frogs on the Qinghai Tibet Plateau in the future, the thermal safety margin of different geographical populations of plateau forest frogs was calculated through the data of thermophysiological indexes and environmental effective temperature, and the threat of climate warming of different geographical populations of plateau forest frogs was evaluated. This data set includes field activity body temperature, resting metabolic rate, ambient temperature and morphological data of four altitude populations of plateau forest frog, which supplements the selected body temperature, tolerance temperature and temperature correction data of 2000 m altitude populations. The data is stored in Excel format. In order to study the differences of genetic diversity of plateau forest frog at different altitudes, 100 samples of plateau forest frog collected from four altitudes (2000 m, 2600 m, 3200 m and 3800 m) of Qinghai Tibet Plateau were sequenced and analyzed based on the sequences of four mitochondrial genes (12S rRNA, 16S rRNA, coi and cytb), so as to provide scientific basis for the protection of this species. This data includes 12S rRNA, 16S rRNA The sequence data obtained from the sequencing of COI and cytb genes supplement the sequence data of four genes of the population at an altitude of 2000m. The data is stored in FASTA format
ZHANG Yongpu
In order to describe the effects of environmental changes and human disturbance on the temporal and spatial distribution of small mammals in the Qinghai Tibet Plateau, statistical models and molecular techniques were used to identify the species of small mammals with different altitude gradients. In 2021, 105 small mammal resources such as plateau pika, Meriones meridionalis, three toed jerboa, five toed jerboa and Qinghai squirrel were collected in 8 areas of Xihai Town, Gangcha county and Delingha city of Qinghai Province. The solid samples include animal solid samples and muscles, heart, liver, spleen, lung, kidney, pancreas, bladder, testis and ovary. This data set contains one specimen information table, one tissue sample information table and one photo corresponding to each specimen. The sample information table contains basic sample information such as species, variety, detailed sampling place, sample type, collection time, collector and storage method, which is stored in the form of Excel. Photos, stored in JPG format.
HOU Xiang
The data set records the statistical data of natural grassland grade area in Golmud City, Qinghai Province in 1988 and 2012. The data are classified and counted according to the grade code of natural grassland. The grassland is divided into five grades: excellent, good, medium, low and inferior with grassland type as the basic unit. The classification criteria of each grade are as follows: Grade I (excellent) Grassland: the weight of excellent forage accounts for more than 60%; Grade II (good grade) Grassland: the weight of grass above good grade accounts for more than 60%, and that of other types accounts for 40%; Grade III (medium) Grassland: the weight of forages above the medium category accounts for more than 60%, and that of other categories accounts for 40%; Grade IV (low) Grassland: the weight of grass above the low category accounts for more than 60%, and that of other categories accounts for 40%; Grade V (inferior) Grassland: the weight of inferior forage accounts for more than 40% The grassland level is divided into 8 levels according to the fresh grass yield. Standards at all levels are as follows: Level 1 Grassland: more than 12000k g of fresh grass per hectare of grassland; Level 2 Grassland: 9000kg ~ 12000kg fresh grass per hectare; Level 3 Grassland: 6000kg ~ 9000kg fresh grass per hectare; Level 4 Grassland: 4500kg ~ 6000kg fresh grass per hectare; Level 5 Grassland: 30001kg ~ 4500kg fresh grass per hectare; Grade 6 Grassland: 1500kg ~ 3000kg fresh grass per hectare; Grade 7 Grassland: 750KG ~ 1500kg fresh grass per hectare; Grade 8 Grassland: fresh grass per hectare is less than 750KG. The data are compiled from the grassland station of Qinghai Province and the grassland resources statistics of Qinghai Province issued in 1988 and 2012. The data set contains two data tables, namely: Statistics of natural grassland grade area in Golmud City (2012) and statistics of natural grassland grade in Golmud City (1988). The data table structure is similar. For example, there are 9 fields in the statistical data of natural grassland grade area in Golmud City (2012): Field 1: Total Field 2: Level 1 Field 3: Level 2 Field 4: Level 3 Field 5: Level 4 Field 6: Level 5 Field 7:6 level Field 8: Level 7 Field 9: level 8
AGRICULTURAL AND RURAL Department of Qinghai Province
The data set records the statistical data of grassland type area and livestock carrying capacity in Golmud City, Qinghai Province in 1988 and 2012. The data are classified and counted according to the grassland group code, such as: I represents Alpine dry grassland, II represents mountain dry grassland, III represents Alpine desert, B represents medium grass group, J represents shrub group, etc, For specific grassland group type codes and their corresponding meanings, see "description of grassland group type codes in Qinghai Province. PDF" in the data set. The data are compiled from the grassland station of Qinghai Province and the grassland resources statistics of Qinghai Province issued in 1988 and 2012. The data set contains three data tables, which are: statistical data of grassland type area and livestock carrying capacity in Golmud City (1988), statistical data of grassland type area and livestock carrying capacity in Golmud City (2012) and code description of grassland type in Qinghai Province. The data table structure is similar. For example, there are 8 fields in the statistical data (2012) of grassland type, area and livestock carrying capacity in Golmud City: Field 1: type code Field 2: grassland type name Field 3: grassland area Field 4: available area of grassland Field 5: average unit yield of fresh grass Field 6: average unit yield of edible fresh grass Field 7: stocking capacity Field 8: grassland type grade
AGRICULTURAL AND RURAL Department of Qinghai Province
The data set records the statistical data of natural grassland grade area in Gangcha County, Qinghai Province in 1988 and 2012. The data are classified and counted according to the grade code of natural grassland. The grassland is divided into five grades: excellent, good, medium, low and inferior based on the grassland type. The classification criteria of each grade are as follows: Grade I (excellent) Grassland: the weight of excellent forage accounts for more than 60%; Grade II (good grade) Grassland: the weight of grass above good grade accounts for more than 60%, and that of other types accounts for 40%; Grade III (medium) Grassland: the weight of forages above the medium category accounts for more than 60%, and that of other categories accounts for 40%; Grade IV (low) Grassland: the weight of grass above the low category accounts for more than 60%, and that of other categories accounts for 40%; Grade V (inferior) Grassland: the weight of inferior forage accounts for more than 40% The grassland level is divided into 8 levels according to the fresh grass yield. Standards at all levels are as follows: Level 1 Grassland: more than 12000k g of fresh grass per hectare of grassland; Level 2 Grassland: 9000kg ~ 12000kg fresh grass per hectare; Level 3 Grassland: 6000kg ~ 9000kg fresh grass per hectare; Level 4 Grassland: 4500kg ~ 6000kg fresh grass per hectare; Level 5 Grassland: 30001kg ~ 4500kg fresh grass per hectare; Grade 6 Grassland: 1500kg ~ 3000kg fresh grass per hectare; Grade 7 Grassland: 750KG ~ 1500kg fresh grass per hectare; Grade 8 Grassland: fresh grass per hectare is less than 750KG. The data are compiled from the grassland station of Qinghai Province and the grassland resources statistics of Qinghai Province issued in 1988 and 2012. The data set contains two data tables, namely: statistical data of natural grassland grade area in Gangca county (2012) and statistical data of natural grassland grade in Gangca county (1988). The data table structure is similar. For example, there are 9 fields in the statistical data of natural grassland grade area in Gangcha county (2012): Field 1: Total Field 2: Level 1 Field 3: Level 2 Field 4: Level 3 Field 5: Level 4 Field 6: Level 5 Field 7:6 level Field 8: Level 7 Field 9: level 8
AGRICULTURAL AND RURAL Department of Qinghai Province
The data set records the statistical data of grassland type area and livestock carrying capacity in Gangcha County, Qinghai Province in 1988 and 2012. The data are classified and counted according to the grassland group code, such as: I represents Alpine dry grassland, II represents mountain dry grassland, III represents Alpine desert, B represents medium grass group, J represents shrub group, etc, For specific grassland group type codes and their corresponding meanings, see "description of grassland group type codes in Qinghai Province. PDF" in the data set. The data are compiled from the grassland station of Qinghai Province and the grassland resources statistics of Qinghai Province issued in 1988 and 2012. The data set contains three data tables, namely: grassland type area and livestock carrying capacity statistics of Gangca county (1988), grassland type area and livestock carrying capacity statistics of Gangca county (2012) and grassland group code description of Qinghai Province. The data table structure is similar. For example, there are 8 fields in the statistical data (2012) of grassland type, area and livestock carrying capacity in Gangca County: Field 1: type code Field 2: grassland type name Field 3: grassland area Field 4: available area of grassland Field 5: average unit yield of fresh grass Field 6: average unit yield of edible fresh grass Field 7: stocking capacity Field 8: grassland type grade
AGRICULTURAL AND RURAL Department of Qinghai Province
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