The data set includes the spatial distribution of grass yield in the Qinghai-Tibetan Plateau in 1980, 1990, 2000, 2010, and 2017. The gross primary productivity (GPP) of grassland in the Qinghai-Tibetan Plateau was simulated based on the ecological hydrological dynamic model VIP (vegetation interface process) with independent intellectual property of Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences. The net primary productivity (NPP) was estimated by empirical coefficient, and converted it into dry matter, and then the hay yield was estimated by root-shoot ratio. The spatial resolution is 1km. The data set will provide the basis for grassland resource management, development, utilization and the formulation of the strategy of "grass for livestock".
In order to analyze how and when it entered the Qinghai Tibet Plateau and explore the relationship between its spread and domestication in the Qinghai Tibet Plateau and the plateau settlement of early human activities and the ancient Silk Exchange, in June 2018, the research team used three generations of genome sequencing technology to sequence the whole genome and de novo assembly of F1 generation of its self bred varieties in Nangqian County, Qinghai Province, and got a genome size of 40 9.69 MB, contig N50 is 1.21 MB. This result can provide genetic basis for studying the relationship between plant diffusion and human activities. At the same time, this study is helpful to reveal the influence of artificial domestication and human selection on the genetic differentiation of cyanine, and the adaptive mechanism of cyanine to adapt to the plateau ecological environment.
This dataset subsumes sustainable livestock carrying capacity in 2000, 2010, and 2018 and overgrazing rate in 1980, 1990, 2000, 2010, and 2017 at county level over Qinghai Tibet Plateau. Based on the NPP data simulated by VIP (vehicle interface process), an eco hydrological model with independent intellectual property of the institute of geographic sciences and nature resources research(IGSNRR), Chinese academy of Sciences(CAS), the grass yield data (1km resolution) is obtained. Grass yield is then calculated at county level, and corresponding sustainable livestock carring capacity is calculated according to the sustainable livestock capacity calculation standard of China(NY / T 635-2015). Overgrazing rate is calculated based on actual livestock carring capacity at county level.The dataset will provide reference for grassland restoration, management and utilization strategies.
This data is the spatial distribution map of ecological shelters in Nursultan, the capital of Kazakhstan in 2018. The types of features in the map mainly include shelter forests, roads, buildings, lakes and rivers. The data source is four sentinel images in August 2018, with a resolution of 10 meters. At the same time, overlay the vector map of OSM global features. The data set is more accurate after correction. Through visual interpretation and field investigation, the extraction of shelter forest spot has high precision. The data reflects the spatial distribution of urban ecological shelters in Nursultan, the capital of Kazakhstan. At the same time, it has an important reference value for the long-term monitoring of the spatial and temporal pattern of shelter forests.
The content of this data set is the measurements of body weight and body size (body height, body length, chest circumference, tube circumference) of 11 representative yak populations in Qinghai pastoral area at 2018. All the metadata comes from the work of body weight monitoring of yaks in Qinghai pastoral area at 2018, by the Northwest Institute of Plateau Biology, Chinese Academy of Sciences and Qinghai Academy of Animal Husbandry and Veterinary Sciences. The data set is named by “Monitoring Data Set of Body Weights of Traditional Grazing Yaks in Qinghai Pastoral Area (2018)”, consisting of 11 worksheets. The names and contents of worksheets are as follows: 1. Haiyan-Halejing (167 yaks in halejing Mongolian Town, Haiyan County, Haibei Tibetan Autonomous Prefecture); 2. Qilian-Mole (69 yaks in Mole Town, Qilian County, Haibei Tibetan Autonomous Prefecture); 3. Qilian-Yeniugou (42 yaks in Yeniugou Town, Qilian County, Haibei Tibetan Autonomous Prefecture); 4. Qilian-Yanglong (104 yaks in Yanglong Town, Qilian County, Haibei Tibetan Autonomous Prefecture); 5. Qilian-Ebao (28 yaks in Ebao Town, Qilian County, Haibei Tibetan Autonomous Prefecture); 6. Tianjun-Xinyuan (38 yaks in Xinyuan Town, Tianjun County, Haixi Mongolian and Tibetan Autonomous Prefecture); 7. Tianjun-Longmen (100 yaks in Longmen Town, Tianjun County, Haixi Mongolian and Tibetan Autonomous Prefecture); 8. Gande-Ganlong (36 yaks in Ganglong Town, Gande County, Guoluo Tibetan Autonomous Prefecture); 9. Guinan-Taxiu (70 yaks in Taxiu Town, Guinan County, Hainan Tibetan Autonomous Prefecture); 10. Henan-Kesheng (73 yaks in Kesheng Town, Henan Mongolian Autonomous Country, Huangnan Tibetan Autonomous Prefecture); 11. Ledu-Dala (50 yaks in Dala Town, Ledu District, Haidong City). This data set comprehensively evaluates the growth performance of yaks grazing in alpine meadow under the current ecological environment through the measurement of weight and body size data in the representative areas of Qinghai pastoral area. The data set can be compared with the growth characteristics of representative populations of Qinghai yaks measured in 1981 and 2008 recorded in 1983 and 2013, and the degradation index of growth performance of yaks grazing in Qinghai pastoral area can be obtained, which is helpful to assess the impact of ecological environment changes on the growth and production performance of grazing livestock.
JIA Gongxue YANG Qien Tianwei XU
This data set is the data set of ecological elements in the Qinghai Tibet Plateau from 1990 to 2015. It records the change of area proportion of wetland, grassland, forest land and sand land in 15 prefecture level units in Qinghai and Tibet every five years. The data is excel file, and the spatial resolution is the scale of prefecture level administrative unit. The data is based on the land use type data of the Qinghai Tibet Plateau, and is obtained by calculating the proportion of wetland, grassland, forest land and sand land in the area of each land unit. The data set can be used for the change analysis and research of ecological elements of the Qinghai Tibet Plateau, and can provide data support for the study of interaction stress between urbanization and ecological environment.
DU Yunyan YI Jiawei
This data set contains 2018 global forest fire case data for the whole year and 2019, including the forest fire in California in November 2018, the forest fire in Attica, Greece in July 2018, and the forest fire in Shanxi Province in March 2019. Case data. Specific data include: fire intensity data of the monitoring range and data of vegetation index changes before and after the disaster. The data set is mainly used to describe the occurrence, development, impact and recovery of major global forest fire events in the first half of 2018-2019. The data mainly comes from NASA official website and EM-DAT database, it was processed by statistical and spatial analysis methods using EXCEL and ArcGIS tools. The data source is reliable, the processing method is scientific and rigorous, and it can be effectively applied to global (forest fire) disaster case analysis research.
YANG Yuqing GONG Adu WU Jianjun ZHOU Hongmin
The data set recorded one belt, one road area, 65 countries, and 1990-2015 years' forest area. Data source: Food and Agriculture Organization, electronic files and web site. The food and Agriculture Organization of the United Nations provides detailed information on forest coverage and estimates the adjusted forest coverage. The current survey uses a unified forest definition. The data reflect one belt, one road, the rich forest resources in the countries along the border, and it is one of the important bases for determining the forest management and development and utilization policy. The dataset contains one data table: forest area (square kilometers).
To analyzing the demographic history and the genetic mechanism underlying local adaptation of the domestic Equus animals in Qinghai-Tibet Plateau and surrounding regions and building a genetic resources bank of Equus in Pan-Third Pole, we resequenced 236 domestic Equus animal samples collected until 2018, including Tibet horse, Tibet ass, domestic horses and donkeys in the plains. By applying mitochondrial DNA sequencing and D-loop sequencing on 75 samples, including 73 ass and two horses, , a batch of genetic and genome data were generated. It provides basic genetic data to analysis on domestication, immigration and expansion of domestic animals in Qinghai-Tibet Plateau. Meanwhile it helps better understand the adaption of domestic Equus animal to Qinghai-Tibet Plateau environment.
By archaeological investigation and excavation in Tibetan Plateau, we discovered 14 historic period sites, including Meinuo, Sariguo, Rongwaguo, Kaze, Jiha, Yarigei, Bami, Barongbadang, Qingtu, Labu ,Maisong Petroglyph, Gala, Yezere 1 and Yezere 4 . In this dataset, there are some basic informations about these sites, such as location, longitude, latitude, altitude, material culture and so on. On this Basis, we identified animal remains, plant macrofossil, selected some samples for radiocarbon dating and stable carbon and nitrogen isotopes. This dataset provide important basic data for understanding when and how prehistoric human lived in the Tibetan Plateau during the historic period.
DONG Guanghui HOU Guangliang
To analyzing the distribution pattern and genetic background of domain domestic animals in Qinghai-Tibet Plateau and surrounding regions and building a genetic resources bank of animals and plants in Pan-Third Pole, we collected 343 domain domestic animal samples in 2018, including Tibet pigs, Tibet dogs, Tibet sheep and Tibet chickens in Yunnan, Sichuan and Tibet Province. By applying mitochondrial DNA sequencing on 159 chickens from northwest Yunnan and southeast Tibet, genome resequencing on 11 wild and domestic pigs and GBS sequencing on 193 domestic cattle, a batch of genetic and genome data were generated. It provides basic genetic data to analysis on domestication, immigration and expansion of domestic animals in Qinghai-Tibet Plateau. Meanwhile it helps better understand the adaption of domestic animals to Qinghai-Tibet Plateau environment.
YIN Tingting PENG Minsheng
The sustainable development of husbandry industry depends on the conservation of local species, in which the protection of genetic resource is the core. The unique natural environment and long-term artificial selection shape the exclusive characteristics in endemic husbandry animals that well adapt to the local environments in Qinghai and Gansu Provinces. Currently, the introduction of commercial breeds leads to the loss of species diversity of local breeds and challenges the protection of genetic resources. In the present study, extensive field investigations are conducted to assess production performances and species resources, aiming to identify native breeds facing degradations. The achievements of the current study propose the conservative strategies for local domestic animals, which lay the foundation for purification and rejuvenation of endemic species/strains and promote the progression of husbandry industry in Qinghai-Tibetan Plateau and surrounding areas.
In the year of 2018, we collected the samples at Taxkorgan county, Kashgar district, the Xinjiang Uygur Autonomous Region, northwestern China. Taxkorgan county is where the Pamir Plateau located in China. Nearly all this county is on the plateau. The average elevation of this county is more the 4000 m above the sea level. And the lowest part of the county is 3100 m above the sea level. In total, 204 samples were collected in Pamir Plateau this time. The samples collected from several different species which including cattle, yak, sheep, goat, donkey, horse and chicken. Each samples have 3-4 repetitions. For each animal, we recorded the id number, species, sex, date of sample collection, GPS coordination and elevation. Also three mateched images, i.e. from head, hoof or feet and whole body, were took for each animal. All the samples taken from the animal are the blood samples. They were keep into the refrigerator until they were finally tranfered and stored in the germplasm recourses bank.
XU Feng WANG Muyang
Cryptosporidium spp. and E. bieneusi were tested by nested PCR on domestic animals (405 fecal samples from yaks, Tibetan sheep, camels and horses, etc.) in the areas covered by the qinghai-tibet plateau mainly in Tibet and qinghai.1. The overall infection rate of cryptosporidium was 2.96% (12/405), and the detection rate of camels, Tibetan sheep and yaks in qinghai was divided into 15%, 9.8% and 3.1%.The detection rate of yaks in yunnan was 3.1%.No other domestic animals were found in Tibet or yunnan.Two cryptosporidium subspecies were detected in qinghai camels, among which c. ovis subtype was the first detected in camels.C.ryanae subtype was first detected in yaks in yunnan.The overall detection rate of E. bieneusi in domestic animals in qinghai-tibet plateau was 19.75% (80/405), and a total of 9 known subtypes and a new subtype (YN) were detected.The highest detection rate was for camels (45%) in qinghai, followed by Mongolian sheep (42.1%), yak (37.5%), horse (15.62%) and Tibetan sheep (7.3%).The detection rate of Tibetan sheep in Tibet was 10.8%.The detection rates of goats and cattle in yunnan were 36% and 25.7% respectively.CAM2 subtype was first detected in qinghai horses and CAM1 subtype was first detected in yaks.A new subtype YN was detected in yunnan cattle.
ZHANG Zhichao DUAN Ziyuan
By archaeological investigation and excavation in Tibetan Plateau, we discovered 8 Neolithic and Bronze Age sites, including Gaomuxudi, Duojialiang, Shuikou, Qipanshan, Xinzhai, Canxionggasu, Niaodao, Bangga, Baiyangcun and so on. In this dataset, there are some basic informations about these sites, such as location, longitude, latitude, altitude, material culture and so on. On this Basis, we identified animal remains, plant macrofossil, selected some samples for radiocarbon dating and stable carbon and nitrogen isotopes. This dataset provide important basic data for understanding when and how prehistoric human lived in the Tibetan Plateau during the Neolithic and Bronze Age.
DONG Guanghui YANG Xiaoyan Lü Hongliang
By archaeological investigation and excavation in Tibetan Plateau, we discovered 8 Paleolithic sites, including 151, Jiangxigou 1, Jiangxigou 2, Heimahe 1, Xiadawu, Yezere, Niamudi and Lingjiong. In this dataset, there are some basic informations about these sites, such as location, longitude, latitude, altitude, material culture and so on. On this Basis, we identified animal remains, plant macrofossil, selected some samples for radiocarbon dating and stable carbon and nitrogen isotopes. This dataset provide important basic data for understanding when and how prehistoric human lived in the Tibetan Plateau during the Paleolithic.
ZHANG Dongju ZHANG Xiaoling LIU Xiangjun
1. The grassland animal husbandry production and management policies in the study area from 1954 to 2012 mainly include: 1) the time series of the formation and evolution of various policies; 2) the key policies related to herdsman's livestock activities and grassland management and utilization. 2. Residents' perception and response to pastoral socio-economic development policies, grassland management systems, ecological compensation policies, ecological restoration projects, and ecological environment status quo.
Taking Landsat series data as the main data source, including KH in 1965 (only including Gurinai and Guaizi Lake), MSS in 1975, TM in 1990, 1995, 2006 and 2010, and ETM in 2000. Before information extraction, remote sensing images are preprocessed by image synthesis, mosaic, fusion, geometric correction and image enhancement. In the process of correction, ETM + image in 2000 is corrected by 1:100000 topographic map and used as reference image. The 4, 3 and 2 band standard pseudocolor synthesis scheme is selected for image synthesis; during correction, 7 × 8 control points are evenly selected on each image, and the average positioning error is less than 1 pixel, that is, the ground distance is less than 30m. In other years, the datum image of 2000 is used as the reference image for image registration, so that the pixels with the same name on different images have the same geographical coordinates. After correction and registration, the whole image maintains the 30 m spatial resolution of TM. Through field correction, the accuracy of qualitative analysis can be ensured to be over 95%.