This data set records the statistical data of total wages of employees employed in all units by industry in Qinghai Province from 2010 to 2020. Data in an ecological-economic, mining, manufacturing, electricity, gas and water, construction, wholesale and retail trade, transportation, warehousing and postal service, accommodation and catering industry, information transmission, software, finance, real estate, leasing and business services, scientific research and technical services, water environment and public facilities management, residents service, repair and other services, and taught Education, health and social work, culture, sports and entertainment, public administration and social security. The data are collected from qinghai Statistical Yearbook released by Qinghai Provincial Bureau of Statistics. The dataset contains eight data tables, which are: Employees employed in All Units by Industry (2011). XLS, Employees employed in All Units by Industry (2012). XLS, Employees employed in All Units by Industry (2010-2013). XLS, Employees employed in All Units by Industry (2010-2014). Number of Employed Persons in All Units by Industry 2011-2015 XLS, Number of Employed Persons in All Units by Industry 2012-2017 XLS, Number of Employed Persons in All Units by Industry in Qinghai Province (2015-2020) XLS, Employed persons in all Units by Industry 2013-2018. XLS. The data table structure is the same. For example, the data table from 2012 to 2018 has 9 fields: Field 1: Item Field 2: Item Field 3:2012 Field 4:2013 Field 5:2014 Field 6:2015 Field 7:2016 Field 8:2017 Field 9:2018
Qinghai Provincial Bureau of Statistics
This data set records the statistical data of the number of employed persons in Qinghai Province by urban and rural areas at the end of the year, and the data is divided by industry, region, type, etc. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of three tables, which are: the number of employed persons at the end of the year 2005-2006.xls by urban and rural areas, the number of employed persons at the end of the year 2006-2007.xls by urban and rural areas, and the number of employed persons at the end of the year 2007-2008.xls by urban and rural areas. The data table structure is the same. For example, the data table from 2005 to 2006 has three fields: Field 1: Project Field 2: Town Field 3: Rural Field 4: Total
Qinghai Provincial Bureau of Statistics
This data set records the statistical data of the number of employees at the end of the year in Qinghai Province by urban and rural areas, and the data is divided by industry, region, etc. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of 8 tables, which are: number of employees at the end of the year by urban and rural areas (2003). XLS, number of employees at the end of the year by urban and rural areas (1999-2000. XLS), number of employees at the end of the year by urban and rural areas (2000-2001. XLS), number of employees at the end of the year by urban and rural areas (2001-2002. XLS), number of employees at the end of the year by urban and rural areas (2003-2004. XLS), number of employees at the end of the year by urban and rural areas (2003-2004. XLS) Number of employees 2004-2005.xls, number of employed persons by urban and rural areas 2008-2009.xls number of employed persons by urban and rural areas 2009-2010.xls. The data table structure is the same. For example, the data table in 2003 has three fields: Field 1: Total Field 2: Township Field 3: Rural
Qinghai Provincial Bureau of Statistics
The data set records the number of rural labor force in different industries in Qinghai Province from 1952 to 1998, and the data is divided by year. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains one data table, which is: the number of rural labor by industry 1952-1998.xls. The data table structure is the same. For example, there are eight fields in the data table from 1952 to 1998 Field 1: Category Field 2: 1952 Field 3: 1978 Field 4: 1990 Field 5: 1995 Field 6: 1996 Field 7: 1997 Field 8: 1998
Qinghai Provincial Bureau of Statistics
The data set records the number of rural households, population and rural employees in Qinghai Province from 1978 to 2003, and the data is divided by year. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of four tables: rural employees 1978-2001.xls, rural employees 1978-2002.xls, rural households, population and rural employees 1978-2003.xls, rural households, population and rural employees 2004.xls. The data table structure is the same. For example, there are eight fields in the data table from 1978 to 2001 Field 1: Year Region Field 2: total of rural employees Field 3: agriculture, forestry, animal husbandry and fishery Field 4: Industry Field 5: Construction Field 6: transportation, warehousing, posts and Telecommunications Field 7: Wholesale and retail trade catering industry Field 8: other non agricultural industries
Qinghai Provincial Bureau of Statistics
The data set records the population and family planning situation of Qinghai Province from 2001 to 2014, and the data is divided by year. The statistical data of Qinghai Province is published by Qinghai Provincial Bureau of statistics. The data set contains 15 data tables with the same structure. For example, the data table in 2001 has 10 fields: Field 1: Indicators Field 2: Total Field 3: Xining City Field 4: Haidong region Field 5: Haibei Prefecture Field 6: Hainan Field 7: Huang Nanzhou Field 8: Golog Field 9: Yushu prefecture Field 10: Haixi
Qinghai Provincial Bureau of Statistics
The data set records the population changes in Qinghai province from 1952 to 2019, and the data is divided by year. The data are collected from qinghai Statistical Yearbook released by Qinghai Provincial Bureau of Statistics. The dataset contains 19 data tables, all of which have the same structure. For example, the data table from 1952 to 1998 has 11 fields: Field 1: Year Field 2: Year-end population Field 3: Male Field 4: Female Field 5: Town population Field 6: Rural population Field 7: Agricultural population Field 8: Non-agricultural population Field 9: Birth rate Field 10: Population mortality rate Field 11: Natural population growth rate
Qinghai Provincial Bureau of Statistics
The data set records the total population and natural changes of Qinghai Province from 1952 to 2010, and the data are divided by year. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains 13 data tables with the same structure. For example, there are eight fields in the data table from 1952 to 1998 Field 1: year Field 2: total population Field 3: number of births Field 4: birth rate Field 5: number of deaths Field 6: mortality Field 7: natural increase Field 8: natural growth rate
Qinghai Provincial Bureau of Statistics
The data set records the statistical data of birth rate, death rate and natural growth rate (2001-2008) in different regions of China, and the data are divided by year. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains eight data tables, each of which has the same structure. For example, the data table in 2008 has five fields: Field 1: Province (city, district) Field 2: total population at the end of the year Field 3: birth rate Field 4: population mortality Field 5: natural population growth rate
Qinghai Provincial Bureau of Statistics
This data set records the statistical data of the proportion of urban population in various regions of China (2010-2018), which is divided by year. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of three data tables Proportion of urban population in different regions of China (2010-2016). Xls Proportion of urban population in different regions of China (2011-2017). Xls The proportion of urban population in all regions of China (2011-2018). XLS, the data table structure is the same. For example, the data table in 2018 has two fields: Field 1: year Field 2: Region
Qinghai Provincial Bureau of Statistics
This data set records the statistical data of the permanent population size (2007-2018) in different regions of China, and the data are divided by year. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of seven data tables with the same structure. For example, the data table from 2011 to 2018 has two fields: Field 1: year Field 2: Region
Qinghai Provincial Bureau of Statistics
The data set records the statistical data of registered unemployed persons in major years in Qinghai Province, and the data are divided by year. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set includes three data tables: the number of employees at the end of the year 1952-1998.xls, the number of employees at the end of the year 1952-1999.xls, and the number of employees at the end of the year 1952-2000.xls in the main years. The data table structure is the same. For example, the data table in 2000 has eight fields: Field 1: year Field 2: Practitioners Field 3: state owned economy Field 4: collective economy Field 5: urban private economy Field 6: urban individual economy Field 7: foreign investment economy in Hong Kong, Macao and Taiwan Field 8: other economies
Qinghai Provincial Bureau of Statistics
The data set records the statistical data of changes of registered urban unemployed in Qinghai province in major years from 1980 to 2020, and the data is divided by year. The data are collected from qinghai Statistical Yearbook released by Qinghai Provincial Bureau of Statistics. The dataset contains data tables, all of which have the same structure. For example, the 2018 table has seven fields: Field 1: Year Field 2: Total number of unemployed persons Field 3: Number of carryovers from previous year Field 4: New additions for the year Field 5: Number of unemployed persons placed for employment in the current year Field 6: Actual number of unemployed persons at the end of this year Field 7: Registered urban unemployment rate
Qinghai Provincial Bureau of Statistics
The dataset records the statistical data of permanent resident population and natural variation in Qinghai Province in major years from 1952 to 2019, and the data is divided by year. The data of 1990, 2000 and 2010 are the projections of census data of that year, and the data of other years are the projections of sample survey on population change. The data are collected from qinghai Statistical Yearbook released by Qinghai Provincial Bureau of Statistics. The dataset contains 9 data tables, which are: XLS, Permanent Population and Natural Fluctuation in Main Years 1952-2011. XLS, Permanent Population and Natural Fluctuation in Main Years 1952-2012. XLS, Permanent Population and Natural Fluctuation in Main Years 1952-2013 XLS. Permanent Population and Natural Fluctuations in Major Years 1952-2014. XLS, Permanent Population and Natural Fluctuations in Major Years 1952-2016. XLS, Permanent Population and Natural Fluctuations in Major Years 1952-2016. XLS, Permanent Population and Natural Fluctuations in Major Years 1952-2016. XLS, Permanent Population and Natural Fluctuations in Major Years 1952-2016. XLS, Permanent Population and Natural Fluctuations in Major Years 1952-2016. XLS, Permanent Population and Natural fluctuations in Major Years 1952-2016. XLS, Permanent Population and Natural fluctuations in Major Years 1952-2017.xls, Permanent population and natural variation in major years 1952-2018. XLS, data table structure is the same. For example, the 2006 table has 5 fields: Field 1: Year Field 2: Resident population Field 3: Birth Field 4: Death Field 5: Natural growth
Qinghai Provincial Bureau of Statistics
The data set records the statistical data of population change in different regions of Qinghai Province from 1998 to 2010, which is divided by region, total number of households, total population, birth population and death population. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains 10 data tables with different structures. For example, the data table in 1999 has five fields: Field 1: Region Field 2: total number of households Field 3: total population Field 4: birth population Field 5: death population
Qinghai Provincial Bureau of Statistics
The data set records the statistics and statistics of registered residence population in Qinghai Province in 2003-2018 years. The data are divided into regions, total population, total population, population changes, births, deaths, immigration and relocation. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains 19 data tables with different structures. For example, the data table in 2002 has seven fields: Field 1: ground difference Field 2: number of households Field 3: population Field 4: Total Field 5: household Field 6: collective account Field 7: average family size
Qinghai Provincial Bureau of Statistics
This data records the statistical data of the number of employees in different regions and industries of Qinghai Province at the end of 2006-2008. The data are divided according to the project, the total of the whole province, Xining City, Haidong region, Haibei Prefecture, Huangnan Prefecture, Hainan prefecture, Guoluo Prefecture, Yushu prefecture and Haixi Prefecture. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains six data tables with different structures. For example, there are 18 fields in the data table from 1978 to 2002 Field 1: Year Region Field 2: Total Field 3: agriculture, forestry, animal husbandry and fishery Field 4: extractive industries Field 5: manufacturing Field 6: production and supply of electricity, gas and water Field 7: Construction Field 8: geological exploration and water conservancy management Field 9: transportation, warehousing, posts and Telecommunications 10: Wholesale and retail Field 11: finance, insurance Field 12: Real Estate Field 13: social services Field 14: health, sports and social welfare Field 15: education, culture and arts, radio, film and television Field 16: scientific research and integrated technical services Field 17: state organs, political party organs and social organizations Field 18: other
Qinghai Provincial Bureau of Statistics
This data records the statistical data of female employees in different types of registration and sub industries in Qinghai Province from 2001 to 2008. The data are divided by project, total, state-owned units, urban collective units and other units. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains eight data tables with the same structure. For example, the data table in 2008 has six fields: Field 1: Project Field 2: item Field 3: Total Field 4: state owned Units Field 5: urban collective units Field 6: other units
Qinghai Provincial Bureau of Statistics
This data records the statistical data of the number of employees at the end of 2001-2008 in Qinghai Province by registration type and sub industry. The data is divided by project, total, state-owned units, urban collective units and other units. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains eight data tables with the same structure. For example, the data table in 2006 has five fields: Field 1: Project Field 2: Total Field 3: state owned Units Field 4: urban collective unit Field 5: other units
Qinghai Provincial Bureau of Statistics
"The data records statistics on the number of non-private employment in Qinghai province by type of registration and industry at the end of the year from 2011 to 2020. The data are grouped by enterprises, institutions and organs, and by industry of the national economy. The data are collected from qinghai Statistical Yearbook released by Qinghai Provincial Bureau of Statistics. The dataset contains 10 data tables with the same structure. For example, the 2018 table has six fields: Field 1: Item Field 2: Item Field 3: Total Field 4: State-owned units Field 5: Town collective units Field 6: Other units
Qinghai Provincial Bureau of Statistics
This data records the statistical data of the number of employees of urban units in Qinghai Province at the end of 2009-2018, which are divided by project, total, state-owned units, urban collective units and other units. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. There are 12 data tables in the dataset, and the structure of each year's data table is the same. For example, the data table in 2018 has six fields: Field 1: Project Field 2: item Field 3: Total Field 4: state owned Units Field 5: urban collective units Field 6: other units
Qinghai Provincial Bureau of Statistics
The data set records the main data of the fifth population census of Qinghai Province from 2000 to 2009. The data city is divided by region, population aged 6 and above, number of people with various education levels and average years of education. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains 25 data tables with different structures. For example, the data table in 2009 has nine fields: Field 1: Region Field 2: Region Field 3: population aged 6 and above Field 4: number of people with different education levels Field 5: junior college or above Field 6: high school and technical secondary school Field 7: Junior High School Field 8: Primary School Field 9: average years of Education
Qinghai Provincial Bureau of Statistics
The data set records the main data of the sixth national census of Qinghai Province in 2010. The data are divided by province (city, district), permanent population, quantity, gender and proportion. The data set contains 20 data tables, which are: the main data of the sixth national census in 2010.xls, the permanent population aged 6 and above by region, gender and education level in the sixth census in 2011.xls, the permanent population aged 6 and above by age, gender and education level in the sixth census in 2011.xls, and the permanent population aged 6 and above by region, age and gender in the sixth census in 2011.xls In the sixth census, the population aged 15 and above was illiterate in 2011.xls; in the sixth census, the population aged 15 and above was illiterate in 2011.xls; in the sixth census, the population aged 15 and above was illiterate in 2010.xls; in the sixth census, the population aged 15 and above and the sex ratio were illiterate in 2010.xls; in the sixth census, the population aged 15 and above was illiterate in 2010.xls Population with education level 2010.xls, the number and size of households by region and collective households in the sixth population census 2010.xls, the size of households by Region in the sixth population census 2011.xls, the category of households by Region in the sixth population census 2011.xls, the number of rooms and area of households by Region in the sixth population census 2011.xls, and the ethnic composition by Region in the sixth population census 2010.xls The main data of the sixth population census in Qinghai Province are as follows: the age composition of the sixth population census by Region 2010.xls, the population density of the sixth population census by Region 2010.xls, the age composition and dependency ratio of the sixth population census by Region 2011.xls, the age and gender permanent population of the sixth population census 2011.xls, the urbanization rate of the sixth population census by Region 2010.xls Report.docx. The data table structure is different. For example, the data table in 2010 has nine fields: Field 1: Province (city, district) Field 2: Region Field 3: resident population Field 4: quantity Field 5: Rank Field 6: Male Field 7: specific gravity Field 8: Female Field 9: sex ratio
Qinghai Provincial Bureau of Statistics
DNA was extracted from teeth or phalanx. Firstly, we conducted 2 hours UVirradiation on the samples, and removed a layer of surface using a sterile dentistry trill, then again irradiated with 1 hour UV-light on the samples. We drilled out ~80 mg of bone powder for every sample with the sterile dentistry trill, and only do 2 samples at one time (include following procedures until performing sequencing; samples from different archaeological sites were never handled together) to avoid potential individual cross-contamination. Using the 80 mg bone powder, we performed DNA extraction following the silica suspension protocol from an early report (Rohland and Hofreiter 2007), which was modified afterwards (Allentoft, et al. 2015) for customizing recovering of more shorter DNA fragments, that finally resulting a total of 100 μl aliquots for each sample. In brief, the bone powder was digested over night with proteinase K in 0.5M EDTA plus 10% N-Laurylsarcosyl suspension, then the released DNA was absorbed in solution which includes PB buffer, 5M sodium acetate, 5M sodium chloride and SiO2 suspension, and followed by three times of purification using 80% ethyl alcohol. Finally, after airing, the DNA was eluted with 100 μl EB buffer. Next, to perform preliminary aDNA preservation situation screening, using 20μl DNA aliquots of each sample, we built the double strand library (DSL) with no Uracil- DNA-Glycosylase (UDG) treatment under a single indexing with commercial kit (cat no: E7370) from New England Biolabs (Ipswich, MA) following the manufacturer’s guidelines, as previously reported (Meyer and Kircher 2010) that includes end prep, adaptor ligation, purification, PCR amplification and size selection steps. PCRs were conducted in a final volume of 50 μl using AmpliTaq Gold 360 DNA Polymerase (AmpliTaq Gold, Life Technologies Applied Biosystems) which is able to well amplify across uracils, preserve the DNA damage pattern that induced by deamination, which indicating of authentic aDNA (Krause, et al. 2010). We performed all the sequencing (also the following captured library sequencing) on the Illumina HiSeq X Ten (PE-150) platform ( https://www.illumina.com.cn/systems/sequencing-platforms/hiseq-x.html ). The calculated appraise indexes of aDNA quality and preservation are shown in Table S1. Lastly, we rebuilt the DSLs with 3 hours UDG treatment using the remaining DNA extraction aliquots, which could largely remove uracil residues from DNA fragmental end to leave abasic sites, and cuts the DNA at the 5´ and 3´ sides of the abasic sites with enzyme endonuclease VIII (Endo VIII). For these libraries, we performed the mtDNA capture using myBaits® Mito-Target Capture Kits as previous report (Enk, et al. 2014). Briefly, we used the biotinylated RNA “baits” that are transcribed from the human genomic DNA to perform the capture in solution overnight at 65°C, then mixed in streptavidin-coated magnetic beads and sequestered the targets with a magnetic stand. The PCRs for both pre-capture and post-capture are performed using KAPA HiFi Hot start Polymerase (KAPA BIOSYSTEMS).
QI Xuebin
Hanging coffin burial is a kind of burial custom in which the coffin is placed on the cliff, cave and crevice. Hanging coffin burials are widely distributed in the Yangtze River Valley and the south of China, as well as in Southeast Asia and even the Pacific Islands. With the natural weathering and man-made destruction, there are fewer and fewer such relics. As a kind of peculiar and ancient archaeological cultural remains and funeral custom, hanging coffin culture has been widely concerned by archaeologists. Dating method: the wood samples on the hanging coffin were sent to beta analytical testing laboratory in Miami, USA for C14 determination. Methods: 4 in house NEC accelerator mass spectrometers (AMS) and 4 thermo IRMSS under strict chain of custom and quality control using ISO / IEC 17025:2005 testing accreditation pjla accreditation protocols Results: the dating results show that the earliest hanging coffin burial site is located in Wuyishan area of Fujian Province, 3600 years ago, which is equivalent to the Shang and Zhou dynasties in China. Wuyishan area in Fujian Province is considered to be the birthplace of the hanging coffin burial custom, which later spread to other areas in South China, Southeast Asia and the Pacific Islands. Located in the Jinsha River Valley of South Sichuan and Northeast Yunnan, the hanging coffin burial is the latest cultural remains of hanging coffin burial in mainland China (late Ming Dynasty), and also the West pole of the distribution of hanging coffin burial sites in China. There is a hanging coffin group in the mountainous area of Northwest Thailand, 2100-1200 years ago.
QI Xuebin
The complete mitochondrial DNA sequences of 41 human remains from 13 hanging coffin sites 2500-660 years ago in Weixin and Yanjin, Zhaotong, Yunnan, Huacun, Baise, Guangxi and bangmapa, Thailand were analyzed by using the ancient DNA analysis technique. They found that the maternal genetic diversity of the hanging coffin people in Northwest Yunnan was very high, while the genetic diversity of the hanging coffin people in northern Thailand was relatively low. This result is consistent with the view that the hanging coffin burial custom originated in southern China and spread southward to Southeast Asia. In addition, a small number of matrilineal lineages were shared among the hanging coffin people in different regions of Asia, indicating that there is a very close relationship between different hanging coffin people. Combining the results of genetic analysis with the evidences of archaeology, physical anthropology, folklore and history, they speculated that the hanging coffin burial custom originated in the Baiyue ethnic group in the southeast coastal areas of China (such as Wuyishan area) about 3600 years ago, and they are the ancestors of the Dai ethnic group with many ethnic groups. After that, the custom of hanging coffin was widely spread in South China by means of people migration and flow. However, about 2000 years ago (the earliest time of hanging coffin burial in Thailand), a very small number of inheritors of hanging coffin burial spread the custom to some aboriginal groups in Southeast Asia, such as northern Thailand, by means of cultural diffusion. This study only makes a preliminary discussion from the perspective of maternal genetic lineage. For the hanging coffin culture which has spread for more than 3000 years in South China, Southeast Asia and the vast area of the Pacific Islands, the origin and development of its culture and the history of its inheritors may be more complex. In the future, more representative samples of human remains buried in a hanging coffin will be used, from the perspective of genomic DNA and paternal Y-DNA, combined with interdisciplinary research, which will provide more systematic evidence support for a more comprehensive display of the historical and cultural features of the hanging coffin burial custom.
QI Xuebin
1) Data content: this data is the chromatin open group data of umbilical cord endothelial cells of Plateau Tibetan and plain Han people generated during the implementation of the project, including 5 cases of Plateau Tibetan umbilical cord endothelial cell chromatin open group data and 5 cases of plain Han umbilical cord endothelial cell chromatin open group data. The amount of chromatin open group data of each cell is > 15g sequencing depth, which can be used to study the high-risk factors The chromatin opening pattern and gene expression regulation pattern of the original Tibetan population and the plain Han population in high altitude hypoxia environment. 2) Data sources and processing methods: Based on our own data, we used the 150 BP pair end sequencing method of Illumina x-ten. 3) Data quality: > 15g data volume, q30 > 90%. 4) Data application achievements and prospects: the data are used to verify the open mode of cell chromatin and gene expression change mode of high altitude hypoxia adaptation genes under hypoxia environment.
QI Xuebin
The data set is mainly included the population, arable land and animal husbandry data of Qinghai Province and Tibet Autonomous Region in the past 100 years. The data mainly comes from historical documents and modern statistics. The data quality is more reliable. It mainly provides arguments for the majority of researchers in the development of agriculture and animal husbandry on the Qinghai-Tibet Plateau.
LIU Fenggui
This data set includes the urban distribution, urban population and built-up areas of the Qinghai Tibet Plateau from 2000 to 2015. The urban distribution data is the county-level vector boundary in 2015, and the urban population and built-up area data years are 2000, 2005, 2010 and 2015. Among them, the data of urban distribution and built-up areas are from the research team of Kuang Wenhui, Professor of Institute of geography and resources, Chinese Academy of Sciences, and the data of urban population are from the census data of each year, the statistical yearbook of each province in the Qinghai Tibet Plateau, etc. The data quality is excellent, which can be used to analyze the population growth trend, urban expansion and the impact of human activities on the surrounding environment of cities and towns in the Qinghai Tibet Plateau.
KUANG Wenhui
The data includes the gender, age, social security, education level, labor force and employment status of household members in 1280 families at domestic and abroad, which is used to support the analysis of human capital and livelihood Strategy in sustainable livelihoods. The field survey data is collected by the research group. Before collecting the data, the research group and the invited experts conducted a pretest to improve the questionnaire; before the formal survey, the members participating in the data collection were strictly trained; during the formal survey, each questionnaire could be filed after three times of inspection. The data is of great value to understand the human capital, livelihood strategies and demographic characteristics of farmers in the vulnerable areas of environment and economy, and is an important supplement to the national and macro data in this area.
Linxiu ZHANG, BAI Yunli
The whole mitochondrial genomes of 68 Tibetan samples were sequenced by high-throughput second-generation sequencing. The average depth of sequencing was 1000 ×, ensuring that the mitochondrial genome of each sample was completely covered (100%). Based on the phylogenetic analysis, we control the quality of these data to ensure that there is no sample pollution and other quality problems. According to the phylogenetic tree, each individual was allocated into haplogroups. The results showed that in Lhasa Tibetan population, M9a1c1b1a was the highest (19.12%), followed by G2 (13.23%), M13a (11.76%), C4a (7.35%), D4 (7.35%), A11a1a (5.88%), M9a1b (5.88%), and F1c, F1g, B4, F1d, M62b, F1a, F1b, G1, M11, M8a, U7a, Z3a. These haplogroups have different originations, including Paleolithic components (M13a, M62b, M9a1b, etc.), northern China millet farmers’ components (M9a1c1b1a and A11a1a), components distributed mainly in southern East Asia (F1a, etc.), northern East Asian haplogroups (C4a, D4, etc.). It is worth noting that the maternal component of Lhasa Tibetans is mainly composed of millet agricultural population in northern China, indicating the important impact of genetic input of millet agricultural population in northern China on the genetic structure of the population in this area. Taken together, the maternal genetic structure of Lhasa Tibetan population exhibits time stratification, which may represent the genetic imprint of different population entering the region in different periods.
KONG Qingpeng
The Grassland Degradation Assessment Dataset in agricultural and pastoral areas of the Qinghai-Tibet Plateau (QTP) is a data set based on the 500m Global Land Degradation Assessment Data (2015), which is evaluated according to the degree of grassland degradation or improvement. In this dataset, the grassland degradation of the QTP was divided into two evaluation systems. At the first level, the grassland degradation assessment was divided into 3 types, including no change type, improvement type and degradation type. At the second level, the grassland degradation assessment on the QTP was divided into 9 types, among which the type with no change was class 1, represented by 0. There were 4 types of improvement: slight improvement (3), relatively significant improvement (6), significant improvement (9) and extremely significant improvement (12). The degradation types can be divided into 4 categories: slight degradation (-3), relatively obvious degradation (-6), obvious degradation (-9) and extremely obvious degradation (-12). This dataset covers all grassland areas on the QTP with a spatial resolution of 500m and a time of 2015. The projection coordinate system is D_Krasovsky_1940_Albers. The data are stored in TIFF format, named “grassdegrad”, and the data volume is 94.76 MB. The data were saved in compressed file format, named “500 m grid data of grassland degradation assessment in agricultural and pastoral areas of the Qinghai-Tibet Plateau in 2015”. The file volume is 2.54 MB. The data can be opened by ArcGIS, QGIS, ENVI, and ERDAS software, which can provide reference for grassland ecosystem management and restoration on the QTP.
LIU Shiliang, SUN Yongxiu, LIU Yixuan
It is not clear how the Tibetan people adapt to the extreme environment on the plateau. As an important phenotype, metabolism plays an important role in maintaining the normal biological function of individuals. Previous studies have shown that some small metabolic molecules can adapt to the extreme environment by regulating energy metabolism, oxidative stress and other biological processes. In view of this, the project is expected to find the relationship between human metabolism and extreme environmental adaptation by studying the unique metabolic characteristics of Tibetan people compared with plain people, and then study the plateau adaptation mechanism of Tibetan people from the perspective of metabolism. This data is the metabolomic data generated during the implementation of the project, and the current data includes the metabolomic data of 30 people in the plain. The combined analysis of these data and the subsequent metabolomic data can be used to study the metabolic characteristics of Tibetan people in the plateau hypoxia environment. This data set is the update and continuation of metabolomic data v1.0 of modern Chinese population.
LI Gonghua
As the “third pole” of the world, the Qinghai-Tibet Plateau (QTP) is extremely ecologically sensitive and fragile while facing increasing human activities and overgrazing. In this study, eight types of spatial data were firstly selected, including grazing intensity, Night-Time Light, population density, Gross Domestic Product (GDP) density, the ratio of cultivated land, the slope of the Normalized Difference Vegetation Index (NDVI), distance to road, and distance to town. Then, the entropy weight method was applied to determine the weight of each factor. Finally, the five-year interval human activity intensity data in 1990, 1995, 2000, 2005, 2010 and 2015 were made in the agricultural and pastoral areas of QTP through the spatial overlap method. By preparing the historical spatial datasets of human activity intensity, our study will help to explore the influence of human disturbance on the alpine ecosystems on the QTP and provide effective support for decision-making of government aiming at regional ecosystem management and sustainable development.
LIU Shiliang, SUN Yongxiu, LIU Yixuan, LI Mingqi
The natural resources dataset of the Qinghai-Tibetan Plateau covers 215 counties in this area. The observation intervals are 5 years from 2000-2015. The indicators are rainfall, temperature, humidity, population, and land area. The data sources are meteorological station data, regional statistical yearbook, etc., which are expressed by Excel. This data provides a reference for understanding the natural background conditions on the county scale in the Qinghai Tibet Plateau.
FENG Xiaoming
The natural resources dataset of the Qinghai-Tibetan Plateau covers 215 counties in this area. The observation intervals are 5 years from 2000-2015. The indicators are rainfall, temperature, humidity, population, and land area. The data sources are meteorological station data, regional statistical yearbook, etc., which are expressed by Excel. This data provides a reference for understanding the natural background conditions on the county scale in the Qinghai Tibet Plateau.
FENG Xiaoming
This data set records the division of Qinghai Province from 2000 to 208 according to urban and rural areas, as well as economic types and quantitative statistics. The data are collected from the statistical yearbook: Qinghai statistical yearbook, and the accuracy is the same as the statistical yearbook extracted from the data. The data set contains three data tables, which are 2005-2006, 2006-2007 and 2007-2008 year-end employment statistics by urban and rural areas. The data table structure is the same. Each data table has five fields, such as the number of employed persons at the end of the year by urban and rural areas in 2005-2006: Field 1: towns in 2005 Field 2: 2005 rural Field 3: towns in 2006 Field 4: villages in 2006 Field 5: 2005 total Field 6: 2006 total
ZHAO Hu
This data is the population grid data of ten meter scale in 2019. Each grid expresses the total number of population within this range (unit: person). The source data of this data comes from Myanmar's 2019 1km population data set in the world pop data center（ https://www.worldpop.org/geodata/summary?id=40443 ）, the obtained source data are processed by projection transformation and clipping to obtain the population distribution in Yangon, and then the data are downscaled, The spatial distribution data set of refined population (10m) in Yangon deep water port area is obtained. Regular ten meter scale population grid data are obtained by spatial scale conversion and downscaling. Each grid population is calculated by random forest method according to the population of each administrative unit and multi-source auxiliary data. Population data can be used in many fields, including urban planning, elections, risk assessment, disaster relief, disease prevention and control, poverty reduction and poverty alleviation, etc;
GE Yong, LI Qiangzi, LI Yi
The population grid data of 100 meter scale in 2010, each grid expresses the total number of population within the range (unit: person). The data is from the Institute of earth data, University of Southampton, UK. The data is processed by projection transformation and clipping to get the population distribution in Yangon area. Then the data is downscaled to get the refined population spatial distribution data set in Yangon deepwater port area. This data is based on the census data of administrative units, and the regular 100 meter scale population grid data is obtained through spatial scale conversion. Each grid population is calculated by using random forest method according to the population of each administrative unit and multi-source auxiliary data. Population data can be used in many fields, including urban planning, elections, risk assessment, disaster relief, disease prevention and control, poverty alleviation and so on;
GE Yong, LI Qiangzi, LI Yi
The refined population spatial distribution data set of Hambantota port area is generated by reanalysis based on hrsl data of Sri Lanka. Hrsl data provides an estimate of the population distribution in 2015 at a resolution of 1 arcsec (about 30 meters). The latest census information and built-up area information based on satellite images are used in hrsl data. This data set is based on hrsl data. Firstly, the boundary of buildings is extracted from the 0.5m resolution remote sensing image by computer vision technology, and the building types (high-rise buildings, medium and low rise buildings, bungalows, etc.) are determined by combining with manual visual interpretation and field sampling. The population distribution area mask is constructed in the building area, and the 10 meter grid is used as the analysis unit to calculate the population distribution in the unit According to the proportion of different building types, the proportion of main land use types, building density, distance from road and other related indicators, the average density of building type consistent area is calculated from hrsl data, and the corresponding population density of each building is obtained by machine learning method. Then, the population data in the area is allocated to the corresponding unit by proportional allocation method, and the 10 meter resolution is obtained Population distribution products. The data is distributed in the form of GeoTIFF files. Population GeoTIFF represents population estimates (in person) and provides detailed estimates for population, infrastructure and Sustainability Studies in the humanitarian field.
The data set of socio-economic vulnerability parameters in the agricultural and pastoral areas of the Qinghai Tibet Plateau mainly contains the socio-economic vulnerability parameter data at county level. The data time range is from 2000 to 2015, involving 112 counties and districts in Qinghai Province and Tibet Autonomous Region. The main parameters include population density, the proportion of unit employees in the total population, the proportion of rural employees in the total population, the proportion of agricultural, forestry, animal husbandry and fishery employees in rural employees, per capita GDP, per capita savings balance of residents, per capita cultivated land area, per capita grain output, and people Average oil production, livestock stock per unit area, per capita meat production, the proportion of primary and secondary school students in the total population, and the number of hospital beds per 10000 people. The entropy weight method is used to calculate the weight of each index, and ArcGIS is used to spatialize, and finally the county scale socio-economic vulnerability parameter data is obtained. The original data is from the statistical yearbook of Qinghai Province and Tibet Autonomous Region. The data are expressed by shape file and excel file. This data set will provide reference for socio-economic vulnerability assessment and selection of typical agricultural and pastoral areas.
ZHAN Jinyan, TENG Yanmin, LIU Shiliang
This data is the distribution data of the prehistoric era sites on the Qinghai-Tibet Plateau and surrounding areas, which is derived from the Supplementary Maps of the paper: Chen, F.H., Dong, G.H., Zhang, D.J., Liu, X.Y., Jia, X., An, C.B., Ma, M.M., Xie, Y.W., Barton, L., Ren, X.Y., Zhao, Z.J., & Wu, X.H. (2015). Agriculture facilitated permanent human occupation of the Tibetan Plateau after 3600 BP. SCIENCE, 347, 248-250. The Qinghai-Tibet Plateau, with an average altitude of more than 4000m, is the highestand largest plateau all around the world, and also is one of the most unsuitable areas for human life with long-term on the earth. The remains at the archaeological site are direct evidences left behind the ancient human activities. The original data of this data is digitized from the results of the Qinghai-Tibet Plateau high-textual census and archaeological survey (Qinghai Volume and Tibet Volume of the Chinese Cultural Relics Atlas). The map was digitized mainly based on the distribution maps of the sites, and the latitude and longitude coordinates and altitude were obtained. a total of 6,950 sites, most of which are distributed in the northern part of the plateau. The age range of the site is between 7000BP and 2300BP. This data set is of reference value for the research on the process and power of human diffusion to the Tibetan Plateau in the prehistoric era and other studies related to human activities in the Tibetan Plateau and the prehistoric era.
DONG Guanghui , LIU Fengwen
This data set includes a monthly composite of 30 m × 30 m surface vegetation coverage products in the Qilian Mountain Area in 2019. In this paper, the maximum value composition (MVC) method is used to synthesize monthly NDVI products and calculate FVC by using the reflectance data of Landsat 8 and sentinel 2 red and near infrared channels. The data is monthly synthesized by Google Earth engine cloud platform, and the index is calculated by the model. The missing pixels are interpolated with good quality, which can be used in environmental change monitoring and other fields.
QI Xuebin
The data includes the runoff components of the main stream and four tributaries in the source area of the Yellow River. In 2014-2016, spring, summer and winter, based on the measurement of radon and tritium isotopic contents of river water samples from several permafrost regions in the source area of the Yellow River, and according to the mass conservation model and isotope balance model of river water flow, the runoff component analysis of river flow was carried out, and the proportion of groundwater supply and underground ice melt water in river runoff was preliminarily divided. The quality of the data calculated by the model is good, and the relative error is less than 20%. The data can provide help for the parameter calibration of future hydrological model and the simulation of hydrological runoff process.
QI Xuebin
1) Data content: this data is the placenta umbilical cord endothelial cells (HUVEC) transcriptome data of high altitude Tibetan and lowland Han population generated during the implementation of the project, including the RNA-seq data of 3 high altitude Tibetan HUVEC and 3 lowland Han placenta HUVEC. Each RNA-seq data is 6G sequencing depth, which can be used to study the effect of high altitude Tibetan population and lowland Han population for gene expression patterns at hypoxic environment. 2) Data source and processing method: own data, the pair end 150bp sequencing method using Illumina x-ten sequencing platform. 3) Data quality: 6G data depth, q30 > 90%. 4) Results and prospects of data application: the data will be used to validate the gene expression pattern of high altitude hypoxia adaptation gene to hypoxia environment at the cell level.
QI Xuebin
The average altitude of the Tibetan Plateau is more than 4000 meters. The harsh environment such as high cold and low oxygen poses a huge challenge to human survival. However, since the late Paleolithic period, Tibetan people in the plateau have reached the Plateau, and in the Neolithic period, people began to permanently settled on the high-altitude areas on a large scale. The history of population migration in this process has become the focus of different fields. In order to analyze the genetic structure of Tibetan population from the perspective of the whole genome and trace back the history of human settlement on the plateau, we obtained the whole genome variation data of 20 Tibetan individuals. The SNP typing of 20 samples was carried out by DNA array method, and about 700000 loci (including nuclear genome, mitochondrial DNA and Y chromosome) of each sample were obtained. Based on the above data, relevant biological information analysis (mainly including chip site quality control analysis, Y chromosome and mitochondrial DNA haplotype analysis) was carried out. This data is helpful to analyze the genetic structure of Tibetan population from the perspective of nuclear genome, Y chromosome and mitochondrial DNA. By comparing with the data of people around the plateau, we can trace the migration and settlement history of the plateau population comprehensively.
KONG Qingpeng
How the Tibetan people adapt to the extreme environment of the plateau is not clear at present. Metabolism, as an important phenotype, plays an important role in maintaining the normal biological function of individuals. Previous studies have shown that some small metabolic molecules can adapt to the extreme environment by regulating the biological processes such as energy metabolism and oxidative stress. In view of this, this project is to find the relationship between the human metabolism and the extreme environmental adaptation by studying the unique metabolic characteristics of Tibetan population compared with the plain population, and then study the plateau adaptation mechanism of Tibetan population from the perspective of metabolism. This data is the metabolome data generated during the implementation of this project. The current data includes the metabolome data of 30 people in the plain. The combined analysis of this data and the subsequent metabolome data can be used to study the metabolism characteristics of the Tibetan people at high altitude in the low oxygen environment.
LI Gonghua
Gridded population with 100m spaital resolution of the 34 key areas along One Belt One Road in 2010, which indicates that the population count (Unit: person) per pixel (i.e., grid). This data is derived from geodata institute of Southampton University, UK. The prejection transform and extraction processes were done to generate the gridded population with 100m spaital resolution of the 8 key areas along One Belt One Road in 2010. The original gridded popution is spatially downscaled from census data and multisource data by the random forest method. Accurate population data at finer scale are fundamental for a broad range of applications by governments, nongovernmental organizations, and companies, including the urban planing, election, risk estimation, disaster rescue, disease control, and poverty reduction.
GE Yong, LI Qiangzi, DONG Wen
"Total population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship. The values shown are midyear estimates.This dataset includes demographic data of 22 countries from 1960 to 2018, including Sri Lanka, Bangladesh, Pakistan, India, Maldives, etc. Data fields include: country, year, population ratio, male ratio, female ratio, population density (km). Source: ( 1 ) United Nations Population Division. World Population Prospects: 2019 Revision. ( 2 ) Census reports and other statistical publications from national statistical offices, ( 3 ) Eurostat: Demographic Statistics, ( 4 ) United Nations Statistical Division. Population and Vital Statistics Reprot ( various years ), ( 5 ) U.S. Census Bureau: International Database, and ( 6 ) Secretariat of the Pacific Community: Statistics and Demography Programme. Periodicity: Annual Statistical Concept and Methodology: Population estimates are usually based on national population censuses. Estimates for the years before and after the census are interpolations or extrapolations based on demographic models. Errors and undercounting occur even in high-income countries. In developing countries errors may be substantial because of limits in the transport, communications, and other resources required to conduct and analyze a full census. The quality and reliability of official demographic data are also affected by public trust in the government, government commitment to full and accurate enumeration, confidentiality and protection against misuse of census data, and census agencies' independence from political influence. Moreover, comparability of population indicators is limited by differences in the concepts, definitions, collection procedures, and estimation methods used by national statistical agencies and other organizations that collect the data. The currentness of a census and the availability of complementary data from surveys or registration systems are objective ways to judge demographic data quality. Some European countries' registration systems offer complete information on population in the absence of a census. The United Nations Statistics Division monitors the completeness of vital registration systems. Some developing countries have made progress over the last 60 years, but others still have deficiencies in civil registration systems. International migration is the only other factor besides birth and death rates that directly determines a country's population growth. Estimating migration is difficult. At any time many people are located outside their home country as tourists, workers, or refugees or for other reasons. Standards for the duration and purpose of international moves that qualify as migration vary, and estimates require information on flows into and out of countries that is difficult to collect. Population projections, starting from a base year are projected forward using assumptions of mortality, fertility, and migration by age and sex through 2050, based on the UN Population Division's World Population Prospects database medium variant."
DONG Wen
"One belt, one road" along the lines of risk rating, credit risk rating and Moodie's national sovereignty rating reflects the structure of sovereign risk in every country. The rating of Moodie's national sovereignty is from the highest Aaa to the lowest C level, and there are twenty-one levels. Data source: organized by the author. Data quality is good. The rating level is divided into two parts, including investment level and speculation level. AAA level is the highest, which is the sovereign rating of excellent level. It means the highest credit quality and the lowest credit risk. The interest payment has sufficient guarantee and the principal is safe. The factors that guarantee the repayment of principal and interest are predictable even if they change. The distribution position is stable. C is the lowest rating, indicating that it cannot be used for real investment.
SONG Tao
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