The data set include crop leaf stomatal conductance observed at four sample regions, that is the soil moisture control experimental field at Daman county, and the super station, and Shiqiao sample plots at Wuxing village in Zhangye city. 1) Objective Crop leaf stomatal conductance, a key biophysical parameter, was observed as model parameter or a priori knowledge for crop growth model, or evapotranspiration estimation. 2) Measuring instruments Leaf porometer. 3) Measuring site a. the soil moisture control experimental field at Daman county, Twelve soil water treatments are set. The crop leaf stomatal conductance for each treatment is measured on 17, 23 and 29 May, and 3, 9, 14 and 24 June, and 5 and 12 July. b. the Super Station The crop leaf stomatal conductance at the super station is measured on 22 and 28 May, 5, 11, 18, and 25 June, and 1, 8, 15, 22 and 31 July, 9, 15 and 22 August, and 3 and 11 September. c. the Shiqiao sample site The crop leaf stomatal conductance at the Shiqiao village is measured on 17, 22 and 28 May, 4, 11, 17 and 25 June, 1, 8, 15, 22, and 30 July, 8, 16 and 27 August, and 9 September. 4) Data processing The observational data was recorded in the sheets and reorganized in the EXCEL sheets. The time used in this dataset is in UTC+8 Time.
Xu Fengying, Wang Jing, Huang Yongsheng, LI Xin, MA Mingguo
1. Overview of data This data is based on the latest googleearth remote sensing image data to establish the spatial distribution database of crops in Ganzhou District of Zhangye City. 2. Data content Based on the spatial distribution of maize seed production focused by the project, the land use types in the study area are divided into 14 types (maize seed production land, spring wheat land, vegetable land, greenhouse land, intercropping land, rice land, water area, wetland, forest land, urban and rural industrial and mining residential land, roads, railways and unused land). 3. Space-time range The data range includes 19 villages and towns including Pingshanhu, Shajing, Wujiang River, Jingan, Mingyong, Sanzha, Ganjun, Xindun, Shangqin, Jiantan, Chengguan Town, Liangjiadun, Chang 'an, Dangzhai, Xiaoman, Longqu, Daman, Huazhai and Anyang. The data type is vector polygon and stored in Shape format. The data range covers Ganzhou District.
XU Zhongmin
The field experiments of water consumption and irrigation water productivity of corn and cotton were arranged in 2012 and 2013, and the field experiments of irrigation water productivity of corn and sunflower under different mulching and cultivation methods were arranged in 2014. The characteristics of water consumption and irrigation water demand of three crops under different soil conditions, as well as the relationship between key soil properties and crop yield and irrigation water productivity were obtained.
SU Yongzhong
According to the characteristics of the selected field and its surrounding area, a trime tube is arranged in the corn field, and 5 trime tubes are arranged in a direction perpendicular to the field path. When monitoring soil moisture content in the TDR vertical direction, the unit is every 10cm. Monitor down. Location: N 38 ° 52′27.6 ″ E 100 ° 21′14.0 ″ The submitted data includes the water content of the farmland and its surrounding soil (TDR monitoring) after three irrigations in a selected farmland in Yingke Irrigation District, encrypted monitoring after irrigation, one group every 3 hours within 24 hours, and 3 groups per day for the next 5 days. -10 days are two groups per day, and 10-15 days are one group per day.
HUANG Guanhua, JIANG Yao
The data set contains agricultural economic data of all counties and regions in the Tibetan Plateau in 1980-2015, and covering the total number of households and total population in rural areas, agricultural population, rural labor force, cultivated land, paddy field area, the dry land area, power of agricultural machinery, agricultural vehicles, mechanical ploughing area, irrigation area, consumption of chemical fertilizers electricity use, gross output value of agriculture, forestry, animal husbandry and fishery, the output of cattle, pig, sheep, meat, poultry, and fish, the sown area of grain, the output of grain, cotton, oil and all kinds of crops, and characteristic agricultural products and livestock production and other relevant data.The data came from the statistical yearbook of the provinces included in the Tibetan Plateau.The data are of good quality and can be used to analyze the socio-economic and agricultural development of qinghai-tibet plateau.
LV Changhe
This study takes the land resources in the Qinghai-Tibet Plateau as the evaluation object, and clarifies the current situation in the region suitable for agriculture, forestry, animal husbandry production and the quantity, quality and distribution of the reserve land resources. Through field investigations, collect relevant data from the study area, and combine relevant literature and expert experience to determine the evaluation factors (altitude, slope, annual precipitation, accumulated temperature, sunshine hours, soil effective depth, texture, erosion, vegetation type, NDVI). The grading and standardization are carried out, and the weights of each evaluation factor are determined by principal component analysis. The weighted index and model are used to determine the total score of the evaluation unit. Finally, the ArcGis natural discontinuity classification method is used to obtain the Qingshang Plateau. And the grades of farmland, forestry and grassland suitability drawings of the Qinghai-Tibet Plateau with a resolution of 90m were given. Finally, the results are verified and analyzed.
YAO Minglei
The data includes the county-level data of characteristic agriculture distribution in the Qinghai Tibet Plateau, which lays the foundation for the spatial distribution and development of characteristic agriculture in the Qinghai Tibet Plateau. The data comes from the planning documents of each province in the Tibetan Plateau region, such as the development plan of the characteristic agricultural products base of the Tibetan Plateau (2015-2020). The data is the distribution of characteristic agriculture at the county level, including four kinds of agricultural products: highland barley, yak, sheep and wolfberry. The spatialization of main agricultural products of characteristic agriculture at the county level is realized. The time range is set to 2015-2020, referring to the planning and construction time of characteristic agriculture in each province in the data source. The data can be applied to the research on the spatial distribution of characteristic agriculture and the development of characteristic agriculture in the future.
SHI Wenjiao
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
The data set was obtained from UAV aerial photography during the field investigation of the Qinghai Tibet Plateau in August 2020. The data size is 10.1 GB, including more than 11600 aerial photos. The shooting sites mainly include Lhasa, Shannan, Shigatse and other areas along the road, residential areas and surrounding areas. The aerial photos mainly reflect the local land use / cover type, facility agriculture distribution, grassland coverage and other information. The aerial photos have longitude, latitude and altitude information, which can provide better verification information for land use / cover remote sensing interpretation, and can also be used for vegetation coverage estimation, and provide better reference information for land use research in the study area.
LV Changhe, LIU Yaqun
The Tibetan Plateau in China covers six provinces including Tibet, Qinghai, Xinjiang, Yunnan, Gansu and Sichuan, including Tibet and Qinghai, as well as parts of Xinjiang, Yunnan, Gansu and Sichuan. The research on water and soil resources matching aims to reveal the equilibrium and abundance of water resources and land resources in a certain regional scale. The higher the level of consistency between regional water resources and the allocation of cultivated land resources, the higher the matching degree, and the superior the basic conditions of agricultural production. The general agricultural water resource measurement method based on the unit area of cultivated land is used to reflect the quantitative relationship between the water supply of agricultural production in the study area and the spatial suitability of cultivated land resources. The Excel file of the data set contains the generalized agricultural soil and water resource matching coefficient data of the Tibetan Plateau municipal administrative region in China from 2008 to 2015, the vector data is the boundary data of the Tibetan Plateau municipal administrative region in China in 2004, and the raster data pixel value is the generalized agricultural soil and water resource matching coefficient of the year in the region.
DONG Qianjin, DONG Lingxiao
The data set of agricultural activity intensity of the Qinghai Tibet Plateau is based on the County-Level Agricultural statistical data, including the annual cultivated land area, agricultural, forestry, animal husbandry and fishery labor force, total power of agricultural machinery, rural power consumption, effective irrigation area, pesticide use, fertilizer use, total output of grain crops, and total output value of agricultural, forestry, animal husbandry and fishery. The agricultural input index and output index are taken as the first level indicators, and the unit cultivated land area is constructed The intensity index system of agricultural activity is composed of 10 indexes, such as total power of agricultural machinery, fertilizer application amount per unit cultivated area and labor productivity. Entropy method was used to determine the weight of each index, and the input-output index of county-level agriculture in the Qinghai Tibet Plateau was obtained by AHP. The basic data comes from the statistical data released by the National Bureau of statistics, and the original data has been approved and corrected, with high reliability. The input-output index, input-output index and input-output index of county level in the Qinghai Tibet Plateau from 1980s to 2015 included in the data set reflect the spatiotemporal variation characteristics of the intensity of agricultural production activities in the Qinghai Tibet Plateau to a certain extent, and provide data support and theoretical reference for the local agricultural development.
LIU Yujie
In order to study the relationship between the spread of cyanine and human activities, we will resequence the cyanine varieties from the Qinghai Tibet Plateau and its surrounding areas, as well as Pakistan, India, Nepal, Germany, Japan and other places. At the same time, we will cluster the gene families, and make statistics of unique, shared genes and gene families. In addition, we will also carry out the analysis of gene family expansion and contraction, and system development Tree construction, genome-wide replication events and other analysis. The aim is to analyze the molecular basis of adaptation of traditional species of cyanine to the plateau under the dual pressures of human activities and regional climate. Therefore, this study is helpful to reveal the adaptive mechanism of cyanine to adapt to the plateau ecological environment and the influence of artificial domestication and human selection on its genetic differentiation in the process of evolution.
DUAN Yuanwen
In order to explore how and when turnip was successfully domesticated the Qinghai-Tibet Plateau and what is the relationship between turnip domestication and early human settlement on the Qinghai-Tibetan Plateau and human migration along the ancient Silk Road, the whole genome De Novo sequencing of a self-bred F1 variety on Qinghai-Xizang Plateau was conducted, with the assembled genome size of 409.69 Mb,Contig N50 was 1.21 Mb in June 2018 using Pacbio sequencing. Those data will provide a genetic basis for elucidating the relationship between plant disperse and human activities. As we know, traditional turnip landrace is influenced by human domestication and nature selection. Hopefully, the study will help to understand the impacts of human selection on turnip genetic differentiation, and the adaptation mechanism of turnip in the Qinghai-Tibetan Plateau.
DUAN Yuanwen
By archaeological investigation and excavation in Tibetan Plateau and Hexi corridor, we discovered more than 40 Neolithic and Bronze Age sites, including Zongri, Sanjiaocheng, Huoshiliang, Ganggangwa, Yigediwonan, Shaguoliang, Guandi, Maolinshan, Dongjicuona, Nuomuhong, Qugong, Liding 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 fossil, selected some samples for radiocarbon dating, optically stimulated luminescence dating, stable carbon, nitrogen isotopes, polle, fungal sporen and environmental proxies. This dataset provide important basic data for understanding when and how prehistoric human lived in the Tibetan Plateau during the Neolithic and Bronze Age.
YANG Xiaoyan, Lü Hongliang, LIU Xiangjun, HOU Guangliang
The dataset recorded the output statistics of major crops in Qinghai province from 2007 to 2020, including wheat, highland barley, potato (fold grain), oil crops, wolfberry, vegetables and edible fungi, covering the period from 2007 to 2020. The dataset contains 13 data tables, which are: Crop yield (2007), crop yield (2008), crop yield (2009), crop yield (2010), crop yield (2011), crop yield (2012), crop yield (2013), crop yield (2014), crop yield (2015), Crop output (2016), crop output (2017), crop output (2018) Output of major crop products in Qinghai Province (2015-2020).xls. The data table structure is similar. For example, the crop yield (2007) data table has 4 fields: Field 1: Indicator name Field 2: Year 2006 Field 3: Year 2007 Field 4: increase or decrease
AGRICULTURAL AND RURAL Department of Qinghai Province
As the roof of the world, the water tower of Asia and the third pole of the world, the Qinghai Tibet Plateau is an important ecological security barrier for China and even Asia. With the rapid development of social economy, human activities have increased significantly, and the impact on the ecological environment is growing. In this paper, eight factors including cultivated land, construction land, National Road, provincial road, railway, expressway, GDP and population density were selected as the threat factors, and the attributes of the threat factors were determined based on the expert scoring method to evaluate the habitat quality of the Qinghai Tibet Plateau, so as to obtain six data sets of the habitat quality of the agricultural and pastoral areas of the Qinghai Tibet Plateau in 1990, 1995, 2000, 2005, 2010 and 2015. The production of habitat quality data sets will help to explore the habitat quality of the Qinghai Tibet Plateau and provide effective support for the government to formulate sustainable development policies of the Qinghai Tibet Plateau.
LIU Shiliang, LIU Yixuan, SUN Yongxiu, LI Mingqi
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
The data of farmland distribution on the Qinghai-Tibet Plateau were extracted on the basis of the land use dataset in China (2015). The dataset is mainly based on landsat 8 remote sensing images, which are generated by manual visual interpretation. The land use types mainly include the cultivated land, which is divided into two categories, including paddy land (1) and dry land (2). The spatial resolution of the data is 30m, and the time is 2015. The projection coordinate system is D_Krasovsky_1940_Albers. And the central meridian was 105°E and the two standard latitudes of the projection system were 25°N and 47°N, respectively. The data are stored in TIFF format, named “farmland distribution”, and the data volume is 4.39GB. The data were saved in compressed file format, named “30 m grid data of farmland distribution in agricultural and pastoral areas of the Qinghai-Tibet Plateau in 2015”. The data can be opened by ArcGIS, QGIS, ENVI, and ERDAS software, which can provide reference for farmland ecosystem management on the QTP.
LIU Shiliang, SUN Yongxiu, LI Mingqi
Through the bioinformatics analysis after Hi-C sequencing, most of the sequences in the preliminary assembled genome sketch can be located on the chromosome, and the sequence and direction of these sequences on the chromosome can be determined, which lays an important foundation for obtaining high-quality sequence map. Therefore, by using this technology, the research team can divide the sequence in the sketch of the genome sequence of Aralia racemosa into groups with the same chromosome number as the species, and determine the order and orientation of all sequences in each group. After that, we can combine the data of reference genome, EST sequence, related species and genetic map of Aralia racemosa The accuracy of grouping and the order and direction between sequences were evaluated.
DUAN Yuanwen
The data on the consumption and trade of agricultural products for the period 1992-2016 in the five Central Asian countries are derived from the Food and Agriculture Organization of the United Nations (FAO) food statistics database. The main elements include: crop types and yields, crop sown area, breed species and scale, animal product output, dietary structure, population, policy technology, total import and export amount and amount, etc. It can be used to support the development and utilization of agricultural water and soil resources in Central Asia, and the measurement and management of the "virtual water" and "virtual soil" resources contained in agricultural products. It provides the basic data support for the agricultural products trade complementation and agricultural cooperation decision making between China and the five Central Asian countries, and guarantees and promotes the construction of the Silk Road economic belt.
YANG Yonghui, HE Li
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