This dataset contains the monthly/yearly surface shortwave band albedo, fraction of absorbed photosynthetically active radiation (fPAR), leaf area index (LAI), vegetation continuous fields (tree cover and non-tree vegetation cover, VCF), land surface temperature (LST), net radiation (RN), evapotranspiration (ET), aboveground autotrophic respiration (RA-ag), belowground autotrophic respiration (RA-bg), gross primary production (GPP) and net primary production (NPP) in China from 2001 to 2018. The spatial resolution are 0.1 degree. Moreover, the dataset also includes these 11 ecosystem variables under climate-driven scenario (i.e., under no human disturbance). So, it can show the relative influences of climate change and human activities on land ecosystem in China during the 21st century.
Based on the average NDVI (spatial resolution 250m) of MODIS during the growing season from 2000 to 2018, the trend of NDVI was calculated by using Mann-Kendall trend detection method. Three parks of Three River Source National Park are calculated (CJYQ: Yangtze River Park; HHYYQ: Yellow River Park; LCJYQ: Lancang River Park). CJYQ_NDVI_trend_2000_2018_ok.tif: Changjiang Source Park NDVI trend. CJYQ_NDVI_trend_2000_2018_ok_significant.tif: Changjiang Source Park NDVI change trend, excluding the area that is not significant (p > 0.05). CJYYQ_gs_avg_NDVI_2000.tif: The average NDVI of the Yangtze River Source Park in 2000 growing season. Unit NDVI changes every year.
The data set includes three types of data, which are: (1) the data of soil physical and chemical indexes, carbon and nitrogen, plant carbon and nitrogen, and microbial carbon and nitrogen in the collapse area of the Qinghai Tibet Plateau in 2020. These data provide an important reference for the assessment of the carbon and nitrogen cycle in the Tibetan Plateau. This data is mainly obtained through field observation during the investigation in Gangcha, Qinghai Province in 2020. The obtained plant and soil samples were taken back to the laboratory for preliminary classification and impurity removal, and then dried to constant weight in an oven at 65 ° C. Carbon and nitrogen components in soil and plants were measured. A total of 40 quadrats of 4 typical plots were obtained. The data can be used to reveal the spatial variation of soil and plant carbon and nitrogen components, and understand the distribution of carbon and nitrogen components in soil plant microbial system. (2) Data of soil nutrient composition of grassland horizontal transect in Qinghai Tibet Plateau in 2019. This data is mainly obtained from the field drilling during the sample belt investigation in 2019. The soil samples were taken back to the laboratory for preliminary classification, root removal and stone screening. The soil samples were dried naturally, then mixed evenly and divided into two parts (about 100g each). One part was sieved with 2mm soil sieve to obtain sieved samples, and the other part was ground with ball mill to obtain ground samples. The content elements included: the contents of total C, N, P, K, Fe, Mn, Cu, Zn, CA, Na and total Mg; the contents of available P, K, Fe, Mn, Cu, Zn, CA, Na and Mg. Determination of soil total C and N: the grinding samples were packed, and then the contents of total C and N were determined by chnos elemental analyzer (vario El III, GmbH, Hanau, Germany). Determination of total elements in soil: the grinding samples were pressed by a tablet press, and then the contents of total P, K, Fe, Mn, Cu, Zn, CA, Na and total Mg in the samples were determined by X-ray fluorescence spectrometry (XRF, panalytical Axios max, Almelo, the Netherlands). Determination of soil available elements: the sieved samples were extracted, and the contents of available P, K, Fe, Mn, Cu, Zn, CA, Na and Mg were determined by inductively coupled plasma atomic emission spectrometry (ICAP 6300, Thermo Electron Corporation, Waltham, Ma, USA). A total of 13 transects were obtained. Each plot obtained three soil layers (0-10 cm, 10-20 cm, 20-30 cm). Therefore, there are 117 data of each soil nutrient element (C, N, P, Mn, Zn, etc.) in each quadrat. The data are directly obtained from the field soil samples obtained by this scientific research. After air drying, screening and grinding, the data are determined by the relevant analyzer (above) according to the corresponding test specifications, and the quality is reliable, which can be used to analyze the distribution law of soil carbon and nitrogen content or density in different regions and to evaluate soil nutrient In particular, it can be used for the research and modeling of carbon and nitrogen cycle driven by precipitation change, which has a wide range of application value and application prospects. (3) Vegetation productivity data of grassland horizontal transect in Qinghai Tibet Plateau in 2019. This data is mainly obtained from the field observation during the transect survey in 2019. After obtaining the plant samples, they were taken back to the laboratory for preliminary classification, gravel and other impurities were removed, and then dried in the oven at 65 ° C to constant weight. According to the biomass of the sample, it was converted into the key element of ecosystem carbon cycle vegetation productivity (NPP). A total of 13 transect points and 39 quadrats were obtained. The content elements of the data include aboveground biomass, aboveground biomass and NPP. The unit is gram per square meter; this data is the field observation data obtained from this scientific research, with reliable quality, which can be used to analyze the distribution law of vegetation productivity, vegetation cover, carbon storage assessment of ecosystem in different regions, especially for the study of carbon cycle driven by precipitation change and its modeling, and has a wide application value and application prospect.
Net Primary Productivity (NPP) reflects the efficiency of plant fixation and conversion of light energy as a compound. It refers to the amount of organic matter accumulated per unit time and unit area of green plants. It is the organic matter produced by plant photosynthesis. The remainder of the Gross Primary Productivity (GPP) minus Autotrophic Respiration (RA), also known as net primary productivity. As an important part of the surface carbon cycle, NPP not only directly reflects the production capacity of vegetation communities under natural environmental conditions, but also is an important component to measure regional land use/cover change. The net primary productivity data product uses the light energy utilization (GLOPEM) model algorithm to invert multiple scale raster data products obtained from various satellite remote sensing data (Landsat, MODIS, etc.), which is also the main factor for determining and regulating ecological processes.
Monthly meteorological data of Sanjiangyuan includes 32 national standard meteorological stations. There are 26 variables: average local pressure, extreme maximum local pressure, date of extreme maximum local pressure, extreme minimum local pressure, date of extreme minimum local pressure, average temperature, extreme maximum temperature, date of extreme maximum temperature, extreme minimum temperature and date of extreme minimum temperature, average temperature anomaly, average maximum temperature, average minimum temperature, sunshine hours, percentage of sunshine, average relative humidity, minimum relative humidity, date of occurrence of minimum relative humidity, precipitation, days of daily precipitation >=0.1mm, maximum daily precipitation, date of maximum daily precipitation, percentage of precipitation anomaly, average wind speed, maximum wind speed, date of maximum wind speed, maximum wind speed, wind direction of maximum wind speed, wind direction of maximum wind speed and occurrence date of maximum wind speed. The data format is txt, named by the site ID, and each file has 26 columns. The names and units of each column are explained in the SURF_CLI_CHN_MUL_MON_readme.txt file. Projection information: Albers isoconic projection Central meridian: 105 degrees First secant: 25 degrees First secant: 47 degrees West deviation of coordinates: 4000000 meters