This repository contains the dataset used for “Rising CO2 and warming reduce global canopy demand for nitrogen” The deposition consists of: An satellite-derived leaf chlorophyll vcmax25 database (Luo et al., 2019) Simulated Vcmax with all the factors based on the coordination hypothesis Simulated Vcmax with CO2 fixed at 340 ppm based on the coordination hypothesis Simulated Vcmax with fixed climate based on the coordination hypothesis Simulated turnover time. Simulated leaf-level Nrubisco (g m–2 leaf area), canopy-level Nrubisco (g m–2 ground area), annual leaf-level Nrubiscodemand (g m–2 leaf area year–1), and annual canopy-level of Nrubisco demand (g m–2 ground area year–1) in figure 4. Lifespan of evergreen Note. LAI products used in the paper , such as TCDR LAI during 1982­–2016; GLASS LAI during 1982–2014; and GLOBMAP LAI during 1982–2011 are public available, the details information see Jiang et al (2017). Evergreen, deciduous and herbaceous vegetation fractions data derived from ESA CCI land cover products is publicly available, the details information see Li et al (2018). The climate force for Vcmax simulation was used CRU TS4.3 (Harris et al, 2020) for 1982–2016 at 0.5° resolution, which is publicly available at https://crudata.uea.ac.uk/cru/data/hrg/. The data files are all in netcdf format at 0.5 resolution Reference: Luo X, Croft H, Chen JM, He L, Keenan TF. 2019. Improved estimates of global terrestrial photosynthesis using information on leaf chlorophyll content. Global Change Biology 25(7): 2499-2514. Jiang C, Ryu Y, Fang H, Myneni R, Claverie M, Zhu Z. 2017. Inconsistencies of interannual variability and trends in long-term satellite leaf area index products. Global Change Biology 23(10): 4133-4146. Li W, MacBean N, Ciais P, Defourny P, Lamarche C, Bontemps S, Houghton RA, Peng S. 2018. Gross and net land cover changes in the main plant functional types derived from the annual ESA CCI land cover maps (1992–2015). Earth Syst. Sci. Data 10(1): 219-234. Harris I, Osborn TJ, Jones P, Lister D. 2020. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset. Scientific Data 7(1): 109.