An attempt to introduce atmospheric CO2 concentration data to estimate the gross primary production by the terrestrial biosphere and analyze its effects. (January 2018)

• Record Type: Journal Article
• Authors: Sun, Zhongyi; Wang, Xiufeng; Yamamoto, Haruhiko; Tani, Hiroshi; Zhong, Guosheng; Yin, Shuai
• Is Part Of: Ecological indicators. Volume 84(2018)
• Page Start: 218
• Page End: 234
• Publication Date: 2018-01
• Subjects: Gross primary production -- Atmospheric CO2 concentration variation -- GOSAT -- Remote sensing -- Spatial temporal variability; Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2017.08.057
• Languages: English
• ISSNs: 1470-160X

Abstract

Graphical abstract: Highlights: The estimation of the terrestrial GPP introduced continuous spatial satellite-based CO2 concentration data. Elevated CO2 concentration have caused increasing GPP, especially in forest ecosystems from 2000 to 2014. Tempo-spatial variations in the CO2 concentrations significantly affect the distribution of estimated GPP. And these effects on the same monthly estimated GPP of the North Hemisphere and the South Hemisphere are almost opposite. Abstract: Quantitative estimations of the GPP (gross primary production) and its variations at spatial scales are important issues with future significance due to the increasing atmospheric CO2 levels. However, the effects of the spatiotemporal variability in the atmospheric CO2 concentrations on GPP estimations are challenging with respect to the terrestrial ecosystem due to land cover component characteristics and difficulties associated with measuring CO2 concentrations over large spatial areas. The development of remote sensing offer a means to routinely monitor CO2 concentrations both spatially and temporally from space. To introduce continuous spatial CO2 data as an indicator for the estimation of the terrestrial biosphere GPP, we used the decoupling coefficients to evaluate the canopy CO2 concentrations, photosynthetic biochemical models to calculate the photosynthetic rate, and Big-leaf model to scale up to a global scale. The GPPs estimated by this method are relatively consistent with the GPP derived from Flux tower sites. Thus, the method proposed in this study utilizing continuous spatial CO2 data to estimate the GPP is practicable and feasible. Finally, we compared the GPPs under different atmospheric CO2 concentrations conditions between 2000 and 2014 and analyzed the effects of the spatiotemporal variability in the atmospheric CO2 concentrations on the GPP estimates. The results show that, in general, the terrestrial GPP increases as atmospheric CO2 concentrations increase, and the increases in the lower latitudes are more significant than those in the middle and high latitudes; by comparing the annual GPP estimates in 2000 with those in 2014, it was observed that the increases in forest GPP is greater than that of other functional types. The effects of the variations in the spatial distribution of atmospheric CO2 concentrations on the terrestrial GPP distribution vary based on time and location. Regarding the annual GPP estimates, without considering the CO2 spatial distribution, the estimates overestimate the GPP in the lower latitudes and underestimate those in the middle and high latitudes. Regarding the monthly GPP estimates, using the annual averages caused the GPP estimates of the Northern Hemisphere to be overestimated during the first half of the year, while those during the second half of the year were underestimated; the GPP estimates for the Southern Hemisphere were underestimated each month. However, using monthly averages caused the GPP estimates for the Northern Hemisphere to be overestimated in summer and underestimated in spring and autumn, which are opposite to the estimates for the Southern Hemisphere.