Publications

Chen, XN; Tao, X; Yang, YP (2022). Distribution and Attribution of Gross Primary Productivity Increase Over the Mongolian Plateau, 2001-2018. IEEE ACCESS, 10, 25125-25134.

Abstract
Gross primary productivity (GPP) over the Mongolian Plateau (MP) is a vital component of the global terrestrial carbon cycle. Using the latest MODIS GPP estimates at the best achievable spatial resolution along with several ancillary datasets, we investigated GPP variations in the MP region during 2001-2018 and attributed these changes to land-surface temperature (T-s), total precipitation (P-t), landcover change (LCC), and atmospheric carbon dioxide (CO2) concentrations. The 18-year-averaged annual cumulative GPP in the MP region was 357.02 +/- 24.76 gC m(-2) yr(-1) during the study period, ranging from 60.51 +/- 6.10 gC m(-2) yr(-1) in deserts to 596.41 +/- 35.49 gC m(-2) yr(-1) in forests. A linear regression analysis indicated a significant overall increase in GPP, at a rate of 3.91 gC m(-2) yr(-1) (p < 0.01). In comparison, GPP increased at a rate of 0.79 gC m(-2) yr(-1) in deserts (p < 0.01), 4.79 gC m(-2) yr(-1) in forests (p < 0.01), and 5.76 gC m(-2) yr(-1) in grasslands (p < 0.01). Our detailed attribution analysis indicates that GPP is positively sensitive to surface air temperature (0.15 gC degrees C-1 ) and total precipitation (0.25 gC mm(-1)) but negatively sensitive to atmospheric CO2 concentrations (-0.20 gC mol(-1)) and LCC (-0.93 gC class(-1)). Furthermore, we reported large differences in the spatial patterns and magnitudes among individual variables in the GPP attribution analysis, with LCC proving to be the dominant factor followed by CO2 fertilization effects; climatic factors had comparatively little influence on GPP variations during the study period. Although MODIS GPP does not take CO2 fertilization effect into account, the close relationship between MODIS GPP and atmospheric CO2 concentrations still pose referencing value in attributing the GPP increase in this period. Overall, the findings of this study contribute to our understanding of the responses of sensitive ecosystems to the competing effects of climate change and human disturbance at regional scales.

DOI:
10.1109/ACCESS.2022.3155722

ISSN: