Xia Jiangzhou;Chen Yang;Liang Shunlin;Liu Dan;Yuan Wenping;

[Xia, Jiangzhou; Chen, Yang; Liu, Dan; Yuan, Wenping] Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China.

[Liang, Shunlin] Beijing Normal Univ, Sch Geog, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China.

[Liang, Shunlin] Univ Maryland, Dept Geog Sci, College Pk, MD 20742 USA.

ABSTRACT:  The allocation of photosynthate among the plant components plays an important role in regulating plant growth, competition and other ecosystem functions. Several process-based carbon allocation models have been developed and incorporated into ecosystem models; however, these models have used arbitrary model parameters and have never been sufficiently validated on a global scale. This study uses the Integrated Biosphere Simulator (IBIS) model as a platform to integrate a carbon allocation model (resource availability model) with satellite-derived leaf area index (LAI) dataset, which allows us to inversely predict the allocation parameters for five deciduous vegetation types. Our results showed that the carbon allocation coefficients can be reliably constrained by the satellite LAI product, and the new parameters substantially improved model performance for simulating LAI and aboveground biomass globally. The spatial pattern of allocation coefficients among plant parts is supported by a number of studies. Compared with the standard version of the IBIS model using fixed allocation coefficients, the revised resource availability carbon allocation model tends to promote higher root carbon allocation. Our study provides a method for inverting the parameters of the carbon allocation model and improves the model performance in simulating the LAI and biomass.

Published in TELLUS SERIES B-CHEMICAL AND PHYSICAL METEOROLOGY.2015,67(, DOI: 10.3402/tellusb.v67.28016