Inverse analysis of coupled carbon-nitrogen cycles against multiple datasets at ambient and elevated CO2

Abstract

Aims Carbon (C) sequestration in terrestrial ecosystems is strongly regulated by nitrogen (N) processes. However, key parameters that determine the degree of N regulation on terrestrial C sequestration have not been well quantified. .

Methods Here, we used a Bayesian probabilistic inversion approach to estimate 14 target parameters related to ecosystem C and N interactions from 19 datasets obtained from Duke Forests under ambient and elevated carbon dioxide (CO2).

Important Findings Our results indicated that 8 of the 14 target parameters, such as C:N ratios in most ecosystem compartments, plant N uptake and external N input, were well constrained by available datasets whereas the others, such as N allocation coefficients, N loss and the initial value of mineral N pool were poorly constrained. Our analysis showed that elevated CO2 led to the increases in C:N ratios in foliage, fine roots and litter. Moreover, elevated CO2 stimulated plant N uptake and increased ecosystem N capital in Duke Forests by 25.2 and 8.5%, respectively. In addition, elevated CO2 resulted in the decrease of C exit rates (i.e. increases in C residence times) in foliage, woody biomass, structural litter and passive soil organic matter, but the increase of C exit rate in fine roots. Our results demonstrated that CO2 enrichment substantially altered key parameters in determining terrestrial C and N interactions, which have profound implications for model improvement and predictions of future C sequestration in terrestrial ecosystems in response to global change. .

Publication

Publication Zheng Shi, Yuanhe Yang, Xuhui Zhou, Ensheng Weng, Adrien C. Finzi and Yiqi Luo 2015. Inverse analysis of coupled carbon-nitrogen cycles against multiple datasets at ambient and elevated CO2. Journal of Plant Ecology, doi:10.1093/jpe/rtv059.

Data assimilation algorithm by Yuanhe Yang (Download Files)

Note: To run the routine one has to run the "MCMC.m".