Abstract:

Terrestrial ecosystem carbon (C) uptake is remarkably regulated by nitrogen (N) availability in the soil. However, the coupling of C and N cycles, as reflected by C:N ratios in different components, has not been well explored in response to climate change.

Here, we applied a data assimilation approach to assimilate 14 datasets collected from a warming experiment in an alpine meadow in China into a grassland ecosystem model. We attempted to evaluate how experimental warming affects C and N coupling as indicated by constrained parameters under ambient and warming treatments separately.

The results showed that warming increased soil N availability with decreased C:N ratio in soil labile C pool, leading to an increase in N uptake by plants. Nonetheless, C input to leaf increased more than N, leading to an increase and a decrease in the C:N ratio in leaf and root, respectively. Litter C:N ratio was decreased due to the increased N immobilization under high soil N availability or warming-accelerated decomposition of litter mass. Warming also increased C:N ratio of slow soil organic matter pool, suggesting a greater soil C sequestration potential. As most models usually use a fixed C:N ratio across different environments, the divergent shifts of C:N ratios under climate warming detected in this study could provide a useful benchmark for model parameterization and benefit models to predict C–N coupled responses to future climate change.

Key words: Bayesian probabilistic inversion, Markov-Chain Monte-Carlo (MCMC), warming, carbon and nitrogen cycles, stoichiometry, alpine meadow