Differential effects of nitrogen vs. phosphorus limitation on terrestrial carbon storage in two subtropical forests: A Bayesian approach

Nitrogen (N) and phosphorus (P) have been demonstrated to limit terrestrial carbon (C) storage in terrestrial ecosystems. However, the reliable indicator to infer N and P limitation are still lacking, especially in subtropical forests. Here we used a terrestrial ecosystem (TECO) model framework in combination with a Bayesian approach to evaluate effects of nutrient limitation from added N/P processes and data sets on C storage capacities in two subtropical forests (Tiantong and Qianyanzhou [QYZ]). Three of the six simulation experiments were developed with assimilating data (TECO C model with C data [C-C], TECO C-N coupling model with C and N data [CN-CN], and TECO C-N-P model with C, N, and P data [CNP-CNP]), and the other three ones were simulated without as-similating data (C-only, CN-only, and CNP-only). We found that P dominantly constrained C storage capacities in Tiantong (42%) whereas N limitation decreased C storage projections in QYZ (44%). Our analysis indicated that the stoichiometry of wood biomass and soil microbe (e.g., N:P ratio) were more sensitive indicators of N or P limitation than that of other pools. Furthermore, effects of P-induced limitation were mainly on root biomass by additional P data and on both metabolic litter and soil organic carbon (SOC) by added P processes. N-induced effects were mainly from added N data that limited plant non-photosynthetic tissues (e.g., woody biomass and litter). The different effects of N and P modules on C storage projections reflected the diverse nutrient acquisition strategies associated with stand ages and plant species under nutrient stressed environment. These findings sug-gest that the interaction between plants and microorganisms regulate effects of nutrient availability on ecosys-tem C storage, and stoichiometric flexibility of N and P in plant and soil C pools could improve the representation of N and P limitation in terrestrial ecosystem models. (c) 2021 Elsevier B.V. All rights reserved.