Projections of soil carbon using the combination of the CNOP-P method and GCMs from CMIP5 under RCP4.5 in north-south transect of eastern China

Abstract

Background and aimsSoil plays a key role in land-atmosphere carbon exchange as the largest carbon pool in terrestrial ecosystems. Because of the uncertainty in predictions of soil carbon storage, understanding the magnitude and spatial and temporal patterns of terrestrial carbon sinks and sources is difficult.MethodsIn this study, the response of soil carbon to future climate change scenarios, which were provided by 10 general circulation models (GCMs) of the Coupled Model Intercomparison Project 5 (CMIP5) under the Representative Concentration Pathway (RCP) 4.5 scenario, was explored with the Lund-Potsdam-Jena (LPJ) model for a North-South Transect of Eastern China (NSTEC). Additionally, the conditional nonlinear optimal perturbation related to parameters (CNOP-P) approach was used to provide two scenarios to evaluate the possible maximal uncertainties of soil carbon response to future climate change.ResultsBased on the 10 GCMs from 2011 to 2100, the mean soil carbon was from 75.6 Gt C to 86.7 Gt C. As a result of the two climate change scenarios using the CNOP-P approach, soil carbon stocks were respectively 93.1 Gt C and 84.1 Gt C, which were larger than those using the 10 GCMs. The primary difference was determined by the difference in middle and high latitudes (30o N-35o N; 40o N-45o N) of the NSTEC region according to zonal analysis. Soil carbon associated with different plant functional types was also analyzed. The primary contributors to the augmentation of soil carbon under the CNOP-P-type scenario were the increases in soil carbon for temperate broad-leaved summer-green trees and temperate grasslands.ConclusionsAs these numerical results indicated, uncertainty was found in the predictions of soil carbon, and the future soil carbon will increase in NSTEC region compared to 1961–1990. This implied that the soil may play role of carbon sink. And, the CNOP-P approach might offer a possible future upper limit for the evaluation of soil carbon with the LPJ model.