Probability assessment of climate change impacts on soil organic carbon stocks in future periods: a case study in Hyrcanian forests (Northern Iran)

Abstract

Simulations of soil organic carbon (SOC) stocks under climate change are partly subject to uncertainties deriving from the Global Climate Models (GCMs) used for weather projections of future climates. For this reason, SOC simulations are generally performed with a set of GCMs to avoid misleading results. SOC stocks were measured in different land covers in a forest area of Northern Iran (maple, alder, oak, cypress and a mixed natural forest), and the model RothC was used to predict SOC changes under climate change scenarios. We studied the effects on SOC stock changes deriving from an ensemble of nine GCMs and two Representative Concentration Pathways (RCPs), projected on four future periods (FPs) of 20\xa0years between 2020 and 2099. The frequency analysis of SOC stock changes indicated a different effect of the GCMs/RCPs ensemble in the four future periods, with patterns showing more evident nonlinear probabilities of SOC changes in the 2030s and 2050s compared to the almost linear probabilities in the remaining future periods. This would imply that the effect of the GCMs/RCPs ensemble is more important in very close and intermediate future scenarios (the 2030s and 2050s) compared to fully realized climate change scenarios (the 2070s and 2090s). Results indicated the need to provide assistance in the management strategies in the reforestation sector in close and intermediate climate change scenarios. In fact, maple and quercus plantations had the highest probability of cumulated SOC change proving more sensitive to climate change. Conversely, cypress and alder plantations could limit the decrease of SOC stocks representing a good option for GHG mitigation in close and intermediate climate change scenarios and should be preferred in the afforestation of the degraded natural forest, and in mixed plantation systems within maple and oak stands.