Forests contain one of the world's largest carbon (C) pools and represent opportunities for cost-effective climate change mitigation through programmes such as the United Nations-led "Reducing Emissions from Deforestation and Forest Degradation" Programme (REDD). Generic estimates for the conversion of forest biomass into C stock are not sufficiently accurate for assessing the utility of harvesting forest to offset carbon dioxide emissions, currently under consideration by the REDD Programme. We examined the variation in C concentration among tree species and tree functional types (classified based on leaf morphological and phenological traits) in a subtropical forest and evaluated the effects of these variations on stand-level estimations of C stock. This study was conducted in the Paiyashan Forest State Farm and the Dashanchong Forest Park, Hunan Province, China. C concentrations differed significantly among tree species (P < 0.0001) and were significantly higher in gymnosperm than angiosperm species. Estimations of stand C stocks were similar using either functional types or species- and tissue-specific C concentrations. The use of functional type classification to estimate stand C stock is an effective tool for implementing C sequestration trade and C credit programmes and the UN-REDD Programme in subtropical forests.