Effects of different management approaches on soil carbon dynamics in Moso bamboo forest ecosystems

Moso bamboo (Phyllostachys pubescens) is a very important forest resource in subtropical China, and it has excellent carbon sequestration potential, and can play an important role in mitigating climate change. The international community has gradually recognized the benefits of Reducing Emissions from Deforestation and Forest Degradation (REDD+) forest carbon sequestration mechanisms, and the areas available for the development of forest carbon sinks have greatly expanded. Therefore, in this study, we use a two-factor randomized complete block design in which fertilization rate and harvesting intensity were selected to investigate the changes in soil organic carbon (SOC) concentration and carbon (C) storage from 2010 to 2016. With 3k orthogonal method, a factorial analysis with 3 levels of fertilization (high (1800), medium (900) and low (0 kg ha−1 year−1)) and 3 levels of harvesting intensity (high (100%), medium (50%) and low (0%) cutting of the bamboo of 4–5 years old) has been taken. Our results show that fertilization, harvesting, and the fertilization × harvesting interaction had significant effects on SOC concentration changes, but not on C storage after six years of management. Only the interaction between high fertilization and high intensity harvesting, which we called the intensive management model, caused a decrease of 4.48 Mg C ha−1 in the 0–50 cm soil layer C storage. The interaction between no fertilization and low intensity harvesting, which we called the traditional management model, increased soil carbon C by 7.90 Mg C ha−1. The optimized management model of high fertilization and medium intensity harvesting increased soil C the most; by 59.94 Mg C ha−1, which is 2.36 times larger than that of the intensive management model, and 1.86 times larger than that of the traditional management model. The results clearly reveal that the soil carbon pools in Moso bamboo forest have a great carbon sequestration potential under the optimized management model.