Pan Jian-jun

Predicting dynamics of soil organic carbon mineralization with a double exponential model in different forest belts of China

The dynamics of soil organic carbon (SOC) was analyzed by using laboratory incubation and double exponential model that mineralizable SOC was separated into active carbon pools and slow carbon pools in forest soils derived from Changbai and Qilian Mountain areas. By analyzing and fitting the CO2 evolved rates with SOC mineralization, the results showed that active carbon pools accounted for 1.0% to 8.5% of SOC with an average of mean resistant times (MRTs) for 24 days, and slow carbon pools accounted for 91% to 99% of SOC with an average of MRTs for 179 years. The sizes and MRTs of slow carbon pools showed that SOC in Qilian Mountain sites was more difficult to decompose than that in Changbai Mountain sites. By analyzing the effects of temperature, soil clay content and elevation on Soc mineralization, results indicated that mineralization of SOC was directly related to temperature and that content of accumulated SOC and size of slow carbon pools from Changbai Mountain and Qilian Mountain sites increased linearly with increasing clay content, respectively, which showed temperature and clay content could make greater effect on mineralization of SOC.

Dynamics models of soil organic carbon

As the largest pool of terrestrial organic carbon, soils interact strongly with atmosphere composition, climate, and land change. Soil organic carbon dynamics in ecosystem plays a great role in global carbon cycle and global change. With development of mathematical models that simulate changes in soil organic carbon, there have been considerable advances in understanding soil organic carbon dynamics. This paper mainly reviewed the composition of soil organic matter and its influenced factors, and recommended some soil organic matter models worldwide. Based on the analyses of the developed results at home and abroad, it is suggested that future soil organic matter models should be developed toward based-process models, and not always empirical ones. The models are able to reveal their interaction between soil carbon systems, climate and land cover by technique and methods of GIS (Geographical Information System) and RS (Remote Sensing). These models should be developed at a global scale, in dynamically describing the spatial and temporal changes of soil organic matter cycle. Meanwhile, the further researches on models should be strengthen for providing theory basis and foundation in making policy of green house gas emission in China.