LSCNP: A Process and Analytic Hybrid Model Simulating Long-term Soil Carbon and Nitrogen Dynamics.
Tao Li, Dept of Renewable Resources, Univ of Alberta, 442 Earth Science Building, Edmonton, AB T6G 2E3, Canada, Yongsheng Feng, Dept of Renewable Resources, Univ of Alberta, Edmonton, AB T6G2E3, Canada, and Xiaomei Li, Alberta Research Council, 250 Karl Clark Road, Edmonton, AB T6N 1E4, Canada.
The large uncertainties and accumulative errors in long-term soil carbon and nitrogen dynamics is a challenge for simulation modelling. The Long-term Soil Carbon, Nitrogen and Phosphorus (LSCNP) dynamics model is developed to reduce modeling uncertainty and the accumulative simulating error by integrating the process and analytic algorithms into one model. The process module is used to simulate daily plant growth and to represent the short-term dynamics of energy, water, and soil carbon and nitrogen. The analytic module is used to compute the long-term dynamics of soil carbon and nitrogen ignoring the short-term details. The short-term, process based simulation provides inputs for the long-term analytic module. Results show that the accumulative errors of long-term simulation have been minimized. Results also show that the short-term fluctuation in plant growth does not significantly influence the long term results. The increase of soil carbon and nitrogen storage in a few decades does not imply similar rate of increase in the hundred-year time scale. Therefore, the efforts in increasing soil carbon storage should take a long-term view and that the attempt to extrapolate results from short-term (°Ü 10 years) experiments into long-term implications must proceed with care.