The Simulation Of Net Primary Productivity Of Typical Chinese Fir Plantation Based On CENTURY Model

The forest ecosystem plays a very important role in the global ecosystem carbon cycle, and the forest biomass and productivity are the basic data to judge the carbon balance of forest ecosystem. Cunninghamia lanceolata in our country is mainly planted in southern collective Forest sterile important forest types, mainly in the scope of its cultivation throughout our subtropical provinces, accounting for a quarter of the national area planted plantations, ecological construction and forest production in our country and environmental protection plays an important role, the depth and breadth of their research is also far more than other species. In recent years with the plantation bring replanting, showing a decline in CL plantation productivity and other ecological issues, therefore, CL plantation productivity and changes in biomass research, CL for maintaining long-term productivity and sustainability, and provide scientific basis for long-term management of CL instructive.This research used CENTURY model to simulate artificial CL forest productivity and biomass, to verify the applicability of the region in conjunction with CL plantation CENTURY model. This experiment used CENTURY V4.0 test version of the model run. First obtain the data required for the model, then the model parameter initialization, use to obtain data to run the model, after running a number of years to reach equilibrium. Finally, test analysis and evaluation model.（1）In the course of the model initialization, the soil is divided into the chronic, inert, active and soil organic carbon pools. After the model initialization four carbon stocks gradually reaches a stable value, respectively, accounting for 3.88%of active carbon pool library stable 2.74 t·hm^-2; 69.39% of the total carbon pool of chronic library, simulation is 48.55 t·hm^-2; simulation is 17.45 t·hm^-2 inert library, and 26.73% of the total carbon pool; total initial soil carbon stocks level simulation and experimental area 70.35 t·hm^-2 close. Inter annual variability of soil organic carbon pool in the same general trend, but there are variations.（2）In the validation step of the model, CENTURY model simulation biomass typical subtropical CL plantations, the simulation results in line with expectations, chart trends CL forest biomass and the measured value is close to the linear regression equation y=1.317x^-11.894 （R2=0.9371,N=19, P<0.01）, the error is the square root of simulated and measured values （RMSE） was 27.46 t·hm^-2, realized a positive significant correlation.（3）For NPP simulated and measured values of the trend between 1996 and 2009 coincide. Due to change with stand age increase NPP, two generations of CL NPP showed different trends. The three forest age productive seasonal dynamics simulation, productivity peaked in April to June, accounting for 56.22%annual productivity, wherein 7a green fir forest to reach the pinnacle of analog productivity 1.05 t·hm^-2·a^-1 in May 14a of CL was 1.67 t·hm^-2·a^-1,20a green fir forest up to 1.82t·hm^-2·a^-1. January to February next year, productivity declined significantly during February, which 7a old CL productivity reached its lowest point in January to 0.07 t·hm^-2·a^-1，14a green fir forest biomass analog lowest in December fell to 0.11 t·hm^-2·a^-1,20a green vegetation productivity is much higher than the minimum 7a and 14a, in January reached 0.21 t·hm^-2·a^-1. Regression analysis based on the simulation results with the CENTURY model to simulate the value of the model, the coefficient of determination three kinds of CL seasonal dynamics simulation and measured values of R2 are 0.9085,0.8275,0.8893; root mean square error RMSE were 0.0290^ 0.0315、0.3661 t·hm^-2·a^-1（4）In the sensitivity analysis of the parameters of the model and the driving variables, When the optimum growth temperature rose 10%, the biomass decreased by 16.87%, when the optimum growth temperature decreased by 10%, the biomass increased by 9.44%. When the potential productivity factor rose 10%, the biomass increased by 7.79%, when the potential productivity coefficient decreased by 10%, the biomass decreased by 3.42%. When the precipitation increased by 5%, the biomass of Chinese fir forest increased by 13.63%, and the biomass of Chinese fir forest decreased by 13.63% when rainfall was less than 5%. When the monthly average maximum temperature increased by 1 degrees Celsius, the biomass of Chinese fir forest increased by 2.46%, while the average monthly minimum temperature increased by 1, and the biomass of Chinese fir forest decreased by 0.02%, which was almost unchanged. When the monthly average minimum temperature increased by 1 degrees Celsius, the biomass of Chinese fir forest decreased by 1.03%, while the average monthly minimum temperature was 1 degrees Celsius, and the biomass of Chinese fir forest increased by 0.14%.（5）Description simulated and measured values significantly correlated. Simulation of NPP in the future, T early scene in 2020, rising steadily to the peak after 15.58 t·hm^-1·a^-1, simulated late 2050 dropped to 12.08 t·hm^-2·a^-1, a decline of 8.37%. Simulation scenarios P because of a substantial increase in rainfall, vegetation NPP rapid growth in the early stages, the analog value is close to16.70 t·hm^-2·a^-1, reached the end of 13.75 t·hm^-2·a^-1, and higher than the initial simulation 4.36%, T+P scene vegetation T is higher than the overall NPP simulation scenario simulation results, compared to the rate of change PNPP scene is more gradual.