Simulation of wildfire effects on the nitrogen cycle of a Pinus banksiana ecosystem in New Brunswick, Canada

A non-linear, deterministic model of biomass accumulation and nitrogen cycling in an even-aged, pure jack pine (Pinus banksiana Lamb.) stand was developed and used to explore effects of fire intensity and frequency of burning on the long-term nitrogen cycle. Given the model structure and assumptions, simulated results showed that successive fires at both light and severe fire intensities caused gradual depletion of the amount of N accumulated in the vegetation layers. Fires also reduced the amount of N in the litter and soil pools, with the initially large soil organically-bound N pool showing a particularly sharp decline, and decreased the productivity of the simulated stand. A frequency of one fire per 20 years for five successive burns produced declines of N accumulated in the tree stratum of 50–75% (depending upon fire intensity) in comparison with the undisturbed system at a corresponding age, whereas a 100-year frequency produced decreases of 10–22%. Similarly, declines in litter layer N were 54–72% at a 40-year frequency, compared with 30–55% at a 100-year frequency. The simulated results also suggested that both the stand age when burning occurred and the fire frequency were important, because distinctive patterns of accumulation and decline of N in ecosystem pools existed with increasing stand age. A serious lack of information regarding processes inherent in the model was found to exist in certain cases. Important processes which are currently poorly quantified include: (1) the factors controlling rates of tree growth; (2) the relation of foliar and other tissue N to soil N concentrations and foliar translocation; (3) the relation of forest floor conditions to decomposition and stand structural characteristics; and (4) the controls of a variety of soil N transformations, transfers, leaching and decomposition rates. Because of this basic lack of information and the great dependence of the model's behavior on these processes, the present version of the model is not suitable for real-world prediction. The model does have use as a means of combining hypotheses about a system into an explicit structure and examining the collective consequences of this, as well as pointing out future research needs for the system.