Increasing utilization of forest biomass has raised interest in improving understanding of the short-term and long-term effects of intensive timber harvesting. Mathematical modeling provides an approach to quantify recovery of forest ecosystems following harvesting over different temporal and spatial scales and to evaluate the effects of alternative harvesting strategies. The hydrochemical model, PnET-BGC was modified and parameterized to simulate the hydrology, biomass accumulation, and soil solution and stream water chemistry responses to clear-cutting of two experimental northern hardwood watersheds at the Hubbard Brook Experimental Forest, New Hampshire, USA. Watershed 2 was devegetated in 1965 (without biomass removal) and regrowth was prevented for two years by herbicide application. A commercial whole-tree harvest was conducted in watershed 5 in 1983-84.
Model simulations were generally able to depict measured values for aboveground biomass, hydrology and drainage water chemistry over the decades following clear-cutting disturbance. We hypothesized that the accumulation of aboveground biomass for the whole-tree harvested watershed (W5) would exceed values from the devegetation and herbicide treatment (W2). However the model projects that both sites will accumulate aboveground biomass to a similar extent of around 22-24 t/ha by the year 2200. The delay of vegetation regrowth in W2 due to herbicide treatment resulted in higher soil mineralization and nitrification rates and generally causing greater export of dissolved nutrients compared with W5 for three years following the cuts, with annual average streamwater concentrations of 640 and 153 µM for nitrate and 177 and 53 µM for calcium for W2 and W5, respectively. In contrast, streamwater sulfate concentrations decreased 50% in W2 and 30% in W5 from pre-cut values due enhanced soil adsorption immediately following the cut and then increased as that adsorbed sulfate was released back to solution. The model was also used to characterize and compare long-term nutrient budgets and patterns of organic carbon loss and accumulation of both watersheds. Statistical criteria generally indicated high model performance and a first-order sensitivity analysis was conducted to identify parameters with higher sensitivity of the model for tree harvesting applications.