Forest ecosystems represent the dominant form of land cover in the northeastern United States and are heavily relied upon by the region’s residents as a source of fuel, fiber, structural materials, clean water, economic vitality, and recreational opportunities. Although predicted changes in climate have important implications for a number of ecosystem processes, our present understanding of their long-term effects is poor. In this study, we used the PnET-CN model of forest carbon (C), nitrogen (N) and water cycling to evaluate the effects of predicted changes in climate and atmospheric carbon dioxide (CO2) on forest growth, C exchange, water runoff, and nitrate (\( {\text{NO}}^{ - }_{3} \)) leaching at five forest research sites across the northeastern U.S. We used four sets of statistically downscaled climate predictions from two general circulation models (the Hadley Centre Coupled Model, version 3 and the Parallel Climate Model) and two scenarios of future CO2 concentrations. A series of model experiments was conducted to examine the effects of future temperature, precipitation, CO2, and various assumptions regarding the physiological response of forests to these changes. Results indicate a wide range of predicted future growth rates. Increased growth was predicted across deciduous sites under most future conditions, while growth declines were predicted for spruce forests under the warmest scenarios and in some deciduous forests when CO2 fertilization effects were absent. Both climate and rising CO2 contributed to predicted changes, but their relative importance shifted from CO2-dominated to climate-dominated from the first to second half of the twenty-first century. Predicted runoff ranged from no change to a slight decrease, depending on future precipitation and assumptions about stomatal response to CO2. Nitrate leaching exhibited variable responses, but was highest under conditions that imposed plant stress with no physiological effects of CO2. Although there are considerable uncertainties surrounding predicted responses to climate change, these results provide a range of possible outcomes and highlight interactions among processes that are likely to be important. Such information can be useful to scientists and land managers as they plan on means of examining and responding to the effects of climate change.