Forest productivity under projected changes in climate and CO2 in northern Minnesota, Wisconsin, and Michigan using PnET-CN

Background/Question/Methods

While large changes in atmospheric CO₂, temperature and precipitation are predicted by 2100, the long-term consequences for carbon cycling in forests are poorly understood. We used the PnET-CN ecosystem model to evaluate the effects of changing climate and atmospheric CO₂ on productivity in forests of the North American Great Lakes region at 1 km spatial resolution. We examined two statistically downscaled and contrasting climate projections (PCM B1 and GFDL A1FI, with the latter predicting more warming and reduced precipitation) to represent a range in potential future climate. Each climate projection was simulated under two CO₂ scenarios (constant and increasing atmospheric CO₂ concentration) to separate the effects of rising CO₂ from warming and precipitation changes.

Results/Conclusions

Increased productivity under future climate projections and higher CO₂ was largely driven by CO₂ fertilization effects on reduced stomatal conductance and water stress. Consequently, all results that follow were predicted under rising CO₂ levels. Predicted increases in regional average productivity ranged from 67% under the PCM B1 projection (warmer and wetter) to 142% under the GFDL A1FI projection (hotter and drier). Ecosystem responses varied geographically with the largest increases in productivity in northeastern Minnesota, northern Wisconsin, and upper Michigan. Ecosystem responses also varied by forest type, with deciduous forest types (aspen-birch, maple-beech-birch, elm-ash-cottonwood, oak-hickory) showing the largest increases in productivity, followed by pine, and spruce-fir forests. The relative importance of edaphic and climatic spatial drivers of productivity varied over time, suggesting that productivity in Great Lakes forests may switch from being temperature to water limited by the end of the century. This work identifies a potential range of forest ecosystem responses to climate change in the Great Lakes region while highlighting geographical differences in these responses that are useful for natural resource planning and management.