The study found that temperature and photosynthetic active radiation were the two most important variables in predicting what forest landscapes may look like in the future. The uncertainties became very high after the year 2200.

Approximately 100,000 acres of forested area west of Lake Superior which make up the Boundary Waters Canoe Area was used for the study.
Using computer models PnET-II and LANDIS-II, the researchers were able to simulate 209 possible scenarios, including 13 tree species and 27 possible climate profiles to predict how the landscape will look over time.

"The tools that we developed and we're using for the research project can be applied to any discipline dealing with risk and uncertainty in decision making," said University of Illinois at Urbana-Champaign (UI-UC) researcher George Gertner.

"We were dealing with the uncertainties in global change predictions using the projections established by the United Nations Intergovernmental Panel on Climate Change. These projections were based on different carbon dioxide reduction scenarios and global circulation models."

The study found that the most important source of uncertainty in the forest composition prediction is from the uncertainty in temperature predictions. The second most important source is photosynthetic active radiation, the third is carbon dioxide, and the fourth is precipitation, said an UI-UC release.

Gertner said that management can be easier with agricultural systems. "Over short intervals you can adapt very quickly. You can make big changes very quickly, but with a forest, the lifespan is 100, 200 years, so once you do something it's longer term."
These findings were published in Global Change Biology 2009.

--Indo-Asian News Service