Study projects vast regional differences in forest productivity, migration and wildfire impacts
Accounting for nearly one-third of the global land surface, forests help regulate the climate and protect watersheds while providing consumer products and outdoor experiences that enhance the quality of life. Climate change will inevitably influence forests’ ability to deliver these services, but past studies have provided a limited picture of what changes may come this century. Now researchers from the Corvallis Forestry Sciences Laboratory, MIT, Ohio State University and the U.S. Environmental Protection Agency have sharpened that picture by assessing the impact of climate change on three key factors: forest productivity (capacity to extract, store and transform atmospheric carbon dioxide into forest products), migration (geographical shifts of vegetation) and wildfire-induced depletion and regrowth.
Using a combined global vegetation and climate model to compare two climate policy scenarios—a “business-as-usual” scenario in which greenhouse gas emissions are unconstrained, and a “2°C” scenario representing an emissions pathway that would limit the rise in global mean temperature since preindustrial times to two degrees Celsius by 2100—the researchers determined that the impact of climate change on forests in the coming decades is decidedly mixed.
Both scenarios project a net increase in forest carbon stocks across the globe, with most of the gains occurring in tropical forests. The business-as-usual scenario would raise concentrations of atmospheric carbon dioxide substantially, increasing the fertilization effect of CO2, leading to higher vegetation growth and carbon stocks. But because increased CO2 leads to higher surface temperatures, some of these gains would be counteracted by a higher incidence of wildfires, particularly in temperate zones, which release CO2 into the atmosphere as they consume trees and other forest plants. The 2°C climate mitigation scenario, which significantly decreases atmospheric CO2, would, in turn, reduce these forest carbon stock gains, especially in the southern hemisphere.
While unconstrained climate change would likely benefit forests at the global level and in some regions, it would decrease forested areas in many others, particularly in Russia, Canada and China. Wildfires would multiply with increasing temperatures, especially in Russia and Central America. In Russia, climate change would significantly decrease carbon stocks and forest areas while increasing burnt forest areas.
“While climate mitigation would reduce carbon stocks globally, it would also reduce wildfire damages to forests and the adaptation costs associated with those damages,” says Erwan Monier, a co-author of the study and principal research scientist at the MIT Joint Program on the Science and Policy of Global Change. “By minimizing uncertainty about future forest health and productivity, climate mitigation would lower the complexity and expense of future forestry sector management and planning.”
The study, which was primarily funded by the EPA, appears in the journal Environmental Research Letters. (A companion paper published in the same journal used this study’s results to evaluate the economic impacts of climate change on the forestry sector.)
To assess the impact of climate change on forests under different climate scenarios, the researchers used a dynamic global vegetation model under multiple climate simulations from a version of the MIT Integrated Global Systems Modeling (IGSM) framework that incorporates the Community Atmosphere Model. They arrived at their “business-as-usual” and “2°C” scenario projections by tracking changes in forest carbon stocks, total forest area and burnt forest area in 16 geographical regions over the course of the 21st century.
As lead climate scientist of the study, Monier sought to examine the precision of these projections. Recognizing three key sources of uncertainty in climate change impacts on the world's forests—emissions scenarios, the global system climate response (climate sensitivity) and natural variability (year-to-year and longer-term variations in the climate), the researchers ran large numbers of simulations of each scenario to understand the impact of these sources of uncertainty on their estimates.