Thursday, August 9, 2007 - 1:30 PM

OOS 42-5: Climate-induced forest dieback as an emergent global phenomenon: Overview and synthesis

Craig D. Allen1, David D. Breshears2, Nathan L. Stephenson3, and Phillip J. Van Mantgem3. (1) U.S. Geological Survey, Jemez Mountains Field Station, (2) University of Arizona, (3) United States Geological Survey

Climate change models predict substantial shifts in climatic patterns over coming decades in many regions, including warmer temperatures and increases in duration and severity of extreme drought events. Such changes increase physiological stress on long-lived woody vegetation, directly leading to increased mortality and episodes of forest dieback. In some cases forest dieback is amplified by climate-mediated changes in the population dynamics of insect pests, or human-altered land use patterns and disturbances like forest fragmentation and increased fire activity. Forest stress and dieback are now becoming apparent in many parts of the world. Examples are presented from all forested continents, including Australia, Europe, Asia, Africa, South America, and North America. In particular, substantial episodes of recent forest mortality have occurred in North America from Alaska to Mexico, affecting >20 million hectares and many tree species since 1997. Assessing the potential for extensive climate-induced forest dieback is a key global change research topic, since woody mortality losses can occur much faster than tree growth gains, with pervasive and persistent ecological effects, including feedbacks to other disturbance processes (e.g., fire, erosion) and loss of sequestered carbon back to the atmosphere. We present a current synthesis of climate-induced forest dieback as an emergent global phenomenon, including an international overview from ongoing research and existing literature. Collectively the papers in this organized oral session highlight global examples of forest dieback, physiological process drivers of woody plant mortality, and applications of available knowledge to regional and global scale modeling and prediction of forest dieback.