Poster Session #65: Global Change.
Friday, August 9. Presentation from 8:00 AM to 9:30 AM. Exhibit Hall B & C, TCC


Physiological database of common eastern forest tree species growing in natural or experimentally altered conditions.

Scherzer, Amy*,1, Hom, John2, 1 USDA Forest Service, Delaware, OH2 USDA Forest Service, Newtown Square, PA

ABSTRACT- Physiological data including gas exchange (photosynthesis, stomatal conductance, respiration), water relations, nutrient dynamics, and biochemical data from tree species growing in natural or experimentally altered conditions has been compiled from the literature into a relational database containing common tree species found in eastern US forests. The information is designed to supplement the distribution, ecological, and climate parameters outlined in "Atlas of Current and Potential Future Distributions of Common Trees of the Eastern United States" by Iverson, et al. (1999) (see URL: www.fs.fed.us/ne/delaware/atlas). Ranges and variability of the physiological data are included to determine optimal responses as well as responses to individual and interactive stresses (i.e.: CO2, ozone, N deposition/fertilization, temperature, water). The database design enables the summarization of the responses by forest types or at various regional scales (i.e.: individual state, Northeast, Mid-Atlantic, eastern US), or by specific characteristics including species, life forms, shade tolerance, or biological family. The database provides empirical data necessary for the parameterization and validation of process-based computer simulation models used to predict effects of environmental change on forest ecosystem function. Currently the information is being adapted for use by the Northern Global Change Program in modeling applications that utilize the ten USFS Forest Inventory and Analysis major eastern forest type classifications. Specific projects include modeling of forest productivity in the Mid-Atlantic/Chesapeake Bay watershed, the Delaware River Basin Integrated Assessment, and large-scale validation of carbon stock and flux estimates from remote sensing. Other specific models and remote sensing tools that will utilize these physiological parameters and forest type classifications are PnET-CN, TEM, and MODIS.

KEY WORDS: physiological parameters, eastern tree species, database, modeling