PS 111-258 - Incorporation of disturbance and seasonality in terrestrial carbon flux upscaling

Friday, August 10, 2012
Exhibit Hall, Oregon Convention Center
Kusum Naithani1, Erica A.H. Smithwick1, Kenneth J. Davis2, Klaus Keller3, Robert Kennedy4 and Jeff G. Masek5, (1)Department of Geography, The Pennsylvania State University, University Park, PA, (2)Department of Meteorology, The Pennsylvania State University, University Park, PA, (3)Department of Geosciences, The Pennsylvania State University, University Park, PA, (4)Department of Earth and the Environment, Boston University, Boston, MA, (5)NASA, Greenbelt, MD
Background/Question/Methods

Integration of disturbance patterns into carbon (C) flux estimates to improve terrestrial-atmosphere C exchange is a critical priority for the North American Carbon Program. This project is built upon previous finding from The Chequamegon Ecosystem Atmospheric Study and aims to quantify uncertainty in C flux upscaling due to disturbance and seasonality, evaluate multiple disturbance stressors, and develop two-way communication channels between federal agencies and scientists.  This project asks three main questions: (1) Does incorporation of variation in physiological model parameters improve seasonal and interannual CO2 flux hindcasts from eddy flux towers? (2) Does incorporation of stand-replacement and partial disturbance processes from remotely sensed observations improve yearly to decadal CO2 flux hindcasts from eddy flux towers? and (3) To what degree does model-data integration aid regional and landscape decision-making for forest C storage management?

Results/Conclusions

We show that parameter and prediction uncertainty in terrestrial C upscaling increases with increasing stand age with a slight decline at the end of the stand age spectrum (old stands).  The maps of regional C fluxes and uncertainty under different management scenario are of interest to the park managers.  The finding from this project directly contribute to national efforts to constrain uncertainty in terrestrial-atmospheric C exchange in several important ways.  First, it utilizes a new disturbance algorithms using Landsat imagery to test whether inclusion of partial and stand-replacing disturbance reduces uncertainty in C flux upscaling.  Second, it employs a computationally tractable but responsive photosynthetic model to evaluate whether a more sophisticated parameterization of plant physiology aids temporal diagnosis of C flux estimates.  Third, by collaborating with regional and national Forest Service personnel, this project partially addresses the ‘end-to-end’ problem of C cycle science by helping managers to diagnose adaptive capacity of forested landscapes, target locations, and prioritize C management activities.