Incorporating disturbance and associated uncertainty into diagnostic terrestrial carbon flux upscaling

Erica A.H. Smithwick, Pennsylvania State University, smithwick@psu.edu (Presenter)
Kusum J. Naithani, The Pennsylvania State University, naithani@psu.edu
Kenneth James Davis, The Pennsylvania State University, kjd10@psu.edu
Robert E Kennedy, Boston University, kennedyr@bu.edu
Bianchetti Raechel, The Pennsylvania State University, rabianchetti@psu.edu
Parker Linda, U.S. Forest Service, lrparker@fs.fed.gov
Baldwin C. Douglas, The Pennysylvania State University, dcb5006@psu.edu
Keller Klaus, The Pennsylvania State University, klaus@psu.edu
Jeffrey Masek, NASA GSFC, jeffrey.g.masek@nasa.gov

The contribution of landscape disturbance, relative to patterns in plant functional types or climate, on terrestrial-atmosphere CO2 exchange is unknown. New approaches are needed that integrate disturbance patterns into diagnostic models to forecast their impact on landscape carbon flux and its associated uncertainty. Here, we leverage previous data-model fusion efforts to map mean CO2 flux and associated uncertainty by including estimates of forest stand age derived from historical Landsat imagery. We ask whether inclusion of this data improves yearly to decadal CO2 terrestrial flux hindcasts compared to previous efforts based on plant functional type and climate. Initial results indicate that parameter and prediction uncertainty varies with stand age. Extrapolated to the landscape scale, maps of mean CO2 flux and associated uncertainty are critical for meeting climate change mitigation and adaptation efforts that aim to prioritize disturbance activities in the region. However, our work also highlights key challenges. First, geovisualization of uncertainty across complex landscapes depends on explicit efforts to link analyst skill with end-user objectives; in our effort, the characterization of uncertainty reflected only a small slice of this uncertainty spectrum. Second, it was clear that interactions between stand age and disturbance type are likely critical in this landscape; however, towers represented only a subset of conditions present in the broader landscape, hindering model-data fusion efforts. Yet, despite these short-comings, our work represented an important portal for science-management communication of terrestrial carbon science and results highlight the importance of including management activities and data into regional flux models.

Presentation Type:  Poster

Session:  Poster Session 2-B   (Wed 4:30 PM)

Associated Project(s): 

• Influence of Disturbance and Seasonality on Regional Carbon Flux Upscaling

Poster Location ID: 78