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Operational Forest Carbon Assessment and Management

Richard Birdsey, USDA Forest Service, rbirdsey@fs.fed.us (Presenter)
Yude Pan, USDA Forest Service, ypan@fs.fed.us
Fangmin Zhang, University of Toronto, zfmnuist@hotmail.com
Chen Chen, University of Toronto, jing.chen@utoronto.ca
Craig Wayson, USDA Forest Service, cwayson@fs.fed.us
Kristofer Johnson, USDA Forest Service, kristoferjohnson@fs.fed.us

Our team has developed continental-scale, spatially explicit ecosystem process models to assess historical trends in carbon stocks in forest biomass and soils, and to support strategic carbon management analysis at smaller, operational scales. To facilitate strategic analysis at a “management unit” level (e.g. National Forest or State), nested within the national context, this project has begun to explore the feasibility and validity of downscaling the national wall-to-wall analysis products. The primary pilot study area has been the Chequamegon-Nicolet National Forest and surrounding private and other public lands, though recently the project has begun to assess landscape-scale carbon assessment at two National Forests in the West and South. We have developed a new U.S. continental-scale application of an ecosystem process model known as InTEC, using a 1-km2 grid cell (He et al. 2011; Pan et al.2011; Zhang et al. 2011). The model is driven by climate, stand age (time since last disturbance), site productivity, and other variables that affect carbon stocks and changes in carbon stocks. Features of InTEC that are particularly suited to complement other ongoing Forest Service carbon assessment activities such as the greenhouse gas inventory of the forest sector reported to EPA include (1) results are tightly constrained to match recent productivity estimates from FIA, (2) all forest carbon pools are included in the analysis, notably soils (using the CENTURY model) which are not fully represented in other estimates, and (3) satellite-derived disturbance maps (from the NASA LEDAPS project) are used to capture major recent events.

Presentation Type:  Poster

Session:  Science in Support of Decision Making   (Wed 10:00 AM)

Associated Project(s): 

  • Related Activity

Poster Location ID: 124

 


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