Simulating the impacts of disturbances on forest carbon cycling in North America: Processes, data, models, and challenges
Article first published online: 8 NOV 2011
Copyright 2011 by the American Geophysical Union.
Journal of Geophysical Research: Biogeosciences (2005–2012)
Volume 116, Issue G4, December 2011
How to Cite
2011), Simulating the impacts of disturbances on forest carbon cycling in North America: Processes, data, models, and challenges, J. Geophys. Res., 116, G00K08, doi:10.1029/2010JG001585., et al. (
- Issue published online: 8 NOV 2011
- Article first published online: 8 NOV 2011
- Manuscript Accepted: 9 AUG 2011
- Manuscript Revised: 5 AUG 2011
- Manuscript Received: 20 OCT 2010
 Forest disturbances greatly alter the carbon cycle at various spatial and temporal scales. It is critical to understand disturbance regimes and their impacts to better quantify regional and global carbon dynamics. This review of the status and major challenges in representing the impacts of disturbances in modeling the carbon dynamics across North America revealed some major advances and challenges. First, significant advances have been made in representation, scaling, and characterization of disturbances that should be included in regional modeling efforts. Second, there is a need to develop effective and comprehensive process-based procedures and algorithms to quantify the immediate and long-term impacts of disturbances on ecosystem succession, soils, microclimate, and cycles of carbon, water, and nutrients. Third, our capability to simulate the occurrences and severity of disturbances is very limited. Fourth, scaling issues have rarely been addressed in continental scale model applications. It is not fully understood which finer scale processes and properties need to be scaled to coarser spatial and temporal scales. Fifth, there are inadequate databases on disturbances at the continental scale to support the quantification of their effects on the carbon balance in North America. Finally, procedures are needed to quantify the uncertainty of model inputs, model parameters, and model structures, and thus to estimate their impacts on overall model uncertainty. Working together, the scientific community interested in disturbance and its impacts can identify the most uncertain issues surrounding the role of disturbance in the North American carbon budget and develop working hypotheses to reduce the uncertainty.