Forest ecosystem carbon models: structure and suitability for current issues on the West Coast of North America
| Authors: | Andrew Gray, Taylor K. Lucey, David V. D'Amore, John B. Kim, David L. Nicholls, Nadia A. Tase, Andrew C. Yost, Jeffrey D. Kline, Jeremy S. Fried, Daniel E.B. Swann |
| Year: | 2026 |
| Type: | General Technical Report |
| Station: | Pacific Northwest Research Station |
| DOI: | https://doi.org/10.2737/PNW-GTR-1046 |
| Source: | Gen. Tech. Rep. PNW-GTR-1046. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. 89 p. (Online Only). |
Abstract
Increasing carbon dioxide and other greenhouse gases (GHG) in the atmosphere are warming and changing climate globally. Policymakers and land managers want to know the effectiveness of different approaches to reduce the increase in GHG while mitigating effects of future climate change. Forests can store large amounts of carbon and can gain or lose carbon relatively rapidly, making them a focus of study. A variety of ecosystem models have been applied to estimate hard-to-measure forest stocks and processes and to project alternative management scenarios into the future.
We examined the structure and application of ecosystem models for carbon projections, focusing on the West Coast of the United States and Canada. Our goals were to help scientists and managers (1) select models that best address specific questions, and (2) evaluate model results given inherent uncertainties embedded in the data, calibration, and assumptions used. We describe the primary functional attributes of biophysical process, individual-tree, stand growth and yield, landscape process, state-and-transition, and imputation models, and their application to West Coast forests. We discuss the strengths and limitations of each model type for questions concerning climate change, tree harvest, wildfire and fuel reduction treatments, other disturbances, social and economic drivers, hydrology, and wildlife. No single model can simulate forest management, disturbance, and response to climate change well. Efforts using models with different strengths, focusing on consistent parameterization of vegetation, definition of initial conditions and scenarios, and metrics for results, can improve forest carbon projections.
Supplemental table 1 to accompany this report is available here.