WWETAC Projects
Project Title: Evaluation of models used to predict postfire tree mortality
Status: Ongoing
Principal Investigators: David Shaw, Stephen Fitzgerald, and Travis Woolley, Department of Forest Engineering, Resources and Management; Lisa Ganio, Department of Forest Ecosystems and Society, Oregon State University, Corvallis, Oregon
Collaborator: Terry Shaw, USDA Forest Service, Pacific Northwest Research Station, WWETAC, Prineville, OR
E-mail Contact: David Shaw, dave.shaw[at]oregonstate.edu
Key Issues/Problems Addressed: With increasingly large fires occurring throughout the West, there is much interest by land managers in being able to predict postfire tree mortality. Several review papers have summarized the variety of ways that researchers have sought to measure tree injury (condition) and then predict postfire mortality (See for example, Fowler, J.F.; Sieg, C.H. 2004. Postfire Mortality of Ponderosa Pine and Douglas-fir: a review of methods to predict tree death. Gen. Tech. Report RMRS-GTR-132. U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station.). However, there has never been a synthesis or comparison of the variety of models and their structure used to predict postfire tree mortality. Over 30 models have been developed to predict postfire mortality. Most of these are regression models developed from geographically local, empirical data that encompass a wide variety of fire scenarios such as summer or fall wildfires, and spring, summer, or fall prescribed burns for example.
Study Objectives and Goals: Objectives of the study are to summarize and review all existing postfire tree mortality models on western coniferous forests, and provide a reference-able citation for scientists on the models used to predict postfire tree mortality.
General Description: We will summarize and compare characteristics of existing models developed to predict postfire tree mortality. The summaries provided to the Western Wildland Environmental Threats Assessment Center and the USFS will form an accessible review of all existing models. A second objective is to publish this review/synthesis in a peer-reviewed journal so that the information is widely available and to identify groups of structurally similar models.
Status: Began July, 2007.
Deliverables:
OSU will:
- Provide list of all published post fire mortality models.
- Provide a summary of the characteristics of the source data for each model.
For example:
a. Geographic extent and resolution of the source data
b. Fire type—wildfire or prescribed fire
c. Timing of burn: either spring/early summer or late summer/fall
d. Geographic extent of burn
e. Tree species used and the range of diameter at breast height used for each species
f. Variation in fire severity - Summary of model features for each model. For example:
a. Type of model (e.g., logistic regression, multiple regression)
b. Multi- or single-species model
c. Explanatory variables used in the model
d. Range (min, max) of data for each variable in the model
e. Estimated model parameters with estimated standard errors
f. Can the model interface with Forest Vegetation Simulator (FVS)
g. Any unidentified features which impact applicability - Identification and summary of subsets of models with similar data characteristics and model features. Variation among models within a subset demonstrates the extent to which postfire mortality prediction models are similar and variation among subsets identifies the degree to which prediction models differ.
- Develop and apply a set of criteria to evaluate the user-friendliness of each model. Evaluate of the major pros and cons of applying each model to a broad geographic area.
Background Citations:
An example of several papers that have published models which would be included in our analysis:
Regelbrugge, J.C.; Conard, S.G. 1993. Modeling tree mortality following wildfire in Pinus ponderosa forest in central Sierra Nevada of California. International Journal of Wildland Fire. 3: 139-148.
Ryan, K.C.; Peterson, D.L.; Reinhardt, E.D. 1988. Modeling long-term fire-caused mortality of Douglas-fir. Forest Science. 34: 190-199.
Seig, C.H.; McMillin, J.D.; Fowler, J.F.; Allen, K.K.; Negron, J.F.; Wadleigh, L.L.; Anhold, J.A.; Gibson, K.E. 2006. Best predictors for postfire mortality of ponderosa pine trees in the intermountain West. Forest Science. 52: 718-728.
Thies, W.G.; Westlind, D.J.; Loewen, M.; Brenner, G. 2006. Prediction of delayed mortality of fire-damaged ponderosa pine following prescribed fires in eastern Oregon, USA. International Journal of Wildland Fire. 15: 19-29.
Web Sites:
David Shaw:
http://www.forestry.oregonstate.edu/cof/fs/people/faculty/shaw.php; http://www.cof.orst.edu/coops/sncc/
Lisa Ganio:
http://www.forestry.oregonstate.edu/cof/fs/people/faculty/ganio.php
Steve Fitzgerald:
http://extension.oregonstate.edu/deschutes/index.php
Project ID: FY07TS29
