Skip to main content
ARS Home » Research » Publications at this Location » Publication #244516
Title: An analytical framework to assist decision makers in the use of forest ecosystem model predictions

Author
item LAROCQUE, GUY - Canadian Forest Service
item BHATTI, JAGTAR - Canadian Forest Service
item Ascough Ii, James
item LIU, JINXUN - Science Application International Corporation(SAIC)
item LUCKAI, NANCY - Lakehead University
item MAILLY, DANIEL - Canada Ministry Of Natural Resources
item ARCHAMBAULT, LOUIS - Canadian Forest Service
item GORDON, ANDREW - University Of Guelph

Submitted to: Journal of Environmental Modeling and Software
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/26/2010
Publication Date: 3/1/2011
Citation: Larocque, G.R., Bhatti, J.S., Ascough II, J.C., Liu, J., Luckai, N., Mailly, D., Archambault, L., Gordon, A.M. 2011. An analytical framework to assist decision makers in the use of forest ecosystem model predictions. Journal of Environmental Modeling and Software. 26(3):280-288.

Interpretive Summary: The predictions of most terrestrial ecosystem models originate from deterministic simulations. Relatively few uncertainty evaluation exercises in model outputs are performed by either model developers or users. This issue has important consequences for decision makers who rely on models to develop natural resource management policies, as they cannot evaluate the extent to which predictions stemming from the simulation of different management scenarios may result in significant environmental or economical differences. Different analytical methods, such as sensitivity, uncertainty analyses or bootstrap methods, can be used to evaluate models and the errors associated with their outputs. However, there are difficulties with the application of these methods and decision makers do not necessarily know how to deal with the outputs generated from them. In this paper, a decision flow chart is proposed to help decision makers apply, in an orderly manner, the different steps involved in examining the model outputs. The analytical framework is discussed with regards to the definition of the problems and objectives, model selection, identification of alternatives, modelling tasks and the selection of alternatives for developing policy or implement management scenarios. Its application is illustrated using an on-going exercise conducted in Ontario, Canada, to develop silvicultural guidelines for the forest management enterprise.

Technical Abstract: The predictions of most terrestrial ecosystem models originate from deterministic simulations. Relatively few uncertainty evaluation exercises in model outputs are performed by either model developers or users. This issue has important consequences for decision makers who rely on models to develop natural resource management policies, as they cannot evaluate the extent to which predictions stemming from the simulation of different management scenarios may result in significant environmental or economical differences. Different analytical methods, such as sensitivity, uncertainty analyses or bootstrap methods, can be used to evaluate models and the errors associated with their outputs. However, there are difficulties with the application of these methods and decision makers do not necessarily know how to deal with the outputs generated from them. In this paper, a decision flow chart is proposed to help decision makers apply, in an orderly manner, the different steps involved in examining the model outputs. The analytical framework is discussed with regards to the definition of the problems and objectives, model selection, identification of alternatives, modelling tasks and the selection of alternatives for developing policy or implement management scenarios. Its application is illustrated using an on-going exercise conducted in Ontario, Canada, to develop silvicultural guidelines for the forest management enterprise.