About the project

Additional information

Questions regarding the project should be directed to Dr Griess. For information on the Department of Forest Resources Management at UBC, visit http://frm.forestry.ubc.ca. For information on Dr. Griess’ working group, FRESH (Forest Resources and Environmental Services Hub) visit http://fresh.forestry.ubc.ca

 About the project:

As part of a large scale applied research project will develop a decision support system (DSS) that integrates the risk of invasive species outbreaks with related economic consequences. Our forest DSS will help inform management decisions of end users such as government, provincial departments of natural resources, and international authorities.A robust DSS requires accurate estimates of risk, impact, and the financial costs of an invasion. To fill this knowledge gap, we will use tools from mathematical finance, as well as operations research, to build a risk sensitive DSS that will be translated into a software application available to our end-users.Earlier DSS developed for pest management in Canada focused mainly on timber supply losses but identified a need for incorporating other forest values. Our DSS will incorporate timber supply, forest structure, and a detailed cost-benefit analysis of mitigation strategies under several pest threat scenarios.One key feature of our DSS will be a mechanism to search for the best mitigation option(s) based on user-selected criteria. We intend to develop a DSS driven by economic criteria, but we will allow end users to select other indicators of interest (eg forest loss, lowest costs or others) and provide tabular and graphical outcomes based on those selections.The DSS will integrate existing pest risk assessment data, as well as related social, economic and ecological information to select appropriate risk management approaches. We will develop pre-defined scenarios along with a risk management continuum ranging from ‘do nothing’ to ‘implement immediate eradication’, as well as the related sensitivity analyses. The DSS will be developed using a modular approach which ensures a flexible, adaptable framework into which data components can be added as they are develope