Decision support tools: Dynamic models

Aim of the study

Long-term, broad-scale monitoring of population trends is widely proposed as a means to assess forest sustainability. However, there is increasing evidence and opinion that long-term monitoring, especially at broad scales, is unable to provide useful information to address the most immediate concerns of forest management for sustainability. Long time periods and spatial scales, and often precipitous and dramatic declines, are required for trends to be detected with confidence. These time frames often prohibit effective and timely intervention, do not identify causes of decline and do not indicate what management changes may be required to halt species decline.

Because of these difficulties, habitat supply models are being used to predict habitat availability through time within production forests during the development of management plans. This approach allows for the consideration of the habitat requirements of focus species to be explicitly considered during the planning phase. However, environmental and demographic stochasticity or the spatial attributes of species biology such as dispersal and Allee effects are not considered. Consequently, these methods do not consider habitat composition and configuration or temporal fluctuations in habitat occupancy that in turn affect population persistence.

The objective of this study is to explore the utility of spatially explicit population models coupled with forest dynamics models as a tool for predicting the impact of alternative management scenarios on indicator species. To evaluate this approach we have developed 3 case studies (the brown creeper, the red-backed vole, the red-backed salamander) in a large, actively managed, boreal landscape in north-central Ontario. This tool will directly incorporate information on species biology, ecosystem processes, and proposed management activities over multiple scales of space and time. These models will allow us to predict detrimental effects on indicator species populations and hence forest functioning due to management activities. It directly considers uncertainty inherent in our knowledge base, natural processes, and the impacts of management activities on the landscape. This approach represents a significant improvement over existing forest reporting procedures and quantifies the risk to forest sustainability by management activities. This tool will assist managers in designing a management strategy to minimise long-term disturbance to the ecosystem.


  • Dr. Mark Burgman, University of Melbourne, Australia
  • Chris Grant, Domtar
  • Keith Wade and Jen Theberge, Pukaskwa National Park

Project status

  • On-going

Team members