Ecological Considerations in Modelling to Reduce Risk of Wildfires
Presenter(s)
John Hearne
Abstract
Wildfires are a threat to communities in many parts of the world and there is general consensus that this threat will be aggravated by climate change. Mechanical clearing and controlled burning are methods used to reduce fuel loads in the landscape and hence the risk of wildfires. But these actions impact on the habitat needs of fauna. Flora also have limited tolerances to such disturbances while fire-dependent species require a certain frequency of burning. Further given constraints on resources to accomplish fuel-reduction tasks the question of "where to burn when" becomes complex. A spatio-temporal mixed integer programming model will be presented and illustrated to deal with this problem. The model attempts to maximise the spatial fragmentation of high fuel load while maximising connectivity of habitat.
Topic
Forestry
Start Date
6-17-2016 10:30 AM
End Date
6-17-2016 10:50 AM
Room
High Country Conference Center
Recommended Citation
Hearne, John, "Ecological Considerations in Modelling to Reduce Risk of Wildfires" (2016). World Conference on Natural Resource Modeling. 17.
https://scholarexchange.furman.edu/rma/all/presentations/17
Ecological Considerations in Modelling to Reduce Risk of Wildfires
High Country Conference Center
Wildfires are a threat to communities in many parts of the world and there is general consensus that this threat will be aggravated by climate change. Mechanical clearing and controlled burning are methods used to reduce fuel loads in the landscape and hence the risk of wildfires. But these actions impact on the habitat needs of fauna. Flora also have limited tolerances to such disturbances while fire-dependent species require a certain frequency of burning. Further given constraints on resources to accomplish fuel-reduction tasks the question of "where to burn when" becomes complex. A spatio-temporal mixed integer programming model will be presented and illustrated to deal with this problem. The model attempts to maximise the spatial fragmentation of high fuel load while maximising connectivity of habitat.