Genomics-Enhanced Forecasting Tools to Secure Canada's Near-Term Lignocellulosic Feedstock Supply for Bioenergy using the Mountain Pine Beetle System
Janice Cooke, Joerg Bohlmann
University of Alberta, University of British Columbia
The Tria Project
Research Funding Program:
Applied Genomics Research in Bioproducts or Crops (ABC)
The recent mountain pine beetle outbreak in British Columbia, now spreading into Alberta, has caused unprecedented damage to the Canadian forest industry. The current infestation has affected more than 14 million hectares of pine forests and is the largest such epidemic in recorded history. Conifer forests are Canada’s largest renewable source of ligno-cellulose, used for energy production, paper and wood products. Understanding the biology of the mountain pine beetle in order to use that knowledge for anticipating and helping to control future outbreaks is an important contribution to Canadian forest economics, particularly related to energy production. Although massive amounts of dead timber from the mountain pine beetle epidemic have created an unexpected surplus of potential energy feedstock, this will not necessarily provide a sustainable feedstock supply in the future. Before strategic investments are made in the forest industry, current methods of predicting feedstock need to be improved.
An integrated team of social science and humanities (SSH) investigators with experience in environmental risk assessment will use genomic data in developing models for forecasting the possibility of future pine-beetle outbreaks in both time and geographical location.
The investigators will model the spread and likelihood of a pine-beetle outbreak using genomic data for the pine beetle and its associated fungal species. Then, they will use these data to devise environmental-risk models to improve our capacity to estimate the likelihood of outbreaks of mountain pine beetle infestations. This will allow more accurate estimates of fibre supply. The team will then combine this information with estimates of forest-deterioration rates due to the pine beetle with economic variables such as prices of bioenergy, costs, and discount rates. Finally they will weave all this information into a model that will elucidate the viability of the bioenergy industry given the variability of prices and of feedstock availability.
Investigators anticipate that this project will help clarify the economic potential of the bioenergy industry in Canada and inform decisions regarding investment in bioenergy facilities.