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sector_ico_Forestry_trans Forestry

BioSurveillance of Alien Forest Enemies (bioSAFE)

  • Project Leaders: Richard Hamelin, Cameron Duff, Ilga Porth
  • Institutions: University of British Columbia (UBC)
  • Budget: $8877597
  • Program/Competition: Large Scale Applied Research Programs
  • Genome Centre(s): Genome Canada
  • Fiscal Year: 2016
  • Status: Closed

Forests are a crucial part of Canada’s cultural, social and economic fabric. However, invasive alien species and diseases threaten our forests and cause potentially irreversible damage leading to estimated economic losses of $800 million a year. Asian long-horned beetle, Dutch elm disease, sudden oak death and spongy moth are high priority species and diseases not native to Canada. They arrive through the imported goods pathway and pose an economic and environmental threat. To protect our forests, Dr. Hamelin and his expert team developed new genomic tools designed to protect our forests from these invasive species.

Detecting these invaders is crucial to protecting our forests, so the research team began by generating genomic profiles for each of the four menaces. They used global sources to sequence samples of each of these four pests. Using these genomic resources, diagnostics tools were developed and deployed. Forest health professionals can now swiftly and accurately identify harmful species and pinpoint the source of the threat by analyzing samples from traps or infected plants. Early detection can eliminate threats at the source and are an efficient way to prevent future invasions.

Due to genetic variation within species, some individuals pose more of a threat than others. For example, some moths may be able to fly longer distances and invade new territory, while certain pathogens may withstand colder temperatures, allowing them to survive the harsh winters and become established. The research team identified genetic markers associated with the invasive traits of a pest and how much damage it may inflict. By combining this data, the research team developed a prototype algorithm for spongy moth which predicts the potential damage an invader might cause based on its possible invasive traits. The prototype decision support system permits forest management officials to predict pathogenicity based on genomic profiles, allowing them to understand and anticipate the magnitude of the problem. This aides in pest management and mitigation decision making, allowing the elimination of threats using cost-effective and efficient strategies.

The development of these tools empowers forest health professionals to protect our forests, laying the foundation for preventing future invasions and maintaining the productivity of this socially and economically important Canadian resource.