Predicting changes in biodiversity
Axis 3 themes
Theme 3.1: Scenarios
This axis will accelerate the development of biodiversity predictions at multiple levels and time intervals. This will combine the latest computational and statistical technologies with machine learning, iteratively trained and updated with data obtained from field monitoring (Axis 1), including high-throughput methods, remote sensing, as well as EBVs and other relevant biodiversity indicators (and their drivers of change) from Axis 2. Our forecasts will be based on scenarios (derived from Axis 4) produced by partner organizations (e.g., Ouranos).
Theme 3.2: Models
Examples of relevant forecasts that QCBS will publish are species extinctions/invasions, and trends in species abundance and geographic distribution .
Key partners supporting this axis include leaders in artificial intelligence (MILA, IVADO, CRIM), the OE initiative, and the NSERC CREATE programs in biodiversity data analysis (BIOS2, BEES).