smartWhales: Applying integrated ecological modelling and operational systems to reduce risks to whales

Decision-support system forecasts whale movements and risk zones to enhance proactive regulatory decisions that protect North Atlantic Right Whales

With fewer than 350 individuals remaining, the North Atlantic Right Whale (NARW) is one of the world’s most endangered large whale species. These whales face threats from climate change-altered habitats, fishing gear entanglement and vessel strikes. To support conservation efforts, the Canadian Space Agency launched the smartWhales programme, funding research in two areas: Earth observation and ecological modelling. As part of this initiative, a team from WSP, DHI and their partners developed a decision-support system that forecasts where NARWs are likely to be based on habitat preferences and movement patterns. The system also includes forecasts of vessel movements and snow crab fisheries data in the Gulf of St. Lawrence, to simulate when and where whales may be at risk.

Challenge

The primary challenge addressed by the smartWhales programme was the lack of monitoring approaches and predictive tools capable of delivering sufficient spatiotemporal information on the location of NARWs and key stressors. This gap was seen as a hinderance to timely interventions, making it difficult to proactively mitigate vessel and fishing activities. Additionally, existing efforts were fragmented, with siloed data sources and modelling initiatives that limited effective decision-making. To tackle this, the team from DHI, WSP and their partners reframed the broader challenge into one that should apply existing data sources and innovative modelling technologies that improved the precision and effectiveness of existing vessel slow-down regulations and seasonal snow crab fishing restrictions. This included the goal to deliver an integrated decision support platform that provides regulatory agencies with proactive warnings of vessel–NARW collision risks, as well as early indications of periods when NARW movements overlap with snow crab fishing areas.

Solution

To support the protection of the endangered North Atlantic Right Whale (NARW), a pioneering ecological modelling driven web-based decision support system (DSS) was developed using MIKE Powered by DHI software. 

Solution highlights:

• A well-calibrated hindcast hydrodynamic model was established as the foundation for the overall integrated modelling framework
• A habitat suitability model was developed through use of hydrodynamic model results, various environmental datasets, a machine learning model and DHI’s habitat modelling scripts
• Via coupling with the hydrodynamic and habitat suitability models, an agent-based model was developed to provide realistic simulations of NARW movement and presence
• Vessel collision risk forecast modelling was carried out with ecological models (i.e., after conversion from hindcast to forecast mode) and machine learning model vessel trajectory forecasts
• The forecast ecological models and data on snow crab fisheries areas were used to generate a forecast model of snow crab fishing gear entanglement risk
• A NARW decision-support system (DSS) for the Gulf of St. Lawrence was developed through backend scheduling of forecasted models and a GIS-based frontend

The DSS ultimately provides a 3-day forecast of hydrodynamic conditions, NARW habitat suitability and movements, fishing gear entanglement risk, as well as a 12-hour vessel trajectory and collision risk forecast.