Fishermen rely on their on-the-water experience to know where and when to find certain species of fish in the Gulf of Maine, and managers use their knowledge of fish and the fishery to design management policies, such as seasonal closures, aimed at ensuring sustainability. The ability to understand where fish are likely to be and when they are likely to be there is critical for the sustainable management of the region's valuable fisheries.

The Maine NASA EPSCoR (Established Program to Stimulate Competitive Research) project is a collaborative project aimed at developing models that link remotely sensed ocean conditions with the spatiotemporal distributions of key fish species. Scientists from the Gulf of Maine Research Institute, Bigelow Laboratory for Ocean Sciences, and NASA Jet Propulsion Laboratory collaborated on using a statistical approach called Maximum Entropy (MaxEnt) to build models relating the occurrence of fish to high-resolution environmental information measured by NASA satellites. This approach was applied to several important fishery species including Atlantic herring, Atlantic mackerel, and butterfish in the Northwest Atlantic Shelf area. Monthly habitat suitability maps were produced (e.g., Figure, left), the relative influence of environmental factors on fish distributions was assessed (Figure, right), and the predictive ability of the MaxEnt models was evaluated using hindcasts of fish distributions in recent years. Results from the project showed that the MaxEnt models did a good job explaining past changes in fish distributions, showed good predictive ability in hindcasts, and therefore have the potential to provide forecasts of future distributions of these species which serve an important role as prey for commercially important fish (e.g., bluefin tuna). The models also provided insights into what processes drive the distributions of these fish. This MaxEnt modeling framework allowed us to integrate fish records from commercial fisheries and high-resolution environmental data from NASA satellites to describe the spatiotemporal distributions of important fishery species.

Dataset NameProcessing
Level
Start/StopFormatSpatial ResolutionTemporal
Resolution
GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis (v4.1)42002-Jun-01 to PresentNETCDF0.01 degrees (Latitude) x 0.01 degrees (Longitude)1 Day