Application of big data for fisheries prediction and management

Problem addressed

Although the sector and the scientific community generate large volumes of data (catches, fishing effort, oceanographic and satellite variables), these data are often not used efficiently. This limits the ability to anticipate future scenarios, reduces the effectiveness of management measures, and increases uncertainty for fishing fleets.

What we do and how we do it

• We apply machine learning algorithms and ecological niche models that integrate historical catch records, genetic information, oceanographic data (temperature, chlorophyll, currents) and fishing activity.
• This approach generates biomass predictions and probability maps of the presence of commercial species.
• Results are delivered through digital platforms, technical reports and practical tools designed for fishing fleets and management authorities.

Key benefits

• More accurate predictions to reduce uncertainty in management.
• Tools that support improved planning of fishing campaigns.
• Optimal use of available information, transforming scattered data into practical knowledge.
• Enhanced competitiveness and sustainability of the fisheries sector.