Better models for fisheries

Biological modelling of food fish populations is extremely important for scientists in order to ensure the sustainable management of these resources. However, current models rely on inaccurate assumptions or incomplete data, resulting in flawed estimates of population size and strength.

The EU-funded ECOKNOWS (Effective use of ecosystem and biological knowledge in fisheries) project used biological data to produce generic probabilistic models for assessing fish stocks. The initiative integrated itself with and used data from an earlier fish database project called FISHBASE.

Researchers reviewed current fisheries models and concluded that scientists need to use a wider data set than is currently used for stock assessment. Therefore, a new probability-based model was created using data from FISHBASE, which took into account biological parameters such as reproduction dynamics and natural mortality.

ECOKNOWS methods and outcomes were added to the FISHBASE database and the models are now publically available. Researchers also built a tool to allow others to add data to FISHBASE, with built-in data quality control. The new models were applied to case studies on anchovies, salmon, hake and shrimp in various European bodies of water.

The general population dynamics models developed by the consortium can realistically account for remaining uncertainty regarding the current and future states of the fish stock. They can be adopted by fisheries stock assessment groups around the world and used to avoid overfishing and consequent socioeconomic losses.

Furthermore, the use of more realistic assumptions in fish stock assessment will enhance the credibility of the assessment results and increase stakeholder commitment to management actions based on those results.