Towards Sustainable Fisheries: State Space Assessment Models for Complex Fisheries and Biological Data

Why Study Complex Data from Fisheries?

Fisheries scientists collect biological and fisheries data to perform stock assessments. These provide resource managers with information required to regulate fish stocks. 

If fisheries scientists can reliably estimate the biomass of the stock, then they can additionally estimate how many fish can be safely removed from the stock, while ensuring a sustainable resource.

Areas of Exploration

Stock Assessment Models

Includes combining biological and fisheries data into stock assessment models, to estimate the total population or biomass of a given stock. These models make it possible to assess the status and condition of the stock, as well as predict how it will respond to varying levels of fishing pressure in the future. 

Overfishing

Includes analyzing sustainable fishing levels. Overfishing is a global problem that threatens fish stocks and employment, with many serious social, economic, and environmental consequences. The key goals of fisheries management are to eliminate over-fishing and restore stocks that have been previously overfished.

Efficiency in SSAMs

Includes using the Laplace approximation to implement and estimate State-Space Assessment Models (SSAMs). With recent software advancements, these models can be routinely used to manage important fish stocks.

Solving Global Challenges

Research Team’s Goal

To help develop conservation practices for fisheries by improving statistical tools for stock assessment.

Area of Impact

The complex SSAMs required in the field of fish stock assessment make it an interesting and fruitful field for applied statisticians. Further development of the underlying theory and supporting statistical software is necessary, along with the training of qualified personnel in Canada. 
More than 20 official fish stock assessments in the International Council for the Exploration of the Seas are now conducted with SSAMs. The availability of software to easily express and efficiently estimate these models has made all the difference.