Samuel Johnson

PhD Candidate

Education

  • B.Math Honours, University of Newcastle
  • MSc, Mathematics, Simon Fraser University

Biography

I’m interested in non-traditional approaches to multi-species fisheries management. Multi-species fisheries contain a mix of low and high commercial value species that are caught together, but attract different shares of available management resources due to their values. Those species with low commercial value often do not attract the resources for dedicated single-species assessment and management, and as a result are often managed using uncertain and out of date information. Decisions made based on out-of-date information can lead to overfishing, and without assessments overfishing can go un-noticed and uncorrected, endangering future productivity of the fishery. Furthermore, low-value species often have poor data (low quality) or are data-poor (very little data exists), which precludes management using traditional means. 

My research is focused on how to use modern statistical methods to assess and manage multi-species complexes containing evolutionarily similar fish with contrasting data qualities and availabilities. By grouping species in this way, information can be shared among species to increase assessments and produce more scientifically defensible fisheries management.