Paradigm shifts in fisheries stock assessment: From integrated analysis to bayesian analysis and back again

Abstract

I describe integrated analysis and Bayesian analysis, which have been two of the most influential paradigms in fisheries stock assessment during the last two decades of the twentieth century. These two paradigms have generally been considered complementary, rather than competing. However, recent advances in integrated analysis, including the special case of meta-analysis, have made Bayesian analysis somewhat redundant. I describe how data used to create priors for use in Bayesian analysis can be integrated directly into the analyses. This provides a much more convenient way of accurately including the information and associated uncertainty into the analyses. I discuss how there is still a need to describe the uncertainty and suggest that research should focus on the most appropriate methods for doing this. © 2003 Rocky Mountain Mathematics Consortium.