Contemporary Models in Fish Population Dynamics

Models for the dynamics of commercially-utilized fish populations, so-called “fishery models”, are ubiquitous in our times, but new issues arise as models become more and more complex. Current models incorporate biological processes such as reproduction, mortality, and growth. These models integrate diverse data sources such as indices of abundance from the fishery(ies) and from biological surveys, sampling information about age, length, and sex composition from the fishery and from biological surveys, estimates of reproductive parameters, such as maturity and fecundity, and other life history information (e.g., natural mortality, predation, and disease). A common example is the age-structured assessment (ASA) or catch-age model. Complex models are necessary to effect the integration of data sources with population dynamics, though some question whether complexity is becoming excessive. There are three major components of these fishery models: (1) the population dynamics in terms of equation to describe the process of year-classes over time, (2) statistical errors in measurement and process, and (3) an objective function for minimizing the differences between observations and model predictions as a function of population parameters. I review these contemporary models and provide an overview of recent developments to incorporate temporal and spatial variation through stochastic, state-space, and Bayesian models.