Estimating the Relative Abundance of Highly Migratory Bycatch Species

Due to vast spatial distributions and migrations, highly migratory fishes are notoriously difficult to monitor using independent research programs. Thus, the assessment and management of these populations relies heavily on the catch and effort dynamics of commercial and recreational fisheries. While fishery-dependent catch per unit of effort (CPUE) data may capture trends in abundance, they do not represent unbiased samples of the populations; therefore, to accurately estimate relative abundance these data must be standardized to account for factors that may have impacted CPUE but are not related to changes in abundance (i.e., changes in fishing practices). These considerations are particularly important for highly migratory bycatch species (e.g., sharks and billfishes) that are not directly targeted by fisheries. For these species, there may be occasional mismatches between the distribution of fishing effort and the distribution of bycatch species. Two commonly applied methods for standardizing CPUE include generalized linear models (GLMs), which can account for changes in fishing practices in a straightforward linear fashion, and habitat-based standardizations which use a nonlinear framework to directly relate the distribution of fishing effort to the species distribution. Here, we evaluate the accuracy of these methods in a simulation context under a range of potential population trajectories.