Addressing complex fleet structure in fishery stock assessment models: Accounting for a rapidly developing pot fishery for Alaska sablefish (Anoplopoma fimbria)

Fisheries management operates under uncertainty, often driven by the dynamic nature of marine ecosystems and associated fisheries. Stock assessment models, which form the scientific basis of decision-making in fisheries management, strive for realistic representations of biological and fishery processes. However, data limitations and knowledge gaps necessitate simplifying assumptions for representing these complex bio-socioeconomic systems, which can increase uncertainty in the assessment process. Addressing time-varying fishery dynamics (i.e., due to regulatory changes or alterations in harvester behavior) is a common and particularly challenging problem for stock assessment models. Time-varying fishery selectivity is widely utilized to address changes in fishery dynamics but may not be adequate when regulatory changes substantially alter gear usage and associated assessment fleet structures. We explore the implications of accounting for, or ignoring, complex temporal changes in fleet structure and selectivity within stock assessment models by utilizing a recent and high-value case study, Alaska sablefish (Anoplopoma fimbria). Our findings demonstrate that the treatment of fleet structure (i.e., adding fleet complexity to account for gear transitions) did not greatly influence estimates of spawning biomass trajectories. However, associated selectivity assumptions had substantial impacts on sustainable harvest recommendations. We recommend that the treatment of fleet structure and associated selectivity assumptions should incorporate a priori considerations and subject-matter expertise of fishery and biological dynamics to ensure pragmatic and appropriate model parameterizations. Moreover, we advocate for multi-fleet models as a useful diagnostic tool for validating model estimates from single-fleet assessments when uncertainty in fleet dynamics exist.