The longer the better? Trade-offs in fisheries stock assessment in dynamic ecosystems

Environmental change and anthropogenic activity, alone or in combination, may cause vital rates of fish populations to exhibit low-frequency, large-magnitude variation leading to non-stationary population processes in inherently dynamic ecosystems. It remains unclear why, when and, so, whether, non-stationary population processes should be taken into account in fisheries stock assessment models. Here, we clarify the necessity and conditions for including non-stationary population processes in stock assessment models. Specifically, the convention of treating population vital rates with constant parameters might be unreliable under regime shifts characterized by low-frequency, large-magnitude variation in drivers of fish population dynamics. We hypothesized and simulated effects of a U-shaped trade-off between the length of time-series data and model estimation error for fish populations exhibiting non-stationary dynamics. In the case of low-frequency, large-magnitude variation, when measurement errors were small, the effects of non-stationary population processes were stronger than otherwise. Including time-varying parameters of population vital rates in the assessment model resolved this dilemma as anticipated, albeit at the cost of increased model complexity, suggesting that accounting for non-stationarity with time-varying parameters alone may not be sufficient to improve stock assessments and other approaches should also be considered.

Automated summary

This study clarified the necessity and conditions for including non-stationary population processes in stock assessment models, highlighting the unreliability of conventional constant parameter models under regime shifts characterized by low-frequency, large-magnitude variation in drivers of fish population dynamics.