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

Abstract 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.