Looking in the rear-view mirror: bias and retrospective patterns in integrated, age-structured stock assessment models

Abstract

Retrospective patterns are systematic changes in estimates of population size, or other assessment model-derived quantities, that occur as additional years of data are added to, or removed from, a stock assessment. These patterns are an insidious problem, and can lead to severe errors when providing management advice. Here, we use a simulation framework to show that temporal changes in selectivity, natural mortality, and growth can induce retrospective patterns in integrated, age-structured models. We explore the potential effects on retrospective patterns of catch history patterns, as well as model misspecification due to not accounting for time-varying biological parameters and selectivity. We show that non-zero values for Mohn’s ρ (a common measure for retrospective patterns) can be generated even where there is no model misspecification, but the magnitude of Mohn’s ρ tends to be lower when the model is not misspecified. The magnitude and sign of Mohn’s ρ differed among life histories, with different life histories reacting differently from each type of temporal change. The value of Mohn’s ρ is not related to either the sign or magnitude of bias in the estimate of terminal year biomass. We propose a rule of thumb for values of Mohn’s ρ which can be used to determine whether a stock assessment shows a retrospective pattern.

Retrospective forecasting — evaluating performance of stock projections for New England groundfish stocks

“…ICES (2007) conducted such simulation testing and found that the cause of a retrospective pattern could not be identified based on any of the explored diagnostics. This result was recently confirmed by Hurtado-Ferro et al (2015) using a more extensive factorial design. Preliminary management strategy evaluations demonstrated that fixing the retrospective pattern, even using the wrong fix relative to the true cause, produced better performing management advice than ignoring the retrospective pattern (ICES 2008).…”

Forage fish fisheries management requires a tailored approach to balance trade‐offs

“…Though not addressed in this analysis, bias in biomass estimates is also an important consideration for managers. Retrospective bias, which might arise from unanticipated changes in growth or mortality (Hurtado‐Ferro et al., ), could compound the negative impacts of delayed detection and should be considered when testing potential control rules for specific populations. Additionally, although we assume in this analysis that reference points are known by the managers, over‐ or underestimation of those reference points can lead to changes in control rule performance.…”

Growth and Stock Estimation of Greenback Mullet, Liza subviridis (Valenciennes, 1836) from Parangipettai Waters (Southeast Coast of India)

“…Information on biology and population dynamics is essential for monitoring the rational exploitation and management of the stock (Mehanna 2007). Recent studies (detailed in Deroba et al 2015;Hurtado-Ferro et al 2015;Johnson et al 2015;Ono et al 2015) suggested that there are many challenges still to be resolved when applying multiple models to a single stock.…”