scholarly journals Modeling Discards in Stock Assessments: Red Grouper Epinephelus morio in the U.S. Gulf of Mexico

Fishes ◽  
2021 ◽  
Vol 7 (1) ◽  
pp. 7
Author(s):  
Kyle W. Shertzer ◽  
Erik H. Williams ◽  
Skyler R. Sagarese

To be as accurate as possible, stock assessments should account for discard mortality in fisheries if it occurs. Three common approaches to modeling discards in assessments are to lump dead discards with landings, treat dead discards as their own fleet, or link them conversely with landings through use of a retention function. The first approach (lumping) implicitly assumes that the selectivity of landings applies also to discards. In many cases, that assumption is false, for example, if discards comprise smaller fish than do landings. The latter two approaches avoid the assumption by modeling discards explicitly with their own selectivity pattern. Here, we examine these approaches to modeling discards. Using a simulation study, we demonstrate that the two approaches to modeling discards explicitly can provide identical results under both static and time-varying conditions. Then, using a stock assessment case study of red grouper Epinephelus morio in the U.S. Gulf of Mexico, we demonstrate that in practice the approaches to modeling discards can provide different outcomes, with implications for the resultant management advice. We conclude by comparing and contrasting the different approaches, calling for more research to elucidate which approach is most suitable under various sources of error typically encountered in discard data.

2017 ◽  
Vol 193 ◽  
pp. 129-142 ◽  
Author(s):  
Arnaud Grüss ◽  
James T. Thorson ◽  
Skyler R. Sagarese ◽  
Elizabeth A. Babcock ◽  
Mandy Karnauskas ◽  
...  

2014 ◽  
Vol 72 (1) ◽  
pp. 99-110 ◽  
Author(s):  
Felipe Hurtado-Ferro ◽  
Cody S. Szuwalski ◽  
Juan L. Valero ◽  
Sean C. Anderson ◽  
Curry J. Cunningham ◽  
...  

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.


<em>Abstract.—</em> The stock assessment analyses of king and Spanish mackerel fisheries of the southeastern United States have a long history of incorporating uncertainty. The development of this philosophy resulted from a number of unique circumstances, both biological and historical, that encouraged the incorporation of stochastic approaches and risk evaluation to the assessment and management process. The progression from simple discrete decision tree analysis to delta methods to Monte Carlo/bootstrap methods was due not only to advances in assessment technology but also to changing requirements for management. The current method for mackerel stock assessment is a tuned virtual population analysis with uncertainty incorporated via a mixed Monte Carlo/bootstrap algorithm. Through this procedure, uncertainty in the tuning indices, catch-at-age and natural mortality rate are directly incorporated into the advice provided to management. The management advice is given in terms of probability statements, as opposed to point estimates, to reflect this uncertainty in the stock assessments. This approach is a result of the evolution of the assessment and management and provides a pragmatic alternative in the “frequentist versus Bayesian” debate.


Author(s):  
Skyler R Sagarese ◽  
Nathan R. Vaughan ◽  
John F Walter III ◽  
Mandy Karnauskas

Impacts of Karenia brevis red tide blooms have been an increasing cause of concern for fisheries management in the Gulf of Mexico (Gulf). The 2019 Gulf red grouper stock assessment was confronted with the challenges of quantifying and parameterizing red tides during both historical and projection time-periods. Red tide mortality was estimated for each age-class in the model solely in 2005 and 2014 during severe events. Given the considerable uncertainty surrounding the 2018 red tide and its substantial implications on the status of the population, several projection scenarios were evaluated. Under the assumption of no 2018 red tide mortality, near-term catches were projected to nearly double, a predicted outcome that appeared to be in contrast to recent record low catches and fishing industry perceptions of significant stock depletion. In the event that the 2018 red tide caused mortality, but was not accounted for in projections, the recommended catch levels would lead to high probabilities of overfishing and potentially stock collapse. Collectively, these results highlight how consideration of uncertainty in projections can help avoid unintended consequences.


2017 ◽  
Vol 75 (2) ◽  
pp. 596-609 ◽  
Author(s):  
Cody S Szuwalski ◽  
James N Ianelli ◽  
André E Punt

Abstract Retrospective patterns are consistent directional changes in assessment estimates of biomass in a given year when additional years of data are added to an assessment, and have been identified for a number of exploited marine stocks. Retrospective patterns are sometimes reduced by allowing population processes to vary over time in an assessment, but it is unclear how this practice influences management performance. We simulated stocks in which retrospective patterns were induced by forcing natural mortality, selectivity, or growth to vary over time. We then evaluated the impacts of reducing retrospective patterns by allowing population processes to vary in the assessment. In general, allowing selectivity, natural mortality, and growth to vary in the assessment decreased the magnitude of retrospective patterns in estimated spawning biomass, regardless of whether the true time-varying process was allowed to vary. However, the resulting reference points and management advice were sometimes drastically in error when a process other than the true time-varying process was allowed to vary, and these errors resulted in under-utilizing or over-exploiting the stock. Given the potential for error, identifying the important population processes that vary over time when addressing retrospective patterns should be a priority when providing management advice and may require increased longitudinal life history studies.


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