scholarly journals A simulation study of the implications of age-reading errors for stock assessment and management advice

2003 ◽  
Vol 60 (2) ◽  
pp. 314-328 ◽  
Author(s):  
Stuart A. Reeves
Keyword(s):  
Stock Assessment ◽  
Age Determination ◽  
General Tendency ◽  
Fishing Mortality ◽  
Absolute Level ◽  
Total Allowable Catch ◽  
Reading Errors ◽  
Stock Assessments ◽  
Management Advice ◽  
Age Reading

Abstract Catch-at-age data are a crucial input to many stock assessments, so errors in age determination could have an adverse effect on the quality of the stock assessment and the scientific advice based on that assessment. The results of simulation studies presented in this study are intended to quantify the effects of age-reading errors on the perception of stock trends and short-term management advice. The study is based on Eastern Baltic cod, in which problems with consistent interpretation of otolith structures result in the catch-at-age data being particularly problematic. The results indicate a clear distinction between the performance of the assessment, and the performance of catch forecasts and advice based on that assessment. The ageing error affected the absolute level of estimates of fishing mortality and spawning stock biomass from stock assessments, although overall trends are similar, and general conclusions about the state of the stock are likely to be broadly correct. Greater problems arose in catch forecasts and advice, for which ageing error led to discrepancies between the required and the effective fishing mortality, and a general tendency for ageing error to lead to advice on Total Allowable Catch that would be too optimistic and, therefore, less effective for stock conservation.

scholarly journals Time-varying natural mortality in fisheries stock assessment models: identifying a default approach

2014 ◽  
Vol 72 (1) ◽  
pp. 137-150 ◽  
Author(s):  
Kelli F. Johnson ◽  
Cole C. Monnahan ◽  
Carey R. McGilliard ◽  
Katyana A. Vert-pre ◽  
Sean C. Anderson ◽  
...  
Keyword(s):  
Stock Assessment ◽  
Assessment Method ◽  
Reference Points ◽  
Natural Mortality ◽  
Time Varying ◽  
Fishing Mortality ◽  
Total Allowable Catch ◽  
Robust Approach ◽  
Structured Population Models ◽  
Trade Offs

Abstract A typical assumption used in most fishery stock assessments is that natural mortality (M) is constant across time and age. However, M is rarely constant in reality as a result of the combined impacts of exploitation history, predation, environmental factors, and physiological trade-offs. Misspecification or poor estimation of M can lead to bias in quantities estimated using stock assessment methods, potentially resulting in biased estimates of fishery reference points and catch limits, with the magnitude of bias being influenced by life history and trends in fishing mortality. Monte Carlo simulations were used to evaluate the ability of statistical age-structured population models to estimate spawning-stock biomass, fishing mortality, and total allowable catch when the true M was age-invariant, but time-varying. Configurations of the stock assessment method, implemented in Stock Synthesis, included a single age- and time-invariant M parameter, specified at one of the three levels (high, medium, and low) or an estimated M. The min–max (i.e. most robust) approach to specifying M when it is thought to vary across time was to estimate M. The least robust approach for most scenarios examined was to fix M at a high value, suggesting that the consequences of misspecifying M are asymmetric.

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
Keyword(s):  
Gulf Of Mexico ◽  
Stock Assessment ◽  
Time Varying ◽  
Discard Mortality ◽  
Stock Assessments ◽  
Epinephelus Morio ◽  
Red Grouper ◽  
Management Advice ◽  
The U.S

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.

scholarly journals “The Elephant in the Room”: Exploring Natural Mortality Uncertainty in Statistical Catch at Age Models

2020 ◽  
Vol 7 ◽  
Author(s):  
Alessandro Mannini ◽  
Cecilia Pinto ◽  
Christoph Konrad ◽  
Paraskevas Vasilakopoulos ◽  
Henning Winker
Keyword(s):  
Stock Assessment ◽  
Assessment Process ◽  
Sensitivity Analyses ◽  
Fish Stock ◽  
Natural Mortality ◽  
Fishing Mortality ◽  
Food And Agriculture ◽  
Stock Assessments ◽  
The Mediterranean ◽  
The Impact

The natural mortality rate (M) of a fish stock is typically highly influential on the outcome of age-structured stock assessment models, but at the same time extremely difficult to estimate. In data-limited stock assessments, M usually relies on a range of empirically or theoretically derived M estimates, which can vary vastly. This article aims at evaluating the impact of this variability in M using seven Mediterranean stocks as case studies of statistical catch-at-age assessments for information-limited fisheries. The two main bodies carrying out stock assessments in the Mediterranean and Black Seas are European Union’s Scientific Technical Economic Committee for Fisheries (STECF) and Food and Agriculture Organization’s General Fisheries Commission for the Mediterranean (GFCM). Current advice in terms of fishing mortality levels is based on a single “best” M assumption which is agreed by stock assessment expert working groups, but uncertainty about M is not taken into consideration. Our results demonstrate that not accounting for the uncertainty surrounding M during the assessment process can lead to strong underestimation or overestimation of fishing mortality, potentially biasing the management process. We recommend carrying out relevant sensitivity analyses to improve stock assessment and fisheries management in data-limited areas such as the Mediterranean basin.

Incorporating Uncertainty into Fishery Models

2002 ◽  
Keyword(s):  
Monte Carlo ◽  
Stock Assessment ◽  
Population Analysis ◽  
Current Method ◽  
Spanish Mackerel ◽  
Virtual Population ◽  
Stock Assessments ◽  
History Of ◽  
Management Advice ◽  
Bootstrap Algorithm

<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.

scholarly journals Does recreational catch impact the TAC for commercial fisheries?

2014 ◽  
Vol 72 (2) ◽  
pp. 450-457 ◽  
Author(s):  
Margit Eero ◽  
Harry V. Strehlow ◽  
Charles M. Adams ◽  
Morten Vinther
Keyword(s):  
Fisheries Management ◽  
General Framework ◽  
Stock Assessment ◽  
Commercial Fisheries ◽  
Crucial Aspect ◽  
Total Allowable Catch ◽  
Fish Stocks ◽  
Management Advice ◽  
The Impact ◽  
Baltic Cod

Abstract The western Baltic cod is one of the first fish stocks in Europe that, since 2013, includes recreational catches in stock assessment and fisheries management advice. In this paper, we investigate the sensitivity of the calculated commercial total allowable catch (TAC) to including recreational catches in stock assessment. Our results show that the most crucial aspect in terms of the impact on commercial TAC is the assumption on recreational catch dynamics relative to that of commercial fisheries used in forecast. The results were less sensitive to the information on the historical amount and age structure of recreational catch. Our study is intended to inform potential debates related to resource allocation between the commercial and recreational sectors and contribute to developing a general framework for incorporating recreational catches in fisheries management advice in ICES.

scholarly journals Refining Fisheries Advice With Stock-Specific Ecosystem Information

2021 ◽  
Vol 8 ◽  
Author(s):  
Jacob W. Bentley ◽  
Mathieu G. Lundy ◽  
Daniel Howell ◽  
Steven E. Beggs ◽  
Alida Bundy ◽  
...  
Keyword(s):  
Fisheries Management ◽  
Single Species ◽  
Ecosystem Model ◽  
Irish Sea ◽  
Fishing Mortality ◽  
Standard Assessment ◽  
Stock Assessments ◽  
Current Assessment ◽  
The Irish Sea ◽  
Management Advice

Although frequently suggested as a goal for ecosystem-based fisheries management, incorporating ecosystem information into fisheries stock assessments has proven challenging. The uncertainty of input data, coupled with the structural uncertainty of complex multi-species models, currently makes the use of absolute values from such models contentious for short-term single-species fisheries management advice. Here, we propose a different approach where the standard assessment methodologies can be enhanced using ecosystem model derived information. Using a case study of the Irish Sea, we illustrate how stock-specific ecosystem indicators can be used to set an ecosystem-based fishing mortality reference point (FECO) within the “Pretty Good Yield” ranges for fishing mortality which form the present precautionary approach adopted in Europe by the International Council for the Exploration of the Sea (ICES). We propose that this new target, FECO, can be used to scale fishing mortality down when the ecosystem conditions for the stock are poor and up when conditions are good. This approach provides a streamlined quantitative way of incorporating ecosystem information into catch advice and provides an opportunity to operationalize ecosystem models and empirical indicators, while retaining the integrity of current assessment models and the FMSY-based advice process.

scholarly journals Precisely wrong or vaguely right: simulations of noisy discard data and trends in fishing effort being included in the stock assessment of North Sea plaice

2007 ◽  
Vol 64 (9) ◽  
pp. 1641-1649 ◽  
Author(s):  
Mark Dickey-Collas ◽  
Martin A. Pastoors ◽  
Olvin A. van Keeken
Keyword(s):  
North Sea ◽  
Recent Trend ◽  
Stock Assessment ◽  
Target Population ◽  
Fishing Effort ◽  
Fishing Mortality ◽  
Recent Past ◽  
Clear Trend ◽  
The Past ◽  
Stock Assessments

Abstract Dickey-Collas, M., Pastoors, M. A, and van Keeken, O. A. 2007. Precisely wrong or vaguely right: simulations of noisy discard data and trends in fishing effort being included in the stock assessment of North Sea plaice. – ICES Journal of Marine Science, 64: 000–000. ICES stock assessments of North Sea plaice are routinely carried out with eXtended Survivors Analysis (XSA), based on landings and survey data. Recently, the assessments included data on discarded young fish, sampled with high variance. Fishing effort has been declining since the mid-1990s, so conditioning the estimated fishing mortality (F) on the recent past could introduce bias into the perceived stock size. Simulated populations with North Sea plaice-like characteristics are used to explore the dependence of the perceived stock dynamics on the inclusion of discards data at different sampling noise, using the same methods and XSA settings as ICES. The sensitivities of the results were tested against different trends in fishing effort and recruitment, and different scenarios for “shrinkage” (i.e. the way in which the past is used to estimate the most recent fishing mortality). Within the bounds of the simulation assumptions, the perception of population trends from an XSA stock assessment can be biased when there are trends in fishing effort: decreasing effort leads to underestimating SSB and overestimating F. When discards are not included, bias in SSB is greatest when effort decreases, and bias in F is greatest when effort increases. Bias in SSB and F were removed by including discard data, but at substantial loss of precision. If effort shows a clear trend and discards are substantial and estimated noisily, the recent trend in the target population may be hard to track with an XSA-type assessment methodology.

A Bayesian modelling framework for the estimation of catch-at-age of commercially harvested fish species

2012 ◽  
Vol 69 (12) ◽  
pp. 2064-2076 ◽  
Author(s):  
David Hirst ◽  
Geir Storvik ◽  
Hanne Rognebakke ◽  
Magne Aldrin ◽  
Sondre Aanes ◽  
...  
Keyword(s):  
Age Determination ◽  
Stock Identification ◽  
Posterior Distributions ◽  
Bayesian Modelling ◽  
Bayesian Hierarchical ◽  
Modelling Framework ◽  
Reading Errors ◽  
Fishery Data ◽  
Age Reading ◽  
Modelling Approach

A Bayesian hierarchical model was developed to estimate catch-at-age from commercial fishery data. Most common forms of data can be utilized: age and length, length-stratified ages, and length only. There is no need to construct an age–length key. Both landings and discards can be estimated, as can the effects of age reading errors. Estimates can be made for difficult to distinguish stocks, where stock identification is only possible in some fish, for example, by using otoliths and age determination. Uncertainty in stock identification can be included in this modelling approach which allows errors in the estimates to be fully captured in their posterior distributions. An important component of this model is the inclusion of random effects to account for positive correlation in both fish size and age within the sampling units.

scholarly journals Eastern Baltic cod in distress: biological changes and challenges for stock assessment

2015 ◽  
Vol 72 (8) ◽  
pp. 2180-2186 ◽  
Author(s):  
Margit Eero ◽  
Joakim Hjelm ◽  
Jane Behrens ◽  
Kurt Buchmann ◽  
Massimiliano Cardinale ◽  
...  
Keyword(s):  
Baltic Sea ◽  
Gadus Morhua ◽  
Stock Assessment ◽  
The Baltic Sea ◽  
Stock Status ◽  
Management Measures ◽  
Stock Assessments ◽  
Management Advice ◽  
The Baltic ◽  
Eastern Baltic

Abstract The eastern Baltic (EB) cod (Gadus morhua) stock was depleted and overexploited for decades until the mid-2000s, when fishing mortality rapidly declined and biomass started to increase, as shown by stock assessments. These positive developments were partly assigned to effective management measures, and the EB cod was considered one of the most successful stock recoveries in recent times. In contrast to this optimistic view, the analytical stock assessment failed in 2014, leaving the present stock status unclear. Deteriorated quality of some basic input data for stock assessment in combination with changes in environmental and ecological conditions has led to an unusual situation for cod in the Baltic Sea, which poses new challenges for stock assessment and management advice. A number of adverse developments such as low nutritional condition and disappearance of larger individuals indicate that the stock is in distress. In this study, we (i) summarize the knowledge of recent changes in cod biology and ecosystem conditions, (ii) describe the subsequent challenges for stock assessment, and (iii) highlight the key questions where answers are urgently needed to understand the present stock status and provide scientifically solid support for cod management in the Baltic Sea.

scholarly journals Accounting for variable recruitment and fishing mortality in length-based stock assessments for data-limited fisheries

2018 ◽  
Vol 75 (7) ◽  
pp. 1019-1035 ◽  
Author(s):  
Merrill B. Rudd ◽  
James T. Thorson
Keyword(s):  
Stock Assessment ◽  
Assessment Tools ◽  
Biological Information ◽  
Total Catch ◽  
Fishing Mortality ◽  
Stock Assessments ◽  
Length Measurements ◽  
Simulation Testing ◽  
Length Data ◽  
Variable Recruitment

In fisheries with limited capacity for monitoring, it is often easier to collect length measurements from fishery catch than quantify total catch. Conventional stock assessment tools that rely on length measurements without total catch do not directly account for variable fishing mortality and recruitment over time. However, this equilibrium assumption is likely violated in almost every fishery, degrading estimation performance. We developed an extension of length-only approaches to account for time-varying recruitment and fishing mortality. This Length-based Integrated Mixed Effects (LIME) method at a minimum requires a single year of length data and basic biological information but can fit to multiple years of length data, catch, and an abundance index if available. We use simulation testing to demonstrate that LIME can estimate how much fishing has reduced spawning output in the most recent year across a variety of scenarios for recruitment and fishing mortality. LIME improves data-limited fisheries stock assessments by its flexibility to incorporate additional years or types of data if available and obviates the need for equilibrium assumptions.

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