Reconciling conflicting survey indices of abundance prior to stock assessment

2021 ◽  
Author(s):  
Cassidy D Peterson ◽  
Dean L Courtney ◽  
Enric Cortés ◽  
Robert J Latour
Keyword(s):  
Relative Abundance ◽  
Assessment Tool ◽  
Stock Assessment ◽  
Assessment Model ◽  
Dynamic Factor ◽  
Shark Species ◽  
Southeast United States ◽  
Structured Population ◽  
Age Structured ◽  
Stock Abundance

Abstract Indices of relative abundance are one of the most important inputs into a stock assessment model. For many species, we must rely on several indices that routinely conflict with each other and which may result in biased and uncertain outputs. Here, we explored whether reconciled trends obtained from dynamic factor analysis (DFA) applied to conflicting indices can be used as a trend of relative abundance input into a stock assessment model. We simulated an age-structured population of two coastal shark species in the southeast United States to generate multiple disagreeing indices, reconciled the indices using DFA, and then inserted both the multiple conflicting survey indices and the simplified DFA-predicted trend into respective stock assessment models. We compared the results of each stock assessment model to simulated values to evaluate the relative performance of each approach. We found that the DFA-based assessment generally performed similarly to the conflicting index-based assessment and may be a useful assessment tool in situations where conflicting indices with different selectivities, catchabilities, variances, and missing data are present. DFA assessment results were more consistent across simulation scenarios and outperformed many conflicting index assessments when surveys underwent shifts in catchability and the underlying stock abundance exhibited contrast.

Analytical reference points for age-structured models: application to data-poor fisheries

2009 ◽  
Vol 67 (1) ◽  
pp. 165-175 ◽  
Author(s):  
Elizabeth N. Brooks ◽  
Joseph E. Powers ◽  
Enric Cortés
Keyword(s):  
Stock Assessment ◽  
Meta Analysis ◽  
Reproductive Rate ◽  
Biological Data ◽  
Reference Points ◽  
Assessment Model ◽  
Shark Species ◽  
Stock Status ◽  
Age Structured ◽  
Analytical Reference

AbstractBrooks, E. N., Powers, J. E., and Cortés, E. 2010. Analytical reference points for age-structured models: application to data-poor fisheries. – ICES Journal of Marine Science, 67: 165–175. Analytical solutions for biological reference points are derived in terms of maximum lifetime reproductive rate. This rate can be calculated directly from biological parameters of maturity, fecundity, and natural mortality or a distribution for this rate can be derived from appropriate metadata. Minimal data needs and assumptions for determining stock status are discussed. The derivations lead to a re-parameterization of the common stock–recruit relationships, Beverton–Holt and Ricker, in terms of spawning potential ratio. Often, parameters in stock–recruit relationships are restricted by tight prior distributions or are fixed based on a hypothesized level of stock resilience. Fixing those parameters is equivalent to specifying the biological reference points. An ability to directly calculate reference points from biological data, or a meta-analysis, without need of a full assessment model or fisheries data, makes the method an attractive option for data-poor fisheries. The derivations reveal an explicit link between the biological characteristics of a species and appropriate management. Predicted stock status for a suite of shark species was compared with recent stock assessment results, and the method successfully identified whether each stock was overfished.

scholarly journals Stock assessment and projections incorporating discard estimates in some years: an application to the hake stock in ICES Divisions VIIIc and IXa

2010 ◽  
Vol 67 (6) ◽  
pp. 1185-1197 ◽  
Author(s):  
C. Fernández ◽  
S. Cerviño ◽  
N. Pérez ◽  
E. Jardim
Keyword(s):  
Time Series ◽  
Stock Assessment ◽  
Reference Points ◽  
Assessment Model ◽  
Marine Science ◽  
Fishing Mortality ◽  
Change Over Time ◽  
Age Structured ◽  
Available Information ◽  
Over Time

Abstract Fernández, C., Cerviño, S., Pérez, N., and Jardim, E. 2010. Stock assessment and projections incorporating discard estimates in some years: an application to the hake stock in ICES Divisions VIIIc and IXa. – ICES Journal of Marine Science, 67: 1185–1197. A Bayesian age-structured stock assessment model is developed to take into account available information on discards and to handle gaps in the time-series of discard estimates. The model incorporates mortality attributable to discarding, and appropriate assumptions about how this mortality may change over time are made. The result is a stock assessment that accounts for information on discards while, at the same time, producing a complete time-series of discard estimates. The method is applied to the hake stock in ICES Divisions VIIIc and IXa, for which the available data indicate that some 60% of the individuals caught are discarded. The stock is fished by Spain and Portugal, and for each country, there are discard estimates for recent years only. Moreover, the years for which Portuguese estimates are available are only a subset of those with Spanish estimates. Two runs of the model are performed; one assuming zero discards and another incorporating discards. When discards are incorporated, estimated recruitment and fishing mortality for young (discarded) ages increase, resulting in lower values of the biological reference points Fmax and F0.1 and, generally, more optimistic future stock trajectories under F-reduction scenarios.

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

2014 ◽  
Vol 72 (1) ◽  
pp. 99-110 ◽  
Author(s):  
Felipe Hurtado-Ferro ◽  
Cody S. Szuwalski ◽  
Juan L. Valero ◽  
Sean C. Anderson ◽  
Curry J. Cunningham ◽  
...  
Keyword(s):  
Life Histories ◽  
Temporal Change ◽  
Stock Assessment ◽  
Model Misspecification ◽  
Assessment Model ◽  
Time Varying ◽  
Simulation Framework ◽  
Zero Values ◽  
Age Structured ◽  
Management Advice

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.

Performance of a fisheries catch-at-age model (Stock Synthesis) in data-limited situations

2011 ◽  
Vol 62 (8) ◽  
pp. 927 ◽  
Author(s):  
Chantell R. Wetzel ◽  
André E. Punt
Keyword(s):  
Stock Assessment ◽  
Estimation Method ◽  
Assessment Method ◽  
Assessment Model ◽  
Limited Data ◽  
Composition Data ◽  
Spawning Stock ◽  
Age Model ◽  
Age Structured ◽  
The Impact

Limited data are a common challenge posed to fisheries stock assessment. A simulation framework was applied to examine the impact of limited data and data type on the performance of a widely used catch-at-age stock-assessment method (Stock Synthesis). The estimation method provided negatively biased estimates of current spawning-stock biomass (SSB) relative to the unfished level (final depletion) when only recent survey indices were available. Estimation of quantities of management interest (unfished SSB, virgin recruitment, target fishing mortality and final depletion) improved substantially even when only minimal-length-composition data from the survey were available. However, the estimates of some quantities (final depletion and unfished SSB) remained biased (either positively or negatively) even in the scenarios with the most data (length compositions, age compositions and survey indices). The probability of overestimating yield at the target SSB relative to the true such yield was ~50%, a risk-neutral result, for all the scenarios that included length-composition data. Our results highlight the importance of length-composition data for the performance of an age-structured assessment model, and are encouraging for the assessment of data-limited stocks.

Comparison of the performance of age-structured models with few survey indices

2018 ◽  
Vol 75 (6) ◽  
pp. 2016-2024
Author(s):  
Hiroshi Okamura ◽  
Yuuho Yamashita ◽  
Momoko Ichinokawa ◽  
Shota Nishijima
Keyword(s):  
Stock Assessment ◽  
Population Analysis ◽  
Assessment Model ◽  
Sufficient Information ◽  
Abundance Estimates ◽  
Virtual Population ◽  
Stock Biomass ◽  
Abundance Indices ◽  
Spawning Stock ◽  
Age Structured

Abstract Age-structured models have played an important role in fisheries stock assessment. Although virtual population analysis (VPA) was once the most widely used stock assessment model for when catch-at-age information is available, (hierarchical) statistical catch-at-age analysis (SCAA) is about to take that position. However, the estimation performance of different age-structured models has not been evaluated sufficiently, especially in cases where there are few available abundance indices. We examined the performance of VPA and SCAA using simulation data in which only the abundance indices of spawning stock biomass and recruitment were available. The simulation demonstrated that VPA with the ridge penalty selected by minimizing retrospective bias provided near-unbiased abundance estimates without catch-at-age error and moderately biased estimates with catch-at-age error, whereas SCAA with random-walk selectivity suffered from problems in estimating parameters and population states. Without sufficient information on abundance trends, naïvely using SCAA with many random effects should be done cautiously, and comparing results from various age-structured models via simulation tests will be informative in selecting an appropriate stock assessment model.

Comparison of the frequentist properties of Bayes and the maximum likelihood estimators in an age-structured fish stock assessment model

2002 ◽  
Vol 59 (1) ◽  
pp. 136-143 ◽  
Author(s):  
Anders Nielsen ◽  
Peter Lewy
Keyword(s):  
Maximum Likelihood ◽  
Stock Assessment ◽  
Process Variations ◽  
Bayes Estimator ◽  
Assessment Model ◽  
Fish Stock ◽  
The North ◽  
The North Sea ◽  
Age Structured ◽  
Fish Stock Assessment

A simulation study was carried out for a separable fish stock assessment model including commercial and survey catch-at-age and effort data. All catches are considered stochastic variables subject to sampling and process variations. The results showed that the Bayes estimator of spawning biomass is a useful but slightly biased estimator for which the frequentist variance can be estimated by the posterior variance. Comparisons further show that the Bayes estimator is better than the maximum likelihood in the sense that it is less biased and, surprisingly, has a much lesser variance. The catch simulations were based on the North Sea plaice (Pleuronectes platessa) stock and fishery data.

scholarly journals Predicting changes in mean length with an age‐structured stock assessment model

2019 ◽  
Vol 32 (4) ◽  
Author(s):  
Abdul Ben‐Hasan ◽  
Carl Walters ◽  
Villy Christensen ◽  
Brett Poorten ◽  
Sarah Rajab ◽  
...  
Keyword(s):  
Stock Assessment ◽  
Assessment Model ◽  
Age Structured

scholarly journals The importance of length and age composition data in statistical age-structured models for marine species

2014 ◽  
Vol 72 (1) ◽  
pp. 31-43 ◽  
Author(s):  
Kotaro Ono ◽  
Roberto Licandeo ◽  
Melissa L. Muradian ◽  
Curry J. Cunningham ◽  
Sean C. Anderson ◽  
...  
Keyword(s):  
Life History ◽  
Life Histories ◽  
Stock Assessment ◽  
Marine Species ◽  
Reference Points ◽  
Assessment Model ◽  
Sources Of Information ◽  
Age Composition ◽  
Composition Data ◽  
Age Structured

Abstract Management of marine resources depends on the assessment of stock status in relation to established reference points. However, many factors contribute to uncertainty in stock assessment outcomes, including data type and availability, life history, and exploitation history. A simulation–estimation framework was used to examine the level of bias and accuracy in assessment model estimates related to the quality and quantity of length and age composition data across three life-history types (cod-, flatfish-, and sardine-like species) and three fishing scenarios. All models were implemented in Stock Synthesis, a statistical age-structured stock assessment framework. In general, the value of age composition data in informing estimates of virgin recruitment (R0), relative spawning-stock biomass (SSB100/SSB0), and terminal year fishing mortality rate (F100), decreased as the coefficient of variation of the relationship between length and age became greater. For this reason, length data were more informative than age data for the cod and sardine life histories in this study, whereas both sources of information were important for the flatfish life history. Historical composition data were more important for short-lived, fast-growing species such as sardine. Infrequent survey sampling covering a longer period was more informative than frequent surveys covering a shorter period.

Detecting and correcting underreported catches in fish stock assessment: trial of a new method

2010 ◽  
Vol 67 (8) ◽  
pp. 1247-1261 ◽  
Author(s):  
Nicolas Bousquet ◽  
Noel Cadigan ◽  
Thierry Duchesne ◽  
Louis-Paul Rivest
Keyword(s):  
Gadus Morhua ◽  
Stock Assessment ◽  
Population Analysis ◽  
Assessment Model ◽  
Fish Stock ◽  
Stock Biomass ◽  
Stock Assessments ◽  
Spawning Stock ◽  
Age Structured ◽  
Fish Stock Assessment

Landings from fisheries are often underreported, that is, the true landings are greater than those reported. Despite this bias, reported landings are widely used in fish stock assessments, and this might lead to overoptimistic exploitation strategies. We construct a statistical stock assessment model that accounts for underreported landings using the theory of censoring with sequential population analysis (SPA). The new model is developed and implemented specifically for the cod stock ( Gadus morhua ) from the southern Gulf of St. Lawrence (Canada). This stock is known to have unreported overfishing during 1985–1992. We show in simulations that for this stock, the new censored model can correctly detect the problematic landings. These corrections are nearly insensitive to subjective boundaries placed on real catches and robust to modifications imposed in the simulation of landings. However, when surveys are too noisy, the new SPA for censored catches can result in increased uncertainty in parameters used for management such as spawning stock biomass and age-structured stock size.

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