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

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.

2009 ◽  
Vol 66 (3) ◽  
pp. 445-454 ◽  
Author(s):  
H. Moustahfid ◽  
J. S. Link ◽  
W. J. Overholtz ◽  
M. C. Tyrrell

AbstractMoustahfid, H., Link, J. S., Overholtz, W. J., and Tyrrell, M. C. 2009. The advantage of explicitly incorporating predation mortality into age-structured stock assessment models: an application for Atlantic mackerel. – ICES Journal of Marine Science, 66: 445–454. An age-structured assessment programme (ASAP) that explicitly incorporates predation mortality was applied to Atlantic mackerel (Scomber scombrus) in the Northwest Atlantic. Predatory removals were modelled in the same manner as fishing mortality, with a comparable set of time-series, to produce estimates of predation mortality at age and for each year. Results from the analysis showed that incorporating predation into a mackerel stock assessment model notably altered model outputs. When excluding explicitly modelled rates of predation, the model underestimated the magnitude and uncertainty in spawning-stock biomass (SSB) and recruitment. Further, the rates of predation mortality varied across time and were higher for younger fish. Predation mortality was higher than fishing mortality for fish aged 1 year, approximately equal for 2-year-olds, and lower for older fish (3 years and older). Biological reference points for Atlantic mackerel differed considerably when predation mortality was included. For example, SSBMSY was more than twice as high in the model where predation was incorporated than in the fisheries-only model. Although there are several caveats to the predation model outputs, chief of which is that the estimates are conservative because some mackerel predators were excluded, the results demonstrate the feasibility of executing such an approach with an extant tool. The approach presented here ultimately has the advantage of detecting, and upon detection parsing out, the impact of predators relative to fisheries and has the potential to provide useful information to those interested in small pelagic fish and their associated fisheries.


2018 ◽  
Vol 75 (6) ◽  
pp. 2016-2024
Author(s):  
Hiroshi Okamura ◽  
Yuuho Yamashita ◽  
Momoko Ichinokawa ◽  
Shota Nishijima

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.


2014 ◽  
Vol 72 (1) ◽  
pp. 31-43 ◽  
Author(s):  
Kotaro Ono ◽  
Roberto Licandeo ◽  
Melissa L. Muradian ◽  
Curry J. Cunningham ◽  
Sean C. Anderson ◽  
...  

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.


2010 ◽  
Vol 67 (8) ◽  
pp. 1247-1261 ◽  
Author(s):  
Nicolas Bousquet ◽  
Noel Cadigan ◽  
Thierry Duchesne ◽  
Louis-Paul Rivest

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.


2010 ◽  
Vol 67 (6) ◽  
pp. 1185-1197 ◽  
Author(s):  
C. Fernández ◽  
S. Cerviño ◽  
N. Pérez ◽  
E. Jardim

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.


2019 ◽  
Vol 76 (3) ◽  
pp. 401-414 ◽  
Author(s):  
James T. Thorson ◽  
Melissa A. Haltuch

Stock assessment models are fitted to abundance-index, fishery catch, and age–length–sex composition data that are estimated from survey and fishery records. Research has developed spatiotemporal methods to estimate abundance indices, but there is little research regarding model-based methods to generate age–length–sex composition data. We demonstrate a spatiotemporal approach to generate composition data and a multinomial sample size that approximates the estimated imprecision. A simulation experiment comparing spatiotemporal and design-based methods demonstrates a 32% increase in input sample size for the spatiotemporal estimator. A Stock Synthesis assessment used to manage lingcod (Ophiodon elongatus) in the California Current also shows a 17% increase in sample size and better model fit using the spatiotemporal estimator, resulting in smaller standard errors when estimating spawning biomass. We conclude that spatiotemporal approaches are feasible for estimating both abundance-index and compositional data, thereby providing a unified approach for generating inputs for stock assessments. We hypothesize that spatiotemporal methods will improve statistical efficiency for composition data in many stock assessments and recommend that future research explore the impact of including additional habitat or sampling covariates.


2007 ◽  
Vol 58 (10) ◽  
pp. 905 ◽  
Author(s):  
Ian J. Stewart ◽  
Kevin R. Piner

The stock of canary rockfish off the west coast of the continental US is currently assessed using an integrated statistical catch-at-age model. The functional form of an ageing bias detected in production ageing (large numbers of ages read for use in stock assessment) from a bomb radiocarbon study with small sample size (n = 16) was estimated externally and used to adjust the age data in the most recent stock assessment. Using simulation methods, the present study evaluated whether integrating the estimation of the ageing bias inside the assessment model would (1) influence the uncertainty in assessment results and (2) improve our ability to differentiate between competing functional forms (linear, linear with intercept and jointed) for specifying the ageing bias. Internal estimation of the ageing bias relationship increased the approximate 95% confidence interval width about the spawning biomass estimate by 1–10% depending on the functional form assumed. The assessment model was not able to reliably distinguish between all competing functional forms of the ageing bias tested, even with increased radiocarbon sample sizes. However, significant under-ageing at the youngest ages was found to be inconsistent with other sources of data in the assessment model. The question of ageing bias form remains important because it had moderate effects on estimates of spawning biomass and assessment model uncertainty.


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.


2009 ◽  
Vol 67 (1) ◽  
pp. 165-175 ◽  
Author(s):  
Elizabeth N. Brooks ◽  
Joseph E. Powers ◽  
Enric Cortés

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.


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