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 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.

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.

scholarly journals The advantage of explicitly incorporating predation mortality into age-structured stock assessment models: an application for Atlantic mackerel

2009 ◽  
Vol 66 (3) ◽  
pp. 445-454 ◽  
Author(s):  
H. Moustahfid ◽  
J. S. Link ◽  
W. J. Overholtz ◽  
M. C. Tyrrell
Keyword(s):  
Stock Assessment ◽  
Fish Predation ◽  
Reference Points ◽  
Assessment Model ◽  
Fishing Mortality ◽  
Atlantic Mackerel ◽  
Predation Mortality ◽  
Spawning Stock ◽  
Age Structured ◽  
The Impact

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.

scholarly journals Quirky patterns in time-series of estimates of recruitment could be artefacts

2014 ◽  
Vol 72 (1) ◽  
pp. 111-116 ◽  
Author(s):  
M. Dickey-Collas ◽  
N. T. Hintzen ◽  
R. D. M. Nash ◽  
P-J. Schön ◽  
M. R. Payne
Keyword(s):  
Time Series ◽  
Stock Assessment ◽  
Meta Analysis ◽  
Reference Points ◽  
Fish Stocks ◽  
Stock Recruitment ◽  
Modelling Assumptions ◽  
Meta Analyses ◽  
Recruitment Model ◽  
Recruitment Time

Abstract The accessibility of databases of global or regional stock assessment outputs is leading to an increase in meta-analysis of the dynamics of fish stocks. In most of these analyses, each of the time-series is generally assumed to be directly comparable. However, the approach to stock assessment employed, and the associated modelling assumptions, can have an important influence on the characteristics of each time-series. We explore this idea by investigating recruitment time-series with three different recruitment parameterizations: a stock–recruitment model, a random-walk time-series model, and non-parametric “free” estimation of recruitment. We show that the recruitment time-series is sensitive to model assumptions and this can impact reference points in management, the perception of variability in recruitment and thus undermine meta-analyses. The assumption of the direct comparability of recruitment time-series in databases is therefore not consistent across or within species and stocks. Caution is therefore required as perhaps the characteristics of the time-series of stock dynamics may be determined by the model used to generate them, rather than underlying ecological phenomena. This is especially true when information about cohort abundance is noisy or lacking.

AZOV SEA VIMBA INDICATOR ASSESSMENT OF THE STATE OF FISH POPULATION IN TERMS OF LACK OF BIOLOGICAL DATA BY LBI MODEL

Fisheries ◽  
2021 ◽  
Vol 2021 (3) ◽  
pp. 68-75
Author(s):  
Inna Kozobrod ◽  
M. Pyatinsky ◽  
Elena Vlasenko
Keyword(s):  
Stock Assessment ◽  
Fish Population ◽  
Maximum Sustainable Yield ◽  
Biological Data ◽  
Reference Points ◽  
Population Characteristics ◽  
Small Scale ◽  
Assessment Procedure ◽  
Indicator Method ◽  
Yield Level

Stock assessment of vimba population Vimba vimba (Linnaeus, 1758) in period 2015–2020 was performed by qualitative indicator method LBI (Length-Based Indicators) that allows to assess qualitative characteristics of the population and fisheries and MSY biological reference points. The indicator, qualitative approach to stock assessment was applied due to absence vimba population of stable stock-recruitment relationship (due to artificial reproduction exist), which makes impossible to apply surplus production approach to solve production equation dB/dt. LBI model was performed based on available length-weight vimba frequencies dynamics information, which allows to evaluate qualitative population characteristics and fisheries impact. Model results shows no overexploitation signals: in period 2015–2020 fisheries are carried out in maximum sustainable yield level. Indicator results according to reference points indicate no significant signals of reduction optimal length class (Lopt), small-size or large-size class. In 2016 and 2018 uncertain overexploitation of small-scale classes leads to no significant changes was underlined. In terms of biological and fisheries data lacking, LBI methods allow to perform stock assessment procedure more stable and robust then surplus or cohort approach, and output scientific advice to fisheries management.

scholarly journals Ecological Reference Points for Atlantic Menhaden Established Using an Ecosystem Model of Intermediate Complexity

2020 ◽  
Vol 7 ◽  
Author(s):  
David Chagaris ◽  
Katie Drew ◽  
Amy Schueller ◽  
Matt Cieri ◽  
Joana Brito ◽  
...  
Keyword(s):  
Striped Bass ◽  
Fishery Management ◽  
Stock Assessment ◽  
Reference Points ◽  
Atlantic Menhaden ◽  
Assessment Model ◽  
Total Allowable Catch ◽  
Important Species ◽  
Ecosystem Impacts ◽  
Intermediate Complexity

Atlantic menhaden (Brevoortia tyrannus) are an important forage fish for many predators, and they also support the largest commercial fishery by weight on the U.S. East Coast. Menhaden management has been working toward ecological reference points (ERPs) that account for menhaden’s role in the ecosystem. The goal of this work was to develop menhaden ERPs using ecosystem models. An existing Ecopath with Ecosim model of the Northwest Atlantic Continental Shelf (NWACS) was reduced in complexity from 61 to 17 species/functional groups. The new NWACS model of intermediate complexity for ecosystems (NWACS-MICE) serves to link the dynamics of menhaden with key managed predators. Striped bass (Morone saxatilis) were determined to be most sensitive to menhaden harvest and therefore served as an indicator of ecosystem impacts. ERPs were based on the tradeoff relationship between the equilibrium biomass of striped bass and menhaden fishing mortality (F). The ERPs were defined as the menhaden F rates that maintain striped bass at their biomass target and threshold when striped bass are fished at their Ftarget, and all other modeled species were fished at status quo levels. These correspond to an ERP Ftarget of 0.19 and an ERP Fthreshold of 0.57, which are lower than the single species reference points by 30–40%, but higher than current (2017) menhaden F. The ERPs were then fed back into the age-structured stock assessment model projections to provide information on total allowable catch. The ERPs developed in this study were adopted by the Atlantic menhaden Management Board, marking a shift toward ecosystem-based fishery management for this economically and ecologically important species.

scholarly journals A method for calculating a meta-analytical prior for the natural mortality rate using multiple life history correlates

2014 ◽  
Vol 72 (1) ◽  
pp. 62-69 ◽  
Author(s):  
Owen S. Hamel
Keyword(s):  
Life History ◽  
Mortality Rate ◽  
Stock Assessment ◽  
Meta Analysis ◽  
Assessment Model ◽  
Natural Mortality ◽  
Uncertainty Interval ◽  
Free Data ◽  
Stock Assessments ◽  
Measure Of Uncertainty

Abstract The natural mortality rate M is an important parameter for understanding population dynamics, and is extraordinarily difficult to estimate for many fish species. The uncertainty associated with M translates into increased uncertainty in fishery stock assessments. Estimation of M within a stock assessment model is complicated by its confounding with other life history and fishery parameters which are also uncertain, some of which are typically estimated within the model. Ageing error and variation in growth, which may not be fully modelled, can also affect estimation of M, as can various assumptions, including the form of the stock–recruitment function (e.g. Beverton–Holt, Ricker) and the level of compensation (or steepness), which may be fixed (or limited by a prior) in the model. To avoid these difficulties, stock assessors often assume point estimates for M derived from meta-analytical relationships between M and more easily measured life history characteristics, such as growth rate or longevity. However, these relationships depend on estimates of M for a great number of species, and those estimates are also subject to errors and biases (as are, to a lesser extent, the other life history parameters). Therefore, at the very least, some measure of uncertainty in M should be calculated and used for evaluating uncertainty in stock assessments and management strategy evaluations. Given error-free data on M and the covariate(s) for a meta-analysis, prediction intervals would provide the appropriate measure of uncertainty in M. In contrast, if the relationship between the covariate(s) and M is exact and the only error is in the estimates of M used for the meta-analysis, confidence intervals would appropriate. Using multiple published meta-analyses of M’s relationship with various life history correlates, and beginning with the uncertainty interval calculations, I develop a method for creating combined priors for M for use in stock assessment.

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.

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