Spawning biomass reference points for exploited marine fishes, incorporating taxonomic and body size information

2012 ◽  
Vol 69 (9) ◽  
pp. 1556-1568 ◽  
Author(s):  
James T. Thorson ◽  
Jason M. Cope ◽  
Trevor A. Branch ◽  
Olaf P. Jensen
Keyword(s):  
Stock Assessment ◽  
Random Effect ◽  
State Space Model ◽  
Maximum Sustainable Yield ◽  
Marine Fishes ◽  
Reference Points ◽  
Data Set ◽  
Sustainable Fishery ◽  
Spawning Biomass ◽  
Taxonomic Order

Surplus production represents the processes that affect sustainable fishery harvest and is central to the ecology and management of marine fishes. Taxonomy and life history influence the ratio of spawning biomass at maximum sustainable yield to average unfished spawning biomass (SBMSY/SB0), and estimating this ratio for individual stocks is notoriously difficult. We use a database of published landings data and stock assessment biomass estimates and determine that process errors predominate in this data set by fitting a state–space model to data from each stock individually. We then fit multispecies process-error models while treating SBMSY/SB0as a random effect that varies by taxonomic order and maximum length. The estimated SBMSY/SB0 = 0.40 for all 147 stocks is intermediate between the values assumed by the Fox and the Schaefer models, although Clupeiformes and Perciformes have lower and Gadiformes and Scorpaeniformes have higher SBMSY/SB0values. Model selection supports the hypothesis that large-bodied fishes for a given taxonomic order have relatively higher SBMSY/SB0. Results can be used to define reference points for data-poor fisheries or as input in emerging assessment methods.

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 Probability of stochastic depletion: an easily interpreted diagnostic for stock assessment modelling and fisheries management

2014 ◽  
Vol 72 (2) ◽  
pp. 428-435 ◽  
Author(s):  
James T. Thorson ◽  
Olaf P. Jensen ◽  
Ray Hilborn
Keyword(s):  
Stock Assessment ◽  
Biological Effects ◽  
Decision Support Tool ◽  
Maximum Sustainable Yield ◽  
Support Tool ◽  
Management Actions ◽  
Stock Assessments ◽  
Harvest Control Rule ◽  
Recruitment Variability ◽  
Spawning Biomass

Abstract Marine fish populations have high variation in cohort strength, and the production of juveniles (recruitment) may have persistent positive or negative residuals (autocorrelation) after accounting for spawning biomass. Autocorrelated recruitment will occur whenever average recruitment levels change between oceanographic regimes or due to predator release, but may also indicate persistent environmental and biological effects on shorter time-scales. Here, we use estimates of recruitment variability and autocorrelation to simulate the stationary distribution of spawning biomass for 100 real-world stocks when unfished, fished at FMSY, or fished following a harvest control rule where fishing mortality decreases as a function of spawning biomass. Results show that unfished stocks have spawning biomass (SB) below its deterministic equilibrium value (SB0) 58% of the time, and below 0.5SB0 5% of the time on average across all stocks. Similarly, stocks fished at the level producing deterministic maximum sustainable yield (FMSY) are below its deterministic prediction of spawning biomass (SBMSY) 60% of the time and below 0.5SBMSY 8% of the time. These probabilities are greater for stocks with high recruitment variability, positive autocorrelation, and high natural mortality—traits that are particularly associated with clupeids and scombrids. An elevated probability of stochastic depletion, i.e. biomass below the deterministic equilibrium expectation, implies that management actions required when biomass drops below a threshold may be triggered more frequently than expected. Therefore, we conclude by suggesting that fisheries scientists routinely calculate these probabilities during stock assessments as a decision support tool for fisheries managers.

scholarly journals Accounting for uncertainty due to data processing in virtual population analysis using Bayesian multiple imputation

2018 ◽  
Vol 75 (6) ◽  
pp. 883-896 ◽  
Author(s):  
Thomas Carruthers ◽  
Laurence Kell ◽  
Carlos Palma
Keyword(s):  
Data Processing ◽  
Multiple Imputation ◽  
Stock Assessment ◽  
Population Analysis ◽  
Reference Points ◽  
Observation Error ◽  
Predictive Capacity ◽  
Data Set ◽  
Virtual Population Analysis ◽  
Virtual Population

Virtual population analysis (VPA) is used in many stock assessment settings and requires a total catch-at-age data set where an age is assigned to each fish that has been caught. These data sets are typically constructed using ad hoc methods that rely on numerous assumptions. Although approaches are available to account for observation error in these data, no statistically rigorous methods have been developed to account for uncertainty from data processing. To address this, we investigated a Bayesian multiple imputation approach to filling missing size data. Using Atlantic yellowfin tuna (Thunnus albacares) and bigeye tuna (Thunnus obesus) as case studies, we evaluated the hypothesis that data processing is as important in determining management reference points in stock assessments as conventional sources of uncertainty. Size imputation models accounting for location, season, and year provided good predictive capacity. Uncertainty from data processing could be large; however, the circumstances for this were unpredictable and varied depending on the stock. These results indicate that VPA assessments should attempt to account for uncertainty in data processing to avoid potentially large compression of uncertainty in assessment results.

scholarly journals Evaluation of the robustness of maximum sustainable yield based management strategies to variations in carrying capacity or migration pattern of Atlantic bluefin tuna (Thunnus thynnus)

2007 ◽  
Vol 64 (5) ◽  
pp. 837-847 ◽  
Author(s):  
Laurence T Kell ◽  
Jean-Marc Fromentin
Keyword(s):  
Carrying Capacity ◽  
Management Strategy ◽  
Stock Assessment ◽  
Management Strategies ◽  
Maximum Sustainable Yield ◽  
Reference Points ◽  
Sustainable Yield ◽  
Size Limit ◽  
Atlantic Bluefin Tuna ◽  
Spawning Stock

In this study, we examine the performances of current stock assessment methods with respect to their ability to (i) provide estimates of maximum sustainable yield (MSY), FMSY, and BMSY and (ii) assess stock status and exploitation level relative to MSY targets. The robustness of the current International Commission for the Conservation of Atlantic Tunas (ICCAT) management strategy is then evaluated with respect to uncertainty about the true population dynamics and contrasted with a simpler management strategy based solely on a size limit. Reference points are more robust to dynamic uncertainty than the estimates of absolute values and trends in F and spawning stock biomass. However, their performances depend on the underlying dynamics (they perform better when fluctuations come from changes in the carrying capacity than migration) and on when they are implemented relative to the intrinsic cycle of the population. Reference points based on F were less biased and more precise than those based on biomass and (or) yield. Although F0.1 appeared to be the best proxy for FMSY, it cannot indicate past and current levels of exploitation relative to FMSY when there is uncertainty about the dynamics. Finally, the F0.1 management strategy of ICCAT performed only slightly better than a simpler strategy based on size limit and led to lower catch levels.

Reducing retrospective patterns in stock assessment and impacts on management performance

2017 ◽  
Vol 75 (2) ◽  
pp. 596-609 ◽  
Author(s):  
Cody S Szuwalski ◽  
James N Ianelli ◽  
André E Punt
Keyword(s):  
Stock Assessment ◽  
Reference Points ◽  
Natural Mortality ◽  
Time Varying ◽  
Management Performance ◽  
Population Processes ◽  
True Time ◽  
Management Advice ◽  
Spawning Biomass ◽  
Over Time

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.

scholarly journals Grey seal predation mortality on three depleted stocks in the West of Scotland: What are the implications for stock assessments?

2018 ◽  
Vol 75 (5) ◽  
pp. 723-732 ◽  
Author(s):  
Vanessa Trijoulet ◽  
Steven J. Holmes ◽  
Robin M. Cook
Keyword(s):  
Gadus Morhua ◽  
State Space Model ◽  
Maximum Sustainable Yield ◽  
Reference Points ◽  
Melanogrammus Aeglefinus ◽  
Grey Seal ◽  
The West ◽  
The North ◽  
Predation Mortality ◽  
Stock Assessments

The decrease in groundfish stocks in the North Atlantic since the mid-1900s coupled with increases in grey seal (Halichoerus grypus) populations is responsible for an enduring controversy between fishers and conservationists regarding the role seals have played in stock declines. We used a Bayesian state-space model to investigate stock trends in the presence of grey seals and associated maximum sustainable yield (MSY) reference points in the West of Scotland. This study provides new estimates of seal predation mortality on haddock (Melanogrammus aeglefinus) and whiting (Merlangius merlangus) and updates the estimates for cod (Gadus morhua), which together form the traditional main components of the mixed demersal fishery in this area. Grey seal predation mortality is greatest on cod, resulting in estimates of total natural mortality higher than those used in the current ICES assessments. Seal predation mortality is low for haddock and whiting. Considering seal predation in stock assessments changes the scale of biomass and fishing mortality estimates for the three stocks. The estimates of F0.1 and FMSY are sensitive to seal predation for cod and whiting but not for haddock. In all cases, MSY decreases with increased seal predation.

An age-structured model with leading management parameters, incorporating age-specific selectivity and maturity

2008 ◽  
Vol 65 (2) ◽  
pp. 286-296 ◽  
Author(s):  
Robyn E Forrest ◽  
Steven J.D. Martell ◽  
Michael C Melnychuk ◽  
Carl J Walters
Keyword(s):  
Life History Traits ◽  
Stock Assessment ◽  
Maximum Sustainable Yield ◽  
Reference Points ◽  
Fish Stock ◽  
Structured Model ◽  
Specific Selectivity ◽  
Stock Recruitment ◽  
Age Structured ◽  
Age Structured Model

Previous authors have shown analytically that the optimal equilibrium harvest rate (UMSY) for an iteroparous fish stock is a function of the slope of the stock-recruitment curve at low stock size (α) and that UMSY can therefore be considered a direct measure of stock productivity. As such, it can be used as a leading parameter in stock assessment models and directly estimated using Bayesian or similar techniques. Here we present an alternative method for deriving α from UMSY that incorporates age-specific selectivity and fecundity, avoiding assumptions of knife-edged recruitment and maturity. We present an age-structured model with two fisheries reference points (UMSY and maximum sustainable yield, MSY) as its leading parameters. We show equilibrium properties of the model, chiefly in terms of its ability to show relationships between life history traits, density dependence, and UMSY. We also demonstrate a simple Bayesian estimation routine to illustrate estimation of UMSY and MSY directly from data. We compare our results to those from a structurally identical model with leading biological parameters. Using models with leading management parameters can improve communicability of results to managers.

scholarly journals Exploitation status and stock assessment of the smooth clam Callista chione (Linnaeus, 1758) in the northern Alboran Sea (GSA01-W Mediterranean Sea)

2018 ◽  
Vol 19 (1) ◽  
pp. 1
Author(s):  
JORGE BARO ◽  
TERESA GARCIA ◽  
JAVIER URRA ◽  
MATIAS LOZANO ◽  
JOSE LUIS RUEDA
Keyword(s):  
Stock Assessment ◽  
Economic Value ◽  
Maximum Sustainable Yield ◽  
Reference Points ◽  
Production Model ◽  
Total Biomass ◽  
Alboran Sea ◽  
Callista Chione ◽  
Exploitation Status ◽  
Alborán Sea

The smooth clam, Callista chione (Linnaeus, 1758), is a venerid bivalve widely appreciated in southern Spain where it represents the top commercial bivalve species in terms of landings and economic value. In this area, a total of 223 artisanal boats (68% of the artisanal fleet) are involved in shellfishing targeting bivalve molluscs, including the smooth clam. The artisanal mechanised dredging that targets C. chione in the northern Alboran Sea is described and the current exploitation status of its populations is analysed. A surplus-production model was run using ASPIC and used to assess the temporal variation in the levels of fishing for this bivalve throughout the study period (2002-2015), as well as to suggest conservation reference points that could guarantee the sustainable exploitation of this resource. During the study period, the maximum C. chione catch was registered in 2003 (306 t) and the minimum in 2006 (93 t). The ASPIC model for C. chione stock suggests that a Maximum Sustainable Yield (MSY) of 216 t could be produced from a total stock biomass of 983 t (Bmsy) at a fishing mortality rate of total biomass of 0.22 (Fmsy), with B/Bmsy and F/Fmsy values of 1.34 and 0.82, respectively, indicating that the stock is approaching good status.

scholarly journals A continuous hockey stick stock–recruit model for estimating MSY reference points

2010 ◽  
Vol 67 (8) ◽  
pp. 1780-1784 ◽  
Author(s):  
Benoit Mesnil ◽  
Marie-Joëlle Rochet
Keyword(s):  
Stock Assessment ◽  
Maximum Sustainable Yield ◽  
Reference Points ◽  
Sustainable Yield ◽  
Political Commitment ◽  
Hockey Stick ◽  
Differentiable Functions ◽  
Piecewise Function ◽  
Management Plans ◽  
Stock Recruitment

Abstract Mesnil, B., and Rochet, M-J. 2010. A continuous hockey stick stock–recruit model for estimating MSY reference points. – ICES Journal of Marine Science, 67: 1780–1784. With political commitment to restore stocks to levels where they can produce maximum sustainable yield (MSY), fisheries managers request evaluation of management plans that include options for an FMSY policy. The procedure to estimate FMSY with dynamic-pool, stock assessment models is well established for common stock–recruitment relationships (S–RR), and this capacity is extended to another S–RR, a piecewise function known as the hockey stick (HS), which is frequently assumed when the data do not support more elaborate functions. However, the HS is not continuous, which makes it problematic for this application, where differentiable functions are required. The bent-hyperbola model proves to be an adequate continuous equivalent to the HS for estimating FMSY.

scholarly journals Stock Assessment: Sustainable management in high and medium Araguari River, Amapá, Brazil.

2020 ◽  
Vol 42 ◽  
pp. e71
Author(s):  
Luiza Prestes ◽  
Fabiana Calacina da Cunha ◽  
Maria Gercilia Mota Soares ◽  
Marcos Sidney Brito Oliveira ◽  
Netie Izabel Oliveira ◽  
...  
Keyword(s):  
Natural Resources ◽  
Sustainable Management ◽  
Stock Assessment ◽  
Maximum Sustainable Yield ◽  
Reference Points ◽  
Sustainable Yield ◽  
Maximum Economic Yield ◽  
The Status ◽  
Future Management

Fisheries in Araguari river is an alternative income for families that depend on exploitation of natural resources. This study evaluates fisheries production in high and medium Araguari river to determine the bioeconomic reference points of fishery activities. Logbooks of fisheries were used from Fishermen Colony Z-16 from 2003 to 2010. The Maximum Sustainable Yield (MSY) and Effort at Maximum Sustainable Yield (fmsy) was: MSYSchaefer = 11246 kg and fmsy = 754 fisheries/year, and MSYFox = 11478 kg and fmsy = 1214 fisheries/year and at Bioeconomic Equilibrium (Eebe) Eebe = 10712 kg and Effort at Bioeconomic Equilibrium (febe) febe = 918 fisheries/year. The status of fisheries from Araguari River was declared as overfishing and in this study, we found the same results. The Maximum Economic Yield (MEY) was reached too, as the fisheries were at Bioeconomic Equilibrium (EBE). The fishery mortality (Fyear/Fmsy) and fishery effort (fyear/fmsy) trends show that from 2003 to 2009 the values were sustainable. In 2010 those trends became unsustainable, and the Maximum Economic Yield (MEY) for all years is unsustainable too. It is required this study be considered in future management agreements.

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