Incorporating predation interactions in a statistical catch-at-age model for a predator-prey system in the eastern Bering Sea

2005 ◽  
Vol 62 (8) ◽  
pp. 1865-1873 ◽  
Author(s):  
Jesús Jurado-Molina ◽  
Patricia A Livingston ◽  
James N Ianelli
Keyword(s):  
Bering Sea ◽  
Stock Assessment ◽  
Population Analysis ◽  
Adult Population ◽  
Single Species ◽  
Virtual Population Analysis ◽  
Virtual Population ◽  
Statistical Assumptions ◽  
The Difference ◽  
Management Advice

Virtual population analysis and the statistical catch-at-age methods are common stock assessment models used for management advice. The difference between them is the statistical assumptions allowing the fitting of parameters by considering how errors enter into the models and the data sources for the estimation. Fishery managers are being asked to consider multispecies interactions in their decisions. One option to achieve this goal is the multispecies virtual population analysis (MSVPA); however, its lack of statistical assumptions does not allow the use of tools used in single-species stock assessment. We chose to use a two-species system, walleye pollock (Theragra chalcogramma) and Pacific cod (Gadus macrocephalus), to incorporate the predation equations from MSVPA into an age-structured multispecies statistical model (MSM). Results suggest that both models produced similar estimates of suitability coefficients and predation mortalities. The adult population estimates from the single-species stock assessment and MSM were also comparable. MSM provides a measure of parameter uncertainty, which is not available with the MSVPA technologies. MSM is an important advancement in providing advice to fisheries managers because it incorporates the standard tools such as Bayesian methods and decision analysis into a multispecies context, helping to establish useful scenarios for management in the Bering Sea.

scholarly journals Testing the stability of the suitability coefficients from an eastern Bering Sea multispecies virtual population analysis

2005 ◽  
Vol 62 (5) ◽  
pp. 915-924 ◽  
Author(s):  
Jesús Jurado-Molina ◽  
Patricia A. Livingston ◽  
Vincent F. Gallucci
Keyword(s):  
Stomach Content ◽  
Bering Sea ◽  
Population Analysis ◽  
Data Set ◽  
Predator Species ◽  
Eastern Bering Sea ◽  
Virtual Population Analysis ◽  
Virtual Population ◽  
Total Data ◽  
The Stability

Abstract Suitability coefficients are important for the estimation of predation mortality in a multispecies virtual population analysis (MSVPA) and subsequent use in the multispecies forecasting model (MSFOR). Testing the assumption of the stability of the suitability coefficients is important in assessing the robustness of the predictions made with MSFOR. We used different statistical methods to partially test this assumption for the eastern Bering Sea MSVPA model with eight species, using stomach content data for the years 1985–1989. Comparison of the estimates from two different sets of stomach content data (set one with all data and set two mainly with data from 1985) suggested that the differences between the two types of estimates were much reduced when the number of predator stomachs sampled increased. In a second approach, we contrasted the residual variances of partial data sets with the results from the fit of the total data set. Results suggested a small increase (∼10.8%) in the variation of the suitability coefficients. Comparison of the means of the suitability coefficients associated with each predator species suggests that only 13 of the 50 possible pairwise contrasts were significantly different (α = 0.05). In general, results suggested that the predator preferences and prey vulnerabilities remained stable over the time period studied. Therefore, MSFOR could be considered as a tool to advise fisheries managers within a multispecies context.

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 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.

Sensitivities and Variances of Virtual Population Analysis As Applied to the Mackerel, Scomber japonicus

1988 ◽  
Vol 45 (3) ◽  
pp. 539-547 ◽  
Author(s):  
Michael H. Prager ◽  
Alec D. MacCall
Keyword(s):  
Stock Assessment ◽  
Population Analysis ◽  
Error Variance ◽  
Quantitative Model ◽  
Fish Stock ◽  
Scomber Japonicus ◽  
Virtual Population Analysis ◽  
Virtual Population ◽  
Coefficients Of Variation ◽  
Fish Stock Assessment

Virtual population analysis (VPA) is widely used in fish stock assessment. However, VPA results are generally presented as point estimates, without error variance. Using numerical methods, we estimated the total variance of historical (1929–65) biomass estimates of mackerel, Scomber japonicus, off southern California. In the years before 1940, coefficients of variation (CV's) approached 100%; later, when weights at age and the age structure of the catch were better known, the CV's were about 25%. Most of the variability derives from uncertainties in estimates of natural mortality (M) and of weights at age. We also developed dimensionless coefficients (sensitivities) to examine the effects of errors in the inputs on the VPA biomass estimates. The largest sensitivities were to M and the total catch and varied substantially from year to year. As expected, sensitivity to M decreased with increasing exploitation, and sensitivity to catch increased with increasing exploitation. Using such sensitivities, one could estimate the error in a biomass estimate for a past year when M (or any other input) was thought to be unusually high or low. Thus, retrospective corrections can be made. Also, such sensitivities form an analytic tool for examining the properties of VPA, or any quantitative model.

Multispecies versus Single-Species Assessment of North Sea Fish Stocks

1987 ◽  
Vol 44 (S2) ◽  
pp. s360-s370 ◽  
Author(s):  
Niels Daan
Keyword(s):  
Population Analysis ◽  
Stomach Contents ◽  
Single Species ◽  
Fish Stock ◽  
Natural Mortality ◽  
Stock Management ◽  
Fish Stocks ◽  
Virtual Population Analysis ◽  
Virtual Population ◽  
Class Strength

Development of multispecies virtual population analysis (MSVPA), which assesses interspecific and intraspecific predation through an analysis of stomach contents, has verified the hypothesis that predation among exploited fish species contributes significantly to their natural mortality and that predation, and thus natural mortality, is inherently variable from year to year. In single-species virtual population analysis (SSVPA), natural mortality is assumed to be constant. MSVPA also suggests that natural mortality among young fish after recruitment is much higher than previously thought. Although catch quotas based on predictions of short-term catches from multispecies assessments would appear to differ little from those derived from single-species assessments, and certain problems remain to be resolved before multispecies assessments can be accepted for fish stock management, the method has considerable implications for management. For instance, it suggests that effects of mesh sizes and bycatch on fisheries need reevaluation and that year class strength may not be as fixed as previously assumed.

scholarly journals Calibrating virtual population analysis for fisheries stock assessment

2008 ◽  
Vol 21 (2) ◽  
pp. 89-97 ◽  
Author(s):  
Yong Chen ◽  
Yan Jiao ◽  
Chi-Lu Sun ◽  
Xinjun Chen
Keyword(s):  
Stock Assessment ◽  
Population Analysis ◽  
Virtual Population Analysis ◽  
Virtual Population

scholarly journals Lumpers or splitters? Evaluating recovery and management plans for metapopulations of herring

2009 ◽  
Vol 66 (8) ◽  
pp. 1776-1783 ◽  
Author(s):  
Laurence T. Kell ◽  
Mark Dickey-Collas ◽  
Niels T. Hintzen ◽  
Richard D. M. Nash ◽  
Graham M. Pilling ◽  
...  
Keyword(s):  
Stock Assessment ◽  
Population Analysis ◽  
Stock Status ◽  
Virtual Population Analysis ◽  
Virtual Population ◽  
Management Plans ◽  
Management Area ◽  
Term Management

Abstract Kell, L. T., Dickey-Collas, M., Hintzen, N. T., Nash, R. D. M., Pilling, G. M., and Roel, B. A. 2009. Lumpers or splitters? Evaluating recovery and management plans for metapopulations of herring. – ICES Journal of Marine Science, 66: 1776–1783. The long-term management of a stock representing a metapopulation has been simulated in a case study loosely based upon herring to the west of the British isles, where stocks are currently assessed and managed by management area, although there is evidence of mixing between stocks (in terms of connectivity, migrations, and exploitation). The simulations evaluate scientific advice (based on virtual population analysis, VPA) and the sustainability of fishing under two population-structure scenarios, corresponding either to discrete stocks, which only mix on the feeding grounds, or where diffusion between stocks takes place. The ability of stock assessment to monitor stock status and exploitation levels was evaluated for defining stocks based on fishing areas and for stocks that combined fishing areas. The study showed that assessment based on VPA of the metapopulation could fail to detect overexploitation of stocks and fail to detect and distinguish between the effects of exploitation and regime shifts.

scholarly journals Stock assessment of sockeye salmon Oncorhynchus nerka by using adaptive framework virtual population analysis

2015 ◽  
Vol 81 (3) ◽  
pp. 418-428 ◽  
Author(s):  
YU SU ◽  
EMMANUEL ANDREW SWEKE ◽  
TAKASHI DENBOH ◽  
HIROSHI UEDA ◽  
TAKASHI MATSUISHI
Keyword(s):  
Sockeye Salmon ◽  
Stock Assessment ◽  
Population Analysis ◽  
Oncorhynchus Nerka ◽  
Virtual Population Analysis ◽  
Virtual Population ◽  
Adaptive Framework
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