Ridge virtual population analysis to reduce the instability of fishing mortalities in the terminal year

2017 ◽  
Vol 74 (9) ◽  
pp. 2427-2436 ◽  
Author(s):  
Hiroshi Okamura ◽  
Yuuho Yamashita ◽  
Momoko Ichinokawa
Keyword(s):  
Ridge Regression ◽  
Population Analysis ◽  
Japan Sea ◽  
The Sea Of Japan ◽  
Fishing Mortality ◽  
Population Analyses ◽  
Virtual Population ◽  
Stock Assessments ◽  
Abundance Indices ◽  
Stable Estimation

Abstract Tuned virtual population analyses are widely used for fisheries stock assessments. However, accurately estimating abundances and fishing mortality coefficients in the terminal year using tuned virtual population analyses is generally difficult, particularly when there is a limited number of available abundance indices. We propose a new method of integrating the tuned virtual population analyses with a ridge regression approach. In our method, penalization in the ridge regression is applied to the age-specific fishing mortalities in the terminal year, and the penalty parameter is automatically selected by minimizing the retrospective bias. Therefore, our method is able to simultaneously obtain a stable estimation of fishing mortality coefficients in the terminal year and reduce retrospective bias. Simulation tests based on the northern Japan Sea stock of walleye pollock (Gadus chalcogrammus) in the Sea of Japan demonstrated that this method yielded less biased estimates of abundances and avoided overestimations of fishing mortality coefficients in the terminal year. In addition, despite limited abundance indices, our method can perform reliable abundance estimations even under hyperstability and hyperdepletion conditions.

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.

scholarly journals Estimation of the age-specific rate of natural mortality for Shetland sandeels

2004 ◽  
Vol 61 (2) ◽  
pp. 159-164 ◽  
Author(s):  
R.M. Cook
Keyword(s):  
Survey Data ◽  
Population Analysis ◽  
Mean Value ◽  
Specific Rate ◽  
Natural Mortality ◽  
The North ◽  
Virtual Population ◽  
Stock Assessments ◽  
The North Sea ◽  
The Mean

Abstract It is generally difficult to obtain reliable direct estimates of natural mortality, M, from conventional fisheries data and stock assessments. However, as a result of the closure of the Shetland sandeel (Ammodytes marinus) fishery from 1991 to 1994 and in the absence of any significant fishery in other years, research vessel survey data offer a rare opportunity to obtain estimates of M directly. A model is described that assumes that M can be decomposed into an age effect and year effects. Application of the model to the survey data produces values of M that decline from 2.1 for 0-group fish to 0.6 at age 2. There is some indication of an increase for ages 4 and older. Although there does not appear to be an overall trend in the mean value of M for the period 1985–1999, the annual values change by up to 50%. The values calculated from the model are in line with estimates obtained for the North Sea from multispecies virtual population analysis (MSVPA).

Incorporating Uncertainty into Fishery Models

2002 ◽  
Keyword(s):  
Fishery Management ◽  
Population Analysis ◽  
Management Plan ◽  
Atlantic Menhaden ◽  
Production Model ◽  
Fishing Mortality ◽  
Juvenile Abundance ◽  
Stock Assessments ◽  
Mortality Projections ◽  
Production Modeling

<em>Abstract.—</em>Stock assessments of Atlantic menhaden are conducted annually for the Atlantic States Marine Fisheries Commission, as required by the recently updated Fishery Management Plan, adopted in 1992. Uncertainties in stock assessments have been explored over the years from many perspectives. Two general areas of analysis are considered here. The first area is largely deterministic and concerns the virtual population analysis (VPA), including development and coherence of the catch-at-age matrix; historical retrospective problems; implications of assuming constant <EM>M </EM>at all ages analyzed; and reliability of recruitment estimates relative to fishery-independent juvenile abundance indices when used for calibrating the VPA. The second area of consideration comprises stochastic analyses, including stochastic projections based on biological benchmarks determined from yield-per-recruit and spawning-stockbiomass- per-recruit models; bootstrapped application of a surplus-production model; and projections from that production model. Nonetheless, the largest uncertainty in assessment of the stock stems not from modeling considerations, but is a biological question: Can the high stock levels observed in the 1950s be regained by reducing fishing mortality? Projections based on production modeling assume that they can, but if exogenous forces (for example, habitat loss or pollution) have affected the stock, it may be that they cannot. If the recent pattern of lower fishing mortality rates in response to social and economic factors continues, the fishery will in essence conduct an experiment that may answer the question.

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.

Derzhavin's Biostatistical Method of Population Analysis

1971 ◽  
Vol 28 (10) ◽  
pp. 1666-1672 ◽  
Author(s):  
W. E. Ricker
Keyword(s):  
Mortality Rate ◽  
Unbiased Estimate ◽  
Population Analysis ◽  
Total Mortality ◽  
Fishing Mortality ◽  
Virtual Population ◽  
Class Strength ◽  
Minimum Age ◽  
Catch Statistics ◽  
Precise Interpretation

Derzhavin's biostatistical method, as modified by Boiko and others, uses annual age censuses and catch statistics to compute the utilized stock (virtual population), Vi, of year-class i in a given year as the sum of all members of that year-class that are caught in the current and future years. The sum of Vi values for all year-classes present in a given year is the total utilized population, V. The biostatistical rate of exploitation for individual ages (Ci/Vi), or for the stock as a whole (C/V), is the catch divided by the utilized stock. If ages of the fish in the stock are read too low, values of Ci/Vi and C/V are too large. For fully recruited fish, Ci/Vi is an unbiased estimate of the total mortality rate, A, bat for incompletely recruited ages, it differs progressively from A and has no simple interpretation. Variations in abundance of successive year-classes do not affect the interpretation of Ci/Vi or C/V for fully recruited ages, but changes in rate of fishing, F, are disturbing. When incompletely recruited ages are included in a biostatistical computation (as has usually been done), C/V does not have any precise interpretation in terms of population parameters. In addition, variations in year-class strength affect the value of C/V even when F does not change from year to year. It is possible to use C/V for the whole catch as an "arbitrary" index that reflects the direction and magnitude of changes in intensity of fishing over a period of years. However, even for this purpose the same minimum age must be used in all years. When data for a long series of years are available, the utilized year-class strength (ΣCi) of the year-class hatched in year i can be compared with the total utilized stock (or the utilized mature stock) present in year i, in order to examine parent–progeny relations. Incompletely recruited as well as fully recruited ages can be used in this comparison, but adjustments are necessary if mortality rate (natural or fishing) changes from year to year. The biostatistical method does not provide separate estimates of natural and fishing mortality rates. If the possibility of a moderate or large natural mortality is disregarded, serious errors of interpretation may result.

Climate-forcing effects on trophically linked groundfish populations: implications for fisheries management

2002 ◽  
Vol 59 (12) ◽  
pp. 1941-1951 ◽  
Author(s):  
Jesús Jurado-Molina ◽  
Patricia Livingston
Keyword(s):  
Food Web ◽  
Fisheries Management ◽  
Population Analysis ◽  
Regime Shifts ◽  
Climate Forcing ◽  
Fishing Mortality ◽  
Climate Regime ◽  
Virtual Population ◽  
Commercially Important ◽  
Potential Interactions

Commercially important groundfish populations in the Bering Sea are connected through the food web as predators and prey. In addition to having different trophic roles, the recruitment of these species varies on interdecadal time scales and may be related to climate forcing. We simulate the effects of fishing mortality on eight trophically linked species under two scenarios of climate regimes using the multispecies virtual population analysis (MSVPA) model and the multispecies forecasting model (MSFOR). Species respond differently to climate change assumptions and fishing mortality depending on their position in the food web. Results suggest that the assumptions regarding climate regime shifts on mean recruitment may produce effects comparable to the ones produced by fishing and predation interactions. Therefore, accurate models for fisheries management would require considering these factors and their potential interactions. Because responses are complex and difficult to predict, it is necessary to take a risk-averse approach in managing the species with the largest potential variation. The incorporation of climate regime shifts in fisheries management will require a better understanding of recruitment during a particular regime and a reliable way to identify regime shifts based on biological and (or) physical indices.

Trends in Fishing Mortality Rate along with Errors in Natural Mortality Rate can cause Spurious Time Trends in Fish Stock Abundances Estimated by Virtual Population Analysis (VPA)

1989 ◽  
Vol 46 (12) ◽  
pp. 2129-2139 ◽  
Author(s):  
Michael F. Lapointe ◽  
Randall M. Peterman ◽  
Alec D. MacCall
Keyword(s):  
Mortality Rate ◽  
Time Trends ◽  
Biological Effects ◽  
Population Analysis ◽  
Fish Stock ◽  
Natural Mortality ◽  
Fishing Mortality ◽  
Management Actions ◽  
Virtual Population Analysis ◽  
Virtual Population

Many researchers have reported biases in estimates offish abundance reconstructed by virtual population analysis (VPA). We document that VPA can produce changing levels of bias through time, thereby creating spurious time trends in recruitment and stock biomass estimates. We generated catch data from empirically based simulations of nine fish populations, estimated abundances using VPA with a deliberately mis-specified natural mortality rate, M, and compared the estimates to the models' "true" abundances. A period of increasing fishing mortality rate, F, combined with an overestimate of M produced spurious decreasing time trends in estimated abundance and recruitment, even when the true time series of F was known. Analogously, an underestimate of M led to a spurious increasing time trend. Bias was increased by a higher true M, and (for a given total change in F) by a slower increase in F. Because field estimates of M are uncertain and trends in F are common, some apparent trends (or lack of them) in abundances reconstructed by VPA may be artifacts. Therefore, inferences about the results of past management actions and about physical or biological effects on variability in recruitment must be made cautiously when VPA estimates are used.

scholarly journals Among-stock comparisons for improving stock assessments of data-poor stocks: the “Robin Hood” approach

2011 ◽  
Vol 68 (5) ◽  
pp. 972-981 ◽  
Author(s):  
André E. Punt ◽  
David C. Smith ◽  
Anthony D. M. Smith
Keyword(s):  
Marine Science ◽  
Fishing Mortality ◽  
Robin Hood ◽  
Estimated Parameters ◽  
Stock Assessments ◽  
Time Information

Abstract Punt, A. E., Smith, D. C., and Smith, A. D. M. 2011. Among-stock comparisons for improving stock assessments of data-poor stocks: the “Robin Hood” approach. – ICES Journal of Marine Science, 68: 972–981. An approach is outlined for conducting stock assessments in which parameters are estimated for multiple stocks at the same time. Information from data-rich stock assessments, e.g. trends in fishing mortality, and values for parameters of selectivity functions are provided to data-poor assessments in the form of penalties on the estimated parameters, which leads to stock assessments for the most data-poor stocks being informed by those for the most data-rich stocks. The method is applied for example purposes to data for nine stocks in Australia's southern and eastern scalefish and shark fishery. The results of the application confirm that results for data-rich stocks are little impacted by being assessed in conjunction with data-poor stocks and that the results for data-poor stocks can be qualitatively different when information for data-rich stocks is taken into account.

Virtual Population Analysis (VPA) Equations for Nonhomogeneous Populations, and a Family of Approximations Including Improvements on Pope's Cohort Analysis

1986 ◽  
Vol 43 (12) ◽  
pp. 2406-2409 ◽  
Author(s):  
Alec D. MacCall
Keyword(s):  
Mortality Rate ◽  
Population Analysis ◽  
Seasonal Pattern ◽  
Cohort Analysis ◽  
Natural Mortality ◽  
Close Approximation ◽  
Virtual Population Analysis ◽  
Virtual Population ◽  
Special Case

A set of "backward" virtual population analysis (VPA) equations relates catch (Ct) from continuous fishing between times t and t + 1 to population n size (Nt, Nt+1) when a portion of the stock is unavailable to fishing. The usual VPA equations become a special case where the entire stock is available (i.e. the stock is homogeneous). A close approximation to the VPA equations is Nt = Nt+1 exp(M) + CtM/(1 − exp(−M)), which has properties similar to Pope's "cohort analysis" and is somewhat more accurate in the case of a continuous fishery, especially if the natural mortality rate (M) is large. Much closer simple approximations are possible if the seasonal pattern of catches is known.

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