Assessment of Atlantic Red Drum for 1999: Northern and southern regions

An assessment of the status of the Atlantic stock of red drum is conducted using recreational and commercial data from 1986 through 1998. This assessment updates data and analyses from the 1989, 1991, 1992 and 1995 stock assessments on Atlantic coast red drum (Vaughan and Helser, 1990; Vaughan 1992; 1993; 1996). Since 1981, coastwide recreational catches ranged between 762,300 pounds in 1980 and 2,623,900 pounds in 1984, while commercial landings ranged between 60,900 pounds in 1997 and 422,500 pounds in 1984. In weight of fish caught, Atlantic red drum constitute predominantly a recreational fishery (ranging between 85 and 95% during the 1990s). Commercially, red drum continue to be harvested as part of mixed species fisheries. Using available length-frequency distributions and age-length keys, recreational and commercial catches are converted to catch in numbers at age. Separable and tuned virtual population analyses are conducted on the catch in numbers at age to obtain estimates of fishing mortality rates and population size (including recruitment to age 1). In tum, these estimates of fishing mortality rates combined with estimates of growth (length and weight), sex ratios, sexual maturity and fecundity are used to estimate yield per recruit, escapement to age 4, and static (or equilibrium) spawning potential ratio (static SPR, based on both female biomass and egg production). Three virtual analysis approaches (separable, spreadsheet, and FADAPT) were applied to catch matrices for two time periods (early: 1986-1991, and late: 1992-1998) and two regions (Northern: North Carolina and north, and Southern: South Carolina through east coast of Florida). Additional catch matrices were developed based on different treatments for the catch-and-release recreationally-caught red drum (B2-type). These approaches included assuming 0% mortality (BASEO) versus 10% mortality for B2 fish. For the 10% mortality on B2 fish, sizes were assumed the same as caught fish (BASEl), or positive difference in size distribution between the early period and the later period (DELTA), or intermediate (PROP). Hence, a total of 8 catch matrices were developed (2 regions, and 4 B2 assumptions for 1986-1998) to which the three VPA approaches were applied. The question of when offshore emigration or reduced availability begins (during or after age 3) continues to be a source of bias that tends to result in overestimates of fishing mortality. Additionally, the continued assumption (Vaughan and Helser, 1990; Vaughan 1992; 1993; 1996) of no fishing mortality on adults (ages 6 and older), causes a bias that results in underestimates of fishing mortality for adult ages (0 versus some positive value). Because of emigration and the effect of the slot limit for the later period, a range in relative exploitations of age 3 to age 2 red drum was considered. Tuning indices were developed from the MRFSS, and state indices for use in the spreadsheet and FADAPT VPAs. The SAFMC Red Drum Assessment Group (Appendix A) favored the FADAPT approach with catch matrix based on DELTA and a selectivity for age 3 relative to age 2 of 0.70 for the northern region and 0.87 for the southern region. In the northern region, estimates of static SPR increased from about 1.3% for the period 1987-1991 to approximately 18% (15% and 20%) for the period 1992-1998. For the southern region, estimates of static SPR increased from about 0.5% for the period 1988-1991 to approximately 15% for the period 1992-1998. Population models used in this assessment (specifically yield per recruit and static spawning potential ratio) are based on equilibrium assumptions: because no direct estimates are available as to the current status of the adult stock, model results imply potential longer term, equilibrium effects. Because current status of the adult stock is unknown, a specific rebuilding schedule cannot be determined. However, the duration of a rebuilding schedule should reflect, in part, a measure of the generation time of the fish species under consideration. For a long-lived, but relatively early spawning, species as red drum, mean generation time would be on the order of 15 to 20 years based on age-specific egg production. Maximum age is 50 to 60 years for the northern region, and about 40 years for the southern region. The ASMFC Red Drum Board's first phase recovery goal of increasing %SPR to at least 10% appears to have been met. (PDF contains 79 pages)

A generalized stock production model

(PDF contains 83 pages.)

German Eel Model (GEM II) for describing eel, Anguilla anguilla (L.), stock dynamics in the river Elbe system

The eel, Anguilla anguilla (L.), stock of the river Elbe severely decreased during the last decades. Detailed knowledge of the stock dynamics in freshwater and especially of the impact factors is necessary to take effective measures for stock conservation and improvement. The dynamics of the eel stock are modelled based on immigration, stocking, natural mortality and mortalities caused by fishing, angling, cormorants and hydropower plants. The model estimates the number of emigrating eel. Moreover, it enables to study the sensitivity of the estimates related to the uncertainty of the source data of the different influencing factors. The model may be used to develop management strategies and to assess the effi ciency of different management options. Zusammenfassung Der Aalbestand im Elbesystem ist in den letzten Jahrzehnten stark zur

A catch-free stock assessment model with application to goliath grouper (Epinephelus itajara) off southern Florida

Many modern stock assessment methods provide the machinery for determining the status of a stock in relation to certain reference points and for estimating how quickly a stock can be rebuilt. However, these methods typically require catch data, which are not always available. We introduce a model-based framework for estimating reference points, stock status, and recovery times in situations where catch data and other measures of absolute abundance are unavailable. The specif ic estimator developed is essentially an age-structured production model recast in terms relative to pre-exploitation levels. A Bayesian estimation scheme is adopted to allow the incorporation of pertinent auxiliary information such as might be obtained from meta-analyses of similar stocks or anecdotal observations. The approach is applied to the population of goliath grouper (Epinephelus itajara) off southern Florida, for which there are three indices of relative abundance but no reliable catch data. The results confirm anecdotal accounts of a marked decline in abundance during the 1980s followed by a substantial increase after the harvest of goliath grouper was banned in 1990. The ban appears to have reduced fishing pressure to between 10% and 50% of the levels observed during the 1980s. Nevertheless, the predicted fishing mortality rate under the ban appears to remain substantial, perhaps owing to illegal harvest and depth-related release mortality. As a result, the base model predicts that there is less than a 40% chance that the spawning biomass will recover to a level that would produce a 50% spawning potential ratio.

A simple spreadsheet model to incorporate seasonal growth into length-based stock assessment methods

The paper describes a method by which seasonal growth can be incorporated into length-converted catch curves and cohort analyses using a spreadsheet. The method is based on calculating the length of fish using seasonal growth parameters on a daily basis. A LOOKUP function is then used to find the age corresponding to the length.

A general framework for integrating environmental time series into stock assessment models: model description, simulation testing, and example

We present a method to integrate environmental time series into stock assessment models and to test the significance of correlations between population processes and the environmental time series. Parameters that relate the environmental time series to population processes are included in the stock assessment model, and likelihood ratio tests are used to determine if the parameters improve the fit to the data significantly. Two approaches are considered to integrate the environmental relationship. In the environmental model, the population dynamics process (e.g. recruitment) is proportional to the environmental variable, whereas in the environmental model with process error it is proportional to the environmental variable, but the model allows an additional temporal variation (process error) constrained by a log-normal distribution. The methods are tested by using simulation analysis and compared to the traditional method of correlating model estimates with environmental variables outside the estimation procedure. In the traditional method, the estimates of recruitment were provided by a model that allowed the recruitment only to have a temporal variation constrained by a log-normal distribution. We illustrate the methods by applying them to test the statistical significance of the correlation between sea-surface temperature (SST) and recruitment to the snapper (Pagrus auratus) stock in the Hauraki Gulf–Bay of Plenty, New Zealand. Simulation analyses indicated that the integrated approach with additional process error is superior to the traditional method of correlating model estimates with environmental variables outside the estimation procedure. The results suggest that, for the snapper stock, recruitment is positively correlated with SST at the time of spawning.

Stock assessment of the gulf menhaden, Brevoortia patronus, fishery

A stock assessment of the gulf menhaden. Brevoortia patronus, fishery was conducted with data on purse-seine landings from 1946 to 1985 and port sampling data from 1964 to 1985. These data were analyzed to determine growth rates, yield-per-recruit, spawner-recruit relationships, and maximum sustainable yield (MSY). Virtual population analysis was used to estimate stock size, year-class size, and fishing mortality rates. During the period studied, an average of 27% of age-l fish and 55% of age-2 and age-3 fish were taken by the fishery, and 54% for age-I and 38% for age-2 and -3 fish were lost annually to natural causes. Annual yield-per-recruit estimates ranged from 6.9 to 19.3 g, with recent mean conditions averaging 12.2 g since 1978. Surplus production models produced estimates of MSY from 620 to 700 kilometric tons. Recruits to age-I ranged from 8.3 to 41.8 billion fish for 1964-82. Although there was substantial scatter about the fitted curves, Ricker·type spawner-recruit relationships were found suitable for use in a population simulation model. Estimates of MSY from population simulation model runs ranged from 705 to 825 kilometric tons with F -multiples of the mean rate of fishing ranging from 1.0 to 1.5. Recent harvests in excess of the historical MSY may not be detrimental to the gulf menhaden stock. However, one should not expect long-term harvesting above the historical MSY because of the short life span of gulf menhaden and possible changes from currently favorable environmental conditions supporting high recruitment.(PDF file contains 24 pages.)

TUNPOP: A simulation of the dynamics and structure of the yellowfin tuna stock and surface fishery of the Eastern Pacific Ocean

ENGLISH: Three distinct versions of TUNP0P, an age-structured computer simulation model of the eastern Pacific yellowfin tuna, Thunnus albacores, stock and surface tuna fishery, are used to reveal mechanisms which appear to have a significant effect on the fishery dynamics. Real data on this fishery are used to make deductions on the distribution of the fish and to show how that distribution might influence events in the fishery. The most important result of the paper is that the concept of the eastern Pacific yellowfin tuna stock as a homogeneous unit is inadequate to represent the recent history of the fishery. Inferences are made on the size and distribution of the underlying stock as well as its potential yield to the surface fishery as a result of alterations in the level and distribution of the effort. SPANISH: Se han empleado tres versiones diferentes de TUNP0P, un modelo de simulación de la computadora (basado en la estructura de la edad) de la población y la pesca epipelágica del atún aleta amarilla, Tbunnus albacares, del Pacífico oriental, para revelar los mecanismos que parecen tener un efecto importante en la dinámica pesquera. Se emplean los datos verdaderos de esta pesca para hacer deducciones sobre la distribución de los peces y para mostrar cómo puede influir esta distribución en los eventos de pesca. La conclusión más importante de este estudio es que el concepto de que la población del aleta amarilla del Pacífico oriental es una unidad homogénea, es inadecuado para representar la historia reciente de pesca. Se teoriza sobre la talla y distribución de la población subyacente como también sobre su producción potencial en la pesca epipelágica al cambiar el nivel y distribución del esfuerzo.

Interactions of age-dependent mortality and selectivity functions in age-based stock assessment models

The natural mortality rate (M) of fish varies with size and age, although it is often assumed to be constant in stock assessments. Misspecification of M may bias important assessment quantities. We simulated fishery data, using an age-based population model, and then conducted stock assessments on the simulated data. Results were compared to known values. Misspecification of M had a negligible effect on the estimation of relative stock depletion; however, misspecification of M had a large effect on the estimation of parameters describing the stock recruitment relationship, age-specific selectivity, and catchability. If high M occurs in juvenile and old fish, but is misspecified in the assessment model, virgin biomass and catchability are often poorly estimated. In addition, stock recruitment relationships are often very difficult to estimate, and steepness values are commonly estimated at the upper bound (1.0) and overfishing limits tend to be biased low. Natural mortality can be estimated in assessment models if M is constant across ages or if selectivity is asymptotic. However if M is higher in old fish and selectivity is dome-shaped, M and the selectivity cannot both be adequately estimated because of strong interactions between M and selectivity.

A meta-analytic approach to quantifying scientific uncertainty in stock assessments

Quantifying scientific uncertainty when setting total allowable catch limits for fish stocks is a major challenge, but it is a requirement in the United States since changes to national fisheries legislation. Multiple sources of error are readily identifiable, including estimation error, model specification error, forecast error, and errors associated with the definition and estimation of reference points. Our focus here, however, is to quantify the influence of estimation error and model specification error on assessment outcomes. These are fundamental sources of uncertainty in developing scientific advice concerning appropriate catch levels and although a study of these two factors may not be inclusive, it is feasible with available information. For data-rich stock assessments conducted on the U.S. west coast we report approximate coefficients of variation in terminal biomass estimates from assessments based on inversion of the assessment of the model’s Hessian matrix (i.e., the asymptotic standard error). To summarize variation “among” stock assessments, as a proxy for model specification error, we characterize variation among multiple historical assessments of the same stock. Results indicate that for 17 groundfish and coastal pelagic species, the mean coefficient of variation of terminal biomass is 18%. In contrast, the coefficient of variation ascribable to model specification error (i.e., pooled among-assessment variation) is 37%. We show that if a precautionary probability of overfishing equal to 0.40 is adopted by managers, and only model specification error is considered, a 9% reduction in the overfishing catch level is indicated.

Using experiments and expert judgment to model catchability of Pacific rockfishes in trawl surveys, with application to bocaccio (Sebastes paucispinis) off British Columbia

The time series of abundance indices for many groundfish populations, as determined from trawl surveys, are often imprecise and short, causing stock assessment estimates of abundance to be imprecise. To improve precision, prior probability distributions (priors) have been developed for parameters in stock assessment models by using meta-analysis, expert judgment on catchability, and empirically based modeling. This article presents a synthetic approach for formulating priors for rockfish trawl survey catchability (qgross). A multivariate prior for qgross for different surveys is formulated by using 1) a correction factor for bias in estimating fish density between trawlable and untrawlable areas, 2) expert judgment on trawl net catchability, 3) observations from trawl survey experiments, and 4) data on the fraction of population biomass in each of the areas surveyed. The method is illustrated by using bocaccio (Sebastes paucipinis) in British Columbia. Results indicate that expert judgment can be updated markedly by observing the catch-rate ratio from different trawl gears in the same areas. The marginal priors for qgross are consistent with empirical estimates obtained by fitting a stock assessment model to the survey data under a noninformative prior for qgross. Despite high prior uncertainty (prior coefficients of variation ≥0.8) and high prior correlation between qgross, the prior for qgross still enhances the precision of key stock assessment quantities.

Measurement errors in body size of sea scallops (Placopecten magellanicus) and their effect on stock assessment models

Body-size measurement errors are usually ignored in stock assessments, but may be important when body-size data (e.g., from visual sur veys) are imprecise. We used experiments and models to quantify measurement errors and their effects on assessment models for sea scallops (Placopecten magellanicus). Errors in size data obscured modes from strong year classes and increased frequency and size of the largest and smallest sizes, potentially biasing growth, mortality, and biomass estimates. Modeling techniques for errors in age data proved useful for errors in size data. In terms of a goodness of model fit to the assessment data, it was more important to accommodate variance than bias. Models that accommodated size errors fitted size data substantially better. We recommend experimental quantification of errors along with a modeling approach that accommodates measurement errors because a direct algebraic approach was not robust and because error parameters were diff icult to estimate in our assessment model. The importance of measurement errors depends on many factors and should be evaluated on a case by case basis.

Defining plausible migration rates based on historical tagging data: a Bayesian mark-recapture model applied to English sole (Parophrys vetulus)

A generalized Bayesian population dynamics model was developed for analysis of historical mark-recapture studies. The Bayesian approach builds upon existing maximum likelihood methods and is useful when substantial uncertainties exist in the data or little information is available about auxiliary parameters such as tag loss and reporting rates. Movement rates are obtained through Markov-chain Monte-Carlo (MCMC) simulation, which are suitable for use as input in subsequent stock assessment analysis. The mark-recapture model was applied to English sole (Parophrys vetulus) off the west coast of the United States and Canada and migration rates were estimated to be 2% per month to the north and 4% per month to the south. These posterior parameter distributions and the Bayesian framework for comparing hypotheses can guide fishery scientists in structuring the spatial and temporal complexity of future analyses of this kind. This approach could be easily generalized for application to other species and more data-rich fishery analyses.

A Bayesian method for identification of stock mixtures from molecular marker data

Molecular markers have been demonstrated to be useful for the estimation of stock mixture proportions where the origin of individuals is determined from baseline samples. Bayesian statistical methods are widely recognized as providing a preferable strategy for such analyses. In general, Bayesian estimation is based on standard latent class models using data augmentation through Markov chain Monte Carlo techniques. In this study, we introduce a novel approach based on recent developments in the estimation of genetic population structure. Our strategy combines analytical integration with stochastic optimization to identify stock mixtures. An important enhancement over previous methods is the possibility of appropriately handling data where only partial baseline sample information is available. We address the potential use of nonmolecular, auxiliary biological information in our Bayesian model.

A prior for steepness in stock-recruitment relationships, based on an evolutionary persistence principle

Priors are existing information or beliefs that are needed in Bayesian analysis. Informative priors are important in obtaining the Bayesian posterior distributions for estimated parameters in stock assessment. In the case of the steepness parameter (h), the need for an informative prior is particularly important because it determines the stock-recruitment relationships in the model. However, specifications of the priors for the h parameter are often subjective. We used a simple population model to derive h priors based on life history considerations. The model was based on the evolutionary principle that persistence of any species, given its life history (i.e., natural mortality rate) and its exposure to recruitment variability, requires a minimum recruitment compensation that enables the species to rebound consistently from low critical abundances (Nc). Using the model, we derived the prior probability distributions of the h parameter for fish species that have a range of natural mortality, recruitment variabilities, and Nt values.