The measurement error in marine survey catches: the bottom trawl case

We have formulated a model for analyzing the measurement error in marine survey abundance estimates by using data from parallel surveys (trawl haul or acoustic measurement). The measurement error is defined as the component of the variability that cannot be explained by covariates such as temperature, depth, bottom type, etc. The method presented is general, but we concentrate on bottom trawl catches of cod (Gadus morhua). Catches of cod from 10 parallel trawling experiments in the Barents Sea with a total of 130 paired hauls were used to estimate the measurement error in trawl hauls. Based on the experimental data, the measurement error is fairly constant in size on the logarithmic scale and is independent of location, time, and fish density. Compared with the total variability of the winter and autumn surveys in the Barents Sea, the measurement error is small (approximately 2–5%, on the log scale, in terms of variance of catch per towed distance). Thus, the cod catch rate is a fairly precise measure of fish density at a given site at a given time.

Stock assessment of protogynous fish: evaluating measures of spawning biomass used to estimate biological reference points

In stock assessments, recruitment is typically modeled as a function of females only. For protogynous stocks, however, disproportionate fishing on males increases the possibility of reduced fertilization rates. To incorporate the importance of males in protogynous stocks, assessment models have been used to predict recruitment not just from female spawning biomass (Sf), but also from that of males (Sm) or both sexes (Sb). We conducted a simulation study to evaluate the ability of these three measures to estimate biological reference points used in fishery management. Of the three, Sf provides best estimates if the potential for decreased fertilization is weak, whereas Sm is best only if the potential is very strong. In general, Sb estimates the true reference points most closely, which indicates that if the potential for decreased fertilization is moderate or unknown, Sb should be used in assessments of protogynous stocks. Moreover, for a broad range of scenarios, relative errors from Sf and Sb occur in opposite directions, indicating that estimates from these measures could be used to bound uncertainty.

A-SCALA: an age-structured statistical catch-at-length analysis for assessing tuna stocks in the eastern tropical Pacific Ocean

English: We describe an age-structured statistical catch-at-length analysis (A-SCALA) based on the MULTIFAN-CL model of Fournier et al. (1998). The analysis is applied independently to both the yellowfin and the bigeye tuna populations of the eastern Pacific Ocean (EPO). We model the populations from 1975 to 1999, based on quarterly time steps. Only a single stock for each species is assumed for each analysis, but multiple fisheries that are spatially separate are modeled to allow for spatial differences in catchability and selectivity. The analysis allows for error in the effort-fishing mortality relationship, temporal trends in catchability, temporal variation in recruitment, relationships between the environment and recruitment and between the environment and catchability, and differences in selectivity and catchability among fisheries. The model is fit to total catch data and proportional catch-at-length data conditioned on effort. The A-SCALA method is a statistical approach, and therefore recognizes that the data collected from the fishery do not perfectly represent the population. Also, there is uncertainty in our knowledge about the dynamics of the system and uncertainty about how the observed data relate to the real population. The use of likelihood functions allow us to model the uncertainty in the data collected from the population, and the inclusion of estimable process error allows us to model the uncertainties in the dynamics of the system. The statistical approach allows for the calculation of confidence intervals and the testing of hypotheses. We use a Bayesian version of the maximum likelihood framework that includes distributional constraints on temporal variation in recruitment, the effort-fishing mortality relationship, and catchability. Curvature penalties for selectivity parameters and penalties on extreme fishing mortality rates are also included in the objective function. The mode of the joint posterior distribution is used as an estimate of the model parameters. Confidence intervals are calculated using the normal approximation method. It should be noted that the estimation method includes constraints and priors and therefore the confidence intervals are different from traditionally calculated confidence intervals. Management reference points are calculated, and forward projections are carried out to provide advice for making management decisions for the yellowfin and bigeye populations. Spanish: Describimos un análisis estadístico de captura a talla estructurado por edad, A-SCALA (del inglés age-structured statistical catch-at-length analysis), basado en el modelo MULTIFAN- CL de Fournier et al. (1998). Se aplica el análisis independientemente a las poblaciones de atunes aleta amarilla y patudo del Océano Pacífico oriental (OPO). Modelamos las poblaciones de 1975 a 1999, en pasos trimestrales. Se supone solamente una sola población para cada especie para cada análisis, pero se modelan pesquerías múltiples espacialmente separadas para tomar en cuenta diferencias espaciales en la capturabilidad y selectividad. El análisis toma en cuenta error en la relación esfuerzo-mortalidad por pesca, tendencias temporales en la capturabilidad, variación temporal en el reclutamiento, relaciones entre el medio ambiente y el reclutamiento y entre el medio ambiente y la capturabilidad, y diferencias en selectividad y capturabilidad entre pesquerías. Se ajusta el modelo a datos de captura total y a datos de captura a talla proporcional condicionados sobre esfuerzo. El método A-SCALA es un enfoque estadístico, y reconoce por lo tanto que los datos obtenidos de la pesca no representan la población perfectamente. Además, hay incertidumbre en nuestros conocimientos de la dinámica del sistema e incertidumbre sobre la relación entre los datos observados y la población real. El uso de funciones de verosimilitud nos permite modelar la incertidumbre en los datos obtenidos de la población, y la inclusión de un error de proceso estimable nos permite modelar las incertidumbres en la dinámica del sistema. El enfoque estadístico permite calcular intervalos de confianza y comprobar hipótesis. Usamos una versión bayesiana del marco de verosimilitud máxima que incluye constreñimientos distribucionales sobre la variación temporal en el reclutamiento, la relación esfuerzo-mortalidad por pesca, y la capturabilidad. Se incluyen también en la función objetivo penalidades por curvatura para los parámetros de selectividad y penalidades por tasas extremas de mortalidad por pesca. Se usa la moda de la distribución posterior conjunta como estimación de los parámetros del modelo. Se calculan los intervalos de confianza usando el método de aproximación normal. Cabe destacar que el método de estimación incluye constreñimientos y distribuciones previas y por lo tanto los intervalos de confianza son diferentes de los intervalos de confianza calculados de forma tradicional. Se calculan puntos de referencia para el ordenamiento, y se realizan proyecciones a futuro para asesorar la toma de decisiones para el ordenamiento de las poblaciones de aleta amarilla y patudo.

Prediction and confirmation of seasonal migration of Pacific sardine (Sardinops sagax) in the California Current Ecosystem

During the last century, the population of Pacific sardine (Sardinops sagax) in the California Current Ecosystem has exhibited large fluctuations in abundance and migration behavior. From approximately 1900 to 1940, the abundance of sardine reached 3.6 million metric tons and the “northern stock” migrated from offshore of California in the spring to the coastal areas near Oregon, Washington, and Vancouver Island in the summer. In the 1940s, the sardine stock collapsed and the few remaining sardine schools concentrated in the coastal region off southern California, year-round, for the next 50 years. The stock gradually recovered in the late 1980s and resumed its seasonal migration between regions off southern California and Canada. Recently, a model was developed which predicts the potential habitat for the northern stock of Pacific sardine and its seasonal dynamics. The habitat predictions were successfully validated using data from sardine surveys using the daily egg production method; scientific trawl surveys off the Columbia River mouth; and commercial sardine landings off Oregon, Washington, and Vancouver Island. Here, the predictions of the potential habitat and seasonal migration of the northern stock of sardine are validated using data from “acoustic–trawl” surveys of the entire west coast of the United States during the spring and summer of 2008. The estimates of sardine biomass and lengths from the two surveys are not significantly different between spring and summer, indicating that they are representative of the entire stock. The results also confirm that the model of potential sardine habitat can be used to optimally apply survey effort and thus minimize random and systematic sampling error in the biomass estimates. Furthermore, the acoustic–trawl survey data are useful to estimate concurrently the distributions and abundances of other pelagic fishes.

Measurements of resistance and reactance in fish with the use of bioelectrical impedance analysis: sources of error

New technologies can be riddled with unforeseen sources of error, jeopardizing the validity and application of their advancement. Bioelectrical impedance analysis (BIA) is a new technology in fisheries research that is capable of estimating proximate composition, condition, and energy content in fish quickly, cheaply, and (after calibration) without the need to sacrifice fish. Before BIA can be widely accepted in fisheries science, it is necessary to identify sources of error and determine a means to minimize potential errors with this analysis. We conducted controlled laboratory experiments to identify sources of errors within BIA measurements. We concluded that electrode needle location, procedure deviations, user experience, time after death, and temperature can affect resistance and reactance measurements. Sensitivity analyses showed that errors in predictive estimates of composition can be large (>50%) when these errors are experienced. Adherence to a strict protocol can help avoid these sources of error and provide BIA estimates that are both accurate and precise in a field or laboratory setting.

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.

Prosomal-width-to-weight relationships in American horseshoe crabs (Limulus polyphemus): examining conversion factors used to estimate landings

Horseshoe crabs (Limulus polyphemus) are valued by many stakeholders, including the commercial fishing industry, biomedical companies, and environmental interest groups. We designed a study to test the accuracy of the conversion factors that were used by NOAA Fisheries and state agencies to estimate horseshoe crab landings before mandatory reporting that began in 1998. Our results indicate that the NOAA Fisheries conversion factor consistently overestimates the weight of male horseshoe crabs, particularly those from New England populations. Because of the inaccuracy of this and other conversion factors, states are now mandated to report the number (not biomass) and sex of landed horseshoe crabs. However, accurate estimates of biomass are still necessary for use in prediction models that are being developed to better manage the horseshoe crab fishery. We recommend that managers use the conversion factors presented in this study to convert current landing data from numbers to biomass of harvested horseshoe crabs for future assessments.

Using the empirical Bayes method to estimate and evaluate bycatch rates of seabirds from individual fishing vessels

Minimizing bycatch of seabirds is a major goal of the U.S. National Marine Fisheries Service. In Alaska waters, the bycatch (i.e., inadvertent catches) of seabirds has been an incidental result of demersal groundfish longline fishery operations. Notably, the endangered short-tailed albatross (Phoebastria albatrus) has been taken in this groundfish fishery. Bycatch rates of seabirds from individual vessels may be of particular interest because vessels with high bycatch rates may not be functioning effectively with seabird avoidance gears, and there may be a need for suggestions on how to use these avoidance gears more effectively. Therefore, bycatch estimates are usually made on an individual vessel basis and then summed to obtain the total estimate for the entire fleet.

An approach to estimate the natural mortality rate in fish stocks

A simple approach is introduced to estimate the natural mortality rate (M) of fish stocks. The approach is based on the age at maximum cohort biomass, or critical length (L*) concept. The ratio of the critical length to the asymptotic length ( = L*/L8) is relatively constant in 141 fish stocks at 0.62 (CV = 21.4 per cent) and the relationship M = 3K(1- )/ is derived and could be used to estimate M, where K is the growth coefficient of the von Bertalanffy growth function. Average values of are given for the various Families of fish in order to estimate M based on closely related species.

Growth dynamics of the spinner shark (Carcharhinus brevipinna) off the United States southeast and Gulf of Mexico coasts: a comparison of methods

The age and growth dynamics of the spinner shark (Carcharhinus brevipinna) in the northwest Atlantic Ocean off the southeast United States and in the Gulf of Mexico were examined and four growth models were used to examine variation in the ability to fit size-at-age data. The von Bertalanffy growth model, an alternative equation of the von Bertalanffy growth model with a size-at-birth intercept, the Gompertz growth model, and a logistic model were fitted to sex-specific observed size-at-age data. Considering the statistical criteria (e.g., lowest mean square error [MSE], high coefficient-of-determination, and greatest level of significance) we desired for this study, the logistic model provided the best overall fit to the size-at-age data, whereas the von Bertalanffy growth model gave the worst. For “biological validity,” the von Bertalanffy model for female sharks provided estimates similar to those reported in other studies. However, the von Bertalanffy model was deemed inappropriate for describing the growth of male spinner sharks because estimates of theoretical maximum size (L∞) indicated a size much larger than that observed in the field. However, the growth coefficient (k= 0.14/yr) from the Gompertz model provided an estimate most similar to that reported for other large coastal species. The analysis of growth for spinner shark in the present study demonstrates the importance of fitting alternative models when standard models fit the data poorly or when growth estimates do not appear to be realistic.

Using bone measurements to estimate the original sizes of bluefish (Pomatomus saltatrix) from digested remains

The ability to estimate the original size of an ingested prey item is an important step in understanding the community and population structure of piscivorous predators (Scharf et al., 1998). More specifically, knowledge of original prey size is essential for deriving important biological information, such as predator consumption rates, biomass of the prey consumed, and selectivity of a predator towards a specific size class of prey (Hansel et al., 1988; Scharf et al., 1997; Radke et al., 2000). To accurately assess the overall “top-down” pressure a predator may exert on prey community structure, prey size is crucial. However, such information is often difficult to collect in the field (Trippel and Beamish, 1987). Stomach-content analyses are the most common methods for examining the diets of piscivorous fish, but the prey items found are often thoroughly digested and sometimes unidentifiable. As a result, obtaining a direct measurement of prey items is frequently impossible.

Application of pop-up satellite archival tag technology to estimate postrelease survival of white marlin (Tetrapturus albidus) caught on circle and straight-shank (“J”) hooks in the western North Atlantic recreational fis

Short-duration (5- or 10-day) deployments of pop-up satellite archival tags were used to estimate survival of white marlin (Tetrapturus albidus) released from the western North Atlantic recreational fishery. Forty-one tags, each recording temperature, pressure, and light level readings approximately every two minutes for 5-day tags (n= 5) or four minutes for 10-day tags (n= 36), were attached to white marlin caught with dead baits rigged on straight-shank (“J”) hooks (n =21) or circle hooks (n=20) in offshore waters of the U.S. Mid-Atlantic region, the Dominican Republic, Mexico, and Venezuela. Forty tags (97.8%) transmitted data to the satellites of the Argos system, and 33 tags (82.5%) transmitted data consistent with survival of tagged animals over the deployment duration. Approximately 61% (range: 19−95%) of all archived data were successfully recovered from each tag. Survival was significantly (P<0.01) higher for white marlin caught on circle hooks (100%) than for those caught on straight-shank (“J”) hooks (65%). Time-to-death ranged from 10 minutes to 64 hours following release for the seven documented mortalities, and five animals died within the first six hours after release. These results indicate that a simple change in hook type can significantly increase the survival of white marlin released from recreational fis

Use of skeletochronological analysis to estimate the age of leatherback sea turtles Dermochelys coriacea in the western North Atlantic

Although growth rate and age data are essential for leatherback management, estimates of these demographic parameters remain speculative due to the cryptic life history of this endangered species. Skeletochronological analysis of scleral ossicles obtained from 8 captive, known-age and 33 wild leatherbacks originating from the western North Atlantic was conducted to characterize the ossicles and the growth marks within them. Ages were accurately estimated for the known-age turtles, and their growth mark attributes were used to calibrate growth mark counts for the ossicles from wild specimens. Due to growth mark compaction and resorption, the number of marks visible at ossicle section tips was consistently and significantly greater than the number visible along the lateral edges, demonstrating that growth mark counts should be performed at the tips so that age is not underestimated. A correction factor protocol that incorporated the trajectory of early growth increments was used to estimate the number of missing marks in those ossicles exhibiting resorption, which was then added to the number of observed marks to obtain an age estimate for each turtle. A generalized smoothing spline model, von Bertalanffy growth curve, and size-at-age function were used to obtain estimates of age at maturity for leatherbacks in the western North Atlantic. Results of these analyses suggest that median age at maturation for leatherbacks in this part of the world may range from 24.5 to 29 yr. These age estimates are much greater than those proposed in previous studies and have significant implications for population management and recovery.