Estimating relative abundance from catch and effort data, using neural networks

We develop and test a method to estimate relative abundance from catch and effort data using neural networks. Most stock assessment models use time series of relative abundance as their major source of information on abundance levels. These time series of relative abundance are frequently derived from catch-per-unit-of-effort (CPUE) data, using general linearized models (GLMs). GLMs are used to attempt to remove variation in CPUE that is not related to the abundance of the population. However, GLMs are restricted in the types of relationships between the CPUE and the explanatory variables. An alternative approach is to use structural models based on scientific understanding to develop complex non-linear relationships between CPUE and the explanatory variables. Unfortunately, the scientific understanding required to develop these models may not be available. In contrast to structural models, neural networks uses the data to estimate the structure of the non-linear relationship between CPUE and the explanatory variables. Therefore neural networks may provide a better alternative when the structure of the relationship is uncertain. We use simulated data based on a habitat based-method to test the neural network approach and to compare it to the GLM approach. Cross validation and simulation tests show that the neural network performed better than nominal effort and the GLM approach. However, the improvement over GLMs is not substantial. We applied the neural network model to CPUE data for bigeye tuna (Thunnus obesus) in the Pacific Ocean.

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.

Quantum ricochets: surface capture, release and energy loss of fast ions hitting a polar surface at grazing incidence

A diffraction mechanism is proposed for the capture, multiple bouncing and final escape of a fast ion (keV) impinging on the surface of a polarizable material at grazing incidence. Capture and escape are effected by elastic quantum diffraction consisting of the exchange of a parallel surface wave vector G= 2p/ a between the ion parallel momentum and the surface periodic potential of period a. Diffraction- assisted capture becomes possible for glancing angles F smaller than a critical value given by Fc 2- 2./ a-| Vim|/ E, where E is the kinetic energy of the ion,. = h/ Mv its de Broglie wavelength and Vim its average electronic image potential at the distance from the surface where diffraction takes place. For F< Fc, the ion can fall into a selected capture state in the quasi- continuous spectrum of its image potential and execute one or several ricochets before being released by the time reversed diffraction process. The capture, ricochet and escape are accompanied by a large, periodic energy loss of several tens of eV in the forward motion caused by the coherent emission of a giant number of quanta h. of Fuchs- Kliewer surface phonons characteristic of the polar material. An analytical calculation of the energy loss spectrum, based on the proposed diffraction process and using a model ion-phonon coupling developed earlier (Lucas et al 2013 J. Phys.: Condens. Matter 25 355009), is presented, which fully explains the experimental spectrum of Villette et al (2000 Phys. Rev. Lett. 85 3137) for Ne+ ions ricocheting on a LiF(001) surface.

An analysis of the historical catch data from the migratory salmonid fisheries of the River Ribble

The Ribble catchment is the largest and most diverse river system within National Rivers Authority (NRA), North West's Central Area. The river is approximately 100km in length and rises in a limestone area west of the Pennines. This report examines changes in the size and composition of the salmon and sea trout catches from the Ribble migratory salmonid fisheries during the years 1937 to 1991. Comparisons are made between the rod and net fisheries for both salmon and sea trout of the Ribble and Hodder. Patterns of catches shown by the Ribble fisheries are compared with those of other individual rivers and with patterns for the North West Region as a whole. An attempt is made to identify if any relationship exists between catch and stock abundance. Catch patterns shown by the Ribble and Hodder salmon fisheries are compared with electronic resistivity counter data from the two rivers. Annual salmon catch patterns and redd count data are compared both locally and regionally. Recommendations for future studies are made in the light of the report's findings.

An analysis of salmon rod catch data from castle fisheries, River Derwent, 1923-1989.

The aim of this study was to investigate the historical catch record from the Castle Fishery on the River Derwent over the period 1923 - 1989, to determine if changes had taken place in the composition of the catch and to examine the influence of flow on the performance of the fishery. The River Derwent is situated in West Cumbria, North West England. It flows from its source on Scafell Pike (NGR NY 229 089) westwards discharging into the Irish sea at Workington, a distance of 52 km. Over its length it receives water from an additional 214 km of stream, 5 large lakes and approximately 30 small tarns. The catchment drains a total area of 663 km2. The study concludes that through the time period there was considerable variation in catch between years. The trend was for the catch to increase steadily over the period 1923 - 1958, declining rapidly in 1959, after which catches increased steadily reaching a peak in the mid-sixties, before declining towards the end of the decade. During the seventies and eighties catches remained relatively stable at between 300 - 600 salmon per year until 1988 when over 2000 salmon were reported caught, the greatest number in any year over the study period.

An analysis of migratory salmonid catch effort data, derived from anglers' log books, 1991

1000 log books were issued to anglers of which 236 were returned, those from the rivers Derwent, Kent, Lune and Ribble accounted for the vast majority. The Derwent had the highest catch rate of these rivers: one salmon every 13.89 hours followed by the Lune, Kent and Ribble at 16.39, 18.87 and 35.71 hours, respectively. For sea trout the Lune, Derwent and Ribble had a catch rate of approximately one fish every 10.0 hours (9.8, 10.0 and 10.64 hours),and for the Kent one fish per 16.1 hours fished. Salmon angling visits were, in general,longer than those for sea trout being between 2 and 6 hours as opposed to 2 to 4 hours. On the majority of visits (>80%) no fish were caught and was the same for salmon and sea trout. For salmon the majority of fish were caught on fly, spinner or worm, and the least on prawn. For sea trout fly predominated. The majority of salmon caught were less than 91b in weight and were presumed to be grilse (1 sea winter). The majority of the sea trout caught weighed between 1 and 31b. The pattern of catch, effort, CPUE, abundance and catchability for salmon and sea trout were modelled using the data from the rivers Derwent, Kent and Lune. Flow significantly influenced catch, effort and catchability of salmon which had entered in a particular month. For sea trout flow was not significantly correlated with any of the dependent variables. The catchability coefficient for salmon, determined from the total number of fish, remained relatively constant over the period June to October indicating that CPUE was a reasonable measure of within season abundance. This was not found to be the case for sea trout.

Use of telemetric tracking to examine environmental influences on catch/effort indices. A case study of Atlantic Salmon (Salmo salar L.)in the R. Tywi, S. Wales

A case study of Atlantic Salmon runs into the R. Tyvi (S. Wales) is presented. Radio tracking of over 200 salmon in 1988 and 1989 has demonstrated that flow is an important factor in modifying both run timing and migratory success. Entry of salmon into the river is typically in response to flow events, and periods of low falling flows delay entry and may directly result in reduced runs into the river. Delayed entry may also increase the proportion of the run migrating after the end of both rod and net fishing seasons. The implications of these results for net and rod catch and catch/effort data are discussed, using both statutory reported catch data and data from specific catch/effort studies. Flow is demonstrated to be a dominant factor in determining the within-season distribution of rod catch and catch/effort during low-flow years. Estuarial seine net catch and catch/effort tend to be controlled more by time of return than by flow although low flows may delay runs. Annual reported rod catch is correlated with flow, which controls in season availability, catchability and consequently the amount of fishing effort. Use of catch or catch/effort data should take account of inter-year variations in flow and other environmental factors. Although catch and catch/effort are valuable indicators of fishery performance, they are inadequate to represent changing stock levels.

Catch rates and demographics of loggerhead sea turtles (Caretta caretta) captured from the Charleston, South Carolina, shipping channel during the period of mandatory use of turtle excluder devices (TEDs)

Trawling was conducted in the Charleston, South Carolina, shipping channel between May and August during 2004–07 to evaluate loggerhead sea turtle (Caretta caretta) catch rates and demographic distributions. Two hundred and twenty individual loggerheads were captured in 432 trawling events during eight sampling periods lasting 2–10 days each. Catch was analyzed by using a generalized linear model. Data were fitted to a negative binomial distribution with the log of standardized sampling effort (i.e., an hour of sampling with a net head rope length standardized to 30.5 m) for each event treated as an offset term. Among 21 variables, factors, and interactions, five terms were significant in the final model, which accounted for 45% of model deviance. Highly significant differences in catch were noted among sampling periods and sampling locations within the channel, with greatest catch furthest seaward consistent with historical observations. Loggerhead sea turtle catch rates in 2004–07 were greater than in 1991–92 when mandatory use of turtle excluder devices was beginning to be phased in. Concurrent with increased catch rates, loggerheads captured in 2004–07 were larger than in 1991–92. Eighty-five percent of loggerheads captured were ≤75.0 cm straight-line carapace length (nuchal notch to tip of carapace) and there was a 3.9:1 female-to-male bias, consistent with limited data for this location two decades earlier. Only juvenile loggerheads ≤75.0 cm possessed haplotypes other than CC-A01 or CC-A02 that dominate in the region. Six rare and one un-described haplotype were predominantly found in June 2004.

Postrelease survival, vertical and horizontal movements, and thermal habitats of five species of pelagic sharks in the central Pacific Ocean

From 2001 to 2006, 71 pop-up satellite archival tags (PSATs) were deployed on five species of pelagic shark (blue shark [Prionace glauca]; shortfin mako [Isurus oxyrinchus]; silky shark [Carcharhinus falciformis]; oceanic whitetip shark [C. longimanus]; and bigeye thresher [Alopias superciliosus]) in the central Pacific Ocean to determine species-specific movement patterns and survival rates after release from longline fishing gear. Only a single postrelease mortality could be unequivocally documented: a male blue shark which succumbed seven days after release. Meta-analysis of published reports and the current study (n=78 reporting PSATs) indicated that the summary effect of postrelease mortality for blue sharks was 15% (95% CI, 8.5–25.1%) and suggested that catch-and-release in longline fisheries can be a viable management tool to protect parental biomass in shark populations. Pelagic sharks displayed species-specific depth and temperature ranges, although with significant individual temporal and spatial variability in vertical movement patterns, which were also punctuated by stochastic events (e.g., El Niño-Southern Oscillation). Pelagic species can be separated into three broad groups based on daytime temperature preferences by using the unweighted pair-group method with arithmetic averaging clustering on a Kolmogorov-Smirnov Dmax distance matrix: 1) epipelagic species (silky and oceanic whitetip sharks), which spent >95% of their time at temperatures within 2°C of sea surface temperature; 2) mesopelagic-I species (blue sharks and shortfin makos, which spent 95% of their time at temperatures from 9.7° to 26.9°C and from 9.4° to 25.0°C, respectively; and 3) mesopelagic-II species (bigeye threshers), which spent 95% of their time at temperatures from 6.7° to 21.2°C. Distinct thermal niche partitioning based on body size and latitude was also evident within epipelagic species.

Changes in catch rates and length and age at maturity, but not growth, of an estuarine plotosid (Cnidoglanis macrocephalus) after heavy fishing

The hypothesis that heavy fishing pressure has led to changes in the biological characteristics of the estuary cobbler (Cnidoglanis macrocephalus) was tested in a large seasonally open estuary in southwestern Australia, where this species completes its life cycle and is the most valuable commercial fish species. Comparisons were made between seasonal data collected for this plotosid (eeltail catfish) in Wilson Inlet during 2005–08 and those recorded with the same fishery-independent sampling regime during 1987–89. These comparisons show that the proportions of larger and older individuals and the catch rates in the more recent period were far lower, i.e., they constituted reductions of 40% for fish ≥430 mm total length, 62% for fish ≥4 years of age, and 80% for catch rate. In addition, total mortality and fishing-induced mortality estimates increased by factors of ~2 and 2.5, respectively. The indications that the abundance and proportion of older C. macrocephalus declined between the two periods are consistent with the perception of long-term commercial fishermen and their shift toward using a smaller maximum gill net mesh to target this species. The sustained heavy fishing pressure on C. macrocephalus between 1987–89 and 2005–08 was accompanied by a marked reduction in length and age at maturity of this species. The shift in probabilistic maturation reaction norms toward smaller fish in 2005–08 and the lack of a conspicuous change in growth between the two periods indicate that the maturity changes were related to fishery-induced evolution rather than to compensatory responses to reduced fish densities.