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.

Central area redd project [Ribble, Hodder and Lune catchments]

Redd counting is an integral part of most Fishery Officers duties. The number and distribution of salmonid redds throughout salmonid catchments provides invaluable information on the range and extent of spawning by both salmon and sea trout. A project was initiated by the Fisheries Science and Management Team of Central Area, North West Region in England in liaison with the Flood Defence function. The main objective of this project was to assess redd count data for Central Area and attempt to quantify these data in order to produce a grading system that would highlight key salmonid spawning areas. By showing which were the main areas for salmon and sea trout spawning, better informed decisions could be made on whether or not in-stream Flood Defence works should be given the go-ahead. The main salmonid catchments in Central Area were broken into individual reaches, approximately 1 km in length. The number of redds in these individual reaches were then calculated and a density per lkm value was obtained for each reach. A grading system was devised which involved looking at the range of density per km values and dividing this by five to produce 5 classes, A - E. A sixth class (F) was used where the density per Ion value was 0.00. This grading system was calculated at two levels of detail. Grades for salmon and sea trout were produced for each individual catchment and also on an Area-wide level. Maps were produced using a range of colours to represent the grade for each reach. These maps provide a highly useful overview of the status of salmonid spawning for each catchment over individual years and highlight the key salmon and sea trout spawning areas in each catchment. These maps and the associated summary data should now provide Flood Defence and Fisheries staff with a fairly detailed overview of the status of spawning in any location within the. main salmonid catchments in Central Area. Although these maps are very useful they should only be used as a guide. The current practice of consulting with the local Fishery Officer should be continued to ensure that expert local knowledge is taken into account.

A note on the von Bertalanffy growth function concerning the allocation of surplus energy to reproduction

We propose an extended form of the von Bertalanffy growth function (VBGF), where the allocation of surplus energy to reproduction is considered. Any function can be used in our model to describe the ratio of energy allocation for reproduction to that for somatic growth. As an example, two models for energy allocation were derived: a step-function and a logistic function. The extended model can jointly describe growth in adult and juvenile stages. The change in growth rate between the two stages can be either gradual or steep; the latter gives a biphasic VBGF. The results of curve fitting indicated that a consideration of reproductive energy is meaningful for model extension. By controlling parameter values, our comprehensive model gives various growth curve shapes ranging from indeterminate to determinate growth. An increase in the number of parameters is unavoidable in practical applications of this new model. Additional information on reproduction will improve the reliability of model estimates.

An objective method to monitor and quantify texture of salted herring during ripening in barrels at 4°C

Changes in the texture (elastic nature) of the flesh of barrel salted herring during the ripening process at 4°C have been monitored. The method employs the analysis of stress-relaxation curves after compression to half of the sample thickness on an lnstron Model 1112. The parameter 'T/P' for each sample represents the reciprocal of the gradient of a line connecting P and T0.368p. This parameter characteristic of each sample's texture was calculated as the ratio of 'T/P' where, T is the relaxation time and is defined as the time required for a stress at constant strain to decrease to 1/e of its original value, where 'e' is the base of natural logarithms (2.7183). Since 1/e=0.368, the relaxation time is the time required for the force to decay to 36.8% of its original value. P is the peak height of the curve (i.e. the force value at the maximum height). This method was adopted from the bakery industry for testing the degree of gluten development in bread dough. The 'T/P' values obtained over the course of ripening for differently treated salted-herring in barrels ranged between 1 and 12. The trends in 'T/P' value, during ripening period for the different samples, appeared to be parallel changes in texture perceived by sensory observation (subjective measurement), although the heterogeneous nature of the samples gave standard deviations, about the replicate sample mean, around 5%. The method appears promising as an objective measure for monitoring this aspect of the textural quality of barrel salted-herring through ripening if reproducibility of test results can be improved by more careful standardization of sample preparation and test protocol.

Biodiversity values of different aquatic systems, habitats and organisms in relation to restoration and sustaining of biodiversity

Biodiversity values provide objective data and advice from which policy makes could assess the conservation options and determine optimal policies that would balance the needs of conservation with the socia-economic needs of the people in the area.