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.

A history of fishing with explosives and poisons in Hong Kong waters

Fishing with explosives is still being practiced aroung Hong Kong. The first legislation against blast fishing was passed in Hong Kong in 1903. Since then, successive legislation has increased the penalties and fines on blast fishing and fishing with poisons. However, the problem has not been eliminated as enforcement puts pressure on the resources of the marine police. It would be more effective to educate the local communities on the destructive effects of these practices and make them more vigilant and responsible in controlling them.

Trade secrets: a ten year overview of the illegal import of sea turtle products into the United States

For more than 25 years all sea turtle products have been prohibited from international commerce by the 170-member nations of the Convention on International Trade in Endangered Species (CITES). Sea turtles continue to be threatened by direct take (including poaching) and illegal trade despite multi-national protection efforts. Although take may contribute significantly to sea turtle decline, illegal take is difficult to measure since there are few quantified records associated with legal fisheries and fewer still for illegal take (poaching). We can, however, quantify one portion of the illegal sea turtle trade by determining how many illegal products were seized at United States ports of entry over a recent 10-year period. The United States Fish and Wildlife Service (USFWS) oversees the import and export of wildlife and wildlife products, ensuring that wildlife trade complies with United States laws and international treaties. Additionally, the USFWS has legal authority to target suspected illegal wildlife activity through undercover and field investigations. In an effort to assess the scale of illegal sea turtle take and trade, we have conducted a 10-year (1994 – 2003) review of the law enforcement database maintained by the USFWS. This database tracks the number and type of wildlife cases, the quantity of seized products, and the penalties assessed against violators. These data are minimum estimates of the sea turtle products passing through the United States borders, as smuggled wildlife is oftentimes not detected.

Beel fishery and livelihood of the local community in Rajdhala, Netrakona, Bangladesh

Baseline survey and Participatory Rural Appraisal (PRA) during January 2003 to December 2004 on the fishing community revealed that unregulated fishing, use of destructive fishing gears, poaching of fishes, difficulties encountered in enforcing fisheries regulation and the helplessness of fishers to find alternative sources of income during banned fishing period (June to October) were the major management problems. CBFM (Community Based Fisheries Management) system as an alternative management strategy has been introduced to ensure active participation of the target group-the poor fishers living around the beet who were previously deprived to get access to the beet. Establishing a leasing system for controlled access, ensuring greater user-group participation through equitable distribution of all resource benefits among members, attempting to enforce penalties for illegal fishing linked with surprise checks to enforce management regulations are some of the recent steps taken by the BMC (Beel Management Committee). Chapila fish intake by the community was 31.25 g/head/day before stocking the beel by carp fingerlings. After stocking, they consumed chapila as fish protein from 8.33 g to 20.8 g/head/day during the fishing season (November to May) indicating that due to introduction of carp fingerlings, chapila production has been decreased in 2003-2004. About 77.5% families around the beel were found to be dependent directly and/or indirectly on chapila and other indigenous fishes of the beel for their livelihood, through fishing, marketing and other activities like net and boat preparation and nets mending etc. Particularly fishers' families were found to face serious problem during non-fishing period like June to October for their livelihood. Analyzing the present research result it was also observed that other than declination in biodiversity, the fishing pressure on promising chapila of the beel was found high and that is why the production of chapila has also been decreased. To get sustainable chapila production from the heel, it is suggested to ensure successful spawning and recruitment as juveniles, and hence the chapila should be undisturbed during its breeding period from March to July, and fishing pressure on the same species needs to be reduced for obtaining sustainable fish production.