TUNPOP, a computer simulation model of the yellowfin tuna population and the surface tuna fishery of the Eastern Pacific Ocean

ENGLISH: Mathematical documentation of TUNP0P, an age-structured computer simulation model of the yellowfin tuna population and surface tuna fishery of the eastern Pacific Ocean, is described. Example runs of the model are presented and discussed, and the sensitivity of the model output to changes in various parameters is examined. SPANISH: Se describe la documentación matemática de TUNP0P, un modelo computador de simulación basado en la edad de la población del atún aleta amarilla y de la pesca atunera epipelágíca del Océano Pacífico oriental. Se presentan y se discuten ejemplos de las pasadas del modelo, y se examina la sensibilidad de los resultados de salida con relación a los cambios de varios parámetros. (PDF contains 47 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.

A low-level geographic information system for coastal zone management with applications to Brunei Darussalam: Part III:: simulation and tracking oil spills

B:RUN is a low-level GIS software designed to help formulate options for the management of the coastal zone of Brunei Darussalam. This contribution presents the oil spill simulation module of B:RUN. This simple module, based largely on wind and sea surface current vector parameters, may be helpful in formulating relevant oil spill contingency plans. It can be easily adapted to other areas, as can the B:RUN software itself.

Simulation of Tail Weight Distributions in Biological Year 1986–2006 Landings of Brown Shrimp, Farfantepenaeus aztecus, from the Northern Gulf of Mexico Fishery

Size distribution within re- ported landings is an important aspect of northern Gulf of Mexico penaeid shrimp stock assessments. It reflects shrimp population characteristics such as numerical abundance of various sizes, age structure, and vital rates (e.g. recruitment, growth, and mortality), as well as effects of fishing, fishing power, fishing practices, sampling, size-grading, etc. The usual measure of shrimp size in archived landings data is count (C) the number of shrimp tails (abdomen or edible portion) per pound (0.4536 kg). Shrimp are marketed and landings reported in pounds within tail count categories. Statistically, these count categories are count class intervals or bins with upper and lower limits expressed in C. Count categories vary in width, overlap, and frequency of occurrence within the landings. The upper and lower limits of most count class intervals can be transformed to lower and upper limits (respectively) of class intervals expressed in pounds per shrimp tail, w, the reciprocal of C (i.e. w = 1/C). Age based stock assessments have relied on various algorithms to estimate numbers of shrimp from pounds landed within count categories. These algorithms required un- derlying explicit or implicit assumptions about the distribution of C or w. However, no attempts were made to assess the actual distribution of C or w. Therefore, validity of the algorithms and assumptions could not be determined. When different algorithms were applied to landings within the same size categories, they produced different estimates of numbers of shrimp. This paper demonstrates a method of simulating the distribution of w in reported biological year landings of shrimp. We used, as examples, landings of brown shrimp, Farfantepenaeus aztecus, from the northern Gulf of Mexico fishery in biological years 1986–2006. Brown shrimp biological year, Ti, is defined as beginning on 1 May of the same calendar year as Ti and ending on 30 April of the next calendar year, where subscript i is the place marker for biological year. Biological year landings encompass most if not all of the brown shrimp life cycle and life span. Simulated distributions of w reflect all factors influencing sizes of brown shrimp in the landings within a given biological year. Our method does not require a priori assumptions about the parent distributions of w or C, and it takes into account the variability in width, overlap, and frequency of occurrence of count categories within the landings. Simulated biological year distributions of w can be transformed to equivalent distributions of C. Our method may be useful in future testing of previously applied algorithms and development of new estimators based on statistical estimation theory and the underlying distribution of w or C. We also examine some applications of biological year distributions of w, and additional variables derived from them.