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.

A simulation model of the dynamics of Peruvian anchoveta (Engraulis ringens)

The article describes the key elements of a model simulating the dynamics of the anchoveta (Engraulis ringens) in the Peruvian upwelling system (4 degrees to 14 degrees South). This model, based on coupled differential equations, is parametrized mainly using empirical data and functional relationships presented in two volumes issued by ICLARM in 1987 and 1989, and may thus be viewed as test of the hypotheses presented therein. Results to date suggest that present knowledge of mechanisms controlling the anchoveta stock is essentially consistent, and sufficient to build a model reflecting essential features of the stock biomass and recruitment dynamics.

Effects of fishing on growth traits: a simulation analysis

Abstract—Fisheries often target individuals based on size. Size-selective fishing can create selection differentials on life-history traits and, when those traits have a genetic basis, may cause evolution. The evolution of life history traits affects potential yield and sustainability of fishing, and it is therefore an issue for fishery management. Yet fishery managers usually disregard the possibility of evolution, because little guidance is available to predict evolutionary consequences of management strategies. We attempt to provide some generic guidance. We develop an individual-based model of a population with overlapping generations and continuous reproduction. We simulate model populations under size-selective fishing to generate and quantify selection differentials on growth. The analysis comprises a variety of common life-history and fishery characteristics: variability in growth, correlation between von Bertalanffy growth parameters (K and L∞), maturity rate, natural mortality rate (M), M/K ratio, duration of spawning season, fishing mortality rate (F), maximum size limit, slope of selectivity curve, age at 50% selectivity, and duration of fishing season. We found that each characteristic affected the magnitude of selection differentials. The most vulnerable stocks were those with a short spawning or fishing season. Under almost all life-history and fishery characteristics examined, selection differentials created by realistic fishing mortality rates are considerable.