Numeric simulation of fishing effort and strategies (stochastic and cartesian) using cellular automata

Abstract

A cellular automaton (CA) model is developed to analyze the behavior of fishermen in terms of belonging to a group that exchanges information on fishing and the personal aspect of decision making, defining the fishermen as cartesian or stochastic. This model aims to be the generic structure for a subsequent specific model suitable for a real fishery, and shows how the previously described behavior can be represented in a CA. The results show that, in a simulated world, positive effects are observed in terms of capture or rate of capture, the grouping, and the stochastic behavior in the event of resource scarcity. Also shown is how the behavior of including an explorer has the potential of generating benefits, as well as being risky. If the fishing is good, an independent boat benefits more than the group explorer when sharing this information with the other members of the group (cooperation-competition effect); however, in an adverse situation, the group explorer is not as affected as the independent boat.

Simulation of fluid dynamics through complicated networks of channels with cellular automata

“…CA are the simplest discrete representation of a complex dynamic system [19,20] and have been applied in many areas of science [21][22][23][24], since they are an alternative to study connections between the microscopic and the macroscopic world. Due to their computational speed, CA allow one to study a wide range of values of the parameters involved in the problem that otherwise would involve excessive computation time, and are a simple tool to qualitatively test predictions about how a local mechanism can generate a certain response [17,18].…”