Information transfer, behavior of vessels and fishing efficiency: an individual-based simulation approach

Authored by D Gascuel, L Millischer

Date Published: 2006

DOI: 10.1051/alr.2006001

Sponsors: No sponsors listed

Platforms: No platforms listed

Model Documentation: Other Narrative Mathematical description

Model Code URLs: Model code not found

Abstract

A simulator dedicated to the modeling of individual search behaviors of fishing vessels has been built using multi-agents systems methodology. The harvesting activity of a virtual fleet is simulated and applied to a static virtual fish population, distributed in a bi-dimensional spatially explicit environment. The resource population can differ depending on different degrees of aggregation. Each vessel of the fleet is modeled as a singular and autonomous agent of the fishery system. The model focuses on the representation of information transfer among vessels, which results in an orientation of search effort. The informative search behavior is compared to a stochastic search, in order to estimate efficiency gains allowed by information transfers. Results show a strong dependence of the fleet's efficiency towards the level of aggregation of the resource. For higher levels of aggregation the informative behavior results in important pins in efficiency. Conversely, a misleading effect of information appears in the weakest aggregations. The informative behavior leads to the progressive convergence and the gathering of the agents. When the aggregation is strong, this pack effect{''} is stable in time and enables the vessels to make quick, catches. For the weakest aggregation levels, the pack effect{''} is unstable and leads the ships to a perpetual pursuit state, without catches. Thus, the size of existing networks appears as a key parameter of vessel behaviors. This approach, using an individual-based simulator, seems quite appropriate to connect individual behaviors to the dynamics of the fishing efficiency, which are generally studied in an aggregated manner. It allows to quantity the effects of the exchange of information among vessels, which is commonly considered as I qualitative phenomenon. Such an approach should be enlarged to a more global modeling of all of the components of the individual search behaviors of vessels.

Tags

Dynamics Fishery ecology Power Strategies Spatial-distribution Fleet Catch Catchability Trawlers