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 gains 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 quantify
the effects of the exchange of information among vessels, which is commonly
considered as a 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.