A decision support system to assist the sustainable management of navigation activities in the St. Lawrence River Estuary, Canada

摘要

We describe a decision support system that has been developed to inform management and planning in a portion of the St. Lawrence Estuary in Canada (covering the Saguenay-St. Lawrence Marine Park and the proposed St. Lawrence Estuary Marine Protected Area). The system is composed of a spatiotemporal, georeferenced database, a simulator (3MTSim) that reproduces the spatiotemporal movement of marine mammals and maritime traffic in the estuary, and data post-processing tools that can be used to analyse the output of 3MTSim. 3MTSim allows users to test different management scenarios for maritime traffic (e.g., area closures, speed limits, regulations concerning the observation of marine mammals) in order to assess their effects on navigational patterns which may influence marine mammal exposure to vessels. 3MTSim includes an individual-based model of marine mammal movement patterns that has been elaborated based on existing telemetry data on fin, blue, and beluga whales as well as on land-based theodolite tracking of humpback and minke whales. Observations recorded aboard research and whale-watching vessels have provided the spatial data necessary to estimate species' abundances and distribution maps that are used to initialise the whale model. Different types of vessels, including cargo ships and commercial whale-watching boats are also modelled individually, using an agent-based approach. The boat model represents the decision-making process of boat captains as a function of environmental conditions, the contextual setting, and their respective goals. An extensive database of real-time tracking data available for the different types of vessels, coupled with observations and interviews, has served in the elaboration of the boat model. In this paper, an overview of the entire system is presented and its effectiveness as a decision support tool is demonstrated via the results from a sample of scenario-based simulations.