A FRAMEWORK FOR CUMULATIVE RISK ASSESSMENT FOR MARINE SHIPPING: A CASE STUDY IN THE KITIKMEOT REGION

Abstract

The shortening of sea ice in the summer season has caught the attention of the global shipping community due to the potential of the Northwest Passage through the Canadian Arctic becoming a shorter and cheaper alternative route to the Panama Canal. This growing utilization of the Arctic ocean could pose increasing risks to the marine animals in this region, such as noise pollution and potential oil spills. Within this context, a framework for Cumulative Risk Assessment (CRA) of shipping stressors to marine receptors has been developed based on an existing algorithm (Halpern et al., 2009). The framework is composed by spatial, modelling and uncertainty methods and provides a means to combine different stressors-receptors into one single risk equation and presents the results in a simple visualization format using GIS (Geographic Information System) software. Additionally, this study includes an illustrative case study applied to the Kitikmeot region for shipping seasons. The stressors and receptors selected for the case study were based on local communities’ concerns, as documents by Carter et al. (2018). As the basis for the case study, ship-source oil spills and noise pollution are considered to be two of the shipping stressors of greatest concern among the Northern communities. As for receptors, Beluga, Bowhead and Narwhals were included in the analysis because Inuit communities rely on them for their food security through their traditional subsistence hunting and also their cultural importance to these communities. The results from the case study can be used to determine which sections of the proposed Corridors require more elaborated monitoring and regulating to reduce the impacts from vessels for a long-term safety of these marine mammals and consequently the local communities. It can also help with the allocation of public resources for risk mitigation by identifying which areas of Kitikmeot region are most at risk. Ultimately, this study also shows the benefit of including Traditional Knowledge in scientific decision models in order to gain more meaningful insights on the valuable Arctic marine ecosystem.

Key words: Canadian Arctic, Risk assessment, shipping, noise pollution, oil spill.