AUTHOR=Beauchesne David , Daigle Rémi M. , Vissault Steve , Gravel Dominique , Bastien Andréane , Bélanger Simon , Bernatchez Pascal , Blais Marjolaine , Bourdages Hugo , Chion Clément , Galbraith Peter S. , Halpern Benjamin S. , Lavoie Camille , McKindsey Christopher W. , Mucci Alfonso , Pineault Simon , Starr Michel , Ste-Marie Anne-Sophie , Archambault Philippe 

TITLE=Characterizing Exposure to and Sharing Knowledge of Drivers of Environmental Change in the St. Lawrence System in Canada

JOURNAL=Frontiers in Marine Science

VOLUME=Volume 7 - 2020

YEAR=2020

URL=https://www.frontiersin.org/journals/marine-science/articles/10.3389/fmars.2020.00383

DOI=10.3389/fmars.2020.00383

ISSN=2296-7745

ABSTRACT=The St. Lawrence is a vast and complex socio-ecological system providing a wealth of services sustaining numerous economic sectors. These ecosystems are subject to significant human pressures that overlap and potentially interact with climate driven environmental changes. Our objective in this paper is to systematically characterize the distribution and intensity of drivers in the St. Lawrence System. To do so, we launch eDrivers, an open knowledge platform gathering experts committed to structuring, standardizing and sharing knowledge on drivers in support of science and management. We gathered data on 22 coastal, climate, fisheries and marine traffic drivers through collaborations, existing environmental initiatives and open data portals. We show that few areas of the St. Lawrence are free of cumulative exposure. The Estuary, the Anticosti Gyre and coastal areas are particularly exposed, especially in the vicinity of urban centers. We identified 6 areas of distinct cumulative exposure regime that show that certain drivers typically co-occur in different regions of the St. Lawrence and that coastal areas are exposed to all driver types. Of particular concern are two threat complexes capturing most exposure hotspots that show the convergence of contrasting exposure regimes at the head of the Laurentian Channel. eDrivers was built on a series of guiding principles upholding existing data management and open science standards. We therefore expect it to evolve through time to address knowledge gaps and refine current driver layers. Ultimately, we believe that eDrivers represents a much needed solution that could radically influence broad scale research and management practices by increasing knowledge accessibility and interoperability.