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Keywords = Saguenay Fjord

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16 pages, 735 KiB  
Article
The Gradient-Boosting Method for Tackling High Computing Demand in Underwater Acoustic Propagation Modeling
by Dominic Lagrois, Tyler R. Bonnell, Ankita Shukla and Clément Chion
J. Mar. Sci. Eng. 2022, 10(7), 899; https://doi.org/10.3390/jmse10070899 - 29 Jun 2022
Cited by 3 | Viewed by 2411
Abstract
Agent-based models return spatiotemporal information used to process time series of specific parameters for specific individuals called “agents”. For complex, advanced and detailed models, this typically comes at the expense of high computing times and requires access to important computing resources. This paper [...] Read more.
Agent-based models return spatiotemporal information used to process time series of specific parameters for specific individuals called “agents”. For complex, advanced and detailed models, this typically comes at the expense of high computing times and requires access to important computing resources. This paper provides an example on how machine learning and artificial intelligence can help predict an agent-based model’s output values at regular intervals without having to rely on time-consuming numerical calculations. Gradient-boosting XGBoost under GNU package’s R was used in the social-ecological agent-based model 3MTSim to interpolate, in the time domain, sound pressure levels received at the agents’ positions that were occupied by the endangered St. Lawrence Estuary and Saguenay Fjord belugas and caused by anthropomorphic noise of nearby transiting merchant vessels. A mean error of 3.23 ± 3.76(1σ) dB on received sound pressure levels was predicted when compared to ground truth values that were processed using rigorous, although time-consuming, numerical algorithms. The computing time gain was significant, i.e., it was estimated to be 10-fold higher than the ground truth simulation, whilst maintaining the original temporal resolution. Full article
(This article belongs to the Special Issue Numerical Modelling of Atmospheres and Oceans)
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4 pages, 722 KiB  
Article
Ecotoxicological Evaluation of the Immunocompetence of Two Bivalves Species (Mya arenaria and Mytilus edulis) in the Saguenay Fjord Including a Salinity Gradient
by A. Beaudry, E. Lacaze, A. Jobin-Piché, S. Masson, M. Auffret, P. Brousseau and M. Fournier
J. Xenobiot. 2015, 5(2), 5769; https://doi.org/10.4081/xeno.2015.5769 (registering DOI) - 10 Feb 2016
Cited by 1 | Viewed by 888
Abstract
Bivalves are filter feeders widely used in ecotoxicological monitoring because of their sensitivity to contaminants present in the environment. [...]
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599 KiB  
Article
Polychaetes as Bioindicators of Water Quality in the Saguenay Fjord (Quebec, Canada): A Preliminary Investigation
by C. Blaise, F. Gagné, P.L. Gillis and P. Eullaffroy
J. Xenobiot. 2013, 3(s1), s1e1; https://doi.org/10.4081/xeno.2013.s1.e1 - 3 Dec 2013
Cited by 10 | Viewed by 1
Abstract
The Saguenay Fjord, a key affluent of the St-Lawrence River estuary (SLRE), is prone to environmental pressures stemming from mixed and diffuse sources of (in)organic contamination, and has been studied extensively with bivalves as indicators of water quality. [...]
[...] Read more.
The Saguenay Fjord, a key affluent of the St-Lawrence River estuary (SLRE), is prone to environmental pressures stemming from mixed and diffuse sources of (in)organic contamination, and has been studied extensively with bivalves as indicators of water quality. [...]
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