G
Guillaume Dauphin
Researcher at Fisheries and Oceans Canada
Publications - 10
Citations - 137
Guillaume Dauphin is an academic researcher from Fisheries and Oceans Canada. The author has contributed to research in topics: Salmo & Population. The author has an hindex of 4, co-authored 10 publications receiving 100 citations. Previous affiliations of Guillaume Dauphin include University of Pau and Pays de l'Adour & University of New Brunswick.
Papers
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Working group on North Atlantic salmon (WGNAS)
Ida Ahlbeck-Bergendahl,Julien April,Hlynur Bardarson,Geir H. Bolstad,Ian Bradbury,Mathieu Buoro,Gérald Chaput,Guillaume Dauphin,Dennis Ensing,Jaakko Erkinaro,Peter Fiske,Marko Freese,Jonathan Gillson,Stephen D. Gregory,Nora N. Hanson,Nicholas I. Kelly,Hugo Maxwell,David Meerburg,Michael Millane,Rasmus Nygaard,Maxime Olmos,James Ounsley,Sergey Prusov,Etienne Rivot,Martha J. Robertson,Ian Russel,Tim Sheehan,Kjell Rong Utne,Alan Walker,Vidar Wennevik +29 more
Journal ArticleDOI
Host kairomone learning and foraging success in an egg parasitoid: a simulation model
TL;DR: An egg parasitoid that recognises chemical residues left by its host the green stink bug Nezara viridula (L.) as kairomone signals, enabling it to find egg masses in which to lay eggs.
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Using redd counts to estimate salmonids spawner abundances: A Bayesian modelling approach
Guillaume Dauphin,Guillaume Dauphin,Etienne Prévost,Etienne Prévost,Colin E. Adams,Patrick Boylan +5 more
TL;DR: In this article, the authors developed a generic Bayesian hierarchical model relating Atlantic salmon, Salmo salar L. spawner abundance and redd counts which accounts for the associated sources of uncertainty and concluded that redd counts can be a valuable source of information for monitoring spawning abundances of salmonids.
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A Bayesian approach to estimating Atlantic salmon fry densities using a rapid sampling technique
TL;DR: H hierarchical Bayesian modelling framework is used for this inter-calibration because it allows an estimate of absolute abundance from abundance index data alone while accounting for the main sources of uncertainty.
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Length measurement accuracy of adaptive resolution imaging sonar and a predictive model to assess adult Atlantic salmon (Salmo salar) into two size categories with long-range data in a river.
TL;DR: It is concluded that fish length measurements derived from long-range imaging sonar data should be used with caution, however, post-processing can improve the usefulness of the data for specific purposes, such as adult Atlantic salmon population monitoring.