E
Etienne Rivot
Researcher at Agrocampus Ouest
Publications - 65
Citations - 1962
Etienne Rivot is an academic researcher from Agrocampus Ouest. The author has contributed to research in topics: Population & Salmo. The author has an hindex of 23, co-authored 61 publications receiving 1687 citations. Previous affiliations of Etienne Rivot include University of Calgary & École nationale supérieure agronomique de Rennes.
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Fluctuations in European eel (Anguilla anguilla) recruitment resulting from environmental changes in the Sargasso Sea
TL;DR: It is argued that sea warming in the eel spawning area since the early 1980s has modified marine production and eventually affected the survival rate of European eels at early life stages.
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Effect of nursery habitat degradation on flatfish population: Application to Solea solea in the Eastern Channel (Western Europe)
TL;DR: In this paper, the effects of estuarine habitat degradation on the population of the common sole in the Eastern Channel, a key species in the fish community and fisheries in this area, were analyzed.
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Impact of climate on eel populations of the Northern Hemisphere
Sylvain Bonhommeau,Emmanuel Chassot,Benjamin Planque,Etienne Rivot,Anthony H. Knap,Olivier Le Pape +5 more
TL;DR: Evidence that the survival of eel larvae is strongly correlated to food availability during their early life stages is provided, suggesting that changes in the marine production related to global warming may have led to the decline of European, American and Japanese eel populations.
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A Bayesian state-space modelling framework for fitting a salmon stage-structured population dynamic model to multiple time series of field data
TL;DR: The Bayesian state-space modelling framework allows us to derive inferences on stochastic stage-structured population dynamics models from multiple series of sequential observations with measurement or sampling errors, and is efficient for deriving quantitative diagnostics on a probability based rationale.
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Identifying fishing trip behaviour and estimating fishing effort from VMS data using Bayesian Hidden Markov Models
TL;DR: A Bayesian Hierarchical Model using Hidden Markov Process (HMP) is proposed as a template for analyzing fishing boats trajectories based on data available from satellite-based vessel monitoring systems (VMS), and tested to analyse the behaviour of pelagic trawlers in the Bay of Biscay.