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A Bayesian state-space model to estimate population biomass with catch and limited survey data: application to the thornback ray (Raja clavata) in the Bay of Biscay ArchiMer
Marandel, Florianne; Lorance, Pascal; Trenkel, Verena M..
The thornback ray (Raja clavata) in the Bay of Biscay is presumed to have declined during the 20th Century. To evaluate this decline and estimate biomass trajectories, a hypothetical catch time series was created for the period 1903-2013. A Bayesian state-space biomass production model with a Schaefer production function was fitted to the hypothetical catch time series and to a shorter research vessel Catch Per Unit Eeffort (CPUE) time series (1973-2013, with missing years). A censored likelihood made it possible to obtain biomass estimates without a CPUE time series or only with an estimate of biomass depletion. A simulation-estimation approach showed a high sensitivity of results to the prior for the intrinsic growth rate. The model provided biomass...
Tipo: Text Palavras-chave: Population dynamics; Stock assessment; Data poor; Censored data; Bayes; Thornback ray; State-space model.
Ano: 2016 URL: http://archimer.ifremer.fr/doc/00359/47032/46947.pdf
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A HMM-based model to geolocate pelagic fish from high-resolution individual temperature and depth histories: European sea bass as a case study ArchiMer
Woillez, Mathieu; Fablet, Ronan; Tran-thanh Ngo,; Lalire, Maxime; Lazure, Pascal; De Pontual, Helene.
Numerous methods have been developed to geolocate fish from data storage tags. Whereas demersal species have been tracked using tide-driven geolocation models, pelagic species which undertake extensive migrations have been mainly tracked using light-based models. Here, we present a new HMM-based model that infers pelagic fish positions from the sole use of high-resolution temperature and depth histories. A key contribution of our framework lies in model parameter inference (diffusion coefficient and noise parameters with respect to the reference geophysical fields—satellite SST and temperatures derived from the MARS3D hydrodynamic model), which improves model robustness. As a case study, we consider long time series of data storage tags (DSTs) deployed on...
Tipo: Text Palavras-chave: Fish movement; Archival tagging; Migration; Population structure; Hidden Markov Model (HMM); State-space model.
Ano: 2016 URL: http://archimer.ifremer.fr/doc/00300/41097/40270.pdf
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Identifying fishing trip behaviour and estimating fishing effort from VMS data using Bayesian Hidden Markov Models ArchiMer
Vermard, Youen; Rivot, Etienne; Mahevas, Stephanie; Marchal, Paul; Gascuel, Didier.
Recent advances in technologies have lead to a vast influx of data on movements, based on discrete recorded position of animals or fishing boats, opening new horizons for future analyses. However, most of the potential interest of tracking data depends on the ability to develop suitable modelling strategies to analyze trajectories from discrete recorded positions. A serious modelling challenge is to infer the evolution of the true position and the associated spatio-temporal distribution of behavioural states using discrete, error-prone and incomplete observations. In this paper, a Bayesian Hierarchical Model (HBM) using Hidden Markov Process (HMP) is proposed as a template for analyzing fishing boats trajectories based on data available from...
Tipo: Text Palavras-chave: Bayesian Hierarchical Models; Hidden Markov Model; State-space model; VMS; Fleet behaviour; Fishing effort.
Ano: 2010 URL: http://archimer.ifremer.fr/doc/00009/11993/9342.pdf
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Linear Gaussian state-space model with irregular sampling: application to sea surface temperature ArchiMer
Tandeo, Pierre; Ailliot, Pierre; Autret, Emmanuelle.
Satellites provide important information on many meteorological and oceanographic variables. State-space models are commonly used to analyse such data sets with measurement errors. In this work, we propose to extend the usual linear and Gaussian state-space to analyse time series with irregular time sampling, such as the one obtained when keeping all the satellite observations available at some specific location. We discuss the parameter estimation using a method of moment and the method of maximum likelihood. Simulation results indicate that the method of moment leads to a computationally efficient and numerically robust estimation procedure suitable for initializing the Expectation-Maximisation algorithm, which is combined with a standard numerical...
Tipo: Text Palavras-chave: State-space model; Irregular sampling; Ornstein-Uhlenbeck process; EM algorithm; Sea surface temperature.
Ano: 2011 URL: http://archimer.ifremer.fr/doc/00039/15047/12441.pdf
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Statistical ecology comes of age ArchiMer
Gimenez, Olivier; Buckland, Stephen T.; Morgan, Byron J. T.; Bez, Nicolas; Bertrand, Sophie; Choquet, Remi; Dray, Stephane; Etienne, Marie-pierre; Fewster, Rachel; Gosselin, Frederic; Merigot, Bastien; Monestiez, Pascal; Morales, Juan M.; Mortier, Frederic; Munoz, Francois; Ovaskainen, Otso; Pavoine, Sandrine; Pradel, Roger; Schurr, Frank M.; Thomas, Len; Thuiller, Wilfried; Trenkel, Verena; De Valpine, Perry; Rexstad, Eric.
The desire to predict the consequences of global environmental change has been the driver towards more realistic models embracing the variability and uncertainties inherent in ecology. Statistical ecology has gelled over the past decade as a discipline that moves away from describing patterns towards modelling the ecological processes that generate these patterns. Following the fourth International Statistical Ecology Conference (1–4 July 2014) in Montpellier, France, we analyse current trends in statistical ecology. Important advances in the analysis of individual movement, and in the modelling of population dynamics and species distributions, are made possible by the increasing use of hierarchical and hidden process models. Exciting research perspectives...
Tipo: Text Palavras-chave: Citizen science; Hidden Markov model; Hierarchical model; Movement ecology; Software package; Spatially explicit capture-recapture; Species distribution modelling; State-space model.
Ano: 2014 URL: http://archimer.ifremer.fr/doc/00249/36026/35298.pdf
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Uso do filtro de Kalman para correção de temperatura estimada pelo Precis no período de 2000-2010. Infoteca-e
CARVALHO, J. R. P. de; ASSAD, E. D.; PINTO, H. S..
O presente trabalho teve como objetivo avaliar a precisão da estimativa da temperatura média simulada pelo modelo Precis conforme cenários B2 de emissão definido pelo Intergovernmental Panel on Climate Change (IPCC) para o Brasil e desenvolver um filtro de Kalman para corrigir os erros sistemáticos do modelo para os anos de 2000 a 2010. O modelo regionalizado Precis tem como meta reproduzir as características principais do clima em terrenos complexos. O modelo geral foi delineado para dois períodos 1961-1990 e 2070-2100. Para as mesmas coordenadas geográficas dos dois períodos foram estimadas as temperaturas médias de 2000 a 2010 através de uma regressão linear utilizando um fator de correção baseado no conceito de Atmosfera Padrão (Precis-Br). A análise...
Tipo: Boletim de Pesquisa e Desenvolvimento (INFOTECA-E) Palavras-chave: Filtro de Kalman; Estimativa de temperatura; Modelo Precis; Modelo espaço-estado; Previsão climática; State-space model; Systematic errors model; Weather forecasting.
Ano: 2011 URL: http://www.infoteca.cnptia.embrapa.br/handle/doc/921017
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