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WinBUGS for population ecologists: bayesian modeling using markov chain Monte Carlo methods

Gimenez Olivier, Bonner Simon J., King Ruth, Parker Richard A., Brooks Stephen P., Jamieson L.E., Grosbois Vladimir, Morgan Byron J., Thomas Len. 2009. WinBUGS for population ecologists: bayesian modeling using markov chain Monte Carlo methods. In : Modeling demographic processes in marked populations. Thomson David L. (ed.), Cooch Evan G. (ed.), Conroy Michael J. (ed.). New York : Springer [Etats-Unis], Résumé, pp. 883-915. (Environmental and ecological statistics series, 3) ISBN 978-0-387-78150-1

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Abstract : The computer package WinBUGS is introduced. We first give a brief introduction to Bayesian theory and its implementation using Markov chain Monte Carlo (MCMC) algorithms. We then present three case studies showing how WinBUGS can be used when classical theory is difficult to implement. The first example uses data on white storks from Baden Württemberg, Germany, to demonstrate the use of mark-recapture models to estimate survival, and also how to cope with unexplained variance through random effects. Recent advances in methodology and also the WinBUGS software allow us to introduce (i) a flexible way of incorporating covariates using spline smoothing and (ii) a method to deal with missing values in covariates. The second example shows how to estimate population density while accounting for detectability, using distance sampling methods applied to a test dataset collected on a known population of wooden stakes. Finally, the third case study involves the use of state-space models of wildlife population dynamics to make inferences about density dependence in a North American duck species. Reversible Jump MCMC is used to calculate the probability of various candidate models. For all examples, data and WinBUGS code are provided. (Résumé d'auteur)

Mots-clés Agrovoc : Écologie animale, Étude de cas, Animal sauvage, Capture animale, Canard, Dynamique des populations, Modèle mathématique, Méthode statistique, Densité, Survie

Mots-clés géographiques Agrovoc : Amérique du Nord

Classification Agris : U10 - Computer science, mathematics and statistics
U30 - Research methods
L20 - Animal ecology

Champ stratégique Cirad : Axe 6 (2005-2013) - Agriculture, environnement, nature et sociétés

Auteurs et affiliations

  • Gimenez Olivier, CNRS (FRA)
  • Bonner Simon J., University of Kentucky (USA)
  • King Ruth, Université de St Andrews (GBR)
  • Parker Richard A., University of Cambridge (GBR)
  • Brooks Stephen P., University of Cambridge (GBR)
  • Jamieson L.E.
  • Grosbois Vladimir, CIRAD-ES-UPR AGIRs (FRA)
  • Morgan Byron J., University of Kentucky (USA)
  • Thomas Len, Université de St Andrews (GBR)

Autres liens de la publication

Source : Cirad - Agritrop (https://agritrop.cirad.fr/572217/)

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