Agritrop
Home

Mixture of inhomogeneous matrix models for species-rich ecosystems

Mortier Frédéric, Ouédraogo Dakis-Yaoba, Claeys Florian, Tadesse Mahlet G., Cornu Guillaume, Baya Fidèle, Bénédet Fabrice, Freycon Vincent, Gourlet-Fleury Sylvie, Picard Nicolas. 2015. Mixture of inhomogeneous matrix models for species-rich ecosystems. Environmetrics, 26 (1) : pp. 39-51.

Journal article ; Article de revue à facteur d'impact
[img] Published version - Anglais
Access restricted to CIRAD agents
Use under authorization by the author or CIRAD.
document_574764.pdf

Télécharger (871kB)

Quartile : Q2, Sujet : STATISTICS & PROBABILITY / Quartile : Q2, Sujet : MATHEMATICS, INTERDISCIPLINARY APPLICATIONS / Quartile : Q3, Sujet : ENVIRONMENTAL SCIENCES

Abstract : Understanding how environmental factors could impact population dynamics is of primary importance for species conservation. Matrix population models are widely used to predict population dynamics. However, in species-rich ecosystems with many rare species, the small population sizes hinder a good fit of species-specific models. In addition, classical matrix models do not take into account environmental variability. We propose a mixture of regression models with variable selection allowing the simultaneous clustering of species into groups according to vital rate information (recruitment, growth and mortality) and the identification of group-specific explicative environmental variables. We develop an inference method coupling the R packages flexmix and glmnet. We first highlight the effectiveness of the method on simulated datasets. Next, we apply it to data from a tropical rain forest in the Central African Republic. We demonstrate the accuracy of the inhomogeneous mixture matrix model in successfully reproducing stand dynamics and classifying tree species into well-differentiated groups with clear ecological interpretations. (Résumé d'auteur)

Mots-clés Agrovoc : Forêt tropicale humide, Écologie forestière, Composition botanique, Biodiversité, Dynamique des populations, Croissance, Régénération naturelle, Mortalité, Méthode statistique, Modèle mathématique, Modèle de simulation

Mots-clés géographiques Agrovoc : République centrafricaine

Mots-clés complémentaires : Régression (statistique)

Classification Agris : U10 - Mathematical and statistical methods
F62 - Plant physiology - Growth and development
F40 - Plant ecology
K01 - Forestry - General aspects

Champ stratégique Cirad : Axe 6 (2014-2018) - Sociétés, natures et territoires

Auteurs et affiliations

  • Mortier Frédéric, CIRAD-ES-UPR BSef (FRA)
  • Ouédraogo Dakis-Yaoba
  • Claeys Florian, AgroParisTech (FRA)
  • Tadesse Mahlet G., Georgetown University (USA)
  • Cornu Guillaume, CIRAD-ES-UPR BSef (FRA) ORCID: 0000-0002-7523-5176
  • Baya Fidèle, Ministère des eaux et forêts, chasses, pêches et tourisme (République centrafricaine) (CAF)
  • Bénédet Fabrice, CIRAD-ES-UPR BSef (FRA) ORCID: 0000-0001-9281-5677
  • Freycon Vincent, CIRAD-ES-UPR BSef (FRA)
  • Gourlet-Fleury Sylvie, CIRAD-ES-UPR BSef (FRA) ORCID: 0000-0002-1136-4307
  • Picard Nicolas, CIRAD-ES-UPR BSef (CMR)

Source : Cirad - Agritrop (https://agritrop.cirad.fr/574764/)

View Item (staff only) View Item (staff only)

[ Page générée et mise en cache le 2020-10-03 ]