title: Mixtures of GAMs for habitat suitability analysis with overdispersed presence / absence data.
abstract: A new approach to species distribution modelling based on unsupervised classification via a finite mixture of GAMs incorporating habitat suitability curves is proposed. A tailored EM algorithm is outlined for computing maximum likelihood estimates. Several submodels incorporating various parameter constraints are explored. Simulation studies confirm, that under certain constraints, the habitat suitability curves are recovered with good precision. The method is also applied to a set of real data concerning presence/absence of observable small mammal indices collected on the Tibetan plateau. The resulting classification was found to correspond to species-level differences in habitat preference described in previous ecological work.
authors.affiliation: UMR 6249 Laboratoire Chrono-Environnement, Université de Franche-Comté, Place Leclerc, 25030 Besançon Cedex, France.
authors.forename: David R J
authors.initials: DR
authors.lastname: Pleydell
authors.forename: Stéphane
authors.initials: S
authors.lastname: Chrétien
references.citation: Parasitology. 2003;127 Suppl:S121-31
references.pmid: 15027609
references.citation: Comput Stat Data Anal. 2007 May 1;51(8):3631-3653
references.pmid: 18443645
references.citation: Ecol Lett. 2005 Sep;8(9):993-1009
references.pmid: 34517687