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dc.contributor.authorCitores, L.
dc.contributor.authorIbaibarriaga, L.
dc.contributor.authorLee, D.-J.
dc.contributor.authorBrewer, M.J.
dc.contributor.authorSantos, M.
dc.contributor.authorChust, G.
dc.date.accessioned2020-01-13T14:48:42Z
dc.date.available2020-01-13T14:48:42Z
dc.date.issued2020-01-13
dc.identifier.urihttp://hdl.handle.net/20.500.11824/1067
dc.description.abstractAccording to ecological niche theory, species response curves are unimodal with respect to environmental gradients. A variety of statistical methods have been developed for species distribution modelling. A general problem with most of these habitat modelling approaches is that the estimated response curves can display biologically implausible shapes which do not respect ecological niche theory. This work proposes using shapeconstrained generalized additive models (SC-GAMs) to build species distribution models under the ecological niche theory framework, imposing concavity constraints in the linear predictor scale. Based on a simulation study and a real data application, we compared performance with respect to other regression models without shape-constraints (such as standard GLMs and GAMs with varying degrees of freedom) and also to models based on so-called “Plateau” climate-envelopes. The imposition of concavity for response curves resulted in a good balance between the goodness of fit (GOF) and agreement with ecological niche theory. The approach has been applied to fit distribution models for three fish species given several environmental variables.en_US
dc.formatapplication/pdfen_US
dc.language.isoengen_US
dc.rightsReconocimiento-NoComercial-CompartirIgual 3.0 Españaen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/es/en_US
dc.subjectEcological niche theoryen_US
dc.subjectGAMsen_US
dc.subjectGLMsen_US
dc.subjectPlateau methoden_US
dc.subjectShape-constrained GAMsen_US
dc.subjectSpecies distribution modelsen_US
dc.titleModelling species presence–absence in the ecological niche theory framework using shape-constrained generalized additive modelsen_US
dc.typeinfo:eu-repo/semantics/articleen_US
dc.identifier.doi10.1016/j.ecolmodel.2019.108926
dc.relation.publisherversionhttps://doi.org/10.1016/j.ecolmodel.2019.108926en_US
dc.relation.projectIDES/1PE/SEV-2017-0718en_US
dc.relation.projectIDES/1PE/MTM2017-82379-Ren_US
dc.relation.projectIDEUS/BERC/BERC.2018-2021en_US
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen_US
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersionen_US
dc.journal.titleEcological Modellingen_US


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Reconocimiento-NoComercial-CompartirIgual 3.0 España
Except where otherwise noted, this item's license is described as Reconocimiento-NoComercial-CompartirIgual 3.0 España