English   español  
Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/126204
Share/Impact:
Statistics
logo share SHARE logo core CORE   Add this article to your Mendeley library MendeleyBASE

Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar a otros formatos:
DC FieldValueLanguage
dc.contributor.authorChambert, Thierry-
dc.contributor.authorKendall, William Louis-
dc.contributor.authorHines, James E.-
dc.contributor.authorNichols, James D.-
dc.contributor.authorPedrini, Paolo-
dc.contributor.authorWaddle, J. Hardin-
dc.contributor.authorTavecchia, Giacomo-
dc.contributor.authorWalls, Susan C.-
dc.contributor.authorTenan, Simone-
dc.date.accessioned2015-11-30T13:10:09Z-
dc.date.available2015-11-30T13:10:09Z-
dc.date.issued2015-03-28-
dc.identifierdoi: 10.1111/2041-210X.12362-
dc.identifierissn: 2041-210X-
dc.identifier.citationMethods in Ecology and Evolution 6(6): 638-647 (2015)-
dc.identifier.urihttp://hdl.handle.net/10261/126204-
dc.description.abstract© 2015 British Ecological Society. With ongoing climate change, many species are expected to shift their spatial and temporal distributions. To document changes in species distribution and phenology, detection/non-detection data have proven very useful. Occupancy models provide a robust way to analyse such data, but inference is usually focused on species spatial distribution, not phenology. We present a multi-season extension of the staggered-entry occupancy model of Kendall et al. (2013, Ecology, 94, 610), which permits inference about the within-season patterns of species arrival and departure at sampling sites. The new model presented here allows investigation of species phenology and spatial distribution across years, as well as site extinction/colonization dynamics. We illustrate the model with two data sets on European migratory passerines and one data set on North American treefrogs. We show how to derive several additional phenological parameters, such as annual mean arrival and departure dates, from estimated arrival and departure probabilities. Given the extent of detection/non-detection data that are available, we believe that this modelling approach will prove very useful to further understand and predict species responses to climate change.-
dc.description.sponsorshipU.S. Geological Survey-Amphibian Research and Monitoring Initiative (ARMI). Grant Number: 505; Autonomous Province of Trento-
dc.publisherJohn Wiley & Sons-
dc.rightsclosedAccess-
dc.subjectClosure assumption-
dc.subjectDetection-
dc.subjectOccupancy modelling-
dc.subjectSpecies distribution models-
dc.subjectSpecies phenology-
dc.subjectStaggered-entry model-
dc.titleTesting hypotheses on distribution shifts and changes in phenology of imperfectly detectable species-
dc.typeartículo-
dc.identifier.doi10.1111/2041-210X.12362-
dc.relation.publisherversionhttp://dx.doi.org/10.1111/2041-210X.12362-
dc.date.updated2015-11-30T13:10:11Z-
dc.description.versionPeer Reviewed-
dc.language.rfc3066eng-
dc.contributor.funderU.S. Geological Survey-
dc.contributor.funderProvincia Autonoma di Trento-
dc.relation.csic-
dc.identifier.funderhttp://dx.doi.org/10.13039/100000203es_ES
Appears in Collections:(IMEDEA) Artículos
Files in This Item:
File Description SizeFormat 
accesoRestringido.pdf15,38 kBAdobe PDFThumbnail
View/Open
Show simple item record
 

Related articles:


WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.