Por favor, use este identificador para citar o enlazar a este item:
http://hdl.handle.net/10261/126204
COMPARTIR / EXPORTAR:
SHARE CORE BASE | |
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE | |
Título: | Testing hypotheses on distribution shifts and changes in phenology of imperfectly detectable species |
Autor: | Chambert, Thierry; Kendall, William Louis; Hines, James E.; Nichols, James D.; Pedrini, Paolo; Waddle, J. Hardin; Tavecchia, Giacomo CSIC ORCID; Walls, Susan C.; Tenan, Simone | Palabras clave: | Closure assumption Detection Occupancy modelling Species distribution models Species phenology Staggered-entry model |
Fecha de publicación: | 28-mar-2015 | Editor: | John Wiley & Sons | Citación: | Methods in Ecology and Evolution 6(6): 638-647 (2015) | Resumen: | © 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. | Versión del editor: | http://dx.doi.org/10.1111/2041-210X.12362 | URI: | http://hdl.handle.net/10261/126204 | DOI: | 10.1111/2041-210X.12362 | Identificadores: | doi: 10.1111/2041-210X.12362 issn: 2041-210X |
Aparece en las colecciones: | (IMEDEA) Artículos |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | |
---|---|---|---|---|
accesoRestringido.pdf | 15,38 kB | Adobe PDF | Visualizar/Abrir |
CORE Recommender
SCOPUSTM
Citations
21
checked on 12-may-2024
WEB OF SCIENCETM
Citations
14
checked on 23-feb-2024
Page view(s)
339
checked on 13-may-2024
Download(s)
104
checked on 13-may-2024
Google ScholarTM
Check
Altmetric
Altmetric
NOTA: Los ítems de Digital.CSIC están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.