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dc.contributor.authorFerrer, Davides_ES
dc.contributor.authorFernández-López, Javieres_ES
dc.contributor.authorTriguero, Roxanaes_ES
dc.contributor.authorPalencia, Pabloes_ES
dc.contributor.authorVicente, Joaquínes_ES
dc.contributor.authorAcevedo, Pelayoes_ES
dc.date.accessioned2024-04-12T09:28:03Z-
dc.date.available2024-04-12T09:28:03Z-
dc.date.issued2023-
dc.identifier.citationScience of The Total Environment 902: 166053 (2023)es_ES
dc.identifier.urihttp://hdl.handle.net/10261/353641-
dc.description.abstractHabitat use is a virtually universal activity among animals and is highly relevant as regards designing wildlife management and conservation actions. This has led to the development of a great variety of methods to study it, of which resource selection functions combined with biologging-derived data (RSF) is the most widely used for this purpose. However this approach has some constraints, such as its invasiveness and high costs. Analytical approaches taking into consideration imperfect detection coupled with camera trap data (IDM) have, therefore, emerged as a non-invasive cost-effective alternative. However, despite the fact that both approaches (RSF and IDM) have been used in habitat selection studies, they should also be comparatively assessed. The objective of this work is consequently to assess them from two perspectives: explanatory and predictive. This has been done by analyzing data obtained from camera traps (60 sampling sites) and biologging (17 animals monitored: 7 red deer Cervus elaphus, 6 fallow deer Dama dama and 4 wild boar Sus scrofa) in the same periods using IDM and RSF, respectively, in Doñana National Park (southern Spain) in order to explain and predict habitat use patterns for three studied species. Our results showed discrepancies between the two approaches, as they identified different predictors as being the most relevant to determine species intensity of use, and they predicted spatial patterns of habitat use with a contrasted level of concordance, depending on species and scale. Given these results and the characteristics of each approach, we suggested that although partly comparable interpretations can be obtained with both approaches, they are not equivalent but rather complementary. The combination of data from biologging and camera traps would, therefore, appear to be suitable for the development of an analytical framework with which to describe and characterise the habitat use processes of wildlife.es_ES
dc.description.sponsorshipDFF received a Start to Research grant for Master's degree students, financed by the collaboration agreement between the University of Castilla-La Mancha and the Banco Santander (2019-UNIVERS-9556), which allowed him to commence this study, and he also obtained support from the UCLM through a predoctoral scholarship (2020-PREDUCLM-16022), which allowed him to continue with this research. JFL was funded by the Margarita Salas grant from the European Union – NextGenerationEU through the Complutense University of Madrid. PP received support from University of Castilla-La Mancha through a Margarita Salas contract (2022-NACIONAL-110053). Our research group is partly supported by Applied Research Projects (2022-GRIN-34227) funded by UCLM-FEDER.es_ES
dc.formatapplication/pdfes_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.relation.isversionofPreprintes_ES
dc.relation.isbasedonThe underlying dataset has been published as supplementary material of the article in the publisher platform at DOI 10.1016/j.scitotenv.2023.166053es_ES
dc.relation.isbasedonDavid Ferrando Ferrer, Pelayo Acevedo Lavandera, Javier Fernández López, Roxana Triguero Ocaña, Pablo Palencia, & Joaquín Vicente. (2023). Ferrer-Ferrando_et_al.Habitat_Selection_BiologgingANDCameraTraps [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8214538es_ES
dc.rightsopenAccesses_ES
dc.titleThe method matters. A comparative study of biologging and camera traps as data sources with which to describe wildlife habitat selectiones_ES
dc.typeartículoes_ES
dc.identifier.doi10.1016/j.scitotenv.2023.166053-
dc.description.peerreviewedPeer reviewedes_ES
dc.relation.publisherversionhttps://doi.org/10.1016/j.scitotenv.2023.166053es_ES
dc.identifier.e-issn1879-1026-
dc.contributor.funderUniversidad de Castilla La Manchaes_ES
dc.contributor.funderBanco Santanderes_ES
dc.contributor.funderEuropean Commissiones_ES
dc.relation.csices_ES
oprm.item.hasRevisionno ko 0 false*
dc.identifier.funderhttp://dx.doi.org/10.13039/100010784es_ES
dc.identifier.funderhttp://dx.doi.org/10.13039/501100000780es_ES
dc.identifier.funderhttp://dx.doi.org/10.13039/501100007480es_ES
dc.identifier.pmid37543342-
dc.type.coarhttp://purl.org/coar/resource_type/c_6501es_ES
item.cerifentitytypePublications-
item.languageiso639-1en-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextopen-
item.fulltextWith Fulltext-
item.openairetypeartículo-
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