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dc.contributor.authorMostert, Philip Stanley
dc.contributor.authorO'Hara, Robert B.
dc.date.accessioned2023-11-01T07:39:50Z
dc.date.available2023-11-01T07:39:50Z
dc.date.created2023-04-17T12:55:04Z
dc.date.issued2023
dc.identifier.issn2041-210X
dc.identifier.urihttps://hdl.handle.net/11250/3099882
dc.description.abstractEcological data are being collected at a large scale from a multitude of different sources, each with their own sampling protocols and assumptions. As a result, the integration of disparate datasets is a rapidly growing area in quantitative ecology, and is subsequently becoming a major asset in understanding the shifts and trends in species' distributions. However, the tools and software available to construct statistical models to integrate these disparate datasets into a unified framework is lacking. This has made these methods inaccessible to general practitioners and has stagnated the growth of data integration in more applied settings. We therefore present PointedSDMs: an easy to use R package used to construct integrated species distribution models. It provides functions to easily format the data, fit the models in a computationally efficient way and presents the output in a format that is convenient for additional work. This paper illustrates the different uses and functions available in the package, which are designed to simplify the modelling of integrated models. A case study using the package is also presented: combining three datasets coming from different sampling protocols, all containing records of Setophaga caerulescens across Pennsylvania state.en_US
dc.language.isoengen_US
dc.publisherJohn Wiley & Sons Ltd on behalf of British Ecological Society.en_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titlePointedSDMs: An R package to help facilitate the construction of integrated species distribution modelsen_US
dc.title.alternativePointedSDMs: An R package to help facilitate the construction of integrated species distribution modelsen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.pagenumber1200-1207en_US
dc.source.volume14en_US
dc.source.journalMethods in Ecology and Evolutionen_US
dc.source.issue5en_US
dc.identifier.doi10.1111/2041-210X.14091
dc.identifier.cristin2141273
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2


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Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal