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dc.contributor.authorParadinas, Iosu
dc.contributor.authorIllian, Janine
dc.contributor.authorSmout, Sophie
dc.date.accessioned2023-05-31T09:30:19Z
dc.date.available2023-05-31T09:30:19Z
dc.date.issued2023-05-30
dc.identifier286919402
dc.identifier45643e2c-de03-42de-ac60-b551c0832d5e
dc.identifier85160637557
dc.identifier001000621000036
dc.identifier37253039
dc.identifier.citationParadinas , I , Illian , J & Smout , S 2023 , ' Understanding spatial effects in species distribution models ' , PLoS ONE , vol. 18 , no. 5 , e0285463 . https://doi.org/10.1371/journal.pone.0285463en
dc.identifier.issn1932-6203
dc.identifier.otherRIS: urn:1B9BA66F7AB6FB19BF6114B8AABE3C62
dc.identifier.urihttps://hdl.handle.net/10023/27703
dc.descriptionFunding: IP was funded by a Marie Skłodowska-Curie Research Fellowship (GAP-847014).en
dc.description.abstractSpecies Distribution Models often include spatial effects which may improve prediction at unsampled locations and reduce Type I errors when identifying environmental drivers. In some cases ecologists try to ecologically interpret the spatial patterns displayed by the spatial effect. However, spatial autocorrelation may be driven by many different unaccounted drivers, which complicates the ecological interpretation of fitted spatial effects. This study aims to provide a practical demonstration that spatial effects are able to smooth the effect of multiple unaccounted drivers. To do so we use a simulation study that fit model-based spatial models using both geostatistics and 2D smoothing splines. Results show that fitted spatial effects resemble the sum of the unaccounted covariate surface(s) in each model.
dc.format.extent6
dc.format.extent490889
dc.language.isoeng
dc.relation.ispartofPLoS ONEen
dc.subjectQL Zoologyen
dc.subjectGC Oceanographyen
dc.subjectNDASen
dc.subjectMCCen
dc.subject.lccQLen
dc.subject.lccGCen
dc.titleUnderstanding spatial effects in species distribution modelsen
dc.typeJournal articleen
dc.contributor.institutionUniversity of St Andrews. School of Biologyen
dc.contributor.institutionUniversity of St Andrews. Sea Mammal Research Uniten
dc.contributor.institutionUniversity of St Andrews. Scottish Oceans Instituteen
dc.contributor.institutionUniversity of St Andrews. Centre for Research into Ecological & Environmental Modellingen
dc.contributor.institutionUniversity of St Andrews. Coastal Resources Management Groupen
dc.identifier.doi10.1371/journal.pone.0285463
dc.description.statusPeer revieweden


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