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dc.contributor.authorIsaac, Nick J.B.
dc.contributor.authorOHara, Robert Brian
dc.date.accessioned2021-03-09T11:03:43Z
dc.date.available2021-03-09T11:03:43Z
dc.date.created2021-01-18T11:24:14Z
dc.date.issued2019
dc.identifier.issn0169-5347
dc.identifier.urihttps://hdl.handle.net/11250/2732344
dc.description.abstractWith the expansion in the quantity and types of biodiversity data being collected, there is a need to find ways to combine these different sources to provide cohesive summaries of species’ potential and realized distributions in space and time. Recently, model-based data integration has emerged as a means to achieve this by combining datasets in ways that retain the strengths of each. We describe a flexible approach to data integration using point process models, which provide a convenient way to translate across ecological currencies. We highlight recent examples of large-scale ecological models based on data integration and outline the conceptual and technical challenges and opportunities that arise.en_US
dc.language.isoengen_US
dc.publisherCell Pressen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleData Integration for Large-Scale Models of Species Distributionsen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.journalTrends in Ecology & Evolutionen_US
dc.identifier.doi10.1016/j.tree.2019.08.006
dc.identifier.cristin1873057
dc.description.localcode© 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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