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dc.contributor.authorJackson, Andrewen
dc.date.accessioned2014-09-05T10:26:38Z
dc.date.available2014-09-05T10:26:38Z
dc.date.issued2014en
dc.date.submitted2014en
dc.identifier.citationPhillips, D.L., Inger, R., Bearhop, S., Jackson, A.L., Moore, J., Parnell, A.C., Semmens, B.X. & Ward, E.J., Best practices for use of stable isotope mixing models in food web studies, Canadian Journal of Zoology, 92, 10, 2014, 823 - 835en
dc.identifier.otherYen
dc.identifier.urihttp://hdl.handle.net/2262/71218
dc.descriptionPUBLISHEDen
dc.description.abstractStable isotope mixing models are increasingly used to quantify consumer diets, but may be misused and misinterpreted. We address major challenges to their effective application. Mixing models have increased rapidly in sophistication. Current models estimate probability distributions of source contributions, have user friendly interfaces, and incorporate complexities such as variability in isotope signatures, discrimination factors, hierarchical variance structure, covariates, and concentration4dependence. For proper implementation of mixing models, we offer the following suggestions. First, mixing models can only be as good as the study and data. Studies should have clear questions, be informed by knowledge of the system, and have strong sampling designs to effectively characterize isotope variability of consumers and resources on proper spatio4temporal scales. Second, studies should use models appropriate for the question and recognize their assumptions and limitations. Decisions about source grouping or incorporation of concentration4dependence can influence results. Third, studies should be careful about interpretation of model outputs. Mixing model s generally estimate proportions of assimilated resources with substantial uncertainty distributions. Last, common sense, such as graphing data before analyzing, is essential to maximize usefulness of these tools. We hope these suggestions for effective implementation of stable isotope mixing models will aid continued development and application of this field.en
dc.format.extent823en
dc.format.extent835en
dc.language.isoenen
dc.relation.ispartofseriesCanadian Journal of Zoologyen
dc.relation.ispartofseries92en
dc.relation.ispartofseries10en
dc.rightsYen
dc.subjecttrophic levelen
dc.subjectisotopic ratiosen
dc.subjectfood chainen
dc.subjectdieten
dc.subjectconsumersen
dc.titleBest practices for use of stable isotope mixing models in food web studiesen
dc.typeJournal Articleen
dc.type.supercollectionscholarly_publicationsen
dc.type.supercollectionrefereed_publicationsen
dc.identifier.peoplefinderurlhttp://people.tcd.ie/jacksoanen
dc.identifier.rssinternalid96126en
dc.identifier.doihttps://doi.org/10.1139/cjz-2014-0127en
dc.rights.ecaccessrightsopenAccess
dc.subject.TCDThemeSmart & Sustainable Planeten
dc.subject.TCDTagApplied Statisticsen
dc.subject.TCDTagBAYESIAN STATISTICSen
dc.subject.TCDTagBiodiversityen
dc.subject.TCDTagBiodiversity and Conservationen
dc.subject.TCDTagEcologyen
dc.subject.TCDTagEnvironmental Impacts, Interactionsen
dc.subject.TCDTagMULTIVARIATE STATISTICSen
dc.subject.TCDTagSTATISTICSen
dc.identifier.orcid_id0000-0001-7334-0434en


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