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Assessing the reliability of predicted plant trait distributions at the global scale

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dc.creatorBoonman, Coline C. F.spa
dc.creatorBenítez?López, Anaspa
dc.creatorSchipper, Aafke M.spa
dc.creatorThuiller, Wilfriedspa
dc.creatorAnand, Madhurspa
dc.creatorCerabolini, Bruno E. L.spa
dc.creatorCornelissen, Johannes H. C.spa
dc.creatorGonzalez?Melo, Andresspa
dc.creatorHattingh, Wesley N.spa
dc.creatorHiguchi, Pedrospa
dc.creatorLaughlin, Daniel C.spa
dc.creatorOnipchenko, Vladimir G.spa
dc.creatorPeñuelas, Josepspa
dc.creatorPoorter, Lourensspa
dc.creatorSoudzilovskaia, Nadejda A.spa
dc.creatorHuijbregts, Mark A. J.spa
dc.creatorSantini, Lucaspa
dc.date.accessioned2020-05-26T00:09:34Z
dc.date.available2020-05-26T00:09:34Z
dc.date.created2020spa
dc.description.abstractAim: Predictions of plant traits over space and time are increasingly used to improve our understanding of plant community responses to global environmental change. A necessary step forward is to assess the reliability of global trait predictions. In this study, we predict community mean plant traits at the global scale and present a systematic evaluation of their reliability in terms of the accuracy of the models, ecological realism and various sources of uncertainty. Location: Global. Time period: Present. Major taxa studied: Vascular plants. Methods: We predicted global distributions of community mean specific leaf area, leaf nitrogen concentration, plant height and wood density with an ensemble modelling approach based on georeferenced, locally measured trait data representative of the plant community. We assessed the predictive performance of the models, the plausibility of predicted trait combinations, the influence of data quality, and the uncertainty across geographical space attributed to spatial extrapolation and diverging model predictions. Results: Ensemble predictions of community mean plant height, specific leaf area and wood density resulted in ecologically plausible trait–environment relationships and trait–trait combinations. Leaf nitrogen concentration, however, could not be predicted reliably. The ensemble approach was better at predicting community trait means than any of the individual modelling techniques, which varied greatly in predictive performance and led to divergent predictions, mostly in African deserts and the Arctic, where predictions were also extrapolated. High data quality (i.e., including intraspecific variability and a representative species sample) increased model performance by 28%. Main conclusions: Plant community traits can be predicted reliably at the global scale when using an ensemble approach and high-quality data for traits that mostly respond to large-scale environmental factors. We recommend applying ensemble forecasting to account for model uncertainty, using representative trait data, and more routinely assessing the reliability of trait predictions. © 2020 The Authors. Global Ecology and Biogeography published by John Wiley and Sons Ltdeng
dc.format.mimetypeapplication/pdf
dc.identifier.doihttps://doi.org/10.1111/geb.13086
dc.identifier.issn1466822X
dc.identifier.urihttps://repository.urosario.edu.co/handle/10336/24162
dc.language.isoengspa
dc.publisherBlackwell Publishing Ltdspa
dc.relation.citationTitleGlobal Ecology and Biogeography
dc.relation.ispartofGlobal Ecology and Biogeography, ISSN:1466822X,(2020)spa
dc.relation.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85082053081&doi=10.1111%2fgeb.13086&partnerID=40&md5=af2a35408947ee4d709214b7353ab807spa
dc.rights.accesRightsinfo:eu-repo/semantics/openAccess
dc.rights.accesoAbierto (Texto Completo)spa
dc.source.instnameinstname:Universidad del Rosariospa
dc.source.reponamereponame:Repositorio Institucional EdocURspa
dc.subject.keywordEnsemble forecastingspa
dc.subject.keywordEnvironmental filteringspa
dc.subject.keywordIntraspecific trait variationspa
dc.subject.keywordLeaf nitrogen concentrationspa
dc.subject.keywordPlant heightspa
dc.subject.keywordSpecific leaf areaspa
dc.subject.keywordTrait modelspa
dc.subject.keywordTrait–environment relationshipsspa
dc.subject.keywordWood densityspa
dc.titleAssessing the reliability of predicted plant trait distributions at the global scalespa
dc.typearticleeng
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersion
dc.type.spaArtículospa
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