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Mapping local and global variability in plant trait distributions

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dc.creatorButler, Ethan E.spa
dc.creatorDatta, Abhirupspa
dc.creatorFlores-Moreno, Habacucspa
dc.creatorChen, Mingspa
dc.creatorWythers, Kirk R.spa
dc.creatorFazayeli, Faridehspa
dc.creatorBanerjee, Arindamspa
dc.creatorAtkin, Owen K.spa
dc.creatorKattge, Jensspa
dc.creatorAmiaud, Bernardspa
dc.creatorBlonder, Benjaminspa
dc.creatorBoenisch, Gerhardspa
dc.creatorBond-Lamberty, Benspa
dc.creatorBrown, Kerry A.spa
dc.creatorByun, Chaehospa
dc.creatorCampetella, Giandiegospa
dc.creatorCerabolini, Bruno E. L.spa
dc.creatorCornelissen, Johannes H. C.spa
dc.creatorCraine, Joseph M.spa
dc.creatorCraven, Dylanspa
dc.creatorde Vries, Franciska T.spa
dc.creatorDíaz, Sandraspa
dc.creatorDomingues, Tomas F.spa
dc.creatorForey, Estellespa
dc.creatorGonzález-Melo, Andrésspa
dc.creatorGross, Nicolasspa
dc.creatorHan, Wenxuanspa
dc.creatorHattingh, Wesley N.spa
dc.creatorHickler, Thomasspa
dc.creatorJansen, Stevenspa
dc.creatorKramer, Koenspa
dc.creatorKraft, Nathan J. B.spa
dc.creatorKurokawa, Hirokospa
dc.creatorLaughlin, Daniel C.spa
dc.creatorMeir, Patrickspa
dc.creatorMinden, Vanessaspa
dc.creatorNiinemets, Ülospa
dc.creatorOnoda, Yusukespa
dc.creatorPeñuelas, Josepspa
dc.creatorRead, Quentinspa
dc.creatorSack, Lawrenspa
dc.creatorSchamp, Brandonspa
dc.creatorSoudzilovskaia, Nadejda A.spa
dc.creatorSpasojevic, Marko J.spa
dc.creatorSosinski, Eniospa
dc.creatorThornton, Peter E.spa
dc.creatorValladares, Fernandospa
dc.creatorvan Bodegom, Peter M.spa
dc.creatorWilliams, Mathewspa
dc.creatorWirth, Christianspa
dc.creatorReich, Peter B.spa
dc.date.accessioned2020-05-25T23:58:31Z
dc.date.available2020-05-25T23:58:31Z
dc.date.created2017spa
dc.description.abstractOur ability to understand and predict the response of ecosystems to a changing environment depends on quantifying vegetation functional diversity. However, representing this diversity at the global scale is challenging. Typically, in Earth system models, characterization of plant diversity has been limited to grouping related species into plant functional types (PFTs), with all trait variation in a PFT collapsed into a single mean value that is applied globally. Using the largest global plant trait database and state of the art Bayesian modeling, we created fine-grained global maps of plant trait distributions that can be applied to Earth system models. Focusing on a set of plant traits closely coupled to photosynthesis and foliar respiration - specific leaf area (SLA) and dry mass-based concentrations of leaf nitrogen (Nm) and phosphorus (Pm), we characterize how traits vary within and among over 50,000 ?50×50-km cells across the entire vegetated land surface. We do this in several ways - without defining the PFT of each grid cell and using 4 or 14 PFTs; each model's predictions are evaluated against out-of-sample data. This endeavor advances prior trait mapping by generating global maps that preserve variability across scales by using modern Bayesian spatial statistical modeling in combination with a database over three times larger than that in previous analyses. Our maps reveal that the most diverse grid cells possess trait variability close to the range of global PFT means.eng
dc.format.mimetypeapplication/pdf
dc.identifier.doihttps://doi.org/10.1073/pnas.1708984114
dc.identifier.issn10916490
dc.identifier.issn00278424
dc.identifier.urihttps://repository.urosario.edu.co/handle/10336/22879
dc.language.isoengspa
dc.publisherNational Academy of Sciencesspa
dc.relation.citationEndPageE10946
dc.relation.citationIssueNo. 51
dc.relation.citationStartPageE10937
dc.relation.citationTitleProceedings of the National Academy of Sciences of the United States of America
dc.relation.citationVolumeVol. 114
dc.relation.ispartofProceedings of the National Academy of Sciences of the United States of America, ISSN:10916490, 00278424, Vol.114, No.51 (2017); pp. E10937-E10946spa
dc.relation.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85038871701&doi=10.1073%2fpnas.1708984114&partnerID=40&md5=bc50785f52376a4305a7bc29eb72ab2cspa
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.keywordNitrogenspa
dc.subject.keywordstatisticaleng
dc.subject.keywordArticlespa
dc.subject.keywordBayes theoremspa
dc.subject.keywordConcentration (parameters)spa
dc.subject.keywordData basespa
dc.subject.keywordEnvironmentspa
dc.subject.keywordEvergreenspa
dc.subject.keywordLeaf areaspa
dc.subject.keywordLeaf litterspa
dc.subject.keywordModelspa
dc.subject.keywordNonhumanspa
dc.subject.keywordPlantspa
dc.subject.keywordPredictionspa
dc.subject.keywordPriority journalspa
dc.subject.keywordEcosystemspa
dc.subject.keywordGeographyspa
dc.subject.keywordPlant dispersalspa
dc.subject.keywordQuantitative traitspa
dc.subject.keywordSpatial analysisspa
dc.subject.keywordStatistical modelspa
dc.subject.keywordEcosystemspa
dc.subject.keywordEnvironmentspa
dc.subject.keywordGeographyspa
dc.subject.keywordModelseng
dc.subject.keywordPlant dispersalspa
dc.subject.keywordPlantsspa
dc.subject.keywordQuantitative traiteng
dc.subject.keywordSpatial analysisspa
dc.subject.keywordBayesian modelingspa
dc.subject.keywordClimatespa
dc.subject.keywordGlobalspa
dc.subject.keywordPlant traitsspa
dc.subject.keywordSpatial statisticsspa
dc.titleMapping local and global variability in plant trait distributionsspa
dc.typearticleeng
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersion
dc.type.spaArtículospa
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