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Please use this identifier to cite or link to this item: http://hdl.handle.net/1843/55245
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dc.creatorPedro Luiz Silva de Mirandapt_BR
dc.creatorAry Teixeira de Oliveira Filhopt_BR
dc.creatorToby Penningtonpt_BR
dc.creatorDanilo Rafael Mesquita Nevespt_BR
dc.creatorTimothy R. Bakerpt_BR
dc.creatorKyle Graham Dexterpt_BR
dc.date.accessioned2023-06-22T22:02:07Z-
dc.date.available2023-06-22T22:02:07Z-
dc.date.issued2018-
dc.citation.volume27pt_BR
dc.citation.issue8pt_BR
dc.citation.spage899pt_BR
dc.citation.epage912pt_BR
dc.identifier.doihttps://doi.org/10.1111/geb.12749pt_BR
dc.identifier.issn1466-8238pt_BR
dc.identifier.urihttp://hdl.handle.net/1843/55245-
dc.description.resumoAim: To define and map the main biomes of lowland tropical South America (LTSA) using data from tree species inventories and to test the ability of climatic and edaphic variables to distinguish amongst them. Location: Lowland Tropical South America (LTSA), including Argentina, Bolivia, Brazil, Ecuador, Paraguay, Peru and Uruguay. Time period: Present. Major taxa studied: Trees. Methods: We compiled a database of 4,103 geo-referenced tree species inventories distributed across LTSA. We used a priori vegetation classifications and cluster analyses of floristic composition to assign sites to biomes. We mapped these biomes geographically and assessed climatic overlaps amongst them. We implemented classification tree approaches to quantify how well climatic and edaphic data can assign inventories to biomes. Results: Our analyses distinguish savanna and seasonally dry tropical forest (SDTF) as distinct biomes, with the Chaco woodlands potentially representing a third dry biome in LTSA. Amongst the wet forests, we find that the Amazon and Atlantic Forests might represent different biomes, because they are distinct in both climate and species composition. Our results show substantial environmental overlap amongst biomes, with error rates for classifying sites into biomes of 19–21 and 16–18% using only climatic data and with the inclusion of edaphic data, respectively. Main conclusions: Tree species composition can be used to determine biome identity at continental scales. We find high biome heterogeneity at small spatial scales, probably attributable to variation in edaphic conditions and disturbance history. This points to the challenges of using climatic and/or interpolation-based edaphic data or coarse-resolution, remotely sensed imagery to map tropical biomes. From this perspective, we suggest that using floristic information in biome delimitation will allow for greater synergy between conservation efforts centred on species diversity and management efforts centred on ecosystem function.pt_BR
dc.languageporpt_BR
dc.publisherUniversidade Federal de Minas Geraispt_BR
dc.publisher.countryBrasilpt_BR
dc.publisher.departmentICB - DEPARTAMENTO DE BOTÂNICApt_BR
dc.publisher.initialsUFMGpt_BR
dc.relation.ispartofGlobal Ecology and Biogeographypt_BR
dc.rightsAcesso Restritopt_BR
dc.subjectAmazon Forestpt_BR
dc.subjectAtlantic Forestpt_BR
dc.subjectCerradopt_BR
dc.subjectChacopt_BR
dc.subjectCluster analysispt_BR
dc.subjectNeoTropTreept_BR
dc.subjectSavannapt_BR
dc.subjectDry Tropical Forestpt_BR
dc.subject.otherMata Atlânticapt_BR
dc.subject.otherCerrados - Brasilpt_BR
dc.subject.otherClusterspt_BR
dc.subject.otherSavanaspt_BR
dc.titleUsing tree species inventories to map biomes and assess their climatic overlaps in lowland tropical South Americapt_BR
dc.typeArtigo de Periódicopt_BR
dc.url.externahttps://onlinelibrary.wiley.com/doi/full/10.1111/geb.12749pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0002-3008-1556pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0002-8196-288Xpt_BR
dc.identifier.orcidhttps://orcid.org/0000-0002-0855-4169pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0001-9232-5221pt_BR
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