Using tree species inventories to map biomes and assess their climatic overlaps in lowland tropical South America

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dc.creatorPedro Luiz Silva de Miranda
dc.creatorAry Teixeira de Oliveira Filho
dc.creatorToby Pennington
dc.creatorDanilo Rafael Mesquita Neves
dc.creatorTimothy R. Baker
dc.creatorKyle Graham Dexter
dc.date.accessioned2023-06-22T22:02:07Z
dc.date.accessioned2025-09-09T00:27:29Z
dc.date.available2023-06-22T22:02:07Z
dc.date.issued2018
dc.identifier.doihttps://doi.org/10.1111/geb.12749
dc.identifier.issn1466-8238
dc.identifier.urihttps://hdl.handle.net/1843/55245
dc.languagepor
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofGlobal Ecology and Biogeography
dc.rightsAcesso Restrito
dc.subjectMata Atlântica
dc.subjectCerrados - Brasil
dc.subjectClusters
dc.subjectSavanas
dc.subject.otherAmazon Forest
dc.subject.otherAtlantic Forest
dc.subject.otherCerrado
dc.subject.otherChaco
dc.subject.otherCluster analysis
dc.subject.otherNeoTropTree
dc.subject.otherSavanna
dc.subject.otherDry Tropical Forest
dc.titleUsing tree species inventories to map biomes and assess their climatic overlaps in lowland tropical South America
dc.typeArtigo de periódico
local.citation.epage912
local.citation.issue8
local.citation.spage899
local.citation.volume27
local.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.
local.identifier.orcidhttps://orcid.org/0000-0002-3008-1556
local.identifier.orcidhttps://orcid.org/0000-0002-8196-288X
local.identifier.orcidhttps://orcid.org/0000-0002-0855-4169
local.identifier.orcidhttps://orcid.org/0000-0001-9232-5221
local.publisher.countryBrasil
local.publisher.departmentICB - DEPARTAMENTO DE BOTÂNICA
local.publisher.initialsUFMG
local.url.externahttps://onlinelibrary.wiley.com/doi/full/10.1111/geb.12749

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