Satellite remote sensing can operationalise the IUCN Global Ecosystem Typology in the biome-diverse north-east of Brazil

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Autor(es): dc.contributorUniversity of Edinburgh-
Autor(es): dc.contributorRoyal Botanic Garden Edinburgh-
Autor(es): dc.contributorUniversity of Turin-
Autor(es): dc.contributorUniversity of Exeter-
Autor(es): dc.contributorUso e Conservação da Biodiversidade-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorUniversity of Leeds-
Autor(es): dc.creatorWells, Lucy H.-
Autor(es): dc.creatorDexter, Kyle G.-
Autor(es): dc.creatorPennington, R. Toby-
Autor(es): dc.creatorCoutinho, Ítalo Antônio Cotta-
Autor(es): dc.creatorRamos, Desiree-
Autor(es): dc.creatorPhillips, Oliver L.-
Autor(es): dc.creatorBaker, Tim-
Autor(es): dc.creatorRyan, Casey M.-
Data de aceite: dc.date.accessioned2025-08-21T22:31:39Z-
Data de disponibilização: dc.date.available2025-08-21T22:31:39Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2024-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.21425/FOB.18.145498-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/303608-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/303608-
Descrição: dc.descriptionAccurate biome delineation is difficult where biomes occupy the same climatic space, as is the case for tropical dry forest and savanna. The resulting confusion limits our ability to understand and manage impacts of global change on these biomes. To address this, we developed an unsupervised, repeatable method to delineate biomes and their component functional ecosystems, based on landscape-level vegetation structure measured using remote sensing and an understanding of the ecology of the region. This approach contrasts with previous definitions, based on climate differences amongst savanna, dry forest and rain forest. Using the heterogeneous north-east Brazil, where several biomes interdigitate, as a case study, a hierarchical functional ecosystem classification is proposed that aligns with both the IUCN Global Ecosystem Typology (GET) and previous work. Based on fuzzy clustering of remotely sensed vegetation attributes, seven groups were found, identified as rain forest, cerrado (savanna) and five caatinga vegetation groups. These groups broadly align with the literature, for example, sedimentary and arboreal caatinga. These groups align with three ‘Ecosystem Functional Groups’ (EFGs) described by the IUCN GET and, additionally, suggest there is a new, fourth EFG in the region: non-pyric shrublands. Random Forest models showed soil pH was the most important environmental variable distinguishing these vegetation groups. These results suggest a remotely sensed structure-based approach is an effective method for operationalising the IUCN GET. North-East Brazil – where many EFGs are interdigitated – serves as a challenging case study and, therefore, we hope our approach will have generality for other regions globally. Highlights • There are seven vegetation groups in northeast Brazil, including savanna, rain forest and five types of caatinga. • Most of these vegetation groups align with the IUCN Global Ecosystem Typology 2.0, but non-pyric shrubland (caatinga) vegetation may represent a new Ecosystem Functional Group. • Soil pH is the strongest determinant of vegetation distribution in northeast Brazil. • Remote sensing can provide objective, spatially explicit information on vegetation types in the region, largely consistent with previous vegetation classifications. • Accurate biome mapping is vital for management, as biomes differ in ecosystem function and consequently require different management.-
Descrição: dc.descriptionSchool of Geosciences University of Edinburgh-
Descrição: dc.descriptionRoyal Botanic Garden Edinburgh-
Descrição: dc.descriptionDepartment of Life Sciences and Systems Biology University of Turin-
Descrição: dc.descriptionDepartment of Geography University of Exeter-
Descrição: dc.descriptionUniversidade Federal do Ceará Centro de Ciências Programa de Pós-graduação em Sistemática Uso e Conservação da Biodiversidade-
Descrição: dc.descriptionDepartment of Biodiversity Bioscience Institute São Paulo State University UNESP, Rio Claro-
Descrição: dc.descriptionSchool of Geography University of Leeds-
Descrição: dc.descriptionDepartment of Biodiversity Bioscience Institute São Paulo State University UNESP, Rio Claro-
Idioma: dc.languageen-
Relação: dc.relationFrontiers of Biogeography-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectBiome-
Palavras-chave: dc.subjectBrazil-
Palavras-chave: dc.subjectcaatinga-
Palavras-chave: dc.subjectIUCN-
Palavras-chave: dc.subjectremote sensing-
Palavras-chave: dc.subjectsoil-
Palavras-chave: dc.subjectvegetation structure-
Título: dc.titleSatellite remote sensing can operationalise the IUCN Global Ecosystem Typology in the biome-diverse north-east of Brazil-
Tipo de arquivo: dc.typelivro digital-
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