Bayesian methods to analyze historical collections in time and space: a case study using Cabo Verde endemic flora

Bibliographic Details
Main Author: Romeiras, Maria M.
Publication Date: 2020
Other Authors: Carine, Mark, Duarte, Maria Cristina, Catarino, Silvia, Dias, Filipe S., Borda-de-Água, Luís
Format: Article
Language: eng
Source: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Download full: http://hdl.handle.net/10400.5/20281
Summary: Original Research
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spelling Bayesian methods to analyze historical collections in time and space: a case study using Cabo Verde endemic floraBayesian methodsGaussian processesMacaronesian islandsscientific expeditionsspecies discoverytype specimensOriginal ResearchBiological collections, including herbarium specimens, are unique sources of biodiversity data presenting a window on the history of the development and accumulation of knowledge of a specific geographical region. Understanding how the process of discovery impacts that knowledge is particularly important for oceanic islands which are often characterized by both high levels of endemic diversity and high proportions of threatened taxa. The archipelagos of the Macaronesian region (i.e. Azores, Canaries, Savages, Madeira, and Cabo Verde) have been the focus of attention for scientific expeditions since the end of the 17th century. However, there is no integrated study describing the historical process of collecting, discovery and description of its flora. Using as a case study the Cabo Verde endemic angiosperm flora, we review the history of collecting in the flora and apply a Bayesian approach to assess the accumulation of species discovery, through time and space across the nine islands of the archipelago. Our results highlight the central role not only of natural characteristics (e.g. area, age, maximum altitude and average value of the terrain ruggedness index) but also historical factors (i.e. the location of major harbors) for the development of knowledge of the flora. The main factors that have determined the process of species description in the archipelago and how this impact our understanding of diversity patterns across archipelagos are discussedKathleen Pryer, Duke University, USARepositório da Universidade de LisboaRomeiras, Maria M.Carine, MarkDuarte, Maria CristinaCatarino, SilviaDias, Filipe S.Borda-de-Água, Luís2020-09-14T14:22:54Z20202020-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.5/20281engRomeiras MM, Carine M, Duarte MC, Catarino S, Dias FS and Borda-de-Água L (2020) Bayesian Methods to Analyze Historical Collections in Time and Space: A Case Study Using Cabo Verde Endemic Flora. Front. Plant Sci. 11:27810.3389/fpls.2020.00278info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-03-06T14:49:43Zoai:www.repository.utl.pt:10400.5/20281Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:05:03.592332Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Bayesian methods to analyze historical collections in time and space: a case study using Cabo Verde endemic flora
title Bayesian methods to analyze historical collections in time and space: a case study using Cabo Verde endemic flora
spellingShingle Bayesian methods to analyze historical collections in time and space: a case study using Cabo Verde endemic flora
Romeiras, Maria M.
Bayesian methods
Gaussian processes
Macaronesian islands
scientific expeditions
species discovery
type specimens
title_short Bayesian methods to analyze historical collections in time and space: a case study using Cabo Verde endemic flora
title_full Bayesian methods to analyze historical collections in time and space: a case study using Cabo Verde endemic flora
title_fullStr Bayesian methods to analyze historical collections in time and space: a case study using Cabo Verde endemic flora
title_full_unstemmed Bayesian methods to analyze historical collections in time and space: a case study using Cabo Verde endemic flora
title_sort Bayesian methods to analyze historical collections in time and space: a case study using Cabo Verde endemic flora
author Romeiras, Maria M.
author_facet Romeiras, Maria M.
Carine, Mark
Duarte, Maria Cristina
Catarino, Silvia
Dias, Filipe S.
Borda-de-Água, Luís
author_role author
author2 Carine, Mark
Duarte, Maria Cristina
Catarino, Silvia
Dias, Filipe S.
Borda-de-Água, Luís
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Repositório da Universidade de Lisboa
dc.contributor.author.fl_str_mv Romeiras, Maria M.
Carine, Mark
Duarte, Maria Cristina
Catarino, Silvia
Dias, Filipe S.
Borda-de-Água, Luís
dc.subject.por.fl_str_mv Bayesian methods
Gaussian processes
Macaronesian islands
scientific expeditions
species discovery
type specimens
topic Bayesian methods
Gaussian processes
Macaronesian islands
scientific expeditions
species discovery
type specimens
description Original Research
publishDate 2020
dc.date.none.fl_str_mv 2020-09-14T14:22:54Z
2020
2020-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.5/20281
url http://hdl.handle.net/10400.5/20281
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Romeiras MM, Carine M, Duarte MC, Catarino S, Dias FS and Borda-de-Água L (2020) Bayesian Methods to Analyze Historical Collections in Time and Space: A Case Study Using Cabo Verde Endemic Flora. Front. Plant Sci. 11:278
10.3389/fpls.2020.00278
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Kathleen Pryer, Duke University, USA
publisher.none.fl_str_mv Kathleen Pryer, Duke University, USA
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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