Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/223937
Share/Export:
logo share SHARE logo core CORE BASE
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE
Title

Long‐term cloud forest response to climate warming revealed by insect speciation history

AuthorsSalces-Castellano, Antonia ; Stankowski, Sean; Arribas, Paula CSIC ORCID ; Patiño, Jairo; Karger, Dirk N.; Butlin, Roger; Emerson, Brent C. CSIC ORCID
KeywordsColeoptera
Hybridization
Last Glacial Maximum
Quaternary climate
Speciation
Trade‐wind inversion
Issue DateFeb-2021
PublisherWiley-VCH
Society for the Study of Evolution
CitationEvolution 75(2): 231-244 (2021)
AbstractMontane cloud forests are areas of high endemism, and are one of the more vulnerable terrestrial ecosystems to climate change. Thus, understanding how they both contribute to the generation of biodiversity, and will respond to ongoing climate change, are important and related challenges. The widely accepted model for montane cloud forest dynamics involves upslope forcing of their range limits with global climate warming. However, limited climate data provides some support for an alternative model, where range limits are forced downslope with climate warming. Testing between these two models is challenging, due to the inherent limitations of climate and pollen records. We overcome this with an alternative source of historical information, testing between competing model predictions using genomic data and demographic analyses for a species of beetle tightly associated to an oceanic island cloud forest. Results unequivocally support the alternative model: populations that were isolated at higher elevation peaks during the Last Glacial Maximum are now in contact and hybridizing at lower elevations. Our results suggest that genomic data are a rich source of information to further understand how montane cloud forest biodiversity originates, and how it is likely to be impacted by ongoing climate change.
Publisher version (URL)https://doi.org/10.1111/evo.14111
URIhttp://hdl.handle.net/10261/223937
DOI10.1111/evo.14111
ISSN0014-3820
E-ISSN1558-5646
Appears in Collections:(IPNA) Artículos




Files in This Item:
File Description SizeFormat
LongTerm-Arribas-2021-Evolution.pdfArtículo principal971,9 kBAdobe PDFThumbnail
View/Open
Show full item record
Review this work

SCOPUSTM   
Citations

3
checked on Jun 17, 2022

WEB OF SCIENCETM
Citations

5
checked on Jun 22, 2022

Page view(s)

198
checked on Jun 25, 2022

Download(s)

27
checked on Jun 25, 2022

Google ScholarTM

Check

Altmetric

Dimensions


WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.