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Local Adaptation in European Firs Assessed through Extensive Sampling across Altitudinal Gradients in Southern Europe
INRA, Domaine St Paul, URFM Ecol Forets Mediterraneennes UR629, Site Agroparc CS,Site Agroparc CS 40509, F-84914 Avignon 9, France.;Natl Res Council IBBR CNR, Div Florence, Inst Biosci & BioResources, Via Madonna Piano 10, I-50019 Sesto Fiorentino, FI, France..
Natl Res Council IBBR CNR, Div Florence, Inst Biosci & BioResources, Via Madonna Piano 10, I-50019 Sesto Fiorentino, FI, France.;Scuola Super Sant Anna, Piazza Martiri Liberta 33, I-56127 Pisa, Italy.;Natl Inst Forest Res & Dev INCDS, Res Stn Simeria, Str Biscaria 1, Simeria 335900, Romania..
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics, Plant Ecology and Evolution.
Aristotle Univ Thessaloniki, Sch Biol, GR-54124 Thessaloniki, Greece..
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2016 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 11, no 7, e0158216Article in journal (Refereed) PublishedText
Abstract [en]

Background Local adaptation is a key driver of phenotypic and genetic divergence at loci responsible for adaptive traits variations in forest tree populations. Its experimental assessment requires rigorous sampling strategies such as those involving population pairs replicated across broad spatial scales. Methods A hierarchical Bayesian model of selection (HBM) that explicitly considers both the replication of the environmental contrast and the hierarchical genetic structure among replicated study sites is introduced. Its power was assessed through simulations and compared to classical 'within-site' approaches (FDIST, BAYESCAN) and a simplified, within-site, version of the model introduced here (SBM). Results HBM demonstrates that hierarchical approaches are very powerful to detect replicated patterns of adaptive divergence with low false-discovery (FDR) and false-non-discovery (FNR) rates compared to the analysis of different sites separately through within-site approaches. The hypothesis of local adaptation to altitude was further addressed by analyzing replicated Abies alba population pairs (low and high elevations) across the species' southern distribution range, where the effects of climatic selection are expected to be the strongest. For comparison, a single population pair from the closely related species A. cephalonica was also analyzed. The hierarchical model did not detect any pattern of adaptive divergence to altitude replicated in the different study sites. Instead, idiosyncratic patterns of local adaptation among sites were detected by within-site approaches. Conclusion Hierarchical approaches may miss idiosyncratic patterns of adaptation among sites, and we strongly recommend the use of both hierarchical (multi-site) and classical (within-site) approaches when addressing the question of adaptation across broad spatial scales.

Place, publisher, year, edition, pages
2016. Vol. 11, no 7, e0158216
National Category
Evolutionary Biology
URN: urn:nbn:se:uu:diva-301423DOI: 10.1371/journal.pone.0158216ISI: 000380005400037OAI: oai:DiVA.org:uu-301423DiVA: diva2:954593
Available from: 2016-08-23 Created: 2016-08-23 Last updated: 2016-08-23Bibliographically approved

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Lascoux, MartinKällman, Thomas
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Plant Ecology and EvolutionDepartment of Medical Biochemistry and Microbiology
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