Reconciling deep calibration and demographic history: Bayesian inference of post glacial colonization patterns in Carcinus aestuarii (Nardo, 1847) and C. maenas (Linnaeus, 1758)

• Published in: PLoS ONE
• Main Authors: MARINO, ILARIA ANNA MARIA, PUJOLAR CASTANER, JOSE' MARTIN, ZANE, LORENZO
• Other Authors: Marino, ILARIA ANNA MARIA, Zane, Lorenzo
• Format: Article in Journal/Newspaper
• Language: English
• Published: San Francisco, CA : Public Library of Science 2011
• Subjects: molecular clock; historical demography; phylogeography; estuarine habitats; Ice Sheet
• Online Access: http://hdl.handle.net/11577/2480476; https://doi.org/10.1371/journal.pone.0028567

A precise inference of past demographic histories including dating of demographic events using Bayesian methods can only be achieved with the use of appropriate molecular rates and evolutionary models. Using a set of 596 mitochondrial cytochrome c oxidase I (COI) sequences of two sister species of European green crabs of the genus Carcinus (C. maenas and C. aestuarii), our study shows how chronologies of past evolutionary events change significantly with the application of revised molecular rates that incorporate biogeographic events for calibration and appropriate demographic priors. A clear signal of demographic expansion was found for both species, dated between 10,000 and 20,000 years ago, which places the expansions events in a time frame following the Last Glacial Maximum (LGM). In the case of C. aestuarii, a population expansion was only inferred for the Adriatic-Ionian, suggestive of a colonization event following the flooding of the Adriatic Sea (18,000 years ago). For C. maenas, the demographic expansion inferred for the continental populations of West and North Europe might result from a northward recolonization from a southern refugium when the ice sheet retreated after the LGM. Collectively, our results highlight the importance of using adequate calibrations and demographic priors in order to avoid considerable overestimates of evolutionary time scales.