Approximate Bayesian Computation Reveals the Crucial Role of Oceanic Islands for the Assembly of Continental Biodiversity.

Journal Article (Journal Article)

The perceived low levels of genetic diversity, poor interspecific competitive and defensive ability, and loss of dispersal capacities of insular lineages have driven the view that oceanic islands are evolutionary dead ends. Focusing on the Atlantic bryophyte flora distributed across the archipelagos of the Azores, Madeira, the Canary Islands, Western Europe, and northwestern Africa, we used an integrative approach with species distribution modeling and population genetic analyses based on approximate Bayesian computation to determine whether this view applies to organisms with inherent high dispersal capacities. Genetic diversity was found to be higher in island than in continental populations, contributing to mounting evidence that, contrary to theoretical expectations, island populations are not necessarily genetically depauperate. Patterns of genetic variation among island and continental populations consistently fitted those simulated under a scenario of de novo foundation of continental populations from insular ancestors better than those expected if islands would represent a sink or a refugium of continental biodiversity. We, suggest that the northeastern Atlantic archipelagos have played a key role as a stepping stone for transoceanic migrants. Our results challenge the traditional notion that oceanic islands are the end of the colonization road and illustrate the significant role of oceanic islands as reservoirs of novel biodiversity for the assembly of continental floras.

Full Text

Duke Authors

Cited Authors

  • Patiño, J; Carine, M; Mardulyn, P; Devos, N; Mateo, RG; González-Mancebo, JM; Shaw, AJ; Vanderpoorten, A

Published Date

  • July 2015

Published In

Volume / Issue

  • 64 / 4

Start / End Page

  • 579 - 589

PubMed ID

  • 25713307

Electronic International Standard Serial Number (EISSN)

  • 1076-836X

International Standard Serial Number (ISSN)

  • 1063-5157

Digital Object Identifier (DOI)

  • 10.1093/sysbio/syv013


  • eng