Literature DB >> 17400573

Evolution of population structure in a highly social top predator, the killer whale.

A Rus Hoelzel1, Jody Hey, Marilyn E Dahlheim, Colin Nicholson, Vladimir Burkanov, Nancy Black.   

Abstract

Intraspecific resource partitioning and social affiliations both have the potential to structure populations, though it is rarely possible to directly assess the impact of these mechanisms on genetic diversity and population divergence. Here, we address this for killer whales (Orcinus orca), which specialize on prey species and hunting strategy and have long-term social affiliations involving both males and females. We used genetic markers to assess the structure and demographic history of regional populations and test the hypothesis that known foraging specializations and matrifocal sociality contributed significantly to the evolution of population structure. We find genetic structure in sympatry between populations of foraging specialists (ecotypes) and evidence for isolation by distance within an ecotype. Fitting of an isolation with migration model suggested ongoing, low-level migration between regional populations (within and between ecotypes) and small effective sizes for extant local populations. The founding of local populations by matrifocal social groups was indicated by the pattern of fixed mtDNA haplotypes in regional populations. Simulations indicate that this occurred within the last 20,000 years (after the last glacial maximum). Our data indicate a key role for social and foraging behavior in the evolution of genetic structure among conspecific populations of the killer whale.

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Year:  2007        PMID: 17400573     DOI: 10.1093/molbev/msm063

Source DB:  PubMed          Journal:  Mol Biol Evol        ISSN: 0737-4038            Impact factor:   16.240


  38 in total

1.  Cross-cultural and cross-ecotype production of a killer whale 'excitement' call suggests universality.

Authors:  Nicola Rehn; Olga A Filatova; John W Durban; Andrew D Foote
Journal:  Naturwissenschaften       Date:  2010-11-12

2.  Efficient approximate Bayesian computation coupled with Markov chain Monte Carlo without likelihood.

Authors:  Daniel Wegmann; Christoph Leuenberger; Laurent Excoffier
Journal:  Genetics       Date:  2009-06-08       Impact factor: 4.562

3.  Hybridization, ecological races and the nature of species: empirical evidence for the ease of speciation.

Authors:  James Mallet
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2008-09-27       Impact factor: 6.237

4.  Isolation with migration models for more than two populations.

Authors:  Jody Hey
Journal:  Mol Biol Evol       Date:  2009-12-02       Impact factor: 16.240

5.  Patterns of population structure for inshore bottlenose dolphins along the eastern United States.

Authors:  Vincent P Richards; Thomas W Greig; Patricia A Fair; Stephen D McCulloch; Christine Politz; Ada Natoli; Carlos A Driscoll; A Rus Hoelzel; Victor David; Gregory D Bossart; Jose V Lopez
Journal:  J Hered       Date:  2013 Nov-Dec       Impact factor: 2.645

6.  Resource specialisation and the divergence of killer whale populations.

Authors:  A R Hoelzel; A E Moura
Journal:  Heredity (Edinb)       Date:  2015-05-20       Impact factor: 3.821

7.  A response to Hoelzel & Moura.

Authors:  A D Foote; P A Morin
Journal:  Heredity (Edinb)       Date:  2016-12-07       Impact factor: 3.821

8.  Killer whales differentiating in geographic sympatry facilitated by divergent behavioural traditions.

Authors:  A R Hoelzel; A E Moura
Journal:  Heredity (Edinb)       Date:  2016-11-02       Impact factor: 3.821

9.  Cultural transmission of tool use combined with habitat specializations leads to fine-scale genetic structure in bottlenose dolphins.

Authors:  Anna M Kopps; Corinne Y Ackermann; William B Sherwin; Simon J Allen; Lars Bejder; Michael Krützen
Journal:  Proc Biol Sci       Date:  2014-03-19       Impact factor: 5.349

10.  Genome-wide SNP data suggest complex ancestry of sympatric North Pacific killer whale ecotypes.

Authors:  A D Foote; P A Morin
Journal:  Heredity (Edinb)       Date:  2016-08-03       Impact factor: 3.821

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