Marine Biology

, Volume 143, Issue 5, pp 947–962 | Cite as

Molecular and morphological analyses of the cuttlefish Sepia apama indicate a complex population structure

  • K. S. Kassahn
  • S. C. DonnellanEmail author
  • A. J. Fowler
  • K. C. Hall
  • M. Adams
  • P. W. Shaw


The giant Australian cuttlefish Sepia apama Gray, 1849 annually forms a massive and unique spawning aggregation in northern Spencer Gulf, South Australia, which has attracted commercial fishing interests in recent years. However, many basic life-history characteristics of S. apama are unknown, and anecdotal evidence suggests that there is more than one species. The present study assessed the population structure and species status of S. apama using data from allozyme electrophoresis, microsatellite loci, nucleotide sequences of the mitochondrial COXIII gene, multivariate morphometrics and colour patterns. Analyses of allozyme and microsatellite allele frequencies revealed two very divergent but geographically separated populations consisting of specimens from the east coast and southern Australia. However, the presence of a heterozygote in a putative contact zone between the east coast and southern Australia suggested that these populations were not reproductively isolated. Mitochondrial haplotypes seem to have introgressed further north into the contact zone than have nuclear alleles. Differences in colour patterns that previously had been attributed anecdotally to different geographic populations were, in fact, correlated with sexual dimorphism. These data are most consistent with S. apama being one species the populations of which were geographically isolated in the past (historical vicariance) and have come into secondary contact. Comparison of microsatellite allele frequencies among four South Australian samples indicated significant deviations from panmixia. South Australian samples were also reliably diagnosed by means of multivariate morphometrics. Significant differences in mantle length were observed among populations.


Discriminant Function Analysis Mismatch Distribution Discriminant Function Analysis South Australia Mantle Length 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This research was funded by the FRDC project number 98/151. We thank L. Triantafillos, R. Clementson, J. Brace, K. Rowling, H. Malcolm, J. North, J. Haddy, N. Kirby and E. Sporer for their assistance with the collection of samples, and K. Saint and T. Bertozzi for support with laboratory work. The experiments conducted in this project comply with Australian law.


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Copyright information

© Springer-Verlag 2003

Authors and Affiliations

  • K. S. Kassahn
    • 1
  • S. C. Donnellan
    • 2
    Email author
  • A. J. Fowler
    • 3
  • K. C. Hall
    • 3
    • 5
  • M. Adams
    • 2
  • P. W. Shaw
    • 4
  1. 1.Department of Environmental BiologyUniversity of AdelaideAdelaideAustralia
  2. 2.Evolutionary Biology UnitSouth Australian MuseumAdelaideAustralia
  3. 3.SARDI Aquatic SciencesWest BeachAustralia
  4. 4.Environmental and Evolutionary Biology Research Group, School of Biological SciencesUniversity of LondonEghamUK
  5. 5.Department of Environmental BiologyUniversity of AdelaideAdelaideAustralia

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