Factors predicting male fertilization success in an external fertilizer

  • Ståle Liljedal
  • Geir Rudolfsen
  • Ivar FolstadEmail author
Original Paper


In postcopulatory sexual selection both sperm competition and cryptic female choice are considered to be important selective agents, but their relative importance for male fertilization success has received little attention. We tested whether sperm quality, male spawning coloration, male heterozygosity, and genetic overlap with the female explained a male’s fertilization success in controlled in vitro fertilization competition trials between equal numbers of sperm from pairs of male Arctic charr (Salvelinus alpinus), an external fertilizer. Offspring were genotyped to determine each males’ share of paternity. The velocity of a male’s sperm relative to the velocity of the competing male’s sperm was the best predictor of male fertilization success. Yet, sperm velocity was not related to spawning coloration or male heterozygosity. In fact, the most brightly colored male in a pair had the lowest fertilization probability. This could result from cryptic female choice for pale males, but might rather be a result of paler males producing more competitive sperm than more colored males. Furthermore, the more microsatellite alleles a male shared with the female relative to the competing male, the higher fertilization success he had. We argue that this latter may be an effect of assortative cryptic female choice, which might prevent hybridization with sympatric Arctic charr morphs or one form of kin selection.


Sperm competition Sperm velocity Reproductive success 



Eirik Mack Eilertsen, Davnah Urbach, and Andreas Palmèn are acknowledged for enduring endless sessions of egg counting. E. M. Eilertsen is also the brain behind our ingenious, yet expensive, hatchery. Jon-Ivar Westgaard provided information about the microsatellite primers and PCR protocols. Jakob Lohm and Anne Grethe Hestnes never got tired of sharing their insights in various molecular biology techniques. Audun Stien introduced S. L. to quasibinomial tests and how to produce them, and additional plots, in the R software. Bård Jørgen Bårdsen was also very helpful teaching S. L. how to use R. Torkild Tveraa, Frode Skarstein, Jan T. Lifjeld and Anders P. Møller gave immensely improving comments to the manuscript.


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Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  1. 1.Department of BiologyUniversity of TromsøTromsøNorway

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