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Ranking parameters driving siring success during sperm competition in the North African houbara bustard.


ABSTRACT: Sperm competition is a powerful force driving the evolution of ejaculate and sperm traits. However, the outcome of sperm competition depends on many traits that extend beyond ejaculate quality. Here, we study male North African houbara bustards (Chlamydotis undulata undulata) competing for egg fertilization, after artificial insemination, with the aim to rank the importance of 14 parameters as drivers of siring success. Using a machine learning approach, we show that traits independent of male quality (i.e., insemination order, delay between insemination and egg laying) are the most important predictors of siring success. Traits describing intrinsic male quality (i.e., number of sperm in the ejaculate, mass motility index) are also positively associated with siring success, but their contribution to explaining the outcome of sperm competition is much lower than for insemination order. Overall, this analysis shows that males mating at the last position in the mating sequence have the best chance to win the competition for egg fertilization. This raises the question of the importance of female behavior as determinant of mating order.

SUBMITTER: Sorci G 

PROVIDER: S-EPMC10033649 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

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Ranking parameters driving siring success during sperm competition in the North African houbara bustard.

Sorci Gabriele G   Hussein Hiba Abi HA   Levêque Gwènaëlle G   Saint Jalme Michel M   Lacroix Frédéric F   Hingrat Yves Y   Lesobre Loïc L  

Communications biology 20230322 1


Sperm competition is a powerful force driving the evolution of ejaculate and sperm traits. However, the outcome of sperm competition depends on many traits that extend beyond ejaculate quality. Here, we study male North African houbara bustards (Chlamydotis undulata undulata) competing for egg fertilization, after artificial insemination, with the aim to rank the importance of 14 parameters as drivers of siring success. Using a machine learning approach, we show that traits independent of male q  ...[more]

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