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 studied 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 showed that traits independent of male quality (i.e., insemination order, delay between insemination and egg laying) were the most important predictors of siring success. Traits describing intrinsic male quality (i.e., number of sperm in the ejaculate, mass motility index) were also positively associated with siring success, but their contribution to explaining the outcome of sperm competition was 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. 

The dataset includes variables related to the fertilization success of male North African houbara bustards after artificial insemination of females. The data have been collected over years on individuals maintained in captivity for the purpose of a conservation breeding program. The data have been processed using a machine learning approach with the aim of ranking the importance of each of the variables included in the model as predictors of male fertilization success when competing with the sperm of other males.

Data can be accessed using Excel.