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Optimal sex allocation theory is one of the most intricately developed areasof evolutionary ecology. Under a range of conditions, particularly underpopulation sub-division, selection favours sex being allocated to offspringnon-randomly, generating non-binomial variances of offspring group sex ratios.Detecting non-binomial sex allocation is complicated by stochasticdevelopmental mortality, as offspring sex can often only be identified onmaturity with the sex of non-maturing offspring remaining unknown. We show thatcurrent approaches for detecting non-binomiality have limited ability to detectnon-binomial sex allocation when developmental mortality has occurred. Wepresent a new procedure using an explicit model of sex allocation and mortalityand develop a Bayesian model selection approach (available as an R package). Weuse the double and multiplicative binomial distributions to model over- andunder-dispersed sex allocation and show how to calculate Bayes factors forcomparing these alternative models to the null hypothesis of binomial sexallocation. The ability to detect non-binomial sex allocation is greatlyincreased, particularly in cases where mortality is common. The use of Bayesianmethods allows for the quantification of the evidence in favour of eachhypothesis, and our modelling approach provides an improved descriptivecapability over existing approaches. We use a simulation study to demonstratesubstantial improvements in power for detecting non-binomial sex allocation insituations where current methods fail, and we illustrate the approach in realscenarios using empirically obtained datasets on the sexual composition ofgroups of gregarious parasitoid wasps.

Detecting non-binomial sex allocation when developmental mortality operates