A likelihood-based approach for assessment of extra-pair paternity and conspecific brood parasitism in natural populations

Genotypes are frequently used to assess alternative reproductive strategies such as extra-pair paternity and conspecific brood parasitism in wild populations. However, such analyses are vulnerable to genotyping error or molecular artefacts that can bias results. For example, when using multilocus microsatellite data, a mismatch at a single locus, suggesting the offspring was not directly related to its putative parents, can occur quite commonly even when the offspring is truly related. Some recent studies have advocated an ad-hoc rule that offspring must differ at more than one locus in order to conclude that they are not directly related. While this reduces the frequency with which true offspring are identified as not directly related young, it also introduces bias in the opposite direction, wherein not directly related young are categorized as true offspring. More importantly, it ignores the additional information on allele frequencies which would reduce overall bias. In this study, we present a novel technique for assessing extra-pair paternity and conspecific brood parasitism using a likelihood-based approach in a new version of program cervus. We test the suitability of the technique by applying it to a simulated data set and then present an example to demonstrate its influence on the estimation of alternative reproductive strategies.