Experimental alteration of litter sex ratios in a mammal.

Adaptive theory predicts that mothers would be advantaged by adjusting the sex ratio of their offspring in relation to their offspring's future reproductive success. Studies investigating sex ratio variation in mammals, including humans, have obtained notoriously inconsistent results, except when maternal condition is measured around conception. Several mechanisms for sex ratio adjustment have been proposed. Here, we test the hypothesis that glucose concentrations around conception influence sex ratios. The change in glucose levels resulted in a change in sex ratios, with more daughters being born to females with experimentally lowered glucose, and with the change in glucose levels being more predictive than the glucose levels per se. We provide evidence for a mechanism, which, in tandem with other mechanisms, could explain observed sex ratio variation in mammals.

Accurate recapture identification for genetic mark-recapture studies with error-tolerant likelihood-based match calling and sample clustering.

Error-tolerant likelihood-based match calling presents a promising technique to accurately identify recapture events in genetic mark-recapture studies by combining probabilities of latent genotypes and probabilities of observed genotypes, which may contain genotyping errors. Combined with clustering algorithms to group samples into sets of recaptures based upon pairwise match calls, these tools can be used to reconstruct accurate capture histories for mark-recapture modelling. Here, we assess the performance of a recently introduced error-tolerant likelihood-based match-calling model and sample clustering algorithm for genetic mark-recapture studies. We assessed both biallelic (i.e. single nucleotide polymorphisms; SNP) and multiallelic (i.e. microsatellite; MSAT) markers using a combination of simulation analyses and case study data on Pacific walrus (Odobenus rosmarus divergens) and fishers (Pekania pennanti). A novel two-stage clustering approach is demonstrated for genetic mark-recapture applications. First, repeat captures within a sampling occasion are identified. Subsequently, recaptures across sampling occasions are identified. The likelihood-based matching protocol performed well in simulation trials, demonstrating utility for use in a wide range of genetic mark-recapture studies. Moderately sized SNP (64+) and MSAT (10-15) panels produced accurate match calls for recaptures and accurate non-match calls for samples from closely related individuals in the face of low to moderate genotyping error. Furthermore, matching performance remained stable or increased as the number of genetic markers increased, genotyping error notwithstanding.