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Data from: Multiple paternity and number of offspring in mammals


Dobson, F. Stephen et al. (2018), Data from: Multiple paternity and number of offspring in mammals, Dryad, Dataset,


Many cooperative social attributes are being linked to characteristics of mating systems, particularly to the rate of multiple paternity that typifies a population. Under the logic that greater offspring production by females should engender greater competition among males to mate with females, it is predicted that multiple paternity should increase with litter sizes. We tested the predicted positive association of multiple paternity and litter size with a meta-analysis of 59 species of mammals. The probability of multiple paternity and mean litter size were positively correlated, but not significantly (Zr = 0.202). Also, the mean number of sires of litters increased with mean litter size, but not significantly (Zr = 0.235). We developed a combinatorial formula for the influence of number of male mates and litter size on the probability of multiple paternity. We used Bayesian Markov chain Monte Carlo simulations to generate an expectation for the form of the relationship between the probability of multiple paternity and mean litter size. Under the assumption of random samplings of numbers of mates, the expected association of the probability of multiple paternity and mean litter sizes among species was positive, curvilinear, and relatively high. However, the empirical probabilities of multiple paternities were much less than expected, suggesting that behavioral factors (such as mating-associated behaviors) or ecological characteristics (such as population density) likely limit the number of male mates for reproductive females. The probability of multiple paternity in a population is an estimate of mating patterns that does not closely reflect the number of sires of individual litters. We suggest use of the estimated probability of mating success for males as an alternative measure of their contribution to the mating system.

Usage Notes


National Science Foundation, Award: DMS-1343651