PATERNAL CONDITION DRIVES PROGENY SEX-RATIO BIAS IN A LIZARD THAT LACKS PARENTAL CARE: PATERNAL CONDITION AND PROGENY SEX RATIO

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Abstract

Sex-allocation theory predicts that females in good condition should preferentially produce offspring of the sex that benefits the most from an increase in maternal investment. However, it is generally assumed that the condition of the sire has little effect on progeny sex ratio, particularly in species that lack parental care. We used a controlled breeding experiment and molecular paternity analyses to examine the effects of both maternal and paternal condition on progeny sex ratio and progeny fitness in the brown anole (Anolis sagrei), a polygynous lizard that lacks parental care. Contrary to the predictions of sex-allocation theory, we found no relationship between maternal condition and progeny sex ratio. By contrast, progeny sex ratio shifted dramatically from female-biased to male-biased as paternal condition increased. This pattern was driven entirely by an increase in the production of sons as paternal condition improved. Despite strong natural selection favoring large size and high condition in both sons and daughters, we found no evidence that progeny survival was related to paternal condition. Our results emphasize the importance of considering the paternal phenotype in studies of sex allocation and highlight the need for further research into the pathways that link paternal condition to progeny fitness. © 2010 The Author(s). Evolution© 2010 The Society for the Study of Evolution.

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Statistical confidence for likelihood-based paternity inference in natural populations.

T. C. Marshall, J Slate, L. E. B. Kruuk … (1998)

Paternity inference using highly polymorphic codominant markers is becoming common in the study of natural populations. However, multiple males are often found to be genetically compatible with each offspring tested, even when the probability of excluding an unrelated male is high. While various methods exist for evaluating the likelihood of paternity of each nonexcluded male, interpreting these likelihoods has hitherto been difficult, and no method takes account of the incomplete sampling and error-prone genetic data typical of large-scale studies of natural systems. We derive likelihood ratios for paternity inference with codominant markers taking account of typing error, and define a statistic delta for resolving paternity. Using allele frequencies from the study population in question, a simulation program generates criteria for delta that permit assignment of paternity to the most likely male with a known level of statistical confidence. The simulation takes account of the number of candidate males, the proportion of males that are sampled and gaps and errors in genetic data. We explore the potentially confounding effect of relatives and show that the method is robust to their presence under commonly encountered conditions. The method is demonstrated using genetic data from the intensively studied red deer (Cervus elaphus) population on the island of Rum, Scotland. The Windows-based computer program, CERVUS, described in this study is available from the authors. CERVUS can be used to calculate allele frequencies, run simulations and perform parentage analysis using data from all types of codominant markers.