Individual differences in male reproductive success drive genetic drift and natural selection, altering genetic variation and phenotypic trait distributions in future generations. Therefore, identifying the determinants of reproductive success is important for understanding the ecology and evolution of plants. Here, based on the spatially explicit mating model (the neighborhood model), we develop a hierarchical probability model that links co-dominant genotypes of offspring and candidate parents with phenotypic determinants of male reproductive success. The model accounts for pollen dispersal, genotyping errors as well as individual variation in selfing, pollen immigration, and differentiation of immigrant pollen pools. Unlike the classic neighborhood model approach, our approach is specially designed to account for excessive variation (overdispersion) in male fecundity. We implemented a Bayesian estimation method (the Windows computer program available at: https://www.ukw.edu.pl/pracownicy/plik/igor_chybicki/1806/) that, among others, allows for selecting phenotypic variables important for male fecundity and assessing the fraction of variance in fecundity (R2 ) explained by selected variables. Simulations showed that our method outperforms both the classic neighborhood model and the two-step approach, where fecundities and the effects of phenotypic variables are estimated separately. The analysis of two data examples showed that in wind-pollinated trees, male fecundity depends on both the amount of produced pollen and the ability to pollen spread. However, despite that the tree size was positively correlated with male fecundity, it explained only a fraction of the total variance in fecundity, indicating the presence of additional factors. Finally, case studies highlighted the importance of accounting for pollen dispersal in the estimation of fecundity determinants.
Keywords: estimation; male fecundity; mating patterns; plants; pollen dispersal; regression.
© 2020 John Wiley & Sons Ltd.