Genealogical analysis is a powerful tool for analysis of reproductive performance in both natural and captive populations, but assignment of paternity has always been a stumbling block for this sort of work. Statistical methods for determining paternity have undergone several phases of development, ranging from straightforward genetic exclusion to assignment of paternity based on genetic likelihood criteria. In the present study, we present a genetic likelihood-based iterative procedure for fractional allocation of paternity within a progeny pool and apply this method to a population of Chamaelirium luteum, a dioecious member of the Liliaceae. Results from this analysis clearly demonstrate that different males make unequal contributions to the overall progeny pool, with many males contributing essentially nothing to the next generation. Furthermore, the distribution of paternal success among males shows a highly significant departure from (Poisson) randomness. The results from the present analysis were compared with earlier results obtained from the same data set, using likelihood-based categorical paternity assignments. The general biological pattern revealed by the two analyses is the same, but the estimates of reproductive success are only modestly (though significantly) correlated. The iterative procedure makes more complete use of the data and generates a more sharply resolved distribution of male reproductive success.
|Original language||English (US)|
|Number of pages||10|
|State||Published - Jan 10 1994|
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