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Observation and Quantification of Mating Behavior in the Pinewood Nematode, Bursaphelenchus xylophilus
Published on: December 25, 2016
Reproductive skew in the polygynandrous acorn woodpecker
Joseph Haydock1, Walter D Koenig
1Department of Biology, Gonzaga University, 502 East Boone Avenue, Spokane, WA 99258, USA. haydock@gonzaga.edu
Abstract:
Reproductive skew models, which focus on the degree to which reproduction is shared equally (low skew) or monopolized by a single individual (high skew) within groups, have been heralded as providing a general unifying framework for understanding the factors determining social evolution. Here, we test the ability of optimal skew, or "transactional," models, which predict the level of skew necessary to promote stable associations of dominants and subordinates, rather than independent breeding, to predict reproductive partitioning in the acorn woodpecker (Melanerpes formicivorus). This species provides a key test case because only a few vertebrates exhibit polygynandry (multiple breeders of both sexes within a group). Contrary to the predictions of the models, joint-nesting females share reproduction more equitably than expected, apparently because egg destruction and the inability of females to defend their eggs from cobreeders eliminate any possibility for one female to control reproduction. For males, however, reproductive skew is high, with the most successful male siring over three times as many young as the next most successful male. Although this result is consistent with optimal skew models, other aspects of male behavior are not; in particular, the reproductively most successful male frequently switches between nests produced by the same set of cobreeders, and we were unable to detect any phenotypic correlate of success. These results are consistent with an alternative null model in which cobreeder males have equal chance of paternity, but paternity of offspring within broods is nonindependent as a consequence of female, rather than male, control.
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There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
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