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An analysis of hatching success in the great reed warbler Acrocephalus arundinaceus

Author:
  • Jonas Knape
  • Martin Sköld
  • Niclas Jonzén
  • Mikael Åkesson
  • Staffan Bensch
  • Bengt Hansson
  • Dennis Hasselquist
Publishing year: 2008
Language: English
Pages: 430-438
Publication/Series: Oikos
Volume: 117
Issue: 3
Document type: Journal article
Publisher: Wiley-Blackwell

Abstract english

Hatching success is a potentially important fitness component for avian species. Previous studies of hatching success in natural populations have primarily focused on effects of inbreeding but a general understanding of variation in hatching success is lacking. We analyse data on hatching success in a population of great reed warblers Acrocephalus arundinaceus in Lake Kvismaren in south central Sweden. The effects of a range of covariates, including three measures of inbreeding as well as effects of classifications in the data (such as identities of individuals), on hatching success are analysed simultaneously. This is done by means of fitting Bayesian binomial mixed models using Markov chain Monte Carlo methods. Using random effects for each individual parent we check for unexplained variation in hatching success among male and female individuals and compare it to effects of covariates such as degree of inbreeding. Model selection showed that there was a significant amount of unexplained variation in hatching probability between females. This was manifested by a few females laying eggs with a substantially lower hatching success than the majority of the females. The deviations were of the same order of magnitude as the significant effect of parent relatedness on hatching success. Whereas the negative effect of parent relatedness on hatchability is an expression of inbreeding, the female individual effect is not due to inbreeding and could reflect maternal effects, that females differ in fertilisation and/or incubation ability, or an over representation of genetic components from the female acting on the early developing embryo.

Keywords

  • Biological Sciences

Other

Published
  • Molecular Ecology and Evolution Lab
  • ISSN: 1600-0706
Dennis Hasselquist
E-mail: dennis [dot] hasselquist [at] biol [dot] lu [dot] se

Professor

MEMEG

+46 46 222 37 08

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