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Journal of Ornithology

, Volume 152, Supplement 2, pp 539–554 | Cite as

Estimation and comparison of heritability and parent–offspring resemblance in dispersal probability from capture–recapture data using different methods: the Collared Flycatcher as a case study

  • Blandine DoligezEmail author
  • Grégory Daniel
  • Patrick Warin
  • Tomas Pärt
  • Lars Gustafsson
  • Denis Réale
Original Article

Abstract

Understanding the evolution of a trait requires analysing its genetic basis. Many studies have therefore estimated heritability values of different traits in wild populations using quantitative genetic approaches on capture–recapture data of individuals with known parentage. However, these models assume perfect individual detection probability, a hidden hypothesis that is rarely met in natural populations. To what extent ignoring imperfect detection may bias heritability estimates in wild populations needs specific investigation. We give a first insight into this question using dispersal probability in a patchy population of Collared Flycatchers Ficedula albicollis as an example. We estimate and compare heritability and parent–offspring resemblance in dispersal obtained from (1) quantitative genetic approaches (“classical” parent–offspring regressions and more recent animal models) and (2) multi-state capture–recapture models accounting for individual detection probability. Unfortunately, current capture–recapture models do not provide heritability estimates, preventing a full comparison of results between models at this stage. However, in the study population, detection probability may be expected to be lower for dispersing compared to philopatric individuals because of lower mating/breeding success and/or higher temporary emigration, making the use of capture–recapture models particularly relevant. We show significant parent–offspring resemblance and heritable component of between-patch dispersal probability in this population. Accounting for imperfect detection does however not seem to influence the observed pattern of parent–offspring resemblance in dispersal probability, although detection probability is both sensibly lower than 1 and heterogeneous among individuals according to dispersal status. We discuss the problems encountered, the information that can be derived from, and the constraints linked to, each method. To obtain unbiased heritability estimates, combining quantitative genetic and capture–recapture models is needed, which should be one of the main developments of capture–recapture models in the near future.

Keywords

Capture–recapture models Family effects Individual detection probability Mixed models Quantitative genetics 

Notes

Acknowledgments

We thank O. Gimenez, C. Bonenfant, A. Viallefont, R. Pradel, R. Choquet and J.-F. Le Galliard for technical help with analyses and comments on the study. We also thank the many researchers, students and field assistants involved in the long-term monitoring of the Collared Flycatcher population on Gotland, and the landowners and inhabitants of Gotland for allowing us to work on their properties. This study has been financially supported by a International Scientific Cooperation Programme from the French National Centre for Scientific Research (CNRS, PICS no 3054 to B.D.), a research grant from the National Research Agency (ANR-06-JCJC-0082 to B.D.), and research grants from the Swedish Research Council (VR to T.P. and L.G.). The population monitoring complies with Swedish law.

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Copyright information

© Dt. Ornithologen-Gesellschaft e.V. 2011

Authors and Affiliations

  • Blandine Doligez
    • 1
    Email author
  • Grégory Daniel
    • 1
  • Patrick Warin
    • 2
    • 3
  • Tomas Pärt
    • 4
  • Lars Gustafsson
    • 5
  • Denis Réale
    • 6
  1. 1.CNRS; Université de Lyon, 69000 Lyon; Université Lyon 1, France. Department of Biometry and Evolutionary Biology, CNRS UMR 5558, Bâtiment Gregor MendelVilleurbanne cedexFrance
  2. 2.Commissariat à l’Energie Atomique (CEA), INAC, SP2M, NM, UMR-E 9002GrenobleFrance
  3. 3.Université Joseph Fourier, SP2M, UMR-E 9002GrenobleFrance
  4. 4.Department of EcologySwedish University of Agricultural SciencesUppsalaSweden
  5. 5.Department of Ecology and Genetics/Animal Ecology, Evolutionary Biology CentreUniversity of UppsalaUppsalaSweden
  6. 6.Department of Biological SciencesUniversité du Québec à MontréalMontréalCanada

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