Advertisement

Journal of Ornithology

, Volume 152, Supplement 2, pp 457–467 | Cite as

Estimating dispersal, recruitment and survival in a biennially breeding species, the Wandering Albatross

  • Gilles Gauthier
  • Emmanuel Milot
  • Henri Weimerskirch
EURING Proceedings

Abstract

The study of dispersal or recruitment in long-lived birds using capture–recapture methods is challenging because temporary emigration is often a source of heterogeneity in detection probabilities. To deal with this problem, we introduced unobservable states in the multistate, spatial recruitment model of Lebreton et al. (Oikos 101:253–264, 2003) to study dispersal, recruitment and survival in the Wandering Albatross (Diomedea exulans), a species with a biennial reproduction (individuals skip breeding following a successful reproduction). We highlight some of the limitations and challenges encountered in using this approach. Our dataset came from a 36-year capture–recapture study conducted at three colonies of the Crozet archipelago. The model had five reproductive stages: pre-breeders, successful breeders, failed breeders, and birds in the year after a successful or a failed breeding attempt, which are unobservable. In adults, movements between colonies (i.e. breeding dispersal) were nested within reproductive stages. Several models with different constraints on survival equally fitted the data but had some rank deficiencies (i.e. non-identifiable parameters). Survival estimates were most biologically realistic (from 0.91 to 0.95) when survival was set equal between observable/unobservable states but free to vary between successful/failed breeders and among colonies. Age-specific recruitment probabilities peaked at 9–10 years and appeared well estimated despite limitations in setting the age of constant recruitment probability. Modelling natal dispersal and recruitment required a simplification of the structure of the model due to computer limitations. When applying the complete and reduced versions of the model to the same dataset, we found that survival was well estimated in both cases. Some transition probability estimates were also similar, but transitions from unobservable to observable states were poorly estimated in the simplified version. We conclude that the simplified version of the model should be limited to the estimation of natal dispersal and that the model with a full structure should be used to estimate breeding dispersal.

Keywords

Dispersal Philopatry Recruitment Multistate model Unobservable state 

Notes

Acknowledgments

This long-term project was funded by the Terres Australes et Antarctiques Françaises and the Institut Polaire (IPEV, Program #109) and complied with French laws. We thank Dominique Besson for data managment, all the field workers involved in the demographic study on Crozet, and Rémi Choquet, Christophe Barbraud, Andy Royle, Charles Francis and Michael Schaub for their comments on this manuscript. The writing of this paper was supported by a grant from the Natural Sciences and Engineering Research Council of Canada and Université Laval.

References

  1. Barbraud C, Weimerskirch H (2010) Estimating survival and reproduction in a quasi biennially breeding seabird with uncertain and unobservable states. J Ornithol (in this issue)Google Scholar
  2. Cam E, Oro D, Pradel R, Jimenez J (2004) Assessment of hypotheses about dispersal in a long-lived seabird using multistate capture–recapture models. J Anim Ecol 73:723–736CrossRefGoogle Scholar
  3. Catchpole EA, Morgan BJT (1997) Detecting parameter redundancy. Biometrika 84:187–196CrossRefGoogle Scholar
  4. Choquet R, Reboulet AM, Pradel R, Gimenez O, Lebreton JD (2004) M-SURGE: new software specifically designed for multistate capture-recapture models. Anim Biodivers Conserv 27:207–215Google Scholar
  5. Choquet R, Reboulet AM, Pradel R, Gimenez O, Lebreton JD (2005) M-SURGE 1-8 user’s manual. CEFE, Montpellier, France. (http://www.cefe.cnrs.fr/BIOM/En/softwares.htm)
  6. Choquet R, Lebreton JD, Gimenez O, Reboulet AM, Pradel R (2009a) U-CARE: utilities for performing goodness of fit tests and manipulating CApture-REcapture data. Ecography 32:1071–1074CrossRefGoogle Scholar
  7. Choquet R, Rouan L, Pradel R (2009b) Program E-SURGE: a software application for fitting multievent models. In: Thomson DL, Cooch EG, Conroy MJ (eds) Modeling demographic processes in marked populations, Springer Series: Environmental and Ecological Statistics, vol 3, pp 845–865Google Scholar
  8. Clobert J, Danchin E, Dhondt AA, Nichols JD (2001) Dispersal. Oxford University Press, OxfordGoogle Scholar
  9. Converse SJ, Kendall WL, Doherty PF, Ryan PG (2009) Multistate models for estimation of survival and reproduction in the grey-headed albatross (Thalassarche chrysostoma). Auk 126:77–88CrossRefGoogle Scholar
  10. Crespin L, Harris MP, Lebreton JD, Frederiksen M, Wanless S (2006) Recruitment to a seabird population depends on environmental factors and on population size. J Anim Ecol 75:228–238PubMedCrossRefGoogle Scholar
  11. Fujiwara M, Caswell H (2002) A general approach to temporary emigration in mark-recapture analysis. Ecology 83:3266–3275Google Scholar
  12. Gauthier G, Milot E, Weimerskirch H (2010) Small-scale dispersal and survival in a long-lived seabird, the wandering albatross. J Anim Ecol 79:879–887Google Scholar
  13. Gimenez O, Choquet R, Lebreton JD (2003) Parameter redundancy in multistate capture-recapture models. Biom J 6:704–722CrossRefGoogle Scholar
  14. Henaux V, Bregnballe T, Lebreton JD (2007) Dispersal and recruitment during population growth in a colonial bird, the great cormorant. J Avian Biol 38:44–57CrossRefGoogle Scholar
  15. Hestbeck JB, Nichols JD, Malecki RA (1991) Estimates of movement and site fidelity using mark-resight data of wintering Canada geese. Ecology 72:523–533CrossRefGoogle Scholar
  16. Hunter C, Caswell H (2009) Rank and redundancy of multistate mark-recapture models for seabird populations with unobservable states. In: Thomson DL, Cooch EG, Conroy MJ (eds) Modeling demographic processes in marked populations, Springer Series: Environmental and Ecological Statistics, vol 3, pp 883–915Google Scholar
  17. Inchausti P, Weimerskirch H (2002) Dispersal and metapopulation dynamics of an oceanic seabird, the wandering albatross, and its consequences for its response to long-line fisheries. J Anim Ecol 71:765–770CrossRefGoogle Scholar
  18. Jenouvrier S, Tavecchia G, Thibault JC, Choquet R, Bretagnolle V (2008) Recruitment processes in long-lived species with delayed maturity: estimating key demographic parameters. Oikos 117:620–628CrossRefGoogle Scholar
  19. Kendall WL, Nichols JD (2002) Estimating state-transition probabilities for unobservable states using capture-recapture/resighting data. Ecology 83:3276–3284Google Scholar
  20. Lebreton JD, Pradel R (2002) Multistate recapture models: modelling incomplete individual histories. J Appl Stat 29:353–369CrossRefGoogle Scholar
  21. Lebreton JD, Hines JE, Pradel R, Nichols JD, Spendelow JA (2003) Estimation by capture-recapture of recruitment and dispersal over several sites. Oikos 101:253–264CrossRefGoogle Scholar
  22. Milot E (2009) Dispersion et génétique chez un prédateur marin longévif, l’albatros hurleur. PhD thesis, Université Laval, Quebec, CanadaGoogle Scholar
  23. Oro D, Pradel R (2000) Determinants of local recruitment in a growing colony of Audouin’s gull. J Anim Ecol 69:119–132CrossRefGoogle Scholar
  24. Pradel R (2005) Multievent: an extension of multistate capture-recapture models to uncertain states. Biometrics 61:442–447PubMedCrossRefGoogle Scholar
  25. Pradel R, Wintrebert CMA, Gimenez O (2003) A proposal for a goodness-of-fit test to the Arnason-Schwarz multisite capture-recapture model. Biometrics 59:43–53PubMedCrossRefGoogle Scholar
  26. Reid JM, Bignal EM, Bignal S, McCracken DI, Monaghan P (2003) Age-specific reproductive performance in red-billed choughs Pyrrhocorax pyrrhocorax: patterns and processes in a natural population. J Anim Ecol 72:765–776CrossRefGoogle Scholar
  27. Saether BE, Bakke O (2000) Avian life history variation and contribution of demographic traits to the population growth rate. Ecology 81:642–653Google Scholar
  28. Saether BE, Engen S, Moller AP, Weimerskirch H, Visser ME, Fiedler W, Matthysen E, Lambrechts MM, Badyaev A, Becker PH, Brommer JE, Bukacinski D, Bukacinska M, Christensen H, Dickinson J, duFeu C, Gehlbach FR, Heg D, Hotker H, Merila J, Nielsen JT, Rendell W, Robertson RJ, Thomson DL, Torok J, vanHecke P (2004) Life-history variation predicts the effects of demographic stochasticity on avian population dynamics. Am Nat 164:793–802CrossRefGoogle Scholar
  29. Schaub M, Gimenez O, Schmidt BR, Pradel R (2004) Estimating survival and temporary emigration in the multistate capture-recapture framework. Ecology 85:2107–2113CrossRefGoogle Scholar
  30. Tavecchia G, Pradel R, Boy V, Johnson AR, Cezilly F (2001) Sex- and age-related variation in survival and cost of first reproduction in greater flamingos. Ecology 82:165–174CrossRefGoogle Scholar
  31. Viallefont A, Cooke F, Lebreton JD (1995) Age-specific costs of first-time breeding. Auk 112:67–76Google Scholar
  32. Weimerskirch H, Jouventin P (1987) Population of the wandering albatross, Diomedea exulans, of the Crozet Islands: causes and consequences of the population decline. Oikos 49:315–322CrossRefGoogle Scholar
  33. Weimerskirch H, Brothers N, Jouventin P (1997) Population dynamics of wandering albatross Diomedea exulans and Amsterdam albatross D. amsterdamensis in the Indian Ocean and their relationships with long-line fisheries: conservation implications. Biol Conserv 79:257–270CrossRefGoogle Scholar
  34. Weimerskirch H, Lallemand J, Martin J (2005) Population sex ratio variation in a monogamous long-lived bird, the wandering albatross. J Anim Ecol 74:285–291CrossRefGoogle Scholar

Copyright information

© Dt. Ornithologen-Gesellschaft e.V. 2010

Authors and Affiliations

  • Gilles Gauthier
    • 1
    • 2
  • Emmanuel Milot
    • 1
  • Henri Weimerskirch
    • 3
  1. 1.Département de BiologieUniversité LavalQuébec CityCanada
  2. 2.Centre d’Études NordiquesUniversité LavalQuébec CityCanada
  3. 3.Centre d’Études Biologiques de ChizéCNRSVilliers en BoisFrance

Personalised recommendations