Sexual dimorphism, survival and dispersal in red deer

  • E. A. Catchpole
  • Y. Fan
  • B. J. T. Morgan
  • T. H. Clutton-Brock
  • T. Coulson
Editor’s Invited Article

DOI: 10.1198/1085711043172

Cite this article as:
Catchpole, E.A., Fan, Y., Morgan, B.J.T. et al. JABES (2004) 9: 1. doi:10.1198/1085711043172
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Abstract

A detailed and extensive mark-recapture-recovery study of red deer on the island of Rum forms the basis of the modeling of this article. We analyze male and female deer separately, and report results for both in this article, but use the female data to demonstrate our modeling approach. We provide a model-selection procedure that allows us to describe the survival by a combination of age-classes, with common survival within each class, and senility, which is modeled continuously as a parametric function of age. Dispersal out of the study area is modeled separately. Survival and dispersal probabilities are examined for the possible influence of both environmental and individual covariates, including a range of alternative measures of population density. The resulting model is succinct and biologically realistic. We compare and contrast survival rates of male and female deer of different ages and compare the factors that affect their survival. We demonstrate large differences in the rate of senescence between males and females even though their senescence begins at the same age. The differences between the sexes suggest that, in population modeling of sexually size-dimorphic species, it is important to identify sex-specific survival functions.

Key Words

Age classes Cervuselaphus Emigration Logisticregression Mark-recapture Mark-recovery Maximum likelihood Senility Sex-specific survival Size dimorphism 

Copyright information

© International Biometric Society 2004

Authors and Affiliations

  • E. A. Catchpole
    • 1
  • Y. Fan
    • 2
  • B. J. T. Morgan
    • 3
  • T. H. Clutton-Brock
    • 4
  • T. Coulson
    • 5
  1. 1.School of Physical, Environmental and Mathematical SciencesUniversity of New South Wales at the Australian Defence Force AcademyCanberraAustralia
  2. 2.School of MathematicsUniversity of New South WalesSydneyAustralia
  3. 3.Institute of Mathematics and StatisticsUniversity of Kent, Canterbury, KentEngland
  4. 4.Department of ZoologyUniversity of CambridgeCambridgeEngland
  5. 5.Department of Biological SciencesImperial College, Silwood Park, AscotBerkshireEngland

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