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


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 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Barry, S. C., Brooks, S. P., Catchpole, E. A., and Morgan, B. J. T. (2003), “The Analysis of Ring-Recovery Data Using Random Effects,” Biometrics, 59, 54–65.CrossRefMathSciNetGoogle Scholar
  2. Burnham, K. P. (1993), “A Theory for Combined Analysis of Ring-Recovery and Recapture Data,” in Marked Individuals in the Study of Bird Populations, eds. J.-D. Lebreton and P.M. North, Basel: Birkhauser Verlag, pp. 199–213.Google Scholar
  3. Catchpole, E. A., Morgan, B. J. T., Coulson, T. N., Freeman, S. N., and Albon, S. D. (2000), “Factors Influencing Soay Sheep Survival,” Applied Statistics, 49, 453–472.MathSciNetGoogle Scholar
  4. Caughley, G. (1966), “Mortality Patterns in Mammals,” Ecology, 47, 906–918.CrossRefGoogle Scholar
  5. Clutton-Brock, T. H. (1988), Reproductive Success: Studies of Individual Variation in Contrasting Breeding Systems; Chicago: Chicago University Press.Google Scholar
  6. Clutton-Brock, T. H., and Coulson, T. N. (2002), “Ungulate Population Dynamics: the Devil is in the Detail,” Philosophical Transactions of the Royal Society, 357, 1299–1306.CrossRefGoogle Scholar
  7. Clutton-Brock, T. H., Coulson, T., Milner-Gulland, E. J., Armstrong, H. M. and Thomson, D. (2002), “Sex Differences in Emigration and Mortality Affect Optimal Management of Deer Populations,” Nature, 415, 633–637.CrossRefGoogle Scholar
  8. Clutton-Brock, T. H., Guinness, F. E., and Albon, S. D. (1982), Red Deer: Behaviour and Ecology of Two Sexes, Chicago: University of Chicago Press.Google Scholar
  9. Conradt, L., Clutton-Brock, T. H., and Thomson, D. (1999), “Habitat Segregation in Ungulates: Are Males Forced into Suboptimal Foraging Habitats Through Indirect Competition by Females?,” Oecologia, 119, 367–377.CrossRefGoogle Scholar
  10. Conradt, L., Gordon, I. J., Clutton-Brock, T. H., Thomson, D., and Guinness, F. E. (2001), “Could the Indirect Competition Hypothesis Explain Inter-sexual Site Segregation in Red Deer (Cervus elaphus L.)?” Journal of Zoology, 254, 185–193.CrossRefGoogle Scholar
  11. Coulson, T., Guinness, F., Pemberton, J. Clutton-Brock, T. (in press), “The Demographic Consequences of Releasing a Population of Red Deer From Culling,” Ecology.Google Scholar
  12. Fan, Y., Morgan, B. J. T., Catchpole, E. A., and Coulson, T. N. (2003), “Modelling the Survival and Dispersal of Red Deer Using Mark-Recapture-Recovery Data,” Technical Report UKC/1MS/03/19, University of Kent, Canterbury, England.Google Scholar
  13. Festa-Bianchet, M., Gaillard, J.-M., and Cote, S. D. (2003), “Variable Age Structure and Apparent Density Dependence in Survival of Adult Ungulates,” Journal of Animal Ecology, 72, 640–649.CrossRefGoogle Scholar
  14. Gaillard, J.-M., Allaine, D., Pontier, D., Yoccoz, N. G., and Promislow, D. E. L. (1994), “Sensecence in Natural Populations of Mammals: A Reanalysis,” Evolution, 48, 509–516.CrossRefGoogle Scholar
  15. Hall, A. J., McConnell, B. J., and Barker, R. J. (2001), “Factors Affecting First-Year Survival in Grey Seals and Their Implications for Life History Strategy,” Journal of Animal Ecology, 70, 138–149.CrossRefGoogle Scholar
  16. Jorgenson, J. T., Festa-Bianchet, M., Lucherini, M., and Wishart, W. D. (1997), “Effects of Age, Sex, Disease and Density on Survival of Bighorn Sheep,” Ecology, 78, 1019–1032.Google Scholar
  17. Loison, A. (1995), “Approchesintra-et inter-spécifiques de la dynamique des populations: l’exemple du chamois,” PhD thesis, Université Claude-Bernard, Lyon, France.Google Scholar
  18. Loison, A., Festa-Bianchet, M., Gaillard, J.-M., Jorgenson, J. T., and Jullien, J.-M. (1999), “Age-Specific Survival in Five Populations of Ungulates: Evidence of Senescence,” Ecology, 80, 2539–2554.Google Scholar
  19. Metcalfe, N. B., and Monaghan, P. (2001), “Compensation for a Bad Start: Grow Now, Pay Later?,” Trends in Ecology and Evolution, 16, 254–260.CrossRefGoogle Scholar
  20. Mysterud, A., Coulson, T., and Stenseth, N. C. (2002), “The Role of Males in the Dynamics of Ungulate Populations,” Journal of Animal Ecology, 71, 907–915.CrossRefGoogle Scholar
  21. Nasution, M. D., Brownie, C., Pollock, K. H., and Powell, R. A. (2004), “The Effect on Model Identifiability of Allowing Different Relocation Rates for Live and Dead Animals in the Combined Analysis of Telemetry and Recapture Data,” Journal of Agricultural, Biological, and Environmental Statistics, 9, 27–41.CrossRefGoogle Scholar
  22. Nichols, J. D., Hines, J. E., and Blums, P. (1997), “Tests for Senescent Decline in Annual Survival Probabilities of Common Pochards, Aythya ferina,” Ecology, 78, 1009–1018.Google Scholar
  23. Pollock, K. H., Bunck, C. M., Winterstein, S. R., and Chen, C. L. (1995), “A Capture-Recapture Survival Analysis Model for Radio-Tagged Animals,” Journal of Applied Statistics, 22, 661–672.CrossRefGoogle Scholar
  24. Post, E., and Stenseth, N. C. (1999), “Climatic Variability, Plant Phenology and Northern Ungulates,” Ecology, 80, 1322–1339.CrossRefGoogle Scholar
  25. Seber, G. A. F. (1982), The Estimation of Animal Abundance and Related Parameters (2nd ed.) London: Griffin.Google Scholar
  26. Sibly, R. M., Collett, D., Promislow, D. E. L., Peacock, D. J., and Harvey, P. H. (1997), “Mortality Rates of Mammals,” Journal of Zoology, 243, 1–12.CrossRefGoogle Scholar
  27. Siler, W. (1979), “A Competing-Risk Model for Animal Mortality,” Ecology, 60, 750–757.CrossRefGoogle Scholar
  28. White, G. C., and Burnham, K. P. (1999), “Program MARK: Survival Estimation from Populations of Marked Animals,” Bird Study, 46 (suppl), 120–139.CrossRefGoogle Scholar
  29. Wilby, R. L., O’Hare, G., and Barnsley, N. (1997), “The North Atlantic Oscillation and British Isles Climate Variability, 1865–1996,” Weather, 52, 266–276.Google Scholar

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

Personalised recommendations