European Journal of Wildlife Research

, Volume 54, Issue 1, pp 6–14

Accuracy and repeatability of moose (Alces alces) age as estimated from dental cement layers

  • Christer M. Rolandsen
  • Erling J. Solberg
  • Morten Heim
  • Frode Holmstrøm
  • May I. Solem
  • Bernt-Erik Sæther
Original Paper

Abstract

Optimal research and management of species with age structure often depends on estimates of age-specific population parameters, which in turn depends on reliable methods for age determination. By counting annuli in the cementum of incisor root tips from 51 known-age moose (Alces alces) between 1 and 12 years old, we examined the variation in accuracy and repeatability of age estimates provided by three research technicians with different experiences of aging moose. The most experienced technician estimated the moose age correctly in up to 90% of the cases, while the technician with no prior experience estimated age correctly in up to 73% of the cases. The medium-experienced technician achieved a lower accuracy (up to 53%), indicating that experience alone is not sufficient if the basic training or lack of routine checks against other colleagues or a known-age material are not undertaken. The percentage moose aged within ±1 year from correct age was significantly higher in all technicians (94–98%). After the generally high accuracy, we also found high repeatability (0.980–0.994) within technicians. We conclude that this method of age-determination provides reliable estimates that can be used by management and research to gain information about age-specific patterns in moose populations. However, to obtain estimates of high accuracy the technicians should be well trained, have gained the necessary experience, and most preferably, have access to a sample of teeth from known-age moose.

Keywords

Age estimation Alces alces Known-age Moose Tooth sections 

References

  1. Anon (2001) S-PLUS 6 for windows guide to statistics, Vol 1. Insightful Corporation, Seattle, WAGoogle Scholar
  2. Anon (2002) S-PLUS 6.1 for Windows, professional edition, release 1. Insightful Corporation, Seattle, WAGoogle Scholar
  3. Anon (2004) SPSS 13.0 for Windows, release 13.0. SPSSGoogle Scholar
  4. Azorit C, Analla M, Hervas J, Carrasco R, Muñoz-Cobo J (2002) Growth marks observation: preferential techniques and teeth for ageing of Spanish red deer (Cervus elaphus hispanicus). Anat Histol Embryol 31:303–307PubMedCrossRefGoogle Scholar
  5. Brokx PA (1972) Age determination of Venezuelan white-tailed deer. J Wildl Manage 36:1060–1067CrossRefGoogle Scholar
  6. Bubenik AB (1997) Evolution, taxonomy and morphophysiology. In: Franzmann AW, Schwartz CC (eds) Ecology and management of the North American moose. Wildlife Management Institute, Washington, DC, pp 77–123Google Scholar
  7. Burnham KP, Anderson DR (1998) Model selection and inference: a practical information-theoretic approach. Springer, Berlin Heidelberg New YorkGoogle Scholar
  8. Cederlund G, Kjellander P, Stålfelt F (1991) Age determination of roe deer by tooth wear and cementum layers—tests with known age material. Trans 20th Congress of the International Union Game Biology, Gödöllö, Hungary, August 21–26, pp 540–545Google Scholar
  9. Connolly GE, Dudziński ML, Longhurst WM (1969) An improved age-lens weight regression for black-tailed deer and mule deer. J Wildl Manage 33:701–704CrossRefGoogle Scholar
  10. Cook RL, Hart RV (1979) Ages assigned known-age Texas white-tailed deer: tooth wear versus cementum analysis. Proc Annu Conf Southeast Assoc Fish Wildl Agencies 33:195–201Google Scholar
  11. Crawley MJ (2002) Statistical computing: an introduction to data analysis using S-plus. Wiley & Sons, West Sussex, EnglandGoogle Scholar
  12. Dalton WJ, Francis GD (1988) The status of applied moose aging technology. Alces 24:69–77Google Scholar
  13. Erickson JA, Seliger WG (1969) Efficient sectioning of incisors for estimating ages of mule deer. J Wildl Manage 33:384–388CrossRefGoogle Scholar
  14. Fancy SG (1980) Preparation of mammalian teeth for age determination by cementum layers: a review. Wildl Soc Bull 8:242–247Google Scholar
  15. Festa-Bianchet M, Gaillard JM, Côté SD (2003) Variable age structure and apparent density dependence in survival of adult ungulates. J Anim Ecol 72:640–649CrossRefGoogle Scholar
  16. Gaillard JM, Festa-Bianchet M, Yoccoz NG (1998) Population dynamics of large herbivores: variable recruitment with constant adult survival. Trends Ecol Evol 13:58–63CrossRefGoogle Scholar
  17. Gasaway WC, Harkness DB, Rausch RA (1978) Accuracy of moose age determinations from incisor cementum layers. J Wildl Manage 42:558–563CrossRefGoogle Scholar
  18. Gilbert FF (1966) Aging white-tailed deer by annuli in the cementum of the first incisor. J Wildl Manage 30:200–202CrossRefGoogle Scholar
  19. Grue H, Jensen B (1979) Review of the formation of incremental lines in tooth cementum of terrestrial mammals. Dan Rev Game Biol 11:1–48Google Scholar
  20. Haagenrud H (1978) Layers in secondary dentine of incisors as age criteria in moose (Alces alces). J Mammal 59:857–858PubMedCrossRefGoogle Scholar
  21. Hamlin KL, Pac DF, Sime CA, DeSimone RM, Dusek GL (2000) Evaluating the accuracy of ages obtained by two methods for Montana ungulates. J Wildl Manage 64:441–449CrossRefGoogle Scholar
  22. Jacobson HA, Reiner RJ (1989) Estimating age of white-tailed deer: tooth wear versus cementum annuli. Proc Annu Conf Southeast Assoc Fish Wildl Agencies 43:286–291Google Scholar
  23. Keiss RE (1969) Comparison of eruption-wear patterns and cementum annuli as age criteria in elk. J Wildl Manage 33:175–180CrossRefGoogle Scholar
  24. Krebs CJ (1999) Ecological methodology. Addison-Wesley, New YorkGoogle Scholar
  25. Laws RM (1952) A new method of age determination for mammals. Nature 169:972–973PubMedCrossRefGoogle Scholar
  26. Lessells CM, Boag PT (1987) Unrepeatable repeatabilities: a common mistake. Auk 104:116–121Google Scholar
  27. Lockard GR (1972) Further studies of dental annuli for aging white-tailed deer. J Wildl Manage 36:46–55CrossRefGoogle Scholar
  28. Low WA, Cowan IMcT (1963) Age determination of deer by annular structure of dental cementum. J Wildl Manage 27:466–471CrossRefGoogle Scholar
  29. Markgren G (1964) Puberty, dentition and weight of yearling moose in a Swedish county. Viltrevy 2:409–416Google Scholar
  30. McCullough DR (1996) Failure of tooth cementum aging technique with reduced population density of deer. Wildl Soc Bull 24:722–724Google Scholar
  31. McCullough DR, Beier P (1986) Upper vs. lower molars for cementum annuli age determination of deer. J Wildl Manage 50:705–706CrossRefGoogle Scholar
  32. Mysterud A, Solberg EJ, Yoccoz NG (2005) Ageing and reproductive effort in male moose under variable levels of intrasexual competition. J Anim Ecol 74:742–754CrossRefGoogle Scholar
  33. Reimers E, Nordby Ø (1968) Relationship between age and tooth cementum layers in Norwegian reindeer. J Wildl Manage 32:957–961CrossRefGoogle Scholar
  34. Scheffer VB (1950) Growth layers on the teeth of pinnipedia as an indication of age. Science 112:309–311PubMedCrossRefGoogle Scholar
  35. Sergeant DE, Pimlott DH (1959) Age determination in moose from sectioned incisor teeth. J Wildl Manage 23:315–321CrossRefGoogle Scholar
  36. Solberg EJ, Sæther BE, Strand O, Loison A (1999) Dynamics of a harvested moose population in a variable environment. J Anim Ecol 68:186–204CrossRefGoogle Scholar
  37. Solberg EJ, Loison A, Gaillard JM, Heim M (2004) Lasting effects of conditions at birth on moose body mass. Ecography 27:677–687CrossRefGoogle Scholar
  38. Solberg EJ, Rolandsen C, Heim M, Grøtan V, Garel M, Sæther BE, Nilsen EB, Austrheim G, Herfindal I (2006) Moose in Norway—an analysis of material collected by moose hunters 1966–2004. NINA Rapport 125, 197 pp (In Norwegian, with English summary)Google Scholar
  39. Sæther BE (1997) Environmental stochasticity and population dynamics of large herbivores: a search for mechanisms. Trends Ecol Evol 12:143–149CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  • Christer M. Rolandsen
    • 1
  • Erling J. Solberg
    • 1
  • Morten Heim
    • 1
  • Frode Holmstrøm
    • 1
  • May I. Solem
    • 1
  • Bernt-Erik Sæther
    • 1
    • 2
  1. 1.Norwegian Institute for Nature ResearchTrondheimNorway
  2. 2.Department of BiologyNorwegian University of Science and TechnologyTrondheimNorway

Personalised recommendations