IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v212y2008i3p528-535.html
   My bibliography  Save this article

Effects of asymptotic and maximum age estimates on calculated rates of population change

Author

Listed:
  • Skalski, John R.
  • Millspaugh, Joshua J.
  • Ryding, Kristen E.

Abstract

The finite rate of population increase (λ) is a fundamental demographic parameter used to assess the dynamics of wild animal populations. Although, abundance data are commonly used, λ may be estimated by survival and fecundity rates using the Lotka equation or Leslie projection matrices. Implicit in the dimensionality of the Leslie matrix and its formulation is an assumption about maximum attainable age. The purpose of this paper is to discuss the difficulties of accurately calculating maximum life expectancy and the implications of alternative values on estimated rates of population change. We also present a simplified expression for the Lotka equation that can be used to estimate λ and its variance under asymptotic survival assumptions. Our evaluation of estimating maximum life expectancy revealed that a much larger sample size is required for species with high (S≥0.80) versus low annual survival rates (S≤0.30). Uncertainty in maximum age can also lead to sampling error in λˆ and possible bias. Therefore, investigators are encouraged to carefully consider sources used to estimate maximum age expectancy while recognizing that life expectancy is population specific. Specifying the estimation equation used, and the value of maximum age assumed will improve the statistical and biological inferences concerning the rates of population change. Ironically, the asymptotic estimate of λ (i.e., w→∞) will have a smaller sampling error than estimates of λ when age expectancy is unknown. The asymptotic value of λ, when clearly identified, may therefore provide a useful bound, unencumbered by arbitrary and uncertain estimates of maximum life expectancy.

Suggested Citation

  • Skalski, John R. & Millspaugh, Joshua J. & Ryding, Kristen E., 2008. "Effects of asymptotic and maximum age estimates on calculated rates of population change," Ecological Modelling, Elsevier, vol. 212(3), pages 528-535.
  • Handle: RePEc:eee:ecomod:v:212:y:2008:i:3:p:528-535
    DOI: 10.1016/j.ecolmodel.2007.11.012
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380007006047
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolmodel.2007.11.012?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Alexander Shapiro & Jos Berge, 2002. "Statistical inference of minimum rank factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 67(1), pages 79-94, March.
    2. Sakanoue, Seiichi, 2007. "Extended logistic model for growth of single-species populations," Ecological Modelling, Elsevier, vol. 205(1), pages 159-168.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dillingham, Peter W., 2010. "Generation time and the maximum growth rate for populations with age-specific fecundities and unknown juvenile survival," Ecological Modelling, Elsevier, vol. 221(6), pages 895-899.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Anastasiou, Andreas, 2017. "Bounds for the normal approximation of the maximum likelihood estimator from m-dependent random variables," Statistics & Probability Letters, Elsevier, vol. 129(C), pages 171-181.
    2. Denter, Philipp & Sisak, Dana, 2015. "Do polls create momentum in political competition?," Journal of Public Economics, Elsevier, vol. 130(C), pages 1-14.
    3. Salgado Alfredo, 2018. "Incomplete Information and Costly Signaling in College Admissions," Working Papers 2018-23, Banco de México.
    4. Albrecht, James & Anderson, Axel & Vroman, Susan, 2010. "Search by committee," Journal of Economic Theory, Elsevier, vol. 145(4), pages 1386-1407, July.
    5. Blier-Wong, Christopher & Cossette, Hélène & Marceau, Etienne, 2023. "Risk aggregation with FGM copulas," Insurance: Mathematics and Economics, Elsevier, vol. 111(C), pages 102-120.
    6. Simon Bruhn & Thomas Grebel & Lionel Nesta, 2023. "The fallacy in productivity decomposition," Journal of Evolutionary Economics, Springer, vol. 33(3), pages 797-835, July.
    7. Wim J. van der Linden, 2019. "Lord’s Equity Theorem Revisited," Journal of Educational and Behavioral Statistics, , vol. 44(4), pages 415-430, August.
    8. Colomer, M. Àngels & Montori, Albert & García, Eder & Fondevilla, Cristian, 2014. "Using a bioinspired model to determine the extinction risk of Calotriton asper populations as a result of an increase in extreme rainfall in a scenario of climatic change," Ecological Modelling, Elsevier, vol. 281(C), pages 1-14.
    9. Simar, Léopold & Wilson, Paul, 2022. "Modern Tools for Evaluating the Performance of Health-Care Providers," LIDAM Discussion Papers ISBA 2022006, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    10. Baey, Charlotte & Didier, Anne & Lemaire, Sébastien & Maupas, Fabienne & Cournède, Paul-Henry, 2013. "Modelling the interindividual variability of organogenesis in sugar beet populations using a hierarchical segmented model," Ecological Modelling, Elsevier, vol. 263(C), pages 56-63.
    11. Tasche, Dirk, 2013. "Bayesian estimation of probabilities of default for low default portfolios," Journal of Risk Management in Financial Institutions, Henry Stewart Publications, vol. 6(3), pages 302-326, July.
    12. Diers, Dorothea & Linde, Marc & Hahn, Lukas, 2016. "Addendum to ‘The multi-year non-life insurance risk in the additive reserving model’ [Insurance Math. Econom. 52(3) (2013) 590–598]: Quantification of multi-year non-life insurance risk in chain ladde," Insurance: Mathematics and Economics, Elsevier, vol. 67(C), pages 187-199.
    13. Anastasiou, Andreas, 2017. "Bounds for the normal approximation of the maximum likelihood estimator from m -dependent random variables," LSE Research Online Documents on Economics 83635, London School of Economics and Political Science, LSE Library.
    14. Hirschberg, Joe & Lye, Jenny, 2017. "Inverting the indirect—The ellipse and the boomerang: Visualizing the confidence intervals of the structural coefficient from two-stage least squares," Journal of Econometrics, Elsevier, vol. 199(2), pages 173-183.
    15. Serguei Kaniovski & Alexander Zaigraev, 2018. "The probability of majority inversion in a two-stage voting system with three states," Theory and Decision, Springer, vol. 84(4), pages 525-546, June.
    16. Boland, John & Huang, Jing & Ridley, Barbara, 2013. "Decomposing global solar radiation into its direct and diffuse components," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 749-756.
    17. Packham, Natalie & Woebbeking, Fabian, 2021. "Correlation scenarios and correlation stress testing," IRTG 1792 Discussion Papers 2021-012, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    18. Guillermo Martínez-Flórez & Roger Tovar-Falón & Carlos Barrera-Causil, 2022. "Inflated Unit-Birnbaum-Saunders Distribution," Mathematics, MDPI, vol. 10(4), pages 1-14, February.
    19. Xyngis, Georgios, 2017. "Business-cycle variation in macroeconomic uncertainty and the cross-section of expected returns: Evidence for scale-dependent risks," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 43-65.
    20. Nair, Gopalan M. & Turlach, Berwin A., 2012. "The stochastic h-index," Journal of Informetrics, Elsevier, vol. 6(1), pages 80-87.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecomod:v:212:y:2008:i:3:p:528-535. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.