IDEAS home Printed from https://ideas.repec.org/a/bla/jorssc/v57y2008i5p609-632.html
   My bibliography  Save this article

Identifying and diagnosing population declines: a Bayesian assessment of lapwings in the UK

Author

Listed:
  • Ruth King
  • Stephen P. Brooks
  • Chiara Mazzetta
  • Stephen N. Freeman
  • Byron J. T. Morgan

Abstract

Summary. We combine data from separate ring recovery and survey studies to provide indices of estimated abundance for the UK lapwing Vanellus vanellus population. Using a descriptive state space model, we demonstrate the observed decline in population size in relation to directly interpretable parameters describing the demographic characteristics of the population. The Bayesian approach readily provides information that is directly relevant to the conservation of this important bird species. The method proposed extends previous work in this area in several ways. Restrictive normality assumptions that have traditionally been imposed are removed, in addition to the assumption of constant measurement error by using information relating to the index variability across time to account fully for this source of uncertainty within the model. We also provide model‐averaged inference to help to inform management policy and uses.

Suggested Citation

  • Ruth King & Stephen P. Brooks & Chiara Mazzetta & Stephen N. Freeman & Byron J. T. Morgan, 2008. "Identifying and diagnosing population declines: a Bayesian assessment of lapwings in the UK," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 57(5), pages 609-632, December.
    • Handle: RePEc:bla:jorssc:v:57:y:2008:i:5:p:609-632
    DOI: 10.1111/j.1467-9876.2008.00633.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1467-9876.2008.00633.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1467-9876.2008.00633.x?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
    ---><---

    References listed on IDEAS

    as
    1. R. King & S. P. Brooks, 2002. "Model Selection for Integrated Recovery/Recapture Data," Biometrics, The International Biometric Society, vol. 58(4), pages 841-851, December.
    2. S. P. Brooks & E. A. Catchpole & B. J. T. Morgan & S. C. Barry, 2000. "On the Bayesian Analysis of Ring-Recovery Data," Biometrics, The International Biometric Society, vol. 56(3), pages 951-956, September.
    3. P. Besbeas & S. N. Freeman & B. J. T. Morgan & E. A. Catchpole, 2002. "Integrating Mark–Recapture–Recovery and Census Data to Estimate Animal Abundance and Demographic Parameters," Biometrics, The International Biometric Society, vol. 58(3), pages 540-547, September.
    4. S. C. Barry & S. P. Brooks & E. A. Catchpole & B. J. T. Morgan, 2003. "The Analysis of Ring-Recovery Data Using Random Effects," Biometrics, The International Biometric Society, vol. 59(1), pages 54-65, March.
    5. Chiara Mazzetta & Steve Brooks & Stephen N. Freeman, 2007. "On Smoothing Trends in Population Index Modeling," Biometrics, The International Biometric Society, vol. 63(4), pages 1007-1014, December.
    6. Russell B. Millar & Renate Meyer, 2000. "Non‐linear state space modelling of fisheries biomass dynamics by using Metropolis‐Hastings within‐Gibbs sampling," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 49(3), pages 327-342.
    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. R. B. Millar & S. McKechnie, 2014. "A one-step-ahead pseudo-DIC for comparison of Bayesian state-space models," Biometrics, The International Biometric Society, vol. 70(4), pages 972-980, December.
    2. Blanca Sarzo & Ruth King & David Conesa & Jonas Hentati-Sundberg, 2021. "Correcting Bias in Survival Probabilities for Partially Monitored Populations via Integrated Models," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 26(2), pages 200-219, June.
    3. Axel Finke & Ruth King & Alexandros Beskos & Petros Dellaportas, 2019. "Efficient Sequential Monte Carlo Algorithms for Integrated Population Models," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 24(2), pages 204-224, June.
    4. Besbeas, P.T. & McCrea, R.S. & Morgan, B.J.T., 2022. "Selecting age structure in integrated population models," Ecological Modelling, Elsevier, vol. 473(C).

    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. Devin S. Johnson & Jennifer A. Hoeting, 2003. "Autoregressive Models for Capture-Recapture Data: A Bayesian Approach," Biometrics, The International Biometric Society, vol. 59(2), pages 341-350, June.
    2. R. King & S. P. Brooks & B. J. T. Morgan & T. Coulson, 2006. "Factors Influencing Soay Sheep Survival: A Bayesian Analysis," Biometrics, The International Biometric Society, vol. 62(1), pages 211-220, March.
    3. R. B. O'Hara & S. Lampila & M. Orell, 2009. "Estimation of Rates of Births, Deaths, and Immigration from Mark–Recapture Data," Biometrics, The International Biometric Society, vol. 65(1), pages 275-281, March.
    4. J. D. Lebreton & R. Choquet & O. Gimenez, 2012. "Simple Estimation and Test Procedures in Capture–Mark–Recapture Mixed Models," Biometrics, The International Biometric Society, vol. 68(2), pages 494-503, June.
    5. Dunham, Kylee & Grand, James B., 2016. "Effects of model complexity and priors on estimation using sequential importance sampling/resampling for species conservation," Ecological Modelling, Elsevier, vol. 340(C), pages 28-36.
    6. Axel Finke & Ruth King & Alexandros Beskos & Petros Dellaportas, 2019. "Efficient Sequential Monte Carlo Algorithms for Integrated Population Models," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 24(2), pages 204-224, June.
    7. Paul B. Conn & Duane R. Diefenbach & Jeffrey L. Laake & Mark A. Ternent & Gary C. White, 2008. "Bayesian Analysis of Wildlife Age-at-Harvest Data," Biometrics, The International Biometric Society, vol. 64(4), pages 1170-1177, December.
    8. Gimenez, Olivier & Rossi, Vivien & Choquet, Rémi & Dehais, Camille & Doris, Blaise & Varella, Hubert & Vila, Jean-Pierre & Pradel, Roger, 2007. "State-space modelling of data on marked individuals," Ecological Modelling, Elsevier, vol. 206(3), pages 431-438.
    9. Panagiotis Besbeas & Byron J. T. Morgan, 2017. "Variance estimation for integrated population models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 101(4), pages 439-460, October.
    10. O. Gimenez & C. Crainiceanu & C. Barbraud & S. Jenouvrier & B. J. T. Morgan, 2006. "Semiparametric Regression in Capture–Recapture Modeling," Biometrics, The International Biometric Society, vol. 62(3), pages 691-698, September.
    11. Ruiz, Javier & Prieto, Laura & Astorga, Diana, 2012. "A model for temperature control of jellyfish (Cotylorhiza tuberculata) outbreaks: A causal analysis in a Mediterranean coastal lagoon," Ecological Modelling, Elsevier, vol. 233(C), pages 59-69.
    12. Loreto A Correa & Cecilia León & Juan Ramírez-Estrada & Álvaro Ly-Prieto & Sebastián Abades & Loren D Hayes & Mauricio Soto-Gamboa & Luis A Ebensperger, 2021. "One for all and all for one: phenotype assortment and reproductive success in masculinized females," Behavioral Ecology, International Society for Behavioral Ecology, vol. 32(6), pages 1266-1275.
    13. Su, Zhenming & Peterman, Randall M., 2012. "Performance of a Bayesian state-space model of semelparous species for stock-recruitment data subject to measurement error," Ecological Modelling, Elsevier, vol. 224(1), pages 76-89.
    14. S. A. Sisson & Y. Fan, 2009. "Towards automating model selection for a mark–recapture–recovery analysis," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 58(2), pages 247-266, May.
    15. I. B. J. Goudie & M. Goudie, 2007. "Who captures the marks for the Petersen estimator?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(3), pages 825-839, July.
    16. Dennis, Emily B. & Kéry, Marc & Morgan, Byron J.T. & Coray, Armin & Schaub, Michael & Baur, Bruno, 2021. "Integrated modelling of insect population dynamics at two temporal scales," Ecological Modelling, Elsevier, vol. 441(C).
    17. Gurutzeta Guillera-Arroita & José J. Lahoz-Monfort, 2017. "Species occupancy estimation and imperfect detection: shall surveys continue after the first detection?," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 101(4), pages 381-398, October.
    18. Sinnott, Emily A. & Thompson, Frank R. & Weegman, Mitch D. & Thompson, Thomas R. & Mosloff, Alisha R. & Hedges, R. Kyle & Loncarich, Frank L., 2023. "Evaluation of seasonal site-level demography and management for northern bobwhite using integrated population models," Ecological Modelling, Elsevier, vol. 475(C).
    19. Devin S. Johnson & Brian M. Brost & Mevin B. Hooten, 2022. "Greater Than the Sum of its Parts: Computationally Flexible Bayesian Hierarchical Modeling," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(2), pages 382-400, June.
    20. Chaloupka, Milani & Balazs, George, 2007. "Using Bayesian state-space modelling to assess the recovery and harvest potential of the Hawaiian green sea turtle stock," Ecological Modelling, Elsevier, vol. 205(1), pages 93-109.

    More about this item

    Statistics

    Access and download statistics

    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:bla:jorssc:v:57:y:2008:i:5:p:609-632. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.html .

    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.