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Removal models accounting for temporary emigration

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  • Ming Zhou
  • Rachel S. McCrea
  • Eleni Matechou
  • Diana J. Cole
  • Richard A. Griffiths

Abstract

Removal of protected species from sites scheduled for development is often a legal requirement in order to minimize the loss of biodiversity. The assumption of closure in the classic removal model will be violated if individuals become temporarily undetectable, a phenomenon commonly exhibited by reptiles and amphibians. Temporary emigration can be modeled using a multievent framework with a partial hidden process, where the underlying state process describes the movement pattern of animals between the survey area and an area outside of the study. We present a multievent removal model within a robust design framework which allows for individuals becoming temporarily unavailable for detection. We demonstrate how to investigate parameter redundancy in the model. Results suggest the use of the robust design and certain forms of constraints overcome issues of parameter redundancy. We show which combinations of parameters are estimable when the robust design reduces to a single secondary capture occasion within each primary sampling period. Additionally, we explore the benefit of the robust design on the precision of parameters using simulation. We demonstrate that the use of the robust design is highly recommended when sampling removal data. We apply our model to removal data of common lizards, Zootoca vivipara, and for this application precision of parameter estimates is further improved using an integrated model.

Suggested Citation

  • Ming Zhou & Rachel S. McCrea & Eleni Matechou & Diana J. Cole & Richard A. Griffiths, 2019. "Removal models accounting for temporary emigration," Biometrics, The International Biometric Society, vol. 75(1), pages 24-35, March.
  • Handle: RePEc:bla:biomet:v:75:y:2019:i:1:p:24-35
    DOI: 10.1111/biom.12961
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    1. 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.
    2. Rothenberg, Thomas J, 1971. "Identification in Parametric Models," Econometrica, Econometric Society, vol. 39(3), pages 577-591, May.
    3. Roger Pradel, 2005. "Multievent: An Extension of Multistate Capture–Recapture Models to Uncertain States," Biometrics, The International Biometric Society, vol. 61(2), pages 442-447, June.
    4. William L. Kendall & Rhema Bjorkland, 2001. "Using Open Robust Design Models to Estimate Temporary Emigration from Capture—Recapture Data," Biometrics, The International Biometric Society, vol. 57(4), pages 1113-1122, December.
    5. Robert M. Dorazio & Howard L. Jelks & Frank Jordan, 2005. "Improving Removal-Based Estimates of Abundance by Sampling a Population of Spatially Distinct Subpopulations," Biometrics, The International Biometric Society, vol. 61(4), pages 1093-1101, December.
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    Cited by:

    1. Wei Zhang & Simon J. Bonner & Rachel S. McCrea, 2023. "Latent multinomial models for extended batch‐mark data," Biometrics, The International Biometric Society, vol. 79(3), pages 2732-2742, September.
    2. N. O. A. S. Jourdain & D. J. Cole & M. S. Ridout & J. Marcus Rowcliffe, 2020. "Statistical Development of Animal Density Estimation Using Random Encounter Modelling," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 25(2), pages 148-167, June.

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