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Random Effects Models and Multistage Estimation Procedures for Statistical Population Reconstruction of Small Game Populations

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  • Christopher M Gast
  • John R Skalski
  • Jason L Isabelle
  • Michael V Clawson

Abstract

Recently, statistical population models using age-at-harvest data have seen increasing use for monitoring of harvested wildlife populations. Even more recently, detailed evaluation of model performance for long-lived, large game animals indicated that the use of random effects to incorporate unmeasured environmental variation, as well as second-stage Horvitz-Thompson-type estimators of abundance, provided more reliable estimates of total abundance than previous models. We adapt this new modeling framework to small game, age-at-harvest models with only young-of-the-year and adult age classes. Our Monte Carlo simulation results indicate superior model performance for the new modeling framework, evidenced by lower bias and proper confidence interval coverage. We apply this method to male wild turkey harvest in the East Ozarks turkey productivity region, Missouri, USA, where statistical population reconstruction indicates a relatively stationary population for 1996–2010.

Suggested Citation

  • Christopher M Gast & John R Skalski & Jason L Isabelle & Michael V Clawson, 2013. "Random Effects Models and Multistage Estimation Procedures for Statistical Population Reconstruction of Small Game Populations," PLOS ONE, Public Library of Science, vol. 8(6), pages 1-12, June.
    • Handle: RePEc:plo:pone00:0065244
    DOI: 10.1371/journal.pone.0065244
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    References listed on IDEAS

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    1. John R Fieberg & Kyle W Shertzer & Paul B Conn & Karen V Noyce & David L Garshelis, 2010. "Integrated Population Modeling of Black Bears in Minnesota: Implications for Monitoring and Management," PLOS ONE, Public Library of Science, vol. 5(8), pages 1-11, August.
    2. 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.
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    Cited by:

    1. Sergey S. Berg, 2023. "Utility of Particle Swarm Optimization in Statistical Population Reconstruction," Mathematics, MDPI, vol. 11(4), pages 1-28, February.

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    1. John R Fieberg & Kyle W Shertzer & Paul B Conn & Karen V Noyce & David L Garshelis, 2010. "Integrated Population Modeling of Black Bears in Minnesota: Implications for Monitoring and Management," PLOS ONE, Public Library of Science, vol. 5(8), pages 1-11, August.
    2. Sergey S. Berg, 2023. "Utility of Particle Swarm Optimization in Statistical Population Reconstruction," Mathematics, MDPI, vol. 11(4), pages 1-28, February.

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