COMPARING STRATIFICATION SCHEMES FOR AERIAL MOOSE SURVEYS

Authors

  • John R Fieberg Minnesota Department of Natural Resources
  • Mark S Lenarz Minnesota Department of Natural Resources

Keywords:

Alces alces, aerial surveys, boosted regression trees, cum√f rule, land cover types, Poisson regression, stratification

Abstract

Stratification is generally used to improve the precision of aerial surveys. In Minnesota, moose (Alces alces) survey strata have been constructed using expert opinion informed by moose density from previous surveys (if available), recent disturbance, and cover-type information. Stratum-specific distributions of observed moose from plots surveyed during 2005-2010 overlapped, suggesting some improvement in precision might be accomplished by using a different stratification scheme. Therefore, we explored the feasibility of using remote-sensing data to define strata. Stratum boundaries were formed using a 2-step process: 1) we fit parametric and non-parametric regression models using land-cover data as predictors of observed moose numbers; 2) we formed strata by applying classical rules for determining stratum boundaries to the model-based predictions. Although land-cover data and moose numbers were correlated, we were unable to improve upon the current stratification scheme based on expert opinion.

Author Biographies

John R Fieberg, Minnesota Department of Natural Resources

Biometrician

Mark S Lenarz, Minnesota Department of Natural Resources

Group Leader

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Published

2012-06-22

How to Cite

Fieberg, J. R., & Lenarz, M. S. (2012). COMPARING STRATIFICATION SCHEMES FOR AERIAL MOOSE SURVEYS. Alces, 48, 79–87. Retrieved from https://alcesjournal.org/index.php/alces/article/view/101

Issue

Vol. 48 (2012)

Section

Articles

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