COMPARING STRATIFICATION SCHEMES FOR AERIAL MOOSE SURVEYS
Keywords:Alces alces, aerial surveys, boosted regression trees, cum√f rule, land cover types, Poisson regression, stratification
AbstractStratification 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.
How to Cite
Fieberg, J. R., & Lenarz, M. S. (2012). COMPARING STRATIFICATION SCHEMES FOR AERIAL MOOSE SURVEYS. Alces: A Journal Devoted to the Biology and Management of Moose, 48, 79–87. Retrieved from https://alcesjournal.org/index.php/alces/article/view/101
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