During 2012–2016, we queried hunters of deer and elk for observations of groups of a non-target species, moose, across their statewide distribution in Montana.  We used buffer analyses to filter data according to independent observations in space and time and then tallied observations of groups by hunting district.  We then analyzed data in an abundance-detection framework with n-mixture models and evaluated the effects of covariates such as hunter effort, survey response totals, weekly session, and forest cover on detection probability before using models to predict moose abundance.  Lastly, we converted model predictions of group abundnace to total abundance by multiplying number of groups by average group size per administrative region.

Analyzed in Program R with the package unmarked