VISIBILITY OF MOOSE IN A TEMPERATE RAINFOREST

Abstract

Aerial surveys are the principal methods used to estimate populations of moose (Alces alces gigas) in Alaska. Accounting for missed animals during aerial surveys is problematical, especially in forested habitats; incorporation of a visibility correction factor to account for the proportion of animals missed is known to improve accuracy of population estimates. Our purpose was to study factors affecting visibility of radio-collared moose during aerial surveys in a temperate rainforest on the Yakutat Foreland, Alaska, USA. Wildlife managers in the area typically assume they observe only 50% of moose during surveys regardless of widely varying conditions. We used logistic regression to examine factors that influenced visibility including vegetation, light conditions, snow cover, and sex, age, and group size of moose. We then used logistic regression to develop a simpler model that only contained variables easily measured during aerial surveys: forest cover, snow cover, light, open versus vegetated habitat, and group size. We used that model to estimate a visibility correction factor. The mean correction factor was 1.304, ranging from1.005-2.138, yielding a population estimate of 699 (90% CI = 671-724) moose from a survey count of 595 animals. Our correction factor was within the range reported for other populations of moose, and lower than the correction factor (2.0) currently used in this area. We conclude that application of site and time-specific visibility models is critical when estimating populations of large ungulates, especially in forested habitats.