The accuracy and precision of migration counts as population indices are dependent on the counts representing a consistent proportion of the population over time. One potential source of bias is variation in detection probability. My goal is to assess the variability in detectability at the Idaho Bird Observatory’s fall migration hawkwatch at Lucky Peak, four miles east of Boise. Two teams of observers, operating independently, but watching the same extent of sky simultaneously, will count the raptors that pass and record data on factors that may influence probability of detection. Each bird will thus have a two-occasion encounter history that can be used in a Huggins closed-capture model. An information-theoretic model selection procedure will be used to assess the relative effects of observers, environmental conditions, species characteristics, and flight behavior on detectability. Data will be collected in 2009 and 2010 to assess the degree of variability in detectability between years. The results of these analyses will be used to create a mathematical simulation in which I will test the effect of adjusting for detectability on statistical power to detect trends of management interest.