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Indirect information on population size, like pellet counts or volunteercounts, is the main source of information in most ecological studies andapplied population management situations. Often, such observations are treadedas if they were actual measurements of population size. This assumption resultsin incorrect conclusions about a population's size and its dynamics. We proposea model with a temporal varying link, denoted countability, between indirectobservations and actual population size. We show that, when indirectmeasurement has high precision (for instance many observation hours) theassumption of temporal varying countability can have a crucial effect on theestimated population dynamic. We apply the model on two local moose populationsin Sweden. The estimated population dynamics is found to explain 30-50 percentof the total variability in the observation data; thus, countability accountsfor most of the variation. This unreliability of the estimated dynamics has asubstantial negative impact on the ability to manage populations; for example,reducing (increasing) the number of animals that needs to be harvested in orderto sustain the population above (below) a fixed level. Finally, largedifference in countability between two study areas implies a substantialspatial variation in the countability; this variation in itself is highlyworthy of study.

Estimating the unobservable moose - converting index to population size using a Bayesian Hierarchical state space model