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Small sample bias in dynamic occupancy models

Authors


  • Associate Editor: Gary White

Abstract

Occupancy models may be used to estimate the probability that a randomly selected site in an area of interest is occupied by a species (ψ), given imperfect detection (p). This method can be extended, given multiple survey periods, to permit the estimation of seasonal probabilities of ψ, colonization (γ), persistence (φ), and extinction (1 − φ) in season t. We evaluated the sampling properties of estimators of these parameters using simulated data across a range of the parameters, differing levels of sites and visits, with a published dynamic occupancy model (Royle and Kery 2007). Bias depended largely on p and the number of visits, but also on the number of sites, ψt, γ, and 1 − φ. To decrease bias in all parameters to near zero, our results suggest that the number of required visits will depend on p, such that the probability of detection at an occupied site is near 0.9, and the required number of sites will be near 60 for ψt estimation and 120 or greater for γ and 1 − φ estimation. Published 2012. This article is a U.S. Government work and is in the public domain in the USA.

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