Non-uniform coverage estimators for distance sampling.

Abstract

Allocation of sampling effort in the context of distance sampling is considered. Specifically, allocation of effort in proportion to portions of the survey region that likely contain high concentrations of animals are explored. The probability of a portion of the survey region being included in the sample is proportional to the estimated number of animals in that portion. These estimated numbers of animals may be derived from a density surface model. This results in unequal coverage probability, and a Horvitz- Thompson like estimator can be used to estimate population abundance. The properties of this estimator is explored here via simulation. The benefits, measured in terms of increased precision over traditional equal coverage probability estimators, are meagre, and largely manifested when the underlying population distribution is a smooth gradient.