A review of quadrat-based sampling of rare, geographically clustered populations

Some common sampling designs are reviewed from the perspective of their appropriateness for accurately estimating the total abundance of a rare population. In addition, a small simulation study was performed in which the designs for three populations with varying numbers of rare elements were studied. The simulation study provided information on the efficiency of the designs and the shapes of the sampling distributions of the estimators. The best design was stratified random sampling in which strata were constructed so that quadrats with rare elements were confined to a single small stratum and that stratum was disproportionately oversampled. The estimator for this design had the smallest variance and a sampling distribution most similar to a normal distribution. Systematic sampling is a good second choice if an auxiliary variable on which to stratify is not available. The estimator had reasonably small variance, which was further reduced if adaptive cluster sampling was added. The disadvantages are that an estimate of the variance is not available if only a single systematic sample is taken and the sampling distribution of the estimator is discontinuous and definitely not shaped liked a bell curve.