Bias in Estimating Niche Overlap

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Abstract
Bias refers to the accuracy of a particular estimator. We evaluate bias, using analytic and simulation technics, for six measures of overlap: the likelihood ratio measure, the chi—square measure, the measure based on the Freeman—Tukey statistic, Morisita's adjusted index, Morista's original index, and Horn's information index. We present an exact formula for a seventh, the percentage similarity measure. We consider bias due to resource a sample size, total number of different resources, and evenness of resource distribution. Results indicate that of the seven measures, changes in evenness of resource of distribution produce significant bias only in the percentage similarity measure and Morista's adjusted index. All measures show increasing bias with increasing number of resources. For estimating unbiased overlap, Morisita's original measure of overlap gives the most accurate results, especially when using small sample sizes. The percentage similarity measure, one of the most commonly used measures among ecologists, is also one of the most biased and for this reason is not preferred.