Statistical Inference on Measures of Niche Overlap

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Abstract
Estimates of measures of niche overlap are often reported without any indication of sampling variance or an accompanying confidence interval. We have investigated the delta, jackknife, and bootstrap methods for making statistical inferences on four measures of niche overlap: the coefficient of community, Morisita's index, Horn's index, and the Euclidian distance. Our qualitative conclusions are: (1) The bias of these estimators was usually @<10% of the mean unless the sample size was small and the number of resource categories large. The jackknife and bootstrap can significantly reduce this bias. (2) The variance of the bootstrap and jackknife estimators was usually greater than that of the “standard” estimator. (3) Under a variety of circumstances, the population sampled may actually represent several unrecognized subpopulations. In such cases confidence intervals generated by the jackknife and delta techniques can be quite inaccurate, while the nonparametric confidence intervals derived from the bootstrap are highly accurate.

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