Computing parametric beta diversity with unequal plot weights: a solution based on resampling methods

Jost (Ecology, 88:2427-2439, 2007) recently showed that the Shannon diversity is the only standard diversity measure that can be partitioned into meaningful independent alpha and beta components when plot weights are unequal. This conclusion is very disappointing if one wants to calculate the beta diversity of unequal weighted plots using a parametric measure with varying sensitivities to the occurrence of rare and abundant species. To overcome this impasse, at least partially, in this paper, I propose a parametric measure of beta diversity that is based on the combination of Shannon's entropy with Hurlbert's 'expected species diversity'. Unlike most parametric measures of diversity, the proposed index has a clear probabilistic interpretation, allowing at the same time a multiplicative partition of diversity into independent alpha and beta components for unequally weighted plots.