Chao et al.: Coverage-based rarefaction and extrapolation: standardizing samples by completeness rather than size

http://www.esajournals.org/doi/pdf/10.1890/11-1952.1

Interesting read. Don't remember if we have gone over it before...

Abstract
We propose an integrated sampling, rarefaction, and extrapolation methodology
to compare species richness of a set of communities based on samples of equal
completeness (as measured by sample coverage) instead of equal size. Traditional rarefaction
or extrapolation to equal-sized samples can misrepresent the relationships between the
richnesses of the communities being compared because a sample of a given size may be
sufficient to fully characterize the lower diversity community, but insufficient to characterize
the richer community. Thus, the traditional method systematically biases the degree of
differences between community richnesses. We derived a new analytic method for seamless
coverage-based rarefaction and extrapolation. We show that this method yields less biased
comparisons of richness between communities, and manages this with less total sampling
effort. When this approach is integrated with an adaptive coverage-based stopping rule during
sampling, samples may be compared directly without rarefaction, so no extra data is taken and
none is thrown away. Even if this stopping rule is not used during data collection, coverage based
rarefaction throws away less data than traditional size-based rarefaction, and more
efficiently finds the correct ranking of communities according to their true richnesses. Several
hypothetical and real examples demonstrate these advantages.