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This is also known as the ICE (Incidence-based Coverage) Estimator of species richness (Lee and Chao 1994).


It is assumed that




The sample coverage estimate based on incidence data is








In words, the sample coverage estimate is the proportion of all individuals in infrequent species that are not uniques. The ICE estimator of species richness is





where the estimate the coefficient of variation estimates the coefficient of variation of the Qj's, is




   Note: The formula for ICE is undefined when all infrequent species are Uniques (Q1 = Ninfr, yielding C = 0).



The output presents a series of estimates using 1, 2, 3... and so on samples. Thus to get sensible estimates you must ensure that all the data derive from samples obtained from the same community.


If Number of Random Selections (R) is set > 1 then the sequence samples are selected R times at random from the complete set of samples and the mean estimate calculated. As this removes sample order effects it is generally to be recommended.


By looking at the progressive change in the estimates it is possible to assess if sufficient samples have been taken to stabilise the estimate.


A simple plot of the way the estimate changes with the number of samples used is shown by clicking on the Graph tab.