We can use richness and abundance such as S or N.

To compare communities are very useful index to compare

evenness of the two samples is the EH and the slope of ECDF as a graph

as they intercept if n of each samples is measured than 100 Individuals.

And if you want to understand differences in dominance and rarity,

we can just use the relative dominance and the percentage of rare number of

individuals divided by number of species, so PCTRare N divided by S.

For the second scenario so if we have areas of different dimension or

samples from different ecologically community we can use for to estimate

the differences in their richness and abundance the Margalef Index or

the Alpha Index if n of each sample is measured in a 100 or

there the Smith-Wilson index to compare abundances.

If we want to understand the difference in the evenness we

can use evenness of Shannon or the M of ECDF.

So there's no, and to understand the difference between dominance and

rarity we can use absolute or relative dominance.

And percentage rare at 1 or 5% In the third case where the samples are of

more dimension means that the number of individuals are less than 100 or 200.

We can use to evaluate the differences in diversity between the two samples

the Hulbert Simpson index that is very scalable in cases more dimension samples

And we can use 1- D, so 1 minus the Hulbert/Simpson Index.

To evaluate the differences in evenness instead we can just use this evenness.

For the evaluation of dominance Dominance and rarity, relative dominance or

McNaughton index is very useful.

And for rare species, the PctRare5% or

the PctRareN/S are very useful indicators.

Moreover, we can use statistical tests to understand if these differences

between communities are more or less statistically evident.

And one of these is the T-test or the ANOVA test to compare two or

more communities in case of normality of data distribution.

If normality cannot be ensured, we can use the jackknifing process.

To use the jackknifing process is very simple.

We need just to calculate diversity, the Shannon or Simpson Not very important.

We can use one or these two.

And of all add samples together to obtain a kind of aesthetic,

so the original diversity estimation.

Then we calculate n times the diversity excluding

each time only one sample to obtain.

Minus one, or minus j.

Then, we calculate the set of values for

each n samples that is just nst, minus n, minus one.

Of sti, deity or j, depends on our sample.

So, we will remove from the original diversity estimation.

The diversity of each sample we removed and we estimate the diversity

jackknifing as the sum of this pseudo-values divided by n.

That is the total number of samples.

In this way, we can also calculate the standard error That is simple.

The standard error of the estimation of jackknifing process, and

we have a variable statistics to provide information about

the evidence in differences in statistical communities.

So this lecture tried to show you how to compare different communities based

on based on [INAUDIBLE], based on [INAUDIBLE], based on [INAUDIBLE].

And I hope you will use these tools to compare your data and

evaluate difference in your biodiversity data.

See you next time.