The course presents an overview of the theory behind biological diversity evolution and dynamics and of methods for diversity calculation and estimation. We will become familiar with the major alpha, beta, and gamma diversity estimation techniques.
Understanding how biodiversity evolved and is evolving on Earth and how to correctly use and interpret biodiversity data is important for all students interested in conservation biology and ecology, whether they pursue careers in academia or as policy makers and other professionals (students graduating from our programs do both). Academics need to be able to use the theories and indices correctly, whereas policy makers must be able to understand and interpret the conclusions offered by the academics.
The course has the following expectations and results:
- covering the theoretical and practical issues involved in biodiversity theory,
- conducting surveys and inventories of biodiversity,
- analyzing the information gathered,
- and applying their analysis to ecological and conservation problems.
Needed Learner Background:
- basics of Ecology and Calculus
- good understanding of English

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Species-abundance distributions and comparisons

In this module we will talk about the most common species-abundance distribution models and I will show you how to compare different communities and samples in order to achieve a quantitative and statistical measure of the changes in biological diversity due to treatments.
I will explain some Evenness measures and how to represent them in form of curves of biodiversity. This will help to discriminate communities’ diversity and to better analyse the anthropogenic impacts on biodiversity.

Ph.D., Associate Professor in Ecology and Biodiversity Biological Diversity and Ecology Laboratory, Bio-Clim-Land Centre of Excellence, Biological Institute

[MUSIC]

Hi guys, welcome to 18th lecture on the course Biological Diversity, Theories,

Measures and Data sampling techniques.

Today we will talk about of course bio diversity.

There are different ways to represent bio diversity on a graph.

One other way to represent biodiversity in a graph is the k dominance curve.

K-dominance curve is a powerful tool for

measuring abundance trends in communities over time.

K-dominance curve are the cumulative rank in abundance against the log species rank.

In the graph on the X axis you put the species rank, and on the epsilon axis

you put the cumulative relative abundance and you obtain the K-dominance curve.

Another way to represent bio diversity in the graph

is the empirical cumulative distribution function.

In this case you rank the abundances in growing order cumulate them and

divide them for m.

On the x axis you use a log scale and

you match each abundance with the rank and divide it for S.

In this case you obtain a kind of steep graph.

Then you can, for example, many times and this case you [INAUDIBLE].

ECDF are mathematically stronger than rank abundance [INAUDIBLE]

as they are not influenced by species richness, and thus allow for

a direct comparison between habitat, the difference of total species richness.

From ECDF it's possible to evaluate two different biodiversity features.

The first one is the difference in the In this,

the more is vertical the central part of the cube, the more the sample is even.

And the second one is the rate of species proportion.

That there's a low left part placed higher than others, and more species.

Another way to represent biodiversity in species.

In this case you use look of cumulation curve that is called Q-statistic and

you use the 0.25 and 0.75 to calculate this And

then this can be a measure of biological diversity.

The [INAUDIBLE] statistic is shown in the picture.

You could just calculate the lower [INAUDIBLE] that is in this picture,

[INAUDIBLE] and the upper [INAUDIBLE] that is R2.

So it means that you use 0.35 and 0.75 levels.

And you insert these values in the formula to obtain the q value.

A very powerful tool to understand [INAUDIBLE]

biodiversity is the species [INAUDIBLE].

This is a relationship between the area of [INAUDIBLE] or part of a habitat, and

the number of species found within that area.

Larger area tend to contain larger number of species.

And empirically,

the relative number seem to follow systematic mathematical relationships.

Species area curve is a kind of species accumulation curve.

Because in the x axis,

you put the increasing area or the increasing number of samples.

And on the epsilon axis, you put the number of species.

In this way, you see that there is a rise at the beginning of the curve.

And then a kind of plateau.

This means that we reached the maximum area that

can be sampled to obtain that number of species.

The simplest way to assess mathematically this curve is the formula s = cA

elevated to zed, while S is the number of species A is the area sampled.

C and Z are two constants which characterize the site.

if data S and A are transformed with log10 we can

use the linear equation to estimate the two parameters c and z.

You see that the equations become log10s is equal to log10c plus zlog10A.

In this case we convert the group that we saw before

in a log curve that is just aligned.

And from this line,

from the parameters of the equation of the line we can extract the value of C and Z.

Beside the accumulation group,

there are other cues that are very useful in case you want to estimate which number

of species will obtain If you have a reduced number of samples.

This is called rarefaction.

Rarefaction is a technique to assess species richness from the result of

sampling.

Rarefaction allows to calculate species richness for a given number of individual

samples, based on the construction of so called rarefaction cues.

This graph is just a plot of the number of species as a function

of the number of sample.

On the left, the steep slope indicates that

a large fraction of the species' diversity remain to be discovered.

If the curve became flatter on the right, an reasonable number of individual sample

Have been taken more and things likely to yield only a few additional species,

as in the case of species are.

This means that species are a accumulation curve

are read from left side to right side.

As long as the number of plots are very accumulates along the sampling.

Is that rarefaction curve.

All right, I read from right side to left side and this means that we can

reduce the number of samples to estimate the number of species we have down.

[INAUDIBLE] [INAUDIBLE] used for sample [INAUDIBLE] the [INAUDIBLE] data

estimate the number of species in 1,2, etc., samples.

Until we reach t samples on the assumption that

all individuals in all samples are randomly mixed.

That rarefaction generates the expected number of species.

It has more collection of n individuals or

n samples drawn at random from the large pool of n samples.