4.- How to use data cleaning, EOO estimation and environmental of occurrence features in ModestR (Version ModestR v5.3 or higher)

Step by step tutorial:
Using data cleaning and EOO
estimation in ModestR
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What do you need for this tutorial:
1. ModestR v5.3 or higher
2. Environmental data already
integrated in ModestR
3. Internet connection
4. About 30 minutes
ModestR software can be freely downloaded from http://www.ipez.es/ModestR

We’ll describe how to clean occurrence
data in ModestR, and how to estimate
EOO using different hulling algorithms,
as well as environmental occurrence
approach. Follow the next steps!

Let’s suppose you want to download occurrence records from GBIF. To do so, select File/Import/Ocurrences from
online GBIF database (Tutorial No. 2).
Other options already exist such as importing occurrence data from a CSV file, from KML files, shapefiles, etc. All
those options are explained in the ModestR Tutorial No. 2 available in the ModestR website. You can also retrieve a
map stored in a ModestR database, as explained in the step-by-step tutorial “ ModestR Tutorial No. 1.”

In the dialog box that will appear we will enter the species name “Isurus paucus”
1. Type the species name “Isurus
paucus” in the textbox and click on the
Accept button.

The next step will query GBIF database how many occurrence records there are for the selected species. It will display
this information and ask you to confirm you want to continue downloading. Downloading of occurrence records will be
done. Wait a few minutes. When download finished, click on accept and continue.
Just click on the
Accept button to
continue downloading
occurrence data from
GBIF.

Select the valid habitats for the species. In this case, it is the Sea habitat. Once imported, MapMaker will display a brief
summary of the imported, valid and invalid occurrences.
Check the Sea habitat
and the Accept button
to continue
There are other options to clean imported data. You can also check the Land option or All freshwaters valid habitats.
By default occurrences
will autochecked. That
is, ModestR will
automatically check
occurrences validity
regarding the habitat.

Now, an information resume is shown and ModestR will ask you to save the information.

It is recommended to create a folder where the information will be saved. (in this example: Isurus paucus). The folder’s
location depends on your decision.

Now imported data are shown on the map (green dots). In this example usually all occurrences of Isurus paucus are
correctly located.

Let’s suppose you want to automatically clean current data detecting and removing outliers. To do that, go to and click
on the Mapping/Data cleaning/Automatic environmental-based cleaning menu item.
In ModestRv2.0 this option is located on the Process menu item. In more recent releases it is found
in the Mapping menu item.

The first step will be selecting which environmental variables will be used to perform data cleaning. Environmental data has
to be previously integrated importing ASC raster files in ModestR. This is explained in the ModestR Tutorial No. 3 and more
detailed in the ModestR User’s Manual.
For this example we will select all variables from the
Marine folder. You can also select another variable if you
have it integrated in ModestR.
Then click on button.

In the next step, ModestR will detect the value for each one of the variables in the positions of the current occurrences. Then it will apply
different outliers detection methods to determine acceptance ranges for each variable. Then it selects the “best” of them by default (being the
best the one that excludes the less data). You can manually select another method, or even manually set range limits using the Custom
method.
You can select any
variable in the list to
see/modify the
validation mode (i.e.
outlier detection mode)
that will be used to
detect outliers for this
variable.
For this example we will
just use defaults.
Click on
button.

Once data cleaning task ended, a brief summary will be shown, indicating the number of processed occurrences, and
how many were considered invalid (cleaned).
Click on the Accept button.

You can also save a detailed report of the cleaning process into a CSV file, easily readable using a worksheet program
such as Excel.
In the report generated you can check the calculated acceptance ranges for each environmental variable used, the
occurrences cleaned (invalidated), and the rule that caused it. So you can see which environmental variable was out of
range in the sample location and motivated its invalidation.
Note: this report only contains the trace of the cleaning task on occurrences (occurrences). It doesn’t keep trace of the
cleaning on areas, if there is any.

As you can see, cleaned occurrences are not definitely deleted. They are marked using a placemark and another color. But
more important, even if they are preserved, they will not be took into account for any other subsequent task (presence,
hulling, EOO estimation, etc.). So, way are they preserved? First of all, because you may later decide to re-validate those
occurrences. And second, because this way you can keep a trace of the original data.
Cleaned occurrences
are marked by default
using a placemark and
another color.

Now we’ll see how you can estimate Extent Of Occurrence in MapMaker, using different algorithms. To do that, go to and
click on the Mapping/Hull transformation menu item. Let’s start by Convex Hull option.
In ModestRv2.0 Hull
transformation option is
located on the Process menu
item.
In more recent releases it is
found in the Mapping menu
item.
Select Convex Hull option

By default, visual simulation option is selected. So you can preview the resulting hull as a visual template, without
modifying the distribution data.
Convex hull can include areas to be calculated, but this is a NOT recommended and error-prone option,
so it must be avoided unless you clearly understand its implications. See ModestR User’s Manual for
more details.
Just click on the Apply button. A visual template will appear on
the map, as a preview of the EOO calculated using convex hull.
In ModestR a visual template is a polygonal shape
that is shown on the map, but that doesn’t affect
presence data. It is just for displaying purposes, and
it will not be stored with the map. It is usually shown
as a semi transparent shape over the map.

The result is shown in the map. If you want to really add a presence area to the map, just change the option to “Add as
presence area”.

A presence area will be added to the map. Unlike visual templates, this area is added to the map and will be considered
as an area of presence of the species.
As you can see, ModestR only adds the presence area in the species currently valid habitats.
In this example, the area is only added on the sea habitats, because it’s the only habitat we indicated as valid for the
species when we imported occurrences from GBIF (see previous steps).

Well, as we want to test other EOO estimation methods, we’ll undo last changes to remove the convex hull presence
area we have added.
Click on the Undo button to go back to the map as it was previously to convex hull, with occurrences only.

Now we’ll test another method to estimate Extent Of Occurrence in MapMaker. Go to Mapping/Hull transformation
menu item and now click on the Alpha shape option.
Select Alpha shape option
As for convex hull, by default, visual simulation option is selected.
So you can preview the resulting hull as a visual template, without
modifying the distribution data. Just click on the Apply button. A
visual template will appear on the map, as a preview of the EOO
calculated using alpha shape.

As you can see, while with convex hull we’ll obtain a single shape that contains all occurrences, with alpha shape we can
obtain several separated shapes.
Alpha shape is more “fine-grained” in this way than convex hull. The number and size of the shapes depends on the
alpha parameter.

For this example, we won't add a presence area (the procedure would be the same than for convex hull). We’ll just close
the alpha share dialog box, and clear the visual templates that were added.
Use this button to clear visual templates from the map.

We’ll test the last method to estimate Extent Of Occurrence in MapMaker. Go to Mapping/Hull transformation menu
item and now click on the Kernel density/ Distribution map option.
Select Kernel
density/
Distribution
map option.
Kernel density method is based on the density of occurrences of a species.

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The operation is almost the same than previously explained options. By default, visual simulation option is selected. So
you can preview the resulting EOO as a visual template, without modifying the distribution data.
Just click on the Apply button. A visual template will appear on the map, as a
preview of the EOO calculated using Kernel density.
The kernel density “smoothing” parameter can be modified,
even if the default value has been calculated to have a good
performance in most of the situations.
The cell width parameter controls the precision
used to calculate densities in the map. A value of
5’ is a good compromise between precision and
performance. For a fast preview, you can increase
this value (e.g. to 20’)

As we said: Kernel density method is based on the density of occurrences of a species.

Besides calculating EOO, kernel density estimation can be useful to easily visualize the density of the occurrences of a
species. MapMaker can easily show a kernel density map. To do that, go to Mapping/Hull transformation menu item
and now click on the Kernel density/ Density map option.
Select Kernel density
/Density map option
Put plainly, a raster is a bitmap image. That is, an image composed from a
matrix or grid where each cell has a specific color.
Mapmaker can calculate kernel density and show it as a raster on the map.

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The operation is similar to the previously explained for kernel density-based EOO. Just adjust the parameters and click on
Apply. The map will be calculated and shown on the map without modifying the distribution data.
The kernel density
“smoothing”
parameter can be
modified to
produce more
“appealing” and
visual maps. Here
we increased it to
x5.
The cell width
parameter controls
the precision used
to calculate
densities in the
map. A value of 5’ is
a good compromise
between precision
and performance.
For a fast preview,
you can increase
this value (e.g. to
20’)

To have a better visualization, you can hide the occurrences, for example.
You can momentarily hide the occurrences from the map using those checkboxes, to have a clearest view of the density
map.

Now, you can export this map as an image.
Then export the current view (which includes the density map) as an image.

To clear the density map, you just have to use the Clear visual raster button.
Use the Clear visual raster button to remove any raster from the map (the kernel density map is a raster).

Until here we have seen several methods to calculate EOO and add it to the map. But ModestR can refine this approach
applying an environmental filtering to the potential EOO. That’s what is called the Environmental Occurrence in ModestR.
Let’s see how to proceed:
Select Mapping/ Environmental Occurrence option.
In earlier versions this
feature was called
“niche of occurrence”.
In more recent
releases it is called
“Environmental
occurrence”, as Niche
of Ocurrence refers to
a new different
feature based on
environmental layers.

The first step to calculate environmental occurrence is choosing the range: full extent (for all environmental data
available) or EOO.
You can use the Preview button to see a
visual template of the potential EOO on
the map.
Select EOO range and the method to be
used to calculate potential EOO. In this
example, we are using alpha shape.
Then click on the Continue button
In this last case, you should
choose the method to be used
to calculate potential EOO. The
available methods are the
ones we have explained
previously: convex hull, alpha
shape, and kernel density.

In the next step we’ll select the environmental variables to be used to calculate environmental occurrence.
Select the environmental
variables to be used to calculate
environmental occurrence.
Environmental variables
will be used to determine
acceptable ranges of each
variable for the species.
This is done detecting the
values of those variables
where there are
occurrences of the
species.
Then click on the Continue
button
To do that, you must have
previously integrated
environmental data into
ModestR (Tutorial No. 3).

In the next step % coverage for each variable is shown. This is the % of the EOO area where there are data for this variable. A too low
coverage indicates that a variable may not be suitable to calculate environmental occurrence of this species, because there are not enough
data for this variable into the EOO. You can also optionally calculate the VIF (Variance Inflation Factor) of the selected variables to eventually
detect multicollinearities and therefore remove some variables.
Click on the Continue button to
go to the next step
To calculate VIF, click on this button. VIF will be
shown in the list, aside each variable.
You may eventually decide to remove a variable
which has as higher VIF selecting it and using this
button.
Remember that this step is
optional. You can just
continue without calculating
VIF neither modifying the
selected variable list.

In the next step you can optionally calculate a contribution index of the selected variables. This contribution index measures
the relative importance of each variable to determine presence/absence of the species within its potential EOO. Once
calculated, you can set a minimal contribution % to achieve, then ModestR will automatically select the variables with the
highest contributions until attain this % (more details about contribution index calculation can be found on Modestr documentation)
Click on the Continue button to
go to the next step
To calculate contribution index, click on Analyse
button. It will be shown in the list, aside each
variable. You may eventually set a minimal
contribution % to achieve using this checkbox and
entering the wanted % . In this case, selected
variables will appear highlighted in the list (here
with green color).
Remember that this step is optional.
You can just continue without
calculating variable contribution. In
this case all variables will be used to
calculate environmental occurrence.

In the last step you can set how each variable will be used to determine environmental occurrence.
Selecting a variable in the left list, you can see the allowed range on the right panel
(minimum and maximum accepted values). This range results from applying the set
tolerance % to the range detected using the current presence data for the species.
By default, a %1 of tolerance is allowed regarding the range detected for each
environmental variable. This range is determined from the values of each variable in
the current presence areas (in this case, that is where there are occurrences of the
species).
More details about available settings can be found on ModestR User’s Manual.

Click on the
Continue button to
start environmental
occurrence
calculation

Once calculated environmental occurrence, you’ll see new presence areas added to the map.
New presence areas resulting from the environmental occurrence calculation are added to the map. Those areas result from the
selected EOO (alpha shape in this example), where areas that don’t comply with environmental restrictions (that is, where some
variable has a value out of the acceptance range) have been removed.

At first sight it may seems that there are no differences with the EOO using alpha shape. But if we take a detailed look,
we’ll see differences:
Using the Zoom tool, we’ll
select an area to zoom on it
After selecting the area of
interest, righ click over the
rectangle and select Zoom.

As you can see, environmental occurrence results in a filtered EOO, where no areas have been removed because the
environmental conditions were in the determined range.
Here for example, we can see that
all areas are potential EOO
because all of the environmental
variables (from the selected to
perform the environmental
occurrence) took values in the
range accepted for this species..
Of course, here we are showing a
particular example. The results
you’ll obtain will depend of the
species and the environmental
variables used to calculate
environmental occurrence.

Once the environmental occurrence added to the map, maybe you’ll want to save it into a ModestR database.
Click on this button or go to
menu File/Save/To ModestR
maps database to save the
current map into a ModestR
database
For information about creating
databases, check Tutorial No. 1
(“How to create a ModestR
database”).
You can select the database that MapMaker
works with in menu File/Select database. That
will be the database where the maps will be
saved by default.

As this is a new map, MapMaker will search in the database for a species with the same name and ask you to confirm the
whole taxonomy before saving it.
In this example we created a new map from GBIF data. That’s why MapMaker will ask you to confirm taxonomy
before saving it into a database. But if you loaded the map from a database, it will be automatically saved with the
current taxonomy.

Until now we have shown how to clean data, calculate EOO and environmental occurrence, for a single map in MapMaker. This can be
useful when we’re working with few maps; or when we want to test several methods and interactively see results. But if we want to clean
or calculate EOO for many maps, it can be very tedious to do it one by one. In that case, you can use DataManager! In DataManager you
can do the same things than in MapMaker, but for a whole set of maps. For example a full order, a family, etc. All in a single task!
Here, for example, we
are adding EOO to all
maps of a particular
family, calculated using
convex hull or alpha
shape.
It is important to have the
maps with data, otherwise
you won’t be able to apply
the transformations or the
ocurrences.

Example of two branches with and without data and the Process option: without data, you can’t process any map.

The Map processing options dialog box gives you the chance to select the appropriate calculation mode.
As a beginner user, you can
select the None option for
EOO sample based maps and
area-based or mixed maps.
Then, click on Ok button and
wait until the processing
ends.

Then you can proceed like you did in steps before.

It was the
Step by step tutorial:
Using data cleaning and EOO
estimation in ModestR
Thank you for your interest.
MODESTR QUICK TUTORIALS HTTP://WWW.IPEZ.ES/MODESTR/º
You can find this one and other tutorials in
http://www.ipez.es/ModestR
By the ModestR team
Colaborators:
Estefanía Isaza Toro

4.- How to use data cleaning, EOO estimation and environmental of occurrence features in ModestR (Version ModestR v5.3 or higher)

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