Archive | November, 2016

## Creating figures like the paper ‘Completeness of Digital Accessible Knowledge of Plants of Ghana’ Part 3

22 Nov

This is the third part of the of the post where we are replicating the figures from a paper and in this part we are going to create figure 2 the Chronohorogram. Part 2 of this series we created temporal plot for understanding seasonality of the data records (Figure 1b).

If you have not already done so, please follow steps in Part 1 of the post to download and set up the data. Make sure you have v 0.2.9 or higher installed on your system.

To create a chronohorogram, is really very simple using our package bdvis.

```chronohorogram(occ)
```

Though the command has created the diagram, it does not look right. The diagram does not cover the range of all years, represented in the data. Since we have used command without many paramaters, it has used default year values for start and end. Let us check what is the range of years we have in the data. For that we can simply use command bdsummary.

```bdsummary(occ)
```
```Total no of records = 1071315

Temporal coverage...
Date range of the records from 1700-01-01 to 2015-06-07

Taxonomic coverage...
No of Families : 0
No of Genus : 0
No of Species : 1565

Spatial coverage ...
Bounding box of records 6.94423 , -83.65 - 89 , 99.2
Degree celles covered : 352
% degree cells covered : 2.34572837531654```

This tells us that we have data available form 1700 till 2015 in this data set. Let us try by specifying starting year and let package decide the end year.

```chronohorogram(occ, startyear = 1700)
```

Looking at the diagram it is clear that we hardly have any data for first 150 years, i.e. before 1850, so let us generate the diagram with starting year as 1850.

```chronohorogram(occ, startyear = 1850)
```

The diagram looks good except the points look smudged into each other, so let us reduce the point size to get the final figure.

```chronohorogram(occ, startyear = 1850, ptsize = .1)
```

If you have suggestions on improving the features of package bdvis please post them in issues in Github repository and any questions or comments about this post, please poth them here.

References

## Creating figures like the paper ‘Completeness of Digital Accessible Knowledge of Plants of Ghana’ Part 2

8 Nov

Continuing from Part 1, in case you have not done so, please set up the data as described before we try to make this temporal polar plot.

To create Figure 1b. Graph showing accumulation of records through time (during the year) we need  use function tempolar. This name ‘tempolar’ is simply a short of ‘temporal polar’. For this plot, we just count records for each Julian day, without considering the year. This tells us about seasonality of the data records.

Let us continue from the the previous part with code too, if if you do not have the data set up, please visit Part 1 and run the code.

First create just a very basic tempolar plot.

```tempolar(occ)
```

Now this created the following graph:

This graph looks very different than what we want to create. This is plotting the data for each day, but the plot we want is for monthly data. Let us sue timescale = “m” to specify monthly data aggregation.

```tempolar(occ,timescale = 'm')
```

Now this created the following graph:

So now this is what we expected to have as a figure. One final thing is to add a better title.

```tempolar(occ,timescale = 'm', color = "blue",
title = 'Pattern of accumulation of records
of Indian Birds by month')
```

Currently the tempolar does not have ability to display values for each month. Is that very important and needs to be added? We would like to hear form the users.

If you have suggestions on improving the features of package bdvis please leave comments Github repository.

References