**Vijay Barve**, and kindly contributed to R-bloggers)

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**

- Asase, Alex, and A Townsend Peterson. 2016. “Completeness of Digital Accessible Knowledge of Plants of Ghana.” Biodiversity Informatics, 1–11. doi:http://dx.doi.org/10.17161/bi.v11i0.5860.
- Barve, Vijay, and Javier Otegui. 2016. “Bdvis: Visualizing Biodiversity Data in R.” Bioinformatics. doi:http://dx.doi.org/10.1093/bioinformatics/btw333.

**leave a comment**for the author, please follow the link and comment on their blog:

**Vijay Barve**.

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