NatureReads

logo
example graphs

Inspiration

As we move forward each year, urbanization and industrial activity cause sustainability to fall to a new all-time low. Canadian birds are major contributors to our biodiversity but are victims of habitat loss, collisions, the climate crisis, and more, as a result of human actions. In fact, more than 3 billion birds, almost 1 in 3 individuals, have been lost from Canada and the US in under 50 years. We decided to build our package, NatureReads, that would process and visualize the data of the birds in an effort to help preserve the species.

What it does

Using NatureCounts, one of the largest databases on Canadian birds managed by Birds Canada, we developed various functions that visualize and filter information in meaningful graphs, tables, and maps. For example, people are able to find a map of the migration trend of a species, a species list for a specific area, or a graph of the number of sightings per province. We then compiled all of these functions in a package called NatureReads.

Features

Gets (or plots the distribution of) the top n most frequent species in an area.
Generates a named list of the region data in a specific provided region
Searches for a species by a name, returning the first ID in the search results
Gets the English name for a species given its ID, falling back to the scientific name
Gets (or plots) the most common species in each area of the provided data
Finds observations in a region defined by a polygon
Plots the population density of a species.
Plots the estimated migration path of a species filtered by year.
Plots a limited number of the locations of the observations of the given data which can be filtered by a specific species
Plots the line graph of the number of sightings per year
Plots the bar graph of the number of sightings per province
Plots a limited number of sightings of the given data
Calculates the relative observation trend for a species
Gets (or plots) the area containing the most sightings of a species
Gets the province or state containing the most sightings of the species in the given data

How we built it

We used R for all the functionalities of our package and used the naturecounts dataset for our data. For our functions to display the data, we used the Plotly library to visualize information in user-friendly and accessible ways. We also used some other libraries, such as dplyr, to make the data processing easier, and sf to process geographic data.