This repository is no longer maintained since the underlying API changed. Please use rabm instead.

The repo can be found here: https://github.com/davidclarance/rabm

---

The Kenya Bird Map

This will eventually change to the Africa Bird Map.

The Kenya Bird Map project aims to map the current distribution of all of Kenya’s bird species and describe their status with the help of valued input from Citizen Scientists – volunteer members of the public who are keen to contribute through going birding and submitting their observations to the project. By pooling the efforts of many Citizen Scientist birders, Kenya Bird Map will tell the story of changing bird distributions and abundance - and in so doing provide a powerful tool for conservation.

This package is an attempt to make life easier for the researchers and citizen scientists interacting with the Africa Bird Map's data. Some examples on how to use the package are given below. First we start by installing the package.

Installing the package

You would need devtools to install this package directly from github.

1. Install the devtools package if you do not have it.

install.packages("devtools")

2. Load the devtools package.

library(devtools)

3. Install the package

install_github("davidclarance/africabirdmap")

Example 1 : Calculate the reporting rate for a species

First you need to extract data from AFB. This is done using an API call. However, this is temporary solution and must be changed.

# download data for the African Paradise Flycatcher
raw_data <- extract_data(username = "[email protected]" ,
  user_id = 40664, password = "xxxxx", species_id = 682)

```s

Then you can run the reporting rate function with the conditions you like. 

```r 
# get the reporting rate for African Paradise Flycatcher in Kenya
reporting_rate(df = raw_data, species_id = 682, start_date = '1970-01-01', 
  end_date = Sys.Date(), selected_area = "Kenya",
  selection_type = "Country")

You can get reporting rates for a species at the country, province and county level.

# get the reporting rate for African Paradise Flycatcher in Turkana
reporting_rate(df = raw_data, species_id = 682, start_date = '1970-01-01', 
  end_date = Sys.Date(), selected_area = "Turkana",
  selection_type = "County")
  
# get the reporting rate for African Paradise Flycatcher in the Rift Valley
reporting_rate(df = raw_data, species_id = 682, start_date = '1970-01-01', 
  end_date = Sys.Date(), selected_area = "Rift Valley",
  selection_type = "Province")

Example 2: Graph the occurence of a species and fit the Underhill smoother

First we need to create the dataset with the smoothened values

# get the underhill smoothened data for African Paradise Flycatcher (across Africa)
analysis_df <- underhill_smoother(raw_data = raw_data, species_id = 682, start_month = 7,
  pentade_window = 3, first_pentade = 1, last_pentade = 73,
  selection_area = "Kenya", selection_type = "Country")

Once that's done, we'll just need to plug in those values into the plotting function. There are two plotting functions. underhill_single_curves generates plot for a single species and underhill_multiple_curves generate plots for multiple species. An example is given below.

# plot the curves
underhill_curves(underhill_smoother = analysis_df)