Caribou Location Tracking

This data tracks woodland caribou in northern British Columbia, a Canadian province. It consists of almost 250,000 location tags of 260 caribou, from 1988 to 2016.

h/t to Alex Cookson for preparing this week’s data!

The tracking was part of a study prepared in 2014 by the B.C. Ministry of Environment & Climate Change to inform the management and recovery of the species, which is classified as “Vulnerable” on the International Union for the Conservation of Nature’s (IUCN) Red List.

The caribou range in North America/Canada is visualized courtesy of Wikipedia.

Data was accessed through Movebank, “a free online platform that helps researchers manage, share, analyze and archive animal movement data.”

Original article citation

BC Ministry of Environment (2014) Science update for the South Peace Northern Caribou (Rangifer tarandus caribou pop. 15) in British Columbia. Victoria, BC. 43 p. url:https://www2.gov.bc.ca/assets/gov/environment/plants-animals-and-ecosystems/wildlife-wildlife-habitat/caribou/science_update_final_from_web_jan_2014.pdf

Data package citation

Seip DR, Price E (2019) Data from: Science update for the South Peace Northern Caribou (Rangifer tarandus caribou pop. 15) in British Columbia. Movebank Data Repository. https://doi.org/10.5441/001/1.p5bn656k

Get the data here

# Get the Data

individuals <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/main/data/2020/2020-06-23/individuals.csv')
locations <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/main/data/2020/2020-06-23/locations.csv')

# Or read in with tidytuesdayR package (https://github.com/dslc-io/tidytuesdayR)

# Either ISO-8601 date or year/week works!

# Install via pak::pak("dslc-io/tidytuesdayR")

tuesdata <- tidytuesdayR::tt_load('2020-06-23')
tuesdata <- tidytuesdayR::tt_load(2020, week = 26)


individuals <- tuesdata$individuals

Data Dictionary

“Deployment” refers to when the animal was fitted with a location-tracking tag.

`individuals.csv`

variable	class	description
animal_id	character	Individual identifier for animal
sex	character	Sex of animal
life_stage	character	Age class (in years) at beginning of deployment
pregnant	logical	Whether animal was pregnant at beginning of deployment
with_calf	logical	Whether animal had a calf at time of deployment
death_cause	character	Cause of death
study_site	character	Deployment site or colony, or a location-related group such as the herd or pack name
deploy_on_longitude	double	Longitude where animal was released at beginning of deployment
deploy_on_latitude	double	Latitude where animal was released at beginning of deployment
deploy_on_comments	character	Additional information about tag deployment
deploy_off_longitude	double	Longitude where deployment ended
deploy_off_latitude	double	Latitude where deployment ended
deploy_off_type	character	Classification of tag deployment end (see table below for full description)
deploy_off_comments	character	Additional information about tag deployment end

deploy_off_type classifications

deploy_off_type	description
captured	Tag remained on the animal but the animal was captured or confined
dead	Deployment ended with the death of the animal that was carrying the tag
equipment failure	Tag stopped working
fall off	Attachment of the tag to the animal failed, and it fell of accidentally
other	Catch-all category for other deployment end types
released	Tag remained on the animal but the animal was released from captivity or confinement
removal	Tag was purposefully removed from the animal
unknown	Deployment ended by an unknown cause

`locations.csv`

variable	class	description
event_id	double	Identifier for an individual measurement
animal_id	character	Individual identifier for animal
study_site	character	Deployment site or colony, or a location-related group such as the herd or pack name
season	character	Season (Summer/Winter) at time of measurement
timestamp	datetime	Date and time of measurement
longitude	double	Longitude of measurement
latitude	double	Latitude of measurement

Cleaning Script

# Load libraries
library(tidyverse)
library(janitor)

# Import data
individuals_raw <- read_csv("./caribou-location-tracking/raw/Mountain caribou in British Columbia-reference-data.csv")
locations_raw <- read_csv("./caribou-location-tracking/raw/Mountain caribou in British Columbia-gps.csv")

# Clean individuals
individuals <- individuals_raw %>%
  clean_names() %>%
  transmute(animal_id,
            sex = animal_sex,
            # Getting rid of whitespace to address inconsistent spacing
            # NOTE: life stage is as of the beginning of deployment
            life_stage = str_remove_all(animal_life_stage, " "),
            reproductive_condition = animal_reproductive_condition,
            # Cause of death "cod" is embedded in a comment field
            death_cause = str_remove(animal_death_comments, ".*cod "),
            study_site,
            deploy_on_longitude,
            deploy_on_latitude,
            # Renaming to maintain consistency "deploy_on_FIELD" and "deploy_off_FIELD"
            deploy_on_comments = deployment_comments,
            deploy_off_longitude,
            deploy_off_latitude,
            deploy_off_type = deployment_end_type,
            deploy_off_comments = deployment_end_comments) %>%
  # reproductive_condition actually has two dimensions
  separate(reproductive_condition, into = c("pregnant", "with_calf"), sep = ";", fill = "left") %>%
  mutate(pregnant = str_remove(pregnant, "pregnant: ?"),
         with_calf = str_remove(with_calf, "with calf: ?")) %>%
  # TRUE and FALSE are indicated by Yes/No or Y/N
  mutate_at(vars(pregnant:with_calf), ~ case_when(str_detect(., "Y") ~ TRUE,
                                                   str_detect(., "N") ~ FALSE,
                                                   TRUE ~ NA))

# Clean locations
locations <- locations_raw %>%
  clean_names() %>%
  transmute(event_id,
            animal_id = individual_local_identifier,
            study_site = comments,
            season = study_specific_measurement,
            timestamp,
            longitude = location_long,
            latitude = location_lat)

# Write to CSV
write_csv(individuals, "./caribou-location-tracking/individuals.csv")
write_csv(locations, "./caribou-location-tracking/locations.csv")