wildrtrax (pronounced wild-r-tracks) is an R package containing functions to help manage and analyze environmental sensor data. It helps to simplify the entire data life cycle by offering tools for data pre-processing, wrangling, and analysis, facilitating seamless data transfer to and from WildTrax. With wildrtrax, users can effortlessly establish end-to-end workflows and ensure reproducibility in their analyses. By providing a consistent and organized framework, the package promotes transparency and integrity in research, making it effortless to share and replicate results.
You can install the most recent version of wildrtrax directly from this repository with:
# install.packages("remotes")
remotes::install_github("ABbiodiversity/wildrtrax")The development version of this package contains experimental features and recent fixes. It can be installed with:
remotes::install_github("ABbiodiversity/wildrtrax@development")The development version of the package will be periodically merged and will be reflected in the Changelogs.
All functions begin with a wt_* prefix. Column names and metadata align with the WildTrax infrastructure. The goal is to follow the work flow of pre-processing, linking with WildTrax, download and analysis.
Explore data through Data Discover. No login required to access public data! Use wt_auth() to login to see data you have privileges and membership to.
library(wildrtrax)
library(sf)
# Search for public data without a boundary
wt_dd_summary(sensor = 'ARU', species = 'White-throated Sparrow')
# Apply an area of interest. Define a polygon or use a bbox from sf::st_bbox
my_aoi <- list(
c(-113.96068, 56.23817),
c(-117.06285, 54.87577),
c(-112.88035, 54.90431),
c(-113.96068, 56.23817)
)
wt_dd_summary(sensor = 'ARU', species = 'White-throated Sparrow', boundary = my_aoi)
# Alberta bounding box
abbox <- read_sf("...shp") |> # Shapefile of Alberta
filter(Province == "Alberta") |>
st_transform(crs = 4326) |>
st_bbox()
wt_dd_summary(sensor = "ARU", species = "White-throated Sparrow", boundary = abbox)Download data and run and a single-season single-species occupancy analysis. Consult APIs and Acoustic data wrangling for more information.
library(wildrtrax)
library(tidyverse)
# OAuth logins only. Google OAuth2 will be supported soon.
Sys.setenv(WT_USERNAME = "*****", WT_PASSWORD = "*****")
# Authenticate to WildTrax
wt_auth()
# Get a project id
projects <- wt_get_download_summary("ARU") |>
filter(project == "ABMI Ecosystem Health 2023") |>
select(project_id) |>
pull()
# Download the main report
raw_data <- map_dfr(.x = projects, .f = ~wt_download_report(.x, "ARU", weather_cols = F, reports = "main"))
# Format to occupancy for OVEN
dat.occu <- wt_format_occupancy(raw_data, species="OVEN", siteCovs=NULL)
# Run the model
unmarked::occu(~ 1 ~ 1, dat.occu)Conduct some pre-processing on various types of acoustic data. See more in Acoustic pre-processing.
library(wildrtrax)
library(tidyverse)
# Scan files and filter results
my_files <- wt_audio_scanner(path = ".", file_type = "wav", extra_cols = T) |>
mutate(hour = as.numeric(format(recording_date_time, "%H"))) |>
filter(julian == 176, hour %in% c(4:8))
# Run acoustic indices and LDFCs
wt_run_ap(x = my_files, output_dir = paste0(root, 'ap_outputs'), path_to_ap = '/where/you/store/AP')
wt_glean_ap(my_files, input_dir = ".../ap_outputs", purpose = "biotic")Evaluate the performance of BirdNET on a project, and search for false negatives missed by human taggers. See Classifiers Tutorial for more information.
library(wildrtrax)
library(tidyverse)
# OAuth logins only. Google OAuth2 will be supported soon.
Sys.setenv(WT_USERNAME = "*****", WT_PASSWORD = "*****")
# Authenticate to WildTrax
wt_auth()
data <- wt_download_report(project_id = 1144, sensor_id = "ARU", reports = c("main", "birdnet"), weather_cols = FALSE)
eval <- wt_evaluate_classifier(data, resolution = "task", remove_species = TRUE, thresholds = c(10, 99))
threshold_use <- wt_get_threshold(eval)
# Find additional species
wt_additional_species(data, remove_species = TRUE, threshold = threshold_use, resolution="task")The ultimate pipeline for your camera data work flows. See Camera data wrangling for more information.
library(wildrtrax)
library(tidyverse)
# OAuth logins only. Google OAuth2 will be supported soon.
Sys.setenv(WT_USERNAME = "*****", WT_PASSWORD = "*****")
# Authenticate to WildTrax
wt_auth()
# Get a project id
projects <- wt_get_download_summary("CAM") %>%
filter(project == "ABMI Ecosystem Health 2014") %>%
select(project_id) %>%
pull()
# Download data
raw <- map_dfr(.x = projects, .f = ~wt_download_report(.x, "CAM", weather_cols = F, reports = "main"))
# Get individual detections
individual_detections <- wt_ind_detect(raw, 30, "minutes")Format tags from Kaleidoscope for a WildTrax project. Download data from a project into an NABAT acceptable format.
library(wildrtrax)
library(tidyverse)
input <- ".../bat.txt" # Kaleidoscope output
output <- ".../bats" # A folder to store the tags
wt_kaleidoscope_tags(input, output, tz, freq_bump = T) # Add a frequency buffer to the tag, e.g. 20000 kHz
## Upload the tags to a WildTrax project, then authenticate to WildTrax
wt_auth()
# Get a project id
projects <- wt_get_download_summary("ARU") |>
filter(project == "BATS & LATS") |>
select(project_id) |>
pull()
# Download the data
raw_data <- map_dfr(.x = projects, .f = ~wt_download_report(.x, "ARU", weather_cols = F, reports = "main"))
# Experimental
raw_data |>
wt_format_data(format = 'NABAT')Download combined and formatted acoustic and point count data sets together.
library(wildrtrax)
library(tidyverse)
# An ARU project
an_aru_project <- wt_download_report(project_id = 620, sensor_id = 'ARU', reports = "main", weather_cols = F)
# An ARU project as point count format
aru_as_pc <- wt_download_report(project_id = 620, sensor_id = 'PC', reports = "main", weather_cols = F)To report bugs, request additional features, or get help using the package, please file an issue.
We encourage ongoing contributions and collaborations to improve the package into the future. The Alberta Biodiversity Monitoring Institute provides ongoing support, development and funding.
This R package is licensed under MIT license©2024 Alberta Biodiversity Monitoring Institute.
Please note that wildrtrax is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.