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wildRtrax

An R package for environmental sensor data management and analytics.
https://github.com/ABbiodiversity/wildRtrax

Category: Biosphere
Sub Category: Bioacoustics and Acoustic Data Analysis

Keywords

bioacoustics biodiversity-data r-package

Keywords from Contributors

camera-traps

Last synced: about 9 hours ago
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Repository metadata

This is an R package that enables environmental sensor users to create comprehensive work flows for managing and analyzing data

README.md

wildrtrax

Lifecycle: stable CRAN status DOI Codecov test coverage

Overview

wildrtrax (pronounced wild-r-tracks) is an R package containing functions to help manage and analyze environmental sensor data to and from WildTrax. It helps to simplify the entire data life cycle by offering tools for data pre-processing, wrangling, and analysis.

Installation

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.

Usage

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.

Discover Data

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") |> 
  filter(Province == "Alberta") |> # A shapefile of Alberta
  st_transform(crs = 4326) |> 
  st_bbox()

wt_dd_summary(sensor = "ARU", species = "White-throated Sparrow", boundary = abbox)

Acoustic work flows

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)

# Login with your OAuth
Sys.setenv(WT_USERNAME = "*****", WT_PASSWORD = "*****")

# Authenticate to WildTrax
wt_auth()

# Get a project id
projects <- wt_get_projects("ARU") |>
  filter(project == "Ecosystem Health 2023") |>
  pull(project_id) |>
  wt_download_report(sensor_id = "ARU", reports = "main")

# Format to occupancy for OVEN
dat.occu <- wt_format_occupancy(data = 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 = TRUE) |>
              dplyr::mutate(hour = as.numeric(format(recording_date_time, "%H"))) |>
              dplyr::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(x = my_files, input_dir = ".../ap_outputs", purpose = "biotic", include_ldfcs = TRUE)

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()

my_reports <- wt_download_report(project_id = 1144, sensor_id = "ARU", reports = c("main", "ai"))
                           
eval <- wt_evaluate_classifier(data = my_reports, resolution = "task", remove_species = TRUE, thresholds = c(0.01,0.99))

e1 <- wt_classifier_threshold(eval) 

# Select the lowest threshold across classifiers and find additional species (false negatives)
wt_additional_species(my_reports, remove_species = TRUE, threshold = min(e1$threshold), resolution="task")

Camera work flows

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 camera project
raw <- wt_get_projects("CAM") |>
  filter(project == "ABMI Ecosystem Health 2014") |>
  pull(project_id) |>
  wt_download_report(sensor_id = "CAM", reports = "main")

# Get individual species detections using various thresholds and time ranges
individual_detections <- wt_ind_detect(x = raw, threshold = 30, units = "minutes")

Ultrasonic work flows

Format tags from Kaleidoscope for a WildTrax project. Download data from a project into an NABAT acceptable format.

library(wildrtrax)
library(tidyverse)

input <- ".../bat.csv" # A Kaleidoscope output file
output <- ".../bats" # A folder to store the formatted csv

wt_kaleidoscope_tags(input, output, freq_bump = T)

## Authenticate to WildTrax, then upload the tags to a WildTrax project
wt_auth()

# Get a project id
projects <- wt_get_projects("ARU") |>
  filter(project == "A bat project") |> # Enter your bat project name here
  pull(project_id) |>
  wt_download_report(sensor_id = "ARU", reports = "main")

Point count work flows

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", )

# An ARU project as point count format
aru_as_pc <- wt_download_report(project_id = 620, sensor_id = 'PC', reports = "main", )

Issues

To report bugs, request additional features, or get help using the package, please file an issue.

Contributors

We encourage ongoing contributions and collaborations to improve the package into the future. The Alberta Biodiversity Monitoring Institute provides ongoing support, development and funding.

License

This R package is licensed under MIT license©2025 Alberta Biodiversity Monitoring Institute.

Code of Conduct

Please note that wildrtrax is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

Citation (CITATION.cff)

# --------------------------------------------
# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# --------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "wildrtrax" in publications use:'
type: software
license: MIT
title: 'wildrtrax: Environmental Sensor Data Management and Analytics to and from
  WildTrax'
version: 1.5.0
abstract: This R package contains functions to help manage and analyze environmental
  sensor data to and from WildTrax.
authors:
- family-names: MacPhail
  given-names: Alex
  email: agmacpha@ualberta.ca
- family-names: Becker
  given-names: Marcus
  email: mabecker@ualberta.ca
- family-names: Knight
  given-names: Elly
  email: ecknight@ualberta.ca
url: https://abbiodiversity.github.io/wildrtrax/
contact:
- family-names: MacPhail
  given-names: Alex
  email: agmacpha@ualberta.ca
references:
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Name Email Commits
agmacpha a****a@u****a 679
Alexandre MacPhail a****l@A****l 83
Marcus Becker m****r@u****a 62
ecknight e****t@g****m 50
Alex MacPhail 3****a 31
vlucet v****t@g****m 15
github-actions[bot] 4****] 12
Clayton Lamb c****b@u****a 3
Cami Hurtado c****i@a****a 3
Sarah Endicott 3****4 2
Kevin Kelly k****y@u****a 2
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Dependencies

DESCRIPTION cran
  • R >= 3.5.0 depends
  • doParallel * imports
  • dplyr >= 1.0.0 imports
  • foreach * imports
  • fs * imports
  • furrr * imports
  • future * imports
  • httr * imports
  • lubridate * imports
  • pipeR * imports
  • plumber * imports
  • purrr * imports
  • rlang * imports
  • seewave * imports
  • shiny * imports
  • stringr * imports
  • tibble * imports
  • tidyr >= 1.0.2 imports
  • tools * imports
  • tuneR * imports
  • unmarked * imports
  • abmi.themes * suggests
  • knitr * suggests
  • rmarkdown * suggests
  • testthat * suggests
.github/workflows/R-CMD-check.yaml actions
  • actions/cache v2 composite
  • actions/checkout v2 composite
  • actions/upload-artifact main composite
  • r-lib/actions/setup-pandoc v1 composite
  • r-lib/actions/setup-r v1 composite
.github/workflows/pkgdown.yaml actions
  • actions/cache v2 composite
  • actions/checkout v2 composite
  • r-lib/actions/setup-pandoc v1 composite
  • r-lib/actions/setup-r v1 composite
.github/workflows/pr-commands.yaml actions
  • actions/checkout v2 composite
  • r-lib/actions/pr-fetch v1 composite
  • r-lib/actions/pr-push v1 composite
  • r-lib/actions/setup-r v1 composite
.github/workflows/test-coverage.yaml actions
  • actions/cache v2 composite
  • actions/checkout v2 composite
  • r-lib/actions/setup-pandoc v1 composite
  • r-lib/actions/setup-r v1 composite

Score: 5.700443573390686