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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

species-distribution-models camera-traps landscape-ecology control routing virtual transform crop report simulations

Last synced: about 1 hour 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. 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.

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") |> # Shapefile of Alberta
  filter(Province == "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)

# 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 == "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_classifier_threshold(eval)

# Find additional species
wt_additional_species(data, remove_species = TRUE, threshold = threshold_use, 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 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")

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.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')

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", 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)

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©2024 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: 1.3.3
abstract: This R package enables users of environmental sensors to create comprehensive
  workflows for managing and analyzing data associated with WildTrax
authors:
- family-names: MacPhail
  given-names: Alex
  email: [email protected]
- family-names: Becker
  given-names: Marcus
  email: [email protected]
- family-names: Knight
  given-names: Elly
  email: [email protected]
url: https://abbiodiversity.github.io/wildrtrax/
contact:
- family-names: MacPhail
  given-names: Alex
  email: [email protected]
references:
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    orcid: https://orcid.org/0000-0002-2444-4226
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    given-names: Lionel
  - family-names: Müller
    given-names: Kirill
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  - family-names: Vaughan
    given-names: Davis
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    given-names: Jim
  - family-names: Wickham
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  - family-names: Csárdi
    given-names: Gábor
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  abstract: 'ggplot2: Create Elegant Data Visualisations Using the Grammar of Graphics'
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  url: https://ggplot2.tidyverse.org
  repository: https://CRAN.R-project.org/package=ggplot2
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    given-names: Hadley
    email: [email protected]
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    orcid: https://orcid.org/0000-0002-1576-2126
  - family-names: Henry
    given-names: Lionel
  - family-names: Pedersen
    given-names: Thomas Lin
    email: [email protected]
    orcid: https://orcid.org/0000-0002-5147-4711
  - family-names: Takahashi
    given-names: Kohske
  - family-names: Wilke
    given-names: Claus
    orcid: https://orcid.org/0000-0002-7470-9261
  - family-names: Woo
    given-names: Kara
    orcid: https://orcid.org/0000-0002-5125-4188
  - family-names: Yutani
    given-names: Hiroaki
    orcid: https://orcid.org/0000-0002-3385-7233
  - family-names: Dunnington
    given-names: Dewey
    orcid: https://orcid.org/0000-0002-9415-4582
  - family-names: Brand
    given-names: Teun
    name-particle: van den
    orcid: https://orcid.org/0000-0002-9335-7468
  year: '2025'
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  abstract: 'httr2: Perform HTTP Requests and Process the Responses'
  notes: Imports
  url: https://httr2.r-lib.org
  repository: https://CRAN.R-project.org/package=httr2
  authors:
  - family-names: Wickham
    given-names: Hadley
    email: [email protected]
  year: '2025'
  doi: 10.32614/CRAN.package.httr2
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  abstract: 'magick: Advanced Graphics and Image-Processing in R'
  notes: Imports
  url: https://docs.ropensci.org/magick/
  repository: https://CRAN.R-project.org/package=magick
  authors:
  - family-names: Ooms
    given-names: Jeroen
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    orcid: https://orcid.org/0000-0002-4035-0289
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  abstract: 'purrr: Functional Programming Tools'
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  url: https://purrr.tidyverse.org/
  repository: https://CRAN.R-project.org/package=purrr
  authors:
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    given-names: Hadley
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  url: https://rspatial.org/
  repository: https://CRAN.R-project.org/package=terra
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  - family-names: Hijmans
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  repository: https://CRAN.R-project.org/package=tidyr
  authors:
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Alex MacPhail 3****a 31
vlucet v****t@g****m 15
github-actions[bot] 4****] 10
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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: 5.480638923341991