Wrangling In The Antipodes (WITA)

https://wranglingintheantipodes.wordpress.com/

WITA is a blog maintained by Tristan Louth-Robins to explore acoustic ecology with data science tools.

This repo includes scripts, some datasets and other resources relevant to research covered on the blog. Not everything published to the blog is featured here yet, I'm in the process of doing this though.

--- Latest update: 15/3/2024 ---

"14. Introduction to the Acoustic Diversity Index (ADI)" - published 15/03/2024

URL: https://wranglingintheantipodes.wordpress.com/](https://wranglingintheantipodes.wordpress.com/2024/03/15/introduction-to-the-acoustic-diversity-index-adi/

"13. Return to Lady Bay: Part 1 - Tides, seagrass and acoustic complexity" - published 14/04/2023

URL: https://wranglingintheantipodes.wordpress.com/2023/04/14/return-to-lady-bay-part-1-tides-and-seagrass-exploration/

WITA_13-EDA_pt1.R

• R script using tidyverse, ggplot and related package to analyse tidied dataset of pre-processed Acoustic Complexity (ACI) values from deployed AudioMoth in reef location. Analysis explores the acoustic complexity values present in a seagrass meadow located in a shallow tidal pool. The script for pre-processing the acoustic data can be found in the 'AudioMoth - General scripts' section of this README file.**

"12. Acoustic Complexity as an indicator of tidal activity" - published 19/12/2022

URL: https://wranglingintheantipodes.wordpress.com/2022/12/19/acoustic-complexity-as-an-indicator-of-tidal-activity/

WITA_12-EDA_ladybay.R

• R script using tidyverse, ggplot and related packages to analyse tidied dataset of pre-processed Acoustic Complexity (ACI) values from deployed AudioMoth in reef location. Analysis explores potential association between ACI and tidal activity over 22-hour period of deployment. The dataset can be found in the /datasets directory. The script for pre-processing the acoustic data can be found in the 'AudioMoth - General scripts' section of this README file.**

"11. Acoustic detection in monitoR – an overview" - published 10/8/2022

URL: https://wranglingintheantipodes.wordpress.com/2022/08/10/acoustic-detection-in-monitor-an-overview/

WITA_11-intro_to_monitoR.R

• R script for using monitoR package to generate correlation templates and perform analysis. Note: acoustic data is not provided and the user will have to supply their own data.

"10. NDSI: parameters in context" - published 9/4/2022

URL: https://wranglingintheantipodes.wordpress.com/2022/04/09/ndsi-parameters-in-context/

WITA_10-NDSI_params_in_context.R

• R script for exploring NDSI data within a research context. The code permits the user to recreate the EDA and visualisations featured in the published post. WITA_10-dataset.csv
• Dataset to be used in conjunction with the above R code.

"8. Preparing big audio files for analysis" - published 20/10/2021

URL: https://wranglingintheantipodes.wordpress.com/2021/10/20/preparing-big-audio-files-for-analysis/

WITA_08-label_data.R

• R script for generating label data in conjunction with Audacity.

AudioMoth - General scripts

WITA_G-audiomoth_compute_indices_and_tidy_data.R Version history: 2.0 - all three steps now in single script. 2.5 - fixed the error in factorisation turning all month variables into a 'Summer' category. 2.6 - cleaned up file import code, cleaner and more efficient. 2.7 - new function for user input of site variable. 2.8 - (9th July 2023): feature to create directory/folder for outputted results 2.81 - (10th July 2023): code tidy 2.9 - (2nd March 2024): code tidy, extensive testing with single datasets and extended params specific to given indices. 2.91 - (8th June 2024): error fix to compute_indices function 3.0 - (14th June 2024): cleaned up script to accomodate more flexible usibility.

• R script which can be used in conjunction with AudioMoth acoustic data. Contains functions which will perform the following workflow:

1. Compute user-defined acoustic indicies specific to the R package acousticecology and export the results as a .csv dataset.
2. Tidy data function and call to import the .csv dataset and tidy/factorise variable data.
3. Write tidy data to updated .csv file for subsequent EDA.

26/12/22: No current issues in this script.