34 Bat Echolocation

34.1 Introduction

Echolocation call data for 4 species of Vancouver Island bats (https://bcbats.ca/bat-basics/bat-species-in-bc/). Call data comprises 30 unique records for 4 echolocation call parameters for each of the bat species. Call data was recorded using an ultrasonic bat detector (Anabat; Titley Scientific https://www.titley-scientific.com/) with call parameters downloaded and extracted using AnaLook.

For this project, explore the data using the inspiration provided by the penguin analysis (below).

34.1.1 Data source

Variables:

Species

EPFU - Eptesicus fuscus; Big Brown Bat

LACI - Lasiurus cinereus; Hoary Bat

MYLU - Myotis lucifugus; Little Brown Bat

MYVO - Myotis volans; Long-legged Myotis

Filename - Unique ID for each bat call

Echolocation Call Paramters:

Time_Btw_Calls - Time between calls (milliseconds)

Duration - Duration of the body of call (milliseconds)

Frequency - Characteristic frequency (kHz)

Slope - Characteristic slope (the change in frequency, divided by the duration of the call)

Source: Dr. Joanna Burgar; https://github.com/joburgar/Bat_Data

34.1.2 Additional Inspiration

The R package {palmerpenguins} reference page has some tabulations and visualizations that may provide some inspiration:

34.2 Other resources

Information on recording bat calls

Montana Bat Call Identification—this slide deck goes a lot deeper into bat calls.

  • slide 10 has details about the elements that are recorded

Statistical analysis of bat calls

David W. Armitage and Holly K. Ober, A comparison of supervised learning techniques in the classification of bat echolocation calls, Ecological Infomatics, 2010, 5, 465:473.

Xing Chen, Jun Zhaob, Yan-hua Chen, Wei Zhoub, and Alice C.Hughes, Automatic standardized processing and identification of tropical bat calls using deep learning approaches, Biological Conservation, January 2020, Vol.241, doi: 10.1016/j.biocon.2019.108269

Oisin MacAodha, Rory Gibb, Kate E. Barlow, et al., Bat detective—Deep learning tools for bat acoustic signal detection, PLOS Computational Biology, 2018-03-08, doi: 10.1371/journal.pcbi.1005995

Keisuke Masuda, Takanori Matsui, Dai Fukui, et al., Bat species classification by echolocation call using a machine learning system, Honyurui Kagaku (Mammalian Science), Volume 57 (2017) Issue 1. doi: 10.11238/mammalianscience.57.19

Peter Ommundsen,Cori Lausen, Laura Matthias, First Acoustic Records of the Brazilian Free-Tailed Bat (Tadarida brasiliensis) In British Columbia, September 2017, Northwestern Naturalist, 98(2):132-136, DOI: 10.1898/NWN16-24.1

Veronica Zamora-Gutierrez, Celia Lopez-Gonzalez, M. Cristina MacSwiney Gonzalez, et al., Acoustic identification of Mexican bats based on taxonomic and ecological constraints on call design, Methods in Ecology and Evolution 2016, 7, 1082–1091. doi: 10.1111/2041-210X.12556

Other bat communication

Jason Daley, Researchers “Translate” Bat Talk. Turns Out, They Argue—A Lot, Smithsonian Magazine, 2016-12-22.

-30-