DFO & OTN Acoustic Telemetry Workshop

This one-day workshop begins with an overview of OTN and its role in aggregating telemetry data, an introduction to taking your records from fieldnotes to analysis ready data sets, and where when and how to submit data and metadata to OTN. In the second session, you will be introduced to exploring and plotting acoustic telemetry data in R using dplyr and ggplot. The third session offers a brief overview of the glatos R package for performing some of these same tasks using standard functions, and in the final session, you’ll get an introduction to statistical analysis of animal behavioural states using Hidden Markov models and the moveHMM R package.

Powerpoint

Schedule

	Setup	Download files required for the lesson
00:00	1. Collaborating with OTN - Advantages and Best Practices	What is the Ocean Tracking Network? How do I take my records from fieldnotes to analysis ready data sets? Where, when, and how do I submit data and metadata to OTN?
00:30	2. Base R functions vs. Tidyverse	How can I introspect, subset, and plot my data using base R? How do I reformat dates as ‘strings’ into date objects? What are the Tidyverse functions that will do the same tasks?
00:45	3. Making basic plots using ggplot	How do I make more sophisticated plots in ggplot?
01:05	4. Loading, formatting, and plotting spatial data objects	How do I plot my data on a map if my coordinates aren’t in latitude and longitude? Where can I find environmental data for my study area (like bathymetry)?
01:25	5. More Tidyverse functions useful for telemetry data analysis	What dplyr functions are useful to analyze my data? What are some example workflows for analyzing telemetry datasets
01:40	6. Network analysis using detections of animals at stations	How do I prepare my data in order to apply network analysis?
01:55	7. Animating ggplot with gganimate and gifski	How do I animate my tracks?
02:05	8. Introduction to GLATOS Data Processing	How do I load my data into GLATOS? How do I filter out false detections? How can I consolidate my detections into detection events? How do I summarize my data?
02:35	9. Basic Visualization and Plotting
03:05	10. Basic Animations
03:35	11. Basic Tag and Receiver Simulations using GLATOS
04:05	12. Fitting Hidden Markov Models with moveHMM	What can applying hidden markov models to my movement data using moveHMM tell me about the behaviour of my animals?
04:35	13. Accounting For ACF
05:05	14. Choosing Between Numbers of States
05:35	Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.