- This event has passed.
Aquatic Acoustic Telemetry Data Analysis (ATDA01)
28th January 2019 - 1st February 2019
£275.00 – £510.00
Event Date
Monday, January 28th, 2019
Course Format
This is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link, a good internet connection is essential.
Course Program
TIME ZONE – UTC+2 – however all sessions will be recorded and made available allowing attendees from different time zones to follow a day behind with an additional 1/2 days support after the official course finish date (please email oliverhooker@prstatistics.com for full details or to discuss how we can accommodate you).
Course Details
In this course you will learn about the different types of Vemco acoustic telemetry technology and their applicability for use in different study environments and in answering a variety of research questions. Advantages and limitations of the different types of equipment will be discussed, along with resulting study design considerations such as hardware selection and tag programming considerations.
The planning and testing phases of any acoustic telemetry study are critical to success, and you will learn about the importance of testing the suitability of your environment for acoustic telemetry, testing your array once it is deployed, and monitoring your system performance throughout the duration of your study. We will analyze an example range test dataset and discuss the implications of range test results on array design. You will also learn how to test your study deployment in the field and what metrics are best used to determine whether the array is operating as planned. Finally, because interpretation of acoustic telemetry data and inferring animal behaviour from these data is often confounded by array performance questions, this course will teach you techniques for assessing system performance to aid in the correct interpretation of animal detection data.
Since telemetry datasets are growing larger all of the time, data management is becoming increasingly challenging. During this course you will learn to perform basic quality assurance on your data (removal of false detections, time correction of detection data) and basic filtering techniques (identifying residency events, removing duplicate detections) for large datasets.
Finally, this course will include extensive discussion of the proper design and logistics of fine-scale positioning studies and will provide an overview of the different types of analyses that are commonly performed with positional data. You will also have the opportunity to discuss your own telemetry studies with the experts during a Q&A session on the final day of the course. Bring your own data and your questions!
Intended Audiences
Venue
Venue – PR statistics head office, 53 Morrison Street, Glasgow, G5 8LB – Google map
Course Information
Duration – 5 days
Contact hours – Approx. 35 hours
ECT’s – Equal to 3 ECT’s
Language – English
Packages
We offer COURSE ONLY and ACCOMMODATION PACKAGES;
• COURSE ONLY – Includes lunch and refreshments.
• ACCOMMODATION PACKAGE (to be purchased in addition to the course only option) – Includes breakfast, lunch, welcome dinner Monday evening, farewell dinner Thursday evening, refreshments and accommodation. Self catering facilities are available in the accommodation. Accommodation is approx. a 6 minute walk form the PR statistics head office. Accommodation is multiple occupancy (max 3-4 people) single sex en-suite rooms. Arrival Sunday 27th January (after 5pm) and departure Friday 1st February (accommodation must be vacated by 9am). An additional nights accommodation can be purchased, departure 9am Friday morning email for details.
To book ‘COURSE ONLY’ with the option to add the additional ‘ACCOMMODATION PACKAGE’ please scroll to the bottom of this page.
Other payment options are available please email oliverhooker@prstatistics.com
Cancellation policy: Cancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered, contact oliverhooker@prstatistics.com Failure to attend will result in the full cost of the course being charged. In the unfortunate event that PRstatistics must cancel this course due to unforeseen circumstances a full refund for the course will be credited. However PRstatistics cannot be held responsible for any travel fees, accommodation or other expenses incurred to you as a result of the cancellation.
Teaching Format
Assumed quantitative knowledge
A good understanding of statistical concepts. Specifically, statistical significance and hypothesis testing and the basic ideas of probability and likelihood.
Assumed computer background
At entry you should make sure that you have a working knowledge of: Basic R usage (command-line interactive, generation of graphs); Manipulation of data-frames in R; Regression modelling (linear, generalised linear & mixed effects models). In addition, you should have had some exposure to: Programming structures (loops, conditional statements).
Equipment and software requirements
A laptop/personal computer with a working version or R, RStudio and JAGS installed. R, RStudio and JAGS are supported by both PC and MAC and can be downloaded for free by following these links.
https://cran.r-project.org/
Download RStudio
http://mcmc-jags.sourceforge.net
Further information on interfacing JAGS and R using the runjags package can be found from the following website: http://runjags.sourceforge.net/.
It is essential that you come with all necessary software and packages already installed (you will be sent a list of packages prior to the course) internet access may not always be available.
UNSURE ABOUT SUITABLILITY THEN PLEASE ASK oliverhooker@prstatistics.com
Assumed quantitative knowledge
Coming soon..
Assumed computer background
Coming soon..
Equipment and software requirements
Attendees will need to install/update R/RStudio and various additional R packages.
This can be done on Macs, Windows, and Linux.
R – https://cran.r-project.org/
RStudio – https://www.rstudio.com/products/rstudio/download/
PLEASE READ – CANCELLATION POLICY
Cancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited.
COURSE PROGRAMME
Sunday 27th
Meet at Flat 2/1, 43 Cook Street, Glasgow G5 8JN at approx. 17:00 onwards
Monday 28th – Classes from 09:30 to 17:30
Lecture 1
1) Introduction to Acoustic Telemetry
Acoustic vs radio, satellite, PIT tags
History of acoustic telemetry
Comparison of acoustic technologies from different manufacturers
2) How Vemco acoustics work
Continuous vs coded vs HR (High Residence) transmission systems
Pinger tags vs sensor tags
3) Vemco Equipment Overview
Applications of 69 kHz line
Applications of 180 kHz line
Applications of HR (High Residence) technology
4) Designing a Successful Study
Hardware Selection
Tag Programming Considerations
Range Testing
Using Sentinel Tags
5) Vemco Equipment Demo
PPM vs HR coding systems
Surgery techniques
Tuesday 29th – Classes from 09:30 to 17:30
Lecture 2
1) Preparing for Deployment
Preparing your receivers
Initialization tips
Setting up built-in transmitters
2) System performance considerations
Quiet vs noisy locations
Thermoclines
River flow considerations
Mooring design and receiver attachment
3) Testing your deployment
Using transponding data (includes transponding demonstration)
Using offloaded test data/VUE (includes demonstration)
Important considerations during testing
Practical 1
4) Case Study 1 – River migration study (traditional PPM coding example)
Study Design
Range test analysis example
Determining receiver spacing
Tag Programming
Wednesday 30th – Classes from 09:30 to 17:30
1) Practical 2
Data Management (using Case Study 1 data or other example datasets
Assigning stations in VUE
Time Correction
Identifying false detections
Using VUE’s FDA tool
Marking questionable detections in your exported data
2) Filtering your data
Building filters in VUE
Identifying residency events
What to do with duplicate detections
Sensor Tag Data
Bringing in sensor metadata (.VXM) files
How to handle data from sensor tags with multiple IDs
System Performance Assessment using R1
Using detection data
Using ping data
Using receiver sensor / diagnostic data
Data Analysis
Calculating gate detection probabilities
Calculating swimming speeds
Animating your animal movement data
Thursday 31st – Classes from 09:30 to 17:30
Lecture 3
1) Introduction to High Residence technology
VPS (PPM and HR)
Theory (how VPS works)
Special deployment considerations
Special considerations for testing your array
Practical 4
2) Case Study 2 – VPS o Study Design
Range test analysis example Determining receiver spacing
Tag Programming
Testing the array – how do I know my VPS will work?
Data Analysis
Visualizing animal position data
Home Range example
Friday 1st – Classes from 09:30 to 16:00
Practical 5
1) Case Study 3
VPS using High Residence (HR) technology
Lecture 4
2) Summary – what have we learned?
Challenges specific to analyzing telemetry data
Practical 6
3) Discuss your work!
Opportunity for course participants to discuss their work with the group and seek advice
Course Instructor
Dr. Antoine Becker-Scarpitta
Works at – University of Helsink
Teaches – Multivariate analysis of ecological communities in R with the VEGAN package (VGNR03)
Antoine is a plant community ecologist working as a postdoctoral researcher at the University of Helsinki and as a postdoctoral fellow at the Institute of Botany of the Academy of the Czech Republic. Antoine holds a degree in Conservation Biology from the University of Paris-Sud-Orsay, and from the Natural History Museum of Paris, he obtained his PhD in Biology/Ecology from the University of Sherbrooke (Canada). Antoine’s research focuses on the temporal dynamics of biodiversity with a particular focus on the forest and Arctic vegetation. Antoine has taught community ecology, plant ecology and evolution, linear and multivariate statistics assisted on R.