An Introduction to Camera Trap Data Management and Analysis in R
- Start Date: October 26, 2022
- End Date: November 02, 2022
- Time: Varies, see schedule below
- City: Revelstoke BC
- Venue: SD19's admin building: 501 – 11th Street, Revelstoke, BC
- Instructor: Dr. Chris Beirne
- Both courses are now full. To be added to the waitlist, contact [email protected] with the course (1 or 2) to which you would like your name added.
IMAGES: Robin Naidoo
The number of projects employing camera traps to understand ecological phenomena is growing rapidly – as are the number of statistical tools to analyze the resultant data. Consequently, the management and analysis of camera trap data can seem complex and overwhelming. This course aims to guide participants in effective ways to store, manipulate and analyze camera trap data within the R statistical environment.
It will cover data storage and exploration of best practices, introductions to the major methods used to analyze camera trap data, all using real world camera data. The course will give participants the tools to manage, analyze and share camera trap data in an approachable and practical way!
Course 1 Schedule:
Wed, Oct 26, 2022: 11am – 6pm
Thu, Oct 27, 2022: 8am – 4pm
Fri, Oct 28, 2022: 8am – 2pm
Registration for this course is full – waitlist available
Course 2 Schedule:
Wed, Oct 31, 2022: 11am – 6pm
Thu, Nov 1, 2022: 8am – 4pm
Fri, Nov 2, 2022: 8am – 2pm
Registration for this course is full – waitlist available
The following course objectives have informed the course itinerary – a copy of this detailed outline is available upon request:
- Introduce camera trap data standards and formatting
- Explain basic pre-processing workflows
- Introduce common routines for checking the quality of camera data and dealing with commonly encountered errors in real world data
- Give participant hands-on experience in using camera trap data to quantify:
- community composition
- single species habitat-use
- multi-species habitat-use
- activity patterns
- Discuss when and where other analytical approaches not covered by the course may be appropriate (e.g. occupancy, behaviour, species distribution, and structural equation models) and provide resources for further study
- Discuss the WildCAM initiative and other synthesis projects
Christopher Beirne has worked with camera traps for 10 years in North America, South America and Africa resulting in multiple scientific publications and technical reports. He has been using R on a near daily basis since 2011. He is currently a Postdoctoral researcher within the Wildlife Coexistence laboratory at the University of British Columbia and an active member of Camera Trap Network for Western Canada (WildCAM).
For those of you who attended our popular conference, Scaling Up Camera Trap Surveys to Inform Regional Wildlife Conservation, you’ll remember Chris as the lead facilitator for the workshop on how to perform robust exploration and analysis in R with camera trap data. Chris is also well known in CMI circles for his popular CREDtalk (season 5), which we recommend you watch prior to this course.
Who should take this course?
This course will be of interest to undergraduates, graduates, wildlife professionals, regional biologists, and interested communities/organizations in camera trapping methods and analysis.
Prerequisites, preparation and what to bring
To get the most out of this course students should be familiar with the basics of using R and R Studio. Experience with importing and exporting datasets, using “data frame” objects, and making basic plots (e.g. scatter plots and boxplots) will be beneficial. That said, all code will be provided and reproducible, so even students with minimal R experience will get a lot from the course!
Example camera trap data and course materials will be provided two weeks before the course start date.
Please come prepared to the course with:
- Laptop with the following programs installed
- R: https://www.r-project.org/
- R Studio Desktop: https://www.rstudio.com/products/rstudio/
- If participant have their own data, they should format it into the Wildlife Insights metadata standard format.
- *Optional but highly recommended* Watch Chris’ previous seminar delivered in season 5 of CMI’s CREDtalks. You can find that here
What is included with this course?
- Instruction, course manual, and other course materials
- Reproducible code to use on your own projects
- Coffee breaks with snacks!
- Participants will have the option of purchasing bagged lunches upon registration. If they choose not to, we suggest you bring your own lunch as there are limited options for quick lunches near the college where the course will take place
Bagged lunches $14/day, optional. Refreshments will be provided at the breaks as part of your registration fees. All food provided by La Baguette.
Limited class size of ~18 people, register immediately to secure your spot.
*Memberships may be purchased and renewed while you register. More about membership here.
Both courses are now full. You may request to join the waitlist for the course – Anyone on the waitlist will have the chance of filling registration cancellations as well as being the first to be notified when we open up registration for next season’s course. Please email firstname.lastname@example.org to be placed on the wait list.
Where to stay?
We have set up a discounted group rate at the Stoke Hotel of $94 + tax /night, or $109+tax /night for double queen room. Hot breakfast included, outdoor hot tub on site. When booking your room ask for the rate arranged by the “Columbia Mountains Institute.”
You may also like the Monashee Inn. Again, this isn’t anything fancy but it’s clean, affordable and easy walking distance from the college. We don’t have a room discount here, so inquire about rates via the website or telephone.
CMI will be following the guidelines provided by the Province of BC’s Public Health Authority to keep us all safe during the COVID19 Pandemic. See here for current protocols – all students must review this document before the field component of this course.
Our event partners
A big thanks to the WildCAM Network for all the work they do and for supporting this course.