Motion Detected: WildCAM is back!
Membership updates, paper summaries, feral pigs, and everything in between.
Hello WildCAM Members,
Welcome to WildCAM’s first newsletter for the year! As you may have noticed, we’ve moved over to Substack to deliver our newsletters since we heard that some of you weren’t receiving our newsletters through MailChimp. You can continue finding our upcoming newsletters both here in your inbox and at wildcam.substack.com. Our past newsletter can be found on our website. I was going to send this yesterday but decided that April Fools’ Day was not the best to begin a comeback.
We’ve changed since you last heard from us. WildCAM is now administered by the UBC Wildlife Coexistence Lab, and we thank the BC Parks Foundation for their important work in helping to administer the network in its nascent years. In the coming weeks, we will also be updating our website (wildcams.ca), and are looking forward to working on a number of exciting initiatives (stay tuned).
WildCAM’s core mission framework remains the same. We are committed to improving and communicating the science of camera trapping and wildlife monitoring, and with your help, we look forward to advancing stewardship of wildlife for all.
Thank you for your continued support, and please reach out to us in case of any queries at info@wildcams.ca.
Raunaq Nambiar, WildCAM Coordinator
⚠️ Membership Check-in ⚠️
It’s been a while since we’ve spoken—how’s it going?
✅ Task 1 [Mandatory] — Membership Status Update
Please find linked here a membership check-in form (you will have already received this form if you are an existing member of WildCAM — if you aren’t a member yet, you can sign up here). 5 minutes is all I need, I promise! You can ignore this if you have already filled out this form.
🔄 Task 2 [Still Important] — Project Update
We’re getting the website up to date! If you have a project on wildcams.ca (and you can get in touch with me if you’re not sure), please update them by using the project update form with which I can update the contents of your project page!
We’ve added some new sections to the Project page to make it more informative (you can now add your project’s website and associated publications to the project page!). See the Cathedral Provincial Park Mammal Monitoring Program as an example.
🎁 Task 3 [Pretty Please?] — Membership Wishlist
This is the part where you talk and I listen! What do you want to see from WildCAM? Whether a few words or an essay, send them along and let me get started on them at info@wildcams.ca.
Project Spotlight 🌟
Kootenay Density Project
Applied Conservation Macro Ecology (ACME) Lab | Wildlife Coexistence Lab
“Density rules!” — Jamie Clarke, MSc Candidate
Those of you who have followed WildCAM for a while might remember me – I was the Wildlife Data Coordinator in 2022, and wrote the WildCAM density handbook! 👋 Hello again!
A little update on where that project has brought me…
I started my Masters at the University of Victoria in September 2023 with Dr Jason Fisher in the ACME Lab. My thesis work is a continuation of the handbook, which asked: how can we estimate population density with camera traps? Now, we’re moving from theory to practice and testing camera trap density models in the field, with an eye to improving the science guiding wildlife management.
In collaboration with the head of WildCo, Dr Cole Burton, Provincial Ungulate Specialist Holger Bohm, and UVic stats specialist Dr Laura Cowen, I’m testing the spatial count model on moose in the Flathead river valley, southeast of Fernie, BC. Spatial count is an extension of the spatial capture-recapture model that doesn’t require us to individually identify animals.
I spent last spring and summer generating an optimal camera trap sampling design (check out this paper and bookdown for more info – it’s so cool) and deploying 50 cameras in the field (with help from Stu Clow, Alexia Constantinou and Emerald Arthurs – thanks heaps!). I’ll be heading back out in a few months to check cameras and, fingers crossed, collect some incredible moose pictures!
Our plan is to compare spatial count-derived moose density estimates with aerial moose surveys that overlap in space and time. That way, we can assess whether spatial count estimates are ecologically feasible, and evaluate the relative robustness of each method.
This project, and my collaborators, are near and dear to my heart. I’m so grateful for my time at WildCAM and am over the moon I get to continue that work in my graduate degree. Density rules!
Seen a Pig Lately? 🐷
Early detection is key in stemming invasive species growth. This is why the Invasive Species Council of BC (ISCBC) is looking to WildCAM’s network and projects to complement their upcoming early-detection feral pig camera trap network in northern BC.
How can you help?
Detected a feral pig (Sus scrofa) in your network of cameras? Report it!
You can report your sightings to any of the following locations:
Invasive Species Council of BC (info@bcinvasives.ca)
Torin Kelly at ISCBC (tkelly@bcinvasives.ca)
These detections don’t have to be from northern BC, and detections across the province all count!
We Asked, You Answered 📣
In the last newsletter, we introduced a new initiative, the Remote Camera Decision Support Tool, developed by the Alberta Remote Camera Steering Committee (AB RCSC) to help guide users through choices encountered when designing a remote camera study, suggest design choices, and provide related resources. Phase 1.0 will be released in May 2025!
For this tool, we asked you to complete a brief questionnaire to evaluate the usefulness of resources created by the AB RCSC and for your input on the Remote Camera Decision Support Tool. We also held our first round of focus groups.
Here are the results (🥁 drum roll, please)
☑️ Participation Metrics
15 — number of survey responses (40% Academia, 34% Federal Government, 14% ENGO).
9 — number of focus group responses (27% Academia, 9% Provincial Government, 18% ENGO, 9% NGO, 9% Other sectors).
Most participants had intermediate (33%) or advanced (67%) experience with remote cameras.
☑️ Tool Feedback Received
🎊 100% 🎊 — proportion of respondents who saw value in the tool, with 50% indicating they would use it and 12.5% needing it.
The biggest challenges users face include analyzing data, using statistical software, and managing data.
☑️ Feedback Received on Overall AB RCSC Resources
73% — proportion of respondents who want more information on analytical methods, with a strong demand for tools like embedded apps and scripts to assist with decision-making.
However, we also determined that R scripts are inaccessible to many new users, and thus there is also a need for more accessible resources for completing analysis.
🔜 Next Steps
The AB RCSC will enhance the tool with resources for both novice and advanced users, including "overview" and "advanced" tabs. Priorities include developing accessible Shiny apps for new users and more advanced tools like the "Occupancy - Spatial power analysis" app.
Papers of Interest 📖
⛓️💥 Breaking the Bottleneck—How a Lack of Collaboration is Stalling Camera Trap Research in Australia
A synthesis of a decade’s worth of camera trap research in Australia by Bruce et al., (2025) has revealed a number of trends in the field since 2012. Based on literature reviews and interviews with professionals, these researchers reported that sampling effort (deployment duration x number of cameras) has plateaued. Furthermore, multi-year and/or multi-species studies were rare, in part due to limited cross-project data sharing and collaboration.
One of their proposed solutions? — the new Wildlife Observatory of Australia (WildObs). This is intended to help facilitate the use of a common metadata collection app, a large public-use repository of images, and building capacity in image processing using machine learning models like MegaDetector and ClassifyMe. Cited as one example of a network of projects on which to model WildObs is WildCAM!
Journal Article | 25 min read | Biological Reviews | January 2025
👨💻 A Camera-Trapper’s Guide to Pixel-proofing Your Database
4.8%. That is the percentage of the over 140 camera-trap articles reviewed that reported quality control metrics on their data. For Silva-Rodríguez et al. (2025), this is concerning given the widespread use of camera-trapping in wildlife ecology and beyond. Even more concerning is the lack of a widely agreed upon quality control standard and methodology. Their solution? — protocol changes before, during, and after image classification.
Check camera set up details and independently record details at time of set up and removal. If possible, use a two-reviewer classification set up as opposed to a single reviewer. Estimate database error rate through an independent review of post-classified images. These are just some of the suggestions made by the authors to improve the quality and accuracy of camera-trap images. This is especially important given the potential for databases to be used by multiple researchers and groups.
“[…]unlike traditional wildlife survey methods based on human observers, recent technological methods give us the opportunity to check the quality of the resulting data and avoid biases in subsequent analyses.”
Journal Article | 25 min read | Journal of Applied Ecology | January 2025
🤌 Traps v. Telemetry — an Italian Case Study
50 camera traps and 23 GPS collars — these were the players in an experiment occurring in the Italian alps. Between 2019 and 2023, a team of researchers led by Valerio Donini compared these two schools of wildlife observation. The team used camera traps to study habitat selection in red deer (Cervus elaphus), using GPS telemetry data as a benchmark to compare its results to. The team split the 100 km2 study area in Stelvio National Park into 50 cells where cameras were randomly placed in each cell. For the telemetry data, 15 female and 8 male red deer individuals were captured and collared.
10,394 images and 54,939 location pings later, and the results are in! For a number of variables such as human presence (calculated using Strava data!) and shrub cover, camera traps and GPS collars were in agreement for both male and female deer. However, overall, a higher degree of agreement was observed amongst the female deer than the male deer (a function of, amongst other things, the smaller male sample size).
“It is important to note that camera trapping relates the presence of an animal to the habitat around the camera trap itself, i.e. refers to ‘habitat use’. Telemetry data, on the other hand, investigate individual’s selection of a particular habitat, and therefore refers to ‘habitat selection’.”
Journal Article | 40 min read | Landscape Ecology | February 2025
Photos 🎞️
Cause wouldn’t that be really funny if this comeback newsletter about wildlife image science had no images of wildlife? Couldn’t be me. Enjoy these photos from the Berg Lake Trail Camera Study at Robson Provincial Park, led by WildCo’s Ali Dimitriou in partnership with BC Parks.
If you would like to showcase your images (and assuming your data sharing agreement allows for it) please email them to me with a quick caption for them and photo credits!
