Raspberry Pi keeps an eye on freshwater fishes in Canada

Jessica Reemeyer is a PhD candidate at McGill University looking at the ecophysiology of imperiled Canadian fishes. I Googled “ecophysiology” for you and found out it’s how the environment interacts with the physiology of living things. So Jess is saving fishes.

pi zero underwater camera
The Raspberry Pi and camera are enclosed in a food container with a locking lid, and strapped to a PVC platform that has been filled with gravel to make it sink in the water

Detecting fishes and their environment

Jessica’s setup comprises a Raspberry Pi Zero W with our High Quality Camera, as well as sensors for dissolved oxygen and temperature. It records fish presence and environmental variables in different habitats. Jessica has tested the equipment in locations across a small channel near Lake Huron, which is nestled between Toronto in Canada and Detroit in the US. The ultimate goal of her research is to create habitat occupancy models in the area. These would tell us the population limit for threatened species of fish.

pi zero underwater camera
Jessica and her research assistant Lucca Mole rowing on the channel where they deploy the cameras

This research is focused on the effects of environmental change on freshwater fishes in Canada. And Jessica explains that she’s a fan of our affordable kit:

“I got my start working with Raspberry Pi when my Master’s thesis advisor instructed me to find a way to build a dissolved oxygen controller for our laboratory experiments where we were holding fish at different oxygen levels to see how it affected their physiology. I had not worked with electronics previously but browsing the web brought me to the Raspberry Pi website where I was able to learn how to get started working with hardware and programming in Python.”

pi zero underwater camera
An example of the camera deployed in the channel

What do threatened species need?

Now, for her PhD research, she is using Raspberry Pi Zero W along with our HQ Cameras to observe fishes in their natural habitat.

Cameras are placed in the Old Ausable Channel of Lake Huron, a freshwater channel that spans 14 kilometres through Pinery Provincial Park in Ontario, Canada. The channel is home to many fish species that are federally listed as being at risk. Jessica and her team are interested in learning more about the habitat requirements of these fishes — in particular, how variation in temperature and dissolved oxygen affect where they live.

Lupi is my colleague Jennifer’s dog! He’s the sweetest boy and absolute best field assistant
Before you ask, we already asked, and the dog in the background is Lupi. He belongs to Jess’ colleague Jennifer and he is rated as “the absolute best field assistant ever.”

Non-invasive monitoring with Raspberry Pi

Previously, to study where a fish species lives, you usually had to invade different habitats and catch the fish either with nets or by electrofishing. Unfortunately, this requires capturing, handling, and identifying the fish as they are caught. Another possibility is to tag fish with transmitters that allow you to track them; however, you can only do this with fish that are large enough to support the tags.

Jessica found an alternative to these methods using Raspberry Pi cameras to detect fish in situ. These get a good look at the habitat, recording characteristics like water depth and vegetation, without disturbing the animals too much. The cameras are connected to Raspberry Pi Zero W boards which run dissolved oxygen and temperature sensors. The Zero Ws relay data each time the cameras record a video, so that researchers can relate the sensor readings to the time the videos are recorded.

Using Raspberry Pi hardware for this project cut equipment costs significantly. It also allowed Jessica’s team to tailor their software more closely to the needs of their project. For underwater camera trapping, researchers often use GoPro cameras, which generally manage less than thirty minutes of video recording before the battery dies. Jessica’s bespoke Raspberry Pi setup meant she could record at a significantly reduced frame rate to save on memory. She was also able to use a larger battery that allowed her to deploy the cameras for up to a week.

Your job sounds amazing to us, Jess. And we love that canine field assistant of yours.

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