Cameras used to monitor platypus activity on (or out of) the water
Cameras used in terrestrial wildlife studies are most commonly fitted with passive infrared (PIR) sensors triggered by movement, especially in combination with body warmth. In practice, PIR cameras often fail to detect a swimming platypus due to its low profile and limited heat signature in the water. However, they do sometimes capture platypus images when an animal leaves the water, as illustrated by the photo below of a platypus climbing up onto a log (taken by a camera trap set up to survey turtles).
Time-lapse cameras provide a much more reliable way to record platypus activity. These take photos at regular fixed intervals and so are triggered regardless of surface body temperature. Many models are also fitted with an infrared flash so they can work at night, when a platypus is most likely to be active. Their main disadvantage is that they produce many blank images (when no platypus is present) that must eventually be identified and discarded. This can be addressed with the help of machine learning software (Hilton et al. 2022) or by recruiting citizen scientists to assist with reviewing images (Jones et al. 2018).
Alternatively, software can be used to convert photos into a video sequence, thereby greatly reducing the time needed to manage image files. For example, a platypus monitoring study along a Tasmanian creek found that the species could be reliably detected by taking one photo every 3 seconds and then reviewing the images as a video with one minute of video time equalling one hour of real time (Roberts and Serena 2024). The image below provides a sense for the size of area that was monitored effectively in this study during daylight hours (note the platypus swimming near the fern at the left end of the pool).
Importantly, Roberts and Serena (2024) found that the least-effective camera model (of three trialled) reliably captured at least one platypus image within the first day of being deployed at two sites that were located just 200 metres apart. However, camera attributes and settings contributed to a 10-fold difference among the three models in how many platypus images were recorded. It was concluded that time-lapse cameras can be a very useful tool for platypus survey or monitoring as long as appropriate equipment is selected for the intended purpose. To see this paper’s full results and conclusions, click here.
Underwater cameras
Underwater infrared camera systems developed to assist with nocturnal fish research have a limited detection range even in clear water (e.g. Chidami et al. 2007). Alternatively, it’s now possible to purchase video equipment that uses sound waves instead of light waves to create underwater images. This technology copes well with darkness and high turbidity and registers images over a far greater distance than is possible with conventional video gear. The downside is that it’s quite expensive to install, especially if numerous sites are to be monitored simultaneously.
Photos courtesy of Jesse Miller (above); Simon Roberts (below)
LITERATURE CITED
Chidami S, Guenard G and Amyot M (2007) Underwater infrared video system for behavioural studies in lakes. Limnology and Oceanography: Methods 5, 371-378.
Hilton ML, Goesslig JM, Knezevich LM and Downer JM (2022) Utility of machinelearning for segmenting camera trap time-lapse recordings. Wildlife Soceity Bulletin 46, e1342.
Jones FM, Allen C, Arteta C, Arthur J, Black C, Emmerson LM, Freeman R et al. (2018) Time-lapse imagery and volunteer classifications from the Zooniverse Penguin Watch project. Scientific Data 5, 180124.
Roberts S and Serena M (2024) Use of consolidated time-lapse camera imagery to detect and monitor platypus (Ornithorhynchus anatinus) activity. Australian Mammalogy in press. doi:10.1071/AM23045.