I am researching how we can best use camera traps to monitor foxes (Vulpes vulpes) in the mallee. I don’t know much about camera traps yet, so I decided to learn more about best practice in detecting wildlife with camera traps. Here’s what I found.
Camera traps are a useful monitoring tool that has become increasingly popular in wildlife monitoring over the past decade. They are relatively new compared to more traditional tools and techniques, but, just as with any other tool, you want to be using it the right way. What affects camera trap performance in wildlife surveys (particularly monitoring change in fox abundance) and how should they best be set up?
Each different camera brand and type has different qualities that should be taken into account when designing a wildlife survey, because this defines what type of camera you will need. Some qualities are inherent to the camera (such as trigger speed), and some can be chosen when setting up the camera (such as delay).
Trigger speed affects how quickly a picture is taken after detection. When a trigger speed is too slow, the animal might have left the field of view (the area captured in the photograph) before a picture is taken. However, if a trigger is too quick, it is possible that the animal has not entered the field of view of the camera, but only the detection zone (see below). Trigger speeds of 0.2–2.1 s have been found to be a good range for mammals (Glen et al. 2013). Trigger speeds can usually not be chosen and are dependent on the camera type and brand.
This is zone in which the infrared sensor detects animal movement and causes the camera to be triggered and take a picture. This zone is important because it affects how likely the camera is to detect an animal. The detection zone is not always the same as the field of view of the camera and both aspects differ per brand and camera type.
The quality of the pictures taken is also important. The quality necessary depends on the type of survey. When individual recognition of animals in necessary, quality should generally be high and a white flash is needed to take pictures at night. When only species identification is necessary, infrared flash during night time is usually sufficient. When monitoring a species that is difficult to identify, it can be helpful set the camera to take multiple pictures when triggered.
A delay period can be set for a camera trap, preventing it from taking pictures for a certain time after it was triggered. This reduces the chance of detecting the same individual multiple times and saves memory.
Cameras can have technical failures sometimes, so make sure that enough camera traps are set up in the field to account for this. Replacement costs of camera traps and budget may influence how well this can be accounted for.
Setting up the camera trap
When setting up a camera trap in the field, it is important to have the right field of view. This means that cameras have to be set up at the right height and angle. It is important that field of view is standardised across all camera traps, so capture rates are comparable across space and time (Glen et al. 2013).
To be able to detect foxes, they will have to be set up at the right height. A rule of thumb is that the height of the camera should be similar to the core mass of the animal you want to detect (Meek et al. 2012). It is also important that the camera trap is set up the right angle. Facing downwards is preferred for small animals, but for larger ones outward facing is more often recommended.
When setting up the camera traps, vegetation that can move in the wind nearby the camera trap should be removed. Also, the camera trap should be attached to post, not a tree, as these tend to move in the wind as well. Moving vegetation and trees can cause false triggers, causing the camera to take empty pictures (no animals in it). These take up a lot of memory and increase the time it takes to sort all the pictures afterwards.
False triggers can occur in the morning as the sun rises and starts to warm sunspots and vegetation. False triggers can also occur where the sun shining directly on the face of the camera. To reduce glare, it is a good idea to face the camera southerly.
Most camera traps use passive infrared sensors. This means that the camera will detect heat and motion and take photos when it detects a difference between air temperature and the animal body temperature. Body heat can be masked by background heat on hot days. When ambient temperatures range between 35.7 and 41.7⁰ C, it can become difficult for the camera traps to detect foxes because the difference between body heat and ambient heat is too small. Setting the sensitivity of infrared sensor to high in summer is therefore recommended. Low sensitivity is recommended during cooler winter months.
Detection of camera traps by foxes
Camera traps emit light and sound which can be detected by a range of species. This could affect their behaviour in camera traps surveys. It has been found that foxes can easily hear some of the infra and ultra sounds emitted by camera traps as well as flash illumination and possible infrared flash lights (Meek et al. 2014).
Literature and further reading
(Most information in this blog post is based on “An introduction to camera trapping for wildlife surveys”)
- Glen, A. S., Cockburn, S., Nichols, M., Ekanayake, J., & Warburton, B. (2013). Optimising Camera Traps for Monitoring Small Mammals. PLoS ONE, 8(6), 1–8.
- Meek, P., Ballard, G., & Fleming, P. J. S. (2012). An introduction to camera trapping for wildlife surveys in Australia, (p. 94). Invasive Animals Cooperative Research Centre.
- Meek, P. D., Ballard, G.-A., Fleming, P. J. S., Schaefer, M., Williams, W., & Falzon, G. (2014). Camera Traps Can Be Heard and Seen by Animals. PLoS ONE, 9(10), e110832.
- Meek, P., Fleming, P., Ballard, G., Banks, P., Claridge, A., Sanderson, J., & Swann, D. (2014). Camera Trapping: Wildlife Management and Research (p. 392). CSIRO.
- O’Connel, A. F., Nichols, J. D., & Karanth, K. U. (2011). Camera Traps in Animal Ecology: Methods and Analyses. In Camera Traps in Animal Ecology: Methods and Analyses (pp. 27–43).