Monitoring mammal populations with camera traps

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 read how others have used camera traps to monitor mammal populations. Here’s what I found.

What are camera traps?Camera traps are used to take picture of wildlife without needing presence of a human. Camera traps consist of a motion sensor linked to a camera that takes a picture (or multiple pictures, depending on the settings and camera type) when the motion sensor is triggered (e.g. Meek et al. 2012).

A typical camera trap
A typical camera trap

Benefits of camera traps vs. other monitoring tools Because there is no presence of a human required when using camera traps, they are very effective in monitoring wildlife. Shy wildlife will not be scared away, and labour costs will be significantly reduced when monitoring with camera traps, as less people have to go into the field less often compared to other monitoring techniques (Engeman & Witmer 2000, Silveira et al. 2003).

What can we do with camera traps? Camera traps are mainly used for three goals: hunting, wildlife photography and ecological surveys. The use of camera traps for hunting, where cameras are set up to scout prey, has led to a strong growth of the camera trap market, with variety of different camera types and qualities now available.

Use of camera traps for wildlife photography was done as early as the 1880s and nowadays still used to produce stunning pictures. National geographic wrote an interesting piece about it which you can read here. For stunning pictures see here.

Bobcats on camera trap
Bobcats in Bosque del Apache, New Mexico, US – camera trap photo (cropped) taken with a Moultrie Game Camera by J.N. Stuart via Flickr

The use of camera traps to survey wildlife has strongly increased over the past decades. These are the four main ways in which camera are used for ecological purposes:

  1. to map occupancy of a species in an area;
  2. to monitor how many different species there are in an area;
  3. to prove that a species is present;
  4. to monitor a species and estimate (changes in) their abundance.

My research will be focusing on option 4.

Using camera traps to monitor species abundance How can we use camera traps to estimate species abundance? This depends on the type of species. Camera traps will need to be set up in different angles depending on the size of the species that will be monitored.

Depending on how the camera traps are set up, different types of abundance estimates can be obtained. Often activity or density are estimated (e.g. Bengsen et al. 2011, Rowcliffe et al. 2014), but sometimes researchers look at bait uptake (how often bait was taken from a bait station set up in front of the camera) as an indication of abundance (Hegglin et al. 2004).

Most camera traps are motion-triggered, but there is also the possiblity to set up time-triggered cameras. Hamel et al. (2014) have found that time-triggered cameras can provide smaller error rates in daily presence of species than motion-triggered cameras.

Camera traps can be set up in the field randomly, but some researchers have found that this is not the most effective way to gain abundance estimates (Guthlin et al. 2014). Other approaches are setting up the camera along known tracks or unpaved roads. Furthermore, some researchers have chosen to place lures or baits near the camera traps (Bengsen et al. 2011). All these choices affect the way the data will have to be analysed later on.

Data analysis Most data analysis is done based on capture-mark-recapture methods, where individual recognition is necessary. This method is particularly effective when looking at species that prevail at low densities (Foster & Harmsen 2012), where each individual can be recognised, such as tigers. The main benefit of using individual recognition is that one will have certainty about whether the same animal triggered a camera several times instead of it being several animals. A disadvantage of using individual recognition is that a picture of the whole animal or even both sides of the animal are necessary, which means that camera traps tigger time should be set to trigger at exactly the right moment and should produce high quality pictures (Meek et al. 2012).

More recently researchers have started to develop abundance estimation methods for which no individual recognition is necessary. For these methods, less accurate pictures are necessary, as only species recognition is important. However, this methods also introduces uncertainty, as it is no longer possible to see if the same animal triggered a camera several times. The only methods that I have been able to find so far that allows for abudance estimation without the need for individual recognition is by Ratcliffe et al. (2008). This method is based on the assumption that animals move according to a gas model.

How to monitor foxes with camera traps? So far I have been able to identify three ways to monitor foxes and estimate their abudance.

  1. Individual recognition has been used as a way to monitor fox abundance in foxes, but this method is rather time consuming and difficult when multiple people analyse the photos, especially when animal densities are high (e.g. Sarmento et al. 2009).
  2. Others have looked at the bait uptake by foxes by setting up camera traps near bait stations (Hegglin et al. 2004).
  3. Rowcliffe et al.’s paper on estimating abundance without the need for individual recognition might be an intersting alternative, especially if large amounts of picture need to be processed and this will be done by different people (Rowcliffe et al. 2008).

That’s it for now. If you’ve found that something I stated is incorrect, please let me know! My next step will be to sort out which will be the best method for monitoring foxes as part of the malleefowl conservation project. Stay tuned!


  • Bengsen et al. (2011) Estimating and indexing feral cat population abundances using camera traps, Wildlife Research, 38:8, 732-739
  • Engeman & Witmer (2000), IPM strategies: indexing difficult to monitor populations of pest species, In: Salmon, T. P., Crabb, A.C., (Eds.), Proceedings of the 19th Vertebrate Pest Conference. University of California, Davis, pp. 183-189.
  • Guthlin et al. (2014)Toward reliable estimates of abundance: comparing index methods to assess the abundance of a Mammalian predator, PloS one, 9:4, e94537
  • Hamel et al. (2014) Towards good practice guidance in using camera-traps in ecology: influence of sampling design on validity of ecological inferences, Methods in Ecology and Evolution, 4:2, 105-113
  • Hegglin et al. (2004) Baiting Red Foxes in an Urban Area: a Camera Trap Study, Journal of Wildlife Management, 68:4, 1010-1017
  • Meek et al. (2012) An introduction to camera trapping for wildlife surveys in Australia, Vertebrate Pest Research Unit NSW Department of Primary Industries
  • Rowcliffe et al. (2008) Estimating animal density using camera traps without the need for individual recognition, Journal of Applied Ecology, 45, 1228-1236
  • Rowcliffe et al. (2014) Quantifying levels of animal activity using camera-trap data, Methods in Ecology and Evolution, 5, 1170-1179
  • Sarmento et al. (2009) Evaluation of Camera Trapping for Estimating Red Fox Abundance, Journal of Wildlife Management, 2009, 73:7, 1207-1212
  • Silveira et al. (2003) Camera trap, line transect census and track surveys: a comparative evaluation, Biological Conservation, 114:3, 351-355

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