Revealing activity patterns: Accelerometers give us a glimpse into the (hidden) lives of wildlife
by Sophie Kooros
Traditionally, behavioural observations have been used to infer the activity patterns of wild animals. Whilst comprehensive and valuable, behavioural observations are time-consuming and it can be extremely difficult to observe wild animals that live in inaccessible environments, avoid humans or are awake during the night.
Enter new possibilities… In the late 1990s, the first wildlife studies using accelerometers to measure animal activity started to appear (Brown et al. 2013). Since then, these devices have proven to deliver invaluable data to wildlife biologists wishing to understand activity in elusive wild species.
In this blog post, we discuss what accelerometers are and how we can use them in wildlife biology to understand animal activity.
Acceler…what???
Before diving into accelerometers, let's discuss what they actually are. Accelerometers are very common; you almost certainly have one in your phone right now and use it every day on games, when using GPS or for health monitoring.
Accelerometers are sensors that measure acceleration. Acceleration can describe the following three things:
- How fast something is speeding up
- How fast something is slowing down
- Whether something is changing directions.
Let’s think about acceleration in an example: you can imagine your car speeding up - that is acceleration; when your car slows down (commonly called deceleration) - that is also acceleration but in the opposite direction. Finally, when your car turns a corner - that is inward acceleration. Acceleration is commonly measured in m/s2, which means how speed is changing every second.
Wildlife accelerometers generally measure acceleration on 1, 2 or 3 separate axes and they can also measure acceleration in different time intervals that range from 0.5 times a second up to 10 000 times a second (Brown et al. 2013).
Tip!
Before using an accelerometer, it is important to identify how many axes and how many measurements a second you will need to answer your research questions. Current research papers are a great place to begin when first understanding how accelerometers can be used. In most wildlife studies, having an accelerometer with three axes, that measures at least 16 times a second is the most informative option (Brown et al. 2013; Wang et al. 2015).
How are accelerometers used in wildlife biology?
Many wildlife scientists wish to understand the activity patterns of wild animals and accelerometers are great for this task as they take away many of the traditional challenges of behavioural observations by allowing us to monitor animal activity remotely and continuously for extended periods.
Note!
Did you know accelerometers are used in fitness watches to monitor your activity and track your steps? If you think about accelerometers like that, then you can imagine how we can use them to measure activity in wildlife!
Accelerometers can record data 24 hours a day and batteries often last over a year. Additionally, these devices are relatively non-invasive - most are attached by collar or harness to the animal and nowadays, some accelerometers fit even the tiniest of species. Most accelerometers on collars are pre-programmed to fall off after a certain time. This makes recapturing of the animal unnecessary.
In one recent research paper, accelerometer collars were used to continuously measure activity in spider monkeys (Ateles geoffroyi) living on an island in Mexico (Muñoz-Delgado et al. 2018). This study discovered that these monkeys actually had a 7-day activity pattern where activity peaked on weekends when tourist boat densities were highest (Muñoz-Delgado et al. 2018). Using accelerometers allowed these activity patterns to be discovered and therefore, impacts from factors such as tourist density could be quantified.
In my own research during my master’s which was based at the Danau Girang Field Research in Malaysia, accelerometers allowed me to study nocturnal activity in proboscis monkeys (Nasalis larvatus) – monkeys that live in thick, often flooded rainforest. Without the use of these devices, studying their activity at night would have been impossible.
Ok, sounds good… what do they look like?
Figure 1 shows the usual set-up of a collar-attached accelerometer. The accelerometer sits on the top of the neck on this deer and has three axes recording activity. The X-axis records movement when the individual moves forward and backwards, the Y-axis records side to side movement and the Z-axis records up and down movement.
Figure 1 An example of an accelerometer attached to a collar. This accelerometer has 3 axes as depicted in this picture.
This is not their only use
Accelerometers allow us to delve deeply into the activity patterns displayed by wildlife. However, that is not all - they have been used in many animal energetics studies (Wang et al. 2015) and very recently, they have been used to help monitor welfare in shelter dogs (Jones et al. 2014) and farm animals (Barwick et al., 2020).
Whilst accelerometers provide invaluable information on wildlife, working with accelerometer data is not always intuitive and takes time to get the hang of.
Finally, consider these two top tips…
Based on my experience of working with accelerometers, I suggest that starting with these will help you discover the world of accelerometers and how valuable they are to many wildlife studies.
- Know your goals beforehand – most accelerometer sensors come with different activity modes that must be set before placing the accelerometer on the animal. It is useful to know what you want to do, including which statistically tests you want to use before you place the accelerometer on the animal. Doing this means that you will collect data that can answer your research question successfully.
- Pre-calibrate the accelerometer – most (but not all) accelerometers need pre-calibration to ensure the data collected is usable. Before using your accelerometer, find out whether the accelerometer needs to be calibrated, or if not, how do the makers of the sensor otherwise calibrate it for you. If calibration is recommended in the accelerometer user manual, do it!
Have you ever used accelerometers before? Do you have any burning questions? Let us know in the comments!
About the author:
Sophie graduated from her Master's of Environmental Biology in December 2020, she is excited to now build a career in wildlife conservation and has a particular interest in the behavioural ecology of non-human primates. You can learn more and connect with Sophie via LinkedIn.
References
Barwick, Jamie, David William Lamb, Robin Dobos, Mitchell Welch, Derek Schneider, and Mark Trotter. 2020. “Identifying Sheep Activity from Tri-Axial Acceleration Signals Using a Moving Window Classification Model.” Remote Sensing 12 (4): 1–13.
Brown, D, R Kays, M Wikelski, R Wilson, and P Klimley. 2013. “Observing the Unwatchable through Acceleration Logging of Animal Behaviour.” Animal Biotelemetry 1 (29): 1–16.
Jones, Sarah, Seana Dowling-Guyer, Gary J. Patronek, Amy R. Marder, Sheila Segurson D’Arpino, and Emily McCobb. 2014. “Use of Accelerometers to Measure Stress Levels in Shelter Dogs.” Journal of Applied Animal Welfare Science 17 (1): 18–28.
Muñoz-Delgado, Jairo, Sergio Pérez-Galicia, Jose Carlos Sánchez-Ferrer, Domingo Canales-Espinosa, and Hans G. Erkert. 2018. “Diel and Infradian (7-Day) Activity Rhythms in Mexican Spider Monkeys (Ateles Geoffroyi) Kept with and without Visitor Contact.” American Journal of Primatology 80: 1–11.
Tagg, Nikki, Maureen McCarthy, Paula Dieguez, Gaëlle Bocksberger, Jacob Willie, Roger Mundry, Fiona Stewart, et al. 2018. “Nocturnal Activity in Wild Chimpanzees (Pan Troglodytes): Evidence for Flexible Sleeping Patterns and Insights into Human Evolution.” American Journal of Physical Anthropology 166 (3): 510–29.
Wang, Yiwei, Barry Nickel, Matthew Rutishauser, Caleb M. Bryce, Terrie M. Williams, Gabriel Elkaim, and Christopher C. Wilmers. 2015. “Movement, Resting, and Attack Behaviors of Wild Pumas Are Revealed by Tri-Axial Accelerometer Measurements.” Movement Ecology 3 (1): 1–12.
