Making Tags Less of a Drag: Optimising Biologging Devices with Computational Fluid Dynamics

Post provided by WILLIAM KAY

Drag and Biologging Devices

A harbour seal tagged with a biologging device. ©Dr Abbo van Neer

A harbour seal tagged with a biologging device. ©Dr Abbo van Neer

Michael Phelps is one of the most decorated Olympic athletes of all time and the world’s fastest swimmer. And yet, he could swim faster. Wearing the Speedo LZR Racer supersuit Michael Phelps could reduce his hydrodynamic drag, or water resistance, by upwards of 40%. That could increase his swim speed by more than 4%! In competition, that’s the difference between silver and gold. But, if Phelps forgot to remove his “drag socks” – cumbersome footwear designed to increase water resistance for strength training – his speed would be dramatically reduced. He’d be lucky to walk away with bronze!

Professional swimmers have adapted to the use of performance enhancing technologies to decrease their drag, but that’s nothing compared to the adaptations made by wild animals. Creatures in the marine environment have evolved incredible adaptations to decrease drag, such as extreme streamlining in marine mammals and seabirds. This allows them to move underwater as quickly and efficiently as possible. Seals, for example, are pretty ungainly on land, but in the water they’re sleek and rapid. They have a body shape designed to maximise speed while swimming.

When we study marine animals we often use tracking devices, which can be attached using harnesses, glue, or suction-cups. These ‘biologging devices‘, or tags, are similar to Fitbits. Attaching them to animals allows us to record, amongst other things, all of the animal’s movements and behaviours. This information is crucial to understanding their ecology and for improving their conservation management. Continue reading

Bat Appreciation Day: The Latest Methodological Advances

Post provided by Kate Jones and the Biodiversity Modelling Research Group

The Funnel-eared bat (Natalus stramineus)

The Funnel-eared bat (Natalus stramineus) – © Veronica Zamora-Gutierrez

Today (17 April) is Bat Appreciation Day! Yes I know, a whole day to appreciate bats. Although my biodiversity modelling research group at University College London would argue that 24 hours is just not enough time to appreciate these cool, yet misunderstood animals, we wanted to mark the day by giving MEE a round-up of the latest methodological advances in bat monitoring and what we hope to see in the next few years.

Bat Detectives and Machine Learning

oisin_pictureOisin Mac Aodha PostDoc – If you have ever tried to spot bats flying around at night you will know that it can be very difficult. However, bats leak information about themselves into the environment in the form of the sounds they make while navigating and feeding. These calls are often too high for us to hear, but we can use devices known as bat detectors to transform them into a form that we can record and listen to. Monitoring bat populations over wide areas or long periods can result in huge amounts of data which is difficult to analyse though. To address this problem, our group, along with Zooniverse, have setup a citizen science project called Bat Detective which asks members of the public help us find bat calls in audio recordings that have been collected from all over Europe (the infographic below gives a bit more information on this). We have had an amazing response to date and our detectives have already located several thousand bat calls. However, to scale up monitoring, we need more automated methods of detecting calls. Using the analysis provided by our Bat Detectives, we are currently working on building algorithms that can automatically tell us if a recording contains a bat call.

In this video we see a visual representation of an audio signal called a spectrogram that features several bat calls. On top you see the result of an automated method we have developed for detecting bat calls. The larger the value, the more certain the algorithm is that there is a bat call at that point in time. Continue reading