Trappes – Big data in behavioural biology – DS² 2021
Channel: CEFISES at UCLouvain
Date: 19/03/2021

The talk “Big data in behavioural biology” by Rose Trappes (Bielefeld University), recorded at the DS² 2021 online conference, March 18, 2021.


Ethology was founded as a science of naturalists. Early students of animal behaviour Konrad Lorenz and Niko Tinbergen were avid birders and known for their penchant for watching and wondering about animals domestic and wild. Through careful, prolonged observation, these scientists developed an understanding of animals’ regular suites of behavioural patterns in their natural contexts, forming the foundation for their theories of instinct and adaptive strategies.


The naturalist tradition persists to this day, especially in fields like primate studies. But behavioural biologists increasingly accomplish their observations with the help of technology. Audio and video recording has been employed for many years, and automatic coding of some behavioural responses is beginning to alleviate the burden of hours spent watching and listening, counting and timing. In addition, recent years have seen the increasing availability of affordable, small and relatively non-invasive radio transmitters, accelerometers and GPS tracking devices. These new technologies, coupled with the funding made available to satisfy a growing interest in species’ responses to climate change, have led to an explosion of data on animal movement and behaviour. Even the international space station has dedicated some of its precious space to a receiver station for animal observation as part of the Icarus project. Behavioural biology is now often conducted remotely, tracing animals’ steps with a heavy dose of statistics.


The new tracking technologies offer many advantages. Animals can now be observed day and night, at the bottom of the sea off the coast of South America, in underground burrows in Canadian forests, on the inaccessible cliffs of the Scottish isles, or in nest boxes in the dead of a Finnish winter. In addition, given a ready supply of tracking devices (and the field technicians to attach them and sometimes relocate them), observations can be made of a greater proportion of a population. Tracking devices also permit single individuals to be followed over days and months, meaning that insights can be gained below the level of species-typical characteristics. Finally, tracking devices remove many sources of observer bias and human influences on animal behaviour.


The increases in scope, power, precision and objectivity are welcomed by behavioural biologists, who can often be heard exclaiming with joy over their brand-new toys and the far-reaching insights they enable. On the other hand, and unsurprisingly, the use of tracking technology presents particular challenges. Especially difficult is the reconstruction of animal behaviour from data points representing a bare minimum of variables such as position, acceleration, and time. Where early ethologists could directly observe a foraging event or a social interaction, specialist statisticians are now needed to interpret such events from patterns in movement data. This is a strange predicament: at the very moment in which behavioural biology looks to exceed the confines of a naturalist approach, its object of study seems to dissolve in a mire of tracking data.


Much could be said about the computational approaches for acquiring and analysing animal movement data, as well as the technological side of calibrating and validating tracking devices. No specialist in the statistics nor the technology, I will instead look at how statisticians cooperate with behavioural biologists to develop biologically sound interpretations of the data. Statisticians can reveal patterns in data, but they need constraints to do so and they can often only guess what the patterns mean in terms of animals’ behaviour in their natural habitats. Biologists with an understanding of animals’ ways of life, gained through a combination of empirical and theoretical work, are thus necessary for the study of animal behaviour from tracking data. Statisticians can of course deliver genuinely novel insights, for instance by discovering patterns of which biologists were unaware. But a fully automated study of animal behaviour remains a distant dream. Instead, the necessity of interpreting big data in behavioural biology calls for a continuing interplay between data science and ethological insights. This also limits some of the advantages of using tracking technology, for instance by reintroducing sources of observer bias and limits on precision.