Electronic Thesis and Dissertation Repository

Thesis Format

Integrated Article


Doctor of Philosophy




Sherry, David F.

2nd Supervisor

Guglielmo, Chris


The major forces that govern social groups, namely fission-fusion dynamics, cohesion and maintenance, are nearly ubiquitous across animal groups. The field of animal collective behaviour has recently been married with automated radiotracking producing a ‘re-wilding’ of field research into sociality. The combination of this with Social Network Analysis has led to discoveries such as population wide information transfer and the flexibility of animal groups to change social connectivity based on environmental context. However, these networks are constructed, and do not include the dynamic environmental, spatio-temporal, and social contexts which directly affect sociality. I conducted the first automated radiotracking study I know of to track free-living flocks of black-capped chickadees, through the non-breeding season. My major objective was to combine existing radiotelemetry methods with advanced statistical techniques to create novel methodologies to track and quantify socially relevant movements and behaviours. Firstly, I used Linear Discriminant Analysis to match signal strength profiles of key individuals to all others as a new method of flock identification. Secondly, I examined onset of daily activity to test whether this was cohesive in flocks. Since unexpected spikes of early activity prior to onset were observed, I investigated the possibility that these restless events were related to environmental stressors. Finally, I used known activity thresholds to investigate the general activity patterns of ranks to address previous contradictions of rank and activity, and to test if field activity was consistent with theoretical predictions of optimal winter bird activity. Flocks were effectively tracked and identified with automated radiotelemetry alone and fusion-fission events could be tracked as well. Onset of activity was found to be cohesive within flocks, which was further supported by onset changes during fission-fusion events. Environmental pressure, temperature, windspeed and winter storm events were all related to sleep disturbances. Daily activity amount was higher in high ranks than low ranks and general activity patterns agreed with theoretical models. My findings contribute new methodologies to the field of collective animal movement and demonstrate the importance of automated radiotelemetery studies in providing important applications to social dynamics and beyond.

Summary for Lay Audience

Advancements in the field of radiotelemetry (e.g. smaller radiotags with longer battery life), have allowed small animals to be tracked for longer than ever before. By using a network of radiotower stations, the process of detecting pulses from tagged individuals is completely automated, meaning that multiple individuals can be tracked simultaneously and in real-time directly in the field.

The black-capped chickadee (Poecile atricapillus) is a small bird found in mostly wooded habitats from coast to coast in most of North America. In winter, chickadees form flocks of approximately 3-12 individuals which a range of roughly 9.5 hectares. Flocks are relatively stable, and flock-mates engage in most behaviours as a group through the winter, before ultimately breaking up into breeding pairs in the spring. Occasionally, individuals will ‘flock-switch’ and leave one flock and join another or become solitary. Flocks are organized via a dominance hierarchy in that the highest ranking bird, outcompetes lower ranks for resources and skews fitness in their favour. Because chickadees do not migrate in the winter, they provide an excellent model to explore how automated radiotelemetery can advance the study of social dynamics.

I erected four radiotelemetry stations in a 60 hectare forest in Elginfield, Ontario and caught and tagged chickadees with Avian Nanotags (0.35g) via a figure-8 harness. I ultimately tracked the movements of 12 flocks in the winter seasons of 2016 and 2017. I first used advanced statistical methods to discover a new method to separate and track both flocks and flock switchers. Next, I examined the wake-up times of flocks, and found these were synchronized in the group. During this analysis, unexpected early spikes of activity were observed, so I compared weather data from a local station to these events and found extreme weather (winter storms) likely caused sleep disturbances. Lastly, I used this dataset to examine rank-specific daily activity, and found high ranks are more active and that daily activity curves from all birds are consistent with theoretical predictions. Collectively, my thesis expanded on known methods of radiotelemetry and demonstrated the value of such a dataset to the animal collective movement field.

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.