
Thesis subject
MSc thesis topic: Quantifying animal fear using collective movement metrics
In order to survive, the movement of animals is for a large part driven by two factors: resource availability (e.g., food) and fear of threats (e.g., predation) [1, 2].
Resource scarcity induces animals to prioritize foraging behaviour and high predation risk induces animals to prioritize vigilance behaviour [3]. Given that these two behaviours often cannot be performed efficiently simultaneously, a trade-off exists between food acquisition and predator avoidance regarding optimal fitness [4]. Emerging from individual movement, collective animal movement (e.g., group formation) is to a large extent also shaped by both resources and predation [5, 6, 7]. In general, when the chance of predation is high it benefits an individual to live in a group with many individuals, through both the dilution (i.e., less chance to be chosen by a predator during an attack [8]) and the “many eyes” effect (i.e., benefiting from the vigilance of group members [4]).
References
[1] Nathan R, Getz WM, Revilla E, Holyoak M, Kadmon R, Saltz D, et al. A movement ecology paradigm for unifying organismal movement research. Proceedings of the National Academy of Sciences. 2008;105(49):19052–19059.
[2] Brown JS, Laundr´e JW, Gurung M. The Ecology of Fear: Optimal Foraging, Game Theory, and Trophic Interactions. Journal of Mammalogy. 1999;80(2):385–399.
[3] Laundr´e JW, Hern´andez L, Altendorf KB. Wolves, elk, and bison: reestablishing the ”landscape of fear” in Yellowstone National Park, U.S.A. Canadian Journal of Zoology. 2001;79(8):1401–1409.
[4] Lima SL. Back to the basics of anti-predatory vigilance: the group-size effect. Animal Behaviour. 1995;49(1):11–20.
[5] Krause J, Ruxton GD. Living in groups. New York, U.S.A.: Oxford University Press; 2002.
[6] Couzin ID, Krause J. Self-Organization and Collective Behavior in Vertebrates. In: Advances in the Study of Behavior. vol. 32. Academic Press; 2003. p. 1–75.
[7] Alexander RD. The Evolution of Social Behavior. Annual Review of Ecology and Systematics. 1974 11;5(1):325–383.
[8] Hamilton WD. Geometry for the selfish herd. Journal of Theoretical Biology. 1971;31(2):295–311.
Besides group size, there are also other collective movement features that are potentially influenced by resource availability and fear (e.g. see image attached to this proposal; Strandburg-Peshkin et al. 2017). Especially given that the group size of animals does not change rapidly in response to external conditions, other group features are potentially more useful to quantify when trying to measure a proxy for the animals’ fear level (e.g. Eikelboom et al. 2024). However, some new geometric algorithms need to be developed in order to keep track of this.
Relevance to research/projects at GRS or other groups
For this project there is also an external advisor available from the Algorithms Cluster at the TU Eindhoven.
Objectives and Research questions
- Accurately keep track of group features over time by constructing new algorithms
- Correlate computed group features to landscape characteristics for baboons (see Crofoot et al. 2021)
- Optionally relate computed group features to a constructed metric that describes Landscape of Fear based on ecologically relevant landscape characteristics
Requirements
- Programming experience (R or Python)
- Affinity with mathematics and data simulations
- Preferably experience with movement analyses
Literature and information
- Crofoot MC, Kays RW, Wikelski M. 2021. Data from: Study "Collective movement in wild baboons". Movebank Data Repository.
- Eikelboom J.A.J., Doelman A., Van Langevelde F. & De Knegt H.J. (2024). Animal group size variation in a minimal attraction-repulsion agent-based model. bioRxiv preprint: 2024.03.20.585938.
Expected reading list before starting the thesis research
- Strandburg-Peshkin A, Farine DR, Crofoot MC, Couzin ID. 2017. Habitat and social factors shape individual decisions and emergent group structure during baboon collective movement. eLife. 6:e19505.
Theme(s): Modelling & visualisation