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Minasandra P, Jensen FH, Gersick AS, Holekamp KE, Strauss ED, Strandburg-Peshkin A. Accelerometer-based predictions of behaviour elucidate factors affecting the daily activity patterns of spotted hyenas. R Soc Open Sci 2023; 10:230750. [PMID: 38026018 PMCID: PMC10645113 DOI: 10.1098/rsos.230750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 10/18/2023] [Indexed: 12/01/2023]
Abstract
Animal activity patterns are highly variable and influenced by internal and external factors, including social processes. Quantifying activity patterns in natural settings can be challenging, as it is difficult to monitor animals over long time periods. Here, we developed and validated a machine-learning-based classifier to identify behavioural states from accelerometer data of wild spotted hyenas (Crocuta crocuta), social carnivores that live in large fission-fusion societies. By combining this classifier with continuous collar-based accelerometer data from five hyenas, we generated a complete record of activity patterns over more than one month. We used these continuous behavioural sequences to investigate how past activity, individual idiosyncrasies, and social synchronization influence hyena activity patterns. We found that hyenas exhibit characteristic crepuscular-nocturnal daily activity patterns. Time spent active was independent of activity level on previous days, suggesting that hyenas do not show activity compensation. We also found limited evidence for an effect of individual identity on activity, and showed that pairs of hyenas who synchronized their activity patterns must have spent more time together. This study sheds light on the patterns and drivers of activity in spotted hyena societies, and also provides a useful tool for quantifying behavioural sequences from accelerometer data.
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Affiliation(s)
- Pranav Minasandra
- Department for the Ecology of Animal Societies, Max Planck Institute of Animal Behavior, Konstanz, Germany
- Biology Department, University of Konstanz, Konstanz, Germany
- Centre for the Advanced Study of Collective Behaviour, University of Konstanz, Konstanz, Germany
- International Max Planck Research School for Organismal Biology, Konstanz, Germany
| | - Frants H. Jensen
- Department of Ecoscience, Aarhus University, Roskilde, Denmark
- Biology Department, Woods Hole Oceanographic Institution, Woods Hole, MA, USA
- Biology Department, Syracuse University, Syracuse, NY, USA
| | - Andrew S. Gersick
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
- Department of Computer Science, San Diego State University, San Diego, CA, USA
| | - Kay E. Holekamp
- Department of Integrative Biology, Michigan State University, East Lansing, MI, USA
- Program in Ecology, Evolution, and Behavior, Michigan State University, East Lansing, MI, USA
| | - Eli D. Strauss
- Department for the Ecology of Animal Societies, Max Planck Institute of Animal Behavior, Konstanz, Germany
- Biology Department, University of Konstanz, Konstanz, Germany
- Centre for the Advanced Study of Collective Behaviour, University of Konstanz, Konstanz, Germany
| | - Ariana Strandburg-Peshkin
- Department for the Ecology of Animal Societies, Max Planck Institute of Animal Behavior, Konstanz, Germany
- Biology Department, University of Konstanz, Konstanz, Germany
- Centre for the Advanced Study of Collective Behaviour, University of Konstanz, Konstanz, Germany
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Kunjar S, Strandburg-Peshkin A, Giese H, Minasandra P, Sarkar S, Jolly MK, Gradwohl N. Link updating strategies influence consensus decisions as a function of the direction of communication. R Soc Open Sci 2023; 10:230215. [PMID: 37293357 PMCID: PMC10245208 DOI: 10.1098/rsos.230215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 05/16/2023] [Indexed: 06/10/2023]
Abstract
Consensus decision-making in social groups strongly depends on communication links that determine to whom individuals send, and from whom they receive, information. Here, we ask how consensus decisions are affected by strategic updating of links and how this effect varies with the direction of communication. We quantified the coevolution of link and opinion dynamics in a large population with binary opinions using mean-field numerical simulations of two voter-like models of opinion dynamics: an incoming model (IM) (where individuals choose who to receive opinions from) and an outgoing model (OM) (where individuals choose who to send opinions to). We show that individuals can bias group-level outcomes in their favour by breaking disagreeing links while receiving opinions (IM) and retaining disagreeing links while sending opinions (OM). Importantly, these biases can help the population avoid stalemates and achieve consensus. However, the role of disagreement avoidance is diluted in the presence of strong preferences-highly stubborn individuals can shape decisions to favour their preferences, giving rise to non-consensus outcomes. We conclude that collectively changing communication structures can bias consensus decisions, as a function of the strength of preferences and the direction of communication.
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Affiliation(s)
- Sharaj Kunjar
- Department for the Ecology of Animal Societies, Max Planck Institute of Animal Behavior, Konstanz 78315, Germany
- Undergraduate Programme, Indian Institute of Science, Bangalore 560012, India
| | - Ariana Strandburg-Peshkin
- Department for the Ecology of Animal Societies, Max Planck Institute of Animal Behavior, Konstanz 78315, Germany
- Department of Biology, University of Konstanz, Konstanz 78464, Germany
- Centre for the Advanced Study of Collective Behaviour, University of Konstanz, Konstanz 78464, Germany
| | - Helge Giese
- Centre for the Advanced Study of Collective Behaviour, University of Konstanz, Konstanz 78464, Germany
- Department of Psychology, University of Konstanz, Konstanz 78464, Germany
- Heisenberg Chair for Medical Risk Literacy and Evidence-based Decisions, Charité–Universitätsmedizin Berlin, Berlin 10117, Germany
| | - Pranav Minasandra
- Department for the Ecology of Animal Societies, Max Planck Institute of Animal Behavior, Konstanz 78315, Germany
- Centre for the Advanced Study of Collective Behaviour, University of Konstanz, Konstanz 78464, Germany
- International Max Planck Research School for Quantitative Behavior, Ecology and Evolution, Radolfzell 78315, Germany
| | - Sumantra Sarkar
- Department of Physics, Indian Institute of Science, Bangalore 560012, India
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
| | - Nico Gradwohl
- Department for the Ecology of Animal Societies, Max Planck Institute of Animal Behavior, Konstanz 78315, Germany
- Centre for the Advanced Study of Collective Behaviour, University of Konstanz, Konstanz 78464, Germany
- Department of Psychology, University of Konstanz, Konstanz 78464, Germany
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Abstract
Abstract
Quantifying and understanding group size distributions can be useful for understanding group behaviour in animal populations. We analysed group size data of the blackbuck, Antilope cervicapra, from six different field sites to estimate the group size distribution of this antelope. We used likelihood based methods (AICs and likelihood ratios) to show that an exponentially truncated power law is the distribution that best describes blackbuck group data, outperforming a simple power-law, an exponential distribution, and a lognormal distribution. Our results show that distribution parameters can be used to draw novel insights regarding group dynamics, and we demonstrate this by investigating how habitat openness affects group size distributions.
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Affiliation(s)
- Pranav Minasandra
- a Undergraduate programme, Indian Institute of Science, Bengaluru, Karnataka 560012, India
| | - Kavita Isvaran
- bCentre for Ecological Sciences, Indian Institute of Science, Bengaluru, India
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