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Merkle JA, Poulin MP, Caldwell MR, Laforge MP, Scholle AE, Verzuh TL, Geremia C. Spatial-social familiarity complements the spatial-social interface: evidence from Yellowstone bison. Philos Trans R Soc Lond B Biol Sci 2024; 379:20220530. [PMID: 39230449 DOI: 10.1098/rstb.2022.0530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2023] [Revised: 12/08/2023] [Accepted: 01/23/2024] [Indexed: 09/05/2024] Open
Abstract
Social animals make behavioural decisions based on local habitat and conspecifics, as well as memorized past experience (i.e. 'familiarity') with habitat and conspecifics. Here, we develop a conceptual and empirical understanding of how spatial and social familiarity fit within the spatial-social interface-a novel framework integrating the spatial and social components of animal behaviour. We conducted a multi-scale analysis of the movements of GPS-collared plains bison (Bison bison, n = 66) residing in and around Yellowstone National Park, USA. We found that both spatial and social familiarity mediate how individuals respond to their spatial and social environments. For instance, individuals with high spatial familiarity rely on their own knowledge as opposed to their conspecifics, and individuals with high social familiarity rely more strongly on the movement of conspecifics to guide their own movement. We also found that fine-scale spatial and social phenotypes often scale up to broad-scale phenotypes. For instance, bison that select more strongly to align with their nearest neighbour have larger home ranges. By integrating spatial and social familiarity into the spatial-social interface, we demonstrate the utility of the interface for testing hypotheses, while also highlighting the pervasive importance of cognitive mechanisms in animal behaviour. This article is part of the theme issue 'The spatial-social interface: a theoretical and empirical integration'.
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Affiliation(s)
- Jerod A Merkle
- Department of Zoology and Physiology, University of Wyoming , Laramie, WY, USA
| | - Marie-Pier Poulin
- Department of Zoology and Physiology, University of Wyoming , Laramie, WY, USA
| | - Molly R Caldwell
- Department of Zoology and Physiology, University of Wyoming , Laramie, WY, USA
- Program in Ecology and Evolution, University of Wyoming , Laramie, WY, USA
| | - Michel P Laforge
- Department of Zoology and Physiology, University of Wyoming , Laramie, WY, USA
- Faculty of Natural Resources Management, Lakehead University , Thunder Bay, ON, Canada
| | - Anne E Scholle
- Department of Zoology and Physiology, University of Wyoming , Laramie, WY, USA
- Program in Ecology and Evolution, University of Wyoming , Laramie, WY, USA
| | - Tana L Verzuh
- Department of Zoology and Physiology, University of Wyoming , Laramie, WY, USA
- Program in Ecology and Evolution, University of Wyoming , Laramie, WY, USA
| | - Chris Geremia
- Yellowstone Center for Resources, Yellowstone National Park, Mammoth Hot Springs , Yellowstone, WY, USA
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Williams DM, Beckert S, Martin JG, Blumstein DT. Agonistic and affiliative social relationships are associated with marmot docility but not boldness. Anim Behav 2023. [DOI: 10.1016/j.anbehav.2023.02.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/03/2023]
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Bierbach D, Gómez-Nava L, Francisco FA, Lukas J, Musiolek L, Hafner VV, Landgraf T, Romanczuk P, Krause J. Live fish learn to anticipate the movement of a fish-like robot . BIOINSPIRATION & BIOMIMETICS 2022; 17:065007. [PMID: 36044889 DOI: 10.1088/1748-3190/ac8e3e] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 08/31/2022] [Indexed: 06/15/2023]
Abstract
The ability of an individual to predict the outcome of the actions of others and to change their own behavior adaptively is called anticipation. There are many examples from mammalian species-including humans-that show anticipatory abilities in a social context, however, it is not clear to what extent fishes can anticipate the actions of their interaction partners or what the underlying mechanisms are for that anticipation. To answer these questions, we let live guppies (Poecilia reticulata) interact repeatedly with an open-loop (noninteractive) biomimetic robot that has previously been shown to be an accepted conspecific. The robot always performed the same zigzag trajectory in the experimental tank that ended in one of the corners, giving the live fish the opportunity to learn both the location of the final destination as well as the specific turning movement of the robot over three consecutive trials. The live fish's reactions were categorized into a global anticipation, which we defined as relative time to reach the robot's final corner, and a local anticipation which was the relative time and location of the live fish's turns relative to robofish turns. As a proxy for global anticipation, we found that live fish in the last trial reached the robot's destination corner significantly earlier than the robot. Overall, more than 50% of all fish arrived at the destination before the robot. This is more than a random walk model would predict and significantly more compared to all other equidistant, yet unvisited, corners. As a proxy for local anticipation, we found fish change their turning behavior in response to the robot over the course of the trials. Initially, the fish would turn after the robot, which was reversed in the end, as they began to turn slightly before the robot in the final trial. Our results indicate that live fish are able to anticipate predictably behaving social partners both in regard to final movement locations as well as movement dynamics. Given that fish have been found to exhibit consistent behavioral differences, anticipation in fish could have evolved as a mechanism to adapt to different social interaction partners.
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Affiliation(s)
- David Bierbach
- Faculty of Life Sciences, Thaer-Institute, Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Biology and Ecology of Fishes, Leibniz-Institute of Freshwater Ecology and Inland Fisheries, Berlin, Germany
- Excellence Cluster 'Science of Intelligence', Technische Universität Berlin, 10587 Berlin, Germany
| | - Luis Gómez-Nava
- Excellence Cluster 'Science of Intelligence', Technische Universität Berlin, 10587 Berlin, Germany
- Institute for Theoretical Biology, Department of Biology, Humboldt-Universität zu Berlin, 10115 Berlin, Germany
| | - Fritz A Francisco
- Excellence Cluster 'Science of Intelligence', Technische Universität Berlin, 10587 Berlin, Germany
- Institute for Theoretical Biology, Department of Biology, Humboldt-Universität zu Berlin, 10115 Berlin, Germany
| | - Juliane Lukas
- Faculty of Life Sciences, Thaer-Institute, Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Biology and Ecology of Fishes, Leibniz-Institute of Freshwater Ecology and Inland Fisheries, Berlin, Germany
| | - Lea Musiolek
- Excellence Cluster 'Science of Intelligence', Technische Universität Berlin, 10587 Berlin, Germany
- Adaptive Systems Group, Department of Computer Science, Humboldt-Universität zu Berlin, Germany
| | - Verena V Hafner
- Excellence Cluster 'Science of Intelligence', Technische Universität Berlin, 10587 Berlin, Germany
- Adaptive Systems Group, Department of Computer Science, Humboldt-Universität zu Berlin, Germany
| | - Tim Landgraf
- Excellence Cluster 'Science of Intelligence', Technische Universität Berlin, 10587 Berlin, Germany
- Department of Mathematics and Computer Science, Freie Universität Berlin, Berlin, Germany
| | - Pawel Romanczuk
- Excellence Cluster 'Science of Intelligence', Technische Universität Berlin, 10587 Berlin, Germany
- Institute for Theoretical Biology, Department of Biology, Humboldt-Universität zu Berlin, 10115 Berlin, Germany
- Bernstein Center for Computational Neuroscience, Berlin, Germany
| | - Jens Krause
- Faculty of Life Sciences, Thaer-Institute, Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Biology and Ecology of Fishes, Leibniz-Institute of Freshwater Ecology and Inland Fisheries, Berlin, Germany
- Excellence Cluster 'Science of Intelligence', Technische Universität Berlin, 10587 Berlin, Germany
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Familiarity effects on fish behaviour are disrupted in shoals that contain also unfamiliar individuals. Behav Ecol Sociobiol 2022. [DOI: 10.1007/s00265-022-03210-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
Abstract
Research on several social fishes has revealed that shoals constituted by familiar individuals behave remarkably differently compared to shoals formed by unfamiliar individuals. However, whether these behavioural changes may arise also in shoals composed by a mixture of familiar and unfamiliar individuals, a situation that may commonly occur in nature, is not clear. Here, we observed the behaviour of Mediterranean killifish (Aphanius fasciatus) shoals that were composed by both familiar and unfamiliar individuals (i.e. individuals were familiar to each other in pairs) and compared it with shoals entirely made by either unfamiliar or familiar individuals. Shoals formed by familiar individuals took longer to emerge from a refuge and swam more cohesively compared to shoals formed by unfamiliar fish. Shoals formed by a mixture of familiar and unfamiliar individuals behaved as shoals formed by unfamiliar individuals. Moreover, mixed shoals did not segregate in pairs according to their familiarity. This study suggests that mixed shoals do not show the behavioural effects of familiarity.
Significance statement
Laboratory studies have compared the behaviour of shoals formed by familiar fish versus shoals formed by unfamiliar fish, finding notable advantages in the former ones, such as improved antipredator and foraging behaviour. However, comparing these two opposite shoal types may not provide information on the natural situation, because in nature, shoals often change composition. We investigated how shoals formed by a mixture of familiar and unfamiliar fish behaved. We analysed shoals’ preference for open environment versus covers and shoals’ swimming cohesion. Results showed that shoals formed by both familiar and unfamiliar individuals mostly behave like shoals entirely formed by unfamiliar individuals. This suggests that the advantages of social groups formed by familiar fish might be hardly seen in nature for species in which shoal composition changes frequently.
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