The evolution of distributed sensing and collective computation in animal populations
Many animal groups exhibit rapid, coordinated collective motion. Yet, the evolutionary forces that cause such collective responses to evolve are poorly understood. Here, we develop analytical methods and evolutionary simulations based on experimental data from schooling fish. We use these methods to...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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eLife Sciences Publications Ltd
2015-12-01
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| Series: | eLife |
| Subjects: | |
| Online Access: | https://elifesciences.org/articles/10955 |
| _version_ | 1818018910516019200 |
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| author | Andrew M Hein Sara Brin Rosenthal George I Hagstrom Andrew Berdahl Colin J Torney Iain D Couzin |
| author_facet | Andrew M Hein Sara Brin Rosenthal George I Hagstrom Andrew Berdahl Colin J Torney Iain D Couzin |
| author_sort | Andrew M Hein |
| collection | DOAJ |
| description | Many animal groups exhibit rapid, coordinated collective motion. Yet, the evolutionary forces that cause such collective responses to evolve are poorly understood. Here, we develop analytical methods and evolutionary simulations based on experimental data from schooling fish. We use these methods to investigate how populations evolve within unpredictable, time-varying resource environments. We show that populations evolve toward a distinctive regime in behavioral phenotype space, where small responses of individuals to local environmental cues cause spontaneous changes in the collective state of groups. These changes resemble phase transitions in physical systems. Through these transitions, individuals evolve the emergent capacity to sense and respond to resource gradients (i.e. individuals perceive gradients via social interactions, rather than sensing gradients directly), and to allocate themselves among distinct, distant resource patches. Our results yield new insight into how natural selection, acting on selfish individuals, results in the highly effective collective responses evident in nature. |
| first_indexed | 2024-04-14T07:45:02Z |
| format | Article |
| id | doaj.art-2a0dac8c82f94224a0d6cf0029f9906d |
| institution | Directory Open Access Journal |
| issn | 2050-084X |
| language | English |
| last_indexed | 2024-04-14T07:45:02Z |
| publishDate | 2015-12-01 |
| publisher | eLife Sciences Publications Ltd |
| record_format | Article |
| series | eLife |
| spelling | doaj.art-2a0dac8c82f94224a0d6cf0029f9906d2022-12-22T02:05:21ZengeLife Sciences Publications LtdeLife2050-084X2015-12-01410.7554/eLife.10955The evolution of distributed sensing and collective computation in animal populationsAndrew M Hein0Sara Brin Rosenthal1George I Hagstrom2Andrew Berdahl3Colin J Torney4Iain D Couzin5Department of Ecology and Evolutionary Biology, Princeton University, Princeton, United StatesDepartment of Physics, Princeton University, Princeton, United States; Department of Collective Behaviour, Max Planck Institute for Ornithology, Konstanz, GermanyDepartment of Ecology and Evolutionary Biology, Princeton University, Princeton, United StatesSanta Fe Institute, Santa Fe, United StatesCentre for Mathematics and the Environment, University of Exeter, Penryn, United KingdomDepartment of Collective Behaviour, Max Planck Institute for Ornithology, Konstanz, Germany; Chair of Biodiversity and Collective Behaviour, University of Konstanz, Konstanz, GermanyMany animal groups exhibit rapid, coordinated collective motion. Yet, the evolutionary forces that cause such collective responses to evolve are poorly understood. Here, we develop analytical methods and evolutionary simulations based on experimental data from schooling fish. We use these methods to investigate how populations evolve within unpredictable, time-varying resource environments. We show that populations evolve toward a distinctive regime in behavioral phenotype space, where small responses of individuals to local environmental cues cause spontaneous changes in the collective state of groups. These changes resemble phase transitions in physical systems. Through these transitions, individuals evolve the emergent capacity to sense and respond to resource gradients (i.e. individuals perceive gradients via social interactions, rather than sensing gradients directly), and to allocate themselves among distinct, distant resource patches. Our results yield new insight into how natural selection, acting on selfish individuals, results in the highly effective collective responses evident in nature.https://elifesciences.org/articles/10955Collective BehaviorPhysical ComputationSwarmOptimizationDecision-makingExplore-exploit |
| spellingShingle | Andrew M Hein Sara Brin Rosenthal George I Hagstrom Andrew Berdahl Colin J Torney Iain D Couzin The evolution of distributed sensing and collective computation in animal populations eLife Collective Behavior Physical Computation Swarm Optimization Decision-making Explore-exploit |
| title | The evolution of distributed sensing and collective computation in animal populations |
| title_full | The evolution of distributed sensing and collective computation in animal populations |
| title_fullStr | The evolution of distributed sensing and collective computation in animal populations |
| title_full_unstemmed | The evolution of distributed sensing and collective computation in animal populations |
| title_short | The evolution of distributed sensing and collective computation in animal populations |
| title_sort | evolution of distributed sensing and collective computation in animal populations |
| topic | Collective Behavior Physical Computation Swarm Optimization Decision-making Explore-exploit |
| url | https://elifesciences.org/articles/10955 |
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