Simulating individual movement in fish
Abstract Accurately quantifying an animal’s movement is crucial for developing a greater empirical and theoretical understanding of its behaviour, and for simulating biologically plausible movement patterns. However, we have a relatively poor understanding of how animals move at fine temporal scales...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-09-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-40420-1 |
| _version_ | 1797452764848062464 |
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| author | Thomas W. Pike Oliver H. P. Burman |
| author_facet | Thomas W. Pike Oliver H. P. Burman |
| author_sort | Thomas W. Pike |
| collection | DOAJ |
| description | Abstract Accurately quantifying an animal’s movement is crucial for developing a greater empirical and theoretical understanding of its behaviour, and for simulating biologically plausible movement patterns. However, we have a relatively poor understanding of how animals move at fine temporal scales and in three-dimensional environments. Here, we collected high temporal resolution data on the three-dimensional spatial positions of individual three-spined sticklebacks (Gasterosteus aculeatus), allowing us to derive statistics describing key geometric characteristics of their movement and to quantify the extent to which this varies between individuals. We then used these statistics to develop a simple model of fish movement and evaluated the biological plausibility of simulated movement paths using a Turing-type test, which quantified the association preferences of live fish towards animated conspecifics following either ‘real’ (i.e., based on empirical measurements) or simulated movements. Live fish showed no difference in their response to ‘real’ movement compared to movement simulated by the model, although significantly preferred modelled movement over putatively unnatural movement patterns. The model therefore has the potential to facilitate a greater understanding of the causes and consequences of individual variation in movement, as well as enabling the construction of agent-based models or real-time computer animations in which individual fish move in biologically feasible ways. |
| first_indexed | 2024-03-09T15:13:23Z |
| format | Article |
| id | doaj.art-1bd4c67eab064501bdf865e767ea55da |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-09T15:13:23Z |
| publishDate | 2023-09-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-1bd4c67eab064501bdf865e767ea55da2023-11-26T13:13:05ZengNature PortfolioScientific Reports2045-23222023-09-0113111210.1038/s41598-023-40420-1Simulating individual movement in fishThomas W. Pike0Oliver H. P. Burman1Department of Life Sciences, University of LincolnDepartment of Life Sciences, University of LincolnAbstract Accurately quantifying an animal’s movement is crucial for developing a greater empirical and theoretical understanding of its behaviour, and for simulating biologically plausible movement patterns. However, we have a relatively poor understanding of how animals move at fine temporal scales and in three-dimensional environments. Here, we collected high temporal resolution data on the three-dimensional spatial positions of individual three-spined sticklebacks (Gasterosteus aculeatus), allowing us to derive statistics describing key geometric characteristics of their movement and to quantify the extent to which this varies between individuals. We then used these statistics to develop a simple model of fish movement and evaluated the biological plausibility of simulated movement paths using a Turing-type test, which quantified the association preferences of live fish towards animated conspecifics following either ‘real’ (i.e., based on empirical measurements) or simulated movements. Live fish showed no difference in their response to ‘real’ movement compared to movement simulated by the model, although significantly preferred modelled movement over putatively unnatural movement patterns. The model therefore has the potential to facilitate a greater understanding of the causes and consequences of individual variation in movement, as well as enabling the construction of agent-based models or real-time computer animations in which individual fish move in biologically feasible ways.https://doi.org/10.1038/s41598-023-40420-1 |
| spellingShingle | Thomas W. Pike Oliver H. P. Burman Simulating individual movement in fish Scientific Reports |
| title | Simulating individual movement in fish |
| title_full | Simulating individual movement in fish |
| title_fullStr | Simulating individual movement in fish |
| title_full_unstemmed | Simulating individual movement in fish |
| title_short | Simulating individual movement in fish |
| title_sort | simulating individual movement in fish |
| url | https://doi.org/10.1038/s41598-023-40420-1 |
| work_keys_str_mv | AT thomaswpike simulatingindividualmovementinfish AT oliverhpburman simulatingindividualmovementinfish |