Swarming Insects May Have Finely Tuned Characteristic Reynolds Numbers
Over the last few years, there has been much effort put into the development and validation of stochastic models of the trajectories of swarming insects. These models typically assume that the positions and velocities of swarming insects can be represented by continuous jointly Markovian processes....
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MDPI AG
2024-10-01
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| author | Andy Reynolds |
| author_facet | Andy Reynolds |
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| description | Over the last few years, there has been much effort put into the development and validation of stochastic models of the trajectories of swarming insects. These models typically assume that the positions and velocities of swarming insects can be represented by continuous jointly Markovian processes. These models are first-order autoregressive processes. In more sophisticated models, second-order autoregressive processes, the positions, velocities, and accelerations of swarming insects are collectively Markovian. Although it is mathematically conceivable that this hierarchy of stochastic models could be extended to higher orders, here I show that such a procedure would not be well-based biologically because some terms in these models represent processes that have the potential to destabilize insect flight dynamics. This prediction is supported by an analysis of pre-existing data for laboratory swarms of the non-biting midge <i>Chironomus riparius</i>. I suggest that the Reynolds number is a finely tuned property of swarming, as swarms may disintegrate at both sufficiently low and sufficiently high Reynolds numbers. |
| format | Article |
| id | doaj-art-e02dbc8bffd84c0bb010c1de8816ce40 |
| institution | OA Journals |
| issn | 2313-7673 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | MDPI AG |
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| series | Biomimetics |
| spelling | doaj-art-e02dbc8bffd84c0bb010c1de8816ce402025-08-20T02:28:07ZengMDPI AGBiomimetics2313-76732024-10-0191166010.3390/biomimetics9110660Swarming Insects May Have Finely Tuned Characteristic Reynolds NumbersAndy Reynolds0Rothamsted Research, Harpenden, Hertfordshire AL5 2JQ, UKOver the last few years, there has been much effort put into the development and validation of stochastic models of the trajectories of swarming insects. These models typically assume that the positions and velocities of swarming insects can be represented by continuous jointly Markovian processes. These models are first-order autoregressive processes. In more sophisticated models, second-order autoregressive processes, the positions, velocities, and accelerations of swarming insects are collectively Markovian. Although it is mathematically conceivable that this hierarchy of stochastic models could be extended to higher orders, here I show that such a procedure would not be well-based biologically because some terms in these models represent processes that have the potential to destabilize insect flight dynamics. This prediction is supported by an analysis of pre-existing data for laboratory swarms of the non-biting midge <i>Chironomus riparius</i>. I suggest that the Reynolds number is a finely tuned property of swarming, as swarms may disintegrate at both sufficiently low and sufficiently high Reynolds numbers.https://www.mdpi.com/2313-7673/9/11/660collective motionswarmingstochastic modellingturbulenceReynolds numbers |
| spellingShingle | Andy Reynolds Swarming Insects May Have Finely Tuned Characteristic Reynolds Numbers Biomimetics collective motion swarming stochastic modelling turbulence Reynolds numbers |
| title | Swarming Insects May Have Finely Tuned Characteristic Reynolds Numbers |
| title_full | Swarming Insects May Have Finely Tuned Characteristic Reynolds Numbers |
| title_fullStr | Swarming Insects May Have Finely Tuned Characteristic Reynolds Numbers |
| title_full_unstemmed | Swarming Insects May Have Finely Tuned Characteristic Reynolds Numbers |
| title_short | Swarming Insects May Have Finely Tuned Characteristic Reynolds Numbers |
| title_sort | swarming insects may have finely tuned characteristic reynolds numbers |
| topic | collective motion swarming stochastic modelling turbulence Reynolds numbers |
| url | https://www.mdpi.com/2313-7673/9/11/660 |
| work_keys_str_mv | AT andyreynolds swarminginsectsmayhavefinelytunedcharacteristicreynoldsnumbers |