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"Cylindrical worlds" in biology: Does the aggregation strategy give a selective advantage?
A E Filippov1, R Guillermo-Ferreira2, S N Gorb3
1Functional Morphology and Biomechanics, Zoological Institute, Kiel University, Am Botanischen Garten, 1-9, 24118, Kiel, Germany; Donetsk Institute for Physics and Engineering, National Academy of Sciences of Ukraine, Donetsk, Ukraine.
Bio Systems
|November 4, 2018
Summary
Insect prey gain survival advantages when aggregating on tree trunks. Numerical models show that prey hiding on the opposite side of a cylinder are highly likely to survive predator encounters due to limited predator visibility.
Area of Science:
- Ecology
- Theoretical Biology
- Mathematical Modeling
Background:
- Predator-prey dynamics are typically studied on 2D planes, which may not accurately represent environments like tree trunks where insects aggregate.
- Cylindrical environments present unique spatial challenges for predator-prey interactions compared to flat surfaces.
Purpose of the Study:
- To investigate the specificity of predator-prey interactions in a cylindrical space.
- To compare predator-prey dynamics on a 2D plane versus a 3D cylinder.
- To model the impact of prey aggregation and predator visual detection abilities in these environments.
Main Methods:
- Development of a numerical model to simulate predator-prey interactions.
- Testing the model on both a 2D plane and a 3D cylindrical surface.
- Varying parameters related to predator visual detection and prey aggregation behavior.
Main Results:
- Prey aggregation on cylindrical surfaces offers significant survival advantages.
- Prey subgroups hiding behind the cylinder (occluded by the horizon) exhibit extremely high survival rates.
- Predators moving around the cylinder can lose track of the majority of the prey group.
Conclusions:
- Cylindrical environments and prey aggregation create unique ecological dynamics.
- The 'horizon effect' on a cylinder provides a powerful survival mechanism for aggregated prey.
- Theoretical modeling is crucial for understanding complex spatial interactions in ecological systems.
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