Tools
Tools
Köhnke, MC, Siekmann, I and Malchow, H (2020) Taxis-driven pattern formation in a predator-prey model with group defense. Ecological Complexity, 43. ISSN 1476-945X
|
Text
Taxis_driven_pattern_formation_in_a_predator_prey_model_with_group_defense.pdf - Accepted Version Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (3MB) | Preview |
Abstract
We consider a reaction-diffusion(-taxis) predator-prey system with group defense in the prey. Taxis-driven instability can occur if the group defense influences the taxis rate (Wang et al., 2017). We elaborate that this mechanism is indeed possible but biologically unlikely to be responsible for pattern formation in such a system. Conversely, we show that patterns in excitable media such as spatiotemporal Sierpinski gasket patterns occur in the reaction-diffusion model as well as in the reaction-diffusion-taxis model. If group defense leads to a dome-shaped functional response, these patterns can have a rescue effect on the predator population in an invasion scenario. Preytaxis with prey repulsion at high prey densities can intensify this mechanism leading to taxis-induced persistence. In particular, taxis can increase parameter regimes of successful invasions and decrease minimum introduction areas necessary for a successful invasion. Last, we consider the mean period of the irregular oscillations. As a result of the underlying mechanism of the patterns, this period is two orders of magnitude smaller than the period in the nonspatial system. Counter-intuitively, faster-moving predators lead to lower oscillation periods and eventually to extinction of the predator population. The study does not only provide valuable insights on theoretical spatially explicit predator-prey models with group defense but also comparisons of ecological data with model simulations. © 2020 Elsevier B.V.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | 0501 Ecological Applications, 0502 Environmental Science and Management, 0602 Ecology |
| Subjects: | Q Science > QA Mathematics Q Science > QH Natural history Q Science > QH Natural history > QH301 Biology |
| Divisions: | Applied Mathematics (merged with Comp Sci 10 Aug 20) |
| Publisher: | Elsevier |
| Date Deposited: | 07 Jul 2020 09:04 |
| Last Modified: | 08 Feb 2024 14:15 |
| DOI or ID number: | 10.1016/j.ecocom.2020.100848 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/13262 |
 |
View Item |