Data from: Evolution transforms pushed waves into pulled waves
Cite this dataset
Erm, Philip; Phillips, Ben (2019). Data from: Evolution transforms pushed waves into pulled waves [Dataset]. Dryad. https://doi.org/10.5061/dryad.zpc866t52
Understanding the dynamics of biological invasions is crucial for managing numerous phenomena, from invasive species to tumours. While the Allee effect (where individuals in low-density populations suffer lowered fitness) is known to influence both the ecological and evolutionary dynamics of an invasion, the possibility that an invader's susceptibility to the Allee effect might itself evolve has received little attention. Since invasion fronts are regions of perpetually low population density, selection should be expected to favour vanguard invaders that are resistant to Allee effects. This may not only cause invasions to accelerate over time, but, by mitigating the Allee effects experienced by the vanguard, also make the invasion transition from a pushed wave, propelled by dispersal from behind the invasion front, to a pulled wave, driven instead by the invasion vanguard. To examine this possibility, we construct an individual-based model in which a trait that governs resistance to the Allee effect is allowed to evolve during an invasion. We find that vanguard invaders evolve resistance to the Allee effect, causing invasions to accelerate. This results in invasions transforming from pushed waves to pulled waves, an outcome with consequences for invasion speed, population genetic structure, and other emergent behaviours. These findings underscore the importance of accounting for evolution in invasion forecasts, and suggest that evolution has the capacity to fundamentally alter invasion dynamics.
Simulation output used to generate results and figures in 'Evolution transforms pushed waves into pulled waves'.
Output files are to be used with code located at https://github.com/PhilErm/allee-evolution. For scripts to call on output, output should be deposited in a folder called 'data' in the base directory.
Australian Research Council, Award: DP160101730