Speaker
Prof.
Oskar Hallatschek
(MPI)
Description
The spreading of evolutionary novelties across populations
is the central element of adaptation. Unless population are
well-mixed (like bacteria in a shaken test tube), the
spreading dynamics not only depends on fitness differences
but also on the dispersal behavior of the species. Spreading
at a constant speed is generally predicted when dispersal is
sufficiently short-ranged. However, the case of long-range
dispersal is unresolved: While it is clear that even rare
long-range jumps can lead to a drastic speed-up, it has been
difficult to quantify the ensuing stochastic growth process.
Yet, such knowledge is indispensable to reveal general laws
for the spread of modern human epidemics, which is greatly
accelerated by the human aviation. We present a simple
self-consistent argument supported by simulations that
accurately predicts evolutionary spread for broad
distributions of long distance dispersal. In contrast to the
exponential laws predicted by deterministic 'mean-field'
models, we show that growth is either according to a
power-law or a stretched exponential, depending on the tails
of the dispersal kernel. We also find that the actual
fitness advantage of the mutants has a surprisingly small
impact on the spreading dynamics. This conflicts with the
paradigm that the rapidity of a selective sweep is a good
measure for the selective advantage of the spreading
variant. Due to the simplicity of our model, which lacks any
complex interactions between individuals, we expect our
results to be applicable to a wide range of spreading
processes.
Primary author
Prof.
Oskar Hallatschek
(MPI)
