Gokhale CS, Traulsen A.
Mutualism and evolutionary multiplayer games: revisiting the Red King.
Proceedings of the Royal Society B: Biological Sciences.
Oct 11;279(1747):4611–6, 2012
“Now here you see, it takes all the running you can do, to keep in the same place. If you want to get somewhere else, you must run at least twice as fast as that” (The Red Queen) – Lewis Carroll (Through the Looking-Glass)
“Not on my watch” says the Red King (Bergstrom and Lachmann \& this paper)
Nature is often portrayed as red in tooth and claw with an overarching body of research focused on antagonistic relationships such as predator prey of host parasites. In such relationships it is proposed that it is always better to evolve faster than your antagonist. If the cheetahs start running faster then evolution favours even faster gazelles basically bringing the cheetahs back to square one. In the words of Lewis Carroll’s Red Queen from Through the Looking- Glass, “Now, here, you see, it takes all the running you can do, to keep in the same place”. In evolutionary theory this is often known as the Red Queen Hypothesis.
However, there are other types of interactions than just hostile coevolution. Mutualistic interactions are the ones in which both the interacting species benefit. In such situations it was proposed that the species which evolves slower can get a larger share of the benefit, thus putting forth a Red King hypothesis.
The analysis was based on pairwise interactions, for example when a single individual from a species interacts with a single individual from another species like a hummingbird and the flower it pollinates. But often interactions are not pairwise and a number of individuals from one species can interact with a number of individuals from another species for example ant-aphid mutualism. In such cases the analysis can be much more complicated and we resort to multiplayer evolutionary game theory to address this complexity.
We find that where pairwise analysis predicts that evolving slower is better, a multiplayer analysis of the same case can predict that evolving faster is better. So the picture is much more complex and a larger share of the benefit cannot be obtained by just tweaking the rate of evolution but it has to evolve in the light of interacting group size as well. This mathematical study thus brings into focus the complex interplay of the evolution of the rate of evolution and the evolution of group size, particularly in a mutualistic setting.