Skip to 0 minutes and 11 seconds In the previous lecture we have seen that even simple interactions can lead to very complicated dynamics. However, the interaction partners in biological systems are not fixed, but subject to ongoing evolution. How does evolution affect the interaction dynamics? This is the topic of the present lecture.
Skip to 0 minutes and 34 seconds Some biologists have argued that evolution is the general tendency to create order from chaos. Or, in other words, to proceed in the direction that chaotic dynamics are unlikely and the world is highly predictable.
Skip to 0 minutes and 51 seconds Others, mainly mathematicians, have argued that evolution has the tendency to shift the system to the edge of chaos. That is, to a state that is intermediate between being highly ordered and highly complex.
Skip to 1 minute and 7 seconds In this lecture I will shed some light on this debate, illustrating the role of evolution in the context of rock scissors paper dynamics.
Skip to 1 minute and 17 seconds Consider three different types of organisms, say, three different species of algae that are linked in a competitive cycle corresponding to the rock scissors paper game. Hence, the rock species is harmful to the scissors species, this scissors species is harmful to the paper species, and the paper species is harmful to the rock species.
Skip to 1 minute and 39 seconds When put together into competition, the three species start to oscillate in the characteristic manner. We can now add evolution to the system by creating mutants. That is, variants of the three strategies that differ slightly from the already-existing types. To be concrete, let’s consider the evolution of the degree of harm imposed by the rock species upon the scissors species.
Skip to 2 minutes and 7 seconds We start with a situation where the rock species imposes little harm, and that mutants once in awhile impose either slightly more or slightly less harm than their ancestors. The question then is, which of these mutants will be selected? In other words, which of these mutants will strive to replace their ancestors?
Skip to 2 minutes and 34 seconds Repeating this process many times, we can then see how natural selection affects the harmfulness of the rock species.
Skip to 2 minutes and 42 seconds Marcus Frean and Edward Abraham conducted such a simulation with the following result.
Skip to 2 minutes and 50 seconds First, we see that evolution leads to an increase of the harm imposed. In other words, evolution leads to more nasty strategies in this case. This result does perhaps not come unexpected. What is unexpected, however, is the fact that the evolutionarily successful mutants, which are more harmful to the scissors species, are actually also more harmful to themselves. This can be seen by the gradual decline of the abundance of rock individuals in the course of the generations.
Skip to 3 minutes and 27 seconds When giving it some thought, this all becomes less counterintuitive than it appears at first sight. More aggressive mutants of the rock strategy are successful in competition with other individuals in the rock species, since they exploit the scissors species more efficiently. Hence, they have a selection advantage in their own species.
Skip to 3 minutes and 52 seconds On the other hand, they weaken their own position in line with the saying “the enemy of my enemy is my friend.” The enemy of rock is paper, and scissors is the enemy of paper. Hence, by weakening scissors, aggressive rock mutants indirectly strengthen paper, their own worst enemy.
Skip to 4 minutes and 15 seconds This example shows the effects of evolution can be less straightforward than one might think. Natural selection tends to bring about more efficient strategies, but there’s no foresight, and quite often results in an outcome that is not really favourable for the evolving species.
Skip to 4 minutes and 36 seconds In fact, many evolutionary simulations of the rock scissors paper system considered above result in such an increase in aggressiveness that the aggressive species eventually goes extinct. In other words, seemingly successful strategies can succumb to their own success. And evolution can lead to sub-optimal outcomes, including extinction.
Skip to 5 minutes and 1 second This latter phenomenon, which happens in other models as well, is called evolutionary suicide.
Skip to 5 minutes and 10 seconds Let us now consider the effects of evolution on biological diversity. Here you see the ups and downs in the abundance of five species of algae that compete for a few resources in a droplet of water. Competition is non-transitive, and the dynamics is quite irregular. We now add three mutants, one in each of the three species, and watch how this affects the dynamics.
Skip to 5 minutes and 36 seconds The graphs show three typical outcomes if you run many simulations with the same three mutants but slightly different initial conditions.
Skip to 5 minutes and 46 seconds For a long period of time, almost nothing seems to happen, until eventually one of the three mutants emerges as the clear winner, fighting all its competitors to extinction. Hence, the advent of new mutants can eliminate the diversity and complexity of the system. Which of the three mutants will win is, however, completely unpredictable. Evolution can not only destroy diversity, it can also create high levels of diversity. Here’s a graph showing a long-term simulation in a situation where algae compete for three limiting resources. Every five days one new randomly-created mutant was added to the system. You see that, on the one hand, evolution can lead to an enormous buildup of diversity.
Skip to 6 minutes and 37 seconds But almost 100 species can coexist on only three limiting resources for hundreds of years. On the other hand, the kind of a new mutant can lead to the collapse of diversity from 550 or 100 species to only two or three that remain. Would we see a pattern like this in empirical data, we would undoubtedly ask ourselves, what the hell happened in year 2050 when there was a mass extinction? Apparently, there must have been a major and catastrophic change in the environment. This, however, was not the case. The whole simulation was run under absolutely constant external conditions and in the absence of any external chance events. The only stochastic factor was the generation of new mutants.
Skip to 7 minutes and 30 seconds The sudden and unexpected collapse of diversity is intriguing, but not really well-understood. In none of the cases where biodiversity collapsed was the collapse caused by the advent of the super-competitor that eliminated all inferior types. In contrast, the mutant that initiated the collapse typically went extinct together with most of its competitors.
Skip to 7 minutes and 56 seconds In this lecture, I’ve only shown examples of how evolution responds to and affects the dynamics of competitive cycles involving elements of non-transitive rock scissors paper types of interactions. But the two main conclusions to be drawn are actually much more general. First, natural selection leads to the evolution of strategies that are most efficient competitors within the species. It does not necessarily induce the evolution of properties that are optimal for the species as a whole. Second, evolution can create order from chaos by using the collapse of diverse systems with a high degree of dynamic complexity and limited predictability. But it can also lead to the buildup of diversity and dynamic complexity.
Skip to 8 minutes and 48 seconds There does not seem to be a general tendency, neither from chaos toward order, nor from order to more chaos, nor toward the edge of chaos.
Evolution in a complex world
This lecture goes into detail about the evolutionary process in a complex world. Does evolution proceed in a direction of where there is less chaos and the world is more predictable? Or does evolution have the tendency to shift a system to ‘the edge of chaos’?
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