Visualizing evolution in action: Density-dependence and sympatric speciation

Fitness landscapes were invented by Sewall Wright in 1932. They map fitness, or reproductive success, of individual organisms as a function of genotype or phenotype. Organisms with higher fitness have a higher chance of reproducing, and populations therefore tend to evolve towards higher ground in the fitness landscape. Even though only two traits can be visualized this way, we can actually observe evolution in action. Building on the idea of fitness landscapes, Bjørn Østman and I decided to create some animations of simulated evolving populations to illustrate concepts of evolution that are typically difficult to comprehend.

Here we demonstrate how sympatric speciation can occur when fitness depends on the density of organisms, i.e., density-dependence.

Warning: The GIFs on this page are large and may take some time to load.

static-landscape


density-dependence


Here’s the full video that Bjørn and I submitted to the ALife 2014 Science Visualization Competition.

Randy is a PhD candidate in Michigan State University's Computer Science program. As a member of Dr. Chris Adami's research lab, he studies biologically-inspired artificial intelligence and evolutionary processes.

Posted in data visualization, research Tagged with: , , , , , ,
  • http://gravatar.com/samadamsthedog samadamsthedog

    Looking at the way the “plateau” is populated at high mutation rates, this seemed to me to be a close analogy to free energy in chemistry and physics, where mutation rate plays the role of temperature. As temperature increases, systems depopulate the energetically favorable regions and spread out over available states. It’s a pretty obvious analogy, but, I know little about evolutionary biology (after all, i’m only a dog), so let me ask: have you or others made anything of this connection?

  • http://pleiotropy.fieldofscience.com Bjørn Østman

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The data visualizations on this blog are the result of my “data tinkering” hobby, where I tackle a new data analysis problem every week. If I find something interesting, I report my findings here to share with the world.

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