Digital Evolution Reveals The Many Ways To Get To Diversity

The riddle: Why are some habitats loaded with many more species than others?

The answer: Nature and evolution respect that there’s more than one way of doing things.

“What we’ve learned,” said Michigan State University scientist Charles Ofria, “is that if there isn’t just one way to succeed, you’ll see diversity.”

In an article published in the July 2 issue of Science, an interdisciplinary team of scientists at MSU, the California Institute of Technology and Keck Graduate Institute (KGI), with the help of powerful computers, has used a kind of artificial life, or ALife, to gain insight into questions of evolution.

Up to a point, organisms that are overachievers at what they do to survive – consume resources – will find there’s a ceiling to their good performance. Once they run low on resources, their ability to dominate loses steam and other hard-working organisms have a chance to get a foothold in the habitat.

Ofria, an MSU assistant professor of computer science and engineering and one of the paper’s authors, gives the example of an ambitious organism that eats glucose, a type of sugar. That organism is a glucose-eating machine, and the more it eats, the more it reproduces and dominates. But eventually, there are so many hungry organisms, and glucose starts to run out, so the population’s growth slows.

Meanwhile, he said, mutant fructose-eating organisms, which maybe aren’t quite so vociferous, haven’t run out of food. While their greedy neighbors are suffering from glucose famine, they are able to thrive and gain a foothold.

“We show why more than one species can exist in a place,” Ofria said.“We’ve found that in a place where resources are finite, there are limiting effects of productivity.”

The Alife program, called Avida, is basically an artificial petri dish in which organisms not only reproduce, but also perform mathematical calculations to obtain rewards. Rather than sugar, their reward is more computer time that they can use for making copies of themselves. The digital organisms come in different “species” – identifiable by the mathematical functions they perform.

Avida randomly adds mutations to the copies, thus spurring natural selection and evolution. The research team watches how the bugs adapt and evolve in different environments inside their artificial world.

Avida is the biologist's souped-up race car. To watch the evolution of most living organisms would require thousands of years – without blinking. The digital bugs evolve at lightning speed, and they leave tracks for scientists to study.

“These experiments allow us to look at long-standing questions in ecology, such as why certain environments support more species than others,” said Richard Lenski, MSU Hannah Distinguished Professor of microbial ecology and a co-author. “With Avida, we could look at changes in species diversity across thousands of generations, and see how the ecological relationship between environmental productivity and species diversity could be understood from an evolutionary perspective.”

Ofria points out that the evolutionary scenarios can be seen in the real world. Environments that are harsh and short on resources – like the arctic tundra or a desert – have comparatively little species diversity, not surprisingly perhaps. Unexpectedly, however, some natural environments that have a lot of resources support fewer species than environments that have more modest productivity, a surprising pattern that is also seen in the digital world.

The research seeks to answer questions of evolution that are a piece of the puzzle of understanding ecology.

“The better we understand how our world came about, we can begin to understand how to deal with it,” Ofria said. “Diversity is important to understand.”

In addition to Lenski and Ofria, the team consists of Stephanie Chow, graduate student in Computational & Neural Science at Caltech; Claus Wilke, research assistant professor at KGI; and Christoph Adami, professor of applied life sciences at KGI.

The research is funded by the National Science Foundation under its biocomplexity initiative, with additional funding from the MSU Foundation and KGI.