In the mid-19th century, Charles Darwin unveiled a revolutionary idea. Darwin’s On the Origin of Species crashed through the existing dogma like a storm surge, proposing that life’s staggering diversity arose not from a creator’s whim but from a relentless, blind process: evolution by natural selection.
It was a radical idea that rippled far beyond biology, seeping into philosophy, religion, even our sense of self — suddenly, humans weren’t apart from nature, but a thread in its tangled weave.
Since then, scientists have refined and enriched the mechanisms of evolution. The most seismic addition came with the integration of Gregor Mendel’s genetics in the early 20th century, birthing the “Modern Synthesis,” which fused natural selection with the mechanics of heredity — showing how traits are passed through genes, not just vague “variations.” Molecular biology later revealed DNA as the raw material of evolution, unveiling mechanisms like genetic drift, gene flow, and mutations as key players alongside selection.
Darwin didn’t know about plate tectonics or mass extinctions, which we now recognize as sculptors of life’s diversity, nor could he foresee epigenetics, where environmental factors tweak gene expression without altering the code itself.
Another thing that Darwin likely didn’t foresee is that evolution itself could evolve. But what does that mean?
A new study, suggests just that. Evolutionary biologists have found evidence that the ability to evolve — a concept known as “evolvability” — can improve over generations. It’s another thread in a web of evolutionary complexity that may explain how life becomes so remarkably diverse.
A Digital Lab for Evolution
“Life is really, really good at solving problems,” said Luis Zaman, an evolutionary biologist at the University of Michigan and lead author of the study. “If you look around, there’s so much diversity in life, and that all these things come from a common ancestor seems really surprising to me. Why is evolution so seemingly creative? It seems like maybe that ability is something that evolved itself.”
In this study, scientists used a digital platform called Avida. It hosts tiny computer programs that replicate, mutate, and compete in a digital landscape. These programs develop mutations and traits the same way bacteria adapt in a petri dish — by trial, error, and the occasional lucky jump through mutation.
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The virtual organisms lived in environments with two types of berries: blue and red. In one scenario, blue berries were nutritious, and red ones were poisonous. In another, the roles were reversed. The organisms could evolve to eat one type of berry, but not both.
The researchers repeatedly flipped the conditions, forcing the virtual populations to adapt. Over time, something remarkable happened. The organisms became faster at adapting to new environments — but only if the changes weren’t too rapid. When the environment shifted too quickly, the populations couldn’t keep up. However, over tens or hundreds of generations, their ability to adapt improved and remained high.
“Once a population has achieved this evolvability, it seems like it didn’t get erased by future evolution,” Zaman said.
The researchers explain that high mutation rates create a diverse pool of individuals, some of which are better suited to new conditions. Over time, beneficial mutations accumulate, allowing populations to adapt more efficiently to challenges their ancestors faced.
It’s like evolution is hedging its bets. By increasing mutation rates and shaping the genetic neighborhood, populations can respond to both recurring and novel challenges.
The Dual Pathways to Evolvability
The study reveals that evolvability isn’t a single trait but a combination of strategies. One pathway involves the evolution of “mutational neighborhoods”. These are regions in the genetic landscape where mutations are more likely to produce beneficial traits. In environments that change predictably, populations evolve to have more access to these beneficial mutations, allowing them to adapt quickly when conditions shift back to a familiar state.
The second pathway involves the evolution of higher mutation rates. While most mutations are harmful, a higher mutation rate increases the chances of stumbling upon a beneficial change, especially in entirely new environments. The researchers found that in environments with intermediate rates of change, populations evolved both higher mutation rates and more accessible beneficial mutations.
It’s a delicate balance. Too many mutations can be harmful, but in the right environment, a higher mutation rate can be a powerful tool for adaptation.
Another intriguing pattern that emerged was that evolving populations tend to localize on the boundaries between different phenotypic regions in the genetic landscape. This positioning allows them to switch rapidly between traits, like a surfer riding the edge of a wave.
What This Means for the Real World
These findings help us see, in real-world terms, how a virus might tweak its protein coat or how a crop pest might dodge our best pesticides. When conditions shift predictably (such as recurring seasons or regularly changing drugs), organisms learn to walk that fine line between current survival and future flexibility.
But can digital results really apply to flesh-and-blood life? The authors argue that what happens in these digital cells echoes the fundamental processes that guide real organisms. Mutation, fitness, and natural selection operate according to the same basic principles, whether made of proteins or made of code. While digital organisms are far simpler than real-life species, they provide a controlled environment that allows scientists to essentially play a time-lapse video of evolution. Observing evolution for millions of years is simply not practical.
Could evolvability explain why some species, like bacteria, adapt so quickly to new threats, while others, like elephants, evolve more slowly? And what happens when environmental changes outpace a population’s ability to adapt?
For now, these findings introduce an intriguing concept: evolution is not just a process that shapes life. It is a process that can shape itself.
The findings were reported in the journal PNAS.