Each new example of predictable evolution is striking. But, as Losos warned, we can’t be sure whether scientists have stumbled across a widespread pattern in nature. Certainly, testing more species will help. But Doebeli has taken a very different approach to the question: He’s using math to understand how predictable evolution is overall.
Doebeli’s work draws on pioneering ideas that geneticists like Sewall Wright developed in the early 1900s. Wright pictured evolution like a hilly landscape. Each point on the landscape represents a different combination of traits — the length of a lizard’s legs versus the width of its trunk, for example. A population of lizards might be located on a spot on the landscape that represents long legs and a narrow trunk. Another spot on the landscape would represent short legs and a narrow trunk. And in another direction, there’s a spot representing long legs and a thick trunk.
The precise combinations of traits in an organism will influence its success at reproducing. Wright used the elevation of a spot on the evolutionary landscape to record that success. An evolutionary landscape might have several peaks, each representing one of the best possible combinations. On such a landscape, natural selection always pushes populations up hills. Eventually, a population may reach the top of a hill; at that point, any change will lead to fewer offspring. In theory, the population should stay put.
The future of evolution might seem easy to predict on such a landscape. Scientists could simply look at the slope of the evolutionary landscape and draw a line up the nearest hill.
“This view is just simply wrong,” said Doebeli.
That’s because the population’s evolution changes the landscape. If a population of bacteria evolves to feed on a new kind of food, for example, then the competition for that food becomes fierce. The benefit of specializing on that food goes down, and the peak collapses. “It’s actually the worst place to be,” Doebeli said.
“Over short periods of time, it is predictable, if you have enough information. But you can’t predict it over long periods of time.”
To keep climbing uphill, the population has to veer onto a new course, toward a different peak. But as it travels in a new direction, it alters the landscape yet again.
- More from Carl Zimmer
Doebeli’s work draws on pioneering ideas that geneticists like Sewall Wright developed in the early 1900s. Wright pictured evolution like a hilly landscape. Each point on the landscape represents a different combination of traits — the length of a lizard’s legs versus the width of its trunk, for example. A population of lizards might be located on a spot on the landscape that represents long legs and a narrow trunk. Another spot on the landscape would represent short legs and a narrow trunk. And in another direction, there’s a spot representing long legs and a thick trunk.
The precise combinations of traits in an organism will influence its success at reproducing. Wright used the elevation of a spot on the evolutionary landscape to record that success. An evolutionary landscape might have several peaks, each representing one of the best possible combinations. On such a landscape, natural selection always pushes populations up hills. Eventually, a population may reach the top of a hill; at that point, any change will lead to fewer offspring. In theory, the population should stay put.
The future of evolution might seem easy to predict on such a landscape. Scientists could simply look at the slope of the evolutionary landscape and draw a line up the nearest hill.
“This view is just simply wrong,” said Doebeli.
That’s because the population’s evolution changes the landscape. If a population of bacteria evolves to feed on a new kind of food, for example, then the competition for that food becomes fierce. The benefit of specializing on that food goes down, and the peak collapses. “It’s actually the worst place to be,” Doebeli said.
“Over short periods of time, it is predictable, if you have enough information. But you can’t predict it over long periods of time.”
To keep climbing uphill, the population has to veer onto a new course, toward a different peak. But as it travels in a new direction, it alters the landscape yet again.
- More from Carl Zimmer
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