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COMPUTING SCIENCE

Experimental Lamarckism

Brian Hayes

Costs and Benefits

The rise and fall of melanism in the peppered moth was unquestionably a Darwinian event, brought about by natural selection acting on random mutations. Inheritance of acquired characteristics was impossible simply because there were no acquired characteristics to inherit. A moth has no way to change its color over the course of its lifetime, even if it could somehow figure out that making the change would be advantageous. And if the moth cannot adjust its color, it obviously cannot transmit any adjustments to its descendants.

But in imagination—or in the computer—we can rerun the experiment without the constraints of insect physiology. We can create chameleon moths that sense the color of their environment and adjust their own color to match. I shall refer to this adjustment process as learning, although it needn't imply any kind of cognitive capacity; the term is meant to encompass any adaptation within the lifetime of an organism.

Would moths that learn have an advantage over those that don't? It seems like a sure bet—and yet if adjustable camouflage is such an obvious asset, why don't all prey species have it? A likely answer is the no-free-lunch theorem. Learning has a cost, which in some cases may outweigh the benefits. At a minimum there is a complexity cost: Sensing the state of the environment and responding to it requires metabolic machinery that a simpler organism could do without. Building and maintaining that machinery incurs an energy cost; resources that might have gone into growth and reproduction have to be diverted into learning. Thus a creature that does a lot of learning could be expected to have a slower reproductive cycle than one with more hard-wired traits. (H. sapiens takes 20 or 30 years to accomplish what E. coli can do in 20 or 30 minutes.) Thus adjustable camouflage might reduce mortality, but the price would be reduced fertility.

The cost-benefit analysis for Lamarckism is similar. In a Darwinian world, any acquired improvements cannot cross the generation gap. A smart moth born with white wings might darken gradually to match a sooty environment, but the moth's offspring would be white again (barring mutations). The moth's acquired pigment is no more heritable than a suntan. Lamarckism creates a link between learning and genetics. A moth that adjusts its color during its lifespan will give birth to offspring that share at least some of this adjustment. Is this shortcut advantageous? Again it would seem so. The young moths are hatched with protective coloration already in place. But, as with learning, maintaining the Lamarckian mechanism imposes a metabolic cost, so that lowering the death rate limits the birth rate. The balance between these two effects determines whether Lamarckian inheritance pays off. Finding the point of balance is the aim of the computer simulation.





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