Aging destroys fitness. How could aging have evolved? Below is my answer to this question. This is mainstream science from peer-reviewed journals [Ref 1, Ref 2, Ref 3] , but it is my science, and as Richard Feynman warned us*, I’m the last one who can be objective about the merits of this theory. — Josh Mitteldorf
Too fit for its own good
In 1874, a swarm of Rocky Mountain Locusts descended on the American midwest. They covered the sky and shadowed the earth underneath for hundreds of miles. A single cloud was larger than the state of California. Once on the ground, they ate everything that was green, leaving behind a dust bowl. The earth was thick with egg masses, ready to renew the plague the following year.
Laura Ingalls Wilder wrote in her childhood memoir (in the third person)
Huge brown grasshoppers were hitting the ground all around her, hitting her head and her face and her arms. They came thudding down like hail. The cloud was hailing grasshoppers. The cloud was grasshoppers. Their bodies hid the sun and made darkness. Their thin, large wings gleamed and glittered. The rasping, whirring of their wings filled the whole air and they hit the ground and the house with the noise of a hailstorm. Laura tried to beat them off. Their claws clung to her skin and her dress. They looked at her with bulging eyes, turning their heads this way and that. Mary ran screaming into the house. Grasshoppers covered the ground, there was not one bare bit to step on. Laura had to step on grasshoppers and they smashed squirming and slimy under her feet.
The locusts returned in several more seasons, but the last reported sighting of a Rocky Mountain locust was in 1902. There are preserved specimens in museums and laboratories today, but no living locusts. Entomologists interested in the locust’s rise and fall travel to the glaciers of Wyoming, mining hundred-year-old ice for carcasses that they might study.
Where did they go? The Rocky Mountain Locust drove itself to extinction by overshooting its sustainable population.
Every animal species is part of a food web, and depends on an ecosystem to survive. If the ecosystem collapse, it takes down every species and every individual with it. Because of their mobility, the locusts were able to devastate many ecosystems, denuding one landscape, then flying hundreds of miles to deposit their children in a fresh location. Animals that can’t fly become victims of their own greed much more quickly than the locust. If the lions killed every gazelle on the Serengeti, how long would it be before the lions were gone, too?
Evolution of Individuals and Groups
How would an evolutionary biologist describe this situation? Were the locusts too fit for their own good? To capture this story, you have to distinguish between individual fitness and collective fitness. Individually, these locusts were super-competitors. Collectively, they were a circular firing squad. The science of individual fitness and collective fitness is called Multi-level Selection Theory, and it has been spearheaded by David S Wilson of Binghamton University, based on theoretical foundations by George Price. MLS is regarded with suspicion by most evolutionary biologists, but embraced by a minority as sound science.
Selfish organisms that consume as much of the available food species as possible may thrive for a time. They may crowd out other individuals of the same species that compete less aggressively. But as soon as their kind grows to be the majority, they are doomed – they wipe out the food source on which their children depend.
Animals are evolved to be “prudent predators”†. Species that have exploited their food sources too aggressively, or that have reproduced too fast have become extinct in a series of local population crashes. These extinctions have been a potent force of natural selection, counterbalancing the better-known selective pressure toward ever faster and more prolific reproduction.
How did Evolutionary Theory go Wrong?
This is an idea that has common-sense appeal to anyone who thinks logically and practically about evolutionary science. In order not to to appreciate this idea, you need years of training in the mathematical science of evolutionary genetics. Evolutionary genetics is an axiomatic framework, built up logically from postulates that sound reasonable, but the conclusions to which they lead are deeply at odds with the biological world we see. This is the “selfish gene” theory that says all cooperation in nature is a sort of illusion, based on a gene’s tendency to encourage behaviors that promote the welfare of other copies of the same gene in closely-related individuals.
The “selfish gene” is an idea that should have been rejected long ago, as absurd on its face. Yes, there is plenty of selfishness and aggression in nature. But nature is also rich with examples of cooperation between unrelated individuals, and even cooperation across species lines, which is called “co-evolution”. Species become intimately adapted to depend on tiny details of the other’s shape or habits or chemistry. Examples of this are everywhere, from the bacteria in your gut to the flowers and the honeybees. In the same way, predators and their prey (I’m using this word to include plant as well as animal food sources) adapt to be able to co-exist for the long haul. It is obvious to every naturalist that there is a temperance in nature’s communities, that when ecosystems are out of balance they don’t last very long.
It makes good scientific sense that extinctions from overpopulation are a powerful evolutionary force, and it is part of Darwin’s legacy as well. Natural selection is more than merely a race among individuals to reproduce the fastest. The very word “fitness” came from an ability to fit well into the life of the local community.
But beginning some forty years after Darwin’s death, mathematical thinking has led the evolutionary theorists astray. They have forgotten the first principle of science, which is that every theory must be validated by comparing predictions from the theory to the world we see around us. Predictions of the selfish gene theory work well in the genetics lab, but as a description of nature, they fail spectacularly.
Understanding Aging based on Multi-level Selection
If we are willing to look past the “selfish gene” and embrace the science of multi-level selection, we can understand aging as a tribute paid by the individual in support of the ecosystem. If it weren’t for aging, the only way that individuals would die would be by starvation, by diseases, and by predation. All three of these tend to be “clumpy” – that is to say that either no one is dying or everyone is dying at once. Until food species are exhausted, there is no starvation; but then there is a famine, and everyone dies at once. If a disease strikes a community in which everyone is at the peak of their immunological fitness, then either everyone can fend it off, or else everyone dies in an epidemic. And without aging, even death by predation would be very clumpy. Many large predators are just fast enough to catch the aging, crippled prey individuals. If this were not so, then either all the prey would be vulnerable to predators, or none of them would be. There could be no lasting balance between predators and prey.
Aging helps to level the death rate in good times and bad. Without aging, horde dynamics would prevail, as deaths would occur primarily in famines and epidemics. Population would swing wildly up and down. With aging comes the possibility of predictable life spans and death rates that don’t alternately soar and plummet. Ecosystems can have some stability and some persistence.
Aging is plastic, providing further support for ecosystem stability
This would be true even if aging operated on a fixed schedule; but natural selection has created an adaptive aging clock, which further enhances the stabilizing effect. When there is a famine and many animals are dying of starvation, the death rate from old age is down, because of the Caloric Restriction effect. In times of famine and other environmental stress, the death rate from aging actually takes a vacation, because animals become hardier and age more slowly.
When we ask “Why does an animal live longer when it is starving?” the answer is, of course, that the ability to last out a famine and re-seed the population when food once again becomes plentiful provides a great selective advantage. This may sound like it is an adaptation for individual survival, consistent with the selfish gene. But we might ask the same question conversely: “Why does an animal have a shorter life span when there is plenty to eat?” When we look at it this way, it is clear that tying aging to food cannot be explained in terms of the selfish gene. In order to be able to live longer under conditions of starvation, animals must be genetically programmed to hold some fitness in reserve when they have plenty to eat, and this offers an advantage only to the community, not to the individual.
Hormesis is an important clue concerning the evolutionary meaning of aging. This word refers to the fact that when an individual is in a challenging environment, its metabolism doesn’t just compensate to mitigate the damage, but it overcompensates. It becomes so much stronger that it lives longer with challenge than without. The best-known example is that people (and animals) live longer when they’re underfed than when they’re overfed. We also know that exercise tends to increase our life expectancy, despite the fact that exercise generates copious free radicals (ROS) that ought to be pro-aging in their effect.
Without aging, it is difficult for nature to put together a stable ecosystem. Populations are either rising exponentially or collapsing to zero. With aging, it becomes possible to balance birth and death rates, and population growth and subsequent crashes are tamed sufficiently that ecosystems may persist. This is the evolutionary meaning of aging: Aging is a group-selected adaptation for the purpose of damping the wild swings in death rate to which natural populations are prone. Aging helps to make possible stable ecosystems.
“ The first principle is that you must not fool yourself, and you are the easiest person to fool.” — R P Feynman (from the Galileo Symposium, 1964)
† Here “predator” can mean herbivore as well as carnivore. This is the common usage in ecology.