True, but that’s not really the relevant question to ask. In fact, aging has a major impact on mortality in the wild, and this poses a dilemma for evolutionary theory. In the earliest stages of senescence, already an individual may be losing its competitive edge. When an epidemic passes through, those with compromised immune function are the first to die. When a predator is chasing the herd, those that cannot run quite as fast as they used to are caught at the back of the crowd. In this way, aging can have a big effect on fitness even if no one is “dying of old age”.
In 1951, Peter Medawar put forward the first modern theory for the evolution of aging. He was a self-made Brazilian giant, 6 foot 5, as charismatic as he was brilliant, and at the age of 36 he had achieved a prestigious appointment at University College, London. For his inaugural address, he chose to tackle an Unsolved Problem of Biology, and asked how aging in nature could be reconciled with Darwinian evolution.
There had been no evolutionary theory of aging in the 50 years since August Weismann had disavowed his own. Medawar was astute enough to realize that Weismann was correct to seek an evolutionary understanding of aging. Aging cannot be understood from thermodynamics or physical processes of attrition. No physical law requires aging. Medawar was also correct in judging that Weismann’s proposed solution was no solution at all. “Weismann caters twice round the perimeter of a vicious circle. By assuming that the elders of his race are decrepit and worn out, he assumes all but a fraction of what he has set himself to prove.”
Medawar proposed the theory that natural selection can only work on living, reproducing individuals. But in the wild, there are so many hazards that can lead to death that, past a certain age, there are very few remaining alive. In nature, everyone dies before they reach old age. This creates a “selection shadow”. Bodies are evolved to be healthy, strong or fertile up to the age where there are still survivors in nature. But at advanced ages, natural selection has never had an opportunity to work her magic, so we should not be surprised that the organism is ill-adapted and falls apart.
We get old and die because of evolutionary neglect. Natural selection needs living, reproducing individuals to select from, or it is ineffectual; hence we expect that aging takes over and the body deteriorates soon after that age at which predators and disease and other hazards of the wild have thinned the population near to zero.
The rest is history
Very quickly, Medawar’s idea was enshrined in the canon of evolutionary theory. Building on Medawar, two more ideas were added. One was the concept of “mutational load”. If there was no natural selection at work for “late-acting genes”, then random mutations would creep in, and this would account for the organism going to pot. This became the Mutation Accumulation theory. The other was the idea that selection at late ages may be weak but not zero, and it could then be overpowered by the drive to maximize fertility early in life, even if it had bad consequences for fitness later on. This became the Antagonistic Pleiotropy theory.
The idea that, in the wild, no one lives long enough to die of old age made a great deal of intuitive sense. George Williams (of the pleiotropy theory) added a refinement: that the early stages of senescence would likely have consequences for individual competitiveness, so he based his theory on the idea that selection against aging was weak but not zero. But everyone was agreed that the fitness consequences of aging were very slight, if not actually negligible.
Evolutionary theory went on to develop on this basis, and continued to be embellished for 40 years.
The inconvenient truth came to light gradually, and several decades on. In physics and chemistry, experimental science is an attractive calling because practitioners get to hang out in a lab and perform magic with nifty apparatus and spiffy electronics. But experimental ecology is a field science requiring travel to remote locations, and many lonely, patient hours of observation, away from the comforts of home. The work is often left to doctoral students who are in no position to protest.
So it was 25 more years before evidence started to accumulate that could bear on the question, how many animals in the wild are dying from the (early) effects of aging?
In principle, it is not hard to determine an answer. Collect carcasses in the woods and use established forensic techniques to estimate the age of the animal when it died. Once you have enough cases, you can plot a curve: how many deaths? (on the y axis) vs what age? (on the x axis). For example:
How to interpret the results? If there were no aging in the wild, then we must expect that the percentage of individuals dying at every age is the same. But the number remaining gets smaller and smaller, so the absolute number of deaths would go down with age. The math tells you that “no aging” corresponds to a falling exponential curve.
If the number that we actually find is flat with age, or even if it declines with age but not as rapidly as an exponential curve, this is evidence that aging is taking a toll on fitness in the wild.
It was 1991 before Daniel Promislow first collected and interpreted the appropriate statistics for 56 different mammals in the wild. He was a doctoral student at Oxford, and this study launched his career. In 46 of the 56 species, he found an increasing risk of death with age. In several species, data were complete enough that he was able to detect a Gompertz curve, meaning that for a given individual, risk of death climbs exponentially with age.
The Gompertz shape of the mortality curve had been known for 150 years—nothing new there. The surprise was that previous to Promislow, scientists had thought that the Gompertz shape only applies in protected environments, like humans in civilization and animals in zoos. In the wild, it was expected that (according to Medawar) everyone dies too early to see the rising shape of the Gompertz curve.
The significance of these results was not lost on Promislow. He boldly asserted that his results conflicted with the accepted evolutionary theories for aging. He was also modest and tactful enough to allow for reasons that his conclusion might be premature, and that adjustments could be made to permit the evolutionary theories to hold their own.
The Evidence Piles on
In 1998, Robert Ricklefs expanded on Promislow’s results by including more mammal surveys and some birds. Ironically, he titled his piece Confirmation of a Fundamental Prediction, but in fact the results made all the extant theories for evolution of aging quite untenable. He fitted mortality curves for each of the species in the study, and reported parameters from these curves. From these data, it is a small further step to answer the question, What proportion of deaths in species can be ascribed to aging? Ricklefs set up the equations and provided all the parameters, but he never completed the calculation. Later, I filled in those numbers, the “percentage of senescent deaths” for each species. You can read them in the column highlighted in orange.
As you can see, there are no animals for which the impact of senescence in the wild is negligible. Many are clusted in the range 15-30%. Some are over 70% — meaning, roughly, aging is reducing fitness in these species by more than 2/3.
Heroic field work
All the above work is based on field studies, data compiled after the fact through searching for remains. But the cleanest kind of study would be an experiment, planned in advance, where individual animals could be tracked in the wild and their fates determined by direct observation. As a Canadian grad student in the early 2000s, Russell Bonduriansky set himself the daunting task of individually labeling, releasing, and recapturing thousands of antler flies to answer directly, how did their risk of death change with age? His doctoral work was stunning enough to be profiled in Nature. The result: 28% of antler fly deaths were due to aging.
Nature doesn’t care if you die once your fertility is gone
The numbers above present a dilemma for evolutionary theory. Scientists dealing loosely with this question sometimes say, animals die once their fertility is ended. It’s no surprise that evolution has permitted these animals to age and die once they have reproduced and replaced themselves. But the theory can’t escape so easily, for two reasons.
First, this doesn’t answer the question, but only kicks the can down the road. Yes, there is no selective advantage to be gained by continuing to live on past the end of fertility. But why should fertility decline in the first place? Why haven’t we all adopted the growth pattern of trees and lobsters, continuing to grow and produce more offspring with each passing year? (Or, if there are size constraints that keep land animals from growing forever, at least we should be maintaining our fertility, not losing it with age.)
Second, responding to the argument about “once they have replaced themselves”… We should note that this is a flat denial of the dominant “selfish gene” view of evolution. In standard evolutionary theory, there is no such thing as “enough”, because individuals are in an arms race to dominate the next generation with their genes. If I have 6 offspring and you have 7, it will not be very many generations before my descendants are completely crowded out by yours (according to the way standard evolutionary calculations are performed). This perspective highlights the evolutionary paradox that natural selection has tolerated declining fertility and increasing mortality in so many different animal species.
The bottom line
Sixty years after Medawar, it is untenable to maintain that aging exists in a “selection shadow”. The negative consequence of aging for individual fitness is a force to be reckoned with. But theorists have yet to face this particular monster. I still hear Medawar’s hypothesis cited as gospel regularly in papers and at conferences. The disconnect between theory and observation is stark.
- The idea of “late-acting genes” made sense in the 1950s when Medawar and Williams were formulating their theories, but we now know that all living things have extensive machinery (epigenetics) for deciding when to turn particular genes on and off. Williams imagined that if a gene is beneficial at one stage of life, we would be stuck with it at another stage, when it is detrimental. We now know that genes are routinely turned on and off as needed.
- The idea that fitness depends on maximizing the number of offspring is enshrined in standard evolutionary theory, which is the “selfish gene” model. But there are many ways we know this cannot be right. Producing too many offspring can be just as disastrous for a species as producing too few. This is the inspiration for my Demographic Theory of Aging.
One of the theorists of aging with whom I’m tolerably familiar, Mikhail Blagosklonny, has written that animals don’t experience aging in the wild, and this seems to be central to his theory (mTOR drives aging). For example, he writes, “In the wild, organisms do not live long enough to experience aging.
Therefore, they do not need “brakes.” [something to stop mTOR from working] ” http://www.tandfonline.com/doi/pdf/10.4161/cc.8.24.10310 (2009)
If animals do age in the wild, then I don’t know what that does to his theory.
Great post, Josh, I learned a lot from that.
Well thank you very much Josh, it happens you’ve provided references that I need (I wonder if I could cite this article?).
In intra-specific competition for mating, aging would help offset the advantages in learning and territory (possessions) that an older animal would necessarily have, perhaps fine-tuning selection? Though if that were the case, then you’d expect that there would be a selection for later-appearing aging traits and we don’t really see any of that (mice have probably lived for 3 yrs for millions of years), so there must be an equilibrium which is broken when maximum lifespan is exceeded by potential lifespan (say a predator disappears)- and then perhaps there would be a selection for longer-lived individuals – that would account for the distributions we do see, where relatively safe habitats result in longer lives, squirrels, (25 yrs), compared to rats, (3 yrs), say. Selection for increased lifespan would then continue until a new equilibrium is reached.
Humans are the exceptions among mammals (or animals in general), they are the only mammals (along with killer whales and pilot whales), that stop breeding years before they die. Other animals continue to breed lifelong – so what determines the end of their reproductive age? Death.
> (I wonder if I could cite this article?).
Soon all science will be done by quoting Blog posts, dear Harold. : ) You might as well lead the pack. (not only in your theories ;-))
Not to say there won’t still be a role for journals of course but there will curation blogs too.
I think to disprove Medawar the question is not how many animal dies of old age in the wild, but how many animals reproduce at old age in the wild. Even if they keep their fertility – does it remain uncompromised in case of females? In case of males the disadvantage at mating in later age is too obvious.
I think this might be pretty hard to measure.
Perhaps animals in safer environments eviolve longer lifespans, like the naked mole rat. Or on secluded islands
I wonder if some degree of hormesis might be beneficial to animals as well.
It follows that if it is beneficial in humans, it may very well be beneficial in animals in the wild. Perhaps animals that are too successful, such as a predator that catches more than their fair share of prey versus a calorie restricted one may die sooner? Maybe this is a natural attempt to balance the predator, prey numbers?
Controversially, I also remember reading from Marios Kyriazis that he believes that a small dose of heavy metals may be quite helpful in exposure and may even have beneficial effects by helping the body adapt its repair mechanisms.
Or as the great philosopher, Bane, has said:
“Peace has cost you your strength. Victory has defeated you”.
The passing on of genes must be looked at on a tribal or community level. If a related animal helps a cousin survive then it’s genes do go on to the next generation. Think of wolf packs and ant nests.
Yes – the mechanics of kin selection are well-understood by most everyone in the field. We all agree that kin selection cannot account for the evolution of aging. The proof is short, but not necessarily easy to understand. By dying, I make room in the niche for exactly one individual. The coefficient of relatedness of a cousin might be 1/8 and of a daughter might be 1/2. But in order to have a “winning proposition” by the rules of kin selection, you would need a relatedness greater than 1, which is not possible.
(If this isn’t fully clear, you can read background by googling “Hamilton’s Rule”.)
But doesn’t this “mathz” ignore “boiler plate” code? Meaning all life on earth share a whole lot in common, which could help explain the evolution of empathy or otherwise cooperation amongst different species.. by helping a monkey you’re helping something 97-99% similar to you. If all your offspring died at birth ’cause their heads were too freakish gigantic, then maybe one could *consider* helping a dumber cousin. ^__^’
There is a subtle misunderstanding here about “selfish gene” dynamics.
Think about ONE GENE – a new mutation that makes me do something different. Suppose it makes me take big risks to care for my child. Well, there’s a 50% chance that my child also has this one gene, so the gene promotes behavior that takes care of ITSELF.
Now think about me and a chimpanzee who shares 97% of the same genes I have. I have a new mutation – ONE GENE that makes me want to take care of chimpanzees. The trouble is that the chimpanzee doesn’t have that gene because it’s not closely related to me. It doesn’t matter if I share 97% of my genes with the chimp, because the chimp doesn’t have this new mutant gene that makes me want to care for chimps. So selfish gene theory says that the first kind of gene will spread through the population (because it is a selfish gene), while the second kind of gene will die out, because its benefit is focused on chimps that don’t share that particular gene.
I am not an advocate of selfish gene theory, but I do think it’s important to understand what the theory says and how it’s supposed to work.
Oh.. I see. Thanks. =)
But, what do you mean by ” a “winning proposition””, in the context of the evolution of aging?
Oh I get it! I think what was blinding me is this (seemingly?) assumption they make that this stuff happens in maxed out / saturated / closed environments, thus no room for innovation / disruption / surpluses, arguably the core conditions of evolution itself (don’t you also find it ironic to put this into evolution theories? ^__^’). The technical term for this is: “LoLz”. : )
In truth the payoff function of death would be << 1, if this was the sole consideration of course. (which we both know it isn't).
I have a unsolvable dilemma: I don’t want to live long (not over 70-75) but I want to live very healthy until I die and I don’t want to commit suicide (not even indirectly)
Do you have a hint how to solve it ?
My suggestion is to focus on keeping yourself healthy and loving life in the present, and if there comes a time that you no longer wish to be alive, you can jump from that bridge when you come to it.
“you can jump from that bridge when you come to it”.
That’s the hardest part for a sane man.
On the subject:
The subjective passing of time is relative. When you are old the time pass faster (there are studies). Therefore a man who would live for example 120 years the last 50 years he experiences subjectively (approximately) as long as the first 10 or the 20 (from 20-40) and so on.
In fact I have predicted a sharp spike of the like once aging defeat’s get on the horizon of the mainstream. Or as Aubrey put it, “the sh** hit the fan”.. I mean.. the Death Trance is broken. 😀 (Yes, humans are strange.. some would say “ironic”, but I digress)
What I’m wondering about now is how to mitigate a tandem increase in wars. I posit having medicine for later middle age (or older) at the earliest would mitigate this. Other risky, although more productive/cooperative, endeavors should also help, say, Mars colonization, meteor mining, et cetera.
Just a slight caveat to beware about: A growing population can “shadow” (no pun intended with the old paradigm) the effects of aging; while a shrinking one could produce those results (emulate aging) even if there weren’t any. Shouldn’t be a matter tho, unless the particular species were either going extinct or overshooting its way into it. (which means it’s already rare enough to matter for you argument’s logic, although, I do wonder if old paradigm experimentalists could use this to keep the boat afloat a couple years longer ;-))
MM – could you flesh this out for me, please? I don’t understand.
Hi Josh, your reply isn’t aligning with any of my posts here (perhaps because I block most formatting scripts <:-|), so it's hard to tell which one you replied to, but I assume it's the one about the population size, so here's my answer:
In your post you say:
"How to interpret the results? If there were no aging in the wild, then we must expect that the percentage of individuals dying at every age is the same. But the number remaining gets smaller and smaller, so the absolute number of deaths would go down with age. The math tells you that “no aging” corresponds to a falling exponential curve."
I could be wrong of course (as if it would be the 1st time, hehehe), and aging would still cull everyone *proportionally* (i think is the keyword I'm getting at here) HOWEVER, it seems to me that if a population is producing more offspring, that is, growing, then more individuals would be able to survive to later ages. Specially since the logic seems to be predation? But then again we bumb against the dynamic feedback loops that bamboozles aging theories o____0" So I guess I'd have to risk abandoning KISS/Occam's Razor and posit yet another caveat (darn, I already feel like the opposers of "programmed" aging): predators reproduction would have to be slower. (sounds reasonable tho :p)
You do say "percentage" but then again the graph seems to plot absolute numbers? So I dunno ^_^
Then you go on to say:
"If the number that we actually find is flat with age, or even if it declines with age but not as rapidly as an exponential curve, this is evidence that aging is taking a toll on fitness in the wild."
The pernicious thing (however 'negligible') about the effect I describe (provided I'm not making yet another blunder in logic up there ^_^ you tell me), is that population change (specially growth, so I do predict it would be easier to "shadow" than "emulate", as exponential shrinkage would be a quick business indeed) can be exponential, so…
What do you think?
Thanks for considering : )
btw, am I seeing a clearer signal to noise ratio for aging amongst animals predaded by omnivores, or am I getting all John Nash on you now? <:-|
I was thinking about this issue again. The graph labeled “Figure 4” shows a rising mortality rate with age, but it doesn’t show how many of the animals died at a given age. It could be very small at advanced ages.
As for the numbers of age-related deaths, are we sure this isn’t the numbers of adults? Some species, rodents say, or fish, have extremely high mortality before maturity. I was able to find some information on rabbits (http://www.federaciongalegadecaza.com/biblioteca/coello/CIENTIFICAS_033.pdf). If I’m reading this correctly, ~90% of young rabbits did not live to adulthood. It seems very unlikely that many of these rabbits, from the same group that is, could have died of old age. Therefore, declining force of natural selection holds true in this example.
So I’m questioning this research. Obviously larger animals with smaller litters would have less infant mortality. But did the researchers take that into account? Or are these aging death rates only for adult animals? As far as I can see, that would make a big difference.
> “Fig 4 doesn’t show how many died at a given age…
The number who die at each age can be calculated from the given graph, but it takes some repeated arithmetic – probably better done in a spreadsheet. I’ve shown the calculation here. The age-zero mortality is 0.13, so there are (1-0.13)=87% left after the first year. The age-one mortality is 0.11, so of that 11% of that 87% die the next year leaving (1-0.11)87%=77% at age 2, etc.
> “~90% of young rabbits did not live to adulthood.”
Here it gets even more technical: as it turns out, this doesn’t matter. The rabbits that don’t survive to adulthood leave no progeny, so their existence is irrelevant to evolution. To estimate the selective impact of senescence on fitness, the right way to do the calculation is to start at maturity (call that 100%, even if lots have died before they got there), and then compare two calculations: first, the actuarial table as I did it in the above link, and second the hypothetical actuarial table using the minimum mortality rate (which is usually the first year of adulthood). It is the area between these two curves that determines the impact that senescence has had on fitness.
>”Therefore, declining force of natural selection holds true in this example.”
Not so obvious, I hope you see.
Well, you’re the expert. But if an animal dies before maturity, I don’t see how that isn’t as big a hit to its fitness as death from aging. Since there are far more that die before maturity, seems that evolution shouldn’t care much at all about the relatively few who die from aging.
This entire post is under the assumption that evolution would be solely fitted to competition and fitness, as in “the fittest”. But what does that have anything to do with cooperation and “the fit”, as in a species fitting into its environment.