grandmother hypothesis natural selection

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Grandmothering and natural selection

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1 Department of Human Evolution, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, 04103 Leipzig, Germany. [email protected]
PMID: 20739319
PMCID: PMC3013409
DOI: 10.1098/rspb.2010.1247

Humans are unique among primates in that women regularly outlive their reproductive period by decades. The grandmother hypothesis proposes that natural selection increased the length of the human post-menopausal period-and, thus, extended longevity-as a result of the inclusive fitness benefits of grandmothering. However, it has yet to be demonstrated that the inclusive fitness benefits associated with grandmothering are large enough to warrant this explanation. Here, we show that the inclusive fitness benefits are too small to affect the evolution of longevity under a wide range of conditions in simulated populations. This is due in large part to the relatively weak selection that applies to women near or beyond the end of their reproductive period. However, we find that grandmothers can facilitate the evolution of a shorter reproductive period when their help decreases the weaning age of their matrilineal grandchildren. Because selection favours a shorter reproductive period in the presence of shorter interbirth intervals, this finding holds true for any form of allocare that helps mothers resume cycling more quickly. We conclude that while grandmothering is unlikely to explain human-like longevity, allocare could have played an important role in shaping other unique aspects of human life history, such as a later age at first birth and a shorter female reproductive period.

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Age-dependent mortality (grey) and fertility…

Age-dependent mortality (grey) and fertility (black) trajectories. Male and female mortality is based…

The effect of weaning age…

The effect of weaning age on mean longevity ( x L , blue),…

The effect of grandmothering on…

The effect of grandmothering on mean longevity ( x L , blue) and…

The lifetime inclusive fitness effects…

The lifetime inclusive fitness effects of grandmothering. Each data point represents the mean…

A reappraisal of grandmothering and natural selection. Hawkes K, Kim PS, Kennedy B, Bohlender R, Hawks J. Hawkes K, et al. Proc Biol Sci. 2011 Jul 7;278(1714):1936-8; discussion 1939-41. doi: 10.1098/rspb.2010.2720. Epub 2011 Apr 6. Proc Biol Sci. 2011. PMID: 21471113 Free PMC article. No abstract available.

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Article Contents

Introduction, a grandmother hypothesis for the evolution of human life history, fisher’s reproductive value, inclusive fitness, the fisher condition, sex ratios, sex allocation, and sexual conflict, concluding discussion, acknowledgments.

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The Centrality of Ancestral Grandmothering in Human Evolution

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Kristen Hawkes, The Centrality of Ancestral Grandmothering in Human Evolution, Integrative and Comparative Biology , Volume 60, Issue 3, September 2020, Pages 765–781, https://doi.org/10.1093/icb/icaa029

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When Fisher, Williams, and Hamilton laid the foundations of evolutionary life history theory, they recognized elements of what became a grandmother hypothesis to explain the evolution of human postmenopausal longevity. Subsequent study of modern hunter-gatherers, great apes, and the wider mammalian radiation has revealed strong regularities in development and behavior that show additional unexpected consequences that ancestral grandmothering likely had on human evolution, challenging the hypothesis that ancestral males propelled the evolution of our radiation by hunting to provision mates and offspring. Ancestral grandmothering has become a serious contender to explain not only the large fraction of post-fertile years women live and children’s prolonged maturation yet early weaning; it also promises to help account for the pair bonding that distinguishes humans from our closest living evolutionary cousins, the great apes (and most other mammals), the evolution of our big human brains, and our distinctive preoccupation with reputations, shared intentionality and persistent cultural learning that begins in infancy.

Since the 19th century, a favored explanation for the evolution of late maturation, big brains, long lifespans, and pair bonding that characterize humans points to hunting by ancestral males to provision their mates and offspring. As elaborated in the last several decades, the hunting hypothesis proposes that spreading savannas in ancient Africa made hunting a promising way to make a living. Since dependent offspring could interfere with prey pursuit, ancestral mothers did better to pair with a hunting mate; paternal provisioning thus made nuclear families elementary economic and social units with a sexual division of labor (e.g., Washburn and Lancaster 1968 ; Lancaster and Lancaster 1983 ; Lancaster et al. 2000 ; Kaplan et al. 2000 ; Kaplan and Robson 2002 ; Kaplan and Gurven 2005 ). The stone tools and bones of multiple large ungulates that compose the earliest archaeological sites seemed hard evidence that ancestral hunters brought theirkills home to mates and offspring (e.g., Isaac 1978 ).

Re-examination of the ecological context and assemblage composition of the early sites finds they more likely represent near-kill/ambush/scavenging locations than ancient home bases ( O’Connell et al. 1988a , 1988b , 1999 , 2002 ; Hawkes 2016 ). Quantitative behavioral observations of living people who forage for a living find high daily failure rates for big animal hunting combined with wide distribution of the occasional bonanzas. Unpredictability and collective consumption make successes notable. But those features also make big carcass acquisition unsuited to meeting anyone’s daily consumption needs—let alone those of dependent children ( Hawkes 1990 , 1991 , 1993a ; Hawkes et al. 1991 , 2001a , 2001b , 2014 , 2018 ; Marlowe 2007 , 2010 ). The salience of hunting reputations (e.g., Bliege Bird et al. 2001 ; Smith 2004 ) and the rich ethnographic evidence that men’s alliances dominate community affairs (e.g., Smuts 1992 ; Rodseth 2012 ) make male status competition a better candidate than family provisioning to explain why men hunt ( Hawkes 1990 , 1991 , 1992 , 1993a,b ; Hawkes et al. 1991 , 2001a , 2001b , 2014 , 2018 ; Hawkes and Bliege Bird 2002 ). Male-biased mating sex ratios that accompanied the evolution of our postmenopausal lifespans ( Coxworth et al. 2015 ) point to the probable importance of mate guarding rather than household provisioning in the evolution of our pair bonding habits. Mathematical modeling implicates sexual selection and sexual conflict in the evolution of our exceptional longevity ( Chan et al. 2016 , 2017 ).

My aim here is to explain the basis for a grandmother hypothesis about human evolution and then highlight insights about grandmothering mentioned by the architects of evolutionary life history theory as they developed the concepts of reproductive value, inclusive fitness, adaptive sex ratios, and sexual conflict. They ignored their grandmothering insights in pursuit of other questions, but subsequent evidence about primate phylogeny, population age structures, foraging strategies, and social behavior as well as mammalian brain development and social cognition now link those insights to the key role of ancestral grandmothers in human evolution. By highlighting inferences that the founders recorded but did not exploit themselves, I both applaud their prescience and hope to enlist others to help take more advantage of them.

It is widely agreed that the evolution of human life history began in the context of ancient climate changes that had started in the Miocene, constricting African forests and spreading savanna habitats. In forests, ancestral populations likely relied on fruits and leaves as great apes continue to do today. Ancestral nursing infants, carried by mother, likely began picking and eating the same foods that she was eating just as ape infants do today ( Fletcher 2001 ; van Noordwijk et al. 2009 , 2013 ; Bădescu et al. 2017 ; Bray et al. 2018 ). As more open habitats spread, and seasonal swings steepened, plants that sequester nutrients in geophytes and hard-shelled nuts flourished: opportunities that ancestral populations could exploit. The scenario we hypothesize ( Hawkes et al.1997 , 1998 , 2018 ; Blurton Jones et al. 1999 ; O’Connell et al. 1999 , 2002 ; Alvarez 2000 ; Hawkes 2003 , 2006, 2014 , 2016 ; Hawkes and Coxworth 2013 ; Blurton Jones 2016 ; Parker et al. 2016 ) can be summarized as follows.

Economics of foraging for savanna resources

Ancestral adults could colonize more open habitats to take advantage of savanna resources, pursuing and processing more than enough food for their own consumption. But, as with modern humans today, youngsters were not big enough or strong enough to earn high enough return rates on these foods to feed themselves (e.g., Blurton Jones et al. 1989 ; Hawkes et al. 1995a ; Blurton Jones 2016 ; Crittenden 2016 ). Mothers in those habitats would have to subsidize offspring while they were nursing and then continue to invest more in each one, lengthening their birth intervals. But unlike mothers’ milk, these foods could be supplied by others big and strong enough to handle them.

Of special importance, the savanna foods of interest do not promote scramble or interference competition where more consumers reduce everyone’s return rates because amounts available for consumption increase with extraction and processing effort. Foragers get mutualistic advantages from gregarious acquisition. Deeply buried geophytes allow increasing rather than diminishing returns for additional effort. Return rates are higher for accumulating piles and bulk processing rather than extracting, processing, and consuming items one at a time. All such economies of scale multiply with cooking ( O’Connell et al. 1999 ; Hawkes and Coxworth 2013 ; Parker et al. 2016 ) where start-up costs and maintenance of cooking fires increase marginal benefits for mutual batch processing.

Production of food in lumps in contrast to hand-to-mouth, eat-as-you-go foraging also results in opportunities for others to appropriate shares ( Blurton Jones 1987 ). This was noted by Wrangham et al. (1999 ), Wrangham (2009 ) in association with review of evidence for the importance of cooking in human evolution. Wrangham inferred that risks of robbery for batches of resources would be grounds for enlisting a mate as guard. But we have drawn attention instead to the likely appropriators most immediately at hand: dependent juveniles ( Hawkes and Coxworth 2013 ; Parker et al. 2016 ; Hawkes et al. 2018 ).

Age and sex preferences, risky versus predictable resources

Although systematic behavioral observations of Ache hunter-gatherers in the forest of eastern Paraguay quantified high failure rates and collective consumption that made men’s preferred resources unsuitable for paternal provisioning (Kaplan et al. 1984 ; Hawkes 1990 , 1991 , 1992 , 1993a,b ; Hill and Kaplan 1993 ), it was subsequent ethnographic observations of age and sex differences in foraging among Hadza hunter-gatherers just south of the Serengeti in northern Tanzania that prompted this grandmother hypothesis about the evolution of human life history ( Blurton Jones et al. 1989 ; Hawkes et al. 1995a , 1997 , 1998 , 2018 ; O’Connell et al. 1999 , 2002 ; Hawkes 2003 , 2014 , 2016 ; Hawkes and Coxworth 2013 ; Blurton Jones 2016 ). Hadza men hunt big game. With powerful bows and arrows, they were always successful at aggressively scavenging carcasses from carnivores. But their average rate of large carcass acquisition by both means was less than 3.4% per hunter-day ( Hawkes et al. 1991 , 2001a ). The hunter credited with the kill got no special share for his household ( Hawkes et al. 2001 b, 2014 ). Meanwhile, older women’s foraging productivity was high ( Hawkes et al. 1989 ); and, although children were active foragers ( Blurton Jones et al. 1989 ), youngsters are too small to be very effective at digging the deeply buried tubers that are year-round staples ( Blurton Jones et al. 1989 ; Hawkes et al. 1995a ; Blurton Jones and Marlowe 2002 ). Children’s weight gains depended on their mothers’ foraging effort until she had a new baby and that relationship disappeared; then weaned children’s gains depended on grandmothers’ foraging ( Hawkes et al. 1997 , 2001a ). Effects of grandmothers on grandchild survival are large in this population ( Blurton Jones 2016 ).

If modern mothers and grandmothers foraging in such savanna habitats leave more descendants with this division of labor, then similar tradeoffs could have driven the ancestral evolution of human age-structures. Unlike humans, great apes become decrepit with age in their mid-30s ( Goodall 1986 ) and rarely out-live their fertility ( Hill et al. 2001 ; Hawkes 2003 ; Emery Thompson et al. 2007 ; Hawkes and Smith 2010 ; Muller and Wrangham 2014 ; Wood et al. 2017 ; Emery Thompson and Sabbi 2019 ). Humans have much lower adult mortality rates. People who survive to adulthood remain healthy and productive decades longer, and women usually live well past menopause ( Blurton Jones et al. 2002 ; Hawkes 2003 ; Gurven and Kaplan 2007 ). Our postmenopausal life stage ( Levitis et al. 2013 ) is not shared by other primates ( Alberts et al. 2013 ).

Phylogenetic context of human life history evolution

Our human radiation evolved within the hominid family where genetic evidence now places genus Pan (chimpanzees and bonobos) closer to us than to gorillas, themselves closer to us than to orangutans ( Perelman et al. 2011 ; Prado-Martinez et al. 2013 ; Groves 2018 ). While hominids are the largest bodied, largest brained, latest weaning, and longest maturing of all the primates, the non-human hominids have smaller brains, shorter adult lifespans, earlier ages at maturity, and yet later weaning ages with longer birth spacing than we do (e.g., Hawkes et al. 1998 ; Robson et al. 2006 ). Similarities among our closest living cousins are grounds for inferring features that likely characterized our most recent common ancestors. As in other primate taxa, females reach menopause—if they live long enough; but unlike us, they rarely survive beyond their cycling years ( Emery Thompson et al. 2007 ; Herndon et al. 2012 ). Female fertility ends at about the same age in all hominids, making that likely an ancestral feature. Yet vital rates for living people who forage for a living ( Howell 1979 ; Hill and Hurtado 1996 ; Blurton Jones 2016 ) show girls that survive to adulthood are very likely to long survive their fertility, just as in agricultural and industrial populations. Distinctively large fractions of human female-adult-years are lived after menopause ( Alberts et al. 2013 ; Levitis et al. 2013 ).

Grandmothering in the context of systematic variation in mammalian life histories

Charnov noted that among female mammals average adult lifespan and age at first birth vary with body size at the same allometric rate and constructed a model of female life history evolution aimed at explaining the allometries ( Charnov 1991 , 1993 ). From mice to elephants, the product of the average age at first birth and adult mortality (the inverse of average adult lifespan) is nearly constant, an invariance that Charnov explains as a trade-off between benefits of growing longer before reproducing and risk of dying first. Charnov (1993) plotted primate data (from Harvey and Clutton-Brock 1985 ) to show the correlation between age at first birth and female adult lifespan. At the time the other great apes were classified together as pongids with humans the only hominids and Charnov’s figure includes a point for each. Both fit nicely on the regression, with humans—of course—the highest point. Unremarked at the time, this should have been puzzling. Human females, unlike the other primates, do not continue bearing offspring throughout adulthood. As I review below, both Fisher (1930) and Hamilton (1966) had noted that post-fertile women reproduce their genes through grandmothering. If ancestral grandmothers’ contribution to the ancestry of future generations explains why humans fit that mammalian invariant, it should imply another distinctive, measurable consequence within the model. Rates of baby production should be higher (birth intervals shorter), than predicted for non-grandmothering mammals with our age at first birth. Demographic estimates for ethnographic hunter-gatherers are directly consistent with that expectation ( Hawkes et al. 1998 ; Robson et al. 2006 ; Blurton Jones 2016 ).

Mathematical modeling of the grandmother hypothesis

Yet, could grandmothering subsidies actually propel the shift from ancestral great ape-like life histories to human-like ones? In mathematical models that assume the allometric relationships identified in Charnov’s model for female mammals and start at equilibrium population age structures like those of living great apes, two-sex models show that the addition of grandmothers’ subsidies does just that ( Kim et al. 2012 , 2014 , 2019 ; Chan et al. 2016 , 2017 ). Kim’s agent-based models begin with a great ape-like life history and with longevity mutating and so available to selection, simulations maintain that equilibrium over a million (simulated) years with very few females outliving their fertility. When those few can subsidize dependents, mothers bear next offspring sooner. Subsidizing grandmothers leave more descendants. That drives simulations from the great ape-like equilibrium to new equilibrium age structures like those of living hunter-gatherers where about a third of the adult females are past their childbearing years.

Kim’s initial models ( Kim et al. 2012 , 2014 ) fixed the end of childbearing at age of 45 years based on the similarity between humans and great apes. The question “why 45?” was explicitly left for subsequent work with the aim to see whether, given that end to female fertility, grandmothering could nevertheless propel the evolution of postmenopausal longevity. Since the end of female fertility varies among the mammals—earlier in monkeys than in apes and extending to even older ages in some mammals (e.g., two decades longer in elephants, Moss 2001 ; Lee and Moss 2011 )—we surmised it was selection, not some constraint of biochemistry that accounts for the persistence of ancestral female fertility termination as longevity increased. Tradeoffs between continued fertility on the one hand or more grandmothering subsidies on the other as suggested by our Hadza data seemed likely. Modeling then took up that trade-off ( Chan et al. 2016 , 2017 ; Kim et al. 2019 ). Two-sex models that allow both longevity and the end of female fertility to evolve show that grandmothers’ subsidies alone increase longevity and also hold the end of female fertility below 50 years.

Mating sex ratio consequences of our postmenopausal longevity

These models of the evolutionary consequences of grandmothering assume that the cost of greater longevity in females is later age at first parturition and longer offspring dependence as in Charnov’s mammal model. However, Kim’s and Chan’s models include both sexes. Increased longevity gives males more paternity chances, at the cost of lower success in competition with shorter lived males. Offspring inherit the mean of their parents’ expected adult lifespans. When grandmothers subsidize dependents, mothers have next offspring sooner, so subsidizing grandmothers have more descendants. As longer-lived grandmothers can subsidize more, the older fraction of the population increases. When the age of female fertility ends is also allowed to evolve, it remains little changed. Since old males continue to be fertile—consistent with mammalian reproductive physiology where spermatogenesis persists through adulthood, the survival of those old males turns the sex ratio in the fertile ages from female- to male-biased.

Coxworth et al. (2015) highlighted these changes in mating sex ratios that come along with our grandmothering life history by running simulations of Kim et al.’s (2014) agent-based grandmothering model, plotting the sex ratio in the fertile ages instead of longevity. Attention to that fertile-age sex ratio and consequences for mating strategies has grown in the past couple of decades (see, e.g., Schact et al. 2017). Widespread usage labels the sex ratio in the fertile ages “the Adult Sex Ratio” (ASR) since adulthood in most animals is spent producing offspring (more on this below). In our lineage, however, a substantial fraction of female adult years-lived is post-fertile. Older fertile males push the sex ratio in the fertile ages from the female bias—typical of mammals generally—to become male biased. The more male-biased these ratios are the fewer conception opportunities per male. When the pool of competitors is large, guarding a current mate can give higher fitness benefits than competing for another.

Focusing only on male mating strategies, Schacht and Bell (2016) , Loo et al. (2017a , 2017b ) have modeled the effects of varying mating sex ratios on the relative success of three male strategies: multiple mating, dependent care, and mate guarding ( Hawkes et al. 1995b ). Models converge on a poor showing for dependent care, dominance of multiple mating when sex ratios are female biased, then mate guarding becomes the winning strategy when the bias is toward males—although when the switch occurs depends on the effectiveness of guarding ( Loo et al. 2017b ). These findings and observations about the effects of mating sex ratios on male strategies across a wide range of species suggest “that human pair bonds evolved with increasing payoffs for mate guarding, which resulted from the evolution of our grandmothering life history” ( Coxworth et al. 2015 , 11810).

Increased longevity and the evolution of big human brains

The fundamental role of adult mortality (indexed by average adult lifespan) and the correct scaling relationships among life history traits are central to Charnov’s (1993) explanation for the variation in female mammal life histories. Lower adult mortality favors lengthened duration of development, and that is also correlated with expanding brain size ( Gonzalez-Lagos et al. 2010 ). As final brain size expands, brain components increase allometrically, across the eutherian mammals, their proportion of the whole scaling with adult brain volume ( Finlay and Darlington 1995 ; Reep et al. 2007 ; Workman et al. 2013 ; Charvet and Finlay 2014 ). Finlay and colleagues have documented this variation, explaining how it results from the duration of development. Their demonstration that constraints of mammalian neural ontogeny underlie the regularity is a direct challenge to persistent claims that human evolution has been driven by selection for a big brain, particularly an expanded neocortex. To quote Finlay (2019 , 318):

The central fact about the nature of the neocortex that has consistently managed to escape attention is that the cortex is precisely the volume it should be for a primate of our overall brain volume … . [Emphasis in original]

Consequences for distinctive features of human cognition are large because the slower neural development that results in our larger brains is combined with earlier weaning ( Finlay and Uchiyama 2017 ; Hawkes and Finlay 2018 ). From the perspective here, both are consequences of ancestral grandmothering. Ancestral baby brains were wiring in the context of our novel life history. Unlike the independent mothering of the other great apes, where infants are not weaned until they can feed on their own, ancestral human mothers were bearing next offspring while the previous one was still completely dependent. Finlay (2019 , 317) tallies costs of the misdirected attention to our “exceptional” neocortex, which:

… has caused both neuroscientists and psychologists to prematurely assign functions distributed widely in the brain to the cortex, to fail to explore subcortical sources of brain evolution, and to neglect genuinely novel features of human infancy and childhood … . [Emphasis added]

Cognitive consequences of our grandmothering life history

Hrdy (1999) pointed out that allomothering allowed human mothers to shorten birth intervals so much that we became more like “litter-bearers” than our singleton-rearing evolutionary cousins. With overlapping dependents, a mother’s fitness depends on how she juggles investments in more than one offspring at a time. Unlike our ape cousins or other anthropoids where it is male infanticide that can be a danger to infants, human mothers sometimes abandon or kill their own offspring ( Hrdy 1999 , 2016b ). With mothers’ distributed attention, human babies are without full maternal engagement as a birthright. Yet infant survival depends entirely on others. Novel survival challenges confronting infants, Hrdy (2009) argued, could explain the notably precocious sociality of human infants, the beginning of our distinctive human appetite for shared intentionality ( Tomasello et al. 1993 , 2005 ). Ancestral infants’ own success at engaging support had life or death consequences ( Hrdy 2009 , 2016a ; Hawkes 2012, 2014 ; Tomasello and Gonzalez-Cabrera 2017 ).

The grandmother hypothesis links features of savanna foods to advantages for mutualistic foraging and economic interdependence in ancestral populations. That interdependence dominated the world of ancestral babies whose survival turned on social relationships. The dependence continued through the neural and somatosensory development of infancy, but it did not stop then. Wired to prioritize relationships with others, reputations and mutual understanding were crucial lifelong. From this perspective, our appetite for anticipating the preferences of others, seeking their approval, and mutual engagement are aspects of our grandmothering life history, which continue to construct the diversity of our cultural lives ( Hawkes 2020 ).

None of the observations that initially prompted skepticism about the hunting hypothesis or those that stimulated an alternative grandmother hypothesis with its many entailments summarized above were available to Fisher, Williams, and Hamilton as they laid the foundations of evolutionary life history theory. They all used human examples to illustrate more general regularities. As they sought to explore the effects of natural selection, they encompassed variety in the living world far beyond humans, or primates, or even vertebrates. Yet, they had identified the large fraction of productive postmenopausal women in human populations and had seen that to be a major clue to what happened in our own evolution. At the time they wrote, human phylogenetic proximity to the other great apes and the variation in life history and social behavior within our hominid clade were largely unknown; no vital rates were available for human populations depending on wild foods under mortality regimes different from those of agricultural and industrial populations; regularities in life history variation and neural development across the mammalian radiation were still to be discovered. Yet as they sought to understand and explain the process that Williams (1966a ) called Mendelian natural selection, they could not ignore the striking fact that all human populations include large proportions of healthy and productive women with zero reproductive value—if that is defined by current and future age-specific fertility.

The concept and evolutionary importance of reproductive value is a central element of Fisher’s foundational role in biology’s modern synthesis. Fisher (1930) established the connection between the consequences of Mendelian inheritance ( Fisher 1919 ) and natural selection to show the combination results in adaptive evolution. Fisher (1927) reviewed the role of vital rates (age specific fertility and age-specific mortality) in determining what happens to age-structured populations over time. Then Fisher (1930 , 27) defined reproductive value and its importance this way:

We may ask … about persons of any chosen age … [to] what extent will persons of this age, on the average, contribute to the ancestry of future generations? The question is one of some interest, since the direct action of Natural Selection must be proportional to this contribution. [Emphasis added]

Fisher had rehearsed how population age-structures become stable whenever age-specific fertility and mortality remain the same for a few generations and migration is negligible. Then individuals in any particular age class have a predictable chance of surviving that age class and each age class that follows. Combining those mortality rates with average fertility at each of those ages, the mortality rates of the resulting offspring at each age, and the average fertility at those ages gives the expected direct contribution of members of any age class to descendant gene pools. Fisher (1930 , 27) then went on to make the qualification of particular interest here:

There will also, no doubt, be indirect effects in cases in which an animal favours or impedes the survival or reproduction of its relatives; as a suckling mother assists the survival of her child, as in mankind a mother past bearing may greatly promote the reproduction of her children … . [Emphasis added]

Fisher had anticipated the importance of the indirect fitness effects that Hamilton (1964) would later elaborate. But then, in the very same paragraph, Fisher surmised that “[n]evertheless such indirect effects will in very many cases be unimportant compared to the effects of personal reproduction.” By ignoring those indirect effects, he could take advantage of the renewal equation, which attends only to age-specific fertility and mortality. On the following page, he used vital rates from “about 1911” to calculate the “Reproductive value of Australian women” (1930, 28). Ignoring contributions to the ancestry of future generations from women past their child bearing years, he showed women’s reproductive value falling to zero before the age of 50 years when their fertility ends.

Reproductive value and somatic versus current reproductive effort

Williams (1966b ) considering how selection would adjust aging rates by trading off somatic and reproductive effort, took up Fisher’s concept of reproductive value, but, like Fisher himself, Williams ignored “indirect effects,” attending only to age-specific fertility and mortality. This quote from Fisher (1930 , 43–4) was Williams’s opening epigram:

It would be instructive to know … what circumstances in the life-history and environment would render profitable the diversion of a greater or lesser share of the available resources towards reproduction.

To address that question, Williams divided “the mean amount of future reproductive success for individuals of [a given] age and sex in the population” into the part “immediately at stake” in any current reproductive effort and the rest, which he called residual reproductive value. Since,

… expenditures on reproductive processes must be in functional harmony with each other and worth the costs in relation to the long-range reproductive interest; and the use of resources for somatic processes is favored to the extent that somatic survival, and perhaps growth, are important for future reproduction . ( Williams 1966b , 687) [Emphasis added]

Tradeoffs between the present and the future are at the heart of evolutionary explanations for the ubiquity of senescence. Williams (1957) had earlier explained why both senescence itself and variation in the pace of senescent decline are inevitable results of a history of natural selection for a wide array of taxa that include the vertebrates. He had built on Medawar’s (1952) crucial observation that even in an imagined non-senescing taxon, the force of selection would weaken across adulthood because accidents alone would decrease cohort size over time. With fewer members, contributions to future gene pools would fall and so the force of selection would decline with adult age. The rate of decline would depend on how fast the cohort shrinks: the adult mortality rate. Williams noted that rate of decline should also depend on what survivors to older ages could do for their fitness. Indeterminate growers like fish that continue to get larger throughout adulthood, produce more eggs the bigger they get. That raises the fitness benefits of reaching older ages favoring slower senescence and longer adulthoods compared to determinate growers like mammals and birds that do not keep growing in adulthood.

Reproductive value, grandmothering and increased longevity

Williams’s (1957) verbal arguments about the effects of selection on senescence were mathematically evaluated by Hamilton (1966) who began with a thought experiment about humans in which four hypothetical genes each give immunity against some lethal disease for one particular year:

Suppose the first gives immunity for the first year, the second for the fifteenth, the third for the thirtieth, and the fourth for the forty-fifth …. If for further simplicity parental care is ignored and it is assumed that the menopause always comes before age 45, it is at once obvious that the fourth gene is null, whereas all the others do confer some advantage. ( Hamilton 1966 , 12–13) [Emphasis added]

Hamilton set parental care aside for the simpler treatment allowed by using only age-specific fertility and mortality. He would return to its complications, considering humans specifically but without exploiting his own previously published observations (1964) that parental care itself is just a special case of something much more general. I will come back to that below.

Hamilton’s thought experiment about selection on age-specific immunity was his set-up for using demographic modeling to investigate how the “age at which a gene acts affects its influence on fitness” (1966, 14). His modeling demonstrated that “ for organisms that reproduce repeatedly, senescence is to be expected as an inevitable consequence of the working of natural selection ” (1966, 26) [emphasis in original]. He confirmed Williams’s inference that selection made senescence inevitable, even among indeterminant growers. Then, turning to evaluate predictions of his theory with empirical examples, Hamilton again began with humans because,

Man is the species for which much the best data is available. … Unfortunately, there are no very good data for contemporary peoples in a pre-agricultural phase, nor even for those with the most primitive forms of agriculture. (1966, 28)

So, he chose rural Chinese farmers in Taiwan around the turn of the 20th century, constructed age-specific survival and age-specific fertility curves, estimated the Malthusian parameter, and calculated what he called reproductive value curves, ignoring indirect contributions to future gene pools. His reproductive value curve for Taiwanese women about 1906 ( Hamilton 1966 , 32 Figure 3) is very like Fisher’s (1930 , 28 Figure 2) for Australian women around 1911. In both, female reproductive value peaks at about the age of 20 years and then falls to zero before the age of 50 years.

Hamilton’s modeling supplied mathematical support for Williams’s (1957 , 407) inference that “There should be little or no postreproductive period in the normal lifecycle of any species.” About that inference, Williams himself said:

At first sight it appears that this prediction is not realized. Long post-reproductive periods are known in many domesticated animals and in man himself. In man it may even be longer than the reproductive period. However, these observations lose much of their seeming importance when it is realized that they are largely artifacts of civilization. In very primitive conditions, such as prevailed throughout almost all of man’s evolution, post-reproductive individuals were extremely rare. (1957, 407)

Williams supported that inference with age-at-death estimates for a sample of fossil skeletal specimens, which—as now widely recognized—could neither be accurately aged nor correctly reflect past population age structures (e.g., review in Hawkes and Blurton Jones 2005 ).

Assuming menopause to be uniquely human, Williams also suggested a second hypothesis about its evolution as a consequence of other distinctly human features. That second hypothesis was cited by Hamilton as he considered the notable discrepancy between the survival curve for Taiwanese women falling to zero only near 90 years, while their fertility ended before the age of 50 years ( Hamilton 1966 , 29 Figure 1).

It is evident that the rise in mortality in the later reproductive ages of man is by no means asymptotic to the age at which reproduction ends; the indefinite rise comes too gradually and too late. This is particularly evident from the curves given for the Taiwanese women, where the rather definite age of the menopause seems to be conspicuously ignored by the as yet gently rising curve of force of mortality. It is, moreover, a matter of common knowledge that the post-menopausal woman normally remains a useful and healthy member of the community for some time. A woman does sometimes live to twice the age of her menopause …. [The] comparatively healthy life of the post-reproductive women is so long … that it inevitably suggests a special value of the old woman as mother or grandmother during a long ancestral period …. ( Hamilton 1966 , 37)

Hamilton continued, “As remarked by Williams, an obvious excuse for this discrepancy is to be found in the factor of parental care.” He was citing Williams’s (1957) second surmise about the evolution of menopause which did not mention a long ancestral value of grandmothers. Williams said,

At some time during human evolution it may have become advantageous for a woman of forty-five or fifty to stop dividing her declining faculties between the care of extant offspring and the production of new ones. A termination of increasingly hazardous pregnancies would enable her to devote her whole remaining energy to the care of her living children, and would remove childbirth mortality as a possible cause for failure to raise these children. Menopause, although apparently a cessation of reproduction, may have arisen as a reproductive adaptation to a life-cycle already characterized by senescence, unusual hazards in pregnancy and childbirth, and a long period of juvenile dependence. ( Williams 1957 , 407–8)

Colleagues and I have characterized this Williams hypothesis as “stopping early,” since it assumes an ancestral condition when female fertility continued to older ages. In contrast, Hamilton’s language suggests that selection favored slower senescence and greater longevity when post-menopausal females contributed to the production of descendants (e.g., Hawkes et al. 1997 , 1998 ; Hawkes and Smith 2010 ; Hawkes and Coxworth 2013 ). The point to underline here is the explicit recognition of grandmother effects both by Fisher and Hamilton (and by Medawar 1952 , fn 1). Fisher himself had recognized that indirect effects could make substantial contributions to reproductive value. Only by ignoring them (as Fisher himself had done) could Hamilton (1966) and Williams (1966b ) focus just on age-specific fertility and mortality.

Hamilton’s (1964) own explanation of the pervasive importance of indirect effects began with this observation:

With very few exceptions, the only parts of the theory of natural selection which have been supported by mathematical models admit no possibility of the evolution of any characters which are on average to the disadvantage of the individuals possessing them. … Sacrifices involved in parental care are a possibility implicit in any model in which the definition of fitness is based, as it should be, on the number of adult offspring. … The selective advantage may be seen to lie through benefits conferred indifferently on a set of relatives each of which has a half chance of carrying the gene in question. (1964, 1)

From that genic perspective, he went on to say

… there is nothing special about the parent-offspring relationship except its close degree and a certain fundamental asymmetry. The full-sib relationship is just as close. … Opportunities for benefitting relatives, remote or not, in the same or an adjacent generation … must be much more common … . (1964, 2)

He then laid out a mathematical argument about selection for both “giving” and “taking” traits that incorporated those relationships, concluding that:

we have discovered a quantity, inclusive fitness, which under the conditions of the model tends to maximize in much the same way that fitness tends to maximize in the simpler classical model … we may consider whether a given character expressed in an individual … is or is not adaptive in the sense of being in the interest of his inclusive fitness. (1964, 8)

Inclusive reproductive value

Hamilton (1964) had demonstrated that classical models miss what his theory building said selection will maximize. Fisher (1930) had recognized that such indirect effects could be important specifically in humans where “a mother past bearing may greatly promote the reproduction of her children.” When Hamilton used Fisher’s (1930) concept of reproductive value two years after publication of his inclusive fitness papers and excluded indirect effects to model the age-specific variation in selection on senescence, he noted that:

it should now be evident that the ratio of the reproductive values is just as important as the coefficient of relationship in determining ideally adaptive social behaviour: the coefficient gives the chance that the offspring carries a replica of a behaviour-causing gene of the parent (Hamilton, l964 … ), while the ratio gives the relative conditional expectation of its reproduction. The inclusive fitness of an individual is maximized by its continually acting in ways that cause increases in its inclusive reproductive value . (1966, 22–3) [Emphasis added].

Recognizing the problem with classic reproductive value, Hamilton might have pursued solutions further. But he subsequently wrote that by the time his 1966 paper was published, “… the theme of senescence no longer excited me much … because my findings on it were not new” (1996, 87). He was already working on what would become his 1967 “Extraordinary sex ratios” paper.

Hamilton’s (1967) field defining contributions to sex ratio evolution started with analysis of Fisher’s explanation for the common pattern of equal offspring sex ratios, now widely known as “the Fisher Condition.” Hamilton then highlighted implicit assumptions in Fisher’s treatment that would not always hold. I will return briefly to Hamilton’s next steps, but to provide a framework for connecting the topic to human life history evolution I begin discussion of the Fisher condition and sex ratio evolution with Charnov’s (1982) treatment. Charnov (1982 , 8) defined the problem of sex allocation this way, “what is the equilibrium sex ratio (proportion of males among offspring) maintained by natural selection?” plus four additional questions about allocation to male or female function in hermaphrodites and sex changers.

… all of the five questions are really one question phrased in different forms. Consider a typical diploid organism, RA Fisher (1930) noted the seemingly trivial fact that with respect to autosomal genes, each zygote gets half its genome from its father, half from its mother. To put it simply: everyone has exactly one father and one mother. However, far from being trivial, this fact holds the key to understanding sex allocation in diploids. … [It] has two implications. First, an individual’s reproductive success through male function (sperm) is to be measured relative to the male function of other individuals (vice versa for female function). Second, since half the zygote genes come via each pathway, male and female function are in a real sense equivalent means to reproductive success. Consider dioecy and the sex ratio. If many daughters are being produced, then large reproductive gains accrue to the producers of the rare sons. (1982, 8–9)

Charnov went on to discuss the resultant frequency dependent selection:

Maynard Smith (1976) has termed the equilibrium value of a trait an “Evolutionary Stable Strategy (or an ESS).” Suppose we have a population made up of individuals who have some attribute Z; we introduce into this population a rare genotype with alternative attribute z ^ and see whether the z ^ individuals are selected for or against (i.e., does the rare mutant spread?). If for some character of interest … there exists a Z such that all deviants are selected against, Z is termed an ESS. The classic example is selection on the primary sex ratio ( Fisher 1930 ) where the ESS is one-half males at conception in the simplest case.

He then ( Charnov 1982 , 13 and following) used “the first formal treatment of sex ratio evolution for diploids, from an early paper by Shaw and Mohler (1953) … [to write] the Shaw-Mohler equation for sex ratio (… first derived by MacArthur, 1965 ),” which gives the sex allocation rule:

Selection favors a mutant gene which alters life history parameters if the percent gain in fitness through one sex function exceeds the percent loss through the other sex function …. It is very often the case that the ESS allocation of resources to male versus female function is that which maximizes the product of the fitness gain through male function … times the fitness gain through female function … Or, more simply selection maximizes m * f. ( Charnov 1982 , 17) [Emphasis in original]

Robert MacArthur (1965 , 390) had treated the same question as follows:

Consider any autosomal gene influencing family size or sex ratio. Half of the genes in the population at this locus came from female parents and half from male parents. Hence, from the grandparent’s viewpoint, the set of all their sons will contribute equally to the set of all their daughters, and precisely one half of the genes at this locus will be expected to have come from the grandparent generation by way of sons and the remaining half by way of daughters.

MacArthur concluded,

… that natural selection will favor that family composition (M[sons], F[daughters]) which maximizes M x F. In this argument M and F … are calculated by counting males and females at the end of the period of parental care, if any, or at the onset of reproduction. … If the genes affect the age at which the mother gives birth (so that generations are no longer synchronized), then the M’s and F’s … must be replaced by the reproductive value of males and females as defined by Fisher . In this case maximizing M x F will involve the simultaneous selection of sex ratio, clutch size, and age at reproduction. This model can be extended to any other factor influencing the reproductive values of the offspring. [Emphasis added]

Before addressing implications of all of this for grandmothering and human evolution, I return to Hamilton (1967) . There Hamilton relaxed Fisher’s (1930) assumption of random mating, a step perhaps prompted at least in part by his 1964 paper’s recognition of substantial interaction between neighborhood composition and inclusive fitness selection. In “Extraordinary sex ratios,” he noted that both theory and empirical observations show large effects on offspring sex ratios from mate competition among relatives. For example, parasitoid wasp mothers put their eggs into hosts where the offspring mature and mate with each other. Sons can participate in conceptions with many females, so brothers compete with each other for the same conceptions, and the number of conceptions possible depends entirely on the number of sisters. Then, mothers that bias their offspring sex ratios toward daughters leave more grandchildren.

Instead of further work on sex ratios, Hamilton turned to sexual reproduction itself and why it is so common in spite of its evident substantial costs (e.g., Williams 1975 ; Maynard Smith 1978 ). His own report about that shift is more than worth attention—especially in the context of this symposium,

… my own reasoning on sex ratios … had shown how under conditions of extreme inbreeding … reproduction could evolve to be much more demographically efficient. Such efficiency came through a drastic reduction of male production, raising very acutely the problem of why males were ever there in the first place. Both my first strongly upward arching graph of my simulation in my ‘Extraordinary sex ratios’ … and all of that paper’s small inbreeders with their male-deficient sex ratios, seem now to be joining in chorus to force me to attend to the issue … I knew from my reading that parthenogenesis … is present throughout both animal and plant kingdoms. If suitable mutations to parthenogenesis can happen, as these cases prove, and if parthenogenesis is so efficient, why weren’t waves of such self-sufficient females … replacing sexual organisms on all sides? How in the long run has this crazy whim of maleness proved itself the opposite of what it should have been – a fleeting disaster and a long-abandoned experiment? ( Hamilton 1996 , 354)

The Fisher condition, offspring sex ratios, and mating sex ratios

In the case of our own evolution, well into the mammalian radiation, males may be here to stay. As noted above in the quote from Charnov, the Fisher condition explains why, in most diploids, there are so many males. Even though the number of babies depends on the number of females that can bear them; and even though one male can usually inseminate many females almost concurrently, the fact that half a baby’s autosomal genes come from each parent has enormous consequences. If males are rare, those rare males father all the babies. Since their average reproductive success must be higher than the female average, biasing offspring sex ratio toward males gives more grandchildren. If fertile males become more abundant than fertile females, the average reproductive success for the more plentiful males falls below the female average and mothers get fewer grandchildren through sons. The Fisher condition usually pushes offspring sex ratios toward the ESS of equal investment in sons and daughters.

The same Fisher condition also has consequences for mating strategies (e.g., Parker 1978 ) with attention growing recently under the label ASRs. The same issue in humans can be framed as “mating markets” or “partner scarcity” (e.g., Schacht et al. 2017 ). As reviewed above, the grandmother hypothesis links notably male-biased sex ratios in the fertile ages to the evolution of human longevity. In Coxworth et al. (2015) , both modeling and empirical data on hunter-gatherer and chimpanzee age structures are consistent about that distinctive male bias in humans. If the ancestral great ape-like condition is assumed similar to chimpanzees, the average proportion female in the fertile ages is 63% for the life tables cited; from four hunter-gatherer life tables, the average female proportion is 38%.

The female bias in chimpanzees is a common pattern in mammals as male mating competition usually includes risky and aggressive behaviors that raise male mortality. Fisher and others following him explained that mortality risk after individuals become independent would not affect equilibrium offspring sex ratios because the fraction that dies raises the average reproductive success for survivors. For example, if adult death rates in males are higher than adult female death rates, probable paternities for a son are conditional on his survival. The female biased sex ratio in adult chimpanzees results from such higher male mortality after weaning, so the higher number of grandchildren a mother might get through a son if he survives is canceled out by the chance he won’t. Along these lines, the Fisher condition usually predicts equal investment in sons and daughters in most mammals, even though ASRs are commonly female-biased.

On the contrary, while mortality is higher at most ages in human males too (e.g., Kruger and Nesse 2006 ), that higher mortality is overwhelmed by the countervailing source of sex-bias among fertile adults: all those old men. According to the grandmother hypothesis, increased longevity was favored in ancestral populations as the economic productivity of females whose own fertility was ending subsidized the offspring production of those still fertile. Greater longevity through grandmothering resulted in shorter birth intervals so more paternities for fertile males to compete over at the same time it expanded the ranks of competing males. In our lineage adult females depart the fertile ages with approaching menopause. That departure is not mortality, could its effects on adaptive offspring sex ratios cancel in the same way?

This is a puzzle posed by ubiquitous male-biased sex ratios in the fertile ages in our lineage. According to the grandmother hypothesis favored here that bias has persisted for tens of thousands of generations. In spite of likely higher male mortality at most ages, fertile males outnumber fertile females. With our grandmothering life history, the average reproductive success of sons has always been predictably lower than the average for daughters. In Hamilton’s (1966) senescence paper, his attention was elsewhere, but he did surmise that

It is fair to say that as a whole the data … cannot be reconciled with Fisher’s theory of the sex-ratio … A Taiwanese couple could reasonably expect a greater total number of grandchildren if they concentrated on supplying the existing deficiency of females; but they show no inclination to do so. ( Hamilton 1966 , 33)

Hamilton suggested, “It seems possible that we have here a case where a human cultural factor, the emphasis on maintaining a male line of descent, with its resultant preferential treatment for male children, has balanced the sex-ratio selection at some distance from its natural equilibrium.” That example and other human datasets contributed to Williams’ skepticism about adaptive sex ratio adjustment in diploids with chromosomal sex determination. After reviewing both models and data, Williams (1979 , 587) said:

I find it rather mysterious that adaptive control of progeny sex ratio seems not to have evolved. In particular the conformity of human progeny sex ratios to binomial distributions seems to contradict evolutionary theory. Either the physiological advantage of adjusting offspring sex to maternal capabilities, or the demographic advantage of decreasing competition for mates, ought to have produced noteworthy effects. Instead, deviations from random sex determination are trivial at best.

Williams’ expectation about “adjusting offspring sex ratio to maternal capabilities” was reference to the plausibility of Trivers and Willard’s (1973) hypothesis that (given the Fisher condition) selection should favor adjustment of progeny sex ratio depending on maternal condition. They proposed that if maternal condition predicts offspring condition; and if reproductive success has higher variance in males than in females; and if sons gain more from better condition while daughters lose less from poor condition; then selection should favor maternal tendencies to adjust offspring sex ratio with their own condition. Greater variance in male reproductive success usually follows from anisogamy ( Parker 2014 ; Parker and Pizzari 2015 ), but both theoretical and empirical work has since shown complications for Trivers–Willard expectations (e.g., reviews in Frank 1990 ; West 2009 ; Navara 2018 ). Veller et al. (2016) have argued that Trivers and Willard’s (1973) paper contains two distinct hypotheses, one about offspring sex ratios and the other about sex-biased investment, only the first of which holds under very general conditions.

Evidence for sex-biased investment is sometimes remarkably strong in human populations. Hamilton was right to surmise a cultural preference for sons among those Chinese farmers in Taiwan. Extreme sex-biased treatment of offspring associated with unilineal inheritance of property and privilege in class stratified societies including historical China has been well documented. M Dickeman contributed to identifying some of the extremes and associated their lineage serving outcomes with the Trivers–Willard hypothesis ( Dickeman 1975 , 1979 ; Hrdy 1999 ). The dramatic sex-biased investment that Dickeman persuasively associated with maintaining lineage position occurs in very steeply stratified states. Those emerged in human populations only after the origins of agriculture, within the climate amelioration of the Holocene ( Richerson et al. 2001 ). However, our grandmothering life history is much older, and the importance of male strategies, and their effects on options for females is a deep primate legacy (e.g., Hrdy 1981 ; Smuts 1992 , 1995 ).

Sexual conflict, longevity, and the product theorem again?

Kim’s ( Kim et al. 2012 , 2014 , 2019 ) and Chan’s ( Chan et al. 2016 , 2017 ) modeling of the grandmother hypothesis included both sexes. Model males and females both face longevity tradeoffs, but the costs and benefits of increased (or decreased) longevity differ for the sexes. That makes sexual conflict inevitable because of the Fisher condition, both mothers and fathers contribute to offspring longevity. So model populations must evolve to a compromise. MacArthur (1965 , 390 quoted above) had derived and described what Charnov later called “the product theorem” for overlapping generations and concluded that “This model can be extended to any other factor influencing the reproductive values of the offspring.” Keeping in mind the problems with standard definitions of reproductive value raised above, that would make the product theorem apply to longevity whenever tradeoffs between somatic and current reproductive effort are adjusted by numerous autosomal alleles. Longevity in the population should evolve to maximize the product of expected future gene copies through males and females.

Easy to say, but Alan Grafen’s formal Darwinism project is still dealing with reproductive value as classically defined and treats inclusive fitness separately ( Grafen 1999 , 2006a , 2006b , 2014 , 2020 ; Crewe et al. 2018 ; Levin and Grafen 2019 ). That project continues to demonstrate that proving how selection drives either reproductive value (ignoring “indirect effects”) or inclusive fitness alone poses difficult mathematical problems. Whether or not particular features of the human case can be helpful in combining them, the review here aims to show the need for it has long been recognized for our own lineage.

Chan’s modeling now seems a start at finding out whether grandmothering complications interfere with treating longevity like any other trait under sexual conflict. Chan et al. (2016) explored the ground laid by the agent-based modeling in Kim et al. (2014) with partial differential equations (PDEs) to investigate parameter effects. Chan allowed age at last birth as well as longevity to evolve (as subsequently did Kim et al. 2019 ). As in Kim et al. (2012 , 2014 ), the model resulted in two equilibria—a great ape-like and a human-like one. The PDE results showed that:

… male competition, arising from a skew in the mating sex ratio toward males, plays a significant role in determining whether the transition from great ape-like longevities to higher longevities is possible and the equilibrium value of the average adult lifespan. ( Chan et al. 2016 , 145)

Chan et al. (2017) then separately calculated the male and female fitnesses across trait-space to visualize the sexual conflict over longevity. This “allows for a straightforward comparison between fitness landscapes of both sexes and the population compromise that evolves with and without grandmothering” ( Chan et al. 2017 , 2134). Plotting variation in “the expected number of births by a female” as a function of longevity may seem to reduce things to the classical elements of the renewal equation (age-specific fertility and mortality) thus falling back on excluding indirect effects. It does not because the whole life history evolves. When “number of births” as a function of longevity is modeled with grandmothering, the number of births expected incorporates the subsidies from the post-fertile years that shorten the birth intervals. For males, as longevity increases with grandmothering, the number of competitors expands (more old males) but so does the number of paternity opportunities (shorter birth intervals). Of course, “A natural question is, to which longevity value … does the population converge for given parameter values and trade-off functions of the model? … the answer is simply the longevity value … that maximises the product F(x)M(x)” ( Chan et al. 2017 , 2137).

Could this be simply a version of the product theorem? The history of ideas reviewed here makes that an arresting possibility. But the modeling assumed equal offspring sex ratios, so the puzzle of how offspring sex ratios can remain so close to equal remains. With male-biased mating sex ratios, producing more daughters should mean more descendants. Yet biases in human offspring sex ratios are as noted by Williams (1979) trivial at best. Further work will be needed. The lesson so far is that the unusual case of a grandmothering species may provide a more general lesson about sex ratios, sexual conflict, and the evolution of life histories.

When Fisher (1930) and Hamilton (1966) recognized that human postmenopausal longevity evolved from a history of natural selection, they established venerable foundations for the grandmother hypothesis. Fisher noted that the “indirect” reproductive value of “women past bearing” implied their role in the evolution of our longevity more than three decades before Hamilton (1964) explained the pervasive importance of inclusive fitness. Then, when Hamilton (1966) calculated the effects of natural selection on senescence, he found that classical models that use only direct reproductive value (fertility and mortality) cannot account for so many “useful and healthy” postmenopausal women. He concluded that selection actually maximizes “inclusive reproductive value.”

Combined with Fisher’s (1930) recognition that Mendelian inheritance implies equal contribution from both sexes to (autosomal) genomes, those insights link evolving postmenopausal longevity in our lineage to likely shifts in male mating strategies. As the fraction of post-fertile females expanded, the fraction of old males expanded too, shifting the sex ratios in the fertile ages of ancestral populations to a regular, persistent male bias ( Coxworth et al. 2015 ). Empirical observations of diverse taxa and mathematical modeling both show that when mating sex ratios are male-biased, mate guarding dominates paternity competitions (e.g., review in Schacht et al. 2017 ). For our lineage, that connects the evolution of a distinctively human pair bonding habit to ancestral grandmothering ( Coxworth et al. 2015 ). Instead of the paternal provisioning proposed in the hunting hypothesis to explain the evolution of human nuclear families, the grandmother hypothesis points to sexual selection and sexual conflict in the evolution of human life history. On Chan’s fitness landscapes, it is sexual conflict over longevity with grandmothering that propels the evolution of model populations from a great ape-like life history to a human-like one.

As reprised above, the grandmother hypothesis now promises to help explain not only postmenopausal longevity, but also our pair bonding habits, big brains, and distinctively cooperative social appetites. As part of our grandmothering life history, ancestral mothers shortened their birth intervals, investing less in each offspring which posed survival challenges to completely dependent ancestral infants and toddlers. The perils of that dependency wired precocious sociality and persistent concerns about relationships early in their slower developing brains. Other people’s actions and responses are central features of our cognitive ecology now because harms and benefits from social relationships have taken priority in developing human somatosensory systems in our human radiation from infancy onward ( Hrdy 2009 ; Finlay and Uchiyama 2017 ; Hawkes and Finlay 2018 ; Hawkes 2020 ). Local understandings about reputations and preferences dominate our lives. Appetites to connect and align understandings with close kin and neighbors helped drive the diversity of languages and cultures in the past ( Hawkes 2020 ). Recent times have witnessed the power of mass communication, now expanded exponentially by social media, to harness our fundamental concerns about reputations to global influencers. Instantaneous reach to distant audiences magnifies the persuasive power of conflicting views of the past, present, and future. According to the hypothesis favored here, credit—or blame—extends all the way back to ancestral grandmothers foraging in the spreading African savannas as climate changed their daily options millions of years ago.

I am grateful to Nick Blurton Jones, Matthew Chan, Eric Charnov, Sarah Hrdy, Peter Kim, and Jim O’Connell for their reliable collaboration, productive ideas, and patient advice. And thanks to Virginia Hayssen and Teri Orr for the symposium invitation to pull all this together.

From the symposium “SICB Wide Symposium: Reproduction: The Female Perspective from an Integrative and Comparative Framework” presented at the annual meeting of the Society for Integrative and Comparative Biology January 3–7, 2020 at Austin, Texas.

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Published: 24 August 2010

'Grandmother hypothesis' takes a hit

Ewen Callaway

Nature ( 2010 ) Cite this article

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Pinning longevity to benefits women bestow on their grandchildren may not be plausible.

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Kachel, A. F., Premo, L. S. & Hublin, J.-J. Proc. R. Soc. B doi: 10.1098/rspb.2010.1247 (2010).

Hamilton, W. D. J. Theor. Biol. 12 , 12-45 (1966).

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DOI: 10.1098/rspb.2010.1247
Corpus ID: 14366425

Grandmothering and natural selection

A. F. Kachel , Lukas S. Premo , J. Hublin
Published in Proceedings of the Royal… 7 February 2011
Proceedings of the Royal Society B: Biological Sciences

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Reevaluating the grandmother hypothesis, increased longevity evolves from grandmothering, grandmothers and the evolution of human longevity: a review of findings and future directions, a mathematical model for the effects of grandmothering on human longevity., why does women's fertility end in mid-life grandmothering and age at last birth., mate choice and the origin of menopause, grandmothering drives the evolution of longevity in a probabilistic model., on age-specific selection and extensive lifespan beyond menopause, evolution of longevity, age at last birth and sexual conflict with grandmothering..

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Genetics of Human Longevity Within an Eco-Evolutionary Nature-Nurture Framework

59 references, when grandmothers matter, grandmothers and the evolution of human longevity, are all grandmothers equal a review and a preliminary test of the "grandmother hypothesis" in tokugawa japan., are humans cooperative breeders, evolution of the human menopause., a critique of the grandmother hypotheses: old and new, the evolution of premature reproductive senescence and menopause in human females, aging and fertility patterns in wild chimpanzees provide insights into the evolution of menopause, grandmothering, menopause, and the evolution of human life histories., menopause: adaptation or epiphenomenon, related papers.

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Grandmothers Are Evolutionarily and Biologically Unique

Humans are one of the only animals that experience menopause. multiple hypotheses try to explain why and highlight the extraordinary role (and benefits) of the human grandma..

Humans share a unique trait with just a few other species: We have grandmas who care for us. While most female mammals keep breeding until they keel over, only whales , elephants and giraffes forgo having their own children to help raise the next generation.

For a human with a female reproductive system, the ovaries typically contain at least a million eggs at the time of birth, reduced from about five times that number in the fetal state; and the egg count continues to dwindle after birth. When most child-bearing women hit their late 40s, egg numbers nose-dive, triggering menopause at around the age of 50.

Menopause is puzzling because, from an evolutionary perspective at least, the aim of the game is to reproduce. So why does nature prematurely switch off reproduction in half of the population?

Grandmother Hypothesis

One answer lies in what is known as the “ grandmother hypothesis ,” the idea that a post-reproductive female can provide an extra pair of hands to support her daughter, who can then have more children. Each grandchild, after all, will inherit approximately a quarter of their genes from that grandmother. So she can continue sowing her genetic material long after having children of her own.

The theory, steeped in gender politics, is not without controversies. Some scientists claim that menopause is simply an artifact of an extended lifespan while others suggest that infertility later in life results from men being more sexually attracted to younger women . Such male-centric theories have faced plenty of backlash.

The first solid evidence for the grandmother hypothesis came from anthropologist Kristen Hawkes in the late 1980s. She was studying the Hadza , a hunter-gatherer community in northern Tanzania, and found that the presence of a grandmother boosted a child’s chances of survival. Similar patterns have been uncovered in 17th- and 18th-century church records of French settlers in present-day Quebec. At the time, the Catholic clergy kept a fastidious eye on their parishioners, logging their births, marriage and deaths. Mining this huge dataset, researchers revealed that women whose mothers were still alive gave birth to more children, more of whom survived to adulthood. The closer these women lived to their mothers, the greater the chances of grandchild survival.

Surviving in such times was a struggle. On average, women had eight children, half of which would die young. In times when food was scarce and disease was rife, both women reproducing at the same time would have increased the chances of child mortality. This is particularly true for humans, who give birth to children with helplessly underdeveloped brains.

According to some biologists, genes that avoid generational overlap in childbirth were favored by natural selection. This may explain the sudden plunge in the number of eggs in a woman between the ages of 40 and 50. The biological phenomenon would cause infertility in the older generation as their offspring start bearing their own children.

So why do older women give up having children instead of the younger generation? In bees and naked mole rats, for example, it is the sterile, younger female workers that assist older, established breeding adults.

Disincentivized Breeding

The human dynamic can be explained in terms of “ female-biased dispersal ,” says Nichola Raihani, a professor of evolution and behaviour at University College London in the UK. Within hunter-gatherer societies, a woman would leave the group to live with her partner’s family when she reached reproductive age, says Raihani. This “sets up a potential conflict of interest with herself and the mother-in-law. If they both try to breed, alongside one another, then all of the offspring will suffer.”

The winner of the baby battle depends on the genetic stake each woman has in the potential offspring. For the older woman, she will be related to her biological grandchildren by a quarter, on average. Whereas the younger woman will share no DNA with any of the older woman’s children. “This is called relatedness asymmetry,” Raihani says, “and it weakens the mother-in-law’s hand because she is slightly disincentivized to breeding if it means she will harm her grandchildren, while the younger female is not disincentivized in the same way.

Over time natural selection may have favored women who become infertile just as their offspring start to have children of their own, forcing them to bow out of the battle for reproduction. Unlike other mammals, whose reproductive lifespans mirror their actual lifespan, reproduction in human females became disentangled from longevity.

Keepers of Knowledge

Grandmothers not only provide extra sets of hands but a wealth of accumulated wisdom. In rural Ghana, for example, grandmas disseminate advice on pregnancy, breastfeeding and treatment options, acting as surrogate healthcare providers in regions where medical assistance is hard to come by. Similarities have been noted in menopausal killer whales , whose ecological knowledge helps the group locate salmon when food is scarce.

The advantages of having a grandma are still apparent today; youngsters with involved grandparents have greater wellbeing and improved academic performance .

It’s easy to forget that for much of human existence, children were cared for by their grandparents, as well as neighbors, cousins and older siblings, Raihani says. In contrast, she points to the guilt that women sometimes feel in today’s modern world when they accept outside help, or how stressed many parents felt while solo-parenting during the pandemic. “Finding that situation challenging is not surprising when you consider that it is such an anomalous situation for our species. It is easy to forget that.”

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New Evidence That Grandmothers Were Crucial for Human Evolution

A computer simulation supports the idea that grandmothers helped our species evolve social skills and longer lives

Joseph Stromberg

Grandmother and child looking out window

For years, anthropologists and evolutionary biologists have struggled to explain the existence of menopause, a life stage that humans do not share with our primate relatives. Why would it be beneficial for females to stop being able to have children with decades still left to live?

According to a study published today in the journal Proceedings of the Royal Society B , the answer is grandmothers. “Grandmothering was the initial step toward making us who we are,” says senior author Kristen Hawkes , an anthropologist at the University of Utah. In 1997 Hawkes proposed the “ grandmother hypothesis ,” a theory that explains menopause by citing the under-appreciated evolutionary value of grandmothering. Hawkes says that grandmothering helped us to develop “a whole array of social capacities that are then the foundation for the evolution of other distinctly human traits, including pair bonding, bigger brains, learning new skills and our tendency for cooperation.”

The new study, which Hawkes conducted with mathematical biologist Peter Kim of the University of Sydney and Utah anthropologist James Coxworth , uses computer simulations to provide mathematical evidence for the grandmother hypothesis. To test the strength of the idea, the researchers simulated what would happen to the lifespan of a hypothetical primate species if they introduced menopause and grandmothers as part of the social structure.

In the real world, female chimpanzees typically live about 35 to 45 years in the wild and rarely survive past their child-bearing years. In the simulation, the researchers replicated this, but they gave 1 percent of the female population a genetic predisposition for human-like life spans and menopause. Over the course of some 60,000 years, the hypothetical primate species evolved the ability to live decades past their child-bearing years, surviving into their sixties and seventies, and eventually 43 percent of the adult female population were grandmothers.

How would grandmothers help us live longer? According to the hypothesis, grandmothers can help collect food and feed children before they are able to feed themselves, enabling mothers to have more children. Without grandmothers present, if a mother gives birth and already has a two-year-old child, the odds of that child surviving are much lower, because unlike other primates, humans aren’t able to feed and take care of themselves immediately after weaning. The mother must devote her time and attention to the new infant at the expense of the older child. But grandmothers can solve this problem by acting as supplementary caregivers.

In the hypothesis—and in the computer simulation—the few ancestral females who were initially able to live to postmenopausal ages increased the odds of their grandchildren surviving. As a result, these longer-lived females were disproportionately likely to pass on their genes that favored longevity, so over the course of thousands of generations, the species as a whole evolved longer lifespans.

But why would females evolve to only ovulate for 40 or so years into these longer lives? Hawkes and other advocates of the hypothesis note that, without menopause, older women would simply continue to mother children, instead of acting as grandmothers. All children would still be entirely dependent on their mothers for survival, so once older mothers died, many young offspring would likely die too. From an evolutionary perspective, it makes more sense for older females to increase the group’s overall offspring survival rate instead of spending more energy on producing their own.

Hawkes goes one step further, arguing that the social relations that go along with grandmothering could have contributed to the larger brains and other traits that distinguish humans. “If you are a chimpanzee, gorilla or orangutan baby, your mom is thinking about nothing but you,” she says. “But if you are a human baby, your mom has other kids she is worrying about, and that means now there is selection on you—which was not on any other apes—to much more actively engage her: ‘Mom! Pay attention to me!’”

As a result, she says, “Grandmothering gave us the kind of upbringing that made us more dependent on each other socially and prone to engage each other’s attention.” This trend, Hawkes says, drove the increase in brain size, along with longer lifespans and menopause.

The theory is by no means definitive, but the new mathematical evidence serves as another crucial piece of support for it. This could help anthropologists better understand human evolution—and should give you another reason to go thank your grandmother.

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Joseph Stromberg was previously a digital reporter for Smithsonian .

Distillations Podcast

Distillations podcast

Grandmothers matter.

Some surprisingly controversial theories of human longevity.

Painting of a toddler dressed in a white nightgown with a red cap holding a kitten while an old woman in a long skirt and blouse gestured kindly at her. The old woman is seated and there is another cat walking around what appears to be a old cottage kitchen.

Baby horses and giraffes walk soon after they’re born, and they can feed and take care of themselves pretty quickly, too. A one-year-old person, on the other hand, is basically helpless. But humans go on to live much longer than most other mammals, and scientists have long been trying to piece together why this is the case.

One theory called the grandmother hypothesis, claims that grandmas are the key to why humans live so long. Unlike most other species, human females live long past their childbearing years and so can help raise their grandchildren, allowing their daughters (or daughters-in-law) to have another baby before the first one can take care of itself.

As warm and fuzzy as this idea sounds, it turns out to be pretty controversial. In this episode of Distillations, we explore the grandmother hypothesis and find out what the debate is all about.

Producer: Mariel Carr Associate Producer: Rigoberto Hernandez Our theme music was composed by Zach Young

Grandmothers Matter: Some surprisingly controversial theories of human longevity

Introduction

Moses Carr >> Sound of rolling tongue

Wanda Carey >> laughs

Mariel : Welcome to Distillations , I’m Mariel Carr.

Rigo : And I’m Rigo Hernandez.

Mariel : And we’re your producers! We’re usually on the other side of the microphones.

Rigo: But this episode got personal for us.

Wanda >> Baby, baby, baby…

Mariel: That’s my mother-in-law Wanda and my one-year-old son Moses. Wanda moved to Philadelphia from North Carolina for ten months this past year so she could take care of Moses while my husband and I were at work.

Rigo: And my mom has been taking care of my niece and nephew in San Diego for 14 years. She lives with my sister and her kids.

Mariel: We’ve heard of a lot of arrangements like the ones our families have: grandma retires and takes care of the grandkids.

Rigo: And it turns out that across cultures and throughout the world scenes like these are taking place.

Mariel: And it’s not a recent phenomenon either. It goes back a really long time. In fact, grandmothers might be the key to human evolution!

Rigo: Meaning they’re the ones that gave us our long lifespans, and made us the unique creatures that we are.

Wanda >> I’m gonna get you! That’s right!

Mariel : A one-year-old human is basically helpless. We’re special like that. Moses can’t feed or dress himself and he’s only just starting to walk. Gravity has just become a thing for him.

Rigo : And my niece and nephew are older, but they’re still too young to fully take care of themselves.

Mariel : Baby giraffes and horses—on the other hand—they can walk soon after they’re born. And they learn to feed themselves pretty quickly too.

Rigo: Here’s another way humans are special: almost every other female mammal reproduces until she dies. So non-human grandmas are busy taking care of their own offspring—until they die.

Mariel : Human are different. If we’re lucky, we’ve got helpful, available grandmothers. But the key to them being helpful is that they don’t have their own babies.

I)Bedlam: Misunderstanding Menopause

Angela Saini >> It’s always been a big riddle for scientists to kind of get to the heart of why it is that women live so long, and often very many healthy years, into infertility.

Rigo: That’s British science journalist Angela Saini.

Saini >> No other primates do that.

Mariel: Men are able to reproduce into old age. But women—who live longer than men on average—often live decades past their childbearing years. So the riddle is this: if natural selection favors reproductive success— having as many babies as possible—then why would anyone outlive their ability to reproduce? What would be the point?

Rigo: Scientists have been trying to make sense of this evolutionary paradox for a long time. And they’ve come up with a variety of theories.

Mariel: Some are pretty heartwarming.

Rigo: Others might make you cringe. For a long time menopause wasn’t just misunderstood, it was vilified.

Saini >> Bedlam is probably one of the most famous mental institutions in the world.

Rigo : That’s Angela Saini again. She recently published a book called Inferior: How Science got Women Wrong and the New Research That’s Rewriting the Story.

Saini >> For us today, the word is synonymous with kind of craziness and chaos.

Rigo: Bethlem Royal Hospital or Bedlam as it is known, is in London and it’s Europe’s oldest psychiatric hospital. It now has a museum chronicling its history. Angela visited and was struck by two photographs from the Victorian Era.

Saini >> One shows a woman kind of holding a doll, almost like a baby. The other image I think is just of an older woman with a kind of far away look in her eyes, this kind of dreamy, far away look. In all likelihood, these two women were menopausal, and they kind of sum up how, in that time, how menopausal women were thought of. They were really though of kind of old crones at the end of their life. They were no longer able to fulfill this vital societal function of having children. If you live in a society or culture in which having babies is your primary function, and suddenly you can’t do that any more, that also has deep psychological impact.

Rigo: But then people started to wonder if there was an evolutionary reason for menopause.

Saini >> Many years ago, somebody came up with the idea that possibly it’s so that they can be around to help their children and their grandchildren.

Mariel : It certainly made sense to us. This is me and Wanda:

Carr >> Was it hard? Were you tired?

Wanda >> Absolutely! Yes. Yeah, it was hard and I was tired, but it was so much fun. I’m in my sixties! And I believe very strongly there’s a reason people are no longer fertile in their sixties and that’s because you get tired!

Rigo : And this is me and my sister, Rosalba.

Rosalba >> Having my mom around to take care of Lesly was an invaluable resource. If I didn’t have that I would have had to find someone else to take care of her. And there was no one better to take care of her than her grandma. Do you know what I mean? If I had left her with someone else I wouldn’t know how she’d be treated because they’d be a stranger. And for my mom it was her granddaughter.

Rigo: Our mom took care of my niece Lesly starting when she was one month old. Now she’s

14. To this day my niece calls my mom, “Mama Carmen.”

Saini >> We know statistically that grandmothers have a really profound effect on childhood survival.

Mariel : The idea is that it’s not enough to get your genes into the next generation. It’s evolutionary beneficiary to make sure those genes grow up. Biologist William Hamilton planted the seeds of this grandmother hypothesis in 1966. But it wasn’t until the 1980s that it really took off.

Saini >> The person who’s done the most work on kind of putting the meat on the bones of the idea was Kristin Hawkes at the University of Utah.

II)Kristen Hawkes and Grandmother Hypothesis

Kristen Hawkes >> I’m always happy to talk about grandmothers.

Mariel: Kristen Hawkes is an anthropologist who’s studied the Ache and Hadza tribes in Paraguay and Tanzania.

Hawkes >> The textbook story about human evolution is mostly still the hunting hypothesis. And I am putting scare quotes around that here which you can’t see.

Mariel: This theory says that at some point in our history men began hunting large and fast animals and women paired off with them so they’d be taken care of. And a whole bunch of things followed from this: nuclear families, tools, language …

Hawkes >> I thought, yeah, you know, of course, that must be it.

Mariel: But then she started looking at the Hadza in Tanzania and that’s not what she saw.

Hawkes >> Yeah, men were hunting, women were gathering, men were spending an enormous amount of time going especially for mammals and they were not especially bringing home the bacon to their wives and kids.

Mariel: So we have to back up for a second here. Hawkes and her team were studying modern hunter-gatherers to try to piece together what happened in our very distant past. Anthropologists look at hunter-gatherers like the Hadza because they live like early humans did, before agriculture. And their environment in East Africa is similar to the one in which our ancestors evolved. So there they were watching the Hadza, which happen to be a tribe studied by a lot of anthropologists, and they saw that the men hunted for big prize animals.

Hawkes >> When they got one, it was just a huge pile of meat.

Mariel: But they found that the hunters only had a five percent success rate on any given day.

Hawkes >> They went out there specializing in this activity that was going to give them a huge bonanza if they were successful and they were going to essentially always fail.

Well that’s a hell of a way to feed the kids.

Mariel : But the tribe wasn’t starving either. They made up the difference by foraging. So Kristen and her team began observing who foraged and how much.

Hawkes >> And just coming out of the data was this astonishing result that the old ladies, holy moly! Were so economically productive.

Mariel : They realized that when Hadza mothers had new babies they couldn’t keep helping their young children forage. But those kids weren’t old enough to do it on their either. So grandmas stepped in to help.

Hawkes >> So there was right before our eyes. We were seeing this trade-off. Moms move on, have that next baby because the previous one, even though it couldn’t yet feed itself, it was subsidized by grandmother. You don’t devote all your attention and effort to one at a time and then have the next one only when that one can manage on its own, we stack them up, because we can. And it’s fitness enhancing if you can do that.

Mariel: So Kristen’s team theorized that natural selection favored helpful grandmas, who could only be helpful if they didn’t have children of their own. From here we get menopause and long lives. It’s pretty nice, right? But as warm and fuzzy as it is, it turns out to be pretty controversial.

III)Opposing Theories/Controversy

Hawkes >> Yeah, the grandmother hypothesis is often framed as ignoring males and somehow privileging female life history over male life history.

Rigo : Harvard Anthropologist Frank Marlowe also studied the Hadza tribe many years after Kristen Hawkes. Even though he was immersed in the same community he came up with a

dramatically different conclusion in 1999. His theory gives men a leading role in our evolution. It’s called the Patriarch Hypothesis.

Saini >> And this says the reason women experience menopause is because no men of any age find older women attractive.

Hawkes >> And his argument was that because men remain fertile to older ages and so older men may have lots of offspring that that’s actually what drove the shift in our life history to make longevity advantageous.

Mariel: All of these life history theories, as they’re called, use mathematical models to back up their hunches. Kristen Hawkes’ team ran a computer simulation that showed how slowly increasing the number of long lived grandmothers in a population made everyone live longer.

Frank Marlowe’s simulation was different.

Hawkes >> They had built a model in which if males preferred younger females, and if females had to compete for every maternity, then their formal models showed that what begin to happen was fertility in females was shortened. I think that’s the way their story goes.

Rigo : The theory adds that because the genes that cause longevity are not on the Y chromosome they get passed on to both men and women. Women get dragged along. But their eggs run out before they do, so the result is menopause. There are scientists and anthropologists in both camps, and new research continues to build on both theories. Rama Singh is an evolutionary biologist at McMaster University in Ontario, Canada. He co-authored a study in 2013 called Mate Choice and the Origin of Menopause . It’s not such a surprise that there was some pushback.

Rama Singh >> We showed that this simple idea, mate choice, male choice for younger women, would have the biological consequence of depriving older women from reproduction and making them infertile. This is a straightforward, population genetics theory, which is common sense really.

Hawkes >> The headlines for their paper was “Putting the men back in menopause.”

Singh : Some women did not like our theory. Those feminist women in general did not react well. They thought that we are showing that in the past men have exercise and women have had no role. That’s not true. Our theory doesn’t say that women have had no role. But you cannot wipe out biology, or biological differences simply because modern society hinders with our concept of equality.

Rigo: Another new study, published in October 2017, claims that none of these theories have anything to do with human longevity. The paper by Jacob Moorad at the Edinburg School of Biology, analyzed birth records of mostly Mormon settlers in Utah. And he found no genetic evidence to prove the grandmother hypothesis or its competitors. The paper basically puts us back where we started. And no doubt this paper will be disputed and debated. Maybe finding out which theory is correct is beside the point.

IV)Gender Bias

Saini >> It’s been interesting for me and especially as a woman, to read these different ideas. I think what was even more fascinating for me, as a journalist, was to see the controversy.

Mariel : While she was researching her book, Inferior , Angela Saini found that mostly women have worked on the grandmother hypothesis, whereas—

Saini >> The patriarch hypothesis, as far as I can tell, pretty much only men have worked on. It’s always interesting when science cuts along gender lines. Why is it that one group of people follow this theory, and another group of people follow this theory? I’m sure that their sex has a role to play in what they choose to research because that’s the case in all of science. We pick topics that are of interest to us.

Rigo : Alyssa Crittenden is an anthropologist at The University of Nevada. She was Frank Marlowe’s graduate student in the early 2000s and she went with him to study the Hadza in Tanzania. And she’s been going back ever since. When we asked what she thought of his theory she said—

Crittenden >> We parted ways on the patriarch hypothesis—

Rigo : But when she described their work with the Hadza things got interesting.

Crittenden >> Frank spent the majority of his time foraging with men and I spent almost all of my time over the last 13 years with women and children and infants. So at the very basic level I have spent the majority of my time with the Hadza with women and children, and Frank spent the majority of his time with men and teenage boys.

Mariel : Alyssa told us all life history theorists pick one driver for human evolution and then stick with it. Kristen Hawkes picked grandmothers, Frank Marlowe picked old men. But it must be hard to have your theory star someone you aren’t even paying attention to.

Saini >> Women have often been overlooked by men historically. In the 20th century, when hunter-gatherer societies were studied, or even when primates were studied, people focused on the males because they just assumed they would have the more interesting behavior that they were leading evolution development somehow. And women bothered to look at women.

Mariel : But Alyssa says it’s complicated. Even if Frank Marlowe had wanted to study Hadza women, they wouldn’t have let him.

Crittenden >> So as a female scientist there are certain aspects of Hadza male life that I am not welcome to study and vice versa. So, for instance, I have seen several Hadza births and Frank was never invited to attend a birth.

Rigo: Both the research and the criticism of these theories can cut along gender lines. Donna Holmes is an exception. She’s an evolutionary biologist at the University of Idaho and she does not agree with the grandmother hypothesis. This has caused some tension.

Donna Holmes >> There was a period of time in the ’90s when, when I’d be at meetings with other evolutionary biologists, men that I knew that had argued about the grandmother hypothesis would talk about how many nasty emails they got from feminists, and they’d say, “You know, I’m just dropping this subject. It’s just too loaded. I don’t need to get flamed.” You don’t want to be a bad feminist. You don’t want to be anti- Hawkes. You don’t want to be anti-grandma…

Rigo : Donna doesn’t believe in the grandmother hypothesis because she says evidence is anecdotal and lacks in qualitative data. She also says that the field of anthropology in general has flaws.

Holmes >> It doesn’t use a comparative approach. It doesn’t use a physiological approach. It doesn’t use a quantitative genetic approach. It’s just not the same set of intellectual customs that are followed in anthropology.

Rigo : Donna says she understands that anthropologists might be overcorrecting for a lifetime of research that has ignored women.

Holmes >> Who doesn’t like the idea that grandmas are special and that they contribute? And they do! I mean we do. When we can, we do. But it doesn’t mean that we do that because it’s an outcome of natural selection.

Mariel : So are grandmothers the drivers of human evolution? It’s still unclear. And the answer will depend on who you ask—maybe because of their gender, but maybe because of what kind of scientist they are. But one thing no one is debating is how important grandmothers are.

Moses Carr >> rolling tongue

Wanda Carey >> Okay! Yes! Precious one. You precious one.

Carmen Rigo >> Hoy quiero vivir, un dia la vez, un dia la vez.

Mariel: Distillations is more than a podcast. We are also a multimedia magazine. You can find our videos, our blog and our print stories at Distillations.org. You can also follow Chemheritage on Twitter, Facebook, and Instagram. This episode of Distillations was produced by myself and Rigo Hernandez. And original music was composed by Zach Young.

Mariel: For Distillations , I am Mariel Carr.

Rigo: And I am Rigo Hernandez.

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Grandmother Hypothesis, The

Reference work entry
First Online: 01 January 2021
pp 3499–3503
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grandmother hypothesis natural selection

Mirkka Lahdenperä 3 ,
Antti O Tanskanen 4 , 6 &
Mirkka Danielsbacka 4 , 5

190 Accesses

Altriciality life span hypothesis ; Mother hypothesis ; Stopping-early hypothesis

The grandmother hypothesis states that the long post-reproductive life span in human females would have evolved because women were able to gain more fitness by investing in their adult offspring and grand-offspring rather than by reproducing until old age. Because of this fitness benefit, selection would have favored a longer post-reproductive life span during human evolution.

Introduction

In most animals, reproductive and somatic senescence occurs at the same time as a part of the gradual decline in overall physical condition with age. In few species, however, the reproductive functions show an abrupt deterioration well before other body functions, leading to a total loss of fertility during middle age and subsequent post-reproductive life span of several decades. So far, the most convincing evidence from menopause and long post-reproductive life span comes from a few whale species,...

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#HowToRaiseAHuman

Why grandmothers may hold the key to human evolution.

Grandmothers and mothers were keeping the kids fed, not man the hunter. Fabio Consoli for NPR hide caption

A hunter with bow and arrow, in a steamy sub-Saharan savanna, stalks a big, exotic animal. After killing and butchering it, he and his hunt-mates bring it back to their families and celebrate.

About 'How To Raise A Human'

Does raising kids have to be stressful? Is it really dangerous for babies to sleep with mom? Do chores have to be a fight? Over the next month, NPR travels around the world for ideas to make parenting easier. Sign up for NPR Health's newsletter to get the stories delivered to your inbox.

This enduring scenario is probably what many of us have stuck in our heads about how early humans lived. It's an image with drama and danger. And it happens to coincide with Western ideas about the division of labor and the nuclear family that were prevalent in the 1960s when this so-called "Man the Hunter" theory first emerged.

A newer body of research and theory, much of it created by women, has conjured a very different scenario. It probably looks a little more like a quirky indie film than a Hollywood blockbuster. The star of this new film? Grandma.

Kristen Hawkes is an anthropologist at the University of Utah. She tries to figure out our past by studying modern hunter-gatherers like the Hadza, who likely have lived in the area that is now northern Tanzania for thousands of years. Groups like this are about as close as we can get to seeing how our early human ancestors might have lived.

A Hadza hunter in Tanzania. Researchers have looked at the hunting success of the Hadza and found that they bagged an animal on 3.4 percent of their excursions. Nigel Pavitt/Getty Images/AWL Images hide caption

Over many extended field visits, Hawkes and her colleagues kept track of how much food a wide sample of Hadza community members were bringing home. She says that when they tracked the success rates of individual men, "they almost always failed to get a big animal." They found that the average hunter went out pretty much every day and was successful on exactly 3.4 percent of those excursions. That meant that, in this society at least, the hunting hypothesis seemed way off the mark. If people here were depending on wild meat to survive, they would starve.

So if dad wasn't bringing home the bacon, who was? After spending a lot of time with the women on their daily foraging trips, the researchers were surprised to discover that the women, both young and old, were providing the majority of calories to their families and group-mates.

Mostly, they were digging tubers, which are deeply buried and hard to extract. The success of a mother at gathering these tubers correlated with the growth of her child. But something else surprising happened once mom had a second baby: That original relationship went away and a new correlation emerged with the amount of food their grandmother was gathering.

A Hadza woman digs for tubers with a digging stick. Nigel Pavitt/Getty Images/AWL Images hide caption

She describes this finding as "mind-blowing." In this foraging society, it turns out, grandmothers were more important to child survival than fathers. Mom and grandma were keeping the kids fed. Not Man the Hunter.

This finding led Hawkes to completely re-evaluate what she thought she knew about human evolution. Grandmothers were crucial in this environment to childhood survival. So maybe it wasn't an accident that humans are the only great ape species in which women live so long past reproductive age. If having a helpful grandmother increased a kid's chances of survival, natural selection may well have started selecting for older and older women. (This endowment would have passed also to human men.)

Sarah Hrdy is a primatologist at U.C. Davis who also studies connections between child-rearing and human evolution. She has spent a lot of time thinking and writing about a related topic. She says, "An ape that produced such costly, costly slow-maturing offspring as we have could not have evolved unless mothers had a lot of help." First among these helpers, she thinks, would have been grandma – likely joined eventually by many other new helpers, who could have included fathers, aunts, uncles and siblings.

If young kids were being fed by people besides mom, she thinks that over evolutionary time, this could have led humans to develop the deep social orientation that characterizes our species – to care so much about the thoughts and intentions of other people. She says, "People often try to explain the fact that humans are so good at cooperating by saying, well, we needed to cooperate in order to succeed at big game hunting, or so that men in one group could bond with other men to go wipe out the neighboring group. What that doesn't do is explain why these traits emerge so early."

A Tanzanian Hadza grandmother sits in the shade with her grandchild during the 1995 dry season. James O'Connell hide caption

She's talking about babies and the advanced social traits that we can see even before they begin walking – like pointing, sharing and paying attention to social cues like smiling and frowning. From the standpoint of a human baby, this caregiving situation is very different than for any other species of great ape child. Baby chimpanzees, bonobos, orangutans and gorillas are all cared for exclusively by mom. And these primate moms are extremely protective of their babies — sometimes not even letting another ape touch the baby for months after birth.

For human babies though, other human adults are usually present right at, or shortly after, birth — first helping the mother and then later helping and feeding the baby. We are the only great ape species that does this. Human babies, Hrdy argues, have an incentive to care about what other people are doing and thinking and feeling in a way that other apes don't. Knowing who might help and who might hurt, and learning how to appeal to the former, might be the difference between eating well or going hungry – maybe even the difference between life and death in some cases.

Michael Tomasello is a developmental psychologist at Duke University and the Max Planck Institute. After a career of comparing cognitive differences between babies and apes, he has found that other apes don't show anywhere near the level of interest in the sharing and cooperative behaviors that emerge so early in humans: "Humans as individuals aren't that much cleverer than other apes. It's the fact that we can put our heads together with others and communicate and collaborate and learn from others and teach others. Human children are adapted for cooperation and shared intentionality in ways that apes aren't."

Tomasello originally assumed that the pro-social traits seen in human babies were preparing kids for skills they'd need as adults, in line with the Man the Hunter hypothesis. Now he thinks that Hrdy's proposal – that human babies are so socially oriented as a result of shared child care and feeding – is a more compelling theory. The traits appear so early in a human's life that it makes better sense that they were adapted to early childhood situations rather than adult hunting behaviors.

It's this ability to "put our heads together," as Tomasello puts it, that may have allowed humans to survive, thrive and spread across the globe. While the men were out hunting, grandmothers and babies were building the foundation of our species' success – sharing food, cooperating on more and more complex levels and developing new social relationships. In a nutshell, humanity's success may all be dependent on the unique way our ancestors raised their kids. Thanks, Grandma.

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National Academy of Sciences (US); Avise JC, Ayala FJ, editors. In the Light of Evolution: Volume IV: The Human Condition. Washington (DC): National Academies Press (US); 2010.

In the Light of Evolution: Volume IV: The Human Condition.

Hardcopy Version at National Academies Press

11 How Grandmother Effects Plus Individual Variation in Frailty Shape Fertility and Mortality: Guidance from Human-Chimpanzee Comparisons

KRISTEN HAWKES

In the first paper to present formal theory explaining that senescence is a consequence of natural selection, W. D. Hamilton concluded that human postmenopausal longevity results from the contributions of ancestral grandmothers to the reproduction of their relatives. A grandmother hypothesis, subsequently elaborated with additional lines of evidence, helps explain both exceptional longevity and additional features of life history that distinguish humans from the other great apes. However, some of the variation observed in aging rates seems inconsistent with the tradeoffs between current and future reproduction identified by theory. In humans and chimpanzees, our nearest living relatives, individuals who bear offspring at faster rates do not cease bearing sooner. They continue to be fertile longer instead. Furthermore, within both species, groups with lower overall mortality rates have faster rates of increase in death risk with advancing age. These apparent contradictions to the expected life history tradeoffs likely result from heterogeneity in frailty among individuals. Whereas robust and frail alike must allocate investments between current and future reproduction, the more robust can afford more of both. This heterogeneity, combined with evolutionary tradeoffs and the key role of ancestral grandmothers they identify, helps explain aspects of human aging that increasingly concern us all.

L ong postmenopausal survival is a characteristic of our species. The use of life expectancy to compare human populations can obscure this fact because high infant and juvenile mortality kept all national life expectancies below 50 until the 20th century (Oeppen and Vaupel, 2002). As historical demography shows, girls that survived childhood usually lived long past menopause in previous centuries (Keyfitz and Fleiger, 1968). Hunter-gatherer survival curves are especially instructive (Howell, 1979; Hill and Hurtado, 1996; Early and Headland, 1998; Blurton Jones et al., 2002; Hill et al., 2007). They document characteristic human longevity in the absence of agriculture, public health institutions, and scientific medicine, all of which emerged long after the initial evolution of our species (Hawkes and Blurton Jones, 2005; Gurven and Kaplan, 2007). Distinctive and at first puzzling human postmenopausal survival was addressed in classic papers that used evolutionary theory to explain why living things grow old.

G. C. Williams (1957) laid out demographic reasons why declines in adaptive performance with increasing adult age emerge from the forces of natural selection. Because life is risky, cohorts inevitably diminish across adulthood. Consequently, the forces of selection weaken with age as fewer remain to be affected by it at older ages. Williams explained how the same forces result in different rates of senescence among species that reproduce more than once depending on two aspects of life history. First, when background mortality risk is lower, more individuals survive to older ages and selection against senescence is stronger. Second, selection against senescence is also stronger when the potential fitness-related payoffs to survivors increase with age. He illustrated the latter effect with the slow senescence of indeterminate growers that continue to increase in size and rate of egg production throughout adulthood.

Concluding that evolutionary life history theory predicts no post-reproductive period in normal life spans, Williams then addressed the apparent contradiction posed by survival past menopause in our own species by observing that older women still investing in descendants are not literally postreproductive. Hamilton (1966) mathematically modeled the tradeoffs nominated by Williams and demonstrated that the forces of selection shape mortality schedules to converge asymptotically with the age when reproduction ends. This process leaves, as Williams had surmised, few if any postreproductives. Because “much the best” (Hamilton, 1966, p. 27) demographic data are available on humans, Hamilton used a human population to explore the fit of observation with theory. This required him to explicitly confront the apparent discrepancy in the case of humans (Hamilton, 1966, p. 37):

[T]he rather definite age of menopause seems conspicuously ignored by the as yet gently rising curve of the force of mortality. It is, moreover, a matter of common knowledge that the post menopausal woman normally remains a useful and healthy member of the community for some time… . [This] can be attributed to the beneficial effects of continued survival on the survival and reproduction of descendants…. In fact … the comparatively healthy life of the postreproductive woman … inevitably suggests a special value of the old woman as a mother or grandmother during a long ancestral period….

Such a grandmother hypothesis, subsequently elaborated with comparative and phylogenetic evidence not available when the classic papers appeared, can explain not only the evolution of human longevity but other similarities and differences in life history between humans and the other great apes. We live longer; we take longer to mature but have shorter birth intervals; and we share common ages of terminal female fertility with the other great apes (Hawkes et al., 1998; Robson et al., 2006). The hypothesis focuses on females because as noted by both Williams and Hamilton our mid-life menopause is a central clue to human life history evolution and because the hypothesis employs E. L. Charnov’s (1991, 1993) model of tradeoffs faced by females to explain mammalian life history variation. The forces of selection explored by Williams (1957, 1966), Hamilton (1966), Charnov (1993), and many other students of life history evolution (Stearns, 1992; Charlesworth, 1994) attend to fitness effects and not to proximate mechanisms, but T. B. L. Kirkwood’s disposable soma model (Kirkwood and Rose, 1991) based on the same evolutionary tradeoffs between current and future reproduction has directed attention to processes of cellular maintenance and repair that affect somatic aging rates (Kirkwood and Holliday, 1979; Finch, 2007). Such processes likely have similar effects in both sexes, because longer-lived mothers pass on their cellular maintenance mechanisms to both sons and daughters.

I briefly summarize this elaborated grandmother hypothesis, then turn to patterns that initially seem inconsistent with the tradeoffs between current and future reproduction identified in evolutionary explanations for senescence. I focus on two apparent inconsistencies between theoretical expectations and empirical observations. First, theory predicts that current reproductive output should subtract from effort invested in maintenance for survival and reproduction in the future, yet individuals with higher fertility rates tend to continue bearing offspring to older ages; and in humans, women with later last births then survive longer afterward (Perls et al., 1997; Jacobsen et al., 2003; Emery Thompson et al., 2007; Gagnon et al., 2009). Second, theory predicts that lower adult mortality should slow rates of senescence, yet when populations of the same species are compared, the groups with lower mortality have steeper increases in death risk with advancing age (Strehler and Mildvan, 1960; Gavrilov and Gavrilova, 2001). More survival to older ages makes senescence—measured as the pace of increase in age-specific mortality—appear to be faster. Heterogeneity of frailty within populations may explain these apparent contradictions (Hawkes et al., 2009).

J. W. Vaupel and colleagues (1979, 1998) proposed that heterogeneity in frailty might explain why the increase in mortality rates across adulthood begins to slow and even cease at advanced ages in humans and many other taxa. If individuals vary in their vulnerabilities to death, the more frail will usually die younger. Survivors to the oldest ages will therefore be a subset of the population enriched with individuals that had lower vulnerability all along. L. D. Mueller, M. R. Rose, C. L. Rauser, and colleagues (Mueller and Rose, 1996; Rauser et al., 2006; Rose et al., 2007) judged Vaupel’s hypothesis to be in conflict with Hamilton’s forces and found those forces themselves sufficient to explain the mortality plateaus. I argue here that rather than being mutually exclusive alternatives, heterogeneity of frailty and tradeoffs between current and future reproduction explain different things. Both are needed to account for salient aspects of fertility and mortality schedules in general, and those of humans and chimpanzees in particular. As Williams and Hamilton recognized, women usually outlive their fertility. This is not true of chimpanzees. Although childbearing ends at the same age in both species, only humans regularly survive for decades longer. Heterogeneity within populations can explain why this divergence in life history results in fertility schedules with different shapes.

A GRANDMOTHER HYPOTHESIS

Anthropologists continue to debate the phylogenetic relationships among fossil taxa representing our ancestors and cousins (Wood, 2010), but genetic evidence unequivocally corroborates Darwin’s hypothesis about our African ape ancestry (Glazko and Nei, 2003). The genera ancestral to our own are often characterized as bipedal apes (Wood and Collard, 1999), and chimpanzees are commonly used as a living model for the ancestors of our genus because they are genetically closest to us and similar in body and brain size to these extinct taxa (Robson and Wood, 2008). Correlations between life history traits and adult size across the living primates (Charnov, 1993) support the relevance of a chimpanzee model for the early members of our lineage.

Like other primates, chimpanzees feed themselves after weaning (Goodall, 1986). Systematic observations among modern hunter-gatherers show that human youngsters can be remarkably efficient foragers, acquiring large fractions of their own requirements at young ages (Blurton Jones et al., 1997; Bliege-Bird and Bird, 2002; Bird and Bliege-Bird, 2005); but unlike chimpanzees, humans still depend on provisioning by others after weaning. Help is especially crucial for certain kinds of foods (Hawkes et al., 1995). Reliance on resources that young juveniles cannot handle effectively requires mothers to provision weaned offspring, but mothers nursing new infants provide less for their weaned children who receive subsidies from grandmothers (Hawkes et al., 1997).

The productivity of Hadza hunter-gatherer grandmothers especially in gathering hard-to-acquire staples, and the importance of their subsidies to weaned children with infant siblings (Hawkes et al., 1997), suggests a scenario about the ancestral past. An ecological change that reduced the availability of foods juveniles could handle independently would have opened a novel fitness window to older females without nursing infants of their own (Hawkes et al., 1997). By helping to feed weanling grandchildren, elder females would have allowed their daughters to bear the next baby sooner without affecting the survival of previous offspring. More vigorous elders, through greater reproductive success of their daughters, would have spread their slower somatic aging to more descendants. Longer adult life spans then reduced the cost of waiting longer to mature, delaying age at maturity and increasing adult body size (Hawkes et al., 2003). Because later births would interfere with grandmothering, selection would not have favored delaying ages of fertility decline. Increased allocation to somatic maintenance would have left less for current reproduction through the childbearing years, but subsidies from elders would have more than compensated, raising the fertility of childbearers (Hawkes, 2003).

We hypothesized that such a shift might have given rise to genus Homo (O’Connell et al., 1999; Hawkes, 2003) when drying environments and increased seasonality altered foraging opportunities for ancestral populations between 2 and 3 million years ago as forests shrank and grasslands spread across Africa (deMenocal, 1995; Bromage and Schrenk, 1999). Changes in body size and form are consistent with such a shift, as is the colonization of new habitats about that time. The hypothesis also helps explain the location of early archaeological sites and the composition of the faunal assemblages associated with them (O’Connell et al., 2002).

A formal model of the verbal grandmother scenario outlined here remains to be developed, but others have formalized links between the evolution of human longevity and the economic productivity of elders. H. S. Kaplan and A. J. Robson (2009) have shown that aging rates can be connected to the contribution adults make to juvenile survival. R. D. Lee (2003) has demonstrated that when intergenerational transfers of assistance are incorporated into a formal theory of senescence, it is the transfers instead of fertility that determine equilibrium aging rates. His simulations show that when elders transfer resources to close kin, mortality schedules very like those observed in hunter-gatherers are maintained by selection against deleterious mutations (Lee, 2008).

AGE STRUCTURES

Our grandmother hypothesis relies on Charnov’s model of life history evolution (Charnov, 1991, 1993) to explain how correlated allometries in mammalian life history features apply to humans (Hawkes et al., 1998; Alvarez, 2000). Comparisons between other great apes and humans (Robson et al., 2006) have been essential in highlighting distinctive human life history features. As noted, chimpanzees are an especially important comparative model for phylogenetic, ecological, and morphological reasons. Fig. 11.1 shows the female side of the age structure for a human hunter-gatherer population and wild chimpanzees modeled from life tables.

FIGURE 11.1

Female age structures modeled from life tables. Each bar shows the percentage of the population in the 5-year age class indicated in the vertical axis. Lightest bars, juvenile years; medium-gray bars, childbearing years; darkest bars, post-fertile years. (more...)

The human example on the right in Fig. 11.1 , the Hadza (Hawkes and Blurton Jones, 2005), is similar to other hunter-gatherers. Life expectancy at birth is <40 years, but a substantial fraction of adults are past the child-bearing years. This is not true of chimpanzees, modeled on the left of Fig. 11.1 from the wild population synthesized from five wild study sites (Hill et al., 2001). Lower mortality in humans as compared to the other great apes has long been attributed to our propensity for cooperation and resource sharing (Sahlins, 1959), patterns that must surely affect death risks. The grandmother hypothesis highlights sharing by grandmothers in particular because, as noted by Hamilton, evidence that women remain healthy and productive past their fertility provides a clear link between human longevity and fitness payoffs to ancestral grandmothering. Sometimes elders survive with help from younger kin, but an evolutionary perspective predicts help to generally flow from older to younger relatives (Kaplan, 1994). Measures of strength and productivity among post-menopausal hunter-gatherers demonstrate their provisioning capacities (Blurton Jones and Marlowe, 2002; Walker and Hill, 2003). High fractions of maximum function through and beyond the childbearing years in humans contrast with the earlier geriatric declines of chimpanzees (Goodall, 1986; Finch and Stanford, 2004).

DEMOGRAPHIC AGING RATES BETWEEN AND WITHIN SPECIES

As expected from Hamilton’s model, age-specific mortality curves increase exponentially across adulthood (Mueller and Rose, 1996). This exponential increase was identified in human actuarial data by B. Gompertz in the early 19th century (Gompertz, 1825). A model bearing his name gives a fair fit to mortality data across a wide range of species (Finch, 1990):

Here m is the mortality hazard rate, G describes the rate of increase in adult mortality with increasing age ( t ), and A represents age-independent adult mortality. Building on previous work by G. A. Sacher (1977), C. E. Finch (1990) labeled A the initial mortality rate (IMR). Taking the natural log, the equation yields a line representing the logarithm of the hazard of death across adulthood with the log of the IMR as its intercept and G as its slope. In the Gompertz model, differences in longevity between populations of the same species or between species can be due to differences in the initial mortality rate ( A ), differences in G [or its transformed value, ln2/ G , the mortality rate doubling time (MRDT)], or both. The slope ( G ), or the MRDT, is the demographic aging rate (Sacher, 1977). Across spe cies, lower initial mortality rates are correlated with shallower slopes and longer doubling times (Sacher, 1977; Finch, 1990; Ricklefs, 1998; Pletcher and Neuhauser, 2000).

Some have suggested that an MRDT of 7–9 years characterizes humans [e.g., Finch (2007, p. 12)], but MRDTs vary at least twofold across human populations (Hawkes et al., 2009). That variation among populations is correlated with variation in the initial mortality rate. However, the correlation is in the direction opposite from that predicted by a current vs. future reproduction tradeoff. Instead of the cross-species pattern identified by Sacher (Sacher, 1977; Finch, 1990; Ricklefs, 1998; Pletcher and Neuhauser, 2000), human populations with lower mortality levels ( A ) have faster rates of demographic aging ( G ). The age-specific mortality rate doubles more quickly, MRDT is shorter, when the age-independent risk of death ( A ) is lower.

This relationship, named for B. L. Strehler and A. S. Mildvan (1960), who first identified it across human populations, is robust and well described (Gavrilov and Gavrilova, 2001). Fig. 11.2 shows this Strehler–Mildvan correlation across a convenience sample of human populations chosen to represent a wide range of socioecologies and initial mortality rates [from Hawkes et al. (2009), with two Pygmy populations (Migliano, 2005) added here]. The figure is constructed from Gompertz models that were fitted to life tables for each population. Following Finch (1990) the models consider age-specific mortality risk from ages 30 to 80 [see discussion in Hawkes et al. (2009)]. The log of A , the hazard of death at age 30 (representing the IMR) is on the horizontal axis, and G , the slope of the log of the Gompertz curve is on the vertical axis. This correlation between the two variables across populations of the same species has also been found in widely diverse taxa where suitable data are available (Pletcher and Neuhauser, 2000; Gavrilov and Gavrilova, 2001). The limited data for chimpanzees are also plotted in Fig. 11.2 . The synthetic chimpanzee population in the wild (Hill et al., 2001) used in Fig. 11.1 and the synthetic population from captivity (Dyke et al., 1995) represent variation in IMRs and demographic aging rates in that species. The same Strehler–Mildvan relationship found across human populations holds for chimpanzees.

FIGURE 11.2

The slope of the log of the hazard of death from ages 30–80 by the log of the intercept at age 30 (IMR) taken from the values of A and G in Gompertz models calculated from life tables for a convenience sample of 11 human (open circles) and two (more...)

A HETEROGENEITY HYPOTHESIS

As noted, Strehler–Mildvan correlations across populations of the same species are opposite to those generally found in cross-species comparisons. Williams’ (1957) verbal arguments, Hamilton’s (1966) formal treatment, and Kirkwood’s disposable soma model (Kirkwood and Rose, 1991) link lower mortality to stronger selection against senescence, and so slower rates of aging. Fig. 11.2 shows the opposite pattern. Within-species lower mortality (lMR) is associated with a steeper increase in death risk across adulthood—faster rates of demographic aging. The evolutionary models all assume that more energy allocated to somatic maintenance pays off in future reproduction but leaves less for current reproductive effort. Life history variation among individuals of the same population often seems to go in the opposite direction as well. Women with higher fertility rates and later ages at last birth also have higher subsequent survival rates (Perls et al., 1997; Müller et al., 2002; Smith et al., 2002, 2009; Jacobsen et al., 2003; Gagnon et al., 2009). Such apparent absence of the expected tradeoffs within populations is a regular finding in field studies in animal behavior (van Noordwijk and de Jong, 1986; Pettifor et al., 1988; Lessels, 1991). A common explanation is that individuals differ in their resources. When these differences are ignored (or unobservable) and subjects are pooled, the resource differences obscure the tradeoff because those with more resources can have more of everything. Like houses and cars (van Noordwijk and de Jong, 1986), more into mortgage payments leaves less for auto loans, but those with bigger budgets can put more into both.

If there is such heterogeneity, so that health and otherwise unobserved differences in frailty vary within the populations shown in Fig. 11.2 , that heterogeneity could account for the Strehler–Mildvan correlations in the following way (Hawkes et al., 2009). Frail individuals die earlier. They die even earlier under more severe conditions. Such mortality selection (Manton and Stallard, 1984), or culling (Wachter, 2003), changes the relative representation of subpopulations among the survivors. Older age classes are a biased subset of younger ones and that bias affects their average mortality risk. In higher mortality populations of both humans and chimpanzees, older age classes are more strongly culled, leaving proportionately fewer frail survivors. Conversely, when background mortality is low, mortality selection is weaker and more of the frail survive longer. Although absolute risk of death is lower, the relative risk in each age class increases more steeply with advancing age because later age classes include more individuals with relatively greater vulnerability.

Heterogeneity could take many forms (Vaupel and Yashin, 1985). One simple possibility is that populations are composed of two (unobserved) subpopulations, each with a Gompertz schedule of risk. The frailer sub-population has higher mortality risk at each age and steeper increasing risk. The log of the risk of death at each age has both a higher intercept and higher slope in the frailer subpopulation (Hawkes et al., 2009; Wilmoth and Horiuchi, 1999). Fig. 11.3 displays the age-specific mortality curves for simulated populations with such heterogeneity facing two different background conditions of mortality risk. In each condition there are two subpopulations, with exactly the same relative differences in age-specific risk of death. Gompertz demographic aging is linear with age on this semilog plot. The simulation uses observed ranges of variation in initial mortality rates and slopes across the sample of human populations in Fig. 11.2 to estimate realistic ranges. Fig. 11.3 shows the age-specific risk for the subpopulations and for the whole population when the subpopulations are pooled. More of the frail die at each age, and older age classes are increasingly biased toward the more robust in both conditions; but when overall mortality is low—the lower set of lines—more of the frail survive to older ages and so their higher and steeper risk has a larger effect on the relative risk of later age classes. The difference between the two subpopulations is identical in both environments, but the increase in mortality with age is about twice as steep when background mortality is lower. This is the same difference seen across empirical populations in Fig. 11.2 .

FIGURE 11.3

Two model subpopulations, one frail (open circles) and the other robust (filled squares), exposed to two conditions of age-independent mortality. Initial mortality rates are low (similar to the United States and Japan) for the lower set of lines and high (more...)

HETEROGENEITY AND FERTILITY

The same kind of differential frailty proposed to underlie the Strehler–Mildvan correlations in Fig. 11.2 , and modeled in Fig. 11.3 , is relevant to age-specific fertility. As shown in Fig. 11.1 , the childbearing years end at the age of ~45 in both humans and chimpanzees. Like other female mammals, humans and chimpanzees build initial oocyte stocks in early life that then deplete with age (vom Saal et al., 1994). Most of the initial stock is lost to atresia, a continuing process of cell death that begins near birth. In women, stocks decline from ~7 million oocytes at 5 months after conception to <2 million at birth and ~400,000 at puberty (Baker, 1963). Only one in a thousand of those remaining when ovarian cycling begins actually ovulate. Numbers continue to fall across young and middle adulthood, reaching thresholds associated first with reduced fecundability, then secondary sterility, and finally menopause ~10 years after last birth. Average ages at these thresholds differ some across populations (Bentley and Muttukrishna, 2007) with substantial variation around the averages (Faddy and Gosden, 1996; O’Connor et al., 2001; Sievert, 2006; Broekmans et al., 2009). The classic counts of human ovarian follicle stocks show that among females of the same age, remaining primordial follicle stocks can vary by two orders of magnitude (Block, 1952; Richardson et al., 1987; Gougeon et al., 1994).

Chimpanzee follicle stocks also vary among individuals of similar age (Jones et al., 2007). Archived ovarian sections taken at necropsy from captive chimpanzees of ages 0–47 years index this variation and the declining numbers with age (Jones et al., 2007). Exponential regressions fit to the age-specific primordial follicle counts on those sections and also to the whole ovary counts across that 0- to 47-year range in the classic human datasets provide a quantitative comparison of follicular loss rate in the two species. The intercepts—the heights—of the two regression lines are necessarily different because the human data represent whole ovaries and only single sections were available for the chimpanzees. [An average section is ~1/2,000 of a human ovary (Block, 1952; Richardson et al., 1987)—likely the same for chimpanzees.] However, the rate of depletion with age measured this way, on these samples, across this age range, is indistinguishable between the two species (Jones et al., 2007). This similarity is consistent with a wider body of findings, including hormone and cycling data from captive chimpanzees (Graham, 1979; Gould et al., 1981; Lacreuse et al., 2008), suggesting they would reach menopause at about the same ages humans do—if they lived long enough (Walker and Herndon, 2008).

As implied by these similarities and noted above, humans and chimpanzees can give birth into their mid-forties but not beyond. However, in spite of this similarity in the end of the childbearing years ( Fig. 11.1 ), the shapes of age-specific fertility curves in the two species are strikingly different. Fig. 11.4 displays the average age-specific fertilities for three hunter-gatherer populations and the conservative age-specific fertility schedule synthesized from six wild chimpanzee populations by M. Emery Thompson and others (2007). Human populations can differ widely in fertility levels, but among them—hunter-gatherers included—the change in the rate of babies born to women of each age has a familiar peaked shape. “[I]n all populations where reliable records have been kept, fertility is zero until about age 15, rises smoothly to a single peak, and falls smoothly to zero by age 45–50” (Coale and Demeny, 1983, p. 27). The fertility schedule for wild chimpanzees is flat-topped instead. The rate reached before the age of 20 continues with little change for two more decades.

FIGURE 11.4

Age-specific fertility rates (ASFR) for humans and chimpanzees. Humans (open circles) are represented by the average of three hunter-gatherer populations: !Kung Bushmen of Botswana (Hill and Hurtado, 1996), Ache of Paraguay (Hill and Hurtado, 1996), and (more...)

The percentages running along the horizontal axis in Fig. 11.4 show the relative size of each age class compared to the first age class of adulthood. The chimpanzee figures come from the number of risk years observed in each age class in Emery Thompson and colleagues’ (2007) supplementary table 2. For human hunter-gatherers the figures come from the female life table for Hadza foragers (Blurton Jones et al., 2002). As the percentages show, almost all of the chimpanzees that survive to adulthood then die during the childbearing years; only 1% do not. By contrast, 24% of the hunter-gatherer women die during the childbearing years; 76% do not.

Emery Thompson and colleagues (2007) demonstrated heterogeneity in chimpanzee fertility in their six-site sample by looking for associations between fertility rates and survival in females over the age of 25. They divided their observations into healthy and unhealthy years. An observation year for a given chimpanzee was considered healthy if she survived an additional 5 years or more, and unhealthy if she did not. Their figure 2 (Emery Thompson et al., 2007, p. 2152) shows that fertility in the thirties was about twice as high in females who would survive at least 5 more years than in those who would not. The finding indicates that mortality selection across the childbearing years culls the females with lower fertility. As the age classes shrink to almost nothing, they are increasingly biased to the less frail, more fertile females. Consequently, average fertility changes little even if the fertility of the survivors is declining relative to their own earlier rate.

We found similar heterogeneity in fertility in 19th century Utah women [the Utah Population Data Base (UPDB) (Bean et al., 1990)]. Although not hunter-gatherers, these women practiced natural fertility (Henry, 1961), so potential for continued childbearing is reflected by actual births. Individual records make it possible to investigate links between variation in fertility rate and age at last birth. Of 42,493 parous UPDB women born between 1849 and 1890, the 10,440 whose fertility ended before the age of 35 had fertility rates in the preceding years about half as high as the 2,695 women who would have last births after 45 (Hawkes and Smith, 2010). This parallels the chimpanzee variation with an important difference: all the women in the Utah sample, whatever their age of last birth, survived at least to the age of 50. The sample was restricted to women who lived at least to that age to avoid the confound of early last births due to early death (Hawkes and Smith, 2009). Subjects were also restricted to those married once and neither widowed nor divorced to reduce effects these characteristics may have on fertility.

Assuming that heterogeneity in fertility is similar in the hunter-gatherer women, this variation combined with the different survival schedules of humans and chimpanzees can explain the different shapes of the fertility schedules shown in Fig. 11.4 . Most women, whatever their frailty, survive the childbearing years, whereas across those years mortality culls chim panzee females down to a least frail few. The human schedule is peaked because women with both high and low risk of fertility failure outlive the childbearing years. Beginning about the age of 30, each subsequent age interval contains more women who are past their last parturition. This drives down the average rate of baby production for later age intervals (Wood, 1989, 1994; Hawkes and Smith, 2010). The chimpanzee schedule is flat because heterogeneity in ovarian aging is culled away by mortality selection. Most chimpanzees die during the childbearing years and the survivors are females whose fertility rate has been high all along (Emery Thompson et al., 2007; Hawkes and Smith, 2010). In captive chimpanzees, lower mortality allows more frail individuals to survive longer so that captive chimpanzee fertility slopes down from a peak, more like the human pattern (Littleton, 2005; Roof et al., 2005).

ORIGINS OF HETEROGENEITY IN EARLY LIFE

Human age structures looked much like the hunter-gatherer example shown in Fig. 11.1 until the 20th century when life expectancies at birth began to increase in some populations (Keyfitz and Fleiger, 1968; Oeppen and Vaupel, 2002). Until the mid-20th century, these increases were largely a consequence of decreasing numbers of dying infants and children: lower juvenile mortality is strongly associated with lower fertility. Fig. 11.5 shows number of births for UPDB women who survived at least to 50 by their own birth year across the 19th century (Hawkes and Smith, 2009). After the middle of the 19th century, fertility began a steady decline—falling to half of its earlier level by 1900. Fig. 11.5 also shows a concurrent change in adult mortality. The average age at death for women who had survived at least to 50 increased from ~75 at mid-century to ~80 at its end. These decreases in mortality and fertility typify changes in some other populations at about the same time, likely due to improvements in nutrition, sanitation, and medicine (Fogel, 2004; Finch, 2007). By the end of the 20th century, continuing decreases in fertility and increases in juvenile and adult survival resulted in life expectancies double those of most historical and ethnographic populations (Oeppen and Vaupel, 2002; Gurven and Kaplan, 2007; Finch, 2010). The increases in survival allowed increased heterogeneity at older ages. Other effects on heterogeneity are likely as well.

FIGURE 11.5

Number of births (filled circles) and age at death (open diamonds) in cohorts of UPDB women by their birth year across the 19th century, redrawn from Hawkes and Smith (2009)]. Only women who survived past the age of 50 are included.

Associations between regional infant mortality rates and late life morbidities led D. J. Barker to propose his infant and fetal origins of adult disease hypothesis (Barker and Osmond, 1986; Barker et al., 1989; Gluckman et al., 2008). Those who survive nutritional and disease insults in early life are predisposed to metabolic and cardiovascular disease in adulthood. Pursuit of Barker’s hypothesis has revealed that when historical cohorts have been exposed to famines and epidemics during fetal life they have higher rates of disease and mortality in later adulthood than do adjacent cohorts (Finch and Crimmins, 2004; Mazumder et al., 2009). Analyses of adult morbidity and mortality by birth month and season have yielded similar evidence of heterogeneity in frailty stemming from nutritional constraints and disease exposure in early life (Moore et al., 1997; Doblhammer and Vaupel, 2001).

Differences between cohorts are necessarily an underestimate of the likely heterogeneity. B. Mazunder and colleagues (2009) compared morbidities in later adulthood between Americans who were likely exposed in fetal life to the 1918 influenza pandemic and those in adjacent cohorts. As they noted, “Maternal health during the pandemic peak … varied widely from no clinical infection, mild uncomplicated flu or flu with severe secondary pneumonia that still permitted normal birth” (p. 4). Those whose birth dates indicate probable fetal flu exposure must include some unexposed individuals. In the same way, adjacent cohorts must include some individuals whose mothers experienced infection. Nutrition, energy expenditure, and stress may also impact the effects of disease (Finch, 2007; Kuzawa and Quinn, 2009; Kuzawa and Sweet, 2009), and recent disease history of groups in the sample may also influence responses to early life conditions (Costa et al., 2007; Pennington et al., 2009). Even with the imperfect association between exposure and birth date and effects of these unmeasured covariates, rates of cardiovascular disease after the age of 60 were >20% higher in those whose fetal development coincided with pan demic (Mazumder et al., 2009). That this is a minimum estimate of early life effects on heterogeneity in aging rates is underscored by longitudinal datasets documenting within-cohort associations between early growth and both ovarian aging and mid-life physical performance (Hardy and Kuh, 2002; Kuh et al., 2002).

The early origins hypothesis predicts that declines in mortality in the Utah women during the second half of the 19th century would affect the next generation. Longer survival likely indicates better nourishment, less illness, and reduced hardship. If so, the children of those surviving longer would have been less exposed to nutritional limits and infection in early life, and so have lower risks of various later morbidities. Improvements in nutrition, general public health, and, subsequently, medical interventions should mitigate early life insults and reduce consequent heterogeneity. However, lowered mortality also reduces mortality selection, allowing greater heterogeneity to persist to older ages. This heterogeneity hypothesis ( Fig. 11.3 ) to explain population variation in demographic aging ( Fig. 11.2 ) applies to chimpanzees (and other taxa) as well as humans. Life expectancy at birth for female chimpanzees in the wild is 15 years (Hill et al., 2001). In captivity it is 29 years (Dyke et al., 1995). This doubling of chimpanzee life expectancy is associated with reductions in rates of infection and nutritional stress (Goodall, 1986; Williams et al., 2008). In both chimpanzees and humans, improvements in nutrition and hygiene combined with medical interventions can double life expectancy. And in both, longer life expectancies are associated with faster rates of demographic aging ( Fig. 11.2 )—due perhaps, as argued here, to increased heterogeneity of frailty at older ages ( Fig. 11.3 ).

BACK TO GRANDMOTHERS

This heterogeneity hypothesis may explain why humans, chimpanzees, and other taxa display Strehler–Mildvan correlations. The similarities cannot explain why humans usually outlive the childbearing years and chimpanzees do not (Figs. 11.1 and 11.2 ). Physiological mechanisms, let alone genetic differences that underlie the survival differences, remain elusive (de Magalhães and Church, 2007; Finch, 2010), although mitochondrial mutation rates may be involved (Kujoth et al., 2007; Nabholz et al., 2007). Hamilton’s forces (Hamilton, 1966; Rose et al., 2007) do not specify particular mechanisms of aging, but their incorporation in an analysis of human survival curves points to a deep history of reproductive benefits accruing to postmenopausal women in our lineage. Mueller, Rose, and Rauser have focused attention on the period of life in many species when mortality rates slow from an exponential increase and may become constant at succeeding age intervals. They reject Vaupel’s heterogeneity of frailty hypothesis (Vaupel et al., 1998) as a general explanation for these mortality plateaus, finding evidence more consistent with expectations from evolutionary theory about late life (Mueller and Rose, 1996; Rauser et al., 2006; Rose et al., 2007). When individuals survive past normal life spans, they are beyond the ages where senescence has been molded by ancestral forces of selection. “Hamiltonian theory predicts that late-life mortality rates should plateau and evolve according to the last age of reproduction in a population’s evolutionary history” (Rauser et al., 2006, p. 26). Because human mortality rates begin to decelerate and depart from a Gompertz curve only around the ninetieth year (Vaupel et al., 1998), the mortality plateau criterion implies that contributions to reproduction from ancestral grandmothers continued through their eighties.

This demographic evidence of grandmaternal effects on reproduction in our lineage has other implications that can barely be touched on here. S. B. Hrdy (Hrdy, 1999, 2005, 2009; Burkart et al., 2009) has hypothesized that selection pressures for distinctively human cognitive and emotional capacities arose from our evolution as cooperatively breeding apes. Unlike our nearest living relatives, human mothers accept help with babies right from parturition. Depending on help, they can bear a new baby while previous offspring still need provisioning. This has consequences for selection pressures on both mothers and infants. Unlike chimpanzee mothers, humans must also consider the occupation and whereabouts of potential helpers as well as the needs of still dependent weaned children. Abilities to juggle these additional concerns supersede the more single-minded focus on the newborn of other ape mothers. The novel maternal sensitivities create problems in turn for human infants that do not arise for other infant apes. Human babies cannot count on mother’s undivided commitment, so capacities to actively engage her and also to evaluate and engage other helpers are crucial. In high infant mortality environments, selection on those capacities would have been especially strong. Hrdy (2009) links those circumstance to the evolution in our lineage of motivations and capacities for intersubjective engagement that M. Tomasello and colleagues (Tomasello and Rakoczy, 2003; Tomasello et al., 2005) identify as the foundation for human prosociality.

Ethnographers have documented the ubiquity and importance of allomothering from many kinds of kin in living human communities (Sear and Mace, 2008), but grandmothers in particular are implicated in the hypothesis about the evolution of human life history entertained here. If ancestral grandmothers provided the help that initially allowed mothers in our lineage to move on to the next baby before the previous one could feed itself, propelling the evolution of human postmenopausal longevity, that initiated cooperative breeding in a previously independently breeding ancestral ape. These arguments link distinctive human cognitive and emotional capacities to selection pressures that arose as a consequence of ancestral grandmothering.

Ovarian aging appears to differ little between modern humans and chimpanzees, making it likely the same pattern characterized our ancestors. Before the shifts to greater longevity in our lineage, heterogeneity in ovarian and somatic aging would have been strongly culled by mortality selection across the childbearing years. If grandmother effects reduced mortality across those years, heterogeneity in ovarian aging would have expanded as more and more women outlived their fertility. Subsidies for relatives’ reproduction would have begun well before the average age at last birth, let alone the average age of menopause. By this argument, heterogeneity in ovarian aging is an ancient legacy of grandmothering in our lineage; but now such heterogeneity poses unprecedented concerns in the human populations where childbearing is delayed and nuclear families are isolated as never before. Many women find they have missed their own windows of fertility (Broekmans et al., 2009). Although aging is often seen as a process that befalls the old, evolutionary theories of aging predict that function begins to decline in early adulthood. Such declines have been documented not only in fertility, but in muscle strength and cognitive performance (Hunter et al., 2000; Salthouse, 2009); and where mortality levels have dropped to evolutionarily unprecedented lows, heterogeneity in somatic competence is increasingly well documented in those past mid-life (Mitnitski et al., 2005; Rockwood and Mitnitski, 2007). Just as grandmothering may have expanded heterogeneity in ovarian aging by lowering mortality across the childbearing years, recently dropping mortality rates at older ages expand heterogeneity well beyond them. As continuing innovations in medical and daily living technologies interact with mortality selection to produce complex dynamics in the health and welfare of elders (Manton, 2008), the heterogeneity in ovarian and somatic aging that is an aspect of our evolved life history becomes an increasing medical as well as social, economic, and political concern of our time.

ACKNOWLEDGMENTS

I am grateful for valuable insights and advice from J. F. O’Connell, J. E. Coxworth, J. K. Blevins, C. W. Kuzawa, and S. B. Hrdy, and for research support from the National Science Foundation.

Department of Anthropology, University of Utah, Salt Lake City, UT 84112. E-mail: ude.hatu.orhtna@sekwah .

Cite this Page National Academy of Sciences (US); Avise JC, Ayala FJ, editors. In the Light of Evolution: Volume IV: The Human Condition. Washington (DC): National Academies Press (US); 2010. 11, How Grandmother Effects Plus Individual Variation in Frailty Shape Fertility and Mortality: Guidance from Human-Chimpanzee Comparisons.
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The Centrality of Ancestral Grandmothering in Human Evolution

Economics of foraging for savanna resources

Age and sex preferences, risky versus predictable resources

Phylogenetic context of human life history evolution

Grandmothering in the context of systematic variation in mammalian life histories

Mathematical modeling of the grandmother hypothesis

Mating sex ratio consequences of our postmenopausal longevity

Increased longevity and the evolution of big human brains

Cognitive consequences of our grandmothering life history

Reproductive value and somatic versus current reproductive effort

Reproductive value, grandmothering and increased longevity

Inclusive reproductive value

The Fisher condition, offspring sex ratios, and mating sex ratios

Sexual conflict, longevity, and the product theorem again?

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In the Light of Evolution: Volume IV: The Human Condition.

11 How Grandmother Effects Plus Individual Variation in Frailty Shape Fertility and Mortality: Guidance from Human-Chimpanzee Comparisons

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