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Evolutionary approaches to the demographic transition

From EverybodyWiki Bios & Wiki






For the last 200 years the fertility/demographic transition has been transforming the global population. In most regions of the world, significant reductions in child mortality rates brought on by economic development and improvements in public health have been followed by population growth , and subsequent reductions in fertility rates. The demographic transition can be described as a process in which an initial decrease in mortality is followed by a decrease in fertility some years later. Specifically, concurrent reductions in mortality and fertility suggests a negative association between modernization and fertility exists. Ultimately, there is mounting evidence that people living in modern state societies (1)do not maximize their reproductive success through their fertility decisions and that (2) higher earning adults produce no more children than their less-earning counterparts.

The evolutionary paradox[edit]

The fact that people in modernized states increasingly elect to reproduce at lower levels than required to maximize their lifetime reproductive success poses a major challenge to evolutionary theorization. Finding an explanation for low 'first-world' fertility is of particular relevance to evolutionary explanations of human behavior because natural selection should favor behaviors that effectively convert resources to offspring. Given such selection pressures, modernized societies with high levels of material well-being would be expected to have high fertility, not low. However, observed fertility patterns deviate from predictions generated by evolutionary theory in two fundamental ways:[1]

  1. The observed fertility rates of people living in modern state societies are lower than that which would be expected by models of fitness maximization.
  3. Wealth and observed fertility rates appear to correlate negatively, such that the more wealthy people become the less likely they are to reproduce.

Since Vining’s 1980’s proposition that the demographic transition presents a fundamental problem to human sociobiology & evolutionary theory,[2] much work has been done to address this puzzle. Within the literature, varied evolutionary pathways (i.e. adaptation, mismatch, or byproduct) have been put forth as candidate explanations for post demographic transition fertility rates. Moreover, the causal mechanism believed to be responsible for motivating people to reduce their fertility has produced debate among the evolutionary community.

Presently, and despite the debate, the work done by evolutionary theorists suggests low first world fertility is the result of (a) changes in parental motivations for fertility or (b) changes in key ecological cues that have downstream implications on parental investment and offspring outcomes.[3][4]

Evolution and evolutionary demography[edit]

Evolutionary approaches to demography emphasize the importance of fitness effects over the course of human evolution. Demography is an integral part of evolutionary biology [5] and evolutionary biologists seek to understand the manner by which physiology, psychology, and behavior have been shaped by natural selection to maximize fitness. An individual is biologically ‘fit’ if, relative to others in the population, they can get many copies of their genes into subsequent generations. A shorthand term used to define ‘fitness’ is ‘reproductive success' which is often measured as the number of children that survive to reproductive maturity. Importantly, maximizing reproductive success does not require that individuals produce as many offspring as physiologically possible (see discussion of Optimality below).

Evolutionary approaches to demography[edit]

Evolutionary approaches to demography start with the prediction that fertility broadly functions to maximize fitness in a particular ecology. This latter point is key, evolutionary theorists see modern fertility patterns as maladaptive but consistent with behaviors that would have been adaptive in the environment of evolutionary adaptation / under ecological conditions similar to those in most premodern societies.[6][7]

The evolutionary approach shares many features with economic approaches because both are concerned with the manner by which costs and benefits determine optimality and produce variation. However, in economic models the currency of “utility” can be anything identified as a preference whereas in evolutionary models the currency of utility is Darwinian fitness.[8] An economic model is only evolutionary if that preference can be explained as benefitting the fitness of the individual or could reasonably be assumed to benefit fitness if people were living in an environment in which the behavior evolved (for an example of an application of evolutionary economic methods to the study of low fertility see Hill et al., 2004[9] ).

Strengths[edit]

The top-down, theoretically motivated approach of evolutionary biology means that the human evolutionary sciences are very diverse, interdisciplinary, and comparative (for a review on evolutionary contributions to the study of human fertility see Sear 2015 [10] ) Evolutionary approaches to demographic phenomenon (1) are integrative, (2) are relevant, and (3) provide a new methods by which to test old hypothesis as well as the ability to generate new ones.

Evolutionary Models are Integrative Evolutionary demographers move across disciplines, drawing on biology, anthropology, and psychology, and across the physiological, psychological, and even cultural causes of fertility variation. Evolutionary models account for cultural effects, they predict how reproductive success is maximized in a given environment and theorists understand that the environment includes social contexts/influences like culture. Further, cultural evolutionary models also touch on areas of wider interest to demographers, such as the importance of diffusion and social learning in changing cultural norms of fertility (see Cultural Transmission model below).[11] Overall, the strength of this approach comes from its ability to predict behavior across ecological and social contexts.

In addition, evolutionary demographers take a within- and cross- species comparative approach to the study of fertility, testing hypotheses across species, in past and extant populations, and in populations with varying densities, cultures, and subsistence practices. Evolutionary theory has much to say about mate choice, parental investment theory, and decision-making-rules − factors which influence not just behavior in traditional small-scale societies but also behavior in developed societies. Overall, the robust focus on comparative work yields a better understanding of our evolutionary history and of what elements in our physical and social environment have or have not changed, thus honing the effectiveness of the approach.

In part due to its cross-cultural and comparative focus, an evolutionary approach can not only add pieces to the puzzle of why fertility varies, it can provide a unifying framework by which seemingly disparate pieces can tie together.

Evolutionary Models are Relevant Findings from behavioral genetics suggests that traits such as age at first birth, age at first attempt to have children, age at menarche, number of children, and even some sexual behaviors are genetically inherited.[12] This highlights the influence of selection pressures and supports the case for evolutionary theorization.

Evolutionary models and novel hypotheses[edit]

Application of evolutionary theory to the phenomenon of low 'first-world' fertility aims to explain why variation in fertility exists and how it changes. The approach may also help make sense of why other social science models sometimes fail to explain why humans behave in seemingly irrational ways that do not necessarily maximize individual wealth or well-being.[10] This is because evolutionary scholars understand that natural selection shaped individuals to maximize Darwinian fitness7 which sometimes leads to behavior that does not maximize health or wealth. Given this, evolutionary anthropologists and demographers have used the tools of their craft to develop new hypotheses and test new variants of old hypotheses in ways that benefit investigations of low fertility. For example, in contemporary industrialized populations, being of low socioeconomic status and/or being exposed to childhood adversity increases the odds of early childbearing, and while some work [13] suggest early childbearing is maladaptive (because it damages the potential to invest in one’s own education and prospects) other lines of evolutionary research see early childbearing as a strategic response to indicators of adversity that in ancestral environments would correlate with a high risk of dying before reaching reproductive maturity.[14]

Weaknesses[edit]

Evolutionary theory is unique in its ability to provide a parsimonious explanation for most aspects of life (physiology, psychology, development, or behavior). Still, its ability to generate explanations for demographic phenomena can be constrained. For example, if the phenomenon of study is likely to have arisen as a resent response to industrialization and urbanization, evolutionary demography may not be able to predict current behavior. Furthermore, as child mortality was probably the most important selection pressure acting on reproductive decision-making, it is not clear how much selection there currently is on human fertility behavior now that both child mortality and fertility are low.[8] However, even in modern settings, having an uncertain future and a higher mortality risk are factors that are still associated with earlier childbearing.[15]

Evolutionary theory[edit]

Natural selection is assumed to act on physiological and decision-making processes such that these processes maximize individual fitness in the environment in which they evolved.

Evolution by natural selection requires that (1) variation in traits exists (2) traits are heritable, and (3) variation in traits be related to individual fitness / differential reproductive success. If these three things hold then those traits which result in higher fitness will spread throughout the population.

‘Fitness’ refers to the representation of genes in future generations: an individual is biologically ‘fit’ if he or she succeeds in getting many copies of their genes into subsequent generations relative to others in the same population. Notably, what individuals are actually maximizing is ‘inclusive fitness’ which is a measure of the number of relatives an individual produces, weighted according to how closely related they are to the individual by direct descent.[16]

What is optimal?[edit]

Maximizing reproductive success is not necessarily about maximizing fitness because maximizing the number of offspring one has does not result in optimal fertility.

It is estimated that over the course of human evolution an average of less than 50% of offspring born contributed to future generations through their own survival and reproduction.[17] A Darwinian demon, an individual who reproduces at the maximum rate, would not succeed in the real world. Under these conditions, it is likely that offspring production and survival would not evenly correspond as there would be costs of reproduction for the mother and father and there would be competition between an infinite number of siblings for finite parental resources.[18] Balancing these costs with the fitness benefits of fertility while also assessing constraints (e.g. age/caloric/partner constraints), ultimately determines the rate and nature of human reproductive decisions.[19] Thus, what is optimal is determined by the energetic resources available and the constraints put forth by competing costs and benefits that vary with locally specific mortality risks.[20]

Life history theory[edit]

One of the frameworks used to understand variation in optimality is life history theory. Variation in an organism’s reproductive strategy and pace of life is reflected in life history characters (e.g. body size, growth rate, fertility rate, etc.) and adoption of a particular investment regime has downstream effects on growth, reproduction, and maintenance schedules.[21] For example, poor nutrition decreases body size, slows down reproductive maturity, and thus has the potential to delay fertility. Similarly, increased mortality risks and stress accelerate reproductive schedules and decrease lifespan.[22]

Life history models emphasize the importance of body size, production rates, and mortality in explaining diverse fertility outcomes.[23][24] Broadly, life history theory offers evolutionary explanations for the timing of life events, with particular focus on age-schedules of fertility and mortality.[24] The focus on fertility and mortality occurs because, in these models, fitness is a measure derived from summing the reproductive output of each year lived.[25] The focus on timing occurs because an age structure to the manner by which energy is required and acquired exists.

The tripartite energetic trade-off[edit]

Life history theory is concerned with the manner by which organisms capture finite energy resources from the environment and allocate them towards the competing systems of growth, maintenance, and reproduction.[21] These systems compete because energy invested in one system cannot be invested in another, this trade-off notion is key because allocation decisions can affect the number of descendants an individual can produce. For example, many if not most traits have opposing effects on survival and fertility, with investments in productivity (e.g. growth and reproduction) necessarily trading-off with investment in maintenance (e.g. lifespan).[26]

Further, there is growing recognition of the importance of social, particularly intergenerational, transfers in the evolution of life history patterns. Each human, for example, relies not only on his or her own energy budget to survive and reproduce but also receives energy transfers from others, a phenomenon described in some of the evolutionary literature as a ‘pooled energy budget’.[27]

Trade-offs within reproduction[edit]

The principles of life history theory state that energy used for one purpose cannot be used for another. Thus, tradeoffs are expected between growth and reproduction as well as maintenance and reproduction but also within reproductive domains. Energy devoted to reproduction must be divided between:

  1. Energy invested in mating and energy invested in offspring
  2. Energy invested in offspring quantity and offspring quality
  3. Energy invested in reproducing now vs. reproducing later
Quantity vs. quality of offspring[edit]

Offspring quality is a function of parental investment and though costly, such investments can benefit a parent’s inclusive fitness by increasing the odds their offspring will survive and reproduce. In general, natural selection on offspring quantity and investment per offspring (offspring quality) is expected to maximize the number of offspring that survive to reproduce.[28][26] Evolutionary models addressing the shift from quantity to quality, explain that natural selection has equipped humans with physiological and psychological mechanisms that allow them to adjust fertility rates and fertility schedules in a manner consistent with changing environmental conditions.[29]

Current vs. future reproduction[edit]

The tripartive tradeoff can produce a tradeoff between current and future reproduction because maintenance and growth affect fitness through their impact on future fertility.[30] Individuals can invest energy in current reproduction or can invest energy in maintenance/growth to ‘buy more time’ and maximize total energetic allocations to reproduce later. Investing in growth has the potential to increase future energy capture rates and thus future fertility outcomes and investing in repair or maintenance of the soma can increase the length of time over which individuals live and harvest energy. Ultimately, the manner by which investments are allocated are context sensitive and often depend on environmental factors such as mortality risk.[24]

Embodied capital[edit]

The embodied capital theory treats investments in life history domains as investments in soma (somatic tissue) or functional abilities (e.g. strength, immunity, knowledge) as a stock of capital that pays off over time.[7] These stocks depreciate over time and so investments in maintenance are proxy measures of embodied capital investments.

Embodied capital models have produced results relevant to fundamental issues in life history allocation challenges and suggest investments that increase energy capture rates coevolve with investments relevant to mortality and longevity.

In addition, exogenous changes in offspring survival rates can affect fertility. If the level of investment required to increase offspring survival or offspring ability to harvest/capture energy, the costs of reproduction increase logarithmically with every child. These results also imply that if payoffs to investments in both offspring income and survival increase, large changes in fertility are expected.[7]

Evolutionary models of post demographic transition fertility trends[edit]

Over the last three decades many authors have addressed the demographic transition from the perspective of evolutionary theory. Some authors have emphasized parental investment factors such as the costs of raising children, others have emphasized the effects of mortality and other forms of risk, and others have emphasized the biased transmission of cultural norms from kin or people of high status.

Mortality risk models[edit]

The primary drivers of life history diversification are ecological : extrinsic mortality threats, nutritional resource availability, etc.,; these affect the manner by which an organism manages allocation challenges across life history domains (e.g. growth, maintenance, and reproduction) but also between competing aspects of reproduction itself (e.g. current vs. future reproduction).[21] If an organism is living in an environment where the risk of mortality by predation or disease is high, an allocation of resources to current reproduction efforts will be favored. It is important to emphasize that mortality based selection has an effect on reproductive maturity, wherein faster/earlier development implies greater investments in current rather than future reproduction, a pattern that makes sense if future survival is less certain.[31]

Is the relationship between mortality and fertility decline causal?

Authors have stressed the importance of decreasing risk, especially mortality risk, as a primary factor in decreasing fertility. While these models suggest that levels and types of risk affect motivations for parental investment (and so in some sense are also parental investment models), they emphasize changes in risk as the causal determinant of changes in reproductive behavior.

Chisholm (1993)[32] argues that human reproductive strategies may be contingent on local mortality rates such that those who experience more loss as children are more likely to pursue mating-oriented reproductive strategies, which may result in earlier and higher fertility, while those who experience a lower mortality environment may delay reproduction or pursue a strategy of high parental investment.

Winterhalder & Leslie (2002)[33] employ a risk-sensitive model of fertility optimization that places special focus on stochasticity in mortality patterns. These conditions serve to lower the degree of variance in completed family size, decrease the costs of abnormally low fertility, or increase the costs of abnormally high fertility. While predictions from their model are context sensitive, they argue that in general lower or more predictable mortality would decrease variance in completed family size outcomes and thus reduce the tendency of families to overcompensate by having numerous offspring.

Quinlan[34] and Quinlan and Quinlan[35] discuss the effects of extrinsic (non care-dependent) forms of risk on parental investment decisions. They use data from Dominica as well as comparative data from the standard cross-cultural sample and suggest humans would reduce parental effort in environments where parenting cannot improve offspring survival and, by implication, that if extrinsic risk decreases then parental effort should increase and fertility should decrease with it.

Investment models[edit]

Many authors who favor the hypothesis that costs and benefits drive the decline in fertility emphasize the importance of increased investment in oneself or one’s offspring (in embodied capital), or the related concept of increasing costs of offspring, as primary factors in decreasing either optimal fertility or age at first reproduction.

The Kaplan et al., model[edit]

The most prominent of these models is from Kaplan et al.[36][37][38][39] who propose that modernized environments (a) change/delay payoffs to investments in child quality, consequently influencing that manner by which potential parents make decisions about the number of children to have and (b) intensify the relationship between parental investment and offspring success, triggering evolved mechanisms of fertility regulation to value offspring quality over quantity.[40] They further suggest that human psychology has evolved to detect the relationship between parental investment and the ‘income’ potential of offspring and that parental decisions about how long to support and provision offspring are made on the basis of this assessment. They propose that reduced fertility results from high parental investment per child combined with maladaptive levels of fertility reduction geared towards reducing total parental investment costs. Kaplan et al.,[39] argues that parents with higher levels of investment themselves (particularly in the form of education) will be more effective at investing in their own children, thus benefiting from higher payoffs and having lower optimal fertility than parents not so well-endowed. This reasoning implies that high payoffs should precede fertility reduction, and Kaplan predicts that they may also spark demand for or uptake of contraceptives.

Modern industrialized societies have raised the costs of reproduction

Consider the costs of childrearing in modern societies, which include investments not only in schooling but also in goods associated with social training and status (e.g. hobbies/sports, clothing, toys, etc.,) with much of these investments demonstrating commitment to favorable placement for offspring in both the mating and market economy. In these contexts, the costs of having children increase and are top-heavy because offspring earning capacity/payoffs are delayed and require increased parental investment to be actualized.

Modernized contexts change the manner by which payoffs are calculated

It is possible that modernization processes trigger commitment to intensive investment in embodied capital.[41] Kaplan and colleagues propose that fertility transitions result from (1) improvements to public health and economic growth, and (2) the interactions of evolved psychological and physiological mechanisms governing human fertility.[42]

  • Public health improvements increase longevity and the length of payoff time. Public health improvements have lowered mortality rates and increased longevity and researchers propose that such improvements have also lengthened the time over which returns on investments in embodied capital are realized, thus suggesting that payoffs to investments in personal or offspring embodied capital depend on time not just the productivity of the investments.[43] According to the model, the effects of increased importance of education in determining wages along with the importance of having a longer productive life interact to produce even larger increases in embodied capital investments.
  • Competitive labor markets enhance payoffs to investments in quality. In addition, Kaplan & Lancaster propose that the emergence of competitive labor markets in the context of an increasingly technological economy greatly enhanced the economic payoffs to investment in the skills and formal education of children. And some research has found that parents respond to increases in skills-based labor market opportunities by reducing their fertility.[44] Thus, to prepare offspring for competition in labor markets where education and acquired skills are prime determinants of success, parents have fewer children and invest more in each child. Moreover, this body of research has demonstrated a relationship between parental investment and offspring academic success, with the increases in parental investment metrics positively associated with offspring educational attainments.[45] And other scholars [46] have developed a similar dynamic optimization model for understanding the demographic transition. This model predicts an increase in the investment cost of rearing offspring leads to a marked reduction in the optimal fertility rate, as well as an increase in wealth and inheritance.

The costs of child rearing[edit]

Research has shown that presence of siblings is associated with very significant reductions in time spent on parental care and yields adverse outcomes for offspring (e.g. shorter stature and poorer academic achievement) even in countries with free education and health care.[47] And a follow up study provides some evidence that sibling competition is more, not less, intense in wealthier homes and societies.[45] Relatedly, some scholars suggest the parental investment process is snowballing, driven by competition between individuals who favor quality over quantity in offspring, and that that is why the negative relationship between wealth and fertility exists.[48]

Proximate mechanisms[edit]

The shift toward parental investment in offspring quality yield the proximate mechanisms that result in low fertility. Kaplan and others suggest that as the trade-off between education and reproduction shifts towards education, women invest in maintenance and reproduce later.[49] Psychological mechanisms regulating parental investment in offspring quality may lead to greater and greater investment in own and offspring education, a smaller desired family size, a delay in the onset of reproduction, and a reduction in the total numbers of offspring produced. This delay in reproduction can cause many individuals to produce fewer children than desired because fecundity declines with time. In some cases, women may overestimate the benefits of education and have fewer offspring than they want, or even wait too long to.

Supporting evidence[edit]

Beyond post-demographic transition settings – societies in which extra-somatic wealth exists are vulnerable to the same investment cost formula and thus show a similar pattern.[50] Furthermore, research testing three competing evolutionary models of low first world fertility and focusing on two indicator of demographic transition (age at first reproduction event as well as total parity) found that though all three motivations are strong predictors of these indicators when they are combined in the same model investment models received the most robust support when compared independently.[51]

Cultural transmission models[edit]

Some evolutionary theorists propose that cultural transmission processes, Darwinian but nongenetic means of inheritance, can explain the low fertility pattern brought about by the demographic transition because they can select for traits that are socially successful but maladaptive. Cultural evolutionary research on social learning is interested in both how people learn from others and what they learn from others because both processes are not random.[52] Cultural evolutionary models examine dual inheritance mechanisms (cultural and biological) and have shown that over the course of a few generations, the cumulative impact of small differences in social influence can yield new reproductive norms.[53] In a study of 22 villages in rural Poland where the demographic transition is underway, researchers found that fertility is just as associated with education at the village level as with the socioeconomic position at the individual level and thus provided support for this view.[54]

Boyd & Richerson[55] provide an explanation of low modern fertility in terms of cultural evolutionary processes by exploring the effects social learning has on fertility behaviors and related outcomes, proposing that low fertility could be the result of prestige-based copying. Individuals that succeed in modern market economies, must often sacrifice their own fertility to achieve socioeconomic success and others copy this behavior because they are successful. This line of research sees these types of biases as heuristics, mental shortcuts, designed to increase reproductive success. The effects of fertility decisions are difficult to predict and can only be known many years after the decisions are made, thus theorists propose that modeling behaviors that are common and/or typical to successful individuals can result in increased reproductive success and is the most effective strategy.

Related models link high fertility with high contact of kin and suggest that the widening of social networks, a byproduct of modernization, explains changes in reproductive norms.[3] The model proposes two core pieces of evidence (1) pro-natalist advice/comments are most likely to come from kin and (2) such advice/comments have meaningful effects on reproduction-related social norms. Studies have shown that parental desire for grandchildren influences the reproductive behavior of their children.[56] In addition, kin enhance one another’s inclusive fitness by providing social support and advice and it is evolutionarily supported that - depending on who is listening and the degree to which the person is genetically related to them - people bias what they say about reproduction. Newsom and colleagues propose that members of modern predominantly non-kinship social networks share no interest in encouraging behaviors that enhance reproduction, but they do share a wide range of competing interests.

These theoretical models have received mathematical support but when tested empirically have produced mixed results. Studies conducted in environments undergoing the demographic transition have tested the effect of kin and other social influences on the decision to use contraception and have either not found support[57] or have found support that is limited to cultural transmission processes occurring within religious networks.[58] Other scholars propose that cultural influence could matter more for neutral traits (e.g. the decision to use a particular type of contraceptive) or for relatively trivial traits (e.g. fashions) than for matters that profoundly influence reproductive success (e.g. the decision about whether to use any type of contraceptive at all).[8] Still, and consistent with investment models, empirical work has revealed land inheritance to predict contraceptive use, with land-owning individuals being more likely to use contraception than their non land-owning counterparts.[59]

See also[edit]

References[edit]

  1. ↑ Borgerhoff Mulder, Monique (July 1998). "The demographic transition: are we any closer to an evolutionary explanation?". Trends in Ecology & Evolution. 13 (7): 266–270. doi:10.1016/S0169-5347(98)01357-3.
  2. ↑ Vining, Daniel R. (1986). "Social versus reproductive success: The central theoretical problem of human sociobiology". Behavioral and Brain Sciences. 9 (1): 167–187. doi:10.1017/S0140525X00021968. ISSN 1469-1825.
  3. ↑ 3.0 3.1 Newson, Lesley; Postmes, Tom; Lea, S. E. G; Webley, Paul (21 December 2016). "Why Are Modern Families Small? Toward an Evolutionary and Cultural Explanation for the Demographic Transition". Personality and Social Psychology Review. 9 (4): 360–375. doi:10.1207/s15327957pspr0904_5. PMID 16223357.
  4. ↑ Shenk, Mary K. (July 2009). "Testing three evolutionary models of the demographic transition: Patterns of fertility and age at marriage in urban South India". American Journal of Human Biology. 21 (4): 501–511. doi:10.1002/ajhb.20943. PMID 19408251.
  5. ↑ Metcalf, C. Jessica E.; Pavard, Samuel (April 2007). "Why evolutionary biologists should be demographers". Trends in Ecology & Evolution. 22 (4): 205–212. doi:10.1016/j.tree.2006.12.001. PMID 17174004.
  6. ↑ Mace, R (1998). "The co-evolution of human fertility and wealth inheritance strategies". Philosophical Transactions of the Royal Society B: Biological Sciences. 353 (1367): 389–397. doi:10.1098/rstb.1998.0217. PMC 1692221. PMID 9569432.
  7. ↑ 7.0 7.1 7.2 Kaplan, Hillard; Hill, Kim; Lancaster, Jane; Hurtado, A. Magdalena (2000). "A theory of human life history evolution: Diet, intelligence, and longevity". Evolutionary Anthropology: Issues, News, and Reviews. 9 (4): 156. doi:10.1002/1520-6505(2000)9:4<156::aid-evan5>3.0.co;2-7. ISSN 1520-6505.
  8. ↑ 8.0 8.1 8.2 Mace, Ruth (4 April 2014). "When not to have another baby: An evolutionary approach to low fertility". Demographic Research. 30: 1074–1096. doi:10.4054/DemRes.2014.30.37.
  9. ↑ Hill, Sarah E.; Reeve, H. Kern (2004-11-03). "Low fertility in humans as the evolutionary outcome of snowballing resource games". Behavioral Ecology. 16 (2): 398–402. doi:10.1093/beheco/ari001. ISSN 1465-7279.
  10. ↑ 10.0 10.1 Sear, Rebecca (26 April 2015). "Evolutionary contributions to the study of human fertility". Population Studies. 69 (sup1): S39–S55. doi:10.1080/00324728.2014.982905. PMID 25912916.
  11. ↑ Whiten, Andrew; Hinde, Robert A.; Laland, Kevin N.; Stringer, Christopher B. (2011-04-12). "Culture evolves". Philosophical Transactions of the Royal Society B: Biological Sciences. 366 (1567): 938–948. doi:10.1098/rstb.2010.0372. PMC 3049105. PMID 21357216.
  12. ↑ Kohler, Hans-Peter; Rodgers, Joseph Lee; Miller, Warren B.; Skytthe, AXEL; Christensen, Kaare (February 2006). "Bio-social determinants of fertility". International Journal of Andrology. 29 (1): 46–53. doi:10.1111/j.1365-2605.2005.00606.x. PMID 16466523.
  13. ↑ McLanahan, Sara (2004). "Diverging destinies: how children are faring under the second demographic transition". Demography. 41 (4): 607–627. doi:10.1353/dem.2004.0033. ISSN 0070-3370. PMID 15622946.
  14. ↑ Nettle, D. (3 January 2011). "Flexibility in reproductive timing in human females: integrating ultimate and proximate explanations". Philosophical Transactions of the Royal Society B: Biological Sciences. 366 (1563): 357–365. doi:10.1098/rstb.2010.0073. PMC 3013465. PMID 21199840.
  15. ↑ Wilson, Margo; Daly, Martin (26 April 1997). "Life expectancy, economic inequality, homicide, and reproductive timing in Chicago neighbourhoods". BMJ. 314 (7089): 1271–4. doi:10.1136/bmj.314.7089.1271. ISSN 0959-8138. PMC 2126620. PMID 9154035.
  16. ↑ Hamilton, W.D. (1964). "The genetical evolution of social behaviour. I". Journal of Theoretical Biology. 7 (1): 1–16. doi:10.1016/0022-5193(64)90038-4. ISSN 0022-5193. PMID 5875341.
  17. ↑ Wells, Jonathan C.K.; Stock, Jay T. (2007). "The biology of the colonizing ape". American Journal of Physical Anthropology. 134 (S45): 191–222. doi:10.1002/ajpa.20735. PMID 18046751.
  18. ↑ Trivers, R. (1972). Parental Investment and Sexual Selection. Aldine de Gruyter, New York: Chicago. pp. 136–179. Search this book on
  19. ↑ Hendrie, Colin A.; Brewer, Gayle; Lewis, Hannah; Mills, Francesca (3 April 2014). "Contemporary and Historical Evidence to Suggest that Women's Preference for Age at Birth of First Child Remains Consistent Across Time" (PDF). Archives of Sexual Behavior. 43 (7): 1373–1378. doi:10.1007/s10508-014-0290-6. PMID 24696388.
  20. ↑ Vitzthum, Virginia J. (October 2008). "Evolutionary Models of Women's Reproductive Functioning". Annual Review of Anthropology. 37 (1): 53–73. doi:10.1146/annurev.anthro.37.081407.085112.
  21. ↑ 21.0 21.1 21.2 Stearns, S. C. (1989). "Trade-Offs in Life-History Evolution". Functional Ecology. 3 (3): 259–268. doi:10.2307/2389364. JSTOR 2389364.
  22. ↑ Kuzawa, Christopher W.; Bragg, Jared M. (December 2012). "Plasticity in Human Life History Strategy". Current Anthropology. 53 (S6): S369–S382. doi:10.1086/667410.
  23. ↑ Kuzawa, Christopher W.; Bragg, Jared M. (December 2012). "Plasticity in Human Life History Strategy". Current Anthropology. 53 (S6): S369–S382. doi:10.1086/667410.
  24. ↑ 24.0 24.1 24.2 Roff, Derek (1994). "Charnov, E. L. 1993; Life History Invariants. Oxford University Press, Oxford. Xv + 167 pp., f13.50 (pbk). ISBN 0-19-854072-8 (cloth). ISBN 0-19-854071-X (paper)". Journal of Evolutionary Biology. 7 (3): 399–400. doi:10.1046/j.1420-9101.1994.7030399.x.
  25. ↑ Hill, Kim; Kaplan, Hillard (October 1999). "Life History Traits in Humans: Theory and Empirical Studies". Annual Review of Anthropology. 28 (1): 397–430. doi:10.1146/annurev.anthro.28.1.397. PMID 12295622.
  26. ↑ 26.0 26.1 Smith, Christopher C.; Fretwell, Stephen D. (1974). "The Optimal Balance between Size and Number of Offspring". The American Naturalist. 108 (962): 499–506. doi:10.1086/282929. ISSN 0003-0147.
  27. ↑ Kramer, Karen L.; Greaves, Russell D.; Ellison, Peter T. (July 2009). "Early reproductive maturity among Pumé foragers: Implications of a pooled energy model to fast life histories". American Journal of Human Biology. 21 (4): 430–437. doi:10.1002/ajhb.20930. PMID 19402033.
  28. ↑ Lawson, David W.; Borgerhoff Mulder, Monique (28 March 2016). "The offspring quantity–quality trade-off and human fertility variation". Philosophical Transactions of the Royal Society B: Biological Sciences. 371 (1692): 20150145. doi:10.1098/rstb.2015.0145. PMID 27022072.
  29. ↑ Hill, Kim; Kaplan, Hillard (1 October 1999). "Life History Traits in Humans: Theory and Empirical Studies". Annual Review of Anthropology. 28 (1): 397–430. doi:10.1146/annurev.anthro.28.1.397. ISSN 0084-6570. PMID 12295622.
  30. ↑ Hill, Kim; Kaplan, Hillard (1 October 1999). "Life History Traits in Humans: Theory and Empirical Studies". Annual Review of Anthropology. 28 (1): 397–430. doi:10.1146/annurev.anthro.28.1.397. ISSN 0084-6570. PMID 12295622.
  31. ↑ Charnov, Eric L. (22 May 1997). "Trade-off-invariant rules for evolutionary stable life histories". Nature. 387 (6631): 393–394. Bibcode:1997Natur.387..393C. doi:10.1038/387393a0.
  32. ↑ Chisholm, James S.; Ellison, Peter T.; Evans, Jeremy; Lee, P. C.; Lieberman, Leslie Sue; Pavlik, Zdenek; Ryan, Alan S.; Salter, Elizabeth M.; Stini, William A.; Worthman, Carol M. (1993). "Death, Hope, and Sex: Life-History Theory and the Development of Reproductive Strategies [and Comments and Reply]". Current Anthropology. 34 (1): 1–24. doi:10.1086/204131. JSTOR 2743728.
  33. ↑ Winterhalder, Bruce; Leslie, Paul (January 2002). "Risk-sensitive fertility". Evolution and Human Behavior. 23 (1): 59–82. doi:10.1016/s1090-5138(01)00089-7. ISSN 1090-5138.
  34. ↑ Quinlan, R. J (7 January 2007). "Human parental effort and environmental risk". Proceedings of the Royal Society B: Biological Sciences. 274 (1606): 121–125. doi:10.1098/rspb.2006.3690. PMC 1679876. PMID 17134996.
  35. ↑ Quinlan, Robert J; Quinlan, Marsha B (2007). "Parenting and Cultures of Risk: A Comparative Analysis of Infidelity, Aggression, and Witchcraft". American Anthropologist. 109: 164–179. doi:10.1525/aa.2007.109.1.164.
  36. ↑ Kaplan, Hillard; Lancaster, Jane B.; Tucker, W. Troy; Anderson, K.G. (March 2002). "Evolutionary approach to below replacement fertility". American Journal of Human Biology. 14 (2): 233–256. doi:10.1002/ajhb.10041. PMID 11891936.
  37. ↑ Kaplan, Hillard; Lancaster, Jane B.; Tucker, W. Troy; Anderson, K.G. (March 2002). "Evolutionary approach to below replacement fertility". American Journal of Human Biology. 14 (2): 233–256. doi:10.1002/ajhb.10041. PMID 11891936.
  38. ↑ Kaplan, Hillard; Hill, Kim; Lancaster, Jane; Hurtado, A. Magdalena (2000). "A theory of human life history evolution: Diet, intelligence, and longevity". Evolutionary Anthropology: Issues, News, and Reviews. 9 (4): 156. doi:10.1002/1520-6505(2000)9:4<156::AID-EVAN5>3.0.CO;2-7.
  39. ↑ 39.0 39.1 Kaplan, Hillard (1996). "A theory of fertility and parental investment in traditional and modern human societies". American Journal of Physical Anthropology. 101: 91. doi:10.1002/(sici)1096-8644(1996)23+<91::aid-ajpa4>3.0.co;2-c.
  40. ↑ Kaplan, Hillard; Lancaster, Jane B.; Tucker, W. Troy; Anderson, K.G. (March 2002). "Evolutionary approach to below replacement fertility". American Journal of Human Biology. 14 (2): 233–256. doi:10.1002/ajhb.10041. PMID 11891936.
  41. ↑ Hill, Kim; Kaplan, Hillard (1 October 1999). "Life History Traits in Humans: Theory and Empirical Studies". Annual Review of Anthropology. 28 (1): 397–430. doi:10.1146/annurev.anthro.28.1.397. ISSN 0084-6570. PMID 12295622.
  42. ↑ Kaplan, Hillard; Lancaster, Jane B.; Tucker, W. Troy; Anderson, K.G. (March 2002). "Evolutionary approach to below replacement fertility". American Journal of Human Biology. 14 (2): 233–256. doi:10.1002/ajhb.10041. PMID 11891936.
  43. ↑ Kaplan, Hillard; Lancaster, Jane B.; Tucker, W. Troy; Anderson, K.G. (March 2002). "Evolutionary approach to below replacement fertility". American Journal of Human Biology. 14 (2): 233–256. doi:10.1002/ajhb.10041. PMID 11891936.
  44. ↑ Kaplan, Hillard S.; Lancaster, Jane B.; Bock, John A.; Johnson, Sara E. (1995). "Fertility and Fitness Among Albuquerque Men: A Competitive Labour Market Theory". Human Reproductive Decisions. Palgrave, London: 96–136. doi:10.1007/978-1-349-23947-4_6. ISBN 978-1-349-23949-8.
  45. ↑ 45.0 45.1 Lawson, D. W.; Mace, R. (3 January 2011). "Parental investment and the optimization of human family size". Philosophical Transactions of the Royal Society B: Biological Sciences. 366 (1563): 333–343. doi:10.1098/rstb.2010.0297. PMC 3013477. PMID 21199838.
  46. ↑ Mace, R. (29 March 1998). "The co-evolution of human fertility and wealth inheritance strategies". Philosophical Transactions of the Royal Society B: Biological Sciences. 353 (1367): 389–397. doi:10.1098/rstb.1998.0217. PMC 1692221. PMID 9569432.
  47. ↑ Lawson, David W.; Mace, Ruth (9 March 2010). "Optimizing Modern Family Size". Human Nature. 21 (1): 39–61. doi:10.1007/s12110-010-9080-6. PMC 2847167. PMID 20376180.
  48. ↑ Hill, Sarah E.; Reeve, H. Kern (3 November 2004). "Low fertility in humans as the evolutionary outcome of snowballing resource games". Behavioral Ecology. 16 (2): 398–402. doi:10.1093/beheco/ari001. ISSN 1465-7279.
  49. ↑ Kaplan, Hillard; Hill, Kim; Lancaster, Jane; Hurtado, A. Magdalena (2000). "A theory of human life history evolution: Diet, intelligence, and longevity". Evolutionary Anthropology: Issues, News, and Reviews. 9 (4): 156. doi:10.1002/1520-6505(2000)9:4<156::AID-EVAN5>3.0.CO;2-7.
  50. ↑ Hill, Kim; Kaplan, Hillard (1 October 1999). "Life History Traits in Humans: Theory and Empirical Studies". Annual Review of Anthropology. 28 (1): 397–430. doi:10.1146/annurev.anthro.28.1.397. ISSN 0084-6570. PMID 12295622.
  51. ↑ Shenk, Mary K. (July 2009). "Testing three evolutionary models of the demographic transition: Patterns of fertility and age at marriage in urban South India". American Journal of Human Biology. 21 (4): 501–511. doi:10.1002/ajhb.20943. ISSN 1042-0533. PMID 19408251.
  52. ↑ Whiten, A.; Hinde, R. A.; Laland, K. N.; Stringer, C. B. (28 February 2011). "Culture evolves". Philosophical Transactions of the Royal Society B: Biological Sciences. 366 (1567): 938–948. doi:10.1098/rstb.2010.0372. PMC 3049105. PMID 21357216.
  53. ↑ Rendell, Luke; Fogarty, Laurel; Hoppitt, William J.E.; Morgan, Thomas J.H.; Webster, Mike M.; Laland, Kevin N. (February 2011). "Cognitive culture: theoretical and empirical insights into social learning strategies". Trends in Cognitive Sciences. 15 (2): 68–76. doi:10.1016/j.tics.2010.12.002. PMID 21215677.
  54. ↑ Colleran, Heidi (19 April 2016). "The cultural evolution of fertility decline". Phil. Trans. R. Soc. B. 371 (1692): 20150152. doi:10.1098/rstb.2015.0152. ISSN 0962-8436. PMC 4822432. PMID 27022079.
  55. ↑ Richerson, Robert Boyd & Peter J. (1988). Culture and the evolutionary process (Pbk. ed. 1988. ed.). Chicago: University of Chicago Press. ISBN 0226069338. Search this book on
  56. ↑ Barber, Jennifer S.; Axinn, William G. (1998). "The Impact of Parental Pressure for Grandchildren on Young People's Entry into Cohabitation and Marriage". Population Studies. 52 (2): 129–144. doi:10.1080/0032472031000150336. JSTOR 2584745.
  57. ↑ Alvergne, Alexandra; Jokela, Markus; Lummaa, Virpi (29 June 2010). "Personality and reproductive success in a high-fertility human population". Proceedings of the National Academy of Sciences. 107 (26): 11745–11750. Bibcode:2010PNAS..10711745A. doi:10.1073/pnas.1001752107. ISSN 0027-8424. PMID 20538974.
  58. ↑ Munshi, Kaivan; Myaux, Jacques (1 June 2006). "Social norms and the fertility transition". Journal of Development Economics. 80 (1): 1–38. doi:10.1016/j.jdeveco.2005.01.002. ISSN 0304-3878.
  59. ↑ Gibson, Mhairi A.; Gurmu, Eshetu (8 February 2011). "Land inheritance establishes sibling competition for marriage and reproduction in rural Ethiopia". Proceedings of the National Academy of Sciences. 108 (6): 2200–2204. Bibcode:2011PNAS..108.2200G. doi:10.1073/pnas.1010241108. ISSN 0027-8424. PMID 21262826.


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