Life History Evolution
By: Daniel Fabian & Thomas Flatt
Life history theory seeks to explain how natural selection and other evolutionary forces shape organisms to optimize their survival and reproduction in the face of ecological challenges posed by the environment (Stearns 1992, Roff 1992, Stearns 2000), or as David Reznick has recently put it:
“Life history theory predicts how natural selection should shape the way organisms parcel their resources into making babies”
-Reznick 2010, p. 124
The theory does so by analyzing the evolution of fitness components, so-called life history traits, and how they interact:
- size at birth;
- growth pattern;
- age and size at maturity;
- number, size, and sex of offspring;
- age-, stage- or size-specific reproductive effort;
- age-, stage- or size-specific rates of survival;
- and lifespan.
The classical theory treats life history evolution as an optimization problem: given particular ecological factors (e.g., predators, nutrition) that affect an organism's probability of survival and reproduction, and given limiting constraints and trade-offs intrinsic to the organism, what are the optimal values and combinations of life history traits that maximize reproductive success? To find the solution to this problem we need to understand its "boundary conditions" (Stearns 2000):
- how extrinsic, environmental factors affect survival and reproduction; and
- how intrinsic connections among life history traits (trade-offs) and other constraints limit whether and how life history traits can evolve.
Once these conditions have been understood and defined, life history models can be used to answer questions such as: How small or large should an organism grow? At what age and size should it mature? How many times should it reproduce? How many offspring should it produce and what size should they be? For how long should it reproduce and how long should it live?
http://www.nature.com/scitable/knowledge/library/life-history-evolution-68245673
r-K Selection: The Development-Reproduction Trade-off
In order to maximize fitness in a predictable environment, it pays to invest resources in long-term development and long life (K selection); in a risky environment, it is better to produce as much offspring as quickly as possible (r selection).
Fitness can fundamentally be achieved by two different strategies: long life (stability) or fast reproduction (multiplication, replication). These strategies are to some degree dependent: since no organism is immortal, a minimum amount of reproduction is needed to replace the organisms that have died; yet, in order to reproduce, the system must live long enough to reach the degree of development where it is able to reproduce. On the other hand, the two strategies cannot both be maximally pursued:
the resources used for fast reproduction cannot be used for developing a system that will live long, and vice-versa. This means that all evolutionary systems are confronted with a development-reproduction trade-off: they must choose whether they invest more resources in the one or in the other.
How much a given system will invest in one strategy at the expense of the other one depends on the selective environment. In biology, this is called r-K selection:
- in an r-situation, organisms will invest in quick reproduction,
- in a K-situation they will rather invest in prolonged development and long life.
Typical examples of r-species are mice, rabbits, weeds and bacteria, which have a lot of offspring, but a short life expectancy. Examples of organisms undergoing K-selection are tortoises, elephants, people, and sequoia trees: their offspring are few but long-lived. In summary, r-selection is selection for quantity, K-selection for quality of offspring.
- Selection for many offspring is most useful in an uncertain, dangerous environment, where most offspring will die anyway, whether the parents invest much resources in their development or not. The more offspring there is, the more chances that at least one of them will survive and continue the lineage.
- Selection for prolonged development is most useful when the environment provides a stable, predictable supply of resources, without great dangers. In that case, the one most likely to survive the competition with others will be the one that has had most time to develop its strength, experience or size.
- In a uncertain environment, reproduction is basically a a lottery: you cannot predict or influence which of your offspring will survive; the only way to increase your chances that at least one of them will survive is to produce as many as possible (like you can increase your chances of winning only by buying more lottery tickets).
- In a predictable environment, on the other hand, reproduction is more like a game of chess: the best way to win is to make few but well-prepared moves, rather than quickly making a lot of moves at random. K-selection, therefore, is selection for increasing control over the environment, whereas r-selection is caused by an environment that is intrinsically difficult to control.
r-K selection: the development-reproduction trade-off
http://pespmc1.vub.ac.be/RKSELECT.html
Wikipedia - r/K Selection Theory
In ecology, r/K selection theory relates to the selection of combinations of traits in an organism that trade off between quantity and quality of offspring. The focus on either an increased quantity of offspring at the expense of individual parental investment of r-strategists, or on a reduced quantity of offspring with a corresponding increased parental investment of K-strategists, varies widely, seemingly to promote success in particular environments. The concepts of quantity or quality offspring are sometimes referred to as "cheap" or "expensive", a comment on the expendable nature of the offspring and parental commitment made. The stability of the environment can predict if many expendable offspring are made or if fewer offspring of higher quality would lead to higher reproductive success. An unstable environment would encourage the parent to make many offspring, because the likelihood of all (or the majority) of them surviving to adulthood is slim. In contrast, more stable environments allow parents to confidently invest in one offspring because they are more likely to survive to adulthood.
The terminology of r/K-selection was coined by the ecologists Robert MacArthur and E. O. Wilson in 1967 based on their work on island biogeography; although the concept of the evolution of life history strategies has a longer history (see e.g. plant strategies).
The theory was popular in the 1970s and 1980s, when it was used as a heuristic device, but lost importance in the early 1990s, when it was criticized by several empirical studies. A life-history paradigm has replaced the r/K selection paradigm, but continues to incorporate its important themes as a subset of life history theory. Some scientists now prefer to use the terms fast versus slow life history as a replacement for, respectively, r versus K reproductive strategy.
r-selection
r-selected species are those that emphasize high growth rates, typically exploit less-crowded ecological niches, and produce many offspring, each of which has a relatively low probability of surviving to adulthood (i.e., high r, low K). A typical r species is the dandelion (genus Taraxacum).
In unstable or unpredictable environments, r-selection predominates due to the ability to reproduce rapidly. There is little advantage in adaptations that permit successful competition with other organisms, because the environment is likely to change again. Among the traits that are thought to characterize r-selection are high fecundity, small body size, early maturity onset, short generation time, and the ability to disperse offspring widely.
Organisms whose life history is subject to r-selection are often referred to as r-strategists or r-selected. Organisms that exhibit r-selected traits can range from bacteria and diatoms, to insects and grasses, to various semelparous cephalopods and small mammals, particularly rodents.
K-selection
By contrast, K-selected species display traits associated with living at densities close to carrying capacity and typically are strong competitors in such crowded niches, that invest more heavily in fewer offspring, each of which has a relatively high probability of surviving to adulthood (i.e., low r, high K). In scientific literature, r-selected species are occasionally referred to as "opportunistic" whereas K-selected species are described as "equilibrium".
In stable or predictable environments, K-selection predominates as the ability to compete successfully for limited resources is crucial and populations of K-selected organisms typically are very constant in number and close to the maximum that the environment can bear (unlike r-selected populations, where population sizes can change much more rapidly).
Traits that are thought to be characteristic of K-selection include large body size, long life expectancy, and the production of fewer offspring, which often require extensive parental care until they mature. Organisms whose life history is subject to K-selection are often referred to as K-strategists or K-selected. Organisms with K-selected traits include large organisms such as elephants, humans, and whales, but also smaller long-lived organisms such as Arctic terns, parrots and eagles.
Continuous Spectrum
Although some organisms are identified as primarily r- or K-strategists, the majority of organisms do not follow this pattern. For instance, trees have traits such as longevity and strong competitiveness that characterise them as K-strategists. In reproduction, however, trees typically produce thousands of offspring and disperse them widely, traits characteristic of r-strategists.
Similarly, reptiles such as sea turtles display both r- and K-traits: although sea turtles are large organisms with long lifespans (provided they reach adulthood), they produce large numbers of unnurtured offspring.
The r/K dichotomy can be re-expressed as a continuous spectrum using the economic concept of discounted future returns, with r-selection corresponding to large discount rates and K-selection corresponding to small discount rates.
https://en.wikipedia.org/wiki/R/K_selection_theory
The Adaptive Cycle - ecosystems respond to disturbance & change
The adaptive cycle, originally conceptualised by Holling (1986) interprets the dynamics of complex ecosystems in response to disturbance and change. In terms of its dynamics, the adaptive cycle has been described as moving slowly from exploitation (r) to conservation (K), maintaining and developing very rapidly from K to release (Omega), continuing rapidly to reorganisation (alpha) and back to exploitation (r). Depending on the particular configuration of the system, it can then begin a new adaptive cycle or alternatively it may transform into a new configuration, shown as an exit arrow. The adaptive cycle is one of the five heuristics used to understand social-ecological system behaviour. The other four heuristics are: resilience, panarchy, transformability, and adaptability, are of considerable conceptual appeal, and it is claimed to be generally applicable to ecological and social systems as well as to coupled social-ecological systems. Adaptability is the capacity of a social-ecological system to learn and adjust to both internal and external processes. Transformability is the capacity of a system to transform into a completely new system, when ecological, economic, or social structures make the current system unsustainable. Adaptability and transformability are prerequisites for resilience.
The two main dimensions that determine changes in an adaptive cycle are connectedness and potential. The connectedness dimension is the visual depiction of a cycle and stands for the ability to internally control its own destiny. It "reflects the strength of internal connections that mediate and regulate the influences between inside processes and the outside world" (p. 50). The potential dimension is represented by the vertical axis, and stands for the “inherent potential of a system that is available for change" (p. 393). Social or cultural potential can be characterised by the "accumulated networks of relationships-friendship, mutual respect, and trust among people and between people and institutions of governance" (p. 49). According to the adaptive cycle heuristic, the levels of both dimensions differ during the course of the cycle along the four phases. The adaptive cycle thus predicts that the four phases of the cycle can be distinguished based on distinct combinations of high or low potential and connectedness.
The notion of panarchy and adaptive cycles has become an important theoretical lens to describe the resilience of ecological systems and, more recently, social-ecological systems. Although panarchy theory originates in ecology, it has found widespread applications in other disciplines. For example, in management, Wieland (2021) describes a panarchy that represents the planetary, political-economic, and supply chain levels. Hereby, the panarchical understanding of the supply chain leads to a social-ecological interpretation of supply chain resilience.
https://en.wikipedia.org/wiki/Socio-ecological_system#Adaptive_cycle
Is r/K selection theory still valid? A look at the (glaring) problems
https://eco-intelligent.com/2019/08/13/is-r-k-selection-theory-still-valid-a-look-at-the-glaring-problems/
Prototypical r-/K-Selected (Fast/Slow) Species
Pol Capdevila & Roberto Salguero-Gomez Department of Zoology,
University of Oxford
Theoretical framework defining the major axes of variability of the life history strategies across the tree of life.
Introduction
The diversity of living forms on Earth is only paralleled by the heterogeneity of their life history traits, such as their longevity or growth rates, which can vary several orders of magnitude. From micro-scopic Escherichia coli to large blue whales (Balaenoptera musculus), species show a great deal of variation in numerous traits that are inexo-rably linked to their success on earth’s environ-ments. Despite such a great diversity, all living creatures experience the same demographic pro-cesses of survival, development, and reproduction.
The variation of these key demographic processes in timing, intensity, duration, and frequency defines important life history traits (e.g., age at maturity, net reproductive rate, etc.), and the combination of these life history traits results in life history strate-gies (Stearns 1992). Life history strategies ulti-mately determine the dynamics of the species, and they are the result of different evolutionary and ecological processes.
Why Is There So Much Life History Variation?
The course of evolution has sculpted a myriad of life history strategies, with planktonic organisms living for few years, while the Pando aspen clone in Utah (Populus tremuloides) can live up to 80,000 years. At first glance, one may wonder, why are all species not immortal and produce high numbers of progeny at a time? The response is the existence of “boundary condition" (sensu Stearns 1992) that constrain the available combi-nations of life history traits. These constraints can be classified as extrinsic or intrinsic.
Extrinsic life history constraints are those imposed by the surrounding environment. Such life history constraints depict whether the extrin-sic environment favors certain strategies but not others. For example, there are no strictly sessile animals on land, while this strategy is rather com-mon in aquatic animals. In this case, the environ-ment has likely enabled the evolution of sessile organisms that feed on the suspended material lying in the water column. Here, the surrounding environment not only refers to the physical one, but also the intra/interspecific interactions. For example, predation has a high influence on the life history of guppies (Poecilia reticulata) in Trinidad. Under high predation rates, guppies show higher densities, slower growth, with populations dominated by young, small individ-uals (Reznick 1982).
The intrinsic constraints to life history strate-gies, on the other hand, are related to the genetic material, as well as physiological, behavioral, and demographic traits. Evolutionary history or phy-logenetic ancestry plays a key role in determining the potential adaptations that a species has. Genetic material is transmitted from parents to descendants, and this nexus can determine the traits available to the latter ones. Heritable traits also set the limits to the evolutionary changes that can be achieved in the short term, and potentially at long term. For example, birds are more likely to have adaptations to optimize their flight than a mammal, with the exception of bats (order Chiroptera).
Intrinsic relationships between traits are com-monly referred to as trade-offs. These budgetary compromises between investing resources in one trait/biological function at the expense of others are grounded on limiting resources (Stearns 1992). There are physiological constraints to the amount of energy that an organism is able to invest in one particular trait or biological function. The linkage between traits implies that the evolu-tion of certain life history traits (e.g., high repro-ductive output) will have implications for others (e.g., adult survival). Thus, the fitness benefit through increasing a given trait must be balanced against the fitness cost of decreasing another trait. Overall, this means that not all life history com-ponents can be maximized simultaneously.
Life History Theory
The fascination for the vast diversity of living forms on earth has captivated many biologists. The quest of these scientists to reveal the causes and consequences of the variation in the life his-tory strategies of species across the tree of life gave birth to the disciplines of evolutionary ecol-ogy and life history theory. Historically, life his-tory evolution has been approached from the lens of problem optimization. That is, species are selected to evolve the life history strategy or strat-egies that maximize their fitness according to their evolutionary history and their surrounding envi-ronment. However, infinite combinations of strat-egies cannot evolve. This is, partly, due to the fact that life history traits covary, and it is possible to define major axes of life history variation. Thus, a given pool of traits characterizing different demo-graphic processes can be reduced to fewer n dimensions along which species can be classified.
There have been several attempts to unveil the major axis of life history variation. Pioneer Robert MacArthur proposed that species could be classi-fied as organisms, type A or type B, in a similar way to the chemistry’s periodic table of elements (MacArthur 1972). That is, to order species according to a set of life history attributes, as the chemical elements are classified by a combination of their atomic number (protons), configuration of electrons and certain chemical properties. Later on, Eric Pianka formalized the concept as “peri-odic table of ecological niches” (Pianka 1970), a scheme that organized species or organisms based on their similarity, as defined by a set of functional traits associated with various niche dimensions. During the consolidation of life history as an ecological discipline, the classification of life his-tories diverged into several schools, including plant scientists, animal scientists, and bacteriolo-gists. Here we provide a subset of the main frame-works with relevant contributions to the development of life history theory.
r-K Strategies
One of the first attempts to classify species according to their life history strategies was the r-K strategies framework by Pianka (1970). In his seminal paper “On r and K-selection,” Pianka suggested classifying organisms along a contin-uum of strategies with two extremes. The r-endpoint represents the extreme where species are highly reproductive, reproduce early in life, and have rapid development and small body sizes. On the other hand, at the K-endpoint, species are less reproductive, with late reproductive maturity and have slow development and large body sizes. For example, he suggested that vertebrates were K-selected species, while most insects were r-selected.
Pianka also developed the concept of r-K selec-tion, relating species life history strategies with envi-ronmental conditions. This theory predicts that fluctuating environments with high environmental stochasticity and no density-dependence or limited competition (reduced population size), favor those species with traits maximizing productivity (here population growth, r), r-strategies. In contrast, under conditions of high competition and density-dependence but with more environmental stability, species with traits that were more efficient in the use of resources and maximize the equilibrium popula-tion size were favored (K, carrying capacity), K-strategies. This principle was then linked to eco-logical succession. After a major disturbance, eco-systems experience a release of competition and new resources are available. Species colonizing such habitats will be favored when they have high values of r-traits. The “rapid” colonization of the habitat would be followed by its own saturation, increasing the number of individuals and then the competition. Under such saturated conditions, organisms that are more competitive at extracting energy from the habitat would then be favored. That is, phenotypes with a high r will be selectively favored at low densities/high resource conditions; while those with a high K at high densities/low resource conditions.
The dichotomous classification of species being either r- or K-selected gained both adepts and detractors. Perhaps one of the most insidious criticisms was provided by Stearns in extensive reviews about the life history theory (1992). One of his main critiques was that the r-K dichotomy did not provide an explanation for the underlying demographic mechanisms regulating populations. The lack of mechanistic explanations was indeed especially concerning, since different life cycle stages (e.g., young vs. adult) typically suffer dif-ferently the consequences of density-dependence. These, among other major flaws, caused a loss of popularity for the r-K paradigm. However, not much time elapsed till the empty niche was filled with newer life history frameworks.
Extending the r-K Dichotomy: The Fast–Slow Continuum
Following his critical essay to the r-K dichotomy, Stearns proposed a new life history framework (Stearns 1992). By empirically analyzing a set of life history traits from different mammal species, he showed that both body size and phylogeny had significant influences on life history strategies. In his framework, Stearns states that life history strat-egies vary according to how species invest energy in maintenance, development, and/or reproduction. Accordingly, organisms may range between being fast, highly-reproductive but short-lived, to slow, long-lived, and rarely successful at recruiting. This axis of life history variation empirically evidenced an already known life history paradigm, the exis-tence of a trade-off between survival and reproduc-tion. The coined fast–slow continuum, opposed to the r-K framework, included the influence of body size and phylogenetic relationships on life histories (Stearns 1992). Importantly, this continuum also accounted for physiological limitations and trade-offs, a missing block in Pianka’s life history tenet.
The fast–slow continuum still has several lim-itations that remain to be resolved. First, the underlying ecological factors determining life his-tory variation are still unclear. Besides, a rather controversial fact with the fast–slow continuum is that it only accounts for barely half of the life history variation. This flaw was indeed pointed in some early seminal works (e.g., Gaillard et al. 1989), which identified an important second axis related to reproductive traits in birds explaining additional rates of variation. His work suggested that species could be fast or slow in different ways, revealing that more axes of variation may be needed to fully capture the life history of species.
Beyond Dichotomies: The Fast–Slow and Reproductive Strategies
Despite the usefulness of the aforementioned frame-works, these classifications of life history strategies were limited in geographic, taxonomic, and phylo-genetic scales and in the ability to differentiate life history trade-offs. However, these major drawbacks are currently being overcome with the growing body of demographic data. Salguero-Gómez (2017) recently analyzed the demographic trade-offs of 650 vascular plant species across biomes and accounting for the phylogenetic relationship of the species included. He identified two major dimen-sions of demographic variation: the well-established fast–slow continuum and a novel reproductive strat-egy dimension. The main achievement of this framework is that it reconciles the life history frame-works only focused on one single life history axes of variation, such as the r-K or the fast–slow, with those begging for a “beyond K” axis of variation (Stearns 1992; Southwood 1988; Gaillard et al. 1989).
Another novelty of this framework is that it trans-gresses different ecological scales (Salguero-Gómez 2017) and kingdoms (Paniw et al. 2018). Because of the demographic basis of the fast–slow and repro-ductive strategies, and thus based in allocation strat-egies, this framework linked the population level demographic rates with the functional traits that constrain individual performance and fitness. That is, this framework shows connections between the position of species in the fast–slow and reproductive strategies to species’ functional traits (the leaf eco-nomics spectrum), biogeographical characteristics, to their rates of senescence and to their conservation status (Salguero-Gómez 2017). This establishes a nexus between the demographic trade-offs and the “real-world.”
Conclusions
Unlike other scientific disciplines like physics or chemistry, few universal laws have been formulated transcending all hierarchical levels in biology. MacArthur’s vision of a life history periodic table pointed the direction towards which a substantial fraction of life history theory has developed during the last decades. Despite the flaws of the r-K selec-tion schema, this framework triggered the develop-ment of many different and complex life history tenets. Still, life history theory has only scratched the surface of what a “periodic table of life histories” framework may offer to subdisciplines like ecology, evolution, or conservation science. Life history the-ory should aim to provide a better understanding about the complex imbrications within different scales of biological organization. How can inter-and intraspecific variation in traits can be incorpo-rated in such a periodic table? How do life history strategies determine the behavior of individuals? Are there other important axes of life history trait variation? How can we link the position within the periodic table to species’ responses to climate change? Despite all of the challenges that remain ahead, MacArthur's dream is still pursued by many scientists, aided by the increasing availability of high resolution demographic data across the tree of life.
References
Gaillard, J. M., Pontier, D., Allaine, D., Lebreton, J. D., Trouvilliez, J., & Clobert, J. (1989). An analysis of demographic tactics in birds and mammals. Oikos, 56(1), 59–76.
MacArthur, R. H. (1972). Coexistence of species. In J. A. Behnke (Ed.), Challenging biological problems (pp. 253–259). New York: Oxford University Press.
Paniw, M., Ozgul, A., & Salguero-Gómez, R. (2018). Interactive life-history traits predict sensitivity of plants and animals to temporal autocorrelation. Ecology Let-ters, 21(2), 275–286.
Pianka, E. R. (1970). On r-and K-selection. The American Naturalist, 104(940), 592–597.
Reznick, D. (1982). The impact of predation on life history evolution in trinidadian guppies: Genetic basis of observed life history patterns. Evolution, 36(6), 1236–1250.
Salguero-Gómez, R. (2017). Applications of the fast–slow continuum and reproductive strategy framework of plant life histories. New Phytologist, 213(4), 1618–1624.
Southwood, T. R. E. (1988). Tactics, strategies and tem-plates. Oikos, 52(1), 3–18.
Stearns, S. C. (1992). The evolution of life histories.
Oxford: Oxford University Press.
https://www.researchgate.net/publication/332442220_Prototypical_r-K-Selected_FastSlow_Species
(testing the idea that "the near and the far" might fit in somehow with "the fast and the slow" -maybe not)
"Another possibility is that what we're seeing here are the limitations of intuitive human morality; that we evolved in a world in which we didn't deal with people on the other side of the world—the world was our group. We're the good guys. They're the bad guys. The people on the other side of the hill—they're the competition. We have heartstrings that you can tug, but you can't tug them from very far away. There's not necessarily a moral reason why we're like this, it's a tribal reason. We're designed to be good to the people within our group to solve the tragedy of the commons, but we're not designed for the tragedy of common sense morality. We're not designed to find a good solution between our well-being and their well-being. We're really about me and about us, but we're not so much about them..."
"...Another, in my view, more plausible possibility is that we're seeing the limitations of our moral instincts. That, again, our moral heart strings, so to speak, were designed to be tugged, but not from very far away. But it's not for a moral reason. It's not because it's good for us to be that way. It's because caring about ourselves and our small little tribal group helped us survive, and caring about the other groups—the competition—didn't help us survive. If anything, we should have negative attitudes towards them. We're competing with them for resources..."
Moral Tribes - Joshua Greene
https://immortalista.blogspot.com/2022/08/moral-tribes-greene.html
The Trivers-Willard Hypothesis
In evolutionary biology and evolutionary psychology, the Trivers–Willard hypothesis, formally proposed by Robert Trivers and Dan Willard in 1973, suggests that female mammals adjust the sex ratio of offspring in response to maternal condition, so as to maximize their reproductive success (fitness). For example, it may predict greater parental investment in males by parents in "good conditions" and greater investment in females by parents in "poor conditions" (relative to parents in good conditions). The reasoning for this prediction is as follows: Assume that parents have information on the sex of their offspring and can influence their survival differentially. While selection pressures exist to maintain a sex ratio of 50, evolution will favor local deviations from this if one sex has a likely greater reproductive payoff than is usual.
https://en.wikipedia.org/wiki/Trivers%E2%80%93Willard_hypothesis
Live Fast, Die Young
https://www.amazon.com/Broken-Ladder-Inequality-Affects-Think/dp/0525429816
Imagine you are an early human dwelling in the African grasslands. If you are a man, you spend your days hunting and fishing. If your band is in conflict with another band, you are constantly on the watch for enemies, because a raid might happen at any moment. If you are a woman, you are busy gathering fruits and nuts, as your parents did and their parents before them. If you are a young adult, you spend a fair amount of time flirting with other young adults and spreading the gossip that inevitably makes the rounds in a small band where everyone knows everyone else. Given these conditions, how should you best spend your time and energy?
When we think about that question, we naturally consider what would make us the happiest. But from an evolutionary perspective, we have to remember that nature does not care if we are happy. In fact, nature does not care if we pass on our genes or not. It has no vested interest in whether your family line dies out, or if the whole human species goes extinct. Nature does not advocate for any particular outcome or any particular individual or group. Nature is simply whatever happens.
Still, nature is not merely random, because some behaviors do result in more copies of genes being passed on to future generations than others. Such successful behaviors will tend to be more common in future generations. The rhythm of this creative destruction creates exquisite patterns across the waves of evolutionary time. So to understand human nature from an evolutionary perspective, we have to understand what kinds of behaviors pass on more genes, and in what kinds of environments.
From an evolutionary standpoint, there are only two ways to expend resources that matter: survival and reproduction. Every organism faces a trade-off when it comes to how to invest energy (that is, cellular and metabolic energy, not effort and concentration). On the one hand, it can devote lots of energy to keeping itself alive. To do so, it might build muscle for strength and the immune system for maintaining health. On the other hand, it can allocate its energy to reproduction, creating eggs and sperm and the whole system of hormones and the sexy adult bodies that get eggs and sperm introduced to each other. Of course, we don’t control that trade-off with conscious choices. But various physiological systems in our bodies are constantly regulating how much energy we are spending on these various construction projects (as we will see in more detail in the chapter on stress and health).
Which investment—the survival of our bodies or the creation of new ones—offers the best chance to pass along one’s genes? It depends. Among other things, it depends on whether times are good or bad. When times are prosperous and the future looks secure, it is a sign that you are likely to live a long and healthy life.You will leave more descendants if you bide your time and wait to have children until you are really ready to support them well. You should devote everything you can to extensive parenting to make sure that they survive to reproduce themselves, and maybe you can even help raise your grandchildren.
When times are hard, the future is uncertain, and enemies are lurking behind every patch of grass, the odds favor an entirely different approach. You might not live long enough to have children later. Under those conditions, it pays to reproduce early and often. If you are going to reproduce at all, the best bet is to do so as soon as possible. The first approach is what evolutionary biologists call a “slow strategy” of investing for the future. The second is a “fast strategy,” as in, “live fast, die young.”
Of course, early Homo sapiens did not adopt a conscious strategy about how to maximize their genetic fitness. In our early history, however, those who took the fast approach when times were difficult and the slow approach when times were favorable left more descendants than those who were less responsive to the environment. As a result, there were more people in the next generation inclined to toggle between fast strategies in hard times and slow strategies in good ones. Now, so many generations later, we are the descendants of ancestors who were very, very good at adopting these tactics.
Biologists have known for decades that animals adapt to changes in their environments by shifting along the fast-slow continuum. They observed, for example, that butterflies that lived in locations that had a lot of predators would reproduce earlier, devoting less metabolic energy to growth and more to reproduction. The same species in a location with few predators would live longer and would therefore take the opposite approach, starting reproduction later. The definitive evidence came, however, when scientists started doing experiments in the lab to ensure that it really was the dangerous conditions that caused the adaptations.
In one study biologists bred a population of about eight hundred fruit flies from ten “Adams” and ten “Eves.” Then they divided them up into two genetically identical groups. One was fortunate enough to be in the Safe group, which lived out its days eating, reproducing, and doing whatever fruit flies do for fun. The other group was not as lucky. Twice a week 90 percent of this Die Young group was killed and replaced with new flies. The researchers continued this process for four years.
Reading the scientific report of this experiment is unnerving. You can’t help but imagine the situation from the perspective of the flies, finding yourself in this sci-fi nightmare in which some crazed giants in lab coats keep “disappearing” everyone you know. The experimental condition is euphemistically described as the “HAM [high adult mortality] treatment,” and mortality rate is precisely quantified: “The probability of surviving 1 week as an adult was P = 0.01.”
Despite its violence, the study reported important results. The flies in the Die Young group started reproducing at an earlier age, and they laid more eggs per female than those in the Safe group. This is just the effect predicted by the live fast, die young theory. It was not that the flies looked around, decided it was getting dangerous, and made a decision to start a family sooner. The flies that were able to reproduce early simply left more descendants in future generations.
In 1991 psychologist Jay Belsky and colleagues made an argument, based on the evolutionary fast-slow trade-off, that women raised in harsh, stressful, or chaotic environments would be more likely to have children earlier. There was not much data available, however, to test his theory at the time. A few years later, psychologists Margo Wilson and Martin Daly took up the challenge by studying birth and death rates in Chicago. Chicago is a city of neighborhoods. You might start in Lincoln Park, with its leafy streets, wrought-iron streetlamps, and redbrick brownstones. If you travel south to Englewood, with its barren concrete, windowless buildings, and sidewalks strewn with broken glass, you would be forgiven for thinking that in twelve short miles you had crossed some invisible border into another country. In some ways, you have.
Wilson and Daly looked at the average age at which women had their first child in each of Chicago’s neighborhoods. As predicted, women gave birth earlier in poorer areas. They then correlated the age at first birth with life expectancies in each neighborhood, because from an evolutionary perspective it is life expectancy that is the most important source of pressure for reproducing earlier. The correlation was strikingly large, almost a one-to-one correspondence: As life expectancy decreased, so did the women’s age when they started having children. Just as the live fast, die young theory predicts, when people die young, they give birth sooner.
In the years since that groundbreaking research, dozens of studies have confirmed Wilson and Daly’s results. Women brought up in poor or dangerous environments have children earlier. They also have more children, on average, which is another way to increase the chances of passing on genes.
The theory proposed by Belsky therefore seems to have been borne out by the data. But Belsky had not only predicted earlier births. He went further, arguing that the “strategy” for women raised in adversity to have children earlier and more frequently was not simply a choice. Rather, it was a response to the amount of certainty or uncertainty in their environment, which should affect the way they related to the world and to other people, both mentally and physically. Belsky had predicted that girls raised in poor, dangerous, or chaotic conditions would actually reach puberty and begin menstruating earlier than those raised in stable middle-class homes. If so, they would begin having children sooner, on average, because of their earlier maturation. This was a bolder prediction, because it suggested that home conditions not only affected people’s choices, but also their biology.
This work set off a flurry of studies in the 1990s in which researchers from many different labs tracked families for years, from the time that new babies were born through the time when they began having children of their own. If it really was the chaotic environment that caused the changes in birth rates, then the age at which girls reached puberty should be predictable even before they were born, knowing nothing about them other than their neighborhood or family situation. In study after study, Belsky’s prediction was confirmed. By the mid-2000s, it was clear that girls raised in harsh, poor, or chaotic homes reached puberty earlier than those raised in more stable homes.
These results also pushed the theory further in another way. Although the animal studies focused on death rates and birth rates, the human studies looked at a much broader range of troubles. Earlier puberty and earlier childbirth were linked not only to life expectancies, but also to poverty, to homes with an absent father, and to the degree of economic inequality in the region. Even though these sorts of hardships are not themselves lethal (at least not directly), they seemed to cue the same kinds of biological and psychological changes as high mortality rates do.
How extensive are the effects of the fast-slow trade-off among humans? Psychology experiments suggest that they are much more prevalent than anyone previously suspected, influencing people’s behaviors and decisions in ways that have nothing to do with reproduction. Some of the most important now versus later trade-offs involve money. Financial advisers tell us that if we skip our daily latte and instead save that three dollars a day, we could increase our savings by more than a thousand dollars a year. But that means facing a daily choice: How much do I want a thousand dollars in the bank at the end of the year? And how great would a latte taste right now?
The same evaluations lurk behind larger life decisions. Do I invest time and money in going to college, hoping for a higher salary in the long run, or do I takea job that guarantees an income now? Do I work at a regular job and play by the rules, even if I will probably struggle financially all my life, or do I sell drugs? If I choose drugs, I might lose everything in the long run and end up broke, in jail, or dead. But I might make a lot of money today.
Even short-term feelings of affluence or poverty can make people more or less shortsighted. Recall from the earlier chapters that subjective sensations of poverty and plenty have powerful effects, and those are usually based on how we measure ourselves against other people. Psychologist Mitch Callan and colleagues combined these two principles and predicted that when people are made to feel poor, they will become myopic, taking whatever they can get immediately and ignoring the future. When they are made to feel rich, they would take the long view.
Their study began by asking research participants a long series of probing questions about their finances, their spending habits, and even their personality traits and personal tastes. They told participants that they needed all this detailed information because their computer program was going to calculate a personalized “Comparative Discretionary Income Index.” They were informed that the computer would give them a score that indicated how much money they had compared with other people who were similar to them in age, education level, personality traits, and so on. In reality, the computer program did none of that, but merely displayed a little flashing progress bar and the words “Calculating. Please wait . . .” Then it provided random feedback to participants, telling half that they had more money than most people like them, and the other half that they had less money than other people like them.
Next, participants were asked to make some financial decisions, and were offered a series of choices that would give them either smaller rewards received sooner or larger rewards received later. For example, they might be asked, “Would you rather have $100 today or $120 next week? How about $100 today or $150 next week?” After they answered many such questions, the researchers could calculate how much value participants placed on immediate rewards, and how much they were willing to wait for a better long-term payoff.
The study found that, when people felt poor, they tilted to the fast end of the fast-slow trade-off, preferring immediate gratification. But when they felt relatively rich, they took the long view. To underscore the point that this was not simply some abstract decision without consequences in the real world, the researchers performed the study again with a second group of participants. This time, instead of hypothetical choices, the participants were given twenty dollars and offered the chance to gamble with it. They could decline, pocket the money, and go home, or they could play a card game against the computer and take their chances, in which case they either would lose everything or might make much more money. When participants were made to feel relatively rich, 60 percent chose to gamble. When they were made to feel poor, the number rose to 88 percent. Feeling poor made people more willing to roll the dice.
The astonishing thing about these experiments was that it did not take an entire childhood spent in poverty or affluence to change people’s level of shortsightedness. Even the mere subjective feeling of being less well-off than others was sufficient to trigger the live fast, die young approach to life...
Notes;
bred a population of about eight hundred fruit flies: S. C. Stearns, M. Ackermann, M. Doebeli, and M. Kaiser, “Experimental Evolution of Aging, Growth, and Reproduction in Fruitflies,” Proceedings of the National Academy of Sciences 97 (2000): 3309–13.
Belsky and colleagues made an argument: J. Belsky, L. Steinberg, and P. Draper, “Childhood Experience, Interpersonal Development, and Reproductive Strategy: An Evolutionary Theory of Socialization,” Child Development 62 (1991): 647–70.
Wilson and Daly looked at the average age: M. Wilson and M. Daly, “Life Expectancy, Economic Inequality, Homicide, and Reproductive Timing in Chicago Neighbourhoods,” British Medical Journal 314 (1997): 1271–74.
By the mid-2000s, it was clear: M. Del Giudice, S. W. Gangestad, and H. S. Kaplan, “Life History Theory and Evolutionary Psychology,” in The Handbook of Evolutionary Psychology, D. M. Buss (ed.) (Hoboken, NJ: John Wiley and Sons, 2015).
predicted that when people are made to feel poor: M. J. Callan, N. W. Shead, and J. M. Olson, “Personal Relative Deprivation, Delay Discounting, and Gambling,” Journal of Personality and Social Psychology 101 (2011): 955–73.
Cartar was studying the feeding habits of wild bumblebees: R. V. Cartar, “A Test of Risk-Sensitive Foraging in Wild Bumble Bees,” Ecology 72 (1991): 888–95.
To test whether inequality actually increases risk taking: B. K. Payne, J. L. Brown-Iannuzzi, and J. W. Hannay, “Inequality Increases Risk Taking,” Working Paper, 2016.
risky googling tracks real-life risky behavior: B. K. Payne, J. L. Brown-Iannuzzi, and J. W. Hannay, “Income Inequality, Risk Taking, and Social Outcomes,” Working Paper, 2016.
The Broken Ladder: How Inequality Affects the Way We Think, Live, and Die by Keith Payne https://www.amazon.com/Broken-Ladder-Inequality-Affects-Think/dp/0525429816
Life in the Fast Lane, Part II: Developing a Fast Life History Strategy
How does the fast life develop?
You gotta understand,
It's just our bringin' up-ke
That gets us out of hand.
Our mothers all are junkies,
Our fathers all are drunks.
Golly Moses, natcherly we're punks!
Some people live the fast life and some people live a slower life. The constellation of traits and behaviors that comprise the fast life (e.g., risky behaviors, high mating effort, low parental investment) may have evolved through the course of human evolution as a strategy to enhance reproductive fitness in dangerous and unstable environments (see Part I, Evolution of the Fast Life).
Every single human is born with a packet of the total human genome. The mating strategies people use in their lives are heavily influenced by the unique genetic packet they inherited from their personal lineage (dating back to their earliest ancestors at the dawn of human evolution) interacting with their immediate environment. The complex interplay between genes, neighborhood influences (peers, general climate), and family support that contributes to the development of an individual's life history strategy is fascinating and highly nuanced. Let's start with the genes.
Nature
What's the evidence showing that the packet of traits and behaviors that make up the fast life has a genetic basis? Accessing a database that included a nationally representative sample of 309 identical twins and 333 fraternal twin pairs aged 25-74, Figueredo and colleagues (2004) analyzed 30 scales of life history traits (e.g., quality of family relationships, altruistic behaviors), medical symptoms (e.g., thyroid disease, ulcer), personality traits (e.g., neuroticism, extraversion, conscientiousness, openness to experience), and social background (e.g., financial status).
They found that all the items were moderately related to each other and formed a higher-order "K-factor" (see Part I, Evolution of the Fast Life). Individuals scoring higher on the K-factor tend to live a slower life whereas those scoring lower on the K-factor tend to live a faster life. This higher-order K-factor explained most of the genetic correlations among the scales, was 68% heritable and accounted for 82% of the genetic differences among the lower-order factors. According to the researchers, these results suggest that "Life History Strategy might be heavily influenced by regulatory genes that coordinate the expression of an entire array of life history traits."
Regulatory genes don't just activate themselves, however. They require environmental triggers or else they won't be expressed. What are the important environmental triggers?
Harsh and Unpredictable Environments
Both environmental harshness ("self-reported exposure to violence from conspecifics") and unpredictability ("frequent changes or ongoing inconsistency in several dimensions of childhood environments") independently explained a large part of the variation in a K-factor consisting of an intertwined number of life history traits such as mental and physical health, relationship stability, sexual restrictiveness, social deviance, and economic success. Life history traits in adolescence were fairly stable across time and were significantly related to life history strategy in young adults. According to the researchers,
"...by the time people reach their mid-twenties, they have formed a coherent life history strategy that is characterized by their overall health, approach to romantic and sexual partners, and the amount of effort they have put into education and employment."
While it is clear what it means to live in a harsh environment (exposure to mortality and violence has a clear definition), it's not so obvious what the specific unpredictable elements of the environment are that most strongly influence the development of an individual's life history strategy. A number of important studies in the past 20 years or so have looked to the early family environment for clues.
Family
A child's home environment can play a significant role in an individual's life history strategy. While it is certainly true that human parental investment is extremely high compared to other species (Flinn & Ward, 2005), there are many circumstances in which children are raised in unpredictable family environments with little parental care. Various studies, including those that have controlled for the effects of genetic transmission, show that stressful parent-child relations and negative parenting have a significant effect on pubertal timing. This effect seems to be strongest for girls, although family stress can accelerate adrenarche in males as well (see Belsky et al., 2007; Ellis & Essex, 2007; Tither & Ellis, 2008).
There is also research on the effects of total parental absence on the development of life history strategy. Since father absence is more common than mother absence, and shows higher cultural variability (there are "father-absent" and "father-present" societies but no consistent "mother-absent" societies), a particularly active area of investigation is the consequences of father absence on the development of an individual's life history strategy.
In general, when father's don't invest in parental care, there is a tendency for boys to live the fast life- increased delinquency, aggression, and other indicators of high mating effort (Figueredo, Brumbach, Jones, Sefcek, Vasquez, & Jacobs, 2008). Since it easier to osberve a clear-cut landmark of sexual maturation in girls (e.g., age of first menstrual cycle), there is considerably more research on the effect of father absence on girls. Women also tend to remember the age of their first menstrual cycle which allows for retrospective studies.
In an important review of the literature, Ellis (2004) presents evidence that girls who grow up in a home where the father is absent or negligent in their parenting are more likely to go through their first menstrual cycle (i.e., "menarche") by the age of 12 compared to their peers. In fact, the age in which "father-absent girls" tend to go through menarche is related to the number of years of father absence, the amount of time fathers spent taking care of daughters during the first five years of life, and the amount of affection observed in parent-child relationships.
The behavioral and psychological correlates of having a father absent for girls run far and wide, tending to trigger traits and behaviors typical of the fast life such as rapid sexual development, increased fertility, lower adult attachment to romantic partners, greater levels of manipulative and exploitative attitudes, less parental care devoted to one's offspring, greater risk-taking behavior, higher incidence of affective disorders, social aggression, sexual promiscuity, and preference for sexual variety.
Framing the effects of parental absence on life history strategy in an evolutionary context, Belsky et al. (1991) and Chisholm (1993) argue that children in the first few years of life use their level of attachment security as a cue of risk and uncertainty, and this then influences the development of their reproductive strategy. A safe and predictable environment (neighborhood, social, and parental) will trigger a slower reproductive strategy, with a focus on later reproduction and high parenting effort. A dangerous and uncertain environment, on the other hand, will trigger the fast life, involving earlier reproduction, higher mating effort, and less parental investment. According to evolutionary logic (a strictly genes-eye perspective), if a girl's father doesn't invest in her care, then maybe other males will act just the same and therefore it is evolutionarily adaptive to not count on men as long-term providers and instead employ a short-term mating strategy.
The Dynamic Interplay Between Nature and Nurture
The complex, dynamic interplay between nature and nurture is mutually reinforcing. People's genes, which are partially shared with their parents, may influence to a certain extent what aspects of the environment they engage in, and those environments can in turn trigger and reinforce the expression of those genes. This can be unfortunate in situations where, for example, the genes that predispose someone to living the fast life causes that person to take dangerous risks that make his or her environment even more dangerous, causing a dangerous cycle. Therefore, when looking at the development of life history strategy, neither the environment nor genetic makeup can be viewed in total isolation from each other.
For instance, if the father's absence is due to accidental death, and therefore his absence doesn't reflect common genes between father and daughter, the daughter's chances of living the fast life are much lower than if the father's absence is due do divorce or abandonment (Khron & Bogan, 2001). In other research, Comings et al. (2002) found that a variant X-linked androgen receptor gene tends to predispose both fathers to absence from their children and daughters to living the fast life (but see Jorn et al., 2004 where this finding wasn't replicated). The effects of early environment must take into account the influence of genes in common between the child and parent
Fascinating epigenetic research looking at genotype-by-environment (GxE) interactions also suggest that not all people are equally influenced by environmental conditions. Some girls and boys are more reactive to stressful early environments than others because they are biologically prepared to be reactive to such environmental triggers. Infants and toddlers with a highly reactive and negatively emotional temperament tend to be more affected by parenting than other children, as do children carrying a particular dopamine receptor D4 allelle or alleles associated with low MAOA activity (Bradley & Corwyn, 2008; Bakermans-Kraneburg & Van IJzendoorn, 2006; Caspi et al., 2002). Nurturing and supportive family environments seem to have more of a positive effect on these children, and they also seem to be more negatively affected by harsh and unsupportive environments. In a very recent study, Barry, Kochanska and Philibert (in press) looked at attachment security in infants and found that infants with one or two short alleles on the serotonin transporter gene (5-HTT) were, unsurprisingly, affected by maternal sensitivity (low sensitivity led to attachment insecurity), but interestingly virtually all those carrying two long alleles became securely attached irrespective of the quality of care experienced.
Revisions of Belsky et al.'s (1991) and Chisholm's (1993) models acknowledge these important genetic effects by putting genes back into the picture. Belsky (2005) argues that while an early unpredictable family environment may have an effect on the development of an individual's life history strategy, not all daughters are equally prone to the fast life after living in unpredictable home environments. This certainly doesn't mean though that all people can't use a wide range of cues to adjust their life history strategy.
The mutually reenforcing pattern of nature and nurture assures that neither the genes nor the environment alone are destiny (see Straight Talk about Twin Studies, Genes, and Parenting: What Makes Us Who We Are). Just because your life history strategy at a certain age is rather stable does not mean you can't change your strategy (if you so desire); life history strategies are extremely plastic and highly sensitive to environmental triggers (although this doesn't mean change is necessarily going to be easy). Change the triggers, and you increase the chances that you will change the pattern of gene activations. Evolution "designed" humans to be highly sensitive to environmental cues and built in a great deal of plasticity into the human genome. Such plasticity would be more adaptive than rigidly "hard-wiring" at birth a person's life history strategy or allowing the environment to exert complete control. As Figueredo and colleagues (2005) explain,
"Natural and sexual selection would presumably favor enough developmental plasticity in the control of Life History Strategy to respond to an array of adaptive contingencies that were reliably present in human evolutionary history. Our results are consistent with this assertion, indicating that a substantial portion of the variation in life history traits remains under environmental control."
Also, these are all imperfect correlations. Not everyone with the fast life genes who are raised in harsh and unpredictable environments will start living the fast lifestyle. And not everyone living the fast lifestyle necessarily has the fast life genes or even were raised under harsh and unpredictable conditions. We are only talking probabilities.
The seductive allure of the fast life
Prior research had demonstrated a link between early environment and life history traits. For instance, there is research showing a link between a youths' exposure to violence and their chances of cigarette smoking (Fick & Thomas, 1995), a link between the age of first sexual intercourse in adolescence and growing up in a low socioeconomic neighborhood (Browning et al., 2005), and a relation between maternal stress and distress and life history strategy development in boys (Barry, Dunlap, Cotten, & Lochman, 2005).
The life history strategy perspective, however, places these findings in a solid evolutionary framework and delineates the specific conditions that increase the probability of living the fast life. It's not just general stress in the neighborhood or just any aspect of the home environment that influences how a person's life history strategy develops, but particularly an interaction of a person's genes with an unpredictable environment high in mortality risks that primarily influences whether he or she, by their mid 20's, is likely to develop a fast or slower life history.
The fact that such a wide array of behaviors are linked together, are substantially under genetic control, and can be activated by particular life circumstances screams in high, Rock N' Roll fidelity, for an evolutionary explanation (see Part I, Evolution of the Fast Life). Life History Theory, derived from evolutionary principles, provides just that explanation and predicts that "family structure, sexual behavior, social behavior, and personality will be interrelated to produce an overarching life history strategy." For those with a specific constellation of genes living under harsh and unpredictable environmental conditions, the fast life may be particularly alluring.
Other Parts of the Series
Part I, Evolution of the Fast Life
Part III, Romantic Attachment in the Fast Lane
Part IV, Rebelliousness, Risk, Social Deviance, and Educational Intervention
Part V, Social Class and Public Policy
Part VI: Consilience, Pop Culture, and Modern Living
© 2010 by Scott Barry Kaufman http://www.psychologytoday.com/blog/beautiful-minds/201008/life-in-the-fast-lane-part-ii-developing-fast-life-history-strategy
