CHAPTER OVERVIEW 8: Life Histories Learning Objectives Describe life history theory, the traits typically associated with the study of life histories. Explain the role of trade-offs and the principle of allocation in shaping life history traits. Explain correlated life history patterns we often observe across species (e.g., the concepts of r- versus K-selection), and conditions that could favor different life history strategies. Describe why organisms experience senescence, and compare and contrast hypotheses of aging. 8.1: What is life history? 8.2: Semelparity versus Iteroparity 8.3: Life History Evolution 8.4: The Evolution of Aging Summary A species' life history describes the series of events over its lifetime, such as how resources are allocated for growth, maintenance, and reproduction. Life history traits affect the life table of an organism. A species' life history is genetically determined and shaped by the environment and natural selection. Studying life histories can help us understand larger evolutionary questions, like why does biological aging, a deleterious reduction in fecundity and survival, exist? 8: Life Histories is shared under a CC BY-NC-SA license and was authored, remixed, and/or curated by LibreTexts.
8.1: What is life history? Life history theory Life history theory is an analytical framework designed to study the diversity of life history strategies used by different organisms throughout the world, as well as the causes and results of the variation in their life cycles (Vitzthum, 2008; Flatt & Heyland, 2011). It is a theory of biological evolution that seeks to explain aspects of organisms' anatomy and behavior by reference to the way that their life histories--including their reproductive development and behaviors, post-reproductive behaviors, and life span (length of time alive)--have been shaped by natural selection. A life history strategy is the "age- and stage-specific patterns" and timing of events that make up an organism's life, such as birth, weaning, maturation, death, etc (Flatt & Heyland, 2011; Ahlström, 2011). These events, notably juvenile development, age of sexual maturity, first reproduction, number of offspring and level of parental investment, senescence and death, depend on the physical and ecological environment of the organism. The theory was developed in the 1950s and is used to answer questions about topics such as organism size, age of maturation, number of offspring, life span, and many others (Stearns, 1992; Hochberg, 2011). In order to study these topics, life history strategies must be identified, and then models are constructed to study their effects. Finally, predictions about the importance and role of the strategies are made, and these predictions are used to understand how evolution affects the ordering and length of life history events in an organism's life, particularly the life span and period of reproduction (Stearns, 1976; Hill & Kaplan, 1999). Life history theory draws on an evolutionary foundation, and studies the effects of natural selection on organisms, both throughout their lifetime and across generations (Bolger, 2012). It also uses measures of evolutionary fitness to determine if organisms are able to maximize or optimize this fitness, by allocating resources to a range of different demands throughout the organism's life (Preston et al., 2014; Vitzthum, 2008). It serves as a method to investigate further the "many layers of complexity of organisms and their worlds" (Morbeck et al., 1997). Organisms have evolved a great variety of life histories, from Pacific salmon, which produce thousands of eggs at one time and then die, to human beings, who produce a few offspring over the course of decades. The theory depends on principles of evolutionary biology and ecology and is widely used in other areas of science.
Figure : A swallowtail butterfly hatches from a chrysalis. Source: Pixabay.
Life cycle All organisms follow a specific sequence in their development, beginning with gestation and ending with death, which is known as the life cycle (Preston et al., 2014). Events in between usually include birth, childhood, maturation, reproduction, and senescence, and together these comprise the life history strategy of that organism (Ahlström, 2011). The major events in this life cycle are usually shaped by the demographic qualities of the organism (Flatt & Heyland, 2011). Some are more obvious shifts than others, and may be marked by physical changes--for example, teeth erupting in young children (Bolger, 2012). Some events may have little variation between individuals in a species, such as length of gestation, but other events may show a lot of variation between individuals, such as age at first reproduction. Life cycles can be divided into two major stages: growth and reproduction (Ahlström, 2011). These two cannot take place at the same time, so once reproduction has begun, growth usually ends (Preston et al.,
2014). This shift is important because it can also affect other aspects of an organism's life, such as the organization of its group or its social interactions (Bolger, 2012). Each species has its own pattern and timing for these events, often known as its ontogeny, and the variety produced by this is what life history theory addresses (Hawkes, 2006). Evolution then works upon these stages to ensure that an organism adapts to its environment (Hochberg, 2011). For example, a human, between being born and reaching adulthood, will pass through an assortment of life stages, which include: birth, infancy, weaning, childhood and growth, adolescence, sexual maturation, and reproduction (Ahlström, 2011; Hawkes, 2006). All of these are defined in a specific biological way, which is not necessarily the same as the way that they are commonly used (Hawkes, 2006). In life history theory, evolution works on the life stages of particular species (e.g., length of juvenile period) but is also discussed for a single organism's functional, lifetime adaptation. In both cases, researchers assume adaptation--processes that establish fitness (Hochberg, 2011). Traits There are at least seven traits that are traditionally recognized as important in life history theory (Stearns, 1992). The trait that is seen as the most important for any given organism is the one where a change in that trait creates the most significant difference in that organism's level of fitness. In this sense, an organism's fitness is determined by its changing life history traits (Stearns, 1976). The way in which evolutionary forces act on these life history traits serves to limit the genetic variability and heritability of the life history strategies, although there are still large varieties that exist in the world (Stearns, 1992). Commonly studied life history traits: 1. size at birth 2. growth pattern 3. age and size at maturity 4. number, size, and sex ratio of offspring 5. age- and size-specific reproductive investments 6. age- and size-specific mortality schedules 7. length of life Strategies Combinations of these life history traits and life events create the life history strategies. As an example, Winemiller and Rose propose three types of life history strategies in the fish they study: opportunistic, periodic, and equilibrium (Lartillot & Delsuc, 2012). These types of strategies are defined by the body size of the fish, age at maturation, high or low survivorship, and the type of environment they are found in. A fish with a large body size, a late age of maturation, and low survivorship, found in a seasonal environment, would be classified as having a periodic life strategy (Lartillot & Delsuc, 2012). The type of behaviors taking place during life events can also define life history strategies. For example, an exploitative life history strategy would be one where an organism benefits by using more resources than others, or by taking these resources from other organisms (Reynolds & McCrea, 2016). Ecological conditions favor organisms with certain life history strategies through natural selection and evolution, rather than organisms favoring certain strategies based on ecological conditions. Characteristics Life history characteristics are traits that affect the life table of an organism, and can be imagined as various investments in growth, reproduction, and survivorship. The goal of life history theory is to understand the variation in such life history strategies. This knowledge can be used to construct models to predict what kinds of traits will be favored in different environments. Without constraints, the highest fitness would belong to a Darwinian demon, a hypothetical organism for whom such trade-offs do not exist. The key to life history theory is that there are limited resources available, and focusing on only a few life history characteristics is necessary.
Examples of some major life history characteristics include: Age at first reproductive event Reproductive life span and aging Number and size of offspring Variations in these characteristics reflect different allocations of an individual's resources (i.e., time, effort, and energy expenditure) to competing life functions. For any given individual, available resources in any particular environment are finite. Time, effort, and energy used for one purpose diminishes the time, effort, and energy available for another. For example, birds with larger broods are unable to afford more prominent secondary sexual characteristics (Gustafsson et al., 1995). Life history characteristics will, in some cases, change according to the population density, since genotypes with the highest fitness at high population densities will not have the highest fitness at low population densities (Mueller et al., 1991). Other conditions, such as the stability of the environment, will lead to selection for certain life history traits. Experiments have found that unstable environments select for flies with both shorter life spans and higher fecundity--in unreliable conditions, it is better for an organism to breed early and abundantly than waste resources promoting its own survival (Rose & Charlesworth, 1980). Trade-offs An essential component of studying life history strategies is identifying the trade-offs that take place for any given organism (University of California, Riverside, 2013). Energy use in life history strategies is regulated by thermodynamics and the conservation of energy, and the "inherent scarcity of resources", so not all traits or tasks can be invested in at the same time (Ahlström, 2011; Preston et al., 2014). Thus, organisms must choose between tasks, such as growth, reproduction, and survival, prioritizing some and not others (Preston et al., 2014). For example, there is a trade-off between maximizing body size and maximizing life span, and between maximizing offspring size and maximizing offspring number (Hochberg, 2011; Stearns, 1976). This is also sometimes seen as a choice between quantity and quality of offspring (Hill & Kaplan, 1999). These choices are the trade-offs that life history theory studies. One significant trade-off is between somatic effort (towards growth and maintenance of the body) and reproductive effort (towards producing offspring) (Hill & Kaplan, 1999; Preston et al., 2014). Since an organism cannot put energy towards doing these simultaneously, many organisms have a period where energy is put just toward growth, followed by a period where energy is focused on reproduction, creating a separation of the two in the life cycle (Ahlström, 2011). Thus, the end of the period of growth marks the beginning of the period of reproduction. Another fundamental trade-off associated with reproduction is between mating effort and parenting effort. If an organism is focused on raising its offspring, it cannot devote that energy to pursuing a mate (Preston et al., 2014). An important trade-off in the dedication of resources to breeding has to do with predation risk: organisms that have to deal with an increased risk of predation often invest less in breeding. This is because it is not worth as much to invest a lot in breeding when the benefit of such investment is uncertain (Dillon et al., 2018). These trade-offs, once identified, can then be put into models that estimate their effects on different life history strategies and answer questions about the selection pressures that exist on different life events (Hill & Kaplan, 1999). Over time, there has been a shift in how these models are constructed. Instead of focusing on one trait and looking at how it changed, scientists are looking at these trade-offs as part of a larger system, with complex inputs and outcomes (Stearns, 1976). The idea of constraints is closely linked to the idea of trade-offs discussed above. Because organisms have a finite amount of energy, the process of trade-offs acts as a natural limit on the organism's adaptations and potential for fitness. These limits can be physical, developmental, or historical, and they are imposed by the existing traits of the organism (Flatt & Heyland, 2011). Populations can adapt and thereby achieve an "optimal" life history strategy that allows the highest level of fitness possible (fitness maximization). There are several methods from which to approach the study of optimality, including energetic and demographic. Achieving optimal fitness also encompasses multiple generations, because the optimal use of energy includes both the parents and the offspring. For example, "optimal investment in offspring is where the decrease in total number of offspring is equaled by the increase of the number who survive" (Hill & Kaplan, 1999). Optimality is important for the study of life history theory because it serves as the basis for many of the models used, which work from the assumption that natural selection, as it
works on a life history traits, is moving towards the most optimal group of traits and use of energy (Stearns, 1976). This base assumption, that over the course of its life span an organism is aiming for optimal energy use, then allows scientists to test other predictions (Hill & Kaplan, 1999). However, actually gaining this optimal life history strategy cannot be guaranteed for any organism (Stearns, 1976). An organism's allocation of resources ties into several other important concepts, such as trade-offs and optimality. The best possible allocation of resources is what allows an organism to achieve an optimal life history strategy and obtain the maximum level of fitness, and making the best possible choices about how to allocate energy to various trade-offs contributes to this (Preston et al., 2014). The allocation of resources also plays a role in variation, because the different resource allocations by different species create the variety of life history strategies (Ahlström, 2011). Reproductive value and costs of reproduction Reproductive value models the trade-offs between reproduction, growth, and survivorship. An organism's reproductive value (RV) is defined as its expected contribution to the population through both current and future reproduction: (Fisher, 1930) RV = Current Reproduction + Residual Reproductive Value (RRV) The residual reproductive value represents an organism's future reproduction through its investment in growth and survivorship. The cost of reproduction hypothesis predicts that higher investment in current reproduction hinders growth and survivorship and reduces future reproduction, while investments in growth will pay off with higher fecundity (number of offspring produced) and reproductive episodes in the future (Jasienska, 2009). This cost-of-reproduction trade-off influences major life history characteristics. For example, a 2009 study by Creighton et al. on burying beetles provided support for the costs of reproduction (Creighton et al., 2009). The study found that beetles that had allocated too many resources to current reproduction also had the shortest life spans. In their lifetimes, they also had the fewest reproductive events and offspring, reflecting how over-investment in current reproduction lowers residual reproductive value. The related terminal investment hypothesis describes a shift to current reproduction with higher age. At early ages, RRV is typically high, and organisms should invest in growth to increase reproduction at a later age. As organisms age, this investment in growth gradually increases current reproduction. However, when an organism grows old and begins losing physiological function, mortality increases while fecundity decreases. This senescence shifts the reproduction trade-off towards current reproduction: the effects of aging and higher risk of death make current reproduction more favorable. The burying beetle study also supported the terminal investment hypothesis: the authors found beetles that bred later in life also had increased brood sizes, reflecting greater investment in those reproductive events (Creighton et al., 2009). r/K selection theory For more information on r/K selection see the Population Ecology chapter. The selection pressures that determine the reproductive strategy, and therefore much of the life history, of an organism can be understood in terms of r/K selection theory. The central trade-off to life history theory is the number of offspring vs. the timing of reproduction. Organisms that are r-selected have a high growth rate (r) and tend to produce a high number of offspring with minimal parental care; their life spans also tend to be shorter. r-selected organisms are suited to life in an unstable environment, because they reproduce early and abundantly and allow for a low survival rate of offspring. K-selected organisms subsist near the carrying capacity of their environment (K), produce a relatively low number of offspring over a longer span of time, and have high parental investment. They are more suited to life in a stable environment in which they can rely on a long life span and a low mortality rate that will allow them to reproduce multiple times with a high offspring survival rate (Stearns, 1977). Some organisms that are very r-selected are semelparous, only reproducing once before they die. Semelparous organisms may be short-lived, like annual crops. However, some semelparous organisms are relatively long-lived, such as the African flowering plant Lobelia telekii which spends up to several decades growing an inflorescence that blooms only once before the plant dies, or the periodical cicada which spends 17 years as a larva before emerging as an adult (Young, 1984). Organisms with longer life spans are usually iteroparous, reproducing more than once in a lifetime. However, iteroparous organisms can be more r-selected than K-
selected, such as a sparrow, which gives birth to several chicks per year but lives only a few years, as compared to a wandering albatross, which first reproduces at ten years old and breeds every other year during its 40-year life span (Ricklefs, 1977).
Figure : Typical variations seen between r- and K-selected species
: A litter of mice with their mother. The reproduction of mice follows an r-selection strategy, with many offspring, short gestation, less parental care, and a short time until sexual maturity. Source: Seweryn Olkowicz.
Unpredictable environments Many factors can determine the evolution of an organism's life history, especially the unpredictability of the environment. A very unpredictable environment--one in which resources, hazards, and competitors may fluctuate rapidly--selects for organisms that produce more offspring earlier in their lives, because it is never certain whether they will survive to reproduce again. Mortality rate may be the best indicator of a species' life history: organisms with high mortality rates--the usual result of an unpredictable environment--typically mature earlier than those species with low mortality rates, and give birth to more offspring at a time (Promislow & Harvey, 1990). A highly unpredictable environment can also lead to plasticity, in which individual organisms can shift along the spectrum of r-selected vs. K-selected life histories to suit the environment (Baird et al., 1986).
Evolution Connection: Energy Budgets, Reproductive Costs, and Sexual Selection in Drosophila Research into how animals allocate their energy resources for growth, maintenance, and reproduction has used a variety of experimental animal models. Some of this work has been done using the common fruit fly, Drosophila melanogaster. Studies have shown that not only does reproduction have a cost as far as how long male fruit flies live, but also fruit flies that have already mated several times have limited sperm remaining for reproduction. Fruit flies maximize their last chances at reproduction by selecting optimal mates. In a 1981 study, male fruit flies were placed in enclosures with either virgin or inseminated females. The males that mated with virgin females had shorter life spans than those in contact with the same number of inseminated females with which they were unable to mate. This effect occurred regardless of how large (indicative of their age) the males were. Thus, males that did not mate lived longer, allowing them more opportunities to find mates in the future. More recent studies, performed in 2006, show how males select the female with which they will mate and how this is affected by previous matings (Figure ). Males were allowed to select between smaller and larger females. Findings showed that larger females had greater fecundity, producing twice as many offspring per mating as the smaller females did. Males that had previously mated, and thus had lower supplies of sperm, were termed "resource-depleted," while males that had not mated were termed "non-resource-depleted." The study showed that although non-resource-depleted males preferentially mated with larger females, this selection of partners was more pronounced in the resource-depleted males. Thus, males with depleted sperm supplies, which were limited in the number of times that they could mate before they replenished their sperm supply, selected larger, more fecund females, thus maximizing their chances for offspring. This study was one of the first to show that the physiological state of the male affected its mating behavior in a way that clearly maximizes its use of limited reproductive resources.
Figure : Male fruit flies that had previously mated (sperm-depleted) picked larger, more fecund females more often than those that had not mated (non-sperm-depleted). This change in behavior causes an increase in the efficiency of a limited reproductive resource: sperm.
These studies demonstrate two ways in which the energy budget is a factor in reproduction. First, energy expended on mating may reduce an animal's life span, but by this time they have already reproduced, so in the context of natural selection this early death is not of much evolutionary importance. Second, when resources such as sperm (and the energy needed to replenish it) are low, an organism's behavior can change to give them the best chance of passing their genes on to the next generation. These changes in behavior, so important to evolution, are studied in a discipline known as behavioral biology, or ethology, at the interface between population biology and psychology. Adapted from Phillip G. Byrne and William R. Rice, "Evidence for adaptive male mate choice in the fruit fly Drosophila melanogaster," Proc Biol Sci. 273, no. 1589 (2006): 917-922, doi: 10.1098/rspb.2005.3372.
Human life history In studying humans, life history theory is used in many ways, including in biology, psychology, economics, anthropology, and other fields (Preston et al., 2014; Mittal et al., 2014; Schmitt & Rhode, 2013). For humans, life history strategies include all the usual factors--trade-offs, constraints, reproductive effort, etc.--but also includes a culture factor that allows them to solve problems through cultural means in addition to through adaptation (Hochberg, 2011). Humans also have unique traits that make them stand out from other organisms, such as a large brain, later maturity and age of first reproduction, a long life span, and a high level of reproduction, often supported by fathers and older (post-menopausal) relatives (Hill & Kaplan, 1999; Kaplan et al., 2000; Barton et al., 2011; Isler & van Schaik, 2012). There are a variety of possible explanations for these unique traits. For example, a long juvenile period may have been adapted to support a period of learning the skills needed for successful hunting and foraging (Hill &
Kaplan, 1999; Kaplan et al., 2000). This period of learning may also explain the longer life span, as a longer amount of time over which to use those skills makes the period needed to acquire them worth it (Bolger, 2012; Kaplan et al., 2000). Cooperative breeding and the "grandmother hypothesis" have been proposed as the reasons that humans continue to live for many years after they are no longer capable of reproducing (Hill & Kaplan, 1999; Isler & van Schaik, 2012). The large brain allows for a greater learning capacity, and the ability to engage in new behaviors and create new things (Hill & Kaplan, 1999). The change in brain size may have been the result of a dietary shift--towards higher quality and difficult to obtain food sources--or may have been driven by the social requirements of group living, which promoted sharing and provisioning (Kaplan et al., 2000; Bolger, 2012). Research has also indicated that humans may pursue different reproductive strategies (Kim & Lee, 2019; Yao et al., 2014; Vali et al., 2016). Survivorship Curves Another tool used by population ecologists is a survivorship curve, which is a graph of the number of individuals surviving at each age interval plotted versus time (usually with data compiled from a life table). These curves allow us to compare the life histories of different populations (Figure ). Humans and most primates exhibit a Type I survivorship curve because a high percentage of offspring survive their early and middle years--death occurs predominantly in older individuals. These types of species usually have small numbers of offspring at one time, and they give a high amount of parental care to them to ensure their survival. Birds are an example of an intermediate or Type II survivorship curve because birds die more or less equally at each age interval. These organisms also may have relatively few offspring and provide significant parental care. Trees, marine invertebrates, and most fishes exhibit a Type III survivorship curve because very few of these organisms survive their younger years; however, those that make it to an old age are more likely to survive for a relatively long period of time. Organisms in this category usually have a very large number of offspring, but once they are born, little parental care is provided. Thus these offspring are "on their own" and vulnerable to predation, but their sheer numbers assure the survival of enough individuals to perpetuate the species.
Figure : Survivorship curves show the distribution of individuals in a population according to age. Humans and most mammals have a Type I survivorship curve because death primarily occurs in the older years. Birds have a Type II survivorship curve, as death at any age is equally probable. Trees have a Type III survivorship curve because very few survive the younger years, but after a certain age, individuals are much more likely to survive.
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Schmitt, D., & Rhode, P. (2013). The human polygyny index and its ecological correlates: Testing sexual selection and life history theory at the cross-national level. Social Science Quarterly, 94(4), 1159-1184. Stearns, S. (1976). Life-history tactics: A review of the ideas. The Quarterly Review of Biology, 51(1), 3-47. Stearns, S. C. (1977). The evolution of life history traits: A critique of the theory and a review of the data. Annual Review of Ecology and Systematics, 8, 145-171. Stearns, S. (1992). The evolution of life histories. Oxford University Press. University of California, Riverside. (2013, December 5). Trade-offs in life history evolution. idea.ucr.edu. https://idea.ucr.edu Vall, G., Gutiérrez, F., Peri, J. M., Gárriz, M., Baillés, E., Garrido, J. M., & Obiols, J. E. (2016). Seven dimensions of personality pathology are under sexual selection in modern Spain. Evolution and Human Behavior, 37(3), 169-178. Vitzthum, V. (2008). Evolutionary models of women's reproductive functioning. Annual Review of Anthropology, 37, 53-73 Yao, S., Långström, N., Temrin, H., & Walum, H. (2014). Criminal offending as part of an alternative reproductive strategy: Investigating evolutionary hypotheses using Swedish total population data. Evolution and Human Behavior, 35(6), 481-488. Young, T. P. (1984). The comparative demography of semelparous Lobelia telekii and iteroparous Lobelia keniensis on Mount Kenya. Journal of Ecology, 72, 637-650. Contributors and Attributions Modified by Dan Wetzel (University of Pittsburgh) from the following sources: Wikipedia: https://en.wikipedia.org/wiki/Life_history_theory Connie Rye (East Mississippi Community College), Robert Wise (University of Wisconsin, Oshkosh), Vladimir Jurukovski (Suffolk County Community College), Jean DeSaix (University of North Carolina at Chapel Hill), Jung Choi (Georgia Institute of Technology), Yael Avissar (Rhode Island College) among other contributing authors. Original content by OpenStax (CC BY 4.0; Download for free at http://cnx.org/contents/185cbf87-c72...f21b5eabd@9.87). 8.1: What is life history? is shared under a CC BY-NC-SA license and was authored, remixed, and/or curated by LibreTexts. 45.2: Life Histories and Natural Selection by OpenStax is licensed CC BY 4.0.
8.2: Semelparity versus Iteroparity Semelparity versus Iteroparity Semelparity and iteroparity are two contrasting reproductive strategies available to living organisms. A species is considered semelparous if it is characterized by a single reproductive episode before death, and iteroparous if it is characterized by multiple reproductive cycles over the course of its lifetime. In truly semelparous species, death after reproduction is part of an overall strategy that includes putting all available resources into maximizing reproduction, at the expense of future life. In any iteroparous population there will be some individuals who die between their first and second reproductive episodes, but unless this is part of a syndrome of programmed death after reproduction, this would not be called semelparity. This distinction is also related to the difference between annual and perennial plants. An annual is a plant that completes its life cycle in a single season, and is usually semelparous. Perennials live for more than one season and are usually (but not always) iteroparous (Gotelli, 2008). Semelparity and iteroparity are not, strictly speaking, alternative strategies, but extremes along a continuum of possible modes of reproduction. Many organisms considered to be semelparous can, under certain conditions, separate their single bout of reproduction into two or more episodes (Futami & Akimoto, 2005; Hughes & Simons, 2014). Semelparity The word semelparity was coined by evolutionary biologist Lamont Cole, and comes from the Latin semel 'once, a single time' and pario 'to beget' (Cole, 1954). This differs from iteroparity in that iteroparous species are able to have multiple reproductive cycles and therefore can mate more than once in their lifetime. Semelparity is also known as "big bang" reproduction, since the single reproductive event of semelparous organisms is usually large as well as fatal (Ricklefs & Miller, 1999). A classic example of a semelparous organism is Pacific salmon (Oncorhynchus spp.), which lives for many years in the ocean before swimming to the freshwater stream of its birth, spawning, and dying. Other semelparous animals include many insects, including some species of butterflies, cicadas, and mayflies, many arachnids, and some molluscs such as some species of squid and octopus. Annual plants, including all grain crops and most domestic vegetables, are semelparous. Long-lived semelparous plants include century plant (agave), Lobelia telekii, and some species of bamboo.
: Many Pacific salmon, like this sockeye salmon (Oncorhynchus nerka) are semelparous and only reproduce once in their lifetime. Source: Milton Love, Marine Science Institute, available in the public domain.
This form of lifestyle is consistent with r-selected strategies as many offspring are produced and there is low parental input, as one or both parents die after mating. All of the male's energy is diverting into mating and the immune system is repressed. High levels of corticosteroids are sustained over long periods of time. This triggers immune and inflammatory system failure and gastrointestinal hemorrhage, which eventually leads to death.
Iteroparity The term iteroparity comes from the Latin itero, to repeat, and pario, to beget. An example of an iteroparous organism is a human --humans are biologically capable of having offspring many times over the course of their lives. Iteroparous vertebrates include all
birds, most reptiles, virtually all mammals, and most fish. Among invertebrates, most mollusca and many insects (for example, mosquitoes and cockroaches) are iteroparous. Most perennial plants are iteroparous.
: Most mammals, like this domestic pig are iteroparous and reproduce multiple times in their life. Source: Scott Bauer, USDA, available in the public domain.
Trade-offs Within its lifetime, an organism has a limited amount of energy/resources available to it and must always partition it among various functions such as collecting food and finding a mate. Of relevance here is the trade-off between fecundity, growth, and survivorship in its life history strategy. These trade-offs come into play in the evolution of iteroparity and semelparity. It has been repeatedly demonstrated that semelparous species produce more offspring in their single fatal reproductive episode than do closely related iteroparous species in any one of theirs. However, the opportunity to reproduce more than once in a lifetime, and possibly with greater care for the development of offspring produced, can offset this strictly numerical benefit.
Models based on non-linear trade-offs One class of models that tries to explain the differential evolution of semelparity and iteroparity examines the shape of the trade-off between offspring produced and offspring forgone (offspring that will not be produced). In economic terms, offspring produced is equivalent to a benefit function, while offspring forgone is comparable to a cost function. The reproductive effort of an organism-- the proportion of energy that it puts into reproducing, as opposed to growth or survivorship--occurs at the point where the distance between offspring produced and offspring forgone is the greatest (Figure 3).
Figure : A visual model to explain the evolution of semelparity and iteroparity based on different cost/benefit curves. In the first graph, the marginal cost of offspring produced is decreasing (each additional offspring is less "expensive" than the average of
all previous offspring) and the marginal cost of offspring forgone is increasing. In this situation, the organism only devotes a portion of its resources to reproduction, and uses the rest of its resources on growth and survivorship so that it can reproduce again in the future (Roff, 1992). However, it is also possible (second graph) for the marginal cost of offspring produced to increase, and for the marginal cost of offspring forgone to decrease. When this is the case, it is favorable for the organism to reproduce a single time. The organism devotes all of its resources to that one episode of reproduction, so it then dies. This mathematical/graphical model has found only limited quantitative support from nature. Source: Paul Moorcroft, Harvard University, licensed under CC BY-SA 3.0.
Bet-hedging models A second set of models examines the possibility that iteroparity is a hedge against unpredictable juvenile survivorship (avoiding putting all one's eggs in one basket). Again, mathematical models have not found empirical support from real-world systems. In fact, many semelparous species live in habitats characterized by high (not low) environmental unpredictability, such as deserts and early successional habitats. Cole's paradox and demographic models The models that have the strongest support from living systems are demographic. In Lamont Cole's classic 1954 paper, he came to the conclusion that: "For an annual species, the absolute gain in intrinsic population growth which could be achieved by changing to the perennial reproductive habit would be exactly equivalent to adding one individual to the average litter size," (Lamont, 1954). For example, imagine two species--an iteroparous species that has annual litters averaging three offspring each, and a semelparous species that has one litter of four, and then dies. These two species have the same rate of population growth, which suggests that even a tiny fecundity advantage of one additional offspring would favor the evolution of semelparity. This is known as Cole's paradox. In his analysis, Cole assumed that there was no mortality of individuals of the iteroparous species, even seedlings. Twenty years later, Charnov and Schaffer (1973) showed that reasonable differences in adult and juvenile mortality yield much more reasonable costs of semelparity, essentially solving Cole's paradox. An even more general demographic model was produced by Young (1981). These demographic models have been more successful than the other models when tested with real-world systems. It has been shown that semelparous species have higher expected adult mortality, making it more economical to put all reproductive effort into the first (and therefore final) reproductive episode (Young, 1990; Lesica & Young, 2005). Sources Charnov, E.L., & Schaffer, W.M. (1973). Life history consequences of natural selection: Cole's result revisited. American Naturalist, 107(958), pp. 791-793. doi:10.1086/282877. S2CID 83561052. Cole, L.C. (1954). The population consequences of life history phenomena. The Quarterly Review of Biology, 29(2), pp. 103137. doi:10.1086/400074. JSTOR 2817654. PMID 13177850. S2CID 26986186. Futami, K., & Akimoto, S. (2005). Facultative second oviposition as an adaptation to egg loss in a semelparous crab spider. Etholgy, 111(12), pp. 1126-1138. Bibcode:2005Ethol.111.1126F. doi:10.1111/j.1439-0310.2005.01126.x. ISSN 1439-0310. Gotelli, N.J. (2008). A primer of ecology. Sunderland, Mass.: Sinauer Associates, Inc. ISBN 978-0-87893-318-1 Hughes, P.W., & Simons, A.M. (2014). Changing reproductive effort within a semelparous reproductive episode. American Journal of Botany, 101(8), pp. 1323-1331. doi:10.3732/ajb.1400283. ISSN 0002-9122. PMID 25156981. Lamont, C.C. (1954). The population consequences of life history phenomena. The Quarterly Review of Biology, 29(2), pp. 103137. Lesica, P., & Young, T.P. (2005). Demographic model explains life history evolution in Arabis fecunda. Functional Ecology, 19(3), pp. 471-477. doi:10.1111/j.1365-2435.2005.00972.x. S2CID 31222891. Ricklefs, R.E., & Miller, G.L. (1999). Ecology. Macmillan ISBN 0-7167-2829-X Roff, D. A. (1992). The evolution of life histories. Springer. Young, T.P. (1981). A general mode of comparative fecundity for semelparous and iteroparous life histories. American Naturalist, 118, pp. 27-36. doi:10.1086/283798. S2CID 83860904. Young, T.P. (1990). The evolution of semelparity in Mount Kenya lobelias. Evolutionary Ecology, 4(2), pp. 157171. doi:10.1007/bf02270913. S2CID 25993809.
Contributors and Attributions This chapter was written by D. Wetzel with text taken from the following CC-BY resources: Wikipedia: https://en.wikipedia.org/wiki/Semelparity_and_iteroparity 8.2: Semelparity versus Iteroparity is shared under a CC BY-NC-SA license and was authored, remixed, and/or curated by LibreTexts.
8.3: Life History Evolution The content for this subtopic is found in an external page. Please click the link below to access this information. Life History Evolution Fabian, D. & Flatt, T. (2012). Life History Evolution. Nature Education Knowledge, 3(10):24 8.3: Life History Evolution is shared under a CC BY-NC-SA license and was authored, remixed, and/or curated by LibreTexts.
8.4: The Evolution of Aging The Evolution of Aging Senescence or biological aging is the gradual deterioration of functional characteristics in living organisms. The word senescence can refer to either cellular senescence or to senescence of the whole organism. Organismal senescence involves an increase in death rates and/or a decrease in fecundity with increasing age, at least in the latter part of an organism's life cycle. Environmental factors may affect aging - for example, overexposure to ultraviolet radiation accelerates skin aging. Different parts of the body may age at different rates. Two organisms of the same species can also age at different rates, making biological aging and chronological aging distinct concepts. The occurrence of aging in nature poses an evolutionary puzzle: why would such a deleterious, maladaptive process evolve? This puzzle is deepened by the fact that aging is apparently neither inevitable nor universal: germ lines and several organisms do not exhibit senescent decline.
Figure : The nine hallmarks of aging that are common among organisms: genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, deregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, and altered intercellular communication. Source: Rebelo-Marques, De Sousa Lages, Andrade, Ribeiro, Mota-Pinto, Carrilho and
Espregueira-Mendes - https://www.frontiersin.org/articles/10.3389/fendo.2018.00258/full. Is aging universal? Diverse patterns of senescence among species Classic theories of aging pertain mainly to relatively short-lived species with increasing mortality and decreasing fertility after maturity, but patterns of aging--including reproductive senescence--are very diverse (Finch 1990, Shefferson et al. 2017, Comfort 1956, Jones et al. 2014, Baudisch et al. 2013, Garcia et al. 2011, Schaible et al. 2015, Ruby et al. 2018, Lemaitre & Gaillard 2017). In particular, although many species do age, some appear to show `negligible' senescence (i.e., only weak or no signs of aging with advancing age; Finch 1990, Shefferson et al. 2017, Finch & Austad 2001, Finch 2009, Finch 1998), whereas others could--at least theoretically--exhibit `negative' senescence (i.e., physiological improvement with age; Vaupel et al. 2004). In freshwater polyps of the genus Hydra (Figure 3.2), for instance, survival and fertility do not decline with age (Schaible et al. 2015). Similarly, many plants (e.g., ~ 93% of angiosperms) show no signs of aging (Salguero-Gómez et al. 2013, Baudisch et al. 2013); some trees, for example, live thousands of years (Figure ). However, a caveat is that aging might in many cases exist but not be detectable because the studied individuals were not old enough (Peron et al. 2010); for example, a recent study of turtles--typically thought of as exhibiting strongly `negligible' senescence--has shown that reproduction and survival do in fact decline with age, contrary to previous expectations. Many organisms, such as numerous invertebrates and fish, start to reproduce before they are fully grown.
Increasing body size can then lead to increased fecundity and also to protection against size-specific predators and other sources of mortality. Under these circumstances, the force of natural selection can increase over part of adult life, because the reproductive value of the organism increases (Baudisch 2008, Baudisch 2005, Charlesworth 1994, Partridge & Barton 1996). Non- or slowaging species, including some animals (e.g., basal metazoans such as Hydra and sea anemones) and most higher plants, are characterized by modular organization, indeterminate (including clonal) growth, and the capacity to regenerate due to stem cell activity; often such organisms start to reproduce before they have finished growing, or they can grow indefinitely (Munné-Bosch 2015, Petralia et al. 2014, Bythell et al. 2017). Some clones of grasses, for example, have been estimated to become 15,000 years old (Noodén 1988). In addition, unlike the standard laboratory model organisms, which set aside and sequestrate their germline early in development, in organisms such as Hydra and higher plants the cells that will become the germline are only identified during adulthood, and these organisms therefore maintain cell lineages with high regenerative potential. Thus, the force of natural selection does not always decline monotonically with age (Baudisch 2008, Munné-Bosch 2015, Shefferson et al. 2017 Baudisch 2005, Charlesworth 1994).
Figure : Long-lived organisms; many organisms age very slowly, if at all. Left: the freshwater polyp Hydra is potentially immortal ("Hydra" by Frank Fox is licensed under CC BY-SA 3.0). Second from left: some trees like this bristlecone pine (Pinus longaeva) live for thousands of years ("Gnarly" by Rick Goldwaser is licensed under CC BY 2.0). Third from left: in the naked mole-rat (Heterocephalus glaber) mortality does not increase with age ("Nacktmull" by Roman Klementschitz is licensed under CC BY-SA 3.0). Right: the bowhead whale (Balaena mysticetus) is the longest-lived mammal, with an estimated maximum life
span of 211 years ("A bowhead whale" by Olga Shpak is licensed under CC BY-SA 3.0). Hypotheses of aging More than 300 different hypotheses have been posited to explain the nature and causes of aging. Aging hypotheses fall into two broad categories, evolutionary hypotheses of aging and mechanistic hypotheses of aging. Evolutionary hypotheses of aging primarily explain why aging happens, but do not concern themselves with how (the molecular mechanism(s)). All evolutionary hypotheses of aging rest on the basic mechanisms that the force of natural selection declines with age. Mechanistic hypotheses of aging can be divided into hypotheses that propose aging is programmed (i.e., aging follows a biological timetable), and damage accumulation hypotheses (i.e., those that propose aging to be caused by specific molecular changes occurring over time). Evolutionary aging hypotheses Antagonistic pleiotropy One hypothesis proposed by George C. Williams involves antagonistic pleiotropy. Pleiotropy occurs when a single gene has two or more apparently unrelated effects. The idea of antagonistic pleiotropy is that one gene can positively affect a fitness related trait early in life, but can also have negative effects later in life and thus contribute to senescence. Because many more individuals are alive at young ages than at old ages, even small positive effects early can be strongly selected for, and large negative effects later
may be very weakly selected against. Williams suggested the following example: Perhaps a gene codes for calcium deposition in bones, which promotes juvenile survival and will therefore be favored by natural selection; however, this same gene promotes calcium deposition in the arteries, causing negative atherosclerotic effects in old age. Thus, harmful biological changes in old age may result from selection for pleiotropic genes that are beneficial early in life but harmful later on. In this case, selection pressure is relatively high when Fisher's reproductive value is high and relatively low when Fisher's reproductive value is low. Cancer versus cellular senescence trade-off Senescent cells within a multicellular organism can be purged by competition between cells, but this increases the risk of cancer. This leads to an inescapable dilemma between two possibilities--the accumulation of physiologically useless senescent cells, and cancer--both of which lead to increasing rates of mortality with age. Disposable soma The disposable soma hypothesis of aging was proposed by Thomas Kirkwood in 1977. The hypothesis suggests that aging occurs due to a strategy in which an individual only invests in maintenance of the soma for as long as it has a realistic chance of survival. A species that uses resources more efficiently will live longer, and therefore be able to pass on genetic information to the next generation. The demands of reproduction are high, so less effort is invested in repair and maintenance of somatic cells, compared to germline cells, in order to focus on reproduction and species survival. Damage accumulation hypotheses The free radical hypothesis One of the most prominent hypotheses of aging was first proposed by Harman in 1956. It posits that free radicals produced by dissolved oxygen, radiation, cellular respiration and other sources cause damage to the molecular machines in the cell and gradually wear them down. This is also known as oxidative stress. Under normal aerobic conditions, approximately 4% of the oxygen metabolized by mitochondria is converted to superoxide ion, which can subsequently be converted to hydrogen peroxide, hydroxyl radical and eventually other reactive species including other peroxides and singlet oxygen, which can, in turn, generate free radicals capable of damaging structural proteins and DNA. There is substantial evidence to back up this theory. Old animals have larger amounts of oxidized proteins, DNA and lipids than their younger counterparts. Chemical damage One of the earliest aging hypotheses was the Rate of Living Hypothesis described by Raymond Pearl in 1928, which states that fast basal metabolic rate corresponds to shortened maximum life span. While there may be some validity to the idea that for various types of specific damage detailed below that are byproducts of metabolism, all other things being equal, a fast metabolism may reduce life span, in general this hypothesis does not adequately explain the differences in life span either within, or between, species. Calorically restricted animals process as much, or more, calories per gram of body mass, as their ad libitum fed counterparts, yet exhibit substantially longer life spans. Similarly, metabolic rate is a poor predictor of life span for birds, bats and other species that, it is presumed, have reduced mortality from predation, and therefore have evolved long life spans even in the presence of very high metabolic rates. In a 2007 analysis it was shown that, when modern statistical methods for correcting for the effects of body size and phylogeny are employed, metabolic rate does not correlate with longevity in mammals or birds. With respect to specific types of chemical damage caused by metabolism, it is suggested that damage to structural proteins or DNA caused by ubiquitous chemical agents in the body such as oxygen and sugars, are in part responsible for aging. The damage can include breakage of biopolymer chains, cross-linking of biopolymers, or chemical attachment of unnatural substituents to biopolymers. Sugars such as glucose and fructose can react with certain amino acids such as lysine and arginine and certain DNA bases such as guanine to produce sugar adducts, in a process called glycation. These adducts can further rearrange to form reactive species, which can then cross-link the structural proteins or DNA to similar biopolymers or other biomolecules such as nonstructural proteins. There is evidence that sugar damage is linked to oxidant damage in a process termed glycoxidation.
Mutation accumulation Natural selection can support lethal and harmful alleles, if their effects are felt after reproduction. The geneticist J. B. S. Haldane wondered why the dominant mutation that causes Huntington's disease remained in the population, and why natural selection had not eliminated it. The onset of this neurological disease is (on average) at age 45 and is invariably fatal within 10-20 years. Haldane assumed that, in human prehistory, few survived until age 45. Since few were alive at older ages and their contribution to the next generation was therefore small relative to the large cohorts of younger age groups, the force of selection against such lateacting deleterious mutations was correspondingly small. Therefore, a genetic load of late-acting deleterious mutations could be substantial at mutation-selection balance. This concept came to be known as the selection shadow (Figure ). Peter Medawar formalized this observation in his mutation accumulation hypothesis of aging. "The force of natural selection weakens with increasing age--even in a theoretically immortal population, provided only that it is exposed to real hazards of mortality. If a genetic disaster... happens late enough in individual life, its consequences may be completely unimportant".
Figure : The declining force of selection. The strength (`force') of selection measures how strongly natural selection acts on changes in survival and/or fecundity. Often, but not always, the force of selection declines with age. If this is the case, then alleles
with neutral effects on fitness early in life but with deleterious effects late in life can accumulate in a population, unchecked by selection (mutation accumulation). Similarly, alleles with positive effects on fitness components early in life can be selectively favored even if they have negative effects late in life (antagonistic pleiotropy). The late-life negative effects in the `selection shadow' cannot be effectively eliminated by selection, leading to senescence. While the force acting on survival (solid line) only starts to decrease with age after the onset of reproduction, the strength of selection on fecundity (dashed line) can increase or decrease before the onset of reproduction. Source: Flatt and Partridge, https://doi.org/10.1186/s12915-018-0562-z.
Trade-offs with life span are pervasive but can be uncoupled Studies of natural populations have also found support for phenotypic trade-offs consistent with the notion of antagonistic pleiotropy / disposable soma (Nussey et al. 2013, Peron et al. 2010). In bats, for example, species that produce more offspring are shorter-lived than those that produce fewer offspring (Kim et al. 2011). Similarly, a recent review of 26 studies of free-ranging populations of 24 vertebrate species (birds, mammals, reptiles) has identified clear-cut trade-offs between early and late fitness components (Lemaitre et al. 2015), and data in humans have unraveled a genetically based trade-off between reproduction and life span (Wang et al. 2013). Trade-offs thus seem to be pervasive: high resource allocation to growth or reproduction early in life is often associated with earlier or more rapid aging. However, there is also growing evidence that trade-offs between life span and other fitness components are context-dependent and can be `uncoupled', as is observed in some long-lived C. elegans or Drosophila mutants (Flatt & Schmidt 2009, Flatt 2011, Rodrigues & Flatt 2016, Flatt & Heyland 2011), or upon manipulation of specific dietary amino acids in flies (Grandison et al. 2009, Selman et al. 2008; see below), without any apparent fitness costs of longevity. In these cases, a likely explanation is the artificially benign laboratory environment occupied by these organisms, which may allow them to realize their physiologically maximal possible investments into both survival and reproduction. The most famous example of an `uncoupling' of the fecundity-longevity trade-off is seen in eusocial insects (i.e., ants, bees, termites). In many ants, for example, queens are extraordinarily long-lived and highly fertile as compared to the short-lived and
sterile workers (Rodrigues & Flatt 2016, Keller & Genoud 1997, Keller & Jemielity 2006, Kuhn & Korb 2016, Heinze & Schrempf 2008, Schrempf et al. 2017, von Wyschetzki et al. 2015, Hartmann & Heinze 2003, Kramer et al. 2015), even though within the worker caste reproductive costs have been found among fertile bumblebee workers (Blacher et al. 2017). On the other hand, in naked mole rats, which are also eusocial, queens and workers have approximately equivalent life spans but workers do not reproduce while queens can produce up to 900 pups (Buffenstein & Jarvis 2002). How can social insect queens (or kings in termites) escape this trade-off? Surprisingly little formal analysis of this problem exists; the standard explanation that has been put forward is that queens and kings live much longer because they are shielded from extrinsic mortality by the workers (Keller & Genoud 1997, Heinze & Schrempf 2008). In addition, queens or kings may defy the fecundity-longevity trade-off because of tradeoffs at the colony level (Kramer et al. 2016), with resources provided by workers freeing them from individual-level trade-offs; at the colony level, queens and kings might be viewed, metaphorically, as representing the `immortal germline', whereas workers can be seen as representing the `disposable soma' (Kramer & Schaible 2013). Classic theories of aging may also not fully apply to eusocial insects (Kramer et al. 2016): their populations exhibit not only age structure but also strong social structure and division of labor. Since in such a situation survival is not only age- but also state-dependent, the force of selection does not necessarily decline with age (Williams & Day 2003). More theoretical work on aging in eusocial insects is warranted, especially the development of class-structured inclusive fitness (kin selection) models (Rodrigues & Flatt 2016, Kramer et al. 2016, Kramer & Schaible 2013, Bourke 2007). An important insight into the likely explanation for the `breaking' or `uncoupling' of trade-offs comes from the different outcomes of attempts to measure reproductive costs by looking at natural correlations across individuals as opposed to experimental manipulation of reproductive rate. Generally, across individuals in natural populations, there is a positive phenotypic correlation between fecundity and life span. However, the causal connection between the two traits may be the opposite, as experimental manipulations of, for instance, increasing clutch size in birds, often lead to reduced future fecundity or survival (Partridge 1992). This difference occurs because the individual variation in condition and circumstances may obscure the underlying cost of reproduction: healthy individuals in a rich environment may have high fecundity and life span despite the cost of reproduction, which is only revealed by experimental manipulations. This concept has been termed the 'big house, big car effect' (van Noordwijk & de Jong 1986). This underlying cost of reproduction may then constrain the combinations of life history traits that can evolve (van Noordwijk & de Jong 1986, Metcalf 2016). Organisms that live in an environment that is beneficial for development may indeed not experience costs of reproduction (van Noordwijk & de Jong 1986, Metcalf 2016), as often seems to be the case in laboratory animals (Klepsatel et al. 2013). In addition, positive correlations between fitness-related traits can also be caused by mutational variation in recessive deleterious effects (Charlesworth 1990). This arises because such deleterious mutations can have negative pleiotropic effects on two or more traits but the extent of these negative effects varies genetically among individuals. Definition: The big house, big car effect The big house, big car effect says that individuals differ in the amount of resources (energy, time, or space) they can allocate to competing demands. For example, in humans, each of us has a limited amount of monetary resources. If we were forced to choose between spending our money on a nice house or a nice car (an allocation trade-off), most of us would end up with either a nice house or a nice car, but some people are super wealthy and can afford both a big house and a nice car. If we are only looking across individuals and not accounting for the amount of resources each has accumulated, we often see patterns like this, which suggest an uncoupling of trade-offs. But because individuals differ in their available resources, this observation is not an accurate representation of the true trade-off that is being experience by each individual at the within-individual level.
Figure : The 'big house, big car effect' states that individuals differ in the amount of resources they can allocate to competing demands, and thus if we were to correlate life history traits across individuals (A), we can observe an uncoupling of the trade-off. However, because individuals differ in their available resources, this observation is not an accurate representation
of the true trade-off that is being experience by each individual at the within-individual level (B). Each color of dot or line represents a different individual with a different amount of resources. Source: Dan Wetzel. The evolution of aging in humans Human life expectancy worldwide has increased dramatically. During the ~300,000 generations since the divergence from our most recent common ancestor with the great apes, life span evolved to double its previous value (Finch 2010). In the last ~200 years there has been a further substantial increase, on average about 2.5 years per decade, attributable to environmental changes, including improved food, water, hygiene, and living conditions, reduced impact of infectious disease with immunization and antibiotics, and improved medical care at all ages (Vaupel et al. 1998, Wilmoth 2000, Oeppen & Vaupel 2002, Vaupel 2010). Many modern humans inhabit a very different environment from that in which their life history evolved, with both protection from many of its dangers, such as predators, infectious diseases, and harsh physical conditions, and freedom from the need to forage extensively to avoid starvation (Finch 2010). As a result, most people are now living long beyond the ages at which most would have been dead in the past. Natural selection has therefore not had an opportunity to maintain evolutionary fitness at older ages. In humans, where age-related changes are particularly well documented, aging has proved to be a complex process of functional decline and accumulation of diverse pathologies in different tissues (Lopez-Otin et al. 2013, Kirkwood et al. 1999). Williams predicted in 1957 that aging is likely to be a genetically complex trait, and different lineages and taxa might well exhibit different proximate mechanisms of senescence. Indeed, natural variation in the rate of aging is likely influenced by many genes (Burke et al. 2014, Highfill et al. 2016, Ivanov et al. 2015), since survival and reproduction between them harness the activity of much of the genome.
Figure : Aging in humans. Source: RODNAE Productions and Andrea Piacquadio.
Prevention of late-life morbidity in humans ideally would involve interventions that could be started at the earliest in middle age. Pharmacological prevention of cardiovascular disease, with statins and blood pressure lowerers, is already routine in clinical practice (Sundstrom et al. 2018). Unsurprisingly, many of the proteins that have turned out to be important in aging also play prominent roles in the etiology of age-related diseases, and are already the targets of licensed drugs. Consideration is hence starting to be given to widening the preventative, pharmacological approach, for instance by repurposing drugs that are used to treat cancer, prevent rejection of transplanted organs, and diabetes because they have been found to extend life span in model organisms (Blenis 2017, Mannick et al. 2014, Barzilai et al. 2016, Johnson & Kaeberlein 2016). Other possible approaches to emerge from experimental work with animals include removal of damaging senescent cells that accumulate during aging (Childs et al. 2015, Rando & Chang 2012), use of factors from young blood that restore the age-related loss of function of stem cells or synapses between nerve cells in the brain (Rando & Chang 2012, Mair & Dillin 2008), and alteration of the composition of the microorganisms in the gut to a younger profile (Clark & Walker 2018, Kundu et al. 2017, Schmidt et al. 2018), which has already been shown to extend life span in the turquoise killifish (Smith et al. 2017). However, despite the considerable promise of these approaches, the extent to which they can yield health benefits free of side effects needs detailed study, since they could pose some new challenges for an aged system. For instance, removal of senescent cells, or restoration of stem cell function, could be beneficial in the short term, but in the longer term could lead to stem cell exhaustion and tissue dysfunction.
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