Jump to content

User:Ceceholm/sandbox

From Wikipedia, the free encyclopedia

Introduction:

Life history theory (LHT) is an analytical framework[1] 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 [2].  A life history strategy is the “age- and stage-specific patterns” [2] and timing of events that make up an organism’s life, such as birth, weaning, maturation, death, etc [3].

The theory was developed in the 1950s [4] and is used to answer questions about topics such as organism size, age of maturation, number of offspring, life span, and many others [5]. 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[4], and scientists use these predictions to understand how evolution affects the ordering and length of life history events in an organism’s life, particularly the lifespan and period of reproduction [6]. Life history theory draws on an evolutionary foundation, and studies the effects of natural selection on organisms, both throughout their lifetime and across generations [7]. It also uses measures of evolutionary fitness to determine if organisms are able to maximize or optimize this fitness [8] by allocating resources to a range of different demands throughout the organism’s life [1]. It serves as a method to investigate further the “many layers of complexity of organisms and their worlds” [9].

Brief History of Field:

Life history theory is seen as a branch of evolutionary ecology [2] and is used in a variety of different fields. Beginning in the 1950s, mathematical analysis became an important aspect of research regarding LHT [10]. There are two main focuses that have developed over time: genetic and phenotypic [9], but there has been a recent movement towards combining these two approaches [10].

Framework:

Two possible frameworks from which to evaluate life history strategies have been proposed. The first, by Roff, has three main components, and focuses on the optimality approach:

1.     “the assumption that some measure of fitness is maximized.”

2.     “that there exist both constraints and trade-offs between traits that limit the set of possible combinations”

3.     “that there exists sufficient genetic variation to permit the attainment of that combination which maximizes fitness, subject to the aforementioned constraints and trade-offs.” [11]

A second framework is proposed by Stearns, which contains four elements that can be combined in various ways to explain life history strategies.

1)   demography

2)   quantitative genetics and reaction norms

3)   trade-offs

4)   lineage-specific effects.[12]

Life Cycle:

All organisms follow a specific sequence in their development [8], beginning with gestation and ending with death, which is known as the life cycle. Events in between usually include birth, childhood, maturation, reproduction, and senescence, and together these comprise the life history strategy of that organism [3].

The major events in this life cycle are usually shaped by the demographic qualities of the organism [2].  Some are more obvious shifts than others, and may be marked by physical changes – for example, teeth erupting in young children [7]. 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 [3], such as age at first reproduction.

Life cycles can be divided into two major stages: growth and reproduction. These two cannot take place at the same time, so once reproduction has begun, growth usually ends [8]. 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 [7].

Each species has its own pattern and timing for these events, often known as its ontogeny, and the variety produced by this is what LHT studies [13]. Evolution then works upon these stages to ensure that an organism adapts to its environment [5]. 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 [3][13]. All of these are defined in a specific biological way, which is not necessarily the same as the way that they are commonly used [13].

Darwinian Fitness:

In the context of evolution, fitness is determined by the number of descendents an organism produces over the course of its life. The main elements are survivorship and reproductive rate [5]. This means that the organism’s traits and gene are carried on into future generations, and contribute to  evolutionary “success.”  The process of adaptation contributes to this “success” by impacting rates of survival and reproduction [2], which in turn establishes an organism’s level of Darwinian fitness [5]. In life history theory, evolution works on the life stages of organisms and creates adaptation - this process establishes fitness.[5]

Life History Traits:

There are seven traits that are traditionally recognized as important in life history theory [12]. 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 [4]. 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,[12] although there are still large varieties that exist in the world.

List of 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

Life History Strategies:

Combinations of these life history traits and life events create the life history strategies. As an example, Winemiller and Rose, as cited by Lartillot & Delsuc, propose three types of life history strategies in the fish they study: opportunistic, periodic, and equilibrium.[14]. 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. So, a fish with a small body size, a late of age of maturation, and low survivorship, found in a seasonal environment, would be classified as having a periodic life strategy [14]. 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 [15].

Major Ideas:

There are several major ideas that are important in life history theory, and which are used to understand life history strategies and make predictions about their effects. These are: variation, trade-offs, constraints, optimizing fitness, reproductive effort, r/k selection, allocation of resources, and phenotypic plasticity.

Variation

Variation is a major part of what LHT studies, because every organism has its own life history strategy. Differences between strategies can be minimal or great [5]. For example, one organism may have a single offspring while another may have hundreds. Some species may live for only a few hours, and some may live for decades. Some may reproduce dozens of times throughout their lifespan, and others may only reproduce one or twice.

This variety can be useful, because it allows scientists to find trends and then make predictions about why different organisms have similar traits, such as brain size, body size[16], or the existence of provisioning behavior[17]. In contrast, sometimes a single factor can be behind a variety of different strategies[18]. The diversity of life history strategies is also influenced by factors such as environment and the predictability or seasonality of that organism’s situation [14].

The impact of different environments contributes to the creation of a variety of life history strategies because the outcomes of an organism’s energy investments are impacted by the type of environment it occupies. For example, an organism which is at the bottom of its food chain, and an organism that is a top predator will need to spend very different amounts of energy to ensure survival [6]. One unifying factor in all types of life history strategies is the importance of the timing and investment of energy for success, regardless of the type of environment the organism exists in [4].

Trade-offs

An essential component of studying life history strategies is identifying the trade-offs that take place for any given organism. Energy use in life history strategies is regulated by thermodynamics and the conservation of energy [3], and the “inherent scarcity of resources” [8], so not all traits or tasks can be invested in at the same time. Thus, organisms must choose between tasks, such as growth, reproduction, and survival[8], prioritizing some and not others. For example, there is a trade-off between maximizing body size and maximizing lifespan, and between maximizing offspring size and maximizing offspring number [4] [5]. This is also sometimes seen as a choice between quantity and quality of offspring [6]. 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) [8] [6]. Since an organism can’t 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 [3]. 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 [8].

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[6]. 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 [4].

Constraints

            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. This occurs in populations as well [5]. These limits can be physical, developmental, or historical, and they are imposed by the existing traits of the organism [2].

Optimizing Fitness

Optimizing fitness is the idea that an organism can adapt in order to achieve an “optimal” life history strategy that allows it the highest level of fitness possible. There are several methods from which to approach the study of optimality, including energetic and demographic [6]. Achieving optimal fitness also encompasses multiple generations, because the optimal use of energy includes both the parents and the offspring[6]. 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” [6].

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[4]. This base assumption, that over the course of its life span an organism is aiming for optimal energy use [6], then allows scientists to test other predictions. However, actually gaining this optimal life history strategy cannot be guaranteed for any organism [4].

Reproductive Effort

Reproductive effort is the energy spent to successfully pass on genes, which includes attracting a mate, increasing reproductive opportunities (for example, by regulating behavior [19], and parenting. The parenting effort is important because reproduction is only successful if the offspring survives to maturity and can reproduce itself [8][1]. Because mates with appealing qualities are a scarce resource, this creates competition among organisms and thus drives resource allocation [8]. In terms of classifying reproductive effort, there are two main types of organisms: semelparous (one burst of reproduction) and iteroparous (repeated bouts) [6]. Environmental factors may also affect rates of reproduction. For example, an organism’s age at first reproduction may be affected by the amount of resources available in its environment, and whether the population is growing or not [1]. Age of first reproduction is also important because it marks the shift from an organism’s period of growth to its period of reproduction, an essential trade-off [6]. Age at which an organism ceases reproduction is also important, because the fact that some organisms live for many years after stopping reproduction has led to many questions about the purpose of a long period of senescence. For example, the Grandmother Hypothesis argues that the purpose of this period might be to contribute to the reproductive success of one’s children, through providing resources and contributing to care [20]. There are some challenges to this idea as well, such as why both men and women live so long after stopping reproduction [6].

There are certain common patterns among organisms – for example: for vertebrates, reproductive performance tends to get better with age, at least until the start of senescence [21], and can be considered a rate phenomenon[4]. These patterns can be used to inform models and make predictions about the evolutionary processes taking place [21].

Another important concept in evaluating reproductive effort is modulation. This takes place when a change, either physical or behavioral, affects an organism’s opportunities to reproduce or successfully raise its offspring [1]. Such behaviors may be in response to perceived risks[22] [23] . This change may have positive adaptive effects if the change promotes the survival of the organism and any existing offspring, or if it enhances the potential for future opportunity[1].

r/K Selection Theory

r/K selection theory operates on the idea that there is a basic difference between two types of organisms – r-selected organisms and K-selected organisms. r-selected groups have fast maturation and growth, short life-spans, and high fertility with low survival rates. K-selected groups have the opposite: slow maturation and growth, long life-spans, and low fertility with high survival [4].

r-selection takes place in environments that have the resources to promote the rapid growth of a population, while K-selection takes place in environments where resources are scarce and organisms need to be more competitive[4]. More recently, these two theories have been referred to as slow life histories and fast life histories. Fast life histories are similar to r-selection, and slow life histories to K-selection[24]. These two theories can be used to explore why organisms behave in a certain way [25], for example, whether people who grew up in an environment with more resources respond differently to risk than those who grew up with few resources [26].

Allocation of Resources

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 [8], and making the best possible choices about how to allocate energy to various trade-offs contributes to this. Models of resource allocation have been developed and used to study problems such as parental involvement, the length of the learning period for children, and other developmental issues [6]. 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[3].

Phenotypic Plasticity

Phenotypic plasticity focuses on the concept that the same genotype can produce different phenotypes in response to different environments [12]. It affects the levels of genetic variability because by serving as a source of variation and integration of fitness traits[12].

Human Life History:

In studying humans, life history theory is used in many ways, including in biology, psychology, economics, anthropology, and other fields [8][26][27]. 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 [5]. 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 [6], a long lifespan [6] [28], and a high level of reproduction, often supported by fathers and older (post-menopausal) relatives [28] [17] [29][28]. 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 [6][28]. This period of learning may also explain the longer lifespan, as a longer amount of time over which to use those skills makes the period needed to acquire them worth it [7][28]. Cooperative breeding and the grandmothering hypothesis have been proposed as the reasons that humans continue to live for many years after they are no longer capable of reproducing [29][6]. The large brain allows for a greater learning capacity, and the ability to engage in new behaviors and create new things [28]. The change in brain size may have been the result of a dietary shift – towards higher quality and difficult to obtain food sources [28] – or may have been driven by the social requirements of group living, which promoted sharing and provisioning [7]. Recent authors, such as Kaplan, argue that both aspects are probably important [28].

Tools Used:

Mathematical modeling is very commonly used in life history theory, but there are a variety of other tools that scientists use to answer their questions about life history strategies and traits.

Quantitative Genetics

Quantitative genetics, also known as statistical phenomenology[12], is used to study phenotypes that exist along a spectrum, such as height, weight, and age (called “quantitative”), not those that exist in discrete categories, such as eye color (called “Mendelian”) [12]. This tool is used to analyze genetic variation and how it responds to selection [12]. Like most statistical approaches, it begins with basic assumptions about the transmission of traits, and then goes on to create analyses of constantly varying traits based on these assumptions [12]. The types of analyses included are things such as: reaction norms, models of gene value, measures of heritability, measures of genetic covariance, and maximum likelihood estimates[12]. Overall, it is a useful tool, but some argue that is can be misleading, because it evaluates genetics on a phenotypic basis, and the phenotype being studied derives from both genetic and environmental influences [12].

Artificial Selection

            Artificial selection is the process of studying heritability and genetic correlations [11][10] under controlled conditions, often in a lab setting. This is beneficial because natural selection operates over a long time scale in nature, so working artificially makes it easier to study the effects[30].

Demography

Demography uses statistics like population size, average age, number of offspring, and measures of growth to look at the affects of selection on various life history traits [12]. Type of analyses used include the Euler-Lotka equation, models of population growth, life tables, measures of residual reproductive value, and measures of the costs of reproduction [12]. It also looks at rates of mortality and reproduction, and connects these to age, stage, and size-related factors. An example of demographic analyses would be studies that look the demographic transition taking place in modern societies, as people make deliberately make decisions to not maximize their reproductive potential [6].

Optimality Modeling

One common type of mathematical model used in life history theory is optimality modeling [13].  Stearns emphasizes that there is no one model that can be applicable to every organism, though the framework of creating a model can be shared. He writes that other tools, such as demography and comparative analysis, should be used to obtain the information needed to customize a model for each organism [12]. 

Mechanistic Approach

The mechanistic approach to life history theory relies on using proximate mechanisms from molecular biology to evaluate life history strategies [2]. Several authors have argued that understanding the mechanistic aspect of genotypes, and the effects on evolution, better, would help understand the phenotypes that life history theory usually studies[2] [29]

Malthusian Parameter

The Malthusian parameter is a measure of the “instantaneous rate of increase”, identified by the variable r [3]. This measure can be used to see if a population is growing, shrinking, or remaining the same over time [3]. The resulting information can then be plugged into models and used to make inferences about health, reproduction rates, and similar questions about a population.

  1. ^ a b c d e f Vitzthum, V. (2008). Evolutionary models of women's reproductive functioning. Annual Review of Anthropology, 37, 53-73
  2. ^ a b c d e f g h Flatt, T., & Heyland, A. (Eds.). (2011). Mechanisms of Life History Evolution : The Genetics and Physiology of Life History Traits and Trade-Offs. Oxford, GB: OUP Oxford. Retrieved from http://www.ebrary.com.libproxy.sdsu.edu
  3. ^ a b c d e f g h i Ahlström, T. (2011). Life‐history theory, past human populations and climatic perturbations. International Journal of Osteoarchaeology, 21(4), 407-419.
  4. ^ a b c d e f g h i j k Stearns, S. (1976). Life-History Tactics: A Review of the Ideas. The Quarterly Review of Biology, 51(1), 3-47. Retrieved from http://www.jstor.org/stable/2825234
  5. ^ a b c d e f g h i Hochberg, Z. (2011). Evo-Devo of Child Growth : Treatise on Child Growth and Human Evolution (1). Hoboken, US: Wiley-Blackwell. Retrieved from http://www.ebrary.com.libproxy.sdsu.edu
  6. ^ a b c d e f g h i j k l m n o p q r Hill, K., & Kaplan, H. (1999). Life history traits in humans: Theory and empirical studies. Annual Review Of Anthropology, 28(1), 397.
  7. ^ a b c d e Bolger, D. (Ed.). (2012). Wiley Blackwell Companions to Anthropology Ser. : A Companion to Gender Prehistory (1). Somerset, US: Wiley-Blackwell. Retrieved from http://www.ebrary.com.libproxy.sdsu.edu
  8. ^ a b c d e f g h i j k Preston, S. D., Kringelbach, M. L., & Knutson, B. (2014). The Interdisciplinary Science of Consumption. Cambridge, US: The MIT Press. Retrieved from http://www.ebrary.com.libproxy.sdsu.edu
  9. ^ a b Morbeck, M., Galloway, A., & Zihlman, A. The Evolving Female : A Life-history Perspective. (1997). Princeton, N.J.: Princeton University Press
  10. ^ a b c Roff, D. (2002). Life History Evolution. Sunderland, Mass.: Sinauer
  11. ^ a b Roff, D. (1992). The Evolution of Life Histories : Theory and Analysis. New York: Chapman & Hall.
  12. ^ a b c d e f g h i j k l m n Stearns, S. (1992). The Evolution of Life Histories. Oxford ; New York: Oxford University Press.
  13. ^ a b c d Hawkes K., ed. The Evolution of Human Life History. (2006). Santa Fe : Oxford: School of American Research ; James Currey. Gen ed.
  14. ^ a b c Lartillot, N., & Delsuc, F. (2012). JOINT RECONSTRUCTION OF DIVERGENCE TIMES AND LIFE-HISTORY EVOLUTION IN PLACENTAL MAMMALS USING A PHYLOGENETIC COVARIANCE MODEL. Evolution, 66(6), 1773-1787. Retrieved from http://www.jstor.org/stable/41503481
  15. ^ Reynolds, J. , & McCrea, S. (2016). Life history theory and exploitative strategies. Evolutionary Psychology, 14(3),
  16. ^ Charnov, E. (1991). Evolution of Life History Variation Among Female Mammals. Proceedings of the National Academy of Sciences of the United States of America, 88(4), 1134-1137. Retrieved from http://www.jstor.org/stable/2355948
  17. ^ a b Barton, R., Capellini, I., & Stevens, C. (2011). Maternal investment life histories, and the costs of brain growth in mammals. Proceedings of the National Academy of Sciences of the United States of America, 108(15), 6169-6174. Retrieved from http://www.jstor.org/stable/41126625
  18. ^ Figueredo, A. , Vasquez, G. , Brumbach, B. , Schneider, S. , Sefcek, J. , et al. (2006). Consilience and life history theory: From genes to brain to reproductive strategy. Developmental Review, 26(2), 243-275.
  19. ^ Wenner, C. , Bianchi, J. , Figueredo, A. , Rushton, J. , & Jacobs, W. (2013). Life history theory and social deviance: The mediating role of executive function. Intelligence, 41(2), 102-113
  20. ^ Hawkes, K. (1998). Grandmothering, Menopause, and the Evolution of Human Life Histories. Proceedings of the National Academy of Sciences of the USA, 95(3), 1336–1339.
  21. ^ a b Bradley, R. J. and Safran, R. J. (2014), Conceptual Revision and Synthesis of Proximate Factors Associated with Age-Related Improvement in Reproduction. Ethology, 120: 411–426. doi:10.1111/eth.12220
  22. ^ Panter-Brick, C. (2014). Health, risk, and resilience: Interdisciplinary concepts and applications. Annual Review of Anthropology, 43, 431.
  23. ^ Griskevicius, V. , Tybur, J. , Delton, A. , Robertson, T. , & Simpson, J. (2011). The influence of mortality and socioeconomic status on risk and delayed rewards: A life history theory approach. Journal of Personality and Social Psychology, 100(6), 1015-1026
  24. ^ Oli, M. (2004). The fast–slow continuum and mammalian life-history patterns: An empirical evaluation. Basic and Applied Ecology, 5(5), 449-463.
  25. ^ Figueredo, A. , Vasquez, G. , Brumbach, B. , Schneider, S. , Sefcek, J. , et al. (2006). Consilience and life history theory: From genes to brain to reproductive strategy. Developmental Review, 26(2), 243-275.
  26. ^ a b Mittal, C. , Griskevicius, V. , Simpson, J. , & Kawakami, K. (2014). Sense of control under uncertainty depends on people’s childhood environment: A life history theory approach. Journal of Personality and Social Psychology, 107(4), 621-637.
  27. ^ 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.
  28. ^ a b c d e f g h Kaplan, H., Hill, K., Lancaster, J. and Hurtado, A. M. (2000), A theory of human life history evolution: Diet, intelligence, and longevity. Evol. Anthropol., 9: 156–185. doi:10.1002/1520-6505(2000)9:4<156::AID-EVAN5>3.0.CO;2-7
  29. ^ a b c Isler, K. , & van Schaik, C. (2012). Allomaternal care, life history and brain size evolution in mammals. Journal of Human Evolution, 63(1), 52-63.
  30. ^ Blouin, M., Karimi, B., Mathieu, J. and Lerch, T. Z. (2015), Levels and limits in artificial selection of communities. Ecol Lett, 18: 1040–1048. doi:10.1111/ele.12486
Retrieved from "https://en.wikipedia.org/w/index.php?title=User:Ceceholm/sandbox&oldid=755806117"