What is the difference between life cycle and life history

Editors: Anne L. Runehov, Lluis Oviedo. Contents Search. Life Course, life cycle, life history, life span and life stage. Authors Authors and affiliations Duane F. Edited by M. Crawley, 73— Overview of life history variation in plants. Available online by subscription. Flatt, T. Mechanisms of life history evolution: The genetics and physiology of life history traits and trade-offs. An edited volume that presents summaries for a large number of topics in life history evolution, with particular attention to genetic and physiological mechanisms underlying traits and trade-offs.

Marshall, D. Krug, E. Kupriyanova, M. Byrne, and R. The biogeography of marine invertebrate life histories. Annual Review of Ecology, Evolution and Systematics — DOI: Compiles life history and geographic data for more than one thousand species of marine invertebrates, and many traits covary with temperature and local productivity. An excellent example of the utility of the comparative approach, applied here to group whose traits seem less constrained by phylogeny than is true for terrestrial species.

Available online for purchase or by subscription. Nee, S. Colegrave, S. West, and A. The illusion of invariant quantities in life histories. Science The authors show that, for bounded variables, even random simulations of trait values can give the impression of invariance. Roff, D. The Evolution of life histories: Theory and analysis. A thorough compendium of the theory and evidence used to understand life history evolution.

This tour-de-force covers both genetic and optimization approaches for virtually all important traits, and undoubtedly influenced much subsequent work in this field. Life history evolution.

Sunderland, MA: Sinauer. Updates Roff and devotes more attention to quantitative-genetic modeling. By contrast, a mature Coast Redwood Tree Sequoia sempervirens lives for many hundreds of years and produces millions of seeds each year Figure 1. As these two examples illustrate, organisms differ dramatically in how they develop, the time they take to grow, when they become mature, how many offspring of a particular size they produce, and how long they live.

Together, the age-, size-, or stage-specific patterns of development, growth, maturation, reproduction, survival, and lifespan define an organism's life cycle, its life history. Figure 1: Diversity of life histories. The principal aim of life history theory, a branch of evolutionary ecology, is to explain the remarkable diversity in life histories among species. But there is another, more compelling reason for why life history evolution is important: adaptation by natural selection is based on variation in Darwinian fitness among individuals, and since life history traits determine survival and reproduction they are the major components of fitness.

The study of life history evolution is thus about understanding adaptation, the most fundamental issue in evolutionary biology. Here we introduce the basics of life history theory and review what biologists have learned about life history evolution. For more in-depth coverage we refer to Stearns , Roff , , Charlesworth , and Flatt and Heyland Life history theory seeks to explain how natural selection and other evolutionary forces shape organisms to optimize their survival and reproduction in the face of ecological challenges posed by the environment Stearns , Roff , Stearns , or as David Reznick has recently put it: "Life history theory predicts how natural selection should shape the way organisms parcel their resources into making babies" Reznick , p.

The theory does so by analyzing the evolution of fitness components, so-called life history traits, and how they interact: size at birth; growth pattern; age and size at maturity; number, size, and sex of offspring; age-, stage- or size-specific reproductive effort; age-, stage- or size-specific rates of survival; and lifespan.

The classical theory treats life history evolution as an optimization problem: given particular ecological factors e. To find the solution to this problem we need to understand its "boundary conditions" Stearns : 1 how extrinsic, environmental factors affect survival and reproduction; and 2 how intrinsic connections among life history traits trade-offs and other constraints limit whether and how life history traits can evolve.

Once these conditions have been understood and defined, life history models can be used to answer questions such as: How small or large should an organism grow? At what age and size should it mature? How many times should it reproduce?

How many offspring should it produce and what size should they be? For how long should it reproduce and how long should it live?

Life history optimization problems are typically modeled by using the Euler-Lotka equation, which describes population growth rate i. The equation sums the probabilities of survival and reproduction over the entire lifetime of the individuals in the population and can then be solved for r. Note that in the context of life history theory r measures the growth rate or fitness of a clone or, in sexually reproducing organisms, the rate of spread of an allele that affects life history.

Thus, the implicit assumption is that the modeled population consists of phenotypically and genetically identical individuals. If the population described by the Euler-Lotka equation is stationary non-growing , r is zero and the equation becomes.

This equation is simpler than the continuous-time version and can be used whenever r is zero or close to zero; for stable populations that do not change in size, R 0 is the appropriate fitness measure Stearns , Roff , Brommer Using this framework, one can ask what particular combination of life history traits maximizes fitness, or how much fitness is affected when one of the traits is changed. This approach has been used with great success to predict the evolution of life history traits.

The evolution of life history traits by natural selection depends upon genetic variation on which selection can act to produce adaptations in response to the environment. The models mentioned above implicitly assume that life history evolution is not limited by a lack of genetic variation.

This low heritability could be caused by low amounts of additive genetic variance; yet, there exists ample genetic variation for life history traits in natural and laboratory populations. Consistent with the notion that fitness components harbor lots of genetic variation, many artificial selection experiments in the laboratory have successfully managed to cause evolutionary changes in life history traits in the predicted direction Stearns , Roff , Houle One reason for the large V A of life history traits may be that they are highly complex, quantitative, polygenic traits influenced by many loci Houle But how can we reconcile the fact that V A is large while at the same time h 2 is small?

A likely reason for the low heritability of life history traits is that, although V A the numerator is large, V P the denominator is much larger than V A. Note that the phenotypic variance V P consists of V A , the additive genetic variance, plus a remainder, V R , that itself consists of all non-additive genetic sources of variation i. Thus, life history traits probably have low heritability because they are influenced by many loci which inflates both V A and V P while at the same time harboring substantial amounts of residual variation V R , for example variation due to changes in the environment which inflates V P but not V A Houle , Houle Moreover, although life history traits are under strong selection, which should exhaust genetic variance, several factors can maintain genetic variation for these traits, including mutation-selection balance, environmental heterogeneity and genotype by environment interactions, and negative genetic correlations Stearns , Roff , Houle However, despite typically large amounts of life history variation, life history evolution is also subject to constraints.

Fitness would obviously be maximal if survival and reproduction would be maximal at all ages, stages, or sizes of an organism. In principle then, the basic problem of life history evolution is trivial: all life history traits should always evolve so as to maximize survival and reproduction and thus fitness Houle This would very rapidly lead to the evolution of "Darwinian demons" Law that would take over the world, i. Such organisms, however, do not exist in the real world: Resources are finite, and life history traits are subject to intrinsic trade-offs and other types of constraints, so natural selection cannot maximize life history traits — and thus fitness — beyond certain limits.

We call such limits evolutionary constraints Stearns , Houle ; as mentioned above, they represent the intrinsic "boundary condition" we must understand to predict life history evolution.

One of the most important types of constraint are life history trade-offs Stearns , Roff , Flatt and Heyland A trade-off exists when an increase in one life history trait improving fitness is coupled to a decrease in another life history trait reducing fitness , so that the fitness benefit through increasing trait 1 is balanced against a fitness cost through decreasing trait 2 Figure 2A.

Note that trade-offs can also involve more than two traits. At the genetic level, such trade-offs are thought to be caused by alleles with antagonistic pleiotropic effects or by linkage disequilibrium between loci. Trade-offs are typically described by negative phenotypic or genetic correlations between fitness components among individuals in a population Figure 2A. If the relationship is genetic, a negative genetic correlation is predicted to limit i.

Thus, a genetic trade-off exists in a population when an evolutionary change in a trait that increases fitness is linked to an evolutionary change in another trait that decreases fitness. The existence of genetic correlations can be established through quantitative genetic breeding designs or through correlated phenotypic responses to selection. For example, direct artificial selection for extended lifespan in genetically variable laboratory populations of fruit flies Drosophila melanogaster causes the evolution of increased adult lifespan sometimes in 10 or fewer generations , but this evolutionary increase in longevity is coupled to decreased early reproduction e.

This suggests that lifespan and early reproduction are genetically negatively coupled, e. At the physiological level, trade-offs are caused by competitive allocation of limited resources to one life history trait versus the other within a single individual, for example when individuals with higher reproductive effort have a shorter lifespan or vice versa Figure 2B. A helpful way to think resource allocation trade-offs is to imagine a life history as being a finite pie, with the different slices representing how an organism divides its resources among growth, storage, maintenance, survival, and reproduction Reznick ; Figure 2C.

The essential problem is this: given the ecological circumstances, and the fact that making one slice larger means making another one smaller, what is the best way to split the pie? Note that since resource allocation trade-offs might have a genetic basis, and since different genotypes may differ in aspects of resource allocation, the genetic and physiological views of trade-offs are not necessarily incompatible.

However, physiological trade-offs at the individual level do not always translate into genetic evolutionary trade-offs at the population level. For instance, when the physiological within-individual trade-off is genetically fixed "hard-wired" among all individuals within the population, all individuals will exhibit the same negative physiological relationship between two life history traits but the genetic correlation among individuals would be zero Stearns , Stearns Figure 2: Life history trade-offs.

Top A : A negative genetic or phenotypic correlation, i. Middle B : The so-called Y-model of resource allocation trade-offs. In this example, a limited resource e. Bottom C : A useful way of thinking about resource allocation trade-offs is to imagine the life history as being a finite pie. See text for further details.

The book by Stearns lists 45 possible trade-offs among 10 major life history traits, and many more can be envisaged to exist. Those trade-offs that have received most attention include 1 current reproduction versus survival; 2 current versus future reproduction; 3 current reproduction versus parental growth; 4 current reproduction versus parental condition; and 5 number versus size of offspring.

Some of the best evidence for genetically based life history trade-offs comes from artificial selection and experimental evolution experiments carried out in Drosophila see reviews in Stearns and Partridge , Flatt and Schmidt , Flatt In summary, many experiments have found: a negative correlation between early fecundity and adult lifespan; a positive correlation between developmental time and body size; a positive correlation between either developmental time or body size with early fecundity; and a negative correlation between early and late fecundity.

Other constraints on life histories that prevent natural selection from attaining a particular fitness optimum can involve biophysical, biochemical and structural factors, developmental properties of the organism, phylogenetic and historical contingencies, or simply a lack of genetic variation Stearns , Houle Genetic variation and constraints are not the only factors affecting the expression and evolution of life history traits.

Another important issue is that life history variation is often strongly influenced by the environment e. The plasticity of a specific genotype can be conceptually described by a mathematical function called a reaction norm, i. Figure 3: Life history plasticity. Top A. Phenotypic plasticity is often visualized using so-called reaction norms, curves that relate phenotypes and environments for a specific genotype.

An example of a single reaction norm for body size in fruit flies Drosophila , relating changes in ambient temperature during development to the adult body size phenotypes produced by a single fly genotype.

Bottom B : Genetic variation among genotypes in phenotypic plasticity manifests itself as a bundle of reaction norms with different slopes, i. Such a pattern is also called genotype by environment interaction GxE. Shown here is a case of particularly strong GxE, with the reaction norms of three genotypes crossing each other, a pattern that changes the relative ranking of the phenotypes across environments.

The importance of such plasticity in life history evolution is at least three-fold Stearns and Koella , Stearns et al. Many life history traits e. In spadefoot toads Scaphiophus couchii , for example, individuals that develop in ponds of short duration have a shorter larval period and a smaller body size at metamorphosis with the traits being negatively correlated than individuals that develop in ponds of long duration with the traits being positively correlated Newman , Stearns et al.

Having discussed the optimality modeling approach and the factors that influence the expression of life history traits, we turn now to discussing some major predictions for the evolution of life histories for details see Stearns , Roff , Charlesworth , Stearns , Roff At what age and size should an organism mature? A genotype's reproductive success depends strongly on its growth rate and — as a consequence of growth — on its age and size at maturity.

To predict the optimal age and size at maturity we must understand the relative costs and benefits in terms of mortality and reproduction of either maturing early or late and of either growing large or staying small.