Key Questions and Case Studies

Because of their inherent relationship to both fitness and population ecology, the study of life-history patterns has influenced many areas of research within evolution and ecology including: mating systems, sexual selection, migration, species interactions, and community dynamics. It is impossible to cover such broad influences and applications here. Therefore, we focus on a few classic life-history questions and discuss some new directions of research.

The Timing of Reproduction: Age and Size at Maturity

One ofthe most basic questions in life-history theory is when an organism should mature and reproduce. In general, size is positively correlated with fecundity and fertility. Because individuals tend to grow more slowly (if at all) when reproductive, there is an advantage to growing as large as possible before maturity. However, delayed reproduction will not be favored by selection if mortality risk is high. Additionally, resource availability also interacts with the strength of selection on growth and maturation. Classic predictions come from finding the age at maturity a that maximizes population growth rate (r) in the Euler-Lotka equation

where lx represents expected survival to age x, a age at first reproduction, and mx fecundity at age x. This approach makes the assumption that the population is at equilibrium. The life history that maximizes r and satisfies the above equation is predicted to be favored by natural selection. It is possible to examine different patterns of survival and fecundity with age (e.g., different functions for lx and mx with respect to a) and determine how they affect the optimal age at maturity. Theory and empirical studies have shown that higher adult mortality favors early age and size at maturity. Similarly, greater size-dependent reproductive advantages favor later maturity (all else being equal).

An interesting and relatively new application of this theory is in fisheries management. New research suggests that fishing mortality can act as a selective force leading to both plastic responses in individual traits and evolutionary change. For example, in populations of Atlantic cod (Gadus morhua), a decline in observed age and size at maturity is associated with a long history of fishing (Figure 2). Whether this represents an evolved or plastic response is still debated. However, an evolutionary change in size and age at maturity of cod may explain the fact that oc e lxmx dx

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Figure 2 Age at maturity (a) and annual growth based on length increments (b) have decreased in Atlantic cod over time in populations that have also experienced decreased expected annual adult survival (c) due to fishing. Each line represents a different region or division surveyed by the Northwest Atlantic Fisheries Organization (NAFO). Reprinted by permission from Macmillan Publishers Ltd: Nature, (Olsen EB, Heino M, Lilly GR, etal. (2004) Maturation trends indicative of rapid evolution preceded the collapse of northern cod. Nature 428: 932-935), Copyright (2004).

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Figure 2 Age at maturity (a) and annual growth based on length increments (b) have decreased in Atlantic cod over time in populations that have also experienced decreased expected annual adult survival (c) due to fishing. Each line represents a different region or division surveyed by the Northwest Atlantic Fisheries Organization (NAFO). Reprinted by permission from Macmillan Publishers Ltd: Nature, (Olsen EB, Heino M, Lilly GR, etal. (2004) Maturation trends indicative of rapid evolution preceded the collapse of northern cod. Nature 428: 932-935), Copyright (2004).

cod have not recovered despite reduced fishing mortality. Dave Conover and Steve Munch have shown a similar pattern experimentally in artificially selected populations of a small marine fish (Menidia menidia).

Current Versus Future Reproduction and the Evolution of Life Span

Another key tradeoff experienced by organisms is the tradeoff between current and future reproduction. For example, if a plant or animal invests most of their energy in their current reproductive event (e.g., produces more gametes or invests more in parental care), they may invest less energy in survival, growth, or future reproduction (Figure 3). This has led to the question of how many

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I I Perennial grasses I I Annual grasses

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o o Annual grasses a Perennial grasses

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Figure 3 Reproductive investment in annual versus perennial grasses. In general, life-history theory predicts a tradeoff between current and future reproduction. (a) A survey of 40 different species of British grasses found that reproductive effort in annual species was higher than for perennial grasses. (b) The relationship between plant size and reproductive effort also differed between annual and perennial species; annual species invest a larger portion of their energy in reproduction per year than perennial species. Reproduced from Roff DA (1992) The Evolution of Life Histories: Theory and Analysis. New York: Chapman and Hall. Redrawn from Wilson AM and Thompson K (1989) A comparative study of reproductive allocation in 40 British grasses. Functional Ecology 3: 297-302, with kind permission from Springer Science and Business Media and Blackwell Science.

times an organism should reproduce once mature. Organisms that reproduce only once are known as annual (plants) or semelparous (animals). Organisms with multiple reproductive bouts are known as perennials (plants) or iter-oparous (animals). The probability of survival at each age or size class, combined with the relationship between offspring success and size or age affects the degree of iteroparity.

Longevity and senescence (increases in age-specific mortality or decreases in reproductive rates at higher ages) are related to the tradeoff between current and future reproduction. Immense variation in life span exists, with maximum age varying across taxa from days to hundreds of years. Some of this variation can be explained by selection on current versus future reproduction and the costs and benefits associated with delayed maturity. For example, if larger and older individuals have much higher reproductive rates and mortality is relatively low, theory predicts that organisms will be selected to delay maturity and invest in future growth and survival resulting in long life span.

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Time (days)

Figure 4 The evolution of life span and mortality patterns. Linda Partridge and colleagues conducted artificial selection experiments on laboratory populations of Drosophila melanogaster (fruitflies). 'Young' lines of flies (filled circles and solid lines) were selected for early age at reproduction while 'old' lines of flies (open circles and dashed lines) were selected for late maturity. After 31 generations of selection, age-specific differences in mortality rates evolved. 'Old' lines exhibit lower mortality at intermediate ages demonstrating the evolution of mortality patterns and expected life span in response to selection. Reproduced from Partridge L, Prowse N, and Pignatelli P (1999). Another set of responses and correlated responses to selection on age at reproduction in Drosophila melanogaster. Proceedings of the Royal Society of London series B 266: 255-261, figure 3b with kind permission from The Royal Society of London.

A more puzzling question, however, is why most organisms exhibit senescence. One body of theory explains senescence as the result of tissues accumulating damage over time. Another explanation has been that selection is much stronger on earlier age classes, and thus traits expressed later in life are less strongly selected. However, the evolution of life span and the explanation of senescence itself remains an area of life-history evolution that is not fully understood. Some of the most promising research on life span and senescence has been conducted with artificial selection studies especially in Drosophila melanogaster. Linda Partridge and colleagues have shown that mortality patterns (and thus also life span) can evolve in response to differential selection on age at maturity (Figure 4).

Investment Per Offspring and the Size/Number Tradeoff

A tradeoff between energetic effort per individual offspring and total offspring number is expected because resources are limiting for virtually every organism. Furthermore, an intuitive physiological constraint on maximum gonad or brood size exists for any body size. Larger eggs or offspring may have a higher per capita chance of survival or greater expected fitness later in life. Therefore, selection on offspring number and on offspring size is expected to determine the optimal effort per offspring in a given environment (Figure 5).

Effort per offspring

Figure 5 A graphical model presented by Smith and Fretwell in 1974 that predicts the optimal tradeoff between offspring effort and offspring number for a given level of parental reproductive effort. (a) Offspring fitness for two environments. The model assumes offspring fitness is a convex function of parental effort. (b) Corresponding parental fitness for the two environments. Parental fitness is a function of offspring effort; the maximum occurs where the tangent of the curve in (a) intersects with zero. The shape of the curve in (b) is the product of the curve in (a) and by the shape of the tradeoff between offspring size and number (not shown). The model predicts a single optimal offspring size, set by the environment, that maximizes parental fitness, and that this size is 'less' than the size which maximizes offspring fitness. Much of the research on the offspring-size and -number tradeoff is rooted in these simple predictions.

The ornithologist David Lack approached this problem by assuming that as clutch size increases individual offspring survival must decrease, given that parents must feed or provision each offspring. He argued that the optimal clutch size in birds would depend on this tradeoff between offspring number and individual survival. To determine the 'Lack clutch', let Ne represent clutch size (or number of eggs laid), lf the proportion of eggs surviving, and Nf the number of offspring that survive (or the number fledged). Imagine, however, that offspring survival decreases with clutch size such that lf = 1 — cNe. Then the expected number of surviving offspring (a proxy for individual fitness) is given by

Using basic calculus, it can be shown that Ne = 1/2c maximizes Nf (Figure 6). Experiments manipulating clutch size in birds found that Lack's optimal clutch size could predict between species variation in clutch size qualitatively but that actual clutch sizes were often slightly lower than predicted. The primary explanation

Figure 5 A graphical model presented by Smith and Fretwell in 1974 that predicts the optimal tradeoff between offspring effort and offspring number for a given level of parental reproductive effort. (a) Offspring fitness for two environments. The model assumes offspring fitness is a convex function of parental effort. (b) Corresponding parental fitness for the two environments. Parental fitness is a function of offspring effort; the maximum occurs where the tangent of the curve in (a) intersects with zero. The shape of the curve in (b) is the product of the curve in (a) and by the shape of the tradeoff between offspring size and number (not shown). The model predicts a single optimal offspring size, set by the environment, that maximizes parental fitness, and that this size is 'less' than the size which maximizes offspring fitness. Much of the research on the offspring-size and -number tradeoff is rooted in these simple predictions.

Figure 6 Optimal clutch size. (a) Offspring survival as a function of clutch size for c = 0.02 (high, black line) and c = 0.05 (low, gray line). (b) Number of offspring fledged as a function of clutch size. Optimal clutch size is lower (Ne = 10) for low offspring survival than for high offspring survival (Ne = 25). For a description of the model and equations used see the text.

Clutch size (Ne)

Figure 6 Optimal clutch size. (a) Offspring survival as a function of clutch size for c = 0.02 (high, black line) and c = 0.05 (low, gray line). (b) Number of offspring fledged as a function of clutch size. Optimal clutch size is lower (Ne = 10) for low offspring survival than for high offspring survival (Ne = 25). For a description of the model and equations used see the text.

for this pattern has been that the tradeoff between current and future reproduction limits the optimal clutch size even further (see preceding section).

Sex Ratio and Sex Allocation

Another basic question in life-history theory is the relative allocation to sons or daughters in separate-sexed species and into male versus female gamete production in hermaphrodites. In general, most populations exhibit an equal primary sex ratio at birth (i.e., equal numbers of sons and daughters on average). In 1930, Fisher developed a model explaining this observation. If sons and daughters take an equal amount of energy to produce and every zygote is produced by the fusion of one male and female gamete, then it can be shown that sons have an advantage when males are rare and daughter have an advantage when females are rare. The evolutionary stable point occurs where on average individuals produce an equal number of sons and daughters at

Figure 7 Sex-allocation theory argues that the fitness of males and females is negatively frequency-dependent meaning that sons will have a fitness advantage when males are rare in the population while daughters will have greater relative fitness when females are rare in the population. The Fisherian evolutionary stable sex ratio is predicted to occur at a sex ratio of equal males and females (proportion male = 0.50).

Sex ratio (proportion male)

Figure 7 Sex-allocation theory argues that the fitness of males and females is negatively frequency-dependent meaning that sons will have a fitness advantage when males are rare in the population while daughters will have greater relative fitness when females are rare in the population. The Fisherian evolutionary stable sex ratio is predicted to occur at a sex ratio of equal males and females (proportion male = 0.50).

birth (Figure 7). However, deviations from this classic expectation are observed. For example, studies in fig wasps (where females lay eggs in figs where offspring mate before leaving) have shown that females produce more daughters than sons when they are the only females laying eggs in a single fig (thus decreasing competition among their sons to fertilize their daughters). In addition, studies on red deer have found that females in high condition are more likely to produce sons and females in poor condition are more likely to produce daughters. This pattern can be explained by the fact that daughters are able to produce offspring even if small, while small males from low-condition mothers tend to have no reproductive success (as a result of strong competition among males for access to females). Sex-allocation theory has also been able to explain the relative allocation to male and female gamete production in hermaphrodites (mainly in fish and plants) but has been less successful in explaining why any individual species is hermaphroditic instead of dioecious (separate-sexed).

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