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. 2013 Feb 19;8(2):e57133. doi: 10.1371/journal.pone.0057133

Optimal Semelparity

James W Vaupel 1,2,3, Trifon I Missov 1,4,*, C Jessica E Metcalf 5
Editor: Christof Markus Aegerter6
PMCID: PMC3576355  PMID: 23431401

Abstract

Semelparous organisms have a simple life cycle characterized by immediate death after reproduction. We assume that semelparous life histories can be separated into a juvenile non-reproductive period followed by an adult period during which reproduction is possible. We derive formulae for the optimal age and size at reproduction and for the optimal size of the offspring (e.g., seeds). Our main contribution is to determine the conditions under which the optimal size of the offspring does not depend on the optimal size at reproduction and vice versa.

Introduction, Assumptions and Notation

“Plants of any size have seeds that vary approximately 400-650-fold between species”, as authors in [1] point out; they note that “Sequoia sempervirens has a seed mass of 0.0037 gram.” Animal offspring also vary widely in size. What evolutionary factors determine the size of mature adults vs. the size of their progeny?

This question is the subject of a large body of literature. [2], [3], [4], and [1] provide useful overviews of the literature on plants. An early framework was proposed in [5] and expanded in [6]. [7] developed a different perspective with a focus on mammals. Our contribution is to build a biodemographic framework that unifies predictions about adult size and offspring size in simple, precisely-defined optimization models and to rigorously prove key implications of these models. We achieve simplicity by focusing on semelparous species, which reproduce once and die.

Evolutionary biologists have taken advantage of the simplicity of the semelparous life history. For example, demographic models have been developed to explore how stochasticity affects reproductive delays (see [8]), how variation in growth shapes plasticity in timing of reproduction (see [9]), and how the evolution of reproductive delays interacts with pre-reproductive delays such as seed-banks (see [10]). However, to date, no single analytical framework providing dynamic insights into optimal life-histories of semelparous species has been developed. There is a need for such theory to separate the effects of complexities such as changing predation regimes and resource limitation (see [11]) and stochastic environments (see [8]) from patterns driven by the general principles underlying demographic trajectories. Here we make a start at filling this gap by providing an analytical framework that unifies treatment of the two main axes of life-history variation in such species: the optimal timing of reproduction and the optimal offspring size. We focus on the simplest case of constant environments and constant population size.

The life cycle of semelparous species can be viewed as a two-phase process, driven by different mechanisms. Stage Inline graphic is a juvenile non-reproductive period, in which some individuals survive to become adults. Adults can reproduce and, when they do, they die. Hence stage Inline graphic is the period of life in which individuals seek to maximize their reproduction by weighing at each instant the benefits of delaying reproduction further against the risk of death associated with this delay. We assume size Inline graphic is the milestone between the two phases. Without loss of generality, we can further assume that size Inline graphic corresponds to adult age Inline graphic. Table 1 summarizes the basic characteristics of stage 1 vs stage 2.

Table 1. Life-Cycle Phases for Semelparous Species.

Stage Growth Mortality Reproduction
Stage Inline graphic Yes (from Inline graphic to Inline graphic) Yes No
Stage Inline graphic Yes (from Inline graphic onwards) Yes Yes

Let Inline graphic be the duration of stage 1. Let Inline graphic be the age of the organism in stage 2, age 0 in stage 2 being the age when size 1 is reached. Let Inline graphic, Inline graphic, and Inline graphic denote at age Inline graphic the organism's size, its reproductive capacity, and the force of mortality, respectively. By assumption, Inline graphic. We define reproductive capacity as the expected number of offspring that reach size 1. Let Inline graphic denote the age at which reproduction occurs. Let Inline graphic be the number of offspring produced, with each offspring (e.g., seed) being the same size Inline graphic. We consider Inline graphic. Finally, let Inline graphic, Inline graphic, be the probability that an organism born at size Inline graphic survives to size Inline graphic. Note that reproductive capacity is given by Inline graphic.

Using subscripts to denote generations, we define parental size as growing from Inline graphic to Inline graphic and offspring size as growing from Inline graphic to Inline graphic.

In this article we address three questions about semelparous organisms. First, what is the optimal age (in stage 2) at reproduction and what is the organism's size at this age? Second, what is the optimal number of offspring and what is the optimal size of each offspring? Third and most importantly, does the optimal size of an organism at reproduction Inline graphic depend on the optimal size of its offspring Inline graphic (see Fig. 1)? Our first question is what determines Inline graphic, which is assumed to be equal to Inline graphic. Our second question is what determines Inline graphic which is assumed to be equal to Inline graphic. Our third and most important question concerns the relationship between Inline graphic and Inline graphic. The assumptions we made about the separation of the two stages imply that Inline graphic and Inline graphic are independent and, similarly, Inline graphic and Inline graphic are independent. The question of interest is whether Inline graphic and Inline graphic are independent. This formulation has not been clearly developed in previous studies [12] and is a key contribution.

Figure 1. Parent and offspring size notation.

Figure 1

Semelparous Strategies: Models and Results

Optimal Age and Size at Reproduction

Stage 2, which starts once seed size no longer affects the risk of dying, is the stage of adult growth during which reproduction is possible. If reproduction occurs only at age Inline graphic in stage 2, if the chance Inline graphic of surviving to Inline graphic is constant over time and across environments, and if Inline graphic and Inline graphic are similarly constant, then the net reproduction rate Inline graphic for such semelparous species can be expressed as

graphic file with name pone.0057133.e051.jpg (1)

where Inline graphic is the rate of population growth, and Inline graphic measures reproduction at age Inline graphic; Inline graphic at any age Inline graphic other than Inline graphic is zero. This implies that

graphic file with name pone.0057133.e058.jpg (2)

[13, p189], an expression that follows directly from the Lotka equation,

graphic file with name pone.0057133.e059.jpg (3)

Proof that Inline graphic represents the growth rate in the Lotka equation is not straightforward and depends on the assumption of stable populations (see [14]), but (2) for semelparous species is true by definition. The simplicity of (2) facilitates analytical insights into optimal age at reproduction and optimal offspring size.

Solving (2) for Inline graphic yields (see [13], p.189)

graphic file with name pone.0057133.e062.jpg (4)

The value of Inline graphic that maximizes Inline graphic is the optimal age at reproduction, Inline graphic. It satisfies the condition

graphic file with name pone.0057133.e066.jpg (5)

Inserting the expression for Inline graphic from (4) into (5), using the equation for the derivative to solve for Inline graphic, and rearranging terms yields the requirement that the optimal age at reproduction, denoted by Inline graphic, must satisfy:

graphic file with name pone.0057133.e070.jpg (6)

where Inline graphic and Inline graphic. Note that Inline graphic is the relative rate of improvement in reproductive capacity at age Inline graphic, and Inline graphic is the hazard of death (force of mortality) at age Inline graphic. Substituting (4) into (6) shows that

graphic file with name pone.0057133.e077.jpg (7)

At equilibrium, Inline graphic and the optimal age at reproduction is defined by a balance between the rate of growth in reproductive capacity and the force of mortality,

graphic file with name pone.0057133.e079.jpg (8)

Note that in reality populations, especially semelparous populations, might not be always at equilibrium. We will, nevertheless, assume they are in order to illustrate the trade-off mechanism in determining the optimal timing of reproduction. From (8), reproduction should be delayed as long as the reproductive benefits of further growth outweigh the risk of mortality occasioned by delaying. The optimal age at reproduction is the age at which the benefits of further growth are exactly offset by the risk of dying. Note that Inline graphic, the duration of stage 1, does not appear in (8) and does not affect the optimal age (in stage 2) of reproduction. If the population were growing or shrinking, then Inline graphic would matter, as it would affect time to reproduction; with earlier times being favored in growing populations (see [15], [16]); and later times in shrinking populations (see [17]). In the rest of this article we focus on the equilibrium case when Inline graphic and we will use “age” to refer to age in stage 2.

The optimal size at reproduction Inline graphic is the size of the semelparous organism at the optimal age at reproduction. We assume semelparous organisms grow until they reproduce, i.e. Inline graphic is an increasing function of age (this might not always be the case as shown in [18], [19]). As a result, this optimal size can be determined by

graphic file with name pone.0057133.e085.jpg (9)

which results directly from (8) by viewing it as a necessary condition for the optimal size rather than the optimal age. That is, at the optimal size, the increase in reproduction with an increase in size multiplied by the change in size in an additional unit of time (or age) must be counterbalanced by the risk of death during that unit of time.

If environmental conditions worsen such that the rate of growth in reproductive capacity at all ages decreases, when population equilibrium is reached the new optimal Inline graphic is younger than Inline graphic. If mortality increases, the optimal age is also younger, Inline graphic. If both occur simultaneously, the optimal age is even younger Inline graphic.

Optimal Size at Reproduction in a Specific Model for Stage 2

Both (7) and (9) are true in general, whatever functional forms are used for Inline graphic and Inline graphic. Specific functional forms can be used to make more specific predictions. Mortality is a declining function of size in many species, as larger individuals may be more robust to threats such as droughts, or predation. For example, in semelparous plants, the most commonly observed pattern of mortality is declining with size (12 out of 12 species reviewed in [20]). An appropriate model could therefore be

graphic file with name pone.0057133.e092.jpg (10)

where Inline graphic and Inline graphic are constants, and Inline graphic denotes size at age Inline graphic. The parameter Inline graphic captures the causes of death that decline with size, Inline graphic captures no size dependence, and Inline graphic captures ubiquitous causes of death that are independent of size. For many plants, reproductive output scales approximately with biomass, so that allometric relationships can be fitted related seed counts to size (see [20], [21] for a review of estimates for a range of species). As a result reproductive output is generally an increasing function of size and can be modelled as

graphic file with name pone.0057133.e100.jpg (11)

where Inline graphic is a scaling parameter and Inline graphic modulates whether transforming size into reproductive output is an accelerating (Inline graphic) or saturating (Inline graphic) function. In semelparous plants, growth is generally a declining function of size, a function that has been attributed to self-shading, or declining nitrogen content of older leaves (reviewed in [20], [22]). Accordingly, an appropriate model would be

graphic file with name pone.0057133.e105.jpg (12)

where the parameter Inline graphic captures how the growth rate increases with size, and Inline graphic modulates the increase so that eventually size reaches an asymptote. For illustration, we use the exponent Inline graphic, following predictions from the fractal model of scaling (see [23]). However, using a different exponent would not alter the main conclusions of the article. This equation provides a fairly general description of asymptotic growth. If size at age Inline graphic is Inline graphic, we have

graphic file with name pone.0057133.e111.jpg (13)

where the asymptotic size is defined by Inline graphic.

Substitution of (10), (11), and (12) in (9) results in an expression for the optimal Inline graphic that is explicitly independent of the scaling parameter Inline graphic

graphic file with name pone.0057133.e115.jpg (14)

which reduces to

graphic file with name pone.0057133.e116.jpg (15)

The latter is a quartic equation for Inline graphic and its analytic solution is given by Ferrari's formula. Denoting

graphic file with name pone.0057133.e118.jpg

we can express the positive root of the quartic equation (14) in the following manner

graphic file with name pone.0057133.e119.jpg

As a result, Inline graphic increases with Inline graphic and decreases with Inline graphic (see Fig. 2). Therefore, the optimal size of reproduction Inline graphic will increase with positive changes in the reproduction scale parameter Inline graphic or the determinant of asymptotic size Inline graphic, as well as negative changes in mortality parameters Inline graphic or Inline graphic.

Figure 2. Optimal seed size with respect to A and B.

Figure 2

These mathematical results aid biological insight. Because optimal size does not depend on the parameter Inline graphic, species suffering proportional reduction in offspring production will, certibus paribus, not vary in flowering size (see [24]). An example of this might be density dependence of seed establishment (see [20]). Furthermore, if species' relative ranking with respect to asymptotic size Inline graphic, scaling of reproductive output with size Inline graphic, and mortality parameters, Inline graphic and Inline graphic, are known, relative ranking in terms of flowering size could be predicted.

Optimal Seed Size and Number

Let Inline graphic be the probability that a seed germinates and grows until initial size no longer influences mortality, i.e. to Inline graphic and size taken as Inline graphic. Generally Inline graphic increases with seed size Inline graphic. Let reproductive output i.e., number of seeds produced, be denoted by Inline graphic which is an increasing function of plant size (and age), and a decreasing function of seed size. The net reproductive rate is then

graphic file with name pone.0057133.e139.jpg (16)

If the population is in equilibrium, maximizing Inline graphic is generally equivalent to maximizing Inline graphic (see [25]). Further, in [24] it has been shown that maximizing Inline graphic provides the evolutionary stable strategy if population regulation operates on offspring establishment. Such density dependence characterizes many semelparous species (see [20]). The optimal life history is therefore defined by the derivative or relative derivative of Inline graphic being equal to zero. Hence, the optimal age at reproduction can be specified by

graphic file with name pone.0057133.e144.jpg (17)

where Inline graphic defines the rate of change in the number of offspring produced at age Inline graphic. Equation (17) implies Inline graphic, which is similar to the result obtained in (8). Note that optimal time at reproduction depends only on Inline graphic in stage 2 and does not depend on time taken by a seed to grow to Inline graphic (see [12]). The optimal offspring size is specified by

graphic file with name pone.0057133.e150.jpg (18)

where Inline graphic and Inline graphic. This implies Inline graphic. At equilibrium, optimal offspring size is the size at which the benefits accrued through investing less in each offspring and thereby producing more offspring are offset by the risk of mortality for an offspring of that size.

Optimal Seed Size in a Specific Model for Stage 1

Specific functional forms can be used to deepen understanding. The number of seeds Inline graphic of size Inline graphic produced at age Inline graphic can be determined by

graphic file with name pone.0057133.e157.jpg (19)

where parameter Inline graphic captures both saturating and accelerating functional forms of producing larger offspring. The probability of reaching size Inline graphic can be specified by a concave function

graphic file with name pone.0057133.e160.jpg (20)

where Inline graphic is the minimal possible seed size and Inline graphic accounts for the speed of reaching reference size Inline graphic. As a result, the optimal offspring size Inline graphic will be the solution of (18) i.e.

graphic file with name pone.0057133.e165.jpg (21)

Discussion

When is Optimal Seed Size Inline graphic Independent of Optimal Adult Size at Reproduction Inline graphic

Eq. (21) implies that the optimal seed size Inline graphic does not depend on the optimal plant size at reproduction Inline graphic. Using (18), it can be similarly shown that optimal plant size at reproduction does not depend on the optimal size of the seeds produced. This mutual independence holds in general if the number of seeds of size Inline graphic produced at age Inline graphic is proportional to the product of a function of adult size and a function of seed size, i.e.

graphic file with name pone.0057133.e172.jpg (22)

where Inline graphic is a scaling factor. In this case

graphic file with name pone.0057133.e174.jpg (23)

does not depend on Inline graphic and neither does Inline graphic. This is also true for

graphic file with name pone.0057133.e177.jpg (24)

Eq. (22) is a necessary and sufficient condition, in our framework, for the independence of the parent's optimal size at reproduction from the optimal seed size of its offspring. The condition is not implausible, but it is also not trivial. For instance, in (19) Inline graphic might be a function of Inline graphic: bigger plants might be more efficient at producing large seeds than smaller plants are. Also in (19), Inline graphic might be a function of Inline graphic: the relationship between plant size and reproductive capacity may be modulated by seed size.

Note that the assumptions about a juvenile vs. an adult stage imply that Inline graphic is independent of Inline graphic and Inline graphic is independent of Inline graphic (see Fig. 1). To prove independence of optimal seed size and optimal size at maturity, it is also necessary to show that Inline graphic and Inline graphic are independent. Eq. (22) gives the condition for this.

The independence of two characteristics means that the optimal value of either of them does not depend on the value of the other characteristic. This causal independence is different from lack of empirical correlation. For instance, suppose a species grows in two environments, one unfavorable (perhaps because of poor soil or lack of sunlight) and the other favorable. Then Inline graphic, the time it takes a plant to grow from seed to adult size, and Inline graphic, the time it takes for the plant to grow from adult size to size at reproduction and death, might be correlated across the two environments: e.g., both times might be long in the unfavorable environment and short in the favorable one. The long time to develop, however, does not cause the long time to mature: the unfavorable environment causes both and the correlation is merely a statistical association. As explained above, the duration Inline graphic is irrelevant to the optimization problems we addressed.

Conclusion

The simplicity of the semelparous life cycle aids formulating general mathematical models that predict key features of life histories. The analytical framework presented here unifies predictions of timing of reproduction and offspring size. This framework provides insights into how basic demographic features shape the diversity of age trajectories across species and plasticity within species in response to environmental cues. This permits separation of these patterns from complications such as variation in growth, both across individuals (see [20]) and through time (see [26]). Variants of the models may also be relevant for other life-history switches such as metamorphosis (see [27]).

Acknowledgments

We thank Hal Caswell, Kenneth Wachter, Peter Abrams, David Thomson, Joel Cohen, and Roberto Salguero-Gomez for their insightful comments on earlier versions of this paper. We also thank the two anonymous reviewers for their constructive suggestions that improved the quality of the paper.

Funding Statement

The study was funded by the Max Planck Institute for Demographic Rsearch (http://www.demogr.mpg.de). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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