Changes in lifetime reproductive success (<i>LRS</i>) evolution across a variety of trade-off weight values (<i>W</i>_<i>1</i> and <i>W</i>_<i>2</i>) for physiological trait values <i>PTV</i>_<i>1</i> and <i>PTV</i>_<i>2</i>, with <i>b</i>_<i>0</i> fixed at 0.01, the minimum rate of ageing.

<p>Changes in lifetime reproductive success (<i>LRS</i>) evolution across a variety of trade-off weight values (<i>W</i>_<i>1</i> and <i>W</i>_<i>2</i>) for physiological trait values <i>PTV</i>_<i>1</i> and <i>PTV</i>_<i>2</i>, with <i>b</i>_<i>0</i> fixed at 0.01, the minimum rate of ageing.</p

Conceptual framework for the physiological principles underlying trade-offs.

<p>(A) All trade-offs exist in the context of an <b>optimized trait</b>, usually fitness. This trait is modulated by balancing two or more <b>component traits</b> such as reproduction and survival. The genetic control of the trade-off is achieved based on allelic variation in multiple physiological traits such as DNA repair enzyme production rates. For instance, in currency 1 (energy), the rate of DNA repair enzyme production is presumably under tight genetic control with allelic variation. Greater production and use of these enzymes should increase ATP consumption, leaving less available for other tasks including gamete production. These <b>physiological traits</b> can be grouped based on the limiting factor, or “<b>currency</b>,” that they rely on (e.g. energy, carotenoids, gray boxes). Within these groups, a single net impact on reproduction and survival can be calculated because of the shared currency. Each <b>physiological trait</b> takes on a <b>value</b> (<i>PTV</i>) in each individual, assumed here to be fixed across an individual’s life. This <i>PTV</i> indicates how much the physiological trait favours reproduction <i>vs</i>. survival, as depicted by the slopes of the lines. A crucial <b>weight</b> parameter (fulcra, as positioned left-to-right), indicating how much reproduction could be gained for each unit loss in survival and <i>vice versa</i>. (B-C) Not all limiting factors are currencies, and limiting factors can (but do not always) vary in abundance (High: black, Medium: dark gray, Low: light gray lines). In (B), one limiting factor affects only reproduction (dotted lines) while the other affects only survival (dashed lines), showing that not all limiting factors need be currencies. In (C), the limiting factor is a currency trading off between reproduction and survival as indicated by the negative slope of the clines; any variation in abundance of the resource could cause positive co-variance between the fitness components [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0189124#pone.0189124.ref008" target="_blank">8</a>]. Note, however, that not all currencies vary in abundance. Time, for example, is generally available in a fixed quantity equal across individuals. (D) Clines in (B) and (C) indicate different abundances of a single currency; clines in (D) indicate different currencies. Currencies vary in how constraining they are, with currencies #2 and #3 are less constraining than currency #1. Different currencies can also have different weights (<i>W</i> in our model, Eqs <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0189124#pone.0189124.e003" target="_blank">3</a>–<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0189124#pone.0189124.e006" target="_blank">6</a>), as indicated by their slopes. Currency #3 is overall as constraining as currency #2, but its weight favours reproduction over survival, as shown by its steeper slope. In our simulations, variation in a <i>PTV</i> parameter across individuals is variation along a single cline, representing genetic variation in how the currency is invested in survival <i>vs</i>. reproduction. <i>W</i>s are fixed within a given simulation (constant slope of the cline), and constant resource availability is assumed (constant intercept of the cline). <i>W</i> is thus constant for the population, whereas <i>PTV</i> varies across individuals. (E) More realistic models of currency clines are non-linear but decline monotonically. This panel shows the relationship between fertility and expected age at death for actual curves of <i>PTV</i>s for the values of <i>W</i> as used in our models across <i>PTV</i> from -10 (bottom right) to +10 (top left). Background shading indicates the expected lifetime reproductive success <b>(</b><i>LRS)</i> based on the fertility and age at death. Selection is expected to adjust each <i>PTV</i> along its curve to the “reddest” point (highest fitness). Not all clines pass through equally high maximum fitness points. As a result, lower values of <i>W</i> are generally favoured by selection (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0189124#sec002" target="_blank">Results</a>).</p

Model parameters and their specifications.

<p>Model parameters and their specifications.</p

A summary of how multiple trade-off currencies affect evolutionary processes.

<p>This schematic presents a qualitative interpretation of our results based largely on the additive model. Under four trade-off scenarios, one or multiple lines represent currencies, the value of which (left to right; red arrow) represents the relative benefits for the fitness components reproduction and survival. Red bars represent potential values the trait might take at equilibrium/ evolutionary optimum. The position of each red bar on the line depends on the weight for that trait and on any other traits and their weights; when weights of multiple traits are equal, their bars are aligned. “Relative fitness” refers to expected fitness in the hypothetical scenario where, all else equal, individuals at evolutionary equilibrium from the four scenarios are mixed in a single population. “Trait variability” (red bars) refers to how large the role of chance and contingency is in determining final trait values. For example, a single trait has a single optimum and is under strong stabilizing selection (thus, a narrow bar). Two traits with equal weights can compensate for each other and can thus vary substantially for random reasons. When multiple traits are present, fitness is determined by the two most extreme values, which have much less variability than the others.</p

Variation of results across 100 identical simulations where <i>W</i>_<i>1</i> = <i>W</i>_<i>2</i> = 2.

<p>Because both trade-off weights are equal and far from the equilibrium value near 0.43, this parameterization allows us to examine how stochasticity and contingency might affect the physiological trait values when there should not be a tendency for one trait to evolve in a way systematically different from the other. As expected, results are similar across all four models for <i>LRS</i>. However, results are quite different for physiological trait values <i>PTV</i>_<i>1</i> and <i>PTV</i>_<i>2</i> across the four models, and there is also substantial stochastic variation within each model’s results across the 100 simulations. This confirms that both chance and the physiological details that determine trade-off functions can have major roles in determining how physiology evolves, even when life history traits are largely stable.</p

An example of a single run of our model to evaluate the effects of co-existing reproduction-survival trade-offs on the evolution of fertility, age at death and life time reproductive success.

<p>Fixing the trade-off weight <i>W</i>_<i>1</i> at 0.43 assures little evolution in <i>PTV</i>_<i>1</i> over the 500 generations; choosing a different value for <i>W</i>_<i>2</i> produces different outcomes in the two-currency scenarios. All parameters evolve differently under all four scenarios, implying important evolutionary consequences for the number of currencies and the interactions among them under the assumptions of our model (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0189124#sec006" target="_blank">Discussion</a>).</p

The five connections we investigated between, trait redness, carotenoids, immune function and oxidative stress state.

<p>The five connections we investigated between, trait redness, carotenoids, immune function and oxidative stress state.</p

Overview of the parameters included in the meta-analyses, marked with x, per association investigated.

<p>See also <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0043088#pone.0043088.s002" target="_blank">data S1</a> and text for inclusion criteria of the moderators.</p

Plot of separate overall effect sizes (±95% confidence interval) per species.

<p>An overall effect size per species was only calculated when three or more studies were available per relationship of interest. Numbers along the y-axis depict the number of effect sizes included in each overall effect size.</p

Overview of the separate meta-analyses performed.

<p>Overview of the separate meta-analyses performed.</p