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I have conducted a lab with my IB Biology 11 class, regarding changes in allele frequencies within generations overseeing the natural selection of an advantageous phenotype. We were looking to conclude some sort of link between the changing allele frequencies and an overall changing population number of the species. Lab results saw, that as the frequency of the advantageous phenotype increased, the total population dipped and then increased after the 3rd generation. Can anyone point out any possible reasons as to why this occurred - regarding any factors at all? The image below depicts frequency of the advantageous allele vs total population.
This is pretty basic, should have learned it in year one bud, but, here… everyone should be able to decipher this.
You can also use Calculus to solve this.
Edit: The dip was most likely because natural selection often has a bit of a delay until it becomes advantageous to the population. Otherwise, the increase should continue if you go on to further generations.
- A gene pool is the sum of all the alleles (variants of a gene) in a population.
- Allele frequencies range from 0 (present in no individuals) to 1 (present in all individuals) all allele frequencies for a given gene add up to 100 percent in a population.
- The smaller a population, the more susceptible it is to mechanisms like natural selection and genetic drift, as the effects of such mechanisms are magnified when the gene pool is small.
- The founder effect occurs when part of an original population establishes a new population with a separate gene pool, leading to less genetic variation in the new population.
- allele: one of a number of alternative forms of the same gene occupying a given position on a chromosome
- gene pool: the complete set of unique alleles that would be found by inspecting the genetic material of every living member of a species or population
- founder effect: a decrease in genetic variation that occurs when an entire population descends from a small number of founders
Lewontin’s Paradox Resolved? In Larger Populations, Stronger Selection Erases More Diversity
Copyright: © 2015 Roland G. Roberts. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Competing interests: The author has declared that no competing interests exist.
Genetic variety is the spice of life—and it can also be the raw material upon which natural selection works its magic, shaping organisms to fit their circumstances. But there’s also the “dark matter” of genetic variation—neutral genetic diversity—that distinguishes individual genomes within a species from each other, but that has no impact on fitness. Despite its relative unimportance for evolution itself, neutral genetic diversity is of great interest to evolutionary biologists. It provides us with an unbiased picture of the history and population dynamics of a species, acting as a null hypothesis against which the effects of selection can be seen.
Under a simplistic neutral model (i.e., in the absence of selection), theoreticians might expect genetic diversity to scale in proportion to the total number of individuals in a population—a quantity known as the census population size. However, more than 40 years ago, the American evolutionary biologist Richard Lewontin noted that while population sizes of different species can vary across many orders of magnitude, the amount of neutral genetic diversity doesn’t, and indeed has no simple relationship to population size. How can this be?
This observation, which is often known as Lewontin’s paradox, has troubled theoretical and empirical biologists alike, and several potential explanations have been posited. In a new study just published in PLOS Biology, Russell Corbett-Detig, Daniel Hartl, and Timothy Sackton present persuasive empirical evidence for one mechanism that has had strong theoretical support but has hitherto been hard to put to the test—that natural selection is responsible for obliterating the expected relationship between diversity and population size.
When a genetic variant arises that confers a strong advantage on the host organism, natural selection ensures that its frequency will increase in the population, perhaps eventually becoming predominant. However, genes aren’t passed down the generations in isolation instead, each is inherited along with sizeable chunks of neighbouring genomic regions. These genomic chunks are only broken up by the process of meiotic recombination, in which sexual organisms shuffle their two inherited genomes before passing them on to their offspring. Crucially, the consequence of this chunkiness is that selection, by acting on one functional variant, can also inadvertently change the frequency of tens or even hundreds of nearby neutral variants—a phenomenon known as hitchhiking. Thus, the effect of selection on a functional variant is to reduce the diversity of its genomic neighbourhood. A corresponding reduction in diversity is also seen around disadvantageous variants a process known as background selection. Could these diversity-erasing effects of selection explain Lewontin’s paradox?
To address this, the authors took advantage of something that would have been inconceivable when Lewontin was writing: a massive accumulated wealth of genomic sequence diversity data from a wide range of organisms. They were able to select 40 plants and animals for which sufficient diversity data—plus a high-quality map of meiotic recombination rates—were available. Ranging from silkworm moth to watermelon and from baboon to orange (see Fig. 1), the authors believe that this is one of the largest comparative population genetics dataset ever assembled.
We consider a finite strictly asexual haploid population (with constant population size N) that comprises 10 subpopulations, each of which has N/10 individuals and a different mutation rate, with everything else equal. The rationale of the method is that these subpopulations compete for existence under natural selection and random drift. At the end of a simulation, only one subpopulation remains and the rest are extinct. The mutation rate of the remaining population becomes the "fixed" mutation rate in that competition. By simulating the process many times, we can define the most frequently fixed mutation rate as the "optimum" mutation rate.
Each of the ten subpopulations is assigned with a distinct mutation rate per genome per generation (see parameters). Both deleterious and beneficial mutations occur in each subpopulation with fractions for beneficial and deleterious mutations represented by p b and p d (i.e. 1- p b ), respectively. The effects (selection coefficients) of both beneficial and deleterious mutations are drawn from continuous probability distributions. We denote s b as the effects of beneficial mutations (in which case fitness w is increased by a factor 1+ s b ), while s d represents the effects of deleterious mutations (in which case fitness w is decreased by a factor 1- s d ).
We assume that s b follows an exponential distribution: f ( s b , λ ) = λ e − λ s b with 1/λ as the mean value of the distribution. This assumption has good theoretical support from extreme-value theory and has been widely used in population genetics models [22–24]. The effects of deleterious mutations may be complex and no general assumption yet exists about the distribution of s d in analytical calculations however, empirical studies support a gamma distribution with shape parameter smaller than one (other distributions are not necessarily excluded)[25, 26]. In the present study, we assume that s d follows a skewed gamma distribution f ( s d , α , β ) = s d α − 1 e − s d / β / ( β α Γ ( α ) ) (α≤1). The gamma distribution used in our simulations is truncated with the value 1.0, which is necessary to avoid producing a negative fitness. In addition, we assume that the mean effects of beneficial mutations ( s b ¯ ) are much smaller than the mean effects of deleterious ones ( s d ¯ ), which seems to be reasonable in most cases [27, 28].
In our simulations, the sizes of fractions and effects of both beneficial and deleterious mutations are the most important quantitative parameters. Numerous experimental studies on microbes have shed some light on this area and some estimates of these parameters are summarized in Table 1[29–35]. These data provide the best available assumptions of parameters used in the simulations. One example of the distribution of mutation effects and the corresponding fitness variation caused by mutations we adopt is shown in Figure 1. Another essential parameter involved in the simulations is the mutation rates initially assigned to the ten subpopulations. And the logarithmic form of the mutation rates (lg(U)) is roughly uniformly distributed between -4 and -1. In addition, we adopt several ranges consisting of different mutation rates, which are shown in Table 2, to see if this initial range influences the optimum mutation rate.
One example of distribution of mutation effects. (A) The effects of deleterious mutations follow a gamma distribution with α = 0.6 (shape parameter), β = 0.5 (scale parameter) and the mean effects is s ¯ d = 0.3 . (B) The effects of beneficial mutations follow an exponential distribution with λ = 100 and the mean effects is s ¯ b = 0.01 . (C) The distribution of fitness changes by both deleterious and beneficial mutations with p d = 97% and p b = 3%.
Throughout the study, we assume that generations are discrete and non-overlapping. In each generation, the number of new mutations (m) appearing in an individual belonging to the i-th subpopulation is drawn from a Poisson distribution p ( m , U i ) = U i m e − U i i / m ! , where U i is the genome mutation rate of the i-th subpopulation. The deleterious mutation rate is then given by U i ×p d and the beneficial mutation rate is U i ×p b . Given that a deleterious (or beneficial) mutation occurs, the fitness w of the individual is decreased (or increased) by 1- s d (or 1+ s b ), where s d (or s b ) is randomly drawn from a gamma (or exponential) distribution. Here, we assume that no epistasis occurs therefore, all mutations have independent effects on fitness and act multiplicatively. It is possible that an individual may carry multiple mutations within a single generation. In this case, the fitness of an individual in the n-th generation (w n ) is a function of the mutation numbers the individual carries (m), their mutation effects (s j ), and the fitness of its parent in the (n-1)-th generation (w n-1 ). This function can be described as
Offspring are sampled with repetition according to a multinomial distribution, weighted by the fitness of their respective parent. We label each offspring with a unique identifier for its particular subpopulation.
We trace the numbers of individuals of each subpopulation until the population size of one subpopulation reaches N and the sizes of other subpopulations become zero. At this point, the process is stopped and the corresponding mutation rate of the remaining subpopulation is recorded. In addition, the number of generations one competition takes is also traced. We run simulations that vary both the population size and the mutation effects to evaluate how and to what extent these influence the competition results (see Results). Some initial conditions of the population are also relaxed to test the robustness of the method (see Discussion).
How does population size affect the intensity of natural selection or fixation of alleles?
Genetic drift has a clear effect on small populations, by random chance certain alleles beneficial or not may get fixed or eliminated. Does population size dictate the intensity of natural selection?
Nice entry with links to various detailed effects and terms.
In larger populations, there is a larger gene pool, meaning that it would take more time for natural selection to show its affect and cause fixation of alleles than in a smaller population. Think about it in this way: There are two phenotypes in a bird species living in darker shrubbery. One phenotype is dark-feathered, while the other is light-colored feathers. In a small population (say 3 dark-feathered birds and 1 light-feathered), the light-feathered bird would likely be eliminated by predators more quickly than the others because it doesn't match the darker colored habitat. The "light-feathered allele" has been removed from the population. So from now on, the "dark-feathered allele" is all that remains: dark-feathered birds from now on. In a larger population (say 35 dark-feathered birds and 15 light-feathered birds), it would take more time for the "light-feathered allele" to be removed from the population.
TLDR: Population size dictates the time it takes for natural selection to become evident in a population.
Does population size dictate the intensity of natural selection?
I'm not sure if I understand exactly what you mean by the intensity of natural selection. Could you elaborate a bit more? I'll try to answer your question regardless.
Intensity of natural selection aside, population size is still a factor to be considered. For example lets say you have a parent population of 2 individuals, one being homozygous for a dominant form of a trait (AA) and the other homozygous for the recessive form of the same trait (aa). Most of their offspring would wind up being heterozygous for the trait (Aa), and phenotypically, almost all of them would exhibit the dominant form of the trait basically if everything happened perfectly you should always wind up with 25% of their offspring being homozygous recessive, 50% being heterozygous, and 25% being homozygous dominant. If those two parents were to produce two child populations, one small (consisting of only 4 individuals) and the other large (consisting of 16 individuals), then the larger population is more likely to be representative of the actual gene pool by that I mean it’s more likely that close to 25% of the individuals will be homozygous recessive, 25% of the individuals will be homozygous dominant, and 50% will be heterozygous. Simply put, more individuals means that the distribution of genes becomes less random even though each individuals has roughly the same chance of being born with a given genotype as any other individuals, more individuals means a more complete picture of what is there.
So let’s apply this to natural selection. Say for example we have a population of moths, and their wings can either be white or black for the sake of the example let’s say that white wings are dominant (AA) and have historically been advantageous, while black wings are recessive (aa) and have been disadvantageous. If suddenly some disaster happened that made the black wings advantageous, then a larger population of the moths would likely be able to survive better than a smaller population. While a greater number of individuals would die in the larger population, more individuals would likely have black wings which makes them more likely to survive and produce offspring that exhibit the same trait. This could lead to some serious problems later on since the surviving population would no longer be representative of the parent population and would be substantially less diverse than the parent population basically becomes a problem in the same way that a smaller population would have been an issue from the get go, only now it's not so much that the genes are present in the population and just not being expressed, so much as it is that the genes aren't present any more.
A larger sample size means a greater probability that the sample is representative of the population while it means more individuals with the dominant phenotype, it should also mean more individuals with the recessive phenotype.
Aside from genetics, population size affects a number of different things such as intraspecific competition. More individuals means more resource use, and since resources are more or less fixed in any given system, it leads to an increase in intraspecific competition for said resources. Increased competition can then lead to things like increased specialization, which can eventually lead to increased speciation provided that the each sub population neither breeds with each other nor the parent population. Even then, all of that depends on the availability of niches, the intensity of interspecific competition for said niches, and other factors such as rates of predation. In this sense, population size doesn’t really dictate any one thing alone, so much as it inter-relates with a number of other different factors in various different ways.
Impact of Natural Selection on Population Size - Biology
Bottlenecks and founder effects
Genetic drift can cause big losses of genetic variation for small populations.
Population bottlenecks occur when a population's size is reduced for at least one generation. Because genetic drift acts more quickly to reduce genetic variation in small populations, undergoing a bottleneck can reduce a population's genetic variation by a lot, even if the bottleneck doesn't last for very many generations. This is illustrated by the bags of marbles shown below, where, in generation 2, an unusually small draw creates a bottleneck.
Reduced genetic variation means that the population may not be able to adapt to new selection pressures, such as climatic change or a shift in available resources, because the genetic variation that selection would act on may have already drifted out of the population.
An example of a bottleneck
Northern elephant seals have reduced genetic variation probably because of a population bottleneck humans inflicted on them in the 1890s. Hunting reduced their population size to as few as 20 individuals at the end of the 19th century. Their population has since rebounded to over 30,000 but their genes still carry the marks of this bottleneck: they have much less genetic variation than a population of southern elephant seals that was not so intensely hunted.
A founder effect occurs when a new colony is started by a few members of the original population. This small population size means that the colony may have:
- reduced genetic variation from the original population.
- a non-random sample of the genes in the original population.
For example, the Afrikaner population of Dutch settlers in South Africa is descended mainly from a few colonists. Today, the Afrikaner population has an unusually high frequency of the gene that causes Huntington's disease, because those original Dutch colonists just happened to carry that gene with unusually high frequency. This effect is easy to recognize in genetic diseases, but of course, the frequencies of all sorts of genes are affected by founder events.
Impact of Natural Selection on Population Size - Biology
The relationship between population size and the rate of evolution is important
Many factors affect this relationship, sometimes in counterintuitive ways
We synthesise the theoretical and empirical studies of this relationship.
Does evolution proceed faster in larger or smaller populations? The relationship between effective population size (Ne) and the rate of evolution has consequences for our ability to understand and interpret genomic variation, and is central to many aspects of evolution and ecology. Many factors affect the relationship between Ne and the rate of evolution, and recent theoretical and empirical studies have shown some surprising and sometimes counterintuitive results. Some mechanisms tend to make the relationship positive, others negative, and they can act simultaneously. The relationship also depends on whether one is interested in the rate of neutral, adaptive, or deleterious evolution. Here, we synthesize theoretical and empirical approaches to understanding the relationship and highlight areas that remain poorly understood.
I suggest that minimizing the impact of sport hunting on the evolution of hunted species should be a major preoccupation of wildlife managers.Marco Festa-Bianchet (18)
Like fishery managers, wildlife managers have typically placed a primary emphasis on the demographic consequences of hunting, with little direct consideration of potential evolutionary effects (51). European wildlife managers have paid more attention than their North American counterparts to the selective effects of hunting, and hunting in Europe has often targeted specific phenotypic characteristics of game as a result, European hunting regulations are typically more specific than American regulations (18, 52).
Game and especially trophy hunting generally differ from fishing in several ways. For example, key aspects of the life histories of the 2 groups of animals often differ. Game hunting often focuses on animals with relatively low reproductive output, and relatively low natural mortality rates many fishes have higher fecundities and higher natural mortality rates than game animals. We expect that hunting selection could have a considerable effect on the evolution of adult characteristics, particularly those in prime-aged adults under sexual selection because hunting mortality is often substantially higher than natural mortality for adult game animals (18, 53).
Virtually all hunting invokes selective elements of some kind. These elements are often associated with particular phenotypic characteristics such as body size, coat color, and weapons or ornaments such as horns and antlers. As is the case for fishing, hunting for many animals can produce the paradoxical situation of selecting against the traits that are preferred by hunters (18). Because variation in many of these traits has an appreciable genetic component (54 ⇓ ⇓ –57), such selection is likely to produce detectable evolutionary responses that reduce the ability of breeders with desirable characteristics to contribute to reproduction (58). Harris et al. (52) argued that available information is sufficient to recommend hunting patterns that minimize deviations of sex- and age-specific mortality rates from natural mortality rates.
Harris et al. (52) and Allendorf et al. (6) identified 3 primary genetic consequences of hunting: alteration of population structure, loss of genetic variation, and evolution resulting from selection. These general consequences apply to all forms of human exploitation. An early study by Voipio (59) was one of the first to show that the genetic consequences of selective hunting were likely to vary with the phenotypic characteristics of the hunted animals. In a simple, discrete-locus simulation of harvest of antlered male red deer (Cervus elaphus), Thelen (60) demonstrated how the frequency of alleles influencing large antler size, and therefore the yield of trophy males, would decline under different harvest management strategies. With regard to the loss of genetic diversity that can result from hunting mortality, Harris et al. (52) and Allendorf et al. (6) focused on the relationship between harvest and decline in heterozygosity or allelic diversity and how they are reflected in reduced effective population size (Ne) and the ratio of Ne to census size (Nc). These metrics are important indicators of a population's evolutionary potential, and substantial reductions in them can indicate unsustainable practices.
Several key population characteristics can affect genetic variability and adaptive potential. In most ungulates, for example, breeding population size, generation length and adult longevity, and mating structure, including the breeding sex ratio and harem size, can have a large influence on the dynamics of genetic and phenotypic variation under exploitation (61 ⇓ ⇓ –64). Exploitation tends to skew the breeding sex ratio (65) and reduce adult longevity, especially of males, and mean male reproductive success and variance in progeny number per family. However, sex ratio can also be sensitive to population density (66, 67). These factors have a direct influence on Ne. If the mean generation length differs for males and females, which is common for several of these species, exploitation can also contribute to a reduction in Ne. The consequences of reduced Ne for adaptive potential can be serious, but they depend critically on the characteristics of the life history (68).
The reduction in the frequency of the silver morph in the red fox (Vulpes vulpes) between 1834 and 1933 in eastern Canada was perhaps the first documented change over time resulting from selective harvest (69). J. B. S. Haldane used these data to provide one of the first estimates of the strength of selection in a wild population using his then recently developed mathematical models of the effects of selection on a single locus (70). The fur of the homozygous silver morph (RR) was worth approximately 3 times as much as the fur of the cross (Rr) or red (rr) fox to the furrier, and, therefore, was more likely to be pursued by hunters. The fur of the heterozygous cross fox (Rr) was smoky red and was classified as red in the fur trade. The frequency of the desirable silver morph declined from ≈16% in 1830 to 5% in 1930 (Fig. 2). Haldane (70) concluded that this trend could be explained by a slightly greater harvest rate of the silver than the red and cross phenotypes. The lines in Fig. 2 show the expected change in phenotypic frequencies, assuming that the relative fitness of the silver phenotype was 3% less than both the red and cross phenotypes, and the generation interval was 2 years.
Reduction in frequency of the silver morph of the fox in eastern Canada resulting from the preferential harvest by hunters of the more valuable silver morph (69, 70). The points represent data presented by Elton (69). The lines represent the expected change in frequencies of the 3 phenotypes via selection at a single locus assuming that the silver fox morph has a 3% survival disadvantage per generation relative to the red and cross morphs. The initial frequency of the R allele was 0.3 and the mean generation interval was 2 years (70).
For roe deer, Hartl et al. (71) concluded that the intensity of harvest influenced the degree of selection against large body size, larger number of antler points and yearling males with small spikes harvest intensity also affected the length of the antler main beam and produced changes in allele frequencies (see also 72). For mountain sheep, Coltman et al. (2) showed that harvest of trophy rams led to selection for lighter and smaller-horned rams. Different hunters invoke different methods in being selective, and Martínez et al. (73) argued that the urge for hunters to kill males with large antlers and to maximize opportunity to be selective by hunting early in the season were primary motivations. Mysterud et al. (74) found that hunter type (local vs. “foreign”) provided substantial variation in terms of temporal and spatial components of hunting activity, and that although the activities of the different hunter types influenced the relationship between age and antler mass, much of this influence arose from variation in the timing and location of hunting.
In their simulation of the evolution of exploited red deer, Hard et al. (75) found that selective hunting could reduce Ne and Ne/Nc if annual hunting mortality of males is high enough (>25–30%), and they concluded that reducing hunting mortality on males to keep breeding stag:hind ratios during the rut sufficiently high (≥18 stags:100 hinds) is important to maintain adequate Ne and, therefore, long-term adaptive potential. They also found that size-selective hunting is likely to result in only modest short-term evolutionary changes in life-history traits unless the annual harvest rate on males is high (>30%) or realized genetic variance components were large.
Coltman et al. (2) used a quantitative genetic analysis of a reconstructed pedigree for a wild population of Canadian bighorn sheep to show how hunting selection affected body weight and horn size. They showed that selection was most intense against rams with high breeding values because of hunter preference for large rams with large horns, with the consequence that breeding values for both ram traits declined steeply over 35 years. Because both traits are highly heritable and positively genetically correlated (2), continued selection against large rams with large horns is expected to directly reduce horn size with a correlated response in reduced body mass. Such selection will reduce the frequencies of these phenotypes to lower levels, with likely adverse consequences for male breeding success. Both ram weight and horn size are undoubtedly subject to sexual selection through male-male competition during the rut, but it is unclear to what extent such sexual selection can alter the rate of evolution under hunting selection because sexual selection gradients have not been estimated. However, they must be high for some heavily hunted populations, where heritabilities for traits under selection are high and observed temporal declines in breeding values for these traits are often substantial (e.g., ref. 2). Garel et al. (76) found similar patterns in morphology and life history resulting from trophy ram hunting in Europe.
Misconceptions About Natural Selection
Natural selection is easy to understand, but it is misunderstood much too often. Natural selection is not synonymous with evolution. Evolution refers to any genetic change in a population, whereas natural selection specifies one particular way in which such changes are brought about. Natural selection is the most important agent of evolutionary change simply because it results in adaptation of an organism to its environment. Other possible mechanisms of evolution besides natural selection include gene flow, meiotic drive, and genetic drift.
A persistent misconception is that natural selection occurs mainly through differences between organisms in death rates, or differential mortality. Differential mortality can be selective but only to the degree that it creates differences between individuals in the number of reproductive offspring they produce. Reproductive rate, rather than death rate, drives natural selection. A cautious tomcat that seldom crosses busy streets might live to a ripe old age without leaving behind as many descendent kittens as another less staid tomcat killed on a highway at a much younger age. If the short-lived cat leaves more descendants, its genes will spread faster than those of the long-lived cat, and natural selection will favor a short life span. Unless living longer allows or results in higher reproductive success, long life is not favored by natural selection.
Adaptations fashioned by natural selection suit an organism to its particular environment. For instance, a maple tree's broad leaves are well adapted to temperate climates, but unsuited to arctic cold. Similarly, a human's ability to store fat is an adaptation to environments in which fat is scarce, but is poorly suited to the modern fast-food environment. In this respect, natural selection is somewhat shortsighted, since it cannot "see" beyond the next generation.
Natural selection cannot preferentially create favorable variations, but instead must work with what is at hand. For instance, treatment with antibiotics does not create antibiotic-resistant mutants. Instead, it favors microbes that, by chance, already have genes for resistance.
Phrases such as "the struggle for existence" and "survival of the fittest" have had an unfortunate consequence. They tend to emphasize predation and fighting for food as the prevalent means of selection. This reinforces erroneous emphasis on differential death rates, with the strongest and fastest individuals being considered as having a selective advantage over weaker and slower individuals. But if this were true, every species would continually gain in strength and speed.
Because this is not happening, selection against increased strength and speed (counterselection) must be occurring and must limit the process. Animals can sometimes be too aggressive for their own good an extremely aggressive individual may spend so much time and energy chasing its prey that it spends less than average time and energy on mating and reproduction, and as a result, leaves fewer offspring than average. Likewise, an individual could be too submissive and spend too much time and energy running away from others. Usually, intermediate levels of aggressiveness result in the highest fitness.
Natural selection does not operate ȯor the benefit of the species." Birds lay fewer eggs during drought years. Is this because competition for limited food supplies would be detrimental to the species, and do birds hold back ȯor the good of their species"? Such arguments have a fatal flaw: Ȭheaters" that laid as many eggs as possible would reap a higher reproductive success than individuals that voluntarily decreased their clutch size. Over time, cheater genes would spread through a population, and genes for holding-back would become rare.
However, the same phenomenon can be interpreted more plausibly in terms of natural selection at the level of individuals. During droughts, parental birds cannot bring as many insects to their nest and therefore cannot feed and fledge as many chicks as they can when food supplies are more ample. Laying extra eggs means most chicks would die of starvation. Birds can actually leave more surviving offspring to breed in the next generation by laying fewer eggs.
Any individual that sacrifices its own reproductive success for the benefit of a group is at a selective disadvantage within that group to any other individual not making such a sacrifice. Classical selection will always favor individuals that maximize their own selfish reproductive success. Natural selection recognizes only one currency: babies. Although we might wish otherwise, beauty, brains, or brawn need not be favored unless such traits are translated into more offspring than average. If ugly, dumb, weak individuals pass on more genes, those traits will prevail in future generations.
Whenever one organism leaves more successful offspring than others, in time its genes will come to dominate the population gene pool. Ultimately, natural selection operates only by differential reproductive success. An individual's ability to perpetuate itself as measured by its reproductive success is known as its Darwinian fitness.