In 1968, geneticist Motoo Kimura predicted that the vast majority of evolutionary changes at the molecular level are caused not by selection, but by chance: the random drift of selectively neutral mutants. Even in the absence of selection, Kimura reasoned, evolutionary change will occur as a result of chance, and this could be analysed with tools from probability theory.
The idea that selection might have little or no role in shaping some portions of the genome was not altogether new: in a famous disagreement with Ronald Fisher, Sewall Wright emphasized the importance of neutral processes such as drift as early as the 1930s. But Kimura took this idea further, offering a probabilistic method that can readily test for selective effects using data from the genome.
Mathematically, the processes that lead to neutral equilibrium can be explained with the statistician's favorite example, a bag of colored marbles. To model the effects of drift, the experimenter reaches into the bag and grabs two marbles. One is randomly tossed aside, while the other is magically duplicated. The latter (now identical) pair of marbles is put back into the bag. Starting with a bag of ten marbles, each with a different color, just a few replacements is sufficient to change all the marbles to the same (random) color. This process takes much longer with bags of 100 or 1000 marbles. Thus chance ('drift') reduces the number of colors in the bag. Mimicking the effects of mutation can counteract this process: from time to time a marble with a new color is added to the bag as replacement for a discarded marble. Neutral equilibrium is reached when the rate at which new colored marbles are added to the bag through mutation matches the rate at which existing colors are removed by drift.
The idea that selection might have little or no role in shaping some portions of the genome was not altogether new: in a famous disagreement with Ronald Fisher, Sewall Wright emphasized the importance of neutral processes such as drift as early as the 1930s. But Kimura took this idea further, offering a probabilistic method that can readily test for selective effects using data from the genome.
Mathematically, the processes that lead to neutral equilibrium can be explained with the statistician's favorite example, a bag of colored marbles. To model the effects of drift, the experimenter reaches into the bag and grabs two marbles. One is randomly tossed aside, while the other is magically duplicated. The latter (now identical) pair of marbles is put back into the bag. Starting with a bag of ten marbles, each with a different color, just a few replacements is sufficient to change all the marbles to the same (random) color. This process takes much longer with bags of 100 or 1000 marbles. Thus chance ('drift') reduces the number of colors in the bag. Mimicking the effects of mutation can counteract this process: from time to time a marble with a new color is added to the bag as replacement for a discarded marble. Neutral equilibrium is reached when the rate at which new colored marbles are added to the bag through mutation matches the rate at which existing colors are removed by drift.
Drift through random sampling. Creative Commons Attribution-Share Alike 3.0 Unported license.
In genetics, the neutral theory was hotly debated for decades. As Kimura observed in his 1968 paper, the prevalent view in the 1960s held that almost all mutations are under selection, and this opinion was slow to change. But as Stephen J. Gould wrote in 1989,
"[t]hese equations give us for the first time a baseline criterion for assessing any kind of genetic change. If neutralism holds, then actual outcomes will fit the equations. If selection predominates, then results will depart from [neutral] predictions."
This eventually led to a dramatic reversal in the way selection is viewed in molecular biology: geneticists now infer selection only when it can be shown that the assumption of neutrality has been violated. The success of the neutral theory triggered a shift in perspective, from the fitness of individual units of selection, to the population-level consequences of both selection and drift.
But is the neutral theory relevant above the molecular level? Theoretical ecologists began to consider this question in the 1990s. Previously, the prevalence of species in ecological communities was approached from a pan-selectionist perspective too: what are the special attributes of each species that explain its abundance in a given environment? Neutral theory offered an alternative hypothesis. If one assumes that species do not differ in their competitive abilities, what would the prevalence of species be if the diversity depended only on the size of the total ecological community and the chance arrival of new species? In other words, do neutral processes of drift and replacement largely govern the formation and persistence of ecological communities? This question became one of the most hotly debated topics in theoretical ecology (Harte 2003; Alonso, Etienne and McKane 2006). Mathematically, the neutral theory in ecology is faithful to its origins in genetics, with both relying on the same underlying mathematical model.
Although the scope of the neutral theory in ecology is still being tested, a shift is under way from the assumption of pan-selectionism to the view that selection can only be inferred by showing departure from a null model of neutrality. As in genetics, this represents a change in the level of analysis, from the fitness of individuals to the effects of selection at the community level. As Kimura wrote in 1983, "it is easy to invent a selectionist explanation for almost any specific observation; proving it is another story. Such facile explanatory excesses can be avoided by being more quantitative."
In anthropology, comparisons of genetic data at the scale of communities and islands – rather than individuals – make it possible to detect changes in social structure and culture over very long time scales. In the two models illustrated below, we explore genetic data to pursue a new question: the role of Darwinian selection in social life.
Many studies have argued that reproductive skew biased toward dominant or high-ranking men is very common in human communities: "In more than one hundred well studied societies, clear formal reproductive rewards for men are associated with status: high-ranking men have the right to more wives" (Clarke and Low 2001). Demographic statistics collected over short time scales support these claims. However, although variation in male fitness is known to occur, an important unanswered question is whether such differences are heritable and persist long enough to have evolutionary consequences at the population level. If not, selection is ruled out as the cause. Our genetic data from the islands offered a chance to analyse changes in the strength and persistence of reproductive skew in 41 communities, scattered across half a dozen islands.
Unsurprisingly, we find that the role of Darwinian selection in social life is a question for which genetic data is particularly well suited. But while the methods we use originated in molecular biology, they can also be applied to processes of change in which genetics plays no role. For example, archaeologists are often interested in understanding changes in the distribution of artifacts like tools or ceramics. Similarly, ecologists may wish to know whether differences in the prevalence of species in a region are due to selection or simply to chance. And sociologists might wonder whether generational changes in phenomena like the popularity of children's names are under active selection. We examine all three of these cases, not merely as illustrations of the basic concepts, but to explore how models can be adapted to diverse empirical questions. While the conceptual framework for distinguishing selection from drift is simple and intuitive, estimating the strength and power of these processes in specific cases is a little more complicated. Hence we have two goals for this exercise: first, to test whether male dominance is under selection in Indonesian communities, and second, to explore how selection can be detected in other kinds of evolving populations.
"[t]hese equations give us for the first time a baseline criterion for assessing any kind of genetic change. If neutralism holds, then actual outcomes will fit the equations. If selection predominates, then results will depart from [neutral] predictions."
This eventually led to a dramatic reversal in the way selection is viewed in molecular biology: geneticists now infer selection only when it can be shown that the assumption of neutrality has been violated. The success of the neutral theory triggered a shift in perspective, from the fitness of individual units of selection, to the population-level consequences of both selection and drift.
But is the neutral theory relevant above the molecular level? Theoretical ecologists began to consider this question in the 1990s. Previously, the prevalence of species in ecological communities was approached from a pan-selectionist perspective too: what are the special attributes of each species that explain its abundance in a given environment? Neutral theory offered an alternative hypothesis. If one assumes that species do not differ in their competitive abilities, what would the prevalence of species be if the diversity depended only on the size of the total ecological community and the chance arrival of new species? In other words, do neutral processes of drift and replacement largely govern the formation and persistence of ecological communities? This question became one of the most hotly debated topics in theoretical ecology (Harte 2003; Alonso, Etienne and McKane 2006). Mathematically, the neutral theory in ecology is faithful to its origins in genetics, with both relying on the same underlying mathematical model.
Although the scope of the neutral theory in ecology is still being tested, a shift is under way from the assumption of pan-selectionism to the view that selection can only be inferred by showing departure from a null model of neutrality. As in genetics, this represents a change in the level of analysis, from the fitness of individuals to the effects of selection at the community level. As Kimura wrote in 1983, "it is easy to invent a selectionist explanation for almost any specific observation; proving it is another story. Such facile explanatory excesses can be avoided by being more quantitative."
In anthropology, comparisons of genetic data at the scale of communities and islands – rather than individuals – make it possible to detect changes in social structure and culture over very long time scales. In the two models illustrated below, we explore genetic data to pursue a new question: the role of Darwinian selection in social life.
Many studies have argued that reproductive skew biased toward dominant or high-ranking men is very common in human communities: "In more than one hundred well studied societies, clear formal reproductive rewards for men are associated with status: high-ranking men have the right to more wives" (Clarke and Low 2001). Demographic statistics collected over short time scales support these claims. However, although variation in male fitness is known to occur, an important unanswered question is whether such differences are heritable and persist long enough to have evolutionary consequences at the population level. If not, selection is ruled out as the cause. Our genetic data from the islands offered a chance to analyse changes in the strength and persistence of reproductive skew in 41 communities, scattered across half a dozen islands.
Unsurprisingly, we find that the role of Darwinian selection in social life is a question for which genetic data is particularly well suited. But while the methods we use originated in molecular biology, they can also be applied to processes of change in which genetics plays no role. For example, archaeologists are often interested in understanding changes in the distribution of artifacts like tools or ceramics. Similarly, ecologists may wish to know whether differences in the prevalence of species in a region are due to selection or simply to chance. And sociologists might wonder whether generational changes in phenomena like the popularity of children's names are under active selection. We examine all three of these cases, not merely as illustrations of the basic concepts, but to explore how models can be adapted to diverse empirical questions. While the conceptual framework for distinguishing selection from drift is simple and intuitive, estimating the strength and power of these processes in specific cases is a little more complicated. Hence we have two goals for this exercise: first, to test whether male dominance is under selection in Indonesian communities, and second, to explore how selection can be detected in other kinds of evolving populations.
References:
Alonso D, Etienne R, McKane A. 2006. The merits of neutral theory. Trends in Ecology and Evolution 21:451-7.
Clarke AL, Low BS. 2001. Testing evolutionary hypotheses with demographic data. Population and Development Review 27:633-60.
Gould SJ. 1989. Through a lens, darkly: do species change by random molecular shifts or natural selection? Natural History 98:16-24.
Harte J. 2003. Tail of death and resurrection. Nature 424:1006-7.
Kimura M. 1968. Evolutionary rate at the molecular level. Nature 217:624-6.
Kimura M. 1983. The Neutral Theory of Molecular Evolution. Cambridge University Press, p xiv.
Alonso D, Etienne R, McKane A. 2006. The merits of neutral theory. Trends in Ecology and Evolution 21:451-7.
Clarke AL, Low BS. 2001. Testing evolutionary hypotheses with demographic data. Population and Development Review 27:633-60.
Gould SJ. 1989. Through a lens, darkly: do species change by random molecular shifts or natural selection? Natural History 98:16-24.
Harte J. 2003. Tail of death and resurrection. Nature 424:1006-7.
Kimura M. 1968. Evolutionary rate at the molecular level. Nature 217:624-6.
Kimura M. 1983. The Neutral Theory of Molecular Evolution. Cambridge University Press, p xiv.