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Evolution is About Populations, But Its Causes are About Individuals

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Let me be that I am and seek not to alter me.

William Shakespeare, Much Ado About Nothing

Abstract

There is a tension between, on the one hand, the view that natural selection refers to individual-level causes, and on the other hand, the view that it refers to a population-level cause. In this article, I make the case for the individual-level cause view. I respond to recent claims made by McLoone that the individual-level cause view is inconsistent. I show that if one were to follow his arguments, any causal claim in any context would have to be regarded as vindicating a form of population-level cause view. I show why this is implausible and how a consistent individual-level cause position can be held within the interventionist account of causation. Finally, I argue that there is one sense in which natural selection might be said to refer to population-level causes of evolutionary change. The upshot is that, as noted by others, natural selection can be regarded as referring to a population-level cause in the context of frequency-dependent selection and other situations of fitness-altering interactions between the individuals of a population. But whether this statement is true will depend on the empirical case investigated, not some a priori conceptual distinction. Thus, even though situations of frequency dependence might be ubiquitous, it is orthogonal to the conceptual question of whether frequency-independent natural selection—McLoone’s target—refers to individual- or population-level causes.

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Notes

  1. For instance see Matthen and Ariew (2002), Matthen and Ariew (2009), Walsh (2000, 2010), Walsh et al. (2002), Walsh et al. (2017), Bouchard and Rosenberg (2004), Rosenberg and Bouchard (2005), Millstein (2006), Millstein (2013), Reisman and Forber (2005), Shapiro and Sober (2007), Huneman (2012), Stephens (2004), Krimbas (2004), Hitchcock and Velasco (2014), Otsuka (2016b), Bourrat (2018).

  2. By “individual” I will refer to any entity that is part of a Darwinian population after Godfrey-Smith (2009). To be clear, I do not necessarily refer to a biological organism when I use this word.

  3. In Bourrat (2018), I show that the individual-level cause view can be defended against some of the arguments made by Reisman and Forber (2005) for the population-level cause view with a focus on drift rather than natural selection.

  4. Note that by distinguishing individual- and population-level properties, I do not mean “population-level” in a sense that would invalidate the supervenience of population-level properties on individual-level properties. I simply mean that our knowledge about a particular evolutionary dynamics could come from properties that we are only able to characterize at the population level.

  5. Note that by “fitness” Bouchard and Rosenberg have in mind an individual-level property that has some effect on reproductive output. Thus, importantly, fitness (which they characterize as “ecological fitness”) is different from reproductive output in their view. For more on the distinction between fitness and reproductive output see Bourrat (2015a, 2017, 2018, 2019a).

  6. As pointed out by Pocheville et al. (2017), there is some ambiguity in the literature surrounding the notion of invariance. The term invariance has been used to refer to, on the one hand, whether, and if so to what extent, a relationship holds as the value of the causal variable is intervened upon; and on the other hand, whether, and if so to what extent, the relationship holds as diverse variables in the background of the relationship are changed. Following Pocheville et al., by “invariance” I mean the first and by “stability” the second.

  7. For a precise information-theoretic measure of stability see Pocheville et al. (2017). Information theory is best suited for categorical variables. To my knowledge, a quantitative measure of stability for quantitative variables does not exist in the literature.

  8. Note also that other individual-level properties in the background of the relationship might be relevant for the stability of the relationship, such as whether the cell in which the mutation occurs is somatic or germinal. In the former case, this mutation would be associated with no evolutionary change, demonstrating another way in which the relationship is unstable.

  9. Note that one could describe a heap of sand collapsing as a sum of individual grains moving, but that would still make the explanation given of the change refer to all the grains of sand constituting the heap at once. Consequently, if one is interested in the fate of all the grains at once, describing the collapse from the perspective of individual grains would still mean that the effect variable refers to the population of sand grains. Note also that one might be interested in providing a causal explanation about one single sand grain moving in the heap following the addition of another grain to the heap. In this explanation, the other grains of the heap would only be considered as the background of the causal relationship, not as part of the effect variable. In consequence, the resulting explanation would not be an explanation of the heap collapsing, but of a sand grain moving during the collapse. Analogously, one might be interested in a given individual-level event (e.g., the fate of a particular organism) caused by an individual-level variable during an evolutionary process. Although this would be a perfectly valid causal explanation, it would not be an evolutionary one.

  10. Again, I am not claiming that to understand a virus outbreak one need not take into account population-level parameters, just that the level at which the causal relata are described can be different.

  11. Note that even though a given token mutation is an instance of a type of mutation and that some might regard this difference as vindicating two different sorts of causation, I follow Woodward (2003, p. 40) in his view that “a claim such as ‘X is causally relevant to Y’ is a claim to the effect that changing the value of X instantiated in particular, spatio-temporally located individuals will change the value of Y located in particular individuals.” In other words, type-causal claims are generalizations of token-causal claims but both refer to the same hierarchical level.

  12. Frank does say that selection and transmission are “causes,” but he uses this word in a vernacular sense.

  13. We will see in the next section, however, that there is some ambiguity surrounding the notion of “variable” when Otsuka makes his move against the population-level cause view.

  14. Note that Sober (2013) makes a similar point.

  15. Russo (2009) provides a defense of causation as variation, especially in a scientific context, against the view that regularities are enough to establish causation.

  16. I believe that the distinction made by Glennan (2009), to defend the individual-level cause view, between productive and relevant cause is on a similar track.

  17. Recently, Griffiths et al. (2015) have implemented this distinction using a causal variant of mutual information.

  18. Note that strictly speaking this is not the fitness of this individual since it is the outcomes of all factors influencing reproductive output, including those that have nothing to do with natural selection.

  19. As was suggested to me by Jun Otsuka, an alternative way to deal with \(\beta\) being a parameter and not a variable is to think of \(\beta\) as a “constant variable” b with all the probability mass at one value and zero elsewhere (aka Dirac delta distribution). Then the causal graph is \(b \rightarrow w \leftarrow z\), with the structural equation \(w = bz\). This will effectively make the linear parameter a manipulable variable.

  20. More on the significance of this statement in the next section.

  21. Hard interventions are opposed to “soft” interventions, the latter of which do not break incoming arrows in causal graphs but change the probability distribution of the variable intervened upon.

  22. Note also that heritability might be considered as positive for intragenerational changes in line with the point made in Bourrat (2015b).

  23. Note that leaving aside \(\beta\) which is supposed constant and thus only modulates uniformly what each individual contributes, this is almost literally what a variance is. In fact, in words, the variance of a variable is the expected squared difference between an individual value and the mean value in the population (for a formal definition see the main text). This difference is squared in order to obtain the magnitude of this difference, since some deviations will be positive, others negative, and on average will cancel out each other. But rather than the squared difference one might decide to take the standard deviation, which is the square root of the variance, to talk about the average effect of an intervention. Standard deviation is often considered a better measure of variation since it has the same unit as the variable to which it refers.

  24. I thank Peter Takacs for this point.

  25. Note that if y is not perfectly heritable one will have to compute its heritability \(h^2\), which, like \(\beta\), is a parameter of the model. Following our hypotheses, we assumed here that reproduction is perfect, so that (\(h^2=1\)).

  26. This is why the notion of ideal intervention is often associated with that of a miracle. For instance, Woodward (2003, p. 135) considers an ideal intervention to be synonymous with a “localized miracle,” borrowing the notion of miracle from David Lewis. Pearl (2009) talks about “surgical procedure.” He is very clear that ideal interventions can do things that might not be possible physically when he writes “[s]ymbolically, one can surely change one equation without altering others and proceed to define quantities that rest on such ‘atomic’ changes. Whether the quantities defined in this manner correspond to changes that can be physically realized is a totally different question that can only be addressed once we have a formal description of the interventions available to us” (p. 365). For more on the view that ideal interventions need not be physically possible see Woodward (2016).

  27. Woodward (2003, pp. 329-330) distinguishes modular interventions from “level-invariant” interventions. The former refers to invariance of the parameters of different equations in a system of structural equations, while the latter refers to invariance of the parameters of the equation in which the intervention is performed. For my purpose, I will refer to these two types of interventions as “modular.” Note also that modularity is intimately linked to the notions of stability and invariance presented earlier; see Footnote 6.

  28. Illari and Russo (2014, p. 105) borrow the idea of structure-altering intervention from Steel (2006, 2008).

  29. In general, any fitness-altering interaction between the individuals of a population will satisfy this phenomenon.

  30. Note that this would be a particularly bad model precisely because the two characters are correlated.

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Acknowledgements

I am thankful to Mathieu Charbonneau, Paul Griffiths, Jun Otsuka, Peter Takacs, and two anonymous reviewers for comments on previous versions of the manuscript. I also thank the members of the Theory and Method in Biosciences group at the University of Sydney and in particular Stefan Gawronski who proofread the final manuscript. This research was supported by a Macquarie University Research Fellowship and a Large Grant from the John Templeton Foundation (Grant ID 60811).

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  1. Department of Philosophy, Macquarie University, North Ryde, NSW, Australia

    Pierrick Bourrat

  2. Department of Philosophy & Charles Perkins Centre, University of Sydney, Sydney, NSW, Australia

    Pierrick Bourrat

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Bourrat, P. Evolution is About Populations, But Its Causes are About Individuals. Biol Theory 14, 254–266 (2019). https://doi.org/10.1007/s13752-019-00329-3

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