Abstract
Debates over adaptationism can be clarified and partially resolved by careful consideration of the ‘grain’ at which evolutionary processes are described. The framework of ‘adaptive landscapes’ can be used to illustrate and facilitate this investigation. We argue that natural selection may have special status at an intermediate grain of analysis of evolutionary processes. The cases of sickle-cell disease and genomic imprinting are used as case studies.
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Notes
Gould and Lewontin’s classic (1979) paper used both of these lines of criticism.
The relationship between the present framework and some other aspects of the adaptationism debates—including simplicity preferences, model selection, and claims about which biological problems might be central or primary—is discussed in Godfrey-Smith and Wilkins (2008).
In one sense, molecular work is the “finest-grained” work in evolutionary biology, because it works at the scale of molecules and cells. But this is not the same of “grain” as the sense we employ here. Depending on assumptions made about time-scale and the range of variants considered, molecular evolutionary work can be at either the finest or intermediate levels in our sense. Molecular evolution, as noted in our “Introduction”, is a part of biology that has successfully integrated adaptationist and non-adaptationist approaches.
The distinction between evolution on shorter time-scales in which the set of available variants is fixed and longer time-scales in which the set of variants is not fixed has been treated dynamically by Eshel and Feldman (1984, 2001), Hammerstein (1996), and Nowak and Sigmund (2004), with conclusions that complement the present analysis. In effect, this is a tradition of explicit modeling of the relations between the finest and intermediate grains of analysis considered here. These models often, in an understandable idealization, treat the processes at the intermediate level of grain as sequential combinations of processes at the finer level.
Much population genetic modeling is concerned with finding states of populations that are stable (in the short-term sense in which only a fixed range of alleles are considered). An interest in stability is common to both approaches. But the population genetic approach can also consider the details of the dynamics, the role of stochastic effects, and the like, whereas the ESS approach only identifies stable states.
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Acknowledgment
We are grateful to Patrick Forber for helpful comments on an earlier draft.
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Wilkins, J.F., Godfrey-Smith, P. Adaptationism and the adaptive landscape. Biol Philos 24, 199–214 (2009). https://doi.org/10.1007/s10539-008-9147-5
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DOI: https://doi.org/10.1007/s10539-008-9147-5