Abstract
Evolutionary developmental biology (evo-devo) is considered a ‘mechanistic science,’ in that it causally explains morphological evolution in terms of changes in developmental mechanisms. Evo-devo is also an interdisciplinary and integrative approach, as its explanations use contributions from many fields and pertain to different levels of organismal organization. Philosophical accounts of mechanistic explanation are currently highly prominent, and have been particularly able to capture the integrative nature of multifield and multilevel explanations. However, I argue that evo-devo demonstrates the need for a broadened philosophical conception of mechanisms and mechanistic explanation.
Mechanistic explanation (in terms of the qualitative interactions of the structural parts of a whole) has been developed as an alternative to the traditional idea of explanation as derivation from laws or quantitative principles. Against the picture promoted by Carl Craver, that mathematical models describe but usually do not explain, my discussion of cases from the strand of evo-devo which is concerned with developmental processes points to qualitative phenomena where quantitative mathematical models are an indispensable part of the explanation. While philosophical accounts have focused on the actual organization and operation of mechanisms, properties of developmental mechanisms that are about how a mechanism reacts to modifications are of major evolutionary significance, including robustness, phenotypic plasticity, and modularity. A philosophical conception of mechanisms is needed that takes into account quantitative changes, transient entities and the generation of novel types of entities, feedback loops and complex interaction networks, emergent properties, and, in particular, functional-dynamical aspects of mechanisms, including functional (as opposed to structural) organization and distributed, system-wide phenomena. I conclude with general remarks on philosophical accounts of explanation.
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Notes
- 1.
- 2.
“… mechanistic models of how developmental systems produce phenotypes and how changes within these systems contribute to corresponding changes in phenotypes. This differs from the Modern Synthesis view that evolutionary processes are driven largely by (random) genetic changes, on the one hand, and by functional interactions of organisms with their environment, on the other hand, … What the molecular analysis of developmental processes and regulatory gene networks provides is a mechanistic understanding of both the development and evolution of phenotypic characters.” (Laubichler 2010, pp. 202 and 208, my emphasis)
- 3.
Likewise, in his argument that the Hodgkin and Huxley equations are merely phenomenological, Craver (2006) acknowledges that the equations “allow neuroscientists to predict how current will change under various experimental interventions” (p. 363, my emphasis)—which given Woodward’s interventionist account of causation entails that the equations capture some causal factors and thus explain. Craver still rules them to be non-explanatory, apparently on the grounds that they do not provide an account of how the quantitative relation is brought about by lower-level constituents.
- 4.
Note that the model abstracts away from entities mediating the interaction of the activator and inhibitor, e.g., DAN (Fig. 7.1a, b). This omitting of molecular-mechanistic detail is licit assuming that it does not alter the functional interaction and dynamics of the activator and inhibitor. If so, by my criterion ER such (for the target phenomenon) explanatorily irrelevant detail ought to be excluded from the explanation. This shows that a mechanistic account of how an effect is produced (citing all intermediate steps and structural interactions) and an explanation of why it occurs are consistent, but not identical.
- 5.
Figure 7.2 schematically depicts the four oscillating genes Hes1, Hes7, Hes5, and Hey2 (all of which engage in negative feedback) together.
- 6.
Explaining why the oscillation has a period of 120 min (in mice) would definitely necessitate a quantitative account (see also Baetu 2015). In the related context of circadian rhythms (genetic oscillations with a period of about a day), for a philosophical account indicating the relevance of mathematical modeling see Bechtel and Abrahamsen (2010, 2011) and Bechtel (2013).
- 7.
At the end of Sect. 3, I pointed out that not every explanation requires the reductive decomposition of a mechanism’s components. According to my criterion ER, if the component is explanatorily relevant—if changing it would lead to a change in the surrounding mechanism’s features to be explained—but the component’s lower-level constituents are not relevant to the particular explanandum, then the explanation should cite the component but not its constituents. The component exhibiting robustness is a clear way in which this can be the case, as a change in the component’s constituents does not make a causal difference to the component’s robust properties (which are relevant to the explanation).
- 8.
Baetu (2015) points out that the functioning of a mechanism can be due not so much to stable entities, but to a stable concentration (of a type of entity), where individual entities are very short-lived and constantly replaced.
- 9.
There is disagreement on whether philosophical accounts of mechanisms can capture natural selection (Barros 2008; Skipper and Millstein 2005). My view is that explanations in terms of natural selection (in particular when using mathematical models) abstract away from many concrete properties and activities of individual organism. But abstraction from mechanistic detail happens even in mathematical models in molecular and developmental biology (Sect. 3; Bechtel 2015; Brigandt 2013c; Levy 2014; Levy and Bechtel 2013), so that the broad conception of mechanistic explanation advocated here is more likely to accommodate natural selection. One difficulty is that natural selection is about fitness differences among phenotypes. Even if each of two phenotypes is part of a mechanism (by each phenotype being possessed by concrete organisms), what matters is how the phenotypes differ and the phenotypes’ differential behavior across time, which is a complex and unusual aspect of a ‘mechanism.’
- 10.
On related grounds, Baetu (2015) argues that molecular mechanisms are not neatly individuated objects.
- 11.
Baetu (2015) discusses how a mathematical model can reveal a previous molecular-mechanistic account to be explanatorily incomplete. This can prompt and guide further experimental discovery, so a mathematical model can be involved in both discovery and explanation.
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Acknowledgments
I am indebted to Pierre-Alain Braillard, Christophe Malaterre, and two anonymous referees for detailed comments on an earlier version of this paper. I thank Emma Kennedy for proofreading the manuscript and Arnon Levy, Bill Bechtel, Carl Craver, and Maureen O’Malley for discussions on mechanistic explanation and mathematical models. Figure 7.1 was reprinted from Salazar-Ciudad and Jernvall (2002) with the permission of the copyright holder, the National Academy of Sciences, USA. Figure 7.2 was reprinted from Dequéant and Pourquié (2008) by permission from Macmillan Publishers Ltd.
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Brigandt, I. (2015). Evolutionary Developmental Biology and the Limits of Philosophical Accounts of Mechanistic Explanation. In: Explanation in Biology. History, Philosophy and Theory of the Life Sciences, vol 11. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-9822-8_7
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