Explanation in terms of gene regulatory networks has become standard practice in evolutionary developmental biology. In this paper, we argue that GRNs fail to provide a robust, mechanistic, and dynamic understanding of the developmental processes underlying the genotype–phenotype map. Explanations based on GRNs are limited by three main problems: the problem of genetic determinism, the problem of correspondence between network structure and function, and the problem of diachronicity, as in the unfolding of causal interactions over time. Overcoming these problems requires (...) dynamic mechanistic explanations, which rely not only on mechanistic decomposition, but also on dynamic modeling to reconstitute the causal chain of events underlying the process of development. We illustrate the power and potential of this type of explanation with a number of biological case studies that integrate empirical investigations with mathematical modeling and analysis. We conclude with general considerations on the relation between mechanism and process in evo-devo. (shrink)

Psychological evidence suggests that laypeople understand the world around them in terms of intuitive ontologies which describe broad categories of objects in the world, such as ‘person’, ‘artefact’ and ‘animal’. However, because intuitive ontologies are the result of natural selection, they only need to be adaptive; this does not guarantee that the knowledge they provide is a genuine reflection of causal mechanisms in the world. As a result, science has parted ways with intuitive ontologies. Nevertheless, since the brain is evolved (...) to understand objects in the world according to these categories, we can expect that they continue to play a role in scientific understanding. Taking the case of human evolution, we explore relationships between intuitive ontological and scientific understanding. We show that intuitive ontologies not only shape intuitions on human evolution, but also guide the direction and topics of interest in its research programmes. Elucidating the relationships between intuitive ontologies and science may help us gain a clearer insight into scientific understanding. (shrink)