At the interface of developmental biology and evolutionary biology, the very
criteria of scientific knowledge are up for grabs. A central issue is the status of evolutionary genetics models, which some argue cannot coherently be used with complex gene regulatory network (GRN) models to explain the same evolutionary phenomena. Despite those claims, many researchers use evolutionary genetics models jointly with GRN models to study evolutionary phenomena.
How do those researchers deploy those two kinds of models so that they are consistent and compatible with each other? To address that question, this dissertation closely examines, dissects, and compares two recent research projects in which researchers jointly use the two kinds of models. To identify, select, reconstruct, describe, and compare those cases, I use methods from the empirical social sciences, such as digital corpus analysis, content analysis, and structured case analysis.
From those analyses, I infer three primary conclusions about projects of the kind studied. First, they employ an implicit concept of gene that enables the joint use of both kinds of models. Second, they pursue more epistemic aims besides mechanistic explanation of phenomena. Third, they don’t work to create and export broad synthesized theories. Rather, they focus on phenomena too complex to be understood by a common general theory, they distinguish parts of the phenomena, and they apply models from different theories to the different parts. For such projects, seemingly incompatible models are synthesized largely through mediated representations of complex phenomena.
The dissertation closes by proposing how developmental evolution, a field traditionally focused on macroevolution, might fruitfully expand its research agenda to include projects that study microevolution.