Abstract

Recent research in philosophy of science has shown that scientists rely on a plurality of strategies to develop successful explanations of different types of phenomena. In the case of biology, most of these strategies go far beyond the traditional and reductionistic models of scientific explanation that have proven so successful in the fundamental sciences. Concretely, in the last two decades, philosophers of science have discovered the existence of at least two different types of scientific explanation at work in the biological sciences, namely: mechanistic and structural explanations. Despite the growing evidence about the radically different nature of these two types of explanation, no inquiry has been conducted to date to determine the ontological reasons that might underlie these differences, nor the way in which these types of explanations can be systematically related with each other. Here, we aim to cover this gap by connecting this plurality of research strategies with the existence of emergent levels of reality. We argue that the existence of these different—and apparently incompatible—explanatory strategies to account for biological phenomena derives from the existence of “ontological jumps” in nature, which generate different regimes of causation that in turn demand the development of different explanatory frameworks. We identify two of these strategies—mechanistic modelling and network modelling—and connect them to the existence of two ontological regimes of causation. Finally, we relate them with each other in a systematic way. In this vein, our paper provides an ontological justification for the plurality of explanatory strategies that we see in the life sciences.