Different concepts define species at the pattern-level grouping of organisms into discrete clusters, the level of the processes operating within and between populations leading to the formation and maintenance of these clusters, or the level of the inner-organismic genetic and molecular mechanisms that contribute to species cohesion or promote speciation. I argue that, unlike single-level approaches, a multi-level framework takes into account the complex sequences of cause-effect reinforcements leading to the formation and maintenance of various patterns, and allows for revisions and refinements of pattern-based characterizations in light of the gradual elucidation of the causes and mechanisms contributing to pattern formation and maintenance.
The emergence of systems biology is marked by a revival of mathematical modeling approaches to causal-mechanistic explanations and associated experimental practices in molecular biology. From a philosophical standpoint, this ‘mathematical turn’ in biology constitutes an excellent opportunity to investigate the relationship between deductive-nomological and causal-mechanistic accounts of scientific explanation. I argue that mathematical models in systems biology integrate substantial knowledge of molecular mechanisms with the application of laws, modeling and analysis strategies borrowed from chemistry, cybernetics and systems theory in order to yield quantitative mechanistic explanations. Mechanism schemas obtained by abstracting high-resolution biochemical details act as bridges between molecular mechanistic explanations and mathematical models of networks. In turn, mathematical models account for poorly understood aspects of biological phenomena, most notably minute quantitative-dynamic features. Thus, in actual scientific practice, deductive-nomological and casual-mechanistic approaches to explanation are not mutually exclusive, but complementary. Furthermore, mathematical models can reveal unsuspected ‘black boxes’ and motivate revisions of mechanistic explanations. This interplay between mechanistic explanations and their mathematical counterparts constitutes a progressive research approach that generates explanations of novel phenomena, and reveal strange properties of molecular mechanisms that have thus far escaped our attention.