Two kinds of historical explanation in Evolutionary Biology

Abstract

Historical explanations in evolutionary biology are commonly characterized as narrative explanations. Examples include explanations of the evolution of particular traits and explanations of macroevolutionary transitions. In this paper I present two case studies of explanations in accounts of pathogen evolution and host-pathogen coevolution, respectively, and argue that one of them is captured well by established accounts of time-sequenced narrative explanation. The other one differs from narrative explanations in important respects, even though it shares some characteristics with them as it is also a population-level historical explanation. I thus argue that the second case represents a different kind of explanation that I call historical explanation of type phenomena. The main difference between the two kinds of explanation is the conceptualization of the explanandum phenomena as particulars or type phenomena, respectively. Narrative explanations explain particulars but also deal with generalization, regularities and type phenomena. Historical explanations of type phenomena, on the other hand, explain multiply realizable phenomena but also deal with particulars. The two kinds of explanation complement each other because they explain different aspects of evolution.

On the nature of evolutionary explanations: a critical appraisal of Walter Bock’s approach with a new revised proposal

“…For the sake of clarity, the classic and well know definition of what are historical narratives was given by Gould ( 1989 , p. 283): “Historical explanations take the form of narrative: E, the phenomenon to be explained, arose because D came before, preceded by C, B, and A. If any of these earlier stages had not occurred or had transpired in a different way, then E would not exist (or would be present in a substantially altered form, E’, requiring a different explanation).” Recently, the topic of narrative explanation in the sciences has been increasingly fleshed out by philosophers (e.g., Currie, 2013 ; Beatty, 2016 ; Reydon, 2023 ; Kranke, 2022 ). And so, Currie ( 2013 ), summarizes narrative explanations: “(1) account for some particular explanandum in terms of some causal sequence; (2) target a central subject; (3) may or may not appeal explicitly to laws or generalizations; (4) are paradigmatically, but not exclusively, historical.” Later, Currie ( 2013 ) contrasted between a ‘simple’ narrative (an event is explained by a general model, and minimal causal factors are referenced) and a ‘complex narrative’ (an event that no appeal to a general model in explanation is made; rather a unique, detailed causal sequence is employed)—snowball earth being the case for the simple case while sauropod gigantism is for the complex one.…”

“…When deciding which state is primitive and which is advanced between, say, the absence or presence of wings, we cannot content ourselves with pattern analysis of presences and absences in a character matrix. We also need to know something about the functional value of the wing, when present, and the possible adaptive significance of its absence.” Finally, systematics, it must be emphasized, is important because all living things are the product of history, and we can understand little about the diversity of organisms without knowledge of their history—the phylogenetic knowledge provided by systematics, thus “[e]volutionary explanation depends upon systematics” (Lewontin, 2002 , p. 3).…”

Scientific experimental articles are modernist stories

“…3 Narratives are discovered at various sites of scientific practice, especially in idiographic sciences such as history and natural history (Currie & Sterelny, 2017 ; Terrall, 2017 ), but also in mathematical simulations and modelling (Rosales, 2017 ; Wise, 2017 ), sociology (Morgan, 2017 ), clinical case reporting (Hurwitz, 2017 ) and thought experiments (Murphy, 2020 ; Nersessian, 1992 , 2017 ; Swirski, 2006 ; Stuart, 2021 ). Philosophers argue that narratives can do many things, including: explain (Roth, 1989 ); demonstrate the pursuitworthiness of a model (Hartmann, 1999 ); capture complex causal connections (Morgan, 2017 ); identify gaps in knowledge (Currie & Sterelny, 2017 ); provide causal mechanistic explanations (Swaim, 2019 ); order knowledge, provide coherence, and exemplify scientifically important features (Morgan & Wise, 2017 ; Kranke, 2022 ; Haines, 2022 ); as well as operate as a form of counterfactual explanation (Beatty, 2017 ). The intensive work on narratives recently culminated in a volume on narratives in science, edited by Morgan et al ( 2022 ), which characterizes narrative as a general-purpose “technology of sense-making” (p. 4).…”