Cyclic and multilevel causation in evolutionary processes
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Cyclic and multilevel causation in evolutionary processes Jonathan Warrell1,2 · Mark Gerstein1,2,3,4 Received: 30 November 2018 / Accepted: 2 June 2020 © The Author(s) 2020
Abstract Many models of evolution are implicitly causal processes. Features such as causal feedback between evolutionary variables and evolutionary processes acting at multiple levels, though, mean that conventional causal models miss important phenomena. We develop here a general theoretical framework for analyzing evolutionary processes drawing on recent approaches to causal modeling developed in the machine-learning literature, which have extended Pearls do-calculus to incorporate cyclic causal interactions and multilevel causation. We also develop informationtheoretic notions necessary to analyze causal information dynamics in our framework, introducing a causal generalization of the Partial Information Decomposition framework. We show how our causal framework helps to clarify conceptual issues in the contexts of complex trait analysis and cancer genetics, including assigning variation in an observed trait to genetic, epigenetic and environmental sources in the presence of epigenetic and environmental feedback processes, and variation in fitness to mutation processes in cancer using a multilevel causal model respectively, as well as relating causally-induced to observed variation in these variables via information theoretic bounds. In the process, we introduce a general class of multilevel causal evolutionary processes which connect evolutionary processes at multiple levels via coarse-graining relationships. Further, we show how a range of fitness models can be formulated in our framework, as well as a causal analog of Prices equation (generalizing the probabilistic Rice equation), clarifying the relationships between realized/probabilistic fitness and direct/indirect selection. Finally, we consider the potential relevance of our framework to foundational issues in biology and evolution, including supervenience, multilevel selection and individuality. Particularly, we argue that our class of multilevel causal evolutionary processes, in conjunction with a minimum description length principle, provides a conceptual framework in which identification of multiple levels of selection may be reduced to a model selection problem. Keywords Causality · Information theory · Multilevel selection · Price’s equation · Supervenience
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J. Warrell, M. Gerstein
Introduction Causality is typically invoked in accounts of evolutionary processes. For instance, for a variant to be subject to direct selection, it is necessary that it has a causal impact on fitness. The role of causality is made explicit in axiomatic accounts of evolution (Rice 2004). Further, the formal framework of Pearl’s ‘do’-calculus (Pearl 2009) has been used explicitly in analyzing Mendelian Randomization (Lawlor et al. 2008), the relationship between kin and multilevel sel
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