Causality from palaeontological time series

Abstract

As custodians of deep time, palaeontologists have an obligation to seek the causes and consequences of longterm evolutionary trajectories and the processes of ecosystem assembly and collapse. Building explicit process models on the relevant scales can be fraught with difficulties, and causal inference is typically limited to patterns of association. In this review, we discuss some of the ways in which causal connections can be extracted from palaeontological time series and provide an overview of three recently developed analytical frameworks that have been applied to palaeontological questions, namely linear stochastic differential equations, convergent cross mapping and transfer entropy. We outline how these methods differ conceptually, and in practice, and point to available software and worked examples. We end by discussing why a paradigm of dynamical causality is needed to decipher the messages encrypted in palaeontological patterns.

Cope's Rule in a modular organism: Directional evolution without an overarching macroevolutionary trend

“…), and given the association between temperature and zooid size, this global trend may have contributed to part of the pattern we see (Fig. ) but because we only have 16 time points, we cannot justify studying causal relationships between macroevolutionary patterns of size and global temperature more closely until we have more and/or different types of data (Hannisdal and Liow ).…”

REvoSim: Organism‐level simulation of macro and microevolution

“…There is a paucity of systems and methods that bridge this divide: lab‐based systems are currently subject to severe limitations (Bell ). Debate thus continues as to whether macroevolution is fundamentally different to microevolution, or whether it represents the action of microevolutionary processes writ large (Erwin ; Simons ; Jablonski ; this is also touched upon by the discussion of Hannisdal & Liow ). REvoSim may shed light on this by bridging this temporal divide: adaptive radiations, extinctions and speciation can be studied in this context, and the impact of space on these investigated.…”

Are local dominance and inter-clade dynamics causally linked when one fossil clade displaces another?

“…Note that our models are process-based, analyzed for the entire time series rather than single events or short episodes, such as those spanning just two or three stages. While shorter-duration excursions in rates or proportions are "real," they say little about statistical predictability in a Granger causal sense (9,20). Finally, in the lower part of Table 1, we examine relationships between genus origination and extinction rates and local species proportions.…”