Towards a unified framework to study causality in Earth–life systems

Abstract

There is considerable interest in better understanding how earth processes shape the generation and distribution of life on Earth. This question, at its heart, is one of causation. In this article I propose that at a regional level, earth processes can be thought of as behaving somewhat deterministically and may have an organized effect on the diversification and distribution of species. However, the study of how landscape features shape biology is challenged by pseudocongruent or collinear variables. I demonstrate that causal structures can be used to depict the cause–effect relationships between earth processes and biological patterns using recent examples from the literature about speciation and species richness in montane settings. This application shows that causal diagrams can be used to better decipher the details of causal relationships by motivating new hypotheses. Additionally, the abstraction of this knowledge into structural equation metamodels can be used to formulate theory about relationships within Earth–life systems more broadly. Causal structures are a natural point of collaboration between biologists and Earth scientists, and their use can mitigate against the risk of misassigning causality within studies. My goal is that by applying causal theory through application of causal structures, we can build a systems‐level understanding of what landscape features or earth processes most shape the distribution and diversification of species, what types of organisms are most affected, and why.

The information signature of diverging lineages

“…Yet, core questions remain about how often lineages diverge in complete isolation (vicariance) or with gene flow (parapatry, sympatry). While speciation via sexual selection or ecological adaptation may be expected to occur in the presence of gene flow, there remains intense interest in the role geological, climatic, and geographical settings play in mediating or promoting speciation (Antonelli, 2017; Antonelli et al, 2018; Dolby, 2021; Rahbek et al, 2019; Ribas et al, 2022) particularly in the nascent field of geogenomics (Dolby et al, 2022). These settings may be expected to impact gene flow in different ways.…”