Can we use causal theory to understand how Earth processes shape life? Examples from the Baja GeoGenomics consortium

Abstract:

It is well established that geologic and climatic processes shape the distribution and diversification of life on Earth. While biological evolution is often considered to be open-ended and unpredictable, Earth processes can be considered a type of order-forming process (similar to natural selection) in which there is a clear cause-effect relationship between geologic process and biological pattern. Yet the challenge remains: how do we measure this relationship? For example, how can we measure the causal effect a river or climate dipole has on divergence and adaptation of a regional biota? Moreover, how can the cause-effect relationships in one geographic and taxonomic study be compared to those of another? Here, we consider whether causal theory, from computer science, economics, and ecology literature, can be used as an organizing framework to understand how Earth processes shape the diversification and distribution of life. Causal structures, which are a class of tools that use networks to represent cause-effect relations, can be used to guide the development of Earth-life theory alongside the quantitative assessment of cause-effect hypotheses in individual studies. We will discuss how the causal effects of classically studied features, such as mountain ranges, can be deconstructed into networks of indirect and direct causal pathways. These causal pathways can be evaluated and quantified in different combinations in different geologic settings. Finally, we outline our ongoing research on the Baja California peninsula in Mexico to demonstrate how different Earth processes are hypothesized to yield different effects on a resident biota, and demonstrate how to test these hypotheses through the integration of geologic, genomic, and ecological data. The Baja GeoGenomics consortium aims to constrain the major ways in which the peninsula has changed geologically and climatically over the past several million years and test the individual effects of these processes on the evolution of plants and animals using population genomic, seasonal transcriptomic, and niche modeling data. This marks a major advancement in our inclusion of complexity in the study of Earth-life evolution.