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A goal common to several disciplines within earth and life sciences is to understand how earth processes and abiotic conditions shape the diversification and distribution of species on our planet. To develop a mechanistic and detailed understanding of these relationships across taxonomic-geographic settings should inform a set of boundary conditions that describe the geologic and climatic conditions under which new biodiversity is generated along with the organismal traits (e.g., generation time, dispersal ability) that govern why species vary in their evolutionary responses to the same external influences. However, earth and life sciences each encompass a set of highly complex and sometimes nested relationships. This presents a need for new ways to guide the integration of domain knowledge across these complex systems in a way that can generate new hypotheses, facilitate interdisciplinary collaboration, and shape earth-life theory moving forward. Here, I outline the use of causal structures, which are a set of tools to diagram cause-effect relationships at different levels of detail (specification) that include structural equation meta models (SEMMs), causal diagrams (CDs), and structural equation models (SEMs). I will give examples of how to use SEMMs and CDs to detail earth-life relationships, what we can learn from doing so, and pose a way for how we might quantify these relationships. I hope to demonstrate the usefulness and applicability of thinking about earth-life systems within a causal framework, and speculate about temporal dynamics and the potential for abiotic-to-biotic causal thresholds that may occur over time in different earth-life systems.
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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.
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- Award ID(s):
- 1925535
- PAR ID:
- 10446213
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Molecular Ecology
- Volume:
- 30
- Issue:
- 22
- ISSN:
- 0962-1083
- Page Range / eLocation ID:
- p. 5628-5642
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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