Skip to main content
Best practices for moving from correlation to causation in ecological research

Best practices for moving from correlation to causation in ecological research

This is a Preprint and has not been peer reviewed. This is version 1 of this Preprint.

Add a Comment

You must log in to post a comment.


Comments

There are no comments or no comments have been made public for this article.

Downloads

Download Preprint

Authors

Hannah E Correia , Laura E Dee, Jarrett E. K. Byrnes, John Fieberg, Marie-Josee Fortin, Clark Glymour, Jakob Runge, Bill Shipley, Ilya Shpitser, Katherine Johannet Siegel, George Sugihara, Betsy von Holle, Paul J Ferraro

Abstract

In ecology, causal questions are ubiquitous, yet the literature describing systematic approaches to answering these questions is vast and fragmented across different traditions (e.g., randomization, structural equation modeling, convergent cross mapping). In our Perspective, we connect the causal assumptions, tasks, frameworks, and methods across these traditions, thereby providing a synthesis of the concepts and methodological advances for detecting and quantifying causal relationships in ecological systems. Through a newly developed workflow, we emphasize how ecologists’ choices among empirical approaches are guided by the pre-existing knowledge that ecologists have and the causal assumptions that ecologists are willing to make.

DOI

https://doi.org/10.32942/X2DW7Z

Subjects

Applied Statistics, Longitudinal Data Analysis and Time Series, Other Ecology and Evolutionary Biology, Statistical Methodology

Keywords

causal inference, causal discovery, causal assumptions, causal frameworks, causal analysis, conceptual synthesis, causal reasoning, causal ecology

Dates

Published: 2025-06-07 02:47

Last Updated: 2025-06-07 02:47

License

CC-BY Attribution-No Derivatives 4.0 International

Additional Metadata

Language:
English

Conflict of interest statement:
None