This is a Preprint and has not been peer reviewed.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

Best practices for moving from correlation to causation in ecological research
Downloads
Authors
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
There are no comments or no comments have been made public for this article.