Best practices for moving from correlation to causation in ecological research.

Area of Science:

• Ecology
• Causal Inference

Background:

• Causal questions are central to ecology but addressed by fragmented methodologies.
• Existing literature spans diverse traditions like randomization and structural equation modeling.

Purpose of the Study:

• To synthesize diverse causal inference approaches in ecology.
• To provide a unified framework for detecting and quantifying ecological causal relationships.

Main Methods:

• Connecting causal assumptions, tasks, and frameworks across traditions.
• Developing a novel workflow to guide empirical approach selection.

Main Results:

• A comprehensive synthesis of concepts and methodological advances for ecological causal inference.
• A workflow highlighting the role of prior knowledge and causal assumptions.

Conclusions:

• The developed workflow aids ecologists in making informed choices for causal analysis.
• This synthesis advances the systematic detection and quantification of ecological causality.