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A System for Tracking the Dynamics of Social Preference Behavior in Small Rodents

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Published on: November 21, 2019

Three-Dimensional Correlated Random Walks for Animal Movement and Habitat Selection.

Natasha Klappstein¹, Théo Michelot¹, Ron Togunov²

¹Department of Mathematics and Statistics, Dalhousie University, Halifax, Nova Scotia, Canada.

Ecology Letters

|July 2, 2026

Summary

Researchers developed a 3D step selection function (SSF) to better track animal movement and habitat selection in three dimensions, improving ecological understanding for flying and swimming species.

Keywords:

3D Kent distribution animal movement biased random walks correlated random walks habitat selection step selection function telemetry data three‐dimensional

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Area of Science:

Ecology
Movement Ecology
Habitat Selection

Background:

Animal movement and habitat selection are key to understanding ecological patterns.
Current 2D analysis methods limit understanding of 3D animal movement (e.g., flying or swimming species).

Purpose of the Study:

To introduce a novel 3D step selection function (SSF) for quantifying animal movement and habitat selection in three dimensions.
To provide a framework for analyzing 3D animal movement data more accurately.

Main Methods:

Formulation of a general family of 3D correlated random walks.
Application of the 3D SSF model to Antarctic petrel movement data.
Incorporation of vertical stratification, barriers (ground/surface), and directional targets into the model.

Main Results:

Demonstrated the utility of 3D SSFs in assessing habitat selection in vertically stratified environments.
Showcased the model's ability to account for environmental barriers and target attraction.
Provided a robust framework for analyzing complex 3D animal movement patterns.

Conclusions:

The proposed 3D SSF framework significantly enhances the study of animal movement and habitat selection in three dimensions.
This approach is crucial for addressing ecological questions previously unanswerable with 2D methods.
Advances understanding of species navigating complex 3D environments.