Detecting seasonal episodic-like spatiotemporal memory patterns using animal movement modelling

TL;DR

This paper introduces a novel mathematical model to analyze how animals use seasonal and ephemeral environmental cues in their movement patterns, enhancing understanding of animal cognition and resource use.

Contribution

The paper presents a new model that captures seasonal and episodic memory in animal movement, integrating resource selection and long-distance navigation behaviors.

Findings

Model accurately analyzes simulated data with as little as one year of data.

Model selection and parameter estimation improve with more location data.

Potential to reveal mechanisms of memory-based foraging strategies.

Abstract

1. Spatial memory plays a role in the way animals perceive their environments, resulting in memory-informed movement patterns that are observable to ecologists. Developing mathematical techniques to understand how animals use memory in their environments allows for an increased understanding of animal cognition. 2. Here we describe a model that accounts for the memory of seasonal or ephemeral qualities of an animal's environment. The model captures multiple behaviors at once by allowing for resource selection in the present time as well as long-distance navigations to previously visited locations within an animal's home range. 3. We performed a set of analyses on simulated data to test our model, determining that it can provide informative results from as little as one year of discrete-time location data. We also show that the accuracy of model selection and parameter estimation increases with more location data. 4. This model has potential to identify a specific mechanism in which animals use memory to optimize their foraging, by revisiting temporally and predictably variable resources at consistent time lags.