Animal daily mobility patterns analysis using resting event networks

TL;DR

This paper introduces a novel method using resting event networks to analyze daily animal mobility patterns from high-resolution spatio-temporal tracking data, aiding conservation efforts.

Contribution

It presents a new approach for identifying daily movement patterns in animals using resting event networks, applicable to high-resolution trajectory data.

Findings

Successfully applied to fish in a hydropeaking river

Revealed distinct daily mobility patterns

Enhanced understanding of animal behavior

Abstract

Characterizing the movement patterns of animals is crucial to improve our understanding of their behavior and thus develop adequate conservation strategies. Such investigations, which could not have been implemented in practice only a few years ago, have been facilitated through the recent advances in tracking methods that enable researchers to study animal movement at an unprecedented spatio-temporal resolution. However, the identification and extraction of patterns from spatio-temporal trajectories is still a general problem that has relevance for many applications. Here, we rely on the concept of resting event networks to identify the presence of daily mobility patterns in animal spatio-temporal trajectories. We illustrate our approach by analyzing spatio-temporal trajectories of several fish species in a large hydropeaking river.