Detection and tracking of chemical trails by local sensory systems

TL;DR

This paper presents a mathematical model demonstrating how aquatic organisms can detect and follow chemical trails using local sensory information, without needing global position data.

Contribution

It introduces a novel framework for local chemical trail detection and tracking, applicable to aquatic organisms like copepods, without reliance on global positioning.

Findings

The model enables detection of chemical trails using only local concentration data.

Organisms can track trails effectively without global positional awareness.

The framework applies to various aquatic species and scenarios.

Abstract

Many aquatic organisms exhibit remarkable abilities to detect and track chemical signals when foraging, mating and escaping. For example, the male copepod { \em T. longicornis} identifies the female in the open ocean by following its chemically-flavored trail. Here, we develop a mathematical framework in which a local sensory system is able to detect the local concentration field and adjust its orientation accordingly. We show that this system is able to detect and track chemical trails without knowing the trail's global or relative position.