A computational framework for studying energetics and resource management in sea turtle migration and autonomous...

Area of Science:

• Marine Biology
• Computational Ecology
• Bio-inspired Engineering

Background:

• Sea turtles undertake extensive migrations, necessitating satellite tracking for research.
• Satellite tags may impact turtle behavior and energetics, potentially skewing migration data.
• Studying animal energetics during long-distance migrations in the field presents significant challenges.

Purpose of the Study:

• To computationally model the effects of satellite tracking tags on sea turtle migration behavior.
• To investigate the interplay between energy capacity, energy expenditure, and navigation success.
• To inform the design of satellite tags and provide usage recommendations for researchers.

Main Methods:

• Development of an agent-based computational model simulating sea turtle migration.
• Incorporation of environmental factors: synthetic magnetic fields for navigation, ocean currents, and food resource distributions.
• Simulation of an agent's energy dynamics, including consumption during movement and replenishment through foraging.

Main Results:

• The simulation framework demonstrates the critical relationship between an agent's energy reserves, mechanical energy expenditure, and its ability to reach migratory destinations.
• Quantified the impact of tag-related drag and energy demands on migratory success.
• Identified thresholds for energy capacity and foraging efficiency necessary for successful navigation.

Conclusions:

• Computational models are valuable tools for understanding the ecological impacts of tracking technologies on marine megafauna.
• Findings can guide the development of less intrusive satellite tags and optimize their deployment strategies.
• The model's framework is adaptable for studying other marine species and even engineering applications like remotely operated vehicles (ROVs).