Automated Coral Spawn Monitoring for Reef Restoration: The Coral Spawn and Larvae Imaging Camera System (CSLICS)
Dorian Tsai, Christopher A. Brunner, Riki Lamont, F. Mikaela Nordborg, Andrea Severati, Java Terry, Karen E Jackel, Matthew Dunbabin, Tobias Fischer, Scarlett Raine
AI summary
Problem
Manual monitoring of coral spawn in aquaculture is labor-intensive, slow, and creates a critical bottleneck for scaling reef restoration efforts.
Approach
A low-cost, modular camera system mounted in larval rearing tanks uses YOLOv8 object detectors trained with human-in-the-loop labeling to automatically detect, classify, and count coral spawn in real-time.
Key results
- 82.4% F1 score for surface spawn detection across embryogenesis stages
- 83% F1 score for sub-surface spawn detection
- 5,720 labor hours saved per mass spawning event
- Accurate real-time fertilization success and larval count measurements during Great Barrier Reef spawning
Why it matters
Enables scalable, automated monitoring for coral aquaculture, accelerating reef restoration efforts against climate change threats.
Abstract
Coral aquaculture for reef restoration requires accurate and continuous spawn counting for resource distri- bution and larval health monitoring, but current methods are labor-intensive and represent a critical bottleneck in the coral production pipeline. We propose the Coral Spawn and Larvae Imaging Camera System (CSLICS), which uses low cost modular cameras and object detectors trained using human-in-the-loop labeling approaches for automated spawn counting in larval rearing tanks. This paper details the system engineering, dataset collection, and computer vision techniques to detect, classify and count coral spawn. Experimental results from mass spawning events demonstrate an F1 score of 82.4% for surface spawn detection at different embryogenesis stages, 83% F1 score for sub-surface spawn detection, and a saving of 5,720 hours of labor per spawning event compared to manual sampling methods at the same frequency. Comparison of manual counts with CSLICS monitoring during a mass coral spawning event on the Great Barrier Reef demonstrates CSLICS’ accurate measurement of fertilization success and sub-surface spawn counts. These findings enhance the coral aquaculture process and enable upscaling of reef restoration efforts to address climate change threats facing ecosystems like the Great Barrier Reef.