Accessible AI Enhances Monitoring of Coral Seeding Devices in Reef Restoration
1. Coral seeding devices (CSDs) - tools designed to deliver sexually propagated corals to target locations - offer a promising means to increase coral abundance on degraded reefs. However, evaluating CSD effectiveness for coral reef restoration across wide areas and over many years is limited by the lack of robust and efficient monitoring approaches. Large-area reef imagery offers an attractive potential solution, but manual detection of CSDs within imagery is slow and limits the scalability of CSD monitoring. 2. We investigated whether machine learning classifiers could accurately detect CSDs in reef orthoimages and tested the performance of classifiers created following minimal manual annotation effort. Using freely available software, we first evaluated classifier performance in a single-site experiment using an orthoimage containing 989 CSDs deployed in Palau. We then also evaluated performance in a multi-site experiment using orthoimages containing a different CSD design deployed across seven sites in the central Great Barrier Reef, Australia. 3. In Experiment 1, classifiers trained on just 30 CSDs annotated within 10 minutes achieved mean recall and precision of 96.7% and 97.1% respectively, reducing manual annotation time by 95.6% whilst still detecting 98.8% of the number of devices found manually. Larger training sets yielded less reliable classifiers and required more manual effort. In Experiment 2, classifiers trained on 30 CSD annotations from one site performed excellently across seven orthoimages from multiple reefs, achieving mean recall and precision of 99.2% and 93.3%. 4. We present evidence that CSD classifiers can be highly effective across both single- and multi-site CSD deployments. In using a free and user-friendly software, we also demonstrate their accessibility to reef restoration practitioners. To facilitate wider uptake of CSD monitoring, we provide a step-by-step protocol for implementing CSD classifiers. By improving access to efficient, direct assessment of intervention outcomes, this method can play a vital role in guiding the enhancement of approaches aiming to restore coral reefs.