AI in Coral Reef Monitoring Quiz

Answers and explanations appear as you take the quiz.

1. What visual change in coral does an AI bleaching detector primarily look for?
   • A shift toward pale, white, low-saturation tissue
   • Increased green algal cover on the coral
   • A drop in water temperature around the coral
   • Growth of new coral branches
2. Which widely used tool applies machine learning to auto-annotate benthic survey photos?
   • TensorFlow Reef
   • CoralNet
   • DeepBlue
   • SeaScan
3. What is a major reason AI is needed for reef monitoring?
   • Coral reefs are too cold for human divers
   • Satellites cannot photograph the ocean
   • Imagery from cameras and AUVs vastly exceeds what humans can label by hand
   • Coral does not change over time
4. What does the Allen Coral Atlas primarily combine with AI?
   • Tide gauge readings
   • Fishing-boat logbooks
   • Diver heart-rate data
   • Satellite imagery
5. Why is 'domain shift' a challenge for reef-classification models?
   • Water clarity, lighting, and camera color vary widely across sites
   • Reefs are always photographed at the same depth
   • Coral species are identical worldwide
   • AI cannot process color images
6. Besides imagery, what emerging data source can AI use to assess reef health?
   • The phase of the moon
   • The reef's underwater soundscape
   • The number of nearby ships
   • Ocean salinity alone
7. Which satellite-derived variable can be combined with reef imagery to flag bleaching risk?
   • The amount of traffic on nearby roads
   • The average height of coastal buildings
   • Sea-surface temperature and related heat-stress measures
   • The number of boats registered in the reef region
8. What benthic cover information can reef classifiers estimate from survey photos?
   • Only the water's salinity and pH
   • The total number of fish species in the ocean
   • The age of every coral colony in years
   • Percent cover of live coral, algae, sand, and rubble