Can artificial intelligence save the Great Barrier Reef?
Australian researchers are designing a global real-time monitoring system to help save the world's coral reefs from further decline, primarily due to bleaching caused by global warming. The has been published in the journal Electronics.
Coral reefs worldwide are dying at an alarming rate, with 75% of reefs experiencing bleaching-level heat stress in the past two years.
The World Heritage-listed Great Barrier Reef (GBR), considered the jewel in the crown of coral reefs worldwide and one of Australia's most significant ecological and tourism assets, has been decimated by severe bleaching events since 2016, exacerbated by ongoing crown-of-thorns starfish outbreaks and coastal development.
A collaborative project led by the University of South Australia (UniSA), with input from Queensland and Victorian researchers, is integrating remote sensing technologies with machine learning, artificial intelligence and Geographic Information Systems (GIS) to monitor and hopefully stall the damage to the world's most fragile marine ecosystems.
A multimodal platform will distill all research data relating to coral reefs, including underwater videos and photographs, satellite images, text files and time-sensor readings, onto a central dashboard for real-time global monitoring.
UniSA data analyst and lead researcher Dr. Abdullahi Chowdhury says that a single centralized model will integrate all factors affecting coral reefs and provide environmental scientists with real-time predictions.
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"At the moment we have separate models that analyze substantial data on reef health—including bleaching levels, disease incidence, juvenile coral density and reef fish abundance—but these data sets are not integrated, and they exist in silos," Dr. Chowdhury says.
"Consequently, it is challenging to see the 'big picture' of reef health or to conduct large scale, real-time analyses."
The researchers say an integrated system will track bleaching severity and trends over time; monitor crown-of-thorns starfish populations and predation risks; detect disease outbreaks and juvenile coral levels; and assess reef fish abundance, diversity, length, and biomass.
"By centralizing all this data in real time, we can generate predictive models that will help conservation efforts, enabling earlier intervention," according to Central Queensland University Ph.D. candidate Musfera Jahan, a GIS data expert.
"Our coral reefs are dying very fast due to climate change—not just in Australia but across the world—so we need to take serious action pretty quickly," Ms. Jahan says.
Coral reefs are often referred to as the "rainforests of the sea." They make up just 1% of the world's ocean area but they host 25% of all marine life.
The technology will bring together datasets from organizations like the National Oceanic and Atmospheric Administration (NOAA), the Monterey Bay Aquarium Research Institute (MBARI), the Hawaii Undersea Research Laboratory (HURL) and Australia's CSIRO.
"The future of coral reef conservation lies at the intersection of technology and collaboration. This research provides a roadmap for harnessing these technologies to ensure the survival of coral reefs for generations to come," the researchers say.
More information: Abdullahi Chowdhury et al, Coral Reef Surveillance with Machine Learning: A Review of Datasets, Techniques, and Challenges, Electronics (2024).
Provided by University of South Australia