Artificial Intelligence Assists Researchers in Monitoring Endangered Pink Dolphins via Acoustic Surveillance

Researchers have used artificial intelligence (AI) to map the movements of two endangered species of dolphin in the Amazon River by training a neural network to recognize the animals’ unique clicks and whistles.

The findings, published in Scientific Reports on 27 July¹, could lead to better conservation strategies by helping researchers to build an accurate picture of the dolphins’ movements across a vast area of rainforest that becomes submerged each year after the rainy season.

Using sound is much less invasive than conventional tracking techniques, such as the use of GPS tags, boats or aerial drones.

Saving the Amazon: how science is helping Indigenous people protect their homelands

“Sound is probably the only sense that we know of that we all share on Earth,” says co-author Michel André, a bioacoustician at the Technical University of Catalonia in Barcelona, Spain.

André and his colleagues wanted to explore the activity of two species, the boto (Inia geoffrensis) — also known as the pink river dolphin — and the tucuxi (Sotalia fluviatilis) across the floodplains of the Mamirauá reserve in northern Brazil. The researchers placed underwater microphones at several sites to eavesdrop on the animals’ whereabouts.

To distinguish the dolphin sounds from the noisy soundscape of the Amazon, they turned to AI, feeding the recordings into a deep-learning neural network capable of categorizing sounds in real time, “exactly as we do with our own brain”, says André.

Using this technology, researchers can analyse volumes of information “that would otherwise be almost impossible”, says Federico Mosquera-Guerra, who studies Amazonian dolphins at the National University of Colombia in Bogotá.

The AI was trained to identify three types of sound: dolphin, rainfall and boat engines. Both dolphin species use echolocation clicks almost constantly to sense their environment, and they communicate to others by whistling. Detecting these clicks and whistles enabled the researchers to map the animals’ movements. Botos and tucuxis have distinct whistles, so the neural network could distinguish between the species.

Conservation efforts

The study is part of a collaboration between the Technical University of Catalonia and the Mamirauá Institute of Sustainable Development in Tefé, Brazil, which aims to use this technology for monitoring the Amazon’s biodiversity and threats to it.

AI empowers conservation biology

Both dolphin species are endangered: estimates suggest that the boto population is declining by 50% every ten years, and the tucuxi population every nine years². Monitoring when and where the animals move will allow researchers to help protect their populations and come up with measures to help “Indigenous communities to cohabitate with the presence of dolphins”, says André. Dolphins can disrupt fisheries across the floodplains, for example, by competing for fish or becoming tangled in nets.

Mosquera-Guerra says that collecting such information is “fundamental” to inform decisions on conservation across the Amazon region.

In future, the team wants to train the neural network to detect other aquatic species, and to deploy the system over a wider area. The same approach could also be used in the ocean. André’s previous work using this system has shown the effects of human-made noise pollution on sperm whales, and has enabled the development of a warning system for ships to help avoid the animals³.