AI can protect endangered species by mapping and tracking their behaviour and movements - a “time machine for biodiversity”
How can AI help to save endangered species? By using its capacity to sift through massive amounts of animal data, and identify ecological patterns and distinctive behaviours from them.
Conservation AI
Based in Liverpool, Conservation AI uses machine learning to process footage from drones or field camera, identifying species as they move around their environment (see their latest categorisation above—orangutans). Humans can identify a few thousand an hour, but ML/AI can do tens of thousands. As Nature reports:
CAI have handled more than 12.5 million images and detected more than 4 million individual animal appearances across 68 species, including endangered pangolins in Uganda, gorillas in Gabon and orangutans in Malaysia. Says Paul Fergus, one of Conservation Al's lead researchers. "The speed at which Al processes data could allow to protect vulnerable species from sudden threats — such as poaching and fires—quickly," he adds. Conservation Al has already caught a pangolin poacher in the act by analysing footage in real time.
Data-crunching birdsong
As reported on the University of Wurzberg’s website:
Tropical forests are among the most important habitats on our planet. They are characterised by extremely high species diversity and play an eminent role in the global carbon cycle and the world climate. However, many tropical forest areas have been deforested and overexploitation continues day by day.
Reforested areas in the tropics are therefore becoming increasingly important for the climate and biodiversity. How well biodiversity develops on such areas can be monitored very well with an automated analysis of animal sounds.
As part of the DFG research group Reassembly, the team worked in northern Ecuador on abandoned pastures and former cacao plantations where forest is gradually reestablishing itself. There, they investigated whether autonomous sound recorders and artificial intelligence (AI) can be used to automatically recognise how the species communities of birds, amphibians and mammals are composed.
"The research results show that the sound data reflect excellently the return of biodiversity in abandoned agricultural areas," Professor Jörg Müller saids.
Overall it is particularly the communities of vocalizing species that mirrors the recolonisation very well... A preliminary set of 70 AI bird models was able to describe the entire species-communities of birds, amphibians and some calling mammals. Even the changes in nocturnal insects could be meaningfully correlated with them.
“A Time Machine for Biodiversity”
As reported from the Goethe University website:
An AI model developed by a team of scientists from Goethe University Frankfurt and the University of Birmingham, led by Niamh Eastwood and Prof. Luisa Orsini, shows how water pollution, extreme weather events and rising temperatures can change and irreversibly damage the ecosystem of a freshwater lake over many decades.
The model uses weather and climate data as well as data extracted from a sediment core taken from the lake and could in future be used to predict how ecosystems react to complex environmental changes.
As such, it could serve as a “time machine for biodiversity”, explaining past processes while simultaneously pointing to future ecological dangers.
We were also interested to find this July Medium piece from laywer Dennis Hillemann, laying out ‘The Promise and Peril of Artificial Intelligence for Wildlife Conservation’. From its conclusion:
…responsible stewardship of AI for wildlife conservation – focused on balancing its promise with managing potential risks – will determine whether this powerful technology ultimately becomes savior or scourge for vulnerable species.
Conservation goals like preserving biodiversity and ecological balance, rather than simply targeted metrics like reduce poaching incidents, must guide how AI systems are developed, governed. and integrated into environmental protection efforts.
With ethical oversight mechanisms and an eco-centric worldview, AI has the potential to augment – rather than automate away – the uniquely human spirit of caring for nature that mobilizes conservation action.
More here. There is also an evident balance to be struck between AI’s utility in mapping ecosystems, and its energy and material resource requirements - growing ever larger.