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AI has untapped potential to advance biodiversity conservation

New research shows artificial intelligence can accelerate species discovery, improve ecosystem tracking and help meet global conservation targets

Date:
May 6, 2025
Source:
McGill University
Summary:
A new study suggests the use of artificial intelligence (AI) to rapidly analyze vast amounts of biodiversity data could revolutionize conservation efforts by enabling scientists and policymakers to make better-informed decisions.
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A new study from McGill University researchers suggests the use of artificial intelligence (AI) to rapidly analyze vast amounts of biodiversity data could revolutionize conservation efforts by enabling scientists and policymakers to make better-informed decisions.

A collaboration between a computer scientist, an ecologist and an international team of researchers, the review published in Nature Reviews Biodiversity examines the seven "global biodiversity knowledge shortfalls," gaps in what we know about species, including their distributions and interactions.

"The problem is that we still don't have basic information about nature, which prevents us from knowing how to protect it," said Laura Pollock, lead author on the study and assistant professor in McGill's Department of Biology.

The study, which reviewed the existing literature on the subject, identifies key ways AI can close these knowledge gaps. The researchers found that AI is currently only being used in two of the seven shortfall areas, leaving significant opportunities untapped. AI-powered tools like BioCLIP are already being used to detect species traits from images, aiding in species identification. Hundreds of new insects are being identified with automated insect monitoring platforms, such as Antenna.

But machine learning models trained on satellite imagery and environmental DNA have the potential to map species distributions more accurately than ever before. AI could also help infer species interactions, such as food webs and predator-prey relationships, which remain largely unstudied due to the difficulty of direct observation.

"This research looks at a much broader set of biodiversity questions than previous reviews," said David Rolnick, co-author of the study, Canada CIFAR AI Chair and assistant professor of computer science at McGill. "It was also surprising to see just how narrowly AI is being applied when it has so much potential to address many of these shortfalls."

Looking ahead, the research team emphasizes the importance of expanding data-sharing initiatives to improve AI model training, refining algorithms to reduce biases and ensuring that AI is used ethically in conservation. With global biodiversity targets looming, they say AI, if harnessed effectively, could be one of the most powerful tools available to address the biodiversity crisis.

"AI is changing the way the world works, for better or worse. This is one of the ways it could help us," said Pollock. "Protecting biodiversity is crucial because ecosystems sustain human life."


Story Source:

Materials provided by McGill University. Note: Content may be edited for style and length.


Journal Reference:

  1. Laura J. Pollock, Justin Kitzes, Sara Beery, Kaitlyn M. Gaynor, Marta A. Jarzyna, Oisin Mac Aodha, Bernd Meyer, David Rolnick, Graham W. Taylor, Devis Tuia, Tanya Berger-Wolf. Harnessing artificial intelligence to fill global shortfalls in biodiversity knowledge. Nature Reviews Biodiversity, 2025; 1 (3): 166 DOI: 10.1038/s44358-025-00022-3

Cite This Page:

McGill University. "AI has untapped potential to advance biodiversity conservation." ScienceDaily. ScienceDaily, 6 May 2025. <www.sciencedaily.com/releases/2025/05/250506170938.htm>.
McGill University. (2025, May 6). AI has untapped potential to advance biodiversity conservation. ScienceDaily. Retrieved May 6, 2025 from www.sciencedaily.com/releases/2025/05/250506170938.htm
McGill University. "AI has untapped potential to advance biodiversity conservation." ScienceDaily. www.sciencedaily.com/releases/2025/05/250506170938.htm (accessed May 6, 2025).

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