Mathematics and AI in Ecology           

Using AI in monitoring and conservation of marine wildlife

Researchers from the School of Mathematical Sciences work at the intersection of Ecology, Statistics and Artificial Intelligence to study behaviour, measure population abundance and understand threats of wild animals. From AI-driven individual animal identification from images to novel statistical models for citizen science, the developed methods provide key tools for wildlife conservation used by many organisations in UK and overseas. The team has also a successful track record in creating novel interactive tools to make their research accessible and engaging with the public on one hand and raise awareness about threatened species on the other.

Recently, they have developed an interactive educational activity that explores the mathematics behind the application of AI in wildlife monitoring and conservation. Using real field data, the users can follow the full research pipeline: uploading photographs, using AI to recognise individual animals, and applying statistical ecology models to infer population characteristics such as abundance and survival. Through this hands-on platform, one can explore key mathematical concepts underpinning AI and statistical modelling, including probability, uncertainty, and bias, and see how these ideas are essential when interpreting AI-generated data. 

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From pixels to population: Using mathematics and AI to study wildlife

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