Introduction
Researchers are using artificial intelligence (AI) more and more to track biodiversity and support efforts to save endangered species. Artificial Intelligence has the potential to analyze enormous amounts of real-world data quickly and efficiently, in contrast to traditional methods that can upset ecosystems or need a lot of time, labor, and resources.
Carl Chalmers, a machine learning researcher at Conservation AI, a non-profit organization in Liverpool, UK, employs AI technology for various ecology projects. He states, "Without AI, we're never going to achieve the UN's targets for protecting endangered specie.
With up to a million species at risk of extinction, species are disappearing hundreds to thousands of times faster than they did millions of years ago1. As a result, the UN established a target in 2020 to protect at least 30% of the planet's land and seas by the end of that year.
AI is "imperfect," but it has the potential to speed up significant discoveries, according to Nicolas Nail he, the founder of The Future Society, a global non-profit dedicated to improving AI governance. Nail he is based in Paris. He states, "To design models, as well as collect, label, quality check, and interpret data, we very much need human practitioners in the loop
Sound analysis
By recognizing animal species from audio recordings, ecologist Jörg Müller of the University of Würzburg, Germany, and his colleagues have demonstrated how artificial intelligence (AI) tools can assist in quantifying biodiversity in tropical forests.
In a study that was published on October 17 in Nature Communications2, researchers analyzed animal "soundscapes" in the Chocolate, an area of Ecuador renowned for its high species diversity, using artificial intelligence. Forty-three plots of land, comprising. By abandoned areas that had begun to regenerate, and deforested land actively utilized for pasture and cacao plantations, were equipped with recorders. Experts who received the audio files were able to identify 183 birds, 41 amphibians, and 3
Camera-trap video
Researchers at Conservation AI have created models that can search through photos and videos taken by drones or camera traps in order to track the movements of animals and identify wildlife, including species that are in grave danger of extinction.
The technology they developed allows them to automatically analyze images, videos, and audio files, including data from real-time camera-trap footage and other sensors that authorized users can upload. The platform they built us available for free online. When a species of interest us spotted in user-uploaded footage, users can choose to receive an email alert.
More than 12.5 million photos have been processed by Conservation AI to date, and over 4 million individual animal appearances from 68 species—including endangered pangolins in Uganda, gorillas in Gabon, and orangutans in Malaysia—have been found. "The system can
Artificial intelligence (AI) can be used to model the effects of human activity on an ecosystem and reconstruct historical changes, in addition to tracking biodiversity in real time. Researchers have employed artificial intelligence (AI) to ascertain how biodiversity loss in a freshwater ecosystem has resulted from a century of environmental degradation.
While the loss of biodiversity in rivers and lakes due to human activity is widely documented, little is known about the environmental factors that have the biggest effects. Luisa Ordinary, and researcher at the University of Birmingham in the United Kingdom, states that "long-term data is pivotal to link changes in biodiversity to environmental change and to define achievable conservation goals."
Using artificial intelligence, Orsini and her colleagues created a model that connects biodiversity to past environmental changes. In an
Using an AI built to handle a variety of information types, the scientists then combined these data with climate data from a weather station and chemical pollution data from direct measurements and national surveys. Finding correlations amongst the "mayhem" of data was the goal, according to Orsini.
It was discovered that up to 90% of the decline in biodiversity in the lake could be accounted for by the use of fungicides and insecticides in conjunction with precipitation and periods of extremely high temperatures. Study co-author Jiarui Zhou, who is also affiliated with the University of Birmingham, says, "Learning from the past, we showcased the value of AI-based approaches for understanding past drivers of biodiversity loss."
According to Orsini, the fundamental advantage of using AI is that it is data-driven and devoid of hypothesis. "AI 'learns' from historical data
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