Researchers are increasingly using artificial intelligence (AI) to monitor biodiversity and support endangered species. AI has the potential to quickly and effectively analyze large amounts of real-world data without disrupting ecosystems or requiring a significant amount of time, labor, and resources. A spokesperson for Conservation AI asserts that achieving the United Nations’ targets for protecting endangered species is impossible without AI. The UN aims to safeguard at least 30% of Earth’s land and oceans by the end of the decade. While AI is far from perfect, Conservation AI researchers believe it can accelerate important discoveries.
Researchers at the University of Würzburg in Germany have demonstrated that AI can be used to quantify biodiversity in tropical forests by analyzing animal species from audio recordings. In a study published in Nature Communications, the researchers used AI to analyze animal sounds in the Chocó region of Ecuador, identifying various bird, amphibian, and mammalian species. Researchers emphasize the need for more training data collected by humans to further advance AI in species identification in the tropics. AI’s ability to precisely measure biodiversity in regenerated forests can be crucial in evaluating biodiversity projects for funding.
AI not only allows for real-time biodiversity monitoring, but also can track the impact of human activities on ecosystems, and aid in reconstructing historical ecosystem changes. AI has been used to understand how a century’s worth of environmental degradation in a freshwater ecosystem has led to biodiversity loss. By linking biodiversity to historical environmental changes, AI has allowed researchers to identify insecticides, fungicides, extreme-temperature events, and precipitation as factors contributing to biodiversity loss in a contaminated rural lake. AI’s ability to learn from past data and predict future trends in biodiversity with higher accuracy makes it a valuable tool to scientists.
The whytry.ai article you just read is a brief synopsis; the original article can be found here: Read the Full Article…
