Machine learning predicts forest soil fungal diversity from drone images

Machine learning predicts forest soil fungal diversity from drone images

Combining drone data and machine learning can help cover more ground in monitoring forest soil health, University of Alberta research shows. The findings are published in the journal Forest Ecology and Management. Using both tools to map and monitor soil fungal diversity—a key indicator of a healthy forest ecosystem—proved highly effective and could help reduce the need for boots-on-the-ground soil sampling over huge areas of forest, says Dr. Ca…

Hidden fungal networks more than 100 quadrillion km in length help plants survive climate change

Researchers at the Technical University of Munich developed a new 3D imaging method that reveals plant roots and fungal networks in real soil without disturbing their natural structure. The research shows how mycorrhizal fungi form vast underground networks that help plants absorb water and nutrients while also reshaping soil structure and potentially improving water retention. The breakthrough could help scientists identify fungal networks that…