Fungi Underground Are Visible from Space express
Beneath your feet in the forest, a quiet life unfolds: fungi weave around tree roots and trade nutrients with them. But how do you count how many fungal species are in the soil without digging up the whole forest? It turns out the answer can be seen from space. Spectroscopic analysis of satellite images, processed by a smart program, yields a map of underground diversity.
The program finds patterns in the colors and textures of the images on its own, without needing human hints. It explained more than half of the variation in fungal species counts across 12,000 sites from Europe to Asia. Moreover, satellite data proved more useful than climate, soil, and vegetation type combined.
With this level of detail, you can track fungi over time. In UK forests, old oak woodlands are losing fungal species faster than young plantations. The satellite sees how the invisible half of the forest is changing.
Original abstract
as written by the authors arXiv:2604.09818
Mycorrhizal fungi are vital to terrestrial ecosystem functioning. Yet monitoring their biodiversity at landscape scales is often unfeasible due to time and cost constraints. Current predictions suggest that 90\% of mycorrhizal diversity hotspots remain unprotected, opening questions of how to broadly and effectively map underground fungal communities. Here, we show that self-supervised learning (SSL) applied to satellite imagery can predict below-ground ectomycorrhizal fungal richness across diverse environments. Our models explain over half the variance in species richness across ~12,000 field samples spanning Europe and Asia. SSL-derived features prove to be the single most informative predictor, subsuming the majority of information contained in climate, soil, and land cover datasets. Using this approach, we achieve a 10,000-fold increase in spatial resolution over existing techniques, moving from 1km landscape averages to 10m habitat-scale observations with nearly no systematic bias. As satellite observations are dynamic rather than static, this enables temporal monitoring of below-ground biodiversity at landscape scales for the first time. We analyze multi-year trends in predicted fungal richness across UK National Park woodlands, finding that ancient forests may be losing ectomycorrhizal diversity at disproportionate rates. These results establish SSL satellite features as a scalable tool for extending sparse field observations to continuous, high-resolution biodiversity maps for monitoring the invisible half of terrestrial ecosystems.
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