Friday June 16, 2023

Eos —

North American beavers transform ecosystems with their engineering prowess. By ponding water, excavating channels, and foraging nearby vegetation, they drastically alter landscapes across a variety of environments, from tundra to deserts.

Two centuries of fur trading starting in the 17th century decimated the thick-coated builders, but today, beaver populations are rebounding gradually. That’s good news for many ecosystems because beaver construction creates valuable habitats for endangered species, traps carbon, and improves water availability in dry places.

Despite these ecologic implications, large-scale mapping of beaver habitats has been missing from scientific research. Most mapped dams are identified manually, which takes a lot of time and effort.

To accelerate beaver dam identification, Fairfax et al. applied machine learning to scour high-resolution geospatial imagery for likely dam complexes across landscape- and regional-scale areas. The researchers developed the Earth Engine Automated Geospatial Element(s) Recognition (EEAGER) model, which uses a neural network trained on thousands of known locations of beaver dams in aerial and satellite images.

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