KNOWLEDGE BASE

A 2023 survey in Devon, England, found beavers in the Rivers Exe and Taw. The researchers covered over 250 km by foot and canoe, finding six active territories on the Exe and four on the Taw. The beaver populations were small and in their early stages, with few impacts observed - for example, only three lodges were found and damming throughout the catchment was low. The findings were set to help develop strategies for the coexistence of beavers and human communities.

To the west of the Ural mountains, in European Russia, scientists surveyed ten rivers, seeking to understand where beavers built their dams. They found that beavers preferred rivers with loamy soils and with slopes under 3% - the dams got taller as the slope got steeper. The paper included further analyses of the size and shapes of beavers' dams and ponds, discussing their potential contributions in a world of climate change, and also included some pretty impressive photos!

In this study, researchers compared the adrenal glands of male and female Eurasian beavers. They found that the anatomy and histology (microscopic-scale anatomy) of these glands were the same in both sexes. However, a hormone called corticosterone was produced more in females, and certain biochemical receptors were more prevalent in males. Please note, this resource is not open-access.

In this book chapter, the authors explored how river corridors respond to wildfire, defining and distinguishing between three responses: resistance, resilience, and sensitivity. By comparing and contrasting a range of case studies, the authors highlighted the impact that beaver activity can have in improving river resilience, and the potential for beaver reintroduction contributing to watershed-scale restoration.

This experiment tested whether a computer algorithm could help identify individual Eurasian beavers based on their tail scale patterns, extracted from photos, using them a bit like human fingerprints. The algorithm successfully distinguished 95.7% of the beavers, showing that this could be a reliable, non-invasive method for animal recognition. The authors highlighted that this algorithm could allow large sets of photos (with different scaling, illumination, and rotation) to be processed much more quickly than before.