Beaver Library

Beavers are ecosystem engineers that create and maintain riparian wetland ecosystems in a variety of ecologic, climatic, and physical settings. Despite the large-scale implications of ongoing beaver conservation and range expansion, relatively few landscape-scale studies have been conducted, due in part to the significant time required to manually locate beaver dams at scale. To address this need, we developed EEAGER—an image recognition machine learning model that detects beaver complexes in aerial and satellite imagery. We developed the model in the western United States using 13,344 known beaver dam locations and 56,728 nearby locations without beaver dams. Performance assessment was performed in twelve held out evaluation polygons of known beaver occupancy but previously unmapped dam locations. These polygons represented regions similar to the training data as well as more novel landscape settings. Our model performed well overall (accuracy = 98.5%, recall = 63.03%, precision = 25.83%) in these areas, with stronger performance in regions similar to where the model had been trained. We favored recall over precision, which results in a more complete catalog of beaver dams found but also a higher incidence of false positives to be manually removed during quality control. These results have far-reaching implications for monitoring of beaver-based river restoration, as well as potential applications detecting other complex landforms.

A decision support and planning tool for beaver management, to analyze all perennial rivers and streams in Utah. This model assess the upper limits of riverscapes to support beaver dam-building activities.

Traditional restoration efforts are barely scratching the surface of what could be restored. Moreover, a disproportionate amount of funds are spent on too few miles of streams and rivers leaving millions of miles of degraded streams neglected. To fill this gap, restoration practitioners are increasingly trying restoration techniques that are more cost?effective, less intensive, and can more practically scale up to the enormous scope of degradation.

The Low-Tech Process Based Restoration of Riverscapes Pocket Guide is an illustrated and condensed version of the Design Manual. The pocket guide is designed to fit in your pocket (4 x 6”) to use as a reference in the field. 2019.

This fourth webinar in the ASWM-BLM Beaver Restoration Webinar Series focused on common barriers to beaver restoration and beaver dam analog (BDA) work and when/how these barriers can be overcome.

The Utah Beaver Restoration Assessment Tool (BRAT) serves as a decision support and planning tool intended to help resource managers, restoration practitioners, wildlife biologists and researchers assess the potential for beaver as a stream conservation and restoration agent over large regions.