Beaver Library

Wildlife translocation facilitates conservation efforts, including recovering imperiled species, reducing human–wildlife conflict, and restoring degraded ecosystems. Beaver (American, Castor canadensis; Eurasian, C. fiber) translocation may mitigate human–wildlife conflict and facilitate ecosystem restoration. However, few projects measure outcomes of translocations by monitoring beaver postrelease, and translocation to desert streams is relatively rare. We captured, tagged, and monitored 47 American beavers (hereafter, beavers) which we then translocated to two desert rivers in Utah, USA, to assist in passive river restoration. We compared translocated beaver site fidelity, survival, and dam-building behavior to 24 resident beavers. We observed high apparent survival (i.e., survived and stayed in the study site) for eight weeks postrelease of resident adult beavers (0.88 ± 0.08; standard error) and lower but similar apparent survival rates between resident subadult (0.15 ± 0.15), translocated adult (0.26 ± 0.12), and translocated subadult beavers (0.09 ± 0.08). Neither the pre- nor the post-translocation count of river reaches with beaver dams were predicted well by the Beaver Restoration Assessment Tool, which estimates maximum beaver dam capacity by river reach, suggesting beaver-related restoration is not maximized in these rivers. Translocated beavers exhibited similar characteristics as resident subadult beavers during dispersal; they were more vulnerable to predation and many emigrated from the study sites. High mortality and low site fidelity should be anticipated when translocating beavers, but even so, translocation may have contributed to additional beaver dams in the restoration sites, which is the common goal of beaver-assisted river restoration. Multiple releases at targeted restoration sites may eventually result in establishment and meet conservation objectives for desert rivers.

Beavers are ecosystem engineers that can dramatically change the shape of the landscape and how water moves through it. They create and maintain wetland environments across North America and Eurasia in a wide variety of places, including mountains, deserts, coasts, forests, grasslands, shrublands, etc. Despite their large influence on the landscape, there are very few programs that monitor them at the landscape, regional, or continental scale. This is partially due to how much time it takes to find and identify beaver dams in satellite and aerial images. To make it easier for us to find and understand the influence of beavers at larger scales, we built a model that can automatically find beaver dams in satellite and aerial imagery. While our model is trained to find beaver dams, this type of model has promise for finding other landscape features too. The model isn’t perfect, but it is a strong starting point and will continue to improve as more people use it.

A current challenge in ecohydrology is the incorporation of beaver dams into hydrological models. Select works have attempted to solve this problem using routing approaches, Manning coefficient variations, pond dynamics, or fully-distributed hydraulic models; however, all these approaches assume that all beaver dams are homogeneous structures and react in the same way to rainfall events. Recent findings highlight the importance of including the functional heterogeneity of beaver dams, especially the water path past the dam (dam flow state). To overcome the challenge of accounting for different dam flow states interrupting downstream water transmission in different ways, we developed BEAVERPY, a flow state-based Python package that can be coupled with the platform Cold Regions Hydrological Model (CRHM) to represent both streamflow modulation by ponds and dams, while also simulating infiltration and evapotranspiration. We used the broad-crested weir equation for the overflow dams, the Darcy equation for the seep flow dams, and the v-notch weir equation for the gapflow dams, verifying each case with synthetic experiments. To calibrate and validate the model, we instrumented the ponds and streams in a peatland fen in the Canadian Rocky Mountains in Alberta with level sensors and ‘DamCams’ (trail cameras) to capture flow type. Then, we used LIDAR DEM data and high-resolution imagery to delineate the hydrological response units. Each pond is represented as an HRU, which can interact with soil and routing modules. Finally, we conducted a scenario-testing experiment to understand the sensitivity of different beaver dam flow states for several storms. The results indicate the importance of including flow state dynamics for the beaver dam representations, and highlight the importance of integrating animal-ecological aspects into the streamflow modelling. This research has implications for understanding the use of  beaver as a nature-based solution for flood mitigation and river restoration.