Open Collections

Matechuk, Landen

University of British Columbia

Beavers inhabit and alter freshwater ecosystems through the construction of beaver dams, lodges, ponds and canals. Beaver-controlled stream systems exhibit increased sediment and water storage, creating pools and important habitats for fish and invertebrates. However, determining historic and or suitable beaver habitats poses a challenge due to factors such as trapping, land use disturbances, and climate change. As interest in restoring riverine and stream ecosystems grows, the reintroduction of beavers and construction of beaver dam analogs—man-made structures designed to mimic natural beaver dams—are increasingly being used to rehabilitate impaired riverine habitats. A mapping approach that identifies suitable topographic and environmental conditions associated with successful beaver habitats would therefore be a useful guide for future freshwater ecosystem restoration efforts. In this study, beaver dam locations were identified and used to train a random forest machine learning model to assess stream, wetland and river beaver habitat suitability. The model uses provincially available topographic, biological, and hydrologic variables to test their importance for predicting the presence or absence of beaver dams. This procedure produced a measure of habitat suitability with an accuracy score of 97%. The research discussed here can contribute to informed decision-making regarding the reintroduction of beavers and the restoration of stream systems, promoting ecological balance and enhancing the natural state of riverine ecosystems.

Text

2024-08-15

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/88940

Geography

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/