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BERA News Fall 2022
Resource
Understanding how birds respond to landscape disturbance is key to effective restoration. Two studies used non-invasive microphone arrays to determine the exact locations of singing individuals in the...
BERA News Spring 2022
Resource
Mounding is a common restoration technique designed to improve microsite conditions for planted seedlings in wetlands. There are a variety of strategies for constructing mounds, though, and how mounds...
The Boreal Ecosystem Recovery and Assessment (BERA)
Project
Organization:
The boreal region of Alberta contains extensive disturbances from natural resource extraction. Roads, well pads, seismic lines (petroleum-exploration corridors), forest-harvest areas, and other...
The Edge 2022 (BERA Systhesis)
Resource
The central goal of the Boreal Ecosystem Recovery and Assessment (BERA) program is to understand the effects of industrial disturbance on natural ecosystem dynamics, and to develop strategies for...
The Edge: The BERA Program 2024 Synthesis Report
Resource
The 2024 issue of The Edge summarizes the following key findings: Plan A better understanding of passive recovery trajectories will help guide restoration planning LiDAR is a powerful planning tool...
Tracking Vegetation Transitions Due to Invasion of Cattail (Typha) in Lake Superior Coastal Peatlands
Resource
Invasive cattails ( Typha angustifolia and Typha × glauca) pose a problem for many Laurentian Great Lakes wetlands, especially sedge/grass meadows. In western Lake Superior, early signs of invasion...
Webinar - Climate Variability and Change in the Southern Boreal Forest of Northern Saskatchewan
Resource
Presented by Dave Sauchyn, Director of the Prairie Adaptation Research Collaborative at the University of Regina and Professor of Geography and Environmental Studies. Since the mid 20th century, mean...
Webinar: Flooding Risk Prediction on Agricultural Lands Using Artificial Intelligence Techniques
Event
Event Date and Time
September 27th, 2023 at 12:00pm MST to September 27th, 2023 at 1:00pm MST
The study will employ the latest artificial intelligence methodologies for data processing and predictive risk modeling approach