Erin Bayne, PhD MSc BSc (Hons)
Pronouns: He, him, his
Contact
Professor, Faculty of Science - Biological Sciences
- bayne@ualberta.ca
- Phone
- (780) 492-4165
- Address
-
1-275 Centennial Ctr For Interdisciplinary SCS II
11335 Saskatchewan Drive NWEdmonton ABT6G 2H5
Overview
Area of Study / Keywords
Bioacoustics Landscape Ecology Human Impacts Wildlife
About
In addition to my responsibilities as a professor, I am academic director of the WildTrax information system which is used for the open-access sharing and processing of remote camera and ARU data, academic co-director of the Alberta Biodiversity Monitoring Institute's Science Centre, academic co-director of the Boreal Avian Modelling center, and director of the University of Alberta Field Research Office. My lab has participated in the Land Reclamation International Graduate School (LRIGS) and Computational Biodiversity Science and Services (BIOS²) programs sponsored by NSERC CREATE. Current lab members can access information on our internal website
Research
We use autonomous recording units, remote cameras, and telemetry to understand behavioral, population, and community responses of wildlife to human activities. We work closely with industry, conservation organizations, and government to create large-scale models of how human activities influence habitat suitability for a variety of species. Our goal is to understand the various ecological/ economic trade-offs inherent in land-use management. Using big-data approaches we are improving how these technologies are used for monitoring and research by applying advances in machine learning, remote sensing, and automated species recognition to develop more effective data pipelines and workflows.
Summaries of our most recent research papers are here
Courses
BIOL 330 - Introduction to Biological Data
Expands on prior introductions to the scientific method and examines the steps involved in the planning, collection, organization, analysis and presentation of biological data. Classes will explore the types of data used to answer a variety of biological questions and will review several different sampling designs, assess the benefits and limitations of various data types for scientific inference, and integrate the statistical methods that are common to other introductory courses. Labs will teach students how spreadsheets and relational databases can be used to manipulate, analyze, and present the results of scientific research. Prerequisites: BIOL 208 and STAT 151 or SCI 151.
BIOL 471 - Landscape Ecology
Landscapes are holistic entities whose patterns influence ecological processes. Topics highlighted in this course include landscape components, morphology and dynamics; detecting spatial/temporal change in landscapes; issues of scales; movements of organisms, disturbances, and nutrients across landscape mosaics; and restoration, planning and management in a landscape context. Labs emphasize GIS applications to characterizing landscape patterns and heterogeneity in space and time, distributing and moving organisms across landscapes, and restoring or planning landscapes for conservation objectives. Prerequisites: MATH 115 or SCI 100; STAT 151 or SCI 151; one of BIOL 331, 332 or BOT 332. Previous GIS course is useful. Credit cannot be obtained for both BIOL 471 and 571.
BIOL 571 - Landscape Ecology and Applications
Landscapes are holistic entities whose patterns influence ecological processes. Topics highlighted in this course include landscape components, morphology and dynamics; detecting spatial/temporal change in landscapes; issues of scales; movements of organisms, disturbances, and nutrients across landscape mosaics; and restoration, planning and management in a landscape context. Labs emphasize GIS applications to characterizing landscape patterns and heterogeneity in space and time, distributing and moving organisms across landscapes, and restoring or planning landscapes for conservation objectives. Lectures and labs are the same as for BIOL 471, but with an additional research project and evaluation appropriate to graduate studies. Prerequisite: consent of instructor. Credit cannot be obtained for both BIOL 471 and 571.
Research Students
Currently accepting undergraduate students for research project supervision.
The lab provides opportunities for undergraduates interested in learning how to process sound data and camera images. That information is then used with GIS tools to build statistical models that predict how species react to natural and human variation in the environment. Students interested in the use of advanced computing and analysis in conservation biology are encouraged to reach out.