Mairin Deith
Systems Ecologist
Key skills: Statistical and simulation modeling, life cycle modelling of salmonids, landscape ecology, GIS, Bayesian and frequentist hierarchical statistics, decision analysis, data visualization, programming in R.
Dr. Mairin Deith is a quantitative ecologist focusing on analytical and simulation-based approaches to complex ecological challenges. Her work addresses “wicked” problems spanning diverse ecosystems from remote Pacific coral atolls to Southeast Asian tropical forests and temperate aquatic environments. Central to her work is the application of quantitative models and software to support decision-making in data-limited situations, with a focus on assessing and quantifying uncertainty and its impacts.
Mairin brings expertise in ecological modeling, data science, and decision analysis. Before joining ESSA Technologies, she was a postdoctoral researcher at the University of British Columbia (UBC) in partnership with the U.S. Army Corps of Engineers. In this role, she developed life cycle models to evaluate the impacts of high-head dams on juvenile fish passage and long-term population viability of Chinook and steelhead populations in Oregon. She also assessed the potential effects of hatchery augmentation programs on salmonid populations in Oregon and British Columbia.
Mairin has also worked extensively as an independent contractor for academic, government, and non-profit organizations. Her projects include developing R software for population viability analysis in aquatic invasive species removal, spatial modeling of Pacific Ocean groundfish species, and building Shiny applications that allow for diverse audiences to use and understand scientific models. She has also automated the analysis of chemical isotope data for Columbia White Sturgeon and developed Bayesian decision networks for fisheries management strategy evaluations.
She holds a B.Sc. in Biology with Honours from the University of Victoria, where she researched functional and biological diversity in coral reef fish communities and their responses to ecological processes and fishing pressure. She earned her Ph.D. in Zoology from UBC, where she used simulation models, hierarchical Bayesian statistics, Bayesian decision networks and decision analysis to examine the distribution and sustainability of wild meat hunting in data-deficient tropical forests. Her doctoral work also involved developing spatial movement and harvest models to predict hunting pressure and sustainability outcomes.
Beyond research, Mairin has contributed to science communication and education. She has developed and delivered coding workshops, built public-facing R Shiny applications, and engaged in outreach efforts, including mentoring and advising non-profit organizations on data science applications.
When not working, Mairin enjoys tide-pool walking, biking, gardening, knitting, and indulging in science fiction.