I’m a biologist at the Pacific Biological Station with Fisheries and Oceans Canada in Nanaimo, British Columbia. I link theory with data through statistical and simulation models to improve predictions about ecological systems and inform management and policy decisions. In particular, I am interested in spatiotemporal species distribution modelling, how we can estimate population status with limited data, and in the role of variance, risk, and extreme events in population dynamics.

Sean C. Anderson

My research broadly spans the field of quantitative ecology. In my role at Fisheries and Oceans Canada, I am focused on marine fish and fisheries. My current areas of research include:

I teach workshops on statistical modelling and data science in R including multiday workshops on Generalized Linear Mixed Effects Models (GLMMs), Bayesian data analysis in R and Stan, and advanced R.

I develop a number of R packages. For example, with collaborators, I’m developing packages to fit predictive process spatiotemporal GLMMs (generalized linear mixed effect models) (sdmTMB and glmmfields), fit Bayesian statistical models used for COVID-19 forecasts for British Columia and Canada (covidseir), run fisheries stock assessment simulations with Stock Synthesis software (ss3sim), and fit Bayesian Dynamic Factor Analysis time series models (bayesdfa). I also maintain R packages to facilitate rapid data processing, model fitting, and visualization for groundfish stocks on Canada’s West Coast and to facilitate reproducible data-to-document workflows for CSAS (Canadian Science Advisory Secretariat Research) reports (csasdown).

I am interested in taking on postdoctoral researchers and co-supervising graduate students. There are funding opportunities with Fisheries and Oceans Canada. Other excellent funding opportunities are through NSERC/Mitacs, Liber Ero, and the Smith Fellows. If you have a topic of interest, get in touch and we may be able to write a joint proposal.