The following are currently working in or associated with the Gillis Lab:

Dr. Darren M. Gillis is the principle investigator of the lab, holding an NSERC Discovery Grant titled: The impact of ecological dynamics and statistical properties in fisheries data on the sustainability of fish populations and harvest. He has a long standing interest in applying behavioural theory to the study of commercial fisheries through current and emerging quantitative methods.

Frank Vattheuer (M.Sc. student) has a B.Sc. in Biological Sciences from the University of Manitoba. He enjoys ecology and quantitative analysis. After working in our lab as an undergraduate research assistant, he has returned to study the interplay of causality in catch and effort data from commercial fisheries.

Jonah Koscielny (M.Sc. student) is working with Dr. Gillis on the impact of the Ideal Free Distribution on the estimation of Maximum Sutainable Yield in spatially complex fisheries. He is supporting the project through his developing skills in differential equation modeling through R, Agent Based Modeling through Netlogo, and their influence on stock assessments using Baysian surplus production models and Stock Synthesis.

Dr. Inesh Munaweera (Ph.D. graduate, 2023. Co-supervised with Dr. Saman Muthukumarana @ University of Manitoba, Statistics) completed his thesis Bayesian Modeling and Simulation Methods for Fish Movements using data from Lake Winnipeg and Arctic fisheries. His work developed Bayesian methods for the analysis of fish telemetry data for population estimation and movement reconstruction. It provides a modelling framework to elucidate factors that impact both natural and fishing mortality in exploited species.

Brooke Biddlecomb (Ph.D. candidate - co-supervised with Dr. Cortney Wheeler (Watt) @ the Freshwater Institute, Fisheries and Oceans Canada). Her thesis work is focused on developing population models for various Arctic marine mammals based upon survey data to inform local harvests and conservation measures. Data from counts, harvests, and genetic samples are used to develop Bayesian models to follow population trajectories in these culturally significant species.

Hailey Chymy (M.Sc. student - co-supervised with Dr. Kim Howland @ the Freshwater Institute, Fisheries and Oceans Canada) is developing population estimates for the commercial Lake Trout fishery of Great Slave Lake. Specifically, she is investigating the application of data-limited methods such as CMSY++ and Bayesian biomass dynamics models to the fishery’s historical records.

Laura Alsip (M.Sc. Student - co-supervised with Dr. Xinhua Zhu @ the Freshwater Institute, Fisheries and Oceans Canada) is developing improved population abundance indices for the Lake Whitefish of Great Slave Lake using survey data series. She is applying Gaussian Markov Random Fields to account for spatial covariance within a Bayesian framework.

Jesse Shirton (M.Sc. student - co-supervised with Dr. Kim Howland @ the Freshwater Institute, Fisheries and Oceans Canada) is developing a population assessment of Lake trout from Great Bear Lake. This involves the combination of DFO survey data with records from recreational and community fisheries within an integrated analysis framework.

The work of former students can be found under the Publications tab at the top of the page.