Our Research Team

Areas of Expertise:

• State-space and hidden Markov models for animal movement data 

• Close Kin Mark Recapture methods for estimating population size

• Fisheries spatio-temporal stock assessment models
   

Joanna Mills Flemming is a Professor in the Department of Mathematics and Statistics at Dalhousie University. Her research interests centre on the development of statistical methodologies for data exhibiting spatial and/or temporal dependencies with a particular interest in tools for marine ecology, and more broadly, fisheries science. 

Joanna holds a B.Sc. in Mathematics, Statistics and Computer Science (1995) from the University of Guelph, an M.Sc. in Applied Mathematics (1997) from the Technical University of Nova Scotia, and a Ph.D. in Statistics (2000) from Dalhousie University. She also completed a Postdoctoral Fellowship in the Department of Econometrics at the University of Geneva (2002-2004).

Joanna is the Regional Director of CANSSI Atlantic and a member of the International Scientific Advisory Committee for the Ocean Tracking Network. She serves as an Associate Editor for The Canadian Journal of Statistics, Envirometrics, and, most recently, Movement Ecology.

Joanna builds multi-disciplinary collaborations by providing leadership in statistical science. Current collaborators include Clearwater Seafoods and Fisheries and Oceans Canada.

joanna.flemming@dal.ca

Areas of Expertise:

• Nearshore Physical oceanography 

• Ocean biogeochemical data assimilation

• State space models and time series 

• Acoustic whale detection and forecasting 

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Mike Dowd is a professor in the Dept. of Mathematics & Statistics at Dalhousie University and is cross-appointed in the Dept of Oceanography. Mike’s research specialty is environmental statistics with a particular interest in the novel space-time data types arising from new technological developments in the ocean sciences, and their fusion with dynamical models of ocean processes. He has a PhD in physical oceanography, and degrees in the environmental sciences. His research focus is on signal processing, time series analysis, and state space models. Current research projects include acoustic whale detection, quantification of ocean carbon in the northwest Atlantic, marine animal movement and forecasting, and modelling nearshore temperature dynamics for seagrass ecosystems.

michael.dowd@dal.ca

Areas of Expertise:

• Extreme value analysis with applications to the environment, e.g., flood risk analyses. 

• Multivariate and multivariate spatial modeling 

• Clustering

• Discrete and mixed-type data
   

Orla Murphy is an Assistant Professor of Statistics at Dalhousie University. Orla completed a B.Sc. in Mathematics with Honours at Saint Francis Xavier University (Antigonish, NS) and obtained an M.Sc. and Ph.D. in Statistics at McGill University (Montréal, QC). After completing her graduate studies, Orla was a postdoctoral fellow in Computational Statistics at McMaster University (Hamilton, ON).

Orla’s research program includes (i) analyzing extreme environmental events and (ii) developing novel methods for modeling high-dimensional and heterogeneous data. The first component of her research program is focused on developing and using methods in extreme value analysis to model and predict extreme weather-related events, such as flooding. The second component includes research interests such as clustering, high-dimensional data, discrete and mixed-type data, and dependence modeling. Orla is currently supervising projects in multivariate spatial modeling, variable selection, and high-dimensional data clustering with applications in fisheries and health.​

orla.murphy@dal.ca

Areas of Expertise:

• Animal movement modelling

• Hidden Markov and state-space models

• Stochastic differential equations

• Habitat selection modelling

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Theo Michelot is an assistant professor in statistics, his main research interest is the analysis of animal movement data.

Together with his collaborators, he worked on increasing the biological realism of various models used for animal tracking data, such as hidden Markov models, stochastic differential equations, and habitat selection models. His research focuses on identifying the factors that influence animals' movement decisions, including environmental conditions and human disturbances. For example, he developed models for behavioral response studies, to determine whether marine mammals are impacted by ship sonars.

He is also interested in the effect that the spatiotemporal scale of ecological data has on biological inferences. It is often difficult to compare or combine data sets collected at different scales; new statistical models are needed to bridge this gap. This will be an important step towards joint analyses of multiple data types and an improved mechanistic understanding of pattern formation in animal space use.

theo.michelot@dal.ca

Andrew Irwin is a professor of mathematics and statistics with a research focus on modeling in biological oceanography. His research aims to improve biological and ecological understanding of marine plankton including their roles in carbon biogeochemistry and food webs.  A key focus is learning how to document and anticipate consequences of climate change on plankton and the marine biosphere.  Scientists in his group take a highly interdisciplinary approach developing statistical, mathematical, and computational tools to extract information from experimental and observational data. Past projects have used regional and global-scale plankton occurrence data, biochemical data from controlled lab experiments, and molecular transcript data on individual species and communities.  This work is made possible by a network of collaborators at Dalhousie and other universities. Prospective students are encouraged to review the lab web page and contact him to discuss how their experience and goals could fit within the work done in the lab.

a.irwin@dal.ca

Ethan Lawler completed his Ph.D. in Statistics at Dalhousie University under the supervision of Joanna Mills Flemming and Chris Field. He has a strong background in mathematics and has been applying that knowledge to statistical models for marine ecology. His two main areas of research involve developing statistical models and software for analyzing animal movement and species distribution data. Statistical analyses in these areas are challenging due to the noisy and relatively uninformative data typical of the marine environment, as well as computational problems that arise when accounting for correlation across space and time.

et384729@dal.ca

Profile Coming Soon

NMcGinty@dal.ca

Chris Field is a professor Emeritus of Statistics at Dalhousie University. Chris’s research has had a focus on robust methodology since 1976. In recent years his interests have focussed on developing appropriate robustness methodology for models in fisheries science. His current research has focussed on the robust analysis of tracking data  where there is a need to protect against unusual behaviours in the animal tracks. In addition, he works on ensuring that the State Space models, which are becoming more extensively used in stack assessment models, have the built in robustness to provide reliable predictions for assessments in the presence of unusual species counts in a particular year.

chrisfield@gmail.com

Areas of Expertise:

• Fisheries Science

• Stock Assessment

• Spatiotemporal modelling

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Dr. David Keith is a Research Scientist in the Scallop and Benthic Habitat Unit with Fisheries and Oceans Canada. His primary research focus is to develop methods in which environmental considerations are incorporated into the science advice provided to fisheries management, with an emphasis on Atlantic sea scallop (Placopecten Magellanicus). This research is multidisciplinary and has led to collaborations with a diverse team of oceanographers, statisticians, resource managers, and fisheries scientists. For Dr. Keith, the principle goal of these collaborations is the development of the next generation of stock assessment models that will explicitly incorporate habitat and spatial information into the stock assessment framework.  In addition, he is using techniques developed in these collaborations to improve our understanding of future shifts in species distributions and to quantify the impact of fisheries on species of conservation concern.

David.Keith@dfo-mpo.gc.ca

Areas of Expertise:

• Species distribution modeling

• Animal movement modeling

• Tree-based machine learning methods

• State-space behavioral modeling

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Charles Bangley is a Research Associate in the Mathematics & Statistics and Biology departments at Dalhousie University, where he works with the lab of Dr. Joanna Mills Flemming. He earned his BSc in Marine Biology at the University of Rhode Island and his MSc in Biology and PhD in Coastal Resources Management at East Carolina University. Prior to his move to Nova Scotia, Charles worked as a postdoctoral fellow at the Smithsonian Environmental Research Center. His research focuses on movement and habitat selection behaviors of highly migratory marine species, with a focus on elasmobranchs. This work has involved fishery-independent surveys, acoustic and satellite-based telemetry, species distribution modeling using boosted regression trees and other machine learning methods, and hidden Markov modeling of telemetry data. His current research leverages acoustic telemetry data from dozens of collaborators to develop predictive models of migratory fish species in the upper Bay of Fundy to aid in risk assessment for tidal energy development and other marine spatial planning applications. He also continues to work on coastal shark and ray tracking data, with a goal of identifying potential distribution and habitat shifts for these highly mobile predators under the effects of climate change.

Charles.bangley@dal.ca