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Publications

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2024  |  2023  |  2022  |  2021  |  2020  |  2019 

Browse the SEaDAL teams most recent publications below.

2024

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2024

Estimating effective population size using close-kin mark-recapture

Jonathan Babyn, Daniel Ruzzante, Mark Bravington, Joanna Mills Flemming (2024).Estimating effective population size using close-kin mark–recapture. British Ecological Society, Methods in Ecology and Evolution.

Step selection functions with non‐linear and random effects

Klappstein, N. J., Michelot, T., Fieberg, J., Pedersen, E. J., & Mills Flemming, J. (2024). Step selection functions with non‐linear and random effects. Methods in Ecology and Evolution, 15(8), 1332-1346.

Comparing spatiotemporal species distribution models: A case study of a Scotian Shelf sea cucumber (Cucumaria frondosa)

Nathan E. Hebert, Jessica A. Sameoto, David M. Keith, Melanie A. Barrett, Craig J. Brown, Joanna Mills Flemming (2024). "Comparing spatiotemporal species distribution models: A case study of a Scotian Shelf sea cucumber (Cucumaria frondosa)". Ecosphere: An ESA Open Source Journal, Volume15, Issue4.

Can statistics help to uncover the ocean’s secrets?

Joanna Mills Flemming (2024). "Can statistics help to uncover the ocean’s secrets?" Futurum Careers.
This article was produced by Futurum Careers, a free online resource and magazine aimed at encouraging 14-19-year-olds worldwide to pursue careers in science, technology, engineering, maths and medicine (STEM), and social sciences, humanities and the arts for people and the economy (SHAPE): www.futurumcareers.com

Understanding step selection analysis through numerical integration

Michelot, T., Klappstein, N. J., Potts, J. R., & Fieberg, J. (2024). "Understanding step selection analysis through numerical integration". Methods in Ecology and Evolution, 15, 24–35.

Step selection analysis with non-linear and random effects in mgcv

Klappstein, N., Michelot, T., Fieberg, J., Pedersen, E., Field, C., & Flemming, J. M. (2024). "Step selection analysis with non-linear and random effects in mgcv". bioRxiv, 2024-01.

2023

2023

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Flexible hidden Markov models for behaviour-dependent habitat selection

Klappstein, N. J., Thomas, L., & Michelot, T. (2023). "Flexible hidden Markov models for behaviour-dependent habitat selection". Movement Ecology, 11(1), 30.

Continuous-time modelling of behavioural responses in animal movement

Michelot, T., Glennie, R., Thomas, L., Quick, N., Harris, C.M. (2023), "Continuous-time modelling of behavioural responses in animal movement", Annals of Applied Statistics, 17 (4), pp. 3570-3588

Integrating habitat features into spatio-temporal biomass dynamics models for a better understanding of stock productivity: a case study of sea scallop in the Bay of Fundy

McDonald, Raphaël R., Keith, David M., Sameoto, Jessica A., and Mills Flemming, "Integrating habitat features into spatio-temporal biomass dynamics models for a better understanding of stock productivity: a case study of sea scallop in the Bay of Fundy", ICES Journal of Marine Science. 80 (6): 1710-1726

starve: An R package for spatio-temporal analysis of research survey data using nearest-neighbour Gaussian processes

Ethan Lawler, Chris Field, Joanna Mills Flemming, “starve: An R package for spatio-temporal analysis of research survey data using nearest-neighbour Gaussian processes.” Methods in Ecology and Evolution, Volume 14, No.3 (2023):817-830

hmmTMB: Hidden Markov models with flexible covariate effects in R

Michelot, T. (2023). "hmmTMB: Hidden Markov models with flexible covariate effects in R". arXiv preprint arXiv:2211.14139.

Density regulation amplifies environmentally induced population fluctuations

CM Mutshinda, A Mishra, ZV Finkel, AJ Irwin. "Density regulation amplifies environmentally induced population fluctuations", Peer J 11: e14701. 10.7717/peerj.14701

Formulating a spatio-temporal model to analyze longline survey data for the Atlantic Halibut fishery

McDonald, Raphaël R.; Hubley, Brad; Li, Lingbo; den Heyer, Cornelia E., "Formulating a spatio-temporal model to analyze longline survey data for the Atlantic Halibut fishery", Fisheries and Oceans Canada / Pêches et Océans Canada, Canada

Using ecological partitions to assess zooplankton biogeography and seasonality

N McGinty, AJ Irwin, ZV Finkel, S Dutkiewicz. "Using ecological partitions to assess zooplankton biogeography and seasonality", Frontiers 10: 989770. 10.3389/fmars.2023.989770

2022

2022

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Incorporating intra-annual variability in fisheries abundance data to better capture population dynamics

McDonald, Raphaël R.; Keith, David; Sameoto, Jessica A.; Hutchings, Jeffrey A.; Flemming, Joanna Mills. 2022. Incorporating intra-annual variability in fisheries abundance data to better capture population dynamics. Fisheries Research. 246: 106152. Doi: 10.1016/j.fishres.2021.106152 

Extending the Monod Model of Microbial Growth with Memory

MM Amirian, AJ Irwin, ZV Finkel. "Extending the Monod Model of Microbial Growth with Memory",  arXiv 10.48550/arXiv.2207.02028, Frontiers Mar. Sci.. 10.3389/fmars.2022.963734

When Measures Conflict: Towards a Better Understanding of Intergenerational Educational Mobility

Ahsan, Md Nazmul, M. Shahe Emran, Hanchen Jiang, Orla Murphy, and Forhad Shilpi. "When Measures Conflict: Towards a Better Understanding of Intergenerational Educational Mobility." Available at SSRN 4231514 (2022).

A spatial analysis of longline survey data for improved indices of Atlantic halibut abundance

 Jiaxin Luo, Raphaël R McDonald, Brendan F Wringe, Cornelia E den Heyer, Bruce Smith, Yuan Yan, Joanna Mills Flemming, "A spatial analysis of longline survey data for improved indices of Atlantic halibut abundance", 

ICES Journal of Marine Science, Volume 79, Issue 6, August 2022, Pages 1954–1964

Graphical analysis of a marine plankton community reveals spatial, temporal, and niche structure of sub-communities

JT Siddons, AJ Irwin, ZV Finkel. "Graphical analysis of a marine plankton community reveals spatial, temporal, and niche structure of sub-communities", Frontiers in Marine Science 9: 943540. 10.3389/fmars.2022.943540

A real-time data assimilative forecasting system for animal tracking

Randon M, Dowd M, Joy R. 2022. "A real-time data assimilative forecasting system for animal tracking", Ecology e3718

A fine-scale marine mammal movement model for assessing long-term aggregate noise exposure

Joy R, Schick RS, Dowd M, Margolinae T, Joseph JE, Thomas L. 2022. "A fine-scale marine mammal movement model for assessing long-term aggregate noise exposure", Ecological Modelling 464: 109798.

Predicting aquatic animal movements and behavioural states from acoustic telemetry arrays

Kim Whoriskey, Henrik Baktoft, Chris Field, Robert J. Lennox, Jonathan Babyn, Ethan Lawler, Joanna Mills Flemming  “Predicting aquatic animal movements and behavioural states from acoustic telemetry arrays” Methods in Ecology and Evolution, (2022): 987-1000

2021

2021

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Explicit incorporation of spatial variability in a biomass dynamics assessment model

  • McDonald, Raphaël R.; Keith, David; Sameoto, Jessica A.; Hutchings, Jeffrey A.; Flemming, Joanna Mills. 2021. Explicit incorporation of spatial variability in a biomass dynamics assessment model. ICES Journal of Marine Science. 78 (9): 3265-3280. Doi: 10.1093/icesjms/fsab192 

Functional trait complementarity and dominance both determine benthic secondary production in temperate seagrass beds

Wong, M.C., Dowd, M. 2021. "Functional trait complementarity and dominance both determine benthic secondary production in temperate seagrass beds", Ecosphere 12(11): e03794

Distributions of threatened skates and commercial fisheries inform conservation hotspots

Jubinville, Isabelle and Lawler, Ethan and Tattrie, Sophie and Shackell, Nancy L and Flemming, Joanna Mills and Worm, Boris, “Distributions of threatened skates and commercial fisheries inform conservation hotspots.” Volume 679 (2021): 1-18

Varying-coefficient stochastic differential equations with applications in ecology

Michelot, T., Glennie, R., Harris, C., & Thomas, L. "Varying-coefficient stochastic differential equations with applications in ecology." Journal of Agricultural, Biological and Environmental Statistics, Volume 26, (2021): 446-463.

Multiple Metrics of Temperature, Light, and Water Motion Drive Gradients in Eelgrass Productivity and Resilience

Krumhansl, K.A., Dowd, M. and Wong, M.C. "Multiple Metrics of Temperature, Light, and Water Motion Drive Gradients in Eelgrass Productivity and Resilience." Frontiers in Marine Science , Volume 8 (2021): 48.

2020

2020

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Publication Coming Soon

Authors, "Title." Journal, (year): pages

2019

2019

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State‐switching continuous‐time correlated random walks

Michelot, T., & Blackwell, P. G. "State‐switching continuous‐time correlated random walks." Methods in Ecology and Evolution, Volume 10 No.5, (2019): 637-649.

The Langevin diffusion as a continuous‐time model of animal movement and habitat selection

Michelot, T., Gloaguen, P., Blackwell, P. G., & Étienne, M. P. "The Langevin diffusion as a continuous‐time model of animal movement and habitat selection." Methods in Ecology and Evolution, Volume 10, No.11, (2019): 1894-1907.

Modelling extreme rain accumulation with an application to the 2011 Lake Champlain flood

Jalbert, Jonathan, Orla A. Murphy, Christian Genest, and Johanna G. Nešlehová. "Modelling extreme rain accumulation with an application to the 2011 Lake Champlain flood." Journal of the Royal Statistical Society Series C (Applied Statistics) Volume 68, No.4 (2019): 831-858.

Testing for independence in arbitrary distributions

Genest, C., J. G. Nešlehová, B. Rémillard, and O. A. Murphy. "Testing for independence in arbitrary distributions." Biometrika Volume 106, No.1 (2019): 47-68.

The Conditionally Autoregressive Hidden Markov Model (CarHMM): Inferring Behavioural States from Animal Tracking Data Exhibiting Conditional Autocorrelation

Lawler, Ethan and Whoriskey, Kim and Aeberhard, William H and Field, Chris and Mills Flemming, Joanna, “The Conditionally Autoregressive Hidden Markov Model (CarHMM): Inferring Behavioural States from Animal Tracking Data Exhibiting Conditional Autocorrelation.” Journal of Agricultural, Biological and Environmental Statistics, Volume 24 (2019):  651–668

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©2023 by SEaDAL| Statistical Ecology Lab

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