1. Hebert, N., Sameoto, J., Keith, D., Barrett, M., Brown, C., and Mills Flemming, J. (2024) Comparing spatio-temporal species distribution models: a case study of Scotian Shelf sea cucumber (Cucumaria frondosa). Ecosphere.
2. Murdoch, A., Connors, B., Lapointe, N., Mills Flemming, J., Cooke, S., and Mantyka-Pringle C. (2024). Multiple environmental drivers across life stages influence Yukon River Chinook salmon productivity . The Canadian Journal of Fisheries and Aquatic Sciences.
1. Lawler, E., Field, C., & Mills Flemming, J. (2023). starve: An R package for spatio-temporal analysis of research survey data using nearest-neighbour Gaussian processes. Methods in Ecology and Evolution.
2. McDonald, R., Keith, D., Sameoto, J. & Mills Flemming, J. 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.
3. Yan, Y., Cantoni, E., Field, C., Treble, M., Benoit, H., Rideout, R. and Mills Flemming, J. (2023). Spatiotemporal modelling of Greenland halibut maturation across the Northwest Atlantic. ICES Journal of Marine Science.
4. Weise, E., Van Wyngaarden, M., Den Heyer, C., Mills Flemming, J., Kess, T., Einfeldt, A., Fisher, J., Ditta, R., Pare, G. Ruzzante, D. (2023). SNP panel and genomic sex identification in Atlantic Halibut (Hippoglossus hippoglossus), Marine Biotechnology.
Photo Credit: Pixabay on Pexels
1. Yan, Y., Cantoni, E., Field, C., Treble, M., & Flemming, J. M. (2022). Spatiotemporal modeling of bycatch data: methods and a practical guide through a case study in a Canadian Arctic fishery. Canadian Journal of Fisheries and Aquatic Sciences, 79(1), 148-158.
2. Young-Shand, K. L., Dunbar, M. J., Laende, E. K., Flemming, J. M., & Wilson, J. L. A. (2021). Early Identification of Patient Satisfaction Two Years After Total Knee Arthroplasty. The Journal of Arthroplasty.
3. Kiehbadroudinezhad, S., Bruce Martin, S., & Mills Flemming, J. (2021). Estimating minke whale relative abundance in the North Atlantic using passive acoustic sensors. The Journal of the Acoustical Society of America, 150(5), 3569-3580.
4. Babyn, J., Varkey, D., Regular, P., Ings, D., & Flemming, J. M. (2021). A Gaussian field approach to generating spatial age length keys. Fisheries Research, 240, 105956.
5. Jubinville, I., Lawler, E., Tattrie, S., Shackell, N. L., Flemming, J. M., & Worm, B. (2021). Distributions of threatened skates and commercial fisheries inform conservation hotspots. Marine Ecology Progress Series, 679, 1-18.
6. Kiehbadroudinezhad, S., Bruce Martin, S., & Mills Flemming, J. (2021). Estimating minke whale relative abundance in the North Atlantic using passive acoustic sensors. The Journal of the Acoustical Society of America, 150(5), 3569-3580.
7. Whoriskey, K., Baktoft, H., Field, C., Lennox, R. J., Babyn, J., Lawler, E., & Mills Flemming, J. (2022). Predicting aquatic animal movements and behavioural states from acoustic telemetry arrays. Methods in Ecology and Evolution, 13(5), 987-1000.
8. McDonald, R. R., Keith, D. M., Sameoto, J. A., Hutchings, J. A., & Flemming, J. M. (2021). Explicit incorporation of spatial variability in a biomass dynamics assessment model. ICES Journal of Marine Science, 78(9), 3265-3280.
Photo credit: Darwis Alwan on Pexels
1. Aeberhard, W. H., Cantoni, E., Field, C., Kuensch, H. R., Flemming, J. M., & Xu, X. (2020). Robust Estimation for Discrete-Time State Space Models. arXiv preprint arXiv:2004.05023.
2. Auger-Méthé, M., Newman, K., Cole, D., Empacher, F., Gryba, R., King, A. A., ... & Thomas, L. (2020). A guide to state-space modeling of ecological time series. arXiv preprint arXiv:2002.02001.
3. Nowak, B. V. R., Bowen, W. D., Whoriskey, K., Lidgard, D. C., Flemming, J. M., & Iverson, S. J. (2020). Foraging behaviour of a continental shelf marine predator, the grey seal (Halichoerus grypus), is associated with in situ, subsurface oceanographic conditions. Movement ecology, 8(1), 1-14.
Photo credited to Tricia Pearo Drew
1. Ruzzante, D. E., McCracken, G. R., Førland, B., MacMillan, J., Notte, D., Buhariwalla, C., ... & Skaug, H. (2019). Validation of close‐kin mark‐recapture (CKMR) methods for estimating population abundance. Methods in Ecology and Evolution.
2. Yin, Y., Aeberhard, W., Smith, S., and Mills Flemming, J. (2019). Identifiable state-space assessment models, a case study of the Bay of Fundy Sea Scallop fishery. Canadian Journal of Statistics.
3. Whoriskey, K., Martins, E., Auger- Méthé, M., Gustowsky, L., Lennox, R., Cooke, S.J., Power, M., and Mills Flemming, J. (2019). Current and emerging statistical techniques for aquatic telemetry data: A guide to analyzing spatially discrete animal detections. Methods in Ecology and Evolution.
4. Brownscombe, J. W., . . .Mills Flemming, J., Kessel, S.T., Krueger, C.C, and Cooke, S. J. (2019). Conducting and interpreting fish telemetry studies: Considerations for researchers and resource managers. Reviews in Fish Biology and Fisheries.
5. Lawler, E., Whoriskey, K., Aeberhard, W. H., Field, C., and Mills Flemming, J.(2019). The conditionally autoregressive hidden Markov model (CarHMM): Inferring behavioural states from animal tracking data exhibiting conditional autocorrelation. Journal of Agricutural, Biological and Environmental Statistics.
6. Iverson, S. J., Fisk, A. T., Hinch, S. G., Flemming, J. M., Cooke, S. J., & Whoriskey, F. G. (2019). The Ocean Tracking Network: Advancing frontiers in aquatic science and management. Canadian Journal of Fisheries and Aquatic Sciences, 76(7), 1041–1051. doi: 10.1139/cjfas-2018-0481
Image Retrieved from Review of state-space models for fisheries science. Annual Review of Statistics and its Application
1. *Imlay T., Mills Flemming, J., Saldanha, S., Wheelwright, N., Leonard, M. (2018). Breeding phenology and performance for four swallows over 57 years: relationships with temperature and precipitation. Ecosphere.
2. Aeberhard, W.H., Mills Flemming, J., and Nielson, A. (2018). Review of state-space models for fisheries science. Annual Review of Statistics and its Application, 5, 2018.
Image Retrieved from Envisioning the future of aquatic animal tracking: Technology, science, and application. BioScience.
1. Steenweg, R., Crossin, G., Kyser, T.K., Merkel, F., Gilchrist, H., Hennin, H., Roberston, G., Provencher, J., Mills Flemming, J., and Love, O. (2017). Stable isotopes can be used to infer the overwintering locations of pre-breeding marine birds in the Canadian Arctic. Ecology and Evolution.
2. Ogburn, M.B., Harrison, A-L., Whoriskey, F.G., Cooke, S.J., Mills Flemming, J.E., and Torres, L.G. (2017). Addressing challenges in the application of animal movement ecology to aquatic conservation and management. Frontiers in Marine Science.
3. Lennox R.J., Aarestrup, K., Cooke, S.J., Cowley, P., Fisk, A.T., Harcourt, R., Heupel, M., Hinch, S.G., Holland, K., Hussey, N., Iverson, S., Kessel, S., Kocik, J., Mills Flemming, J., Nguyen, V.M., Stokesbury, M., Vagle, S., VanderZwaag, D., Webber, D., Whoriskey, F.G., and Young, N. (2017). Envisioning the future of aquatic animal tracking: technology, science, and application. BioScience.
4. Lotze H, Mills Flemming J, Magera A. (2017) Critical factors for the recovery of marine mammals. Conservation Biology.
5. Carson S, Shackell N, and Mills Flemming J. (2017). Local overfishing may be avoided by examining parameters of a Spatio-temporal model. PloS ONE.
6. Cantoni, E., Mills Flemming, J., and Welsh, A. (2017). A random-effects hurdle model for predicting bycatch of endangered marine species. Annals of Applied Statistics, 11(4), 2178-2199. http://dx.doi.org/10.1214/17-AOAS1074.
7. Auger-Méthé M, Albertsen C, Jonsen I, Derocher A, Lidgard D, Studholme K, Bowen W, Crossin G, Mills Flemming J. (2017). Spatiotemporal modelling of marine movement data using Template Model Builder. Marine Ecology Progress Series, 565:237-249.
Image Retrieved from State-space models' dirty little secrets: even simple linear Gaussian models can have parameter and state estimation problems. Scientific Reports.
1. Barreto, R., Ferretti, F., Mills Flemming, J., Alberto, A., Humber, A., Worm, B., Rosangela, L. (2016). Trends in the exploitation of South Atlantic shark populations. Conservation Biology
2. Whoriskey, K., Auger- Méthé, M., Albertsen, C.M., Whoriskey, F., Binder, T., Kruegar, C., and Mills Flemming, J. (2016) A hidden Markov Movement Model for rapidly identifying behavioral states from animal tracks. Ecology and Evolution
3. Auger- Méthé, M., Field, C., Albertsen, C., Derocher, A., Lewis, M., Jonsen, I., and Mills Flemming, J. (2016). State-space models' dirty little secrets: even simple linear Gaussian models can have parameter and state estimation problems. Scientific Reports
Image Retrieved from Aquatic animal telemetry: a panoramic window into the underwater world. Science.
1. Xu X, Cantoni E, Mills Flemming J, Field C. (2015). Robust state space models for estimating fish stock maturities. Canadian Journal of Statistics.
2. Cosandey-Godin A, Krainski E, Worm B, Mills Flemming J. (2015). Applying Bayesian spatio-temporal models to fisheries by catch in the Canadian Arctic. Canadian Journal of Fisheries and Aquatic Sciences.
3. Hussey N, Kessel S, Aarestrup K, Cooke S, Cowley P, Fisk A, Harcourt R, Holland K, Iverson S, Kocik J, Mills Flemming J, Whoriskey F. (2015). Aquatic animal telemetry: a panoramic window into the underwater world. Science.
4. White E, Myers M, Mills Flemming J, Baum J. (2015). Shifting elasmobranch community assemblage at Cocos Island, an isolated marine protected area. Conversation Biology.
5. Baker L, Mills Flemming J, Jonsen I, Lidgard D, Iverson S, Bowen W. (2015). A Novel Approach to Quantifying the Spatiotemporal Behavior of Instrumented Grey Seals Used to Sample the Environment. Movement Ecology.
6. Albertsen, C., Whoriskey, K., Yurkowski, D., Neilsen, A., Mills Flemming, J. (2015). Fast fitting of non- Gaussian state-space models to animal movement data via Template Model Builder. Ecology
Image Retrieved from Productivity dynamics of Atlantic cod. Canadian Journal of Fisheries and Aquatic Sciences.
1. Baker L, Jonsen ID, Mills Flemming J, Lidgard D, Bowen WD, Iverson SJ, Webber DM. (2014). Probability of detecting marine predator-prey and species interactions using novel hybrid acoustic transmitter-receiver tags. PLoS ONE.
2. Minto C, Mills Flemming J, Britten G, Worm B. (2014). Productivity dynamics of Atlantic cod. Canadian Journal of Fisheries and Aquatic Sciences.
3. Carson S and Mills Flemming J. (2014). Seal encounters at sea: A contemporary spatial approach using R- INLA. Ecological Modelling.
4. Martins EG, Gutowsky LG, Harrison PM, Mills Flemming J, Jonsen ID, Zhu DZ, Leake A, Patterson DA, Power M, Cooke SJ. (2014). Behavioral attributes of turbine entrainment risk for adult resident fish revealed by acoustic telemetry and state-space modeling. Animal Biotelemetry.
5. Farmer RG, Leonard ML, Mills Flemming JE, Anderson SC. (2014). Observer aging and long-term avian survey data quality. Ecology and Evolution. 4(12): 2563-2576.
Image Retrieved from Recovery Trends in Marine Mammal Populations. PLoS ONE.
Magera AM, Mills Flemming J, Kaschner K, Christensen LB, Lotze H. (2013). Recovery trends in marine mammal populations. PLoS ONE.
Image Retrieved from State-Space Methods for More Completely Capturing Behavioral Dynamics from Animal Tracks. Ecological Modelling.
1. Calvert, A. M., Mackenzie, S. A., Mills Flemming, J., Taylor, P. D. and Walde, S. J. (2012). Variation in songbird migratory behaviour offers clues about adaptability to environmental change. Oecologia.
2. Breed G., Costa D, Jonsen I, Robinson P, Mills Flemming J. (2012). State-space methods for more completely capturing behavioral dynamics from animal tracks. Ecological Modelling.
Image Retrieved from Mapping species richness and human impact drivers to inform global pelagic conservation prioritization. Biological Conservation.
1.Cantoni, E., Mills Flemming, J. and Ronchetti, E. (2011). Variable selection in additive models by nonnegative garrote. Statistical Modelling.
2. Anderson S.C., Mills Flemming J., Watson R. and Lotze H.K. (2011). Rapid global expansion of invertebrate fisheries: trends, drivers, and ecosystem effects. PLoS ONE.
3. Trebilco, R., Halpern, B. S., Mills Flemming, J., Field, C. Blanchard, W. and Worm, B. (2011). Mapping species richness and human impact drivers to inform global pelagic conservation prioritization. Biological Conservation.
4. Anderson, S.C., Mills Flemming, J., Watson, R. and Lotze, H.K. (2011). Serial exploitation of global sea cucumber fisheries. Fish and Fisheries 12(3):317-339. Featured in Science on January 14 2011.
Image Retrieved from Hierarchical state-space estimation of leatherback turtle navigation ability. PLoS ONE.
1. Mills Flemming, J., Jonsen, I., Field, C. and Myers, R. (2010). Hierarchical state-space estimation of leatherback turtle navigation ability. PLoS ONE.
2. Ward-Paige, C., Mills Flemming, J. and Lotze, H.K. (2010). Overestimating fish counts by non-instantaneous visual censuses: Consequences for population and community descriptions. PLoS ONE.
3. Mills Flemming, J., Cantoni, E. Field, C. and McLaren, I. (2010). Extracting long-term patterns of population changes from sporadic counts of migrant birds. Environmetrics.
Image Retrieved from Extraction of interannual trends in seasonal events for ecological time series. Limnology and Oceanography: Methods.
1. Calvert, A. M. , Bonner, S. J., Jonsen, I. D., Mills Flemming, J., Walde, S. J. and Taylor, P. D. (2009). A hierarchical Bayesian approach to multi-state mark-recapture: simulations and applications. Journal of Applied Ecology.
2. Almeida, E., Dowd, M., Mills Flemming, J. and Li, W. (2009). Extraction of interannual trends in seasonal events for ecological time series. Limnology and Oceanography: Methods.
3. Hellou, J., Leonard, J., Cook, A., Doe, K., Dunphy, K., Jackman, P., Tremblay, L. and Mills Flemming, J. (2009). Comparison of the partitioning of pesticides relative to the survival and behaviour of exposed amphipods. Ecotoxicology.
Image Retrieved from Determining the bioavailability of contaminants and assessing the quality of sediments, Journal of Soils and Sediments.
Marklevitz, S., Almeida, E., Mills Flemming, J. and Hellou, J. (2008). Determining the bioavailability of contaminants and assessing the quality of sediments. (Part 1: Variables affecting the behavioural response of Ilyanassa obsolete, towards contaminated sediments; Part 2: Behavioural response of snails, Ilyanassa obsoleta, towards contaminated harbour sediments). Journal of Soils and Sediments.
Image Retrieved from The effectiveness of transtelephonic monitoring of pacemaker function in pediatric patients. Pacing and Clinical Electrophysiology.
1. Cantoni, E., Field, C., Mills Flemming, J. and Ronchetti, E. (2007). Longitudinal variable selection by cross-validation in the case of many covariates. Statistics in Medicine.
2. Fox, S., MacKenzie, L., Mills Flemming, J. and Warren, A. (2007). The effectiveness of transtelephonic monitoring of pacemaker function in pediatric patients. Pacing and Clinical Electrophysiology.
Image Retrieved from Modelling peak accelerations from earthquakes. Earthquake Engineering and Structural Dynamics.
1. Dupuis, D., and Mills Flemming, J. (2006). Modelling peak accelerations from earthquakes. Earthquake Engineering and Structural Dynamics.
2. Mills Flemming, J., Field, C., Myers, R. and Jonsen, I. (2006). How well can animals navigate? Estimating the circle of confusion from tracking data. Environmetrics.
Image Retrieved from Robust state-space modelling of animal movement data. Ecology.
1. Jonsen, I., Mills Flemming, J. and Myers, R. (2005). Robust state-space modelling of animal movement data. Ecology.
2. Cantoni, E., Mills Flemming, J. and Ronchetti, E. (2005). Variable selection for marginal longitudinal generalized linear models. Biometrics.
Image Retrieved from Meta-analysis of animal movement using state-space models. Ecology.
1. Jonsen, I., Myers, R., and Mills Flemming, J. (2003). Meta-analysis of animal movement using state-space models. Ecology.
2. Mulcaster, J., Mills Flemming, J., Hung, O., MacQuarrie, K., Law, A., Pytka, S., Imrie, D., and Field, C. (2003). Laryngoscopic intubation: Learning and performance. Anesthesiology.
Mills Flemming, J., Field, C.J. and Dupuis, D.J. (2002). Marginally specified generalized linear mixed models: A robust approach. Biometrics.
1. Hung, O., and Mills Flemming, J. (2000). Predictions and clinical decisions: A fine balance. Canadian Journal of Anesthesia.
2. Mills Flemming, J. (2000). The Analysis of Longitudinal Binary Data, Ph.D. Thesis, Dalhousie University.
Dupuis, D.J., and Mills Flemming, J. (1998). Robust Estimation of the Birnbaum-Saunders Distribution. IEEE Transactions on Reliability.
Mills Flemming, J. (1997). Robust Estimation of the Birnbaum-Saunders Distribution, M.Sc. Thesis, Technical University of Nova Scotia.
Photo Credit: Wexor Tmg
1. Dean, C. B., El‐Shaarawi, A. H., Esterby, S. R., Mills Flemming, J., Routledge, R. D., Taylor, S. W., ... & Zwiers, F. W. (2022). Canadian contributions to environmetrics. Canadian Journal of Statistics, 50(4), 1355-1386.
2. Luo, J., McDonald, R. R., Wringe, B. F., den Heyer, C. E., Smith, B., Yan, Y., & Mills Flemming, J. (2022). A spatial analysis of longline survey data for improved indices of Atlantic halibut abundance. ICES Journal of Marine Science, 79(6), 1954-1964.
3. Bangley, C. W., Hasselman, D. J., Flemming, J. M., Whoriskey, F. G., Culina, J., Enders, L., & Bradford, R. G. (2022). Modelling the Probability of Overlap Between Marine Fish Distributions and Marine Renewable Energy Infrastructure Using Acoustic Telemetry Data. Frontiers in Marine Science, 962.
4. Yin, Y., Sameoto, J. A., Keith, D. M., & Flemming, J. M. (2022). Improving estimation of length–weight relationships using spatiotemporal models. Canadian Journal of Fisheries and Aquatic Sciences, 79(11), 1896-1910.
5. McDonald, R. R., Keith, D. M., Sameoto, J. A., Hutchings, J. A., & Flemming, J. M. (2022). Incorporating intra-annual variability in fisheries abundance data to better capture population dynamics.. Fisheries Research, 246, 106152.
6. Laende, E. K., Flemming, J. M., Wilson, J. L. A., Cantoni, E., & Dunbar, M. J. (2022). The associations of implant and patient factors with migration of the tibial component differ by sex: a radiostereometric study on more than 400 total knee arthroplasties. The Bone & Joint Journal, 104(4), 444-451.