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I am a theoretical ecologist, working mostly on questions in population, community, and evolutionary ecology. My recent work has focused on how rapid evolution affects the dynamics of populations and communities, and on theory and applications of trait-based population and community models (e.g., size-based plant demography, spatial models for plant communities based on long-term mapped quadrats, and evolution of quantitative traits in size-structured populations). My students and postdocs have worked on a variety of related and unrelated projects, such as detection of invasive species, analysis of eco-evolutionary dynamics using fast-slow systems theory, evolution of multiple defense traits in plants, and continental-scale modeling of monarch butterfly populations. I am a Fellow of the Ecological Society of America (class of 2016) and Horace White Professor of Ecology and Evolutionary Biology.
My recent teaching includes BioEE 3620/MATH 3620: Dynamic Models in Biology, BioEE 7600:Introduction to Modeling in Ecology and Evolutionary Biology, and BioEE 3610: Advanced Ecology.
- Ecology and Evolutionary Biology
- Applied Mathematics
- Computational Biology
- Computational Science and Engineering
- Ecology and Evolutionary Biology
- Biogeochemistry and Environmental Biocomplexity (BEB)
- Center for Applied Mathematics (CAM)
My main research projects concern the role of rapid evolution in the dynamics of biological populations and communities, and the development and application of modeling methods and theory for populations structured by continuously-varying attributes (e.g., size-based plant demography, and disease transmission in multi-species communities characterized by functional traits). Students and postdocs in my research group work on a variety of related and unrelated projects, ranging from the the role of human movement patterns in urban disease epidemics, to control of invasive species in heterogeneous landscapes.
- R.E. Snyder and S.P. Ellner. 2016. We happy few: using structured population models to identify the decisive events in the lives of exceptional individuals. American Naturalist 188: E28-E45.
- Holden, M.H. and S.P. Ellner. 2016. Human judgment vs. quantitative models for the management of ecological resources. Ecological Applications 26(5): 1553–1565.
- H. Inamine, S. P. Ellner, J. P. Springer and A. A. Agrawal. Linking the continental migratory cycle of the monarch butterfly to understand its population decline. Oikos 125: 1081–1091. doi: 10.1111/oik.03196.
- S.P. Ellner, D.Z. Childs, and M. Rees. 2016. Data-driven Modeling of Structured Populations: A Practical Guide to the Integral Projection Model. Springer, New York.
- M. Yamamichi and S.P. Ellner. 2016. Antagonistic coevolution between quantitative and Mendelian traits. Proceedings of the Royal Society B 283: 20152926. http://dx.doi.org/10.1098/rspb.2015.2926
- B.J. Teller, P. B. Adler, C.B. Edwards, G. Hooker and S. P. Ellner. 2016. Linking demography with drivers: climate and competition. Methods in Ecology and Evolution 7: 171-183. DOI: 10.1111/2041-210X.12486.
- M. Rees and S. P. Ellner. 2016. Evolving integral projection models: evolutionary demography meets eco-evolutionary dynamics. Methods in Ecology and Evolution 7: 157:170 DOI: 10.1111/2041-210X.12487
- B.D. Dalziel, M. Le Corre, S. Côté, and S.P. Ellner. 2016. Detecting collective behaviour in animal relocation data, with application to migrating caribou. Methods in Ecology and Evolution 7: 30-41. http://dx.doi.org/10.1111/2041-210X.12437.
- E. Benincà, B. Ballantine, S. P. Ellner, and J. Huisman. 2015. Species fluctuations sustained by a cyclic succession at the edge of chaos. Proceedings of the National Academy of Sciences (USA) 112: 6389–6394.
- G. Hooker and S. P. Ellner. 2015. Goodness of fit in nonlinear dynamics: mis-specified rates or mis-specified states? Annals of Applied Statistics 9(2): 754-776.
- I. N. Rubin, S.P. Ellner, A. Kessler, and K. A. Morrell. 2015. Informed herbivore movement and interplant communication determine the effects of induced resistance in an individual-based model. Journal of Animal Ecology 84, 1273–1285.
- C. J. E. Metcalf, S. P. Ellner, D. Z. Childs, R. Salguero-Gómez, C. Merow, S. M. McMahon, E. Jongejans and M. Rees. 2015. Statistical modeling of annual variation for inference on stochastic population dynamics using Integral Projection Models. Methods in Ecology and Evolution 6: 1007-1017.
- P.J. Hurtado, S.R. Hall and S.P. Ellner. 2014. Infectious disease in consumer populations: dynamic consequences of resource-mediated transmission and infectiousness. Theoretical Ecology 7:163–179, doi: 10.1007/s12080-013-0208-2
- M. Rees, D. Z. Childs and S. P. Ellner. 2014. Building integral projection models: a user's guide. Journal of Animal Ecology 83: 528–545. doi: 10.1111/1365-2656.12178
- T. Hiltunen, N. G.Hairston Jr, G. Hooker, L.E. Jones and S. P. Ellner. 2014. A newly discovered role of evolution in previously published consumer-resource dynamics. Ecology Letters. 17: 915–923. doi: 10.1111/ele.12291
- B. D. Dalziel, K. Huang, J. L. Geoghegan, N. Arinaminpathy, E. J. Dubovi, B. T. Grenfell, S. P. Ellner, E. C. Holmes, C.R. Parrish. 2014. Contact heterogeneity, rather than transmission efficiency, limits the emergence and spread of canine influenza virus. PLoS Pathogens 10(10): e1004455. doi:10.1371/journal.ppat.1004455.
- T. Hiltunen, S.P. Ellner, G. Hooker, L.E. Jones, and N.G. Hairston, Jr.. 2014. Eco-Evolutionary Dynamics in a Three-Species Food Web with Intraguild Predation: Intriguingly Complex. Advances in Ecological Research 50: 41-73.
- T. Hiltunen, , L.E. Jones, S.P. Ellner, and N.G. Hairston, Jr. 2013. Temporal dynamics of a simple community with intraguild predation: an experimental test. Ecology 94, 773-779.
- C. Low, S. P. Ellner, and M. H. Holden. 2013. Optimal control and cold war dynamics between plant and herbivore. American Naturalist 182: E25-E39.
- S.P. Ellner. 2013. Rapid evolution: from genes to communities, and back again? Functional Ecology 27: 1087-1099.
- B. D. Dalziel, B. Pourbohloul and S. P. Ellner. 2013. Human mobility patterns predict divergent epidemic patterns among cities. Proceedings of the Royal Society B 280: 20130763 doi: 10.1098/rspb.2013.0763.