Dr. Ilona Naujokaitis-Lewis

Research Scientist - Landscape ecologist: climate change impacts and adaptation strategies for terrestrial biodiversity conservation
Environment and Climate Change Canada

Current research and/or projects

  • Understanding demographic drivers of species responses to climate change and land-use land-cover change
  • Climate change vulnerability assessments across (terrestrial) taxonomic groups
  • Spatial prioritisation of resources for conservation of species-at-risk/Conservation planning
  • Climate change adaptation strategies: translating predictive/population/species distribution model outcomes to inform decision-making

Professional activities / interests

Society for Conservation Biology - Chapters Committee, Toronto Chapter Executive Committee Member

Education and awards

PhD, University of Toronto, Dept. Ecology and Evolutionary Biology (Toronto, CAN)

MREM, Simon Fraser University, School of Resource and Environmental Management (Vancouver, CAN)

BSc Honours, Trent University (Peterborough, CAN)

Key publications

Camaclang, AE, JM Curtis, I Naujokaitis-Lewis, MS Poesch, MA Koops. 2016. Modelling the impact of poaching on metapopulation viability for data-limited species. Canadian Journal of Fisheries and Aquatic Sciences DOI: doi.org/10.1139/cjfas-2015-0508

NAUJOKAITIS-LEWIS, I. and JM Curtis. 2016. Advances in global sensitivity analyses of demographic-based species distribution models to address uncertainties in dynamic landscapes. PeerJ 4 e2204. DOI: doi.org/10.7717/peerj.2204

Tulloch, AIT, P Sutcliffe, I NAUJOKAITIS-LEWIS, R Tingley, L Brotons, KM PMB Ferraz, H Possingham, A Guisan, JR Rhodes. 2016. Conservation planners tend to ignore improved accuracy of modelled species distributions to focus on multiple threats and ecological processes. Biological Conservation 199:157-171. DOI: dx.doi.org/10.1016/j.biocon.2016.04.023

NAUJOKAITIS-LEWIS, I and M-J Fortin. 2015. Spatio-temporal variation of biotic factors underpins contemporary range dynamics of congeners. Global Change Biology DOI: 10.1111/gcb.13145

Anstett, DN, I NAUJOKAITIS-LEWIS, MTJ Johnson 2014. Latitudinal gradients in herbivory on Oenothera biennis vary according to herbivore guild and specialization. Ecology 95:2915–2923. DOI: 10.1890/13-0932.1

Guisan, A, R Tingley, JB Baumgartner, I NAUJOKAITIS-LEWIS, PR Sutcliffe, AIT Tulloch, TJ Regan, L Brotons, E McDonald-Madden, C Mantyka-Pringle, TG Martin, JR Rhodes, R Maggini, SA Setterfield, J Elith, MW Schwartz, BA Wintle, O Broennimann, M Austin, S Ferrier, MR Kearney, HP Possingham, YM Buckley. Predicting species distributions for conservation decisions. Ecology Letters 16 (12): 1424–1435. DOI: 10.1111/ele.12189 [PDF]

Pe’er, G, Matsinos, YG, Johst, K, Franz, KW, Turlure, C, Radchuk, V, Malinowska, AH, Curtis, JMR, NAUJOKAITIS-LEWIS,  I, Wintle, BA and K Henle. Population viability analyses: a protocol for better design, application and communication. Conservation Biology 27(4): 644-656. DOI: 10.1111/cobi.12076

NAUJOKAITIS-LEWIS,  I, JMR Curtis, L Tischendorf, D Badzinski, K Lindsay, M-J Fortin. Uncertainties in coupled species distribution–metapopulation dynamics models for risk assessments under climate change. Diversity and Distributions 19: 541–554. Special issue: Risks, Decisions, and Biological Conservation. DOI: 10.1111/ddi.12063

Above paper highlighted in:
Franklin, J 2013. Species distribution models in conservation biogeography:
developments and challenges. 19 (10): 1217–1223. DOI: 10.1111/ddi.12125

NAUJOKAITIS-LEWIS,  I, Y Rico, J Lovell, M-J Fortin, MA Murphy. 2012. Implications of incomplete networks on estimation of landscape genetic connectivity. Conservation Genetics 1-12. DOI: 10.1007/s10592-012-0385-3

NAUJOKAITIS-LEWIS,  I, JMR Curtis, J Rosenfeld, and P Arcese. 2009. Sensitivity analyses of spatial population viability analysis models for species at risk and habitat conservation planning. Conservation Biology 23: 225-229. DOI: 10.1111/j.1523-1739.2008.01066.x

Curtis, JMR and I NAUJOKAITIS-LEWIS. 2008. Sensitivity analysis of population viability to spatial and non-spatial parameters using GRIP. Ecological Applications 18(4): 1002–1013. http://www.jstor.org/stable/40062205