Dr. Leah Johnson

Statistics
Dr Johnson is a quantitative ecologist working at the intersection of statistics, mathematics, and biology. At a broad level, her research focuses on understanding how differences between individuals in a population result from external heterogeneity and stochasticity, and how this variability influences population level patterns. She address these questions primarily in the context of infectious disease epidemiology, as well as in behavioral and population ecology. Her approach is to use theoretical models to understand how systems behave generally, while simultaneously seeking to confront and validate models with data and make predictions. Thus, a significant portion of her research focuses on methods for statistical — particularly Bayesian — inference and validation for mechanistic mathematical models of biological and ecological systems. In relation to global change, Dr Johnson studies how climate impacts transmission of vector-borne diseases, and how to predict changes in where disease is likely to be transmitted as climate changes. She also examines how environment and human changes to the landscape can impact energetics, foraging behavior, and population dynamics of animals.


Dr Johnson is an Assistant Professor in Statistics and in Computational Modeling and Data Analytics (CMDA), and also has an affiliation in Biology. She teaches courses in Statistics and CMDA especially focusing on biological applications. Dr Johnson is also the US PI on the NIH funded Vector Behavior in Transmission Ecology (VectorBiTE) RCN.

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Recent Relevant Publications

R.A. Taylor, S.J. Ryan, J.S. Brashares and L.R. Johnson. Hunting, Food Subsidies and Mesopredator Release: Understanding the Dynamics of Crop-Raiding Baboons in a Managed Landscape. Ecology, 2016, 97 (4), 951-960. DOI: 10.1890/15-0885.1

S.J. Ryan, A. McNally, L.R. Johnson, E. Mordecai, K. Paaijmans, K. Lafferty. Climate change and malaria shifts: new implications for health geography and targeting control. Vector-Borne and Zoonotic Diseases, 2015, 15(12): 718-725. DOI:10.1089/vbz.2015.1822. (arXiv preprint: arXiv:1407.7612)

S.J. Ryan, T. BenHorin, L.R. Johnson. Malaria control and senescence: the importance of accounting for the pace and shape of ageing in wild mosquitoes. Ecosphere, 2015, 6:art170–art170. DOI:10.1890/ES15-00094.1.

L.R. Johnson, T. Ben-Horin, K.D. Lafferty, A. McNally, E. Mordecai, K. Paaijmans, S. Pawar, S.J. Ryan, Understanding uncertainty in temperature effects on vector-borne disease: A Bayesian approach. Ecology, 2015, 96:203-213. preprint arXiv:1310.5110.

J. Voyles, L.R. Johnson, C.J. Briggs, S.D. Cashins, R.A. Alford, L. Berger, L.F. Skerratt, R. Speare, E.B. Rosenblum. Experimental evolution alters the rate and temporal pattern of population growth in Batrachochytrium dendrobatidis, a lethal fungal pathogen of amphibians. Ecology and Evolution, 2014; 4(18): 3633-3641.

L.R. Johnson, L. Pecquerie and R.M. Nisbet. Bayesian inference for bioenergetic models, Ecology, 2013, 94(4):882-894. doi:10.1890/12-0650.1

E. Mordecai, K. Paaijmans, L.R. Johnson, C. Balzer, T. Ben-Horin, E. de Moor, A. McNally, S. Pawar, S. Ryan, T. Smith, K. Lafferty. Optimal temperature for malaria transmission is dramatically lower than previously predicted, Ecology Letters, 2013, 16(1):22-30. doi: 10.1111/ele.12015