I am broadly interested in exploring impacts of host selection and dispersal at multiple spatial scales as well as scaling up from individual–based behavioural models to population-, community-, and even landscape-level models of insect outbreak and disturbance.
I have considerable experience modelling biological and ecological systems as well as designing and carrying out experiments. As part of my model development and to test model predictions, I have relied on empirical and experimental data collected in both lab and field settings. I have developed strong data analytical and statistical skills, and am a proficient programmer, with experience using C, Mathematica, and R programming languages. I have authored and contributed to several R packages.
In addition to designing and executing computer-based experiments, I have also implemented both lab- and field-work-based studies, all the way through from initial conception, to planning, conducting measurements, and data analysis. I have worked with various data management systems including spreadsheets and databases, as well as using version control systems to ensure data integrity, reproducibility of analyses, and transparency of results reporting.
Working with Eliot McIntire (Canadian Forest Service), my current postdoctoral work involves the development of large scale predictive models of mountain pine beetle (MPB) spread from BC and AB into the western range of the boreal forest. I am developing individual- and population-based models of MPB dispersal and expansion.
Development of these simulation models required software development for building, running, and analyzing outputs. I have been a core author and designer of the
SpaDES R package as well as a web-based user interface, which facilitates the development and deployment of ecological simulation models.
Boreal forest ecosystem forecasts using integrated dynamic simulation models
Working with others in the McIntire lab at PFC, we are working on integrating various simulation models dealing with forest vegetaiton dynamics, fire, insect disturbance, and wildlife populations.
Habitat selection decisions of individuals and effects on population-level processes
Previously, my doctoral research involved development of analytical and simulation models of mountain pine beetle (MPB) habitat selection and dispersal behaviour, and the resulting population distributions and dynamics. Specifically, I considered the role of energy- and time-limited host search in MPB, and I developed individual-based state-dependent dynamic game models of beetle host selection.
Theoretical implementation of bark beetle genetic control
Selfish genetic elements have the potential to drastically reduce the fitness of a pest population via meoitic drive. I evaluated the theoretical potential for such a mechanism to maintain beetle populations below outbreak levels by coupling classic analytical population dynamics and population genetics models incorporating this genetic control element, within a spatially explicit simulation model of beetle infestation across a forest landscape.
Temperature-Dependent Community Dynamics
Working with Bernie Roitberg (SFU), Erin Udal (SFU), and Franz Simon (SFU/Yale), we are developing a temperature-dependent tritrophic community model of a plant, herbivore, and predator system. We are examining the effects of temperature changes and refugia on the dynamics and stability of such systems. We are following up with experiments to test the outcomes of the models.
Evolution of Omnivory in a Community Context
We developed an evolutionary simulation model to consider the feeding strategies (broadly classified as three feeding types: herbivores, omnivores, and carnivores) of a community of individuals and explore how the intrinsic properties of these foragers and extrinsic characteristics of their environment determine the prevalence of omnivores and other feeding types.
Chubaty, A.M., B.O. Ma, R.W. Stein, D.R. Gillespie, L.M. Henry, C. Phelan, E. Palsson, F.W. Simon, B.D. Roitberg (2014) On the evolution of omnivory in a community context. Ecology and Evolution 4(3):251-265. [ DOI: 10.1002/ece3.923 ]