MathBio Seminar | Péter Molnár | The costs of life, and what they can reveal about the future
Mar 13, 2025
2:30PM to 3:30PM
Date/Time
Date(s) - 13/03/2025
2:30 pm - 3:30 pm
Speaker: Péter Molnár (University of Toronto, Scarborough)
Research areas: Ecology, Global Change Ecology, Disease Ecology, Conservation Biology, Mathematical Ecology & Modelling
Location: Hamilton Hall, Room 410 & Zoom
Title: The costs of life, and what they can reveal about the future: Metabolic modelling approaches to the ecological and epidemiological impacts of climate change
Abstract: Climate change, land use change, and other anthropogenic disturbances are altering ecosystems globally at an accelerating rate. Predictive tools are needed to plan proactively, for example, to aid the conservation of endangered species in a changing landscape, or to prevent/mitigate the establishment of new pests and diseases. Classical population and community dynamics models can form the skeleton for global change impact forecasts, but often remain of limited use because it is unclear how key parameters might be changing in a changing environment. Bioenergetic approaches, such as the Metabolic Theory of Ecology and Dynamic Energy Budget modelling, can circumvent the inherent impossibility of measuring future ecological dynamics before that future occurs, by providing mechanistic links between an individual’s energy needs, its performance, and the resultant population dynamics in different environments. In this talk, I will discuss bioenergetic frameworks for understanding the ecological and epidemiological impacts of climate change, and illustrate their use in a variety of case studies: from disease emergence in warming populations; to climate-mediated range expansions of muskox and caribou parasites; to timelines of risk for the disappearance of polar bears. I will conclude the talk with a brief discussion on research gaps, road blocks, and ways forward towards ecological and epidemiological forecast models that might one day rival the power of weather and climate models.