Our research focuses on understanding how plants respond to global environmental change: increasing CO2, temperature, and changing water availability. We integrate a range of observation streams (e.g., manipulation experiments, eddy covariance, and satellite data) with vegetation models to improve our capacity to predict future ecosystem change.
We tackle a diverse range of questions that connect terrestrial ecosystems with climate, including:
how will plants respond to increasing atmospheric CO2 concentration?
can we predict when and where trees might die of drought-induced mortality?
how do we improve our predictions of vegetation function as water and temperature become limiting?
what role does legacy to past environmental conditions (days-years) play in our capacity to predict current plant function?
how resilient are species distributions to future climate change?
how does plant physiology affect land-atmosphere feedbacks during climate extremes?
Our research group employs models of varying complexity, from simple (GDAY), to the more complex: stand (MAESPA), land surface (CABLE), dynamic vegetation (LPJ-GUESS; SDGVM) and coupled-climate (ACCESS) models.
"The method of science depends on our attempts to describe the world with simple theories: theories that are complex may become untestable, even if they happen to be true. Science may be described as the art of systematic over-simplification-the art of discerning what we may with advantage omit" - Karl Popper.