The forecast for biodiversity under climate change requires understanding of biological mechanisms and their interaction with climate through carbon and energy fluxes. In this project, we investigate functional traits related to the light environment, at intra-specifc, inter-specific and community scale. We further investigate constraints within the trait-space and how these constraints regulate fAPAR (a driver of carbon assimilation) and albedo (a driver of the energy budget). Finally, we experimentally test how light-related traits change under a global change driver (i.e. drought) and how these changes feed back to the atmosphere, in the Arctic tundra, Tibetan grassland, and the tropical forest in Borneo.
The interaction of shortwave radiation with vegetation influences key mechanisms (i.e. plant physiology, species interactions through competition) driving biodiversity changes under future conditions, and related feedbacks to climate. Yet, efforts to improve the representation of shortwave radiation with vegetation in ecological models and land surface–atmosphere interaction schemes of climate models have been very limited.
We will use the functional trait approach and combine it with 3D radiative transfer modelling to investigate how traits and their coordination drive shortwave radiation fluxes related to the carbon (fAPAR) and energy (albedo) exchange between the atmosphere and land surface. Two key dimensions were recently identified in the trait space (Diaz, 2016) – size of plants and organs, and construction costs for photosynthetic leaf area.
Simulating a global change driver (i.e. drought), we will analyse if phenotypic plasticity follows a coordination of trait changes and how trait changes affect shortwave radiation. We will further identify deviations under stress conditions from the ‘evolutionary equilibrium’.
We plan to proceed as follows: