Global changes such as elevated atmospheric carbon dioxide (CO2) and warming are not occurring in isolation. It has been assumed that if process-based models represent each of these global changes faithfully, they will accurately represent their interactive effects as well. However, this assumption has rarely been tested with empirical data from an interactive global change experiment. We are harnessing data from the TeRaCON (Temperature, Rainfall, CO2, and N) experiment to determine whether the Community Land Model with two different underlying soil models can faithfully represent interactive effects of elevated CO2 and warming on land carbon storage. 

Scientists use a number of methods to study how terrestrial ecosystems will respond to global change, including observations, manipulative experiments, and process-based models. However, it is unclear whether these methods provide similar responses. To assess this, I am leading a meta-analysis of studies that assess global change responses using at least two different methods. From these studies we will collect direction and comparative magnitude of responses using different methods. If methods provide similar responses we might be more confident in land feedbacks to global change. If they provide different responses, we will have good directions for future work. We are collecting data for this work now.

We have a wealth of soil fungal trait data in numerous databases but struggle to apply these to soil biogeochemical models due to scale mismatches, lack of direct translation between traits and model parameters, and difference in model parametrizations and structures. Working with a team of microbial ecologists and biogeochemical modelers, we are assessing the ability to use fungal trait data in two different soil biogeochemical models (MIMICS and MycoCORPSE) and assessing how empirical variability in fungal traits translates to variability in soil carbon cycling in models. This work will determine what additional data could be useful for models, what model structures could better incorporate empirical data, and how important empirical variation in fungal traits is for ecosystem functions.