DISSERTATION RESEARCH: Refining decomposition models using a model system: Arabidopsis thaliana

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This graduate student dissertation study is using genetic mutants of a small plant, Arabidopsis thaliana, to improve predictions of how quickly dead plant material decomposes in ecosystems. Globally, dead plant material stores vast quantities of carbon and other nutrients. As this material decomposes, the carbon is converted to CO2, a greenhouse gas, and released to the atmosphere where it contributes to global warming. Thus, decomposition is a critical process with global consequences.In collaboration with her PhD advisor and other researchers, the student is also helping to refine the ?Guild-based Decomposition Model?. GDM is a theoretical model that predicts decomposition rates based on the chemical composition of dead plant material. In the past, it has been difficult to test the theory underlying this model (and others), because it has been technologically challenging to directly alter specific types of chemical compounds in plant material. However, the student has found a solution by using genetic mutants that differ in the production of lignin and cellulose, the two dominant chemical compounds in plants. She is decomposing dead material from these mutants in an Alaskan boreal forest, and she will compare her results to those predicted by the current version of GDM. She will then refine the model accordingly to improve its predictive power. Her work will advance predictions of climate change.