A mechanistic understanding of the chemical and microbial mechanisms that drive decomposition is lacking. Lignin:nitrogen or lignin:cellulose ratios of litter are frequently negatively correlated with decomposition rates and are often used to predict mass loss. In addition, traditional empirical models typically relate generic patterns of microbial activity to environmental variables. Both predictive approaches are correlative; neither explicitly represents the dynamic interaction of substrate and microbial activity that determines the rate of decomposition. Recently, a theoretical model of decomposition (Guild-based Decomposition Model, GDM) integrated the dynamics of changing litter chemistry with changing microbial community composition and biochemical activities, but this model has yet to be experimentally validated. This project will test a set of hypotheses that address interactions among lignin, cellulose, nitrogen (N), and microbial community composition on decomposition rates of litter. Results will be used to refine and validate GDM, thus improving predictions of decomposition under global change. Mutant lines of the model plant Arabidopsis thaliana that vary in lignin and cellulose concentrations will be used for litter decomposition experiments. The chemical and microbial composition of that litter will be tracked as it decomposes in N-fertilized and control plots in an Alaskan boreal ecosystem. Nucleotide analog labeling of DNA will permit the determination of the relative abundance of putative lignin- and cellulose-degrading microbes in situ.
This project is high-risk in terms of relating Arabidopsis litter to natural litter. It is high-payoff in terms of supplying a better mechanistic and predictive understanding of ecosystem dynamics. Broader impacts include a novel application of an important model plant to decomposition studies, training for one graduate and one undergraduate student, and development of a summer "Mutant Camp" for local high school students.
