EAGER: MSB: Collaborative Research: Chemical and Microbial Mechanisms Linking Litter Quality and Decomposition Rate

缺乏对驱动分解的化学和微生物机制的机械理解。凋落物的木质素：氮或木质素：纤维素的比例经常与分解率负相关，经常用于预测质量损失。此外，传统的经验模型通常将微生物活动的一般模式与环境变量联系起来。两种预测方法是相关的；两者都没有明确地表示底物和微生物活性之间的动态相互作用，这种相互作用决定了分解的速度。近年来，一种将凋落物化学变化与微生物群落组成和生物化学活性变化相结合的理论分解模型（Guild-based decomposition model， GDM）出现，但该模型尚未得到实验验证。该项目将测试一系列假设，解决木质素、纤维素、氮(N)和微生物群落组成对凋落物分解速率的相互作用。结果将用于改进和验证GDM，从而改进全球变化下分解的预测。模式植物拟南芥的木质素和纤维素浓度变化的突变系将用于凋落物分解实验。这些凋落物的化学和微生物组成将在阿拉斯加北方生态系统的施氮和对照地块上进行分解。DNA的核苷酸类似物标记将允许测定假定的木质素和纤维素降解微生物的相对丰度。本项目在拟南芥凋落物与自然凋落物的关系方面具有高风险。就提供对生态系统动力学的更好的机制和预测性理解而言，这是高回报的。更广泛的影响包括一种重要的模式植物在分解研究中的新应用，一名研究生和一名本科生的培训，以及为当地高中生举办的夏季“突变营”。

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.