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

EAGER：MSB：合作研究：将垫料质量和分解率联系起来的化学和微生物机制

• 批准号: 0946257
• 负责人: Daryl Moorhead
• 金额: $ 6.72万
• 依托单位: University of Toledo
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0946257&HistoricalAwards=false
• 关键词: EAGER; MSB; Collaborative; Research; Chemical

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.

缺乏对驱动分解的化学和微生物机制的机械理解。木质素：氮或木质素：纤维素比率的凋落物往往与分解率呈负相关，并经常被用来预测质量损失。此外，传统的经验模型通常将微生物活性的一般模式与环境变量相关联。这两种预测方法是相关的，没有明确表示的动态相互作用的基板和微生物活性，确定分解率。 最近，分解的理论模型（Guild-based Decomposition Model，GDM）集成了凋落物化学变化与微生物群落组成和生物化学活性变化的动态，但该模型尚未得到实验验证。本项目将测试一组假设，解决木质素，纤维素，氮（N）和微生物群落组成之间的相互作用对凋落物的分解速率。结果将被用来完善和验证GDM，从而提高全球变化下的分解预测。木质素和纤维素浓度不同的模式植物拟南芥的突变株系将用于凋落物分解实验。 该垃圾的化学和微生物组成将被跟踪，因为它在阿拉斯加北部生态系统的氮施肥和控制地块分解。 核苷酸类似物标记的DNA将允许确定的相对丰度推定的木质素和纤维素降解microbiesinsitu.This项目是高风险的有关拟南芥凋落物的自然litter。它在提供对生态系统动态的更好的机械和预测性理解方面是高回报的。更广泛的影响包括一个重要的模型植物分解研究，培训一名研究生和一名本科生，并为当地高中生开发一个夏季“突变体营地”的新应用。