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：垃圾的纤维素比经常与分解速率负相关，并且经常用于预测质量损失。另外，传统的经验模型通常将微生物活动的通用模式与环境变量联系起来。两种预测方法都是相关的。两者都不明确表示底物和微生物活性的动态相互作用，从而决定分解速率。 最近，分解理论模型（基于公会的分解模型，GDM）将改变垃圾化学的动力学与改变微生物群落组成和生化活动的动态，但该模型尚未经过实验验证。该项目将测试一组关于木质素，纤维素，氮（N）和微生物群落组成的假设，这些假设涉及垃圾分解速率。结果将用于完善和验证GDM，从而改善全球变化下分解的预测。木质素和纤维素浓度变化的模型植物拟南芥的突变线将用于垃圾分解实验。 该垃圾的化学和微生物组成将在阿拉斯加北方生态系统中分解并控制在N-有限的和控制图中时。 DNA的核苷酸模拟标记将允许确定原位推定的木质素和降解纤维素降解的微生物的相对丰度。就将拟南芥与自然垃圾关联而言，该项目是高风险的。在提供对生态系统动力学的更好的机械和预测理解方面，这是高额付款。更广泛的影响包括重要的模型工厂在分解研究中的新型应用，一名研究生和一名本科生的培训以及为当地高中生开发夏季“突变营”。