PostDoctoral Research Fellowship in Biological Informatics FY2006

项目名称：“生态新陈代谢理论中资源利用动力学的量化与整合”该项目是2006年生物信息学博士后研究奖学金项目。该项目的目标是(1)确定与河流生物群、种群和生态系统过程有关的数据是否支持新陈代谢生态学理论(MTE)，以及(2)通过整合Michaelis-Menten动力学来量化MTE资源供应期。这些目标将通过(1)运行回归模型来系统地测试MTE的预测；(2)评估跨多个生态尺度的资源使用是否可以使用Michaelis-Menten函数来描述；以及(3)量化Michaelis-Menten方程中关于体重和温度的参数的标度指数来解决这些目标。在研究复杂的生物和生态现象时，MTE的价值在于它能够区分体重和温度的影响。该项目完成后，除身体质量和体温外，还将隔离资源使用造成的影响。该项目的更广泛影响是提高了预测全球变化(气候和资源供应)和生态恢复对从生物到生态系统等不同规模的过程的影响的能力。这位研究员将把通过这个项目获得的技能应用于一个长期研究计划，重点是改变温度、碳和氮供应对社区和生态系统水平的影响。培训的目标是学习如何使用网格和分布式计算来合成现有的数据集，这些数据集包括跨越生态层次和广泛地理范围的信息。这位研究员将与杜克大学的艾米丽·伯恩哈特合作，在那里她将扩大她目前在生态系统生态学和生物地球化学领域的专业知识，包括理论生态学、宏观生态学和生态信息学领域的专业知识。

Project Title: "Quantification And Integration Of Resource Use Dynamics Within The Metabolic Theory Of Ecology" This project is awarded under the Postdoctoral Research Fellowships in Biological Informatics Program for 2006. The goals of the project are to (1) determine whether data pertaining to stream biota, populations, and ecosystem processes support the Metabolic Theory of Ecology (MTE), and (2) quantify the MTE resource supply term through the integration of Michaelis-Menten kinetics. These goals will be addressed by (1) running regression models to systematically test predictions of the MTE; (2) assessing whether resource use across multiple ecological scales can be described using a Michaelis-Menten function; and (3) quantifying the scaling exponents of parameters within the Michaelis-Menten equation with respect to body mass and temperature. The MTE is valuable for its ability to disentangle the effects of body mass and temperature when studying complex biological and ecological phenomena. Completion of this project will allow for the isolation of effects attributed to resource use, in addition to body mass and temperature. The broader impact of this project is an improved capacity to predict the effects of global change (both climate and resource supply) and ecological restoration on processes at different scales, from organisms to ecosystems. The Fellow will apply skills obtained through this project to a long-term research program focused on community and ecosystem-level effects of altered temperature, carbon, and nitrogen supply. The training goals are to learn how to use grid and distributed computing to synthesize existing datasets that include information across ecological hierarchies and broad geographic scales. The Fellow will work with Emily Bernhardt at Duke University where she will broaden her current expertise in the fields of ecosystem ecology and biogeochemistry to include expertise in the fields of theoretical ecology, macroecology, and ecoinformatics.