PostDoctoral Research Fellowship in Biological Informatics FY2006

项目名称：“生态学代谢理论中资源利用动态的量化与整合”，2006年度中国科学院生物信息学博士后科研资助项目。该项目的目标是：(1)确定与溪流生物群、种群和生态系统过程有关的数据是否支持生态学代谢理论（MTE），以及(2)通过Michaelis-Menten动力学的整合来量化MTE资源供应期限。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)利用Michaelis-Menten函数评价资源利用在多个生态尺度上的可描述性；(3)量化Michaelis-Menten方程内参数相对于体重和温度的标度指数。在研究复杂的生物和生态现象时，MTE的价值在于它能够理清体重和温度的影响。该项目完成后，除了体重和温度之外，还可以隔离资源使用的影响。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尺度过程影响的能力。该研究员将把通过该项目获得的技能应用于一项长期研究计划，该计划侧重于改变温度、碳和氮供应对社区和生态系统水平的影响。培训目标是学习如何使用网格和分布式计算来综合现有的数据集，包括跨生态层次和广泛地理尺度的信息。该研究员将与杜克大学的艾米丽·伯恩哈特（Emily Bernhardt）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.