Postdoctoral Research Fellowship in Biological Informatics FY 2006

项目名称：“整合多尺度数据以了解鸟类病原体成功入侵的生态学”本项目是2006年生物信息学博士后研究奖学金项目的一部分。入侵生物的传播以及它们如何与原生群落相互作用是生态学研究的一个重要而具有挑战性的焦点。 发展一个预测性的理解生态系统如何应对入侵物种需要严格的定量方法，可以容纳多种来源的不确定性：在数据中，在生物过程的理解，并由于随机性。 西尼罗河病毒（WNV）是一个有用的模型系统，了解入侵物种的动态，因为大量的相关数据是可用的，病原体传播对当地人口的影响是可以识别的。 该项目将使用来自不同来源的数据，以确定关键的空间和时间变量背后的一个成功的物种（西尼罗河病毒）入侵野生鸟类群落。 这项工作将在俄亥俄州州立大学的诺埃尔克雷西博士的实验室进行。这项研究的预期结果包括：1）明确合并各种生态和基于普查的数据的框架，2）适应规模变化的统计方法（在数据和过程中），3）改进预测入侵和对本地物种影响的技术，4）明确识别数据和科学方面的缺陷，以确定研究优先事项并指导大空间尺度数据收集的设计。 该奖学金将促进研究员职业研究计划的发展，包括识别，量化和预测自然和人为干扰的生态反应所需的新颖分析策略。

Project Title: "Integrating multi-scale data to understand the ecology of a successful pathogen invation in birds"This project is awarded under the Postdoctoral Research Fellowships in Biological Infomatics Program for 2006. The spread of invasive organisms and how they interact with native communities is an important and challenging focus of ecological research. Developing a predictive understanding of how ecosystems respond to invasive species requires rigorous quantitative methods that can accommodate multiple sources of uncertainty: in data, in the understanding of biological processes, and due to stochasticity. West Nile virus (WNV) is a useful model system for understanding invasive species dynamics because large amounts of relevant data are available, and pathogen spread has recognizable impacts on local populations. This project will use data from diverse sources to identify critical spatial and temporal variables behind a successful species (WNV) invasion into wild bird communities. This work will be conducted in the laboratory of Dr. Noel Cressie at Ohio State University.The expected outcome of this study include: 1) a framework for explicitly merging diverse ecological and census-based data, 2) statistical methods for accommodating changes in scale (in data and process), 3) improved techniques for forecasting invasions and impacts on native species, and 4) explicit identification of deficiencies in data and science that will define research priorities and direct designs for collection of data at large spatial scales. The fellowship will facilitate the Fellow's development of a career research program, including novel analytic strategies required to identify, quantify, and forecast ecological responses to natural and human-mediated disturbance.