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Testing models of selection with data on behavioral isolation

Testing models of selection with data on behavioral isolation
用行为隔离数据测试选择模型
批准号:
0843392
负责人:
Stevan Arnold
金额:
$10.0万
依托单位:
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
项目状态:
已结题
起止时间:
2009-07-15 至 2010-06-30

项目摘要

项目成果

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中文摘要
翻译
该奖项是根据2009年美国复苏和再投资法案(公法111-5)资助的。进化生物学家已经开发了一些数学模型来理解伴侣偏好产生的特征选择过程。 然而,缺乏可以用来区分这些模型的测试,部分原因是这些模型的某些方面难以直接测量。 该项目将开发一种新的技术,通过比较替代模型的预测与相关物种之间行为(或生殖)隔离的数据,来测试伴侣偏好导致的选择模型。 该技术将通过应用最大似然的统计方法和利用有关物种之间进化关系的知识来扩展现有数据的能力。 研究人员将使用三个不同群体(蝾螈,鱼类和苍蝇)的可用数据集测试替代模型。 然而,开发的分析框架将适用于行为隔离的任何数据集和广泛的替代模型。 研究人员将在线提供进行分析的软件,扩展现有网站以说明替代模型,并在科学会议上举办有关方法的研讨会。 该项目的这些组成部分将使实证研究人员更好地理解选择模型,并使他们能够根据自己感兴趣的生物体的数据测试替代模型。
英文摘要
This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).Evolutionary biologists have developed a number of mathematical models to understand the process of selection on traits that arises from partner preferences. However, tests that can be used to discriminate among these models are lacking, in part because some aspects of the models are difficult to measure directly. This project will develop a novel technique for testing models of selection that result from partner preferences by comparing the predictions of alternative models with data on behavioral (or reproductive) isolation between related species. The technique will extend the power of existing data by applying the statistical approach of maximum likelihood and by using knowledge about the evolutionary relationships among the species. The investigators will test alternative models with available data sets for three divergent groups (salamanders, fishes, and flies). However, the analytical framework developed will be applicable to any set of data on behavioral isolation and for a wide range of alternative models. The investigators will make software to conduct the analysis available online, extend an existing website to illustrate alternative models and conduct a workshop on the methods at a scientific meeting. These components of the project will both provide a better understanding of selection models among empirical researchers and allow them to test alternative models on data from their own organisms of interest.
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