QEIB: General Genetic Models of the Geographic Mosaic Theory of Coevolution
QEIB: General Genetic Models of the Geographic Mosaic Theory of Coevolution
批准号:
0343023
负责人:
Scott Nuismer
金额:
$23.66万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2004
资助国家:
美国
项目状态:
已结题
起止时间:
2004-04-15 至 2008-03-31
中文摘要
共同进化在塑造生物多样性、塑造生物群落结构和推动相互作用的物种之间的紧密相互适应方面发挥着核心作用。在较短的生态时间尺度上,共同进化也会产生慢性适应不良,并维持相当高水平的遗传多态性。共同进化的地理镶嵌理论为共同进化过程的这些不同方面提供了一个统一的框架。该提案的总体目标是为该理论建立一个严格的理论支柱。这将通过应用最近开发的数学技术来实现,这些技术大大简化了复杂遗传系统的分析。拟议工作的广泛影响是双重的。首先,这些模型将把以前开发的数学技术扩展到共同进化系统。其结果将是新的和强大的分析工具的发展,可以很容易地应用到一系列不同的问题,在共同进化生物学。这种分析技术的传播将通过在年会上公开介绍技术和出版电子版Mathematica附录来促进。其次,培训部分的拟议工作将介绍两个研究生和本科生这些新的数学技术,以及其他计算和分析方法。这一培训将直接促进生物科学中分析和计算技术的进一步整合。
英文摘要
Coevolution plays a central role in shaping biological diversity, molding the structure of biological communities, and driving tight coadaptation between interacting species. Over shorter ecological time scales coevolution also generates chronic maladaptation and maintains substantial levels of genetic polymorphism. The geographic mosaic theory of coevolution provides a unifying framework for these disparate aspects of the coevolutionary process. The overarching goal of this proposal is to develop a rigorous theoretical backbone for this theory. This will be achieved through the application of recently developed mathematical techniques that greatly simplify the analysis of complex genetic systems. The broader impacts of the proposed work are twofold. First, the models will extend previously developed mathematical techniques to coevolving systems. The result will be the development of new and powerful analytical tools that can be readily applied to a diverse array of problems in coevolutionary biology. The distribution of this analytical technology will be facilitated by public presentation of techniques at annual meetings, and by the publication of electronic Mathematica appendices. Second, the training component of the proposed work will introduce two graduate students and an undergraduate to these new mathematical techniques, as well as other computational and analytical approaches. This training will directly contribute to the increased integration of analytical and computational techniques in the biological sciences.
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