NSF Postdoctoral Fellowship in Biology FY 2012

强化分类交配的数学模型数学模型用于深入了解复杂的进化过程并量化进化力量。这项研究提出了两个项目，在这两种方式中使用数学模型来研究自然选择在物种形成中的作用。具体来说，这项工作研究了强化过程，选择有利于生殖隔离的进化，从而降低昂贵的杂交。第一个被提议的项目将创建分析模型，以确定在何种条件下，对杂交的选择会导致选择性交配的强化。第二个提议的项目将结合数学模型和经验观察来估计选择强度、杂交率和迁移对德克萨斯州野生植物Phlox drummondii强化的影响。基于天然drummondii种群的地理和遗传学，建立空间显式模拟模型。该模型将适合于经验数据，以给出涉及强化的进化参数的初步估计。这些项目将培养博士后学习各种数学、模拟和统计方法，如学习创建和解决动态系统、近似方法和似然方法。这项奖学金工作包括在奥斯汀当地的一所中学创建一个科学、技术、工程和数学（STEM）俱乐部，为不同的学生群体提供服务。STEM俱乐部的主要目标是指导学生设计和执行他们自己的研究项目。

Mathematical models for reinforcement of assortative matingMathematical models are used to gain insight into complex evolutionary processes and to quantify evolutionary forces. This study proposes two projects that use mathematical models in both of these ways to investigate the role of natural selection in speciation. Specifically, this work investigates the process of reinforcement in which selection favors the evolution of reproductive isolation that decreases costly hybridization. The first proposed project would create analytic models to determine the conditions under which selection against hybrids can cause reinforcement of assortative mating. The second proposed project will combine mathematical models with empirical observations to estimate the strength of selection, the rate of hybridization, and migration affecting reinforcement in the Texas wildflower, Phlox drummondii. A spatially-explicit simulation model will be developed based on the geography and genetics of natural P. drummondii populations. This model will be fit to empirical data to give the first estimates of evolutionary parameters involved in reinforcement. The proposed projects will train the postdoctoral fellow in diverse mathematical, simulation, and statistical methods such as learning to create and solve dynamic systems, methods of approximation, and likelihood methods. This fellowship work includes creating a Science, Technology, Engineering and Math (STEM) club at a local Austin middle school, which serves a diverse student body. The major goal of the STEM club will be to guide students through the design and execution of their own research projects.