Creating Clines to Study Dispersal and Adaptation

谱系是地理上相邻的具有不同基因组成的人群混合的区域。强大的理论和统计方法可用于研究维持自然曲线的进化力量。在这里，我们证明了线条也为分散和选择的实验研究提供了一个强大的操纵工具。我们建立了一个适合研究快速演化变化的非平衡跃迁动力学模型。我们利用该模型研究了马铃薯作物主要的剥叶虫——科罗拉多马铃薯甲虫在杀虫剂抗性方面的扩散和自然选择。我们将在麻萨诸塞州和缅因州的复制马铃薯田中创建抗性曲线，并用它们来测试关于适应空间变化栖息地的假设，包括扩散模式和选择强度。减缓农药抗性进化速度的基于“避难所”的新策略也取决于对扩散的了解。我们对扩散的测量直接适用于新的管理策略，以减缓马铃薯甲虫对杀虫剂的抗性进化的速度，我们的新方法可以应用于其他作物害虫系统。我们的成果将与马铃薯种植者分享，他们将直接受益。

Clines are regions of blending between geographically abutting populations with different genetic makeup. Powerful theoretical and statistical methods are available to study the evolutionary forces that maintain natural clines. Here we demonstrate that clines also provide a powerful manipulative tool for the experimental study of dispersal and selection. We develop a new model of non-equilibrium cline dynamics that is suitable for studying rapid evolutionary changes. We use the model to study dispersal and natural selection in insecticide resistance in the Colorado potato beetle, a major defoliator of potato crops. We will create resistance clines in replicate potato fields in Massachusetts and Maine, and use them to test hypotheses about adaptation to spatially varying habitats, including dispersal patterns and the strength of selection. New 'refuge'-based strategies to slow the rate that pesticide resistance evolves also depend on knowledge of dispersal. Our measurements of dispersal apply directly to new management strategies to slow the rate that resistance to pesticides evolves in potato beetles, and our new methods can be applied to other crop-pest systems. Our results will be shared with potato growers, who will directly benefit.