灾难后的自然选择
Natural Selection in the Wake of Catastrophe
AI总结：
提出灾难后自然选择理论，发现平均适应度随时间倒数松弛，系数与耦合性状数成正比，并通过大肠杆菌抗生素实验验证，揭示其遵循Levenberg-Marquardt优化算法。
摘要：
从细菌到人类，生物体如果其性状增强适应性则更有可能生存。在良好适应其生态位的种群中，自然选择通过罕见的有利突变进行。但当灾难消除生态位多样性时，通常会发生快速适应。在这里，我们提出了一个经过数据验证的灾难后自然选择理论，并揭示了恢复过程中出现的一个简单规律：平均适应度随时间倒数松弛，其前置因子与耦合到灾后环境的性状数量成正比。我们使用抗生素给药后对大肠杆菌测量的实验适应度景观来检验我们的方法。由此产生的平均性状适应不是通过适应度景观上的梯度上升来描述的，而是遵循一种称为Levenberg-Marquardt优化的算法。在适应度峰值附近，进化轨迹偏向于非贪婪——从优化角度来看，灾后选择是乐观的。
英文摘要：
Living organisms, from bacteria to humans, are more likely to survive if their traits enhance fitness. In populations well adapted to their environmental niches, natural selection proceeds via rarely beneficial mutations. But when a catastrophe wipes out niche diversity, sudden adaptation often follows. Here, we present a data-validated theory of natural selection in the wake of catastrophe and unveil a simple law that emerges during recovery: the mean fitness relaxes inversely with time, with a prefactor proportional to the number of traits coupled to the post-catastrophe environment. We put our approach to test using experimental fitness landscapes measured following antibiotic administration to E. coli. The resulting mean trait adaptation is not described by gradient ascent on a fitness landscape, instead it follows an algorithm known as Levenberg-Marquardt optimization. Near fitness peaks, evolutionary trajectories are biased against greediness - from an optimization perspective, post-catastrophic selection is optimistic.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
