Data from: Parallelism in adaptive radiations of experimental Escherichia coli populations

&lt;b&gt;Abstract&lt;/b&gt;&lt;br/&gt;Adaptive radiations are major contributors to species diversity. While the underlying mechanisms of adaptive radiations, specialization and trade-offs, are relatively well understood, the tempo and repeatability of adaptive radiations remain elusive. Ecological specialization can occur through the expansion into novel niches or through partitioning of an existing niche. To test how the mode of resource specialization affects the tempo and repeatability of adaptive radiations, we selected replicate bacterial populations in environments that promoted the evolution of diversity either through niche expansion or through niche partitioning, and in a third low-quality single-resource environment, in which diversity was not expected to evolve. Colony size diversity evolved equally fast in environments that provided ecological opportunities regardless of the mode of resource specialization. In the low quality environments, diversity did not consistently evolve. We observed the largest fitness improvement in the low quality environment and the smallest the glucose-limited environment. We did not observe a change in the rate of evolutionary change in either trait or environment, suggesting that the pool of beneficial mutations was not exhausted. Overall, the mode of resource specialization did not affect the tempo or repeatability of adaptive radiations. These results demonstrate the limitations of eco-evolutionary feedbacks to affect evolutionary outcomes.<b>摘要</b><br/>适应性辐射（adaptive radiation）是物种多样性形成的核心驱动力之一。尽管适应性辐射的核心机制——生态特化与进化权衡——已得到较为充分的阐释，但其演化速率与可重复性仍有待厘清。生态特化可通过两种路径实现：一是开拓全新生态位，二是对现有生态位进行资源分区。为探究资源特化模式如何影响适应性辐射的速率与可重复性，本研究选取了三类培养环境：两类分别通过生态位开拓、生态位分区的方式促进多样性演化，用以培育重复细菌种群；第三类为低质量单资源环境，预期不会发生多样性演化。在具备生态位机遇的环境中，无论资源特化模式如何，菌落大小多样性的演化速率均无显著差异。而在低质量环境中，多样性并未持续演化。本研究观察到，在低质量环境中细菌的适合度提升幅度最大，而在葡萄糖限制环境中提升幅度最小。无论是针对性状还是环境，我们均未观测到演化变化速率的改变，这表明有益突变库并未被耗尽。总体而言，资源特化模式并未对适应性辐射的速率与可重复性产生影响。本研究结果揭示了生态-演化反馈调控演化结局的局限性。