Data from: Inference of evolutionary jumps in large phylogenies using Lévy processes

While it is now widely accepted that the rate of phenotypic evolution may not necessarily be constant across large phylogenies, the frequency and phylogenetic position of periods of rapid evolution remain unclear. In his highly influential view of evolution, G. G. Simpson supposed that such evolutionary jumps occur when organisms transition into so called new adaptive zones, for instance after dispersal into a new geographic area, after rapid climatic changes, or following the appearance of an evolutionary novelty. Only recently, large, accurate and well calibrated phylogenies have become available that allow testing this hypothesis directly, yet inferring evolutionary jumps remains computationally very challenging. Here, we develop a computationally highly efficient algorithm to accurately infer the rate and strength of evolutionary jumps as well as their phylogenetic location. Following previous work we model evolutionary jumps as a compound process, but introduce a novel approach to sample jump configurations that does not require matrix inversions and thus naturally scales to large trees. We then make use of this development to infer evolutionary jumps in Anolis lizards and Loriinii parrots where we find strong signal for such jumps at the basis of clades that transitioned into new adaptive zones, just as postulated by Simpson's hypothesis.尽管目前学界已普遍认可，大型系统发育树中的表型进化（phenotypic evolution）速率未必恒定，但快速进化阶段的发生频率及其系统发育位置仍不明确。在极具影响力的进化生物学观点中，G·G·辛普森（G. G. Simpson）提出，当生物体跃迁至所谓的新适应区（adaptive zones）时，便会发生这类进化跳跃（evolutionary jumps）——例如在扩散至新地理区域、经历快速气候变迁，或是出现进化革新之后。直至近年，大型、精准且经过良好校准的系统发育树才得以问世，使得该假说可被直接检验，但进化跳跃的推断仍在计算层面极具挑战性。本研究开发了一种计算效率极高的算法，可精准推断进化跳跃的速率、强度及其系统发育位置。沿袭此前研究的思路，我们将进化跳跃建模为复合过程（compound process），但提出了一种无需矩阵求逆（matrix inversions）的全新跳跃配置采样方法，因此可自然适配大型系统发育树的分析需求。随后我们利用该方法对安乐蜥（Anolis lizards）与Loriinii鹦鹉（Loriinii parrots）开展进化跳跃推断，结果在跃迁进入新适应区的支系（clades）基部发现了这类跳跃的强信号，与辛普森假说的推测完全一致。