The ability of lineages to disperse over evolutionary timescales may be influenced by the gain or loss of traits after adaptation to new ecological conditions. For example, rails (Aves: Rallidae) have many cases of flightless insular endemic species that presumably evolved after flying ancestors dispersed over large ocean barriers and became isolated. Nonetheless, the details of how flying and its loss have influenced the clade’s historical biogeography are unknown, as is the importance of other predictors of dispersal such as the geographic distance between regions. Here, we used a dated phylogeny of 158 species of rails to compare trait-dependent and trait-independent biogeography models in BioGeoBEARS. We evaluated a probabilistic historical biogeographical model that allows geographic range and flight to co-evolve and influence dispersal ability on a phylogeny. The best-fitting dispersal model was a trait-dependent dispersal (DEC + j + x + t₂₁ + m₁) that accrued 85.2% of the corrected Akaike Information Criterion (AICc) model weight. The distance-dependence parameter, x was estimated at −0.54, ranging from −0.49 to −0.65 across models, suggesting that a doubling of dispersal distance results in an approximately 31% decrease in dispersal rate (2^−0.54 = 0.69). The estimated rate of loss of flight (t₂₁) was similar across all models (~0.029 loss events per lineage per million years). The multiplier on dispersal rate when a lineage is non-flying, m₁, is estimated to be 0.38 under this model. Surprisingly, the estimate of m₁ was not 0.0, probably because the loss of flight is so common in the rails that entire clades of flightless species are found in the data, forcing the model to attribute some dispersal to flightless lineages. These results indicate that long-distance dispersal over macroevolutionary timespans can be modelled, rather than simply attributed to chance, allowing support for different hypotheses to be quantified and limitations to be identified. Overall, by combining new analytical methods with a comprehensive phylogeny, we use a quantitative framework to show how traits influence dispersal capacity and eventually shape geographical distributions at a macroevolutionary scale.

在适应新的生态条件之后，性状的获得或丧失可能会影响谱系在进化时间尺度上的分散能力。例如，铁轨（Aves：Rallidae）有许多无法飞行的岛状特有物种，它们大概是在飞行祖先分散在大海洋屏障上并变得孤立之后才进化出来的。尽管如此，关于飞行及其损失如何影响进化枝的历史生物地理学的细节尚不清楚，其他散布预测因子（如区域之间的地理距离）的重要性也未知。在这里，我们使用了158种铁轨的带日期的系统发育史，以比较BioGeoBEARS中的特征相关和特征独立的生物地理模型。我们评估了概率历史生物地理模型，该模型允许地理范围和飞行共同进化并影响系统发育上的扩散能力。最适合的扩散模型是特征依赖的扩散（DEC + j  +  x  +  t ₂₁  +  m ₁）占修正的Akaike信息准则（AICc）模型权重的85.2％。距离相关参数x估计为-0.54，整个模型的范围从-0.49到-0.65，这表明分散距离加倍导致分散速率降低约31％（2 ^-0.54  = 0.69）。在所有模型中，估计的飞行损失率（t ₂₁）相似（每百万年每谱系约0.029损失事件）。在该模型下，谱系不飞行时的扩散速率乘数m ₁估计为0.38。令人惊讶的是，m ₁并非0.0，可能是因为飞行损失在铁轨中非常普遍，以至于在数据中发现了所有无法飞行物种的进化枝，迫使模型将某些分散归因于无法飞行的血统。这些结果表明，可以对宏观演化时间跨度上的长距离分散进行建模，而不是简单地将其归因于偶然性，从而可以量化支持不同的假设并确定局限性。总体而言，通过将新的分析方法与全面的系统发育相结合，我们使用了定量框架来显示性状如何影响分散能力并最终以宏观进化尺度塑造地理分布。