Recovering species demographic history from multi-model inference: the case of a neotropical savanna tree species

Abstract

Background: Glaciations were recurrent throughout the Quaternary and potentially shaped species genetic structure worldwide by affecting population dynamics. Here, we implemented a multi-model inference approach to recover the distribution dynamics and demographic history of a Neotropical savanna tree, Tabebuia aurea (Bignoniaceae). Exploring different algorithms and paleoclimatic simulations, we used ecological niche modelling to generate alternative hypotheses of potential demographic changes through the last glacial cycle and estimated genetic parameters using coalescent modelling. Results: Comparing predictions from demographic hypotheses with genetic parameters of modern populations, our findings revealed a likely scenario of population decline, with spatial displacement towards Northeast Brazil from the last glacial maximum to the mid-Holocene. Subsequently, populations expanded in response to the return of the climatically suitable conditions in Central-West Brazil. Nevertheless, a wide historical refugium across Central Brazil likely maintained large populations connected throughout time. The expected genetic signatures from such predicted distribution dynamics are also corroborated by spatial genetic structure observed in modern populations. Conclusion: By exploring uncertainties inherent in multiple working hypotheses, we have shown that multi-model inference is a fruitful and efficient approach to recover the nature, timing and geographical context of the Tabebuia aurea population dynamic in response to the Quaternary climate changes.