BUSCADOR RECOLECTA

Digital.CSIC. Repositorio Institucional del CSIC

oai:digital.csic.es:10261/281260

Appendix 1 - GenBank sequences All sequence data used for this study (a file is generated per gene). Appendix 2 - Gene alignments and trees The individual gene alignments as recovered by MAFFT. Results of the Bayesian phylogenetic analyses for each gene, and an explanation of the results. Appendix 3 - Parnassiinae_Fossils_MB The total-evidence matrix (including molecular and morphological data) used for the phylogenetic placement of fossils with MrBayes. Appendix 4 - BEAST files for the dating analyses The BEAST files for the Bayesian dating analyses (the tree prior can be a Yule process or a birth-death model, and the dataset can include or not the morphological data). Appendix 5 - Parnassiinae Distribution The current geographic species distribution data of all Parnassiinae as coded present (1) or absent (0) in all ten geographic areas (Western Palearctic, North Africa, Turkey, Central Asia, Himalaya, India, Mongolia, Siberia, China-Japan, and Western Nearctic). Appendix 6 - Adjacency matrices through time The time-stratified biogeographic model used for DEC analyses (time slices represent geological epochs or stages in the Cenozoic). Appendix 7 - Himalaya and Tibetan paleoaltimetry Paleo-elevation for the Himalayan and Tibetan compiled from the literature. Appendix 8 - Bayesian paleoenvironmental model Description of the Bayesian episodic environment-dependent birth-death model. Appendix 9 - PartitionFinder analyses and results Results of PartitionFinder performed on the concatenated molecular dataset. Appendix 10 - Time-calibrated trees of Parnassiinae Time-calibrated trees of Parnassiinae as estimated by BEAST following four different analyses. Appendix 11 - Bayes factors Dating Results of the model comparison for the dating analyses based on marginal likelihood estimates and Bayes factors. Appendix 12 - Parnassiinae DEC Biogeographic history of Parnassiinae as estimated by DEC. Appendix 13 - DDD Parnassiinae Results from the diversity-dependence diversification analyses in DDD. Appendix 14 - SSE models Results of the MuSSE and GeoSSE analyses performed on 200 trees randomly taken from the Bayesian dating analysis. Models are ranked by AICc. Appendix 15 - MuSSE MCMC difference on speciation rates Plot of the difference between speciation rates between all traits. When the difference overlaps zero (vertical red bar), the speciation rates are not significantly different. Appendix 16 - Robustness of SSE analyses Robustness of the SSE models with simulation tests, HiSSE analyses and an implementation in RevBayes. For the simulation, the difference of fit between the best model and the reference model is shown with the red vertical line for real data, and in black for simulated data. HiSSE and RevBayes agree with the MuSSE models on host plants. Appendix 17 - BAMM analyses Summary of diversification models in BAMM compared across a gradient of values for the Poison process governing the number of rate shifts. Appendix 18 - Credible set of speciation shifts in Parnassiinae Credible set of configuration shifts inferred with BAMM and five different values of the Poison prior. It shows the distinct shift configurations with the highest posterior probability. For each shift configuration, the locations of rate shifts are shown as black circles, with circle size proportional to the marginal probability of the shift. Appendix 19 - BAMM-like RevBayes analyses Rate-through-time plot as inferred with RevBayes for Parnassiinae. Net diversification rates significantly changed and increased along the stem of the genus Parnassius, in agreement with the rates as estimated with BAMM. Appendix 20 - CoMET analyses Rate-through-time plot as inferred with CoMET for Parnassiinae. The analyses detected one possible mass extinction around 15 Ma and one speciation rate shift around 3.5 Ma, in agreement with two TreePar analyses allowing or not the mass extinction. Appendix 21 - Correlation parameters for Bayesian models Credibility intervals of the correlation parameters for the Bayesian (RevBayes) environment-dependent diversification models. Appendix 22 - Relation butterfly diversification and host-plant diversity Correlation (linear regression) between speciation rates as inferred with MuSSE (a) and BAMM (b) and the species richness of host plants on which each parnassiine clade is feeding. In both cases, a strong and positive correlation is found. Scripts and R codes for diversification analyses Scripts for diversification analyses.zip, In macroevolution, the Red Queen (RQ) model posits that biodiversity dynamics depend mainly on species-intrinsic biotic factors such as interactions among species or life-history traits, while the Court Jester (CJ) model states that extrinsic environmental abiotic factors have a stronger role. Until recently, a lack of relevant methodological approaches has prevented the unraveling of contributions from these two types of factors to the evolutionary history of a lineage. Here we take advantage of the rapid development of new macroevolution models that tie diversification rates to changes in paleoenvironmental (extrinsic) and/or biotic (intrinsic) factors. We inferred a robust and fully-sampled species-level phylogeny, as well as divergence times and ancestral geographic ranges, and related these to the radiation of Apollo butterflies (Parnassiinae) using both extant (molecular) and extinct (fossil/morphological) evidence. We tested whether their diversification dynamics are better explained by a RQ or CJ hypothesis, by assessing whether speciation and extinction were mediated by diversity-dependence (niche filling) and clade-dependent host-plant association (RQ) or by large-scale continuous changes in extrinsic factors such as climate or geology (CJ). For the RQ hypothesis, we found significant differences in speciation rates associated with different host-plants but detected no sign of diversity-dependence. For CJ, the role of Himalayan-Tibetan building was substantial for biogeography but not a driver of high speciation, while positive dependence between warm climate and speciation/extinction was supported by continuously varying maximum-likelihood models. We find that rather than a single factor, the joint effect of multiple factors (biogeography, species traits, environmental drivers, and mass extinction) is responsible for current diversity patterns, and that the same factor might act differently across clades, emphasizing the notion of opportunity. This study confirms the importance of the confluence of several factors rather than single explanations in modeling diversification within lineages., Peer reviewed