Multiple Geographical Origins of Environmental Sex Determination enhanced the diversification of Darwin’s Favourite Orchids

Environmental sex determination (ESD) − a change in sexual function during an individual life span driven by environmental cues − is an exceedingly rare sexual system among angiosperms. Because ESD can directly affect reproduction success, it could influence diversification rate as compared with lineages that have alternative reproductive systems. Here we test this hypothesis using a solid phylogenetic framework of Neotropical Catasetinae, the angiosperm lineage richest in taxa with ESD. We assess whether gains of ESD are associated with higher diversification rates compared to lineages with alternative systems while considering additional traits known to positively affect diversification rates in orchids. We found that ESD has evolved asynchronously three times during the last ~5 Myr. Lineages with ESD have consistently higher diversification rates than related lineages with other sexual systems. Habitat fragmentation due to mega-wetlands extinction, and climate instability are suggested as the driving forces for ESD evolution.

analyses, we estimated the coefficient of variation (CV) to inform us on the rate heterogeneity among branches (CV approaching 0 indicates that the among-branch variation in substitution rate is much smaller magnitude than the mean rate, hence, a strict clock model cannot be rejected). Parameter convergence was confirmed using TRACER 1.6 (http://tree.bio.ed.ac.uk/software/tracer/). All dating analyses were performed at the CIPRES Science Gateway computing facility 7 .

Trait-dependent diversification analyses
We relied on the Binary State Speciation and Extinction (BiSSE) model 8 to estimate diversification rates associated with all three traits (i.e., ESD, epiphytism, and euglossine-bee pollination). BiSSE model built upon the premise that speciation and extinction rates depend on the state of a particular character. We tested eight models with different configurations of speciation, extinction, and transition rates between characters: (i) equal rates model (no effect of the trait on diversification, M 1 ); (ii) free speciation rates in lineages with and without a trait, and equal rates of extinction and transition (M 2 ); (iii) free extinction rates in lineages with and without a trait, and equal rates of speciation and transition (M 3 ); (iv) free transition rates in lineages with and without a trait, and equal rates of speciation and extinction (M 4 ); (v) free speciation and extinction rates in lineages with and without a trait, and equal rates of transition (M 5 ); (vi) free speciation and transition rates in lineages with and without a trait, and equal rates of extinction (M 6 ); (vii) free extinction and transition rates in lineages with and without a trait, and equal rates of speciation (M 7 ); and (viii) all parameters are free (M 8 ).
We estimated the speciation, extinction, and transition rates corresponding to the best fitting model, according to the AICc criterion. We ran Bayesian MCMC analyses on the consensus tree, using exponential priors with parameters obtained from the best fitting model, a 1000-step burn-in, and 10,000-step chain 8 . Convergence occurred within the few first steps and parameter estimates were very stable along the chain. We summarised the posterior distributions of samples to assess variation in net diversification, turnover, and transition rates across character states after the burn-in phase. We used a global sampling of 139 species (~32% of the extant diversity of Catasetinae + Cyrtopodiinae), and we accounted for missing taxa by accommodating sampling fractions for every trait as follows: (i) ESD: 41% of the know species with ESD sampled vs. 44% of the know species with alternative matting systems sampled; (ii) euglossine-bee pollination: 31% of the know species with this trait sampled vs.
33% of the know species with alternative pollination syndromes trait sampled; (iii) epiphytism: 40% of the know epiphyte species sampled vs. 45% of the known species with alternative plant habits sampled. Information on occurrence of epiphytism and euglossine-bee pollination syndrome was obtained from the literature 9,10 . We took phylogenetic and dating uncertainties into account by running these models over a series of 500 dated trees randomly selected from the BEAST dating analysis. We then selected the best-fitting model based on the corrected Akaike Informative Criterion (AICc).
Because BiSSE may be subject to Type I errors biases 11 , we tested whether diversification rates associated to character states are not artefacts. To do so, we reshuffled the coding states onto the phylogeny and ran the BiSSE models. We executed 10,000 iterations, estimating the AIC of the best model at each iteration to get the null distribution of AIC (associated with random states) and compared it with the AIC value obtained with the observed dataset.
Orchidacearum: Vol. 5 Table S1. Species names and voucher information for material use in this study. Taxa sequenced and newly produced sequences are shown in bold face. Table S2. Primer and PCR settings used for amplifying plastid and nuclear DNA loci.    3 Speciation rates 4 Extinction rates 5 transition rates from state 0 to 1 6 transition rates from state 1 to 0  3 Speciation rates 4 Extinction rates 5 transition rates from state 0 to 1 6 transition rates from state 1 to 0                Telipogon_acicularis_Telipogon_acicularis  Telipogon_barbozae_Telipogon_barbozae  Telipogon_biolleyi_Telipogon_biolleyi  Telipogon_bombiformis_Telipogon_bombiformis  Telipogon_bowmanii_Telipogon_bowmanii  Telipogon_butcheri_Telipogon_butcheri  Telipogon_caulescens_Telipogon_caulescens  Telipogon_hystrix_Telipogon_hystrix  Telipogon_monteverdensis_Telipogon_monteverdensis  Telipogon_nervosus_Telipogon_nervosus  Telipogon_obovatus_Telipogon_obovatus  Telipogon_panamensis_Telipogon_panamensis  Telipogon_parvulus_Telipogon_parvulus  Telipogon_pogonostalix_Telipogon_pogonostalix  Telipogon_pulcher_Telipogon_pulcher  Telipogon_venustus_Telipogon_venustus  Thysanoglossa_jordanensis_Thysanoglossa_jordanensis  Tolumnia_henekenii_Tolumnia_henekenii  Tolumnia_triquetra_Tolumnia_triquetra  Tolumnia_tuerckheimii_Tolumnia_tuerckheimii  Tolumnia_variegata_Tolumnia_variegata  Trichocentrum_bicallosum_Trichocentrum_bicallosum  Trichocentrum_cosymbephorum_Trichocentrum_cosymbephorum  Trichocentrum_flavovirens_Trichocentrum_flavovirens  Trichocentrum_splendidum_Trichocentrum_splendidum  Trichoceros_muralis_Trichoceros_muralis  Trichopilia_brevis_Trichopilia_brevis  Trichopilia_fragrans_Trichopilia_fragrans  Trichopilia_leucoxantha_Trichopilia_leucoxantha  Trichopilia_sanguinolenta_Trichopilia_sanguinolenta  Trichopilia_suavis_Trichopilia_suavis  Trichopilia_turialbae_Trichopilia_turialbae  Trizeuxis_falcata_Trizeuxis_falcata  Vitekorchis_lucasiana_Vitekorchis_lucasiana Warmingia_eugenii_Warmingia_eugenii     Ga lea nd ra gre en wo od ian a Ga lea ndr a bat em ani i Ga lea nd ra ba ue ri Ga lea nd ra ma gn ico lum na Ga lea nd ra sta ng ea na Ga lea nd ra mi na x Ga lea nd ra cri sta ta Ga lea nd ra sa nta ren a Ga lea nd ra bla nc he tii Ga lea ndr a ma cro ple ctra Ga lea ndr a lep toc era s Gal ean dra bey rich ii Gal ean dra junc eao ides Ga lea ndr a styl lom isan tha Gal ean dra par agu aye nsis