Flight over the Proto-Caribbean seaway: Phylogeny and macroevolution of Neotropical Anaeini leafwing butterflies

Contents lists available at ScienceDirect Molecular Phylogenetics and Evolution journal homepage: www.elsevier.com/locate/ympev Flight over the Proto-Caribbean seaway: Phylogeny and macroevolution of Neotropical Anaeini leafwing butterflies Emmanuel F.A. Toussaint a,⁎ , Fernando M.S. Dias b , Olaf H.H. Mielke b , Mirna M. Casagrande b , Claudia P. Sañudo-Restrepo c , Athena Lam d , Jérôme Morinière d , Michael Balke d,e , Roger Vila c a Natural History Museum of Geneva, CP 6434, CH 1211 Geneva 6, Switzerland b Laboratório de Estudos de Lepidoptera Neotropical, Departamento de Zoologia, Universidade Federal do Paraná, P.O. Box 19.020, 81.531-980 Curitiba, Paraná, Brazil c Institut de Biologia Evolutiva (CSIC-UPF), Passeig Marítim de la Barceloneta, 37, 08003 Barcelona, Spain d SNSB-Bavarian State Collection of Zoology, Münchhausenstraße 21, 81247 Munich, Germany e GeoBioCenter, Ludwig-Maximilians University, Munich, Germany ARTICLE INFO Keywords: Andes and Central American highland orogenies Butterfly evolution Eocene paleoenvironments Host plant shifts Nymphalidae phylogenetics Panamanian archipelago ABSTRACT Our understanding of the origin and evolution of the astonishing Neotropical biodiversity remains somewhat limited. In particular, decoupling the respective impacts of biotic and abiotic factors on the macroevolution of clades is paramount to understand biodiversity assemblage in this region. We present the first comprehensive molecular phylogeny for the Neotropical Anaeini leafwing butterflies (Nymphalidae, Charaxinae) and, applying likelihood-based methods, we test the impact of major abiotic (Andean orogeny, Central American highland orogeny, Proto-Caribbean seaway closure, Quaternary glaciations) and biotic (host plant association) factors on their macroevolution. We infer a robust phylogenetic hypothesis for the tribe despite moderate support in some derived clades. Our phylogenetic inference recovers the genus Polygrapha Staudinger, [1887] as polyphyletic, rendering the genera Fountainea Rydon, 1971 and Memphis Hübner, [1819] paraphyletic. Consequently, we transfer Polygrapha tyrianthina (Salvin & Godman, 1868) comb. nov. to Fountainea and Polygrapha xenocrates (Westwood, 1850) comb. nov. to Memphis. We infer an origin of the group in the late Eocene ca. 40 million years ago in Central American lowlands which at the time were separated from South America by the Proto-Caribbean seaway. The biogeographical history of the group is very dynamic, with several oversea colonization events from Central America into the Chocó and Andean regions during intense stages of Andean orogeny. These events coincide with the emergence of an archipelagic setting between Central America and northern South America in the mid-Miocene that likely facilitated dispersal across the now-vanished Proto-Caribbean seaway. The Amazonian region also played a central role in the diversification of the Anaeini, acting both as a museum and a cradle of diversity. We recover a diversification rate shift in the Miocene within the species-rich genus Memphis. State speciation and extinction models recover a significant relationship between this rate shift and host plant association, indicating a positive role on speciation rates of a switch between Malpighiales and new plant orders. We find less support for a role of abiotic factors including the progressive Andean orogeny, Proto-Caribbean seaway closure and Quaternary glaciations. Miocene host plant shifts possibly acted in concert with abiotic and/ or biotic factors to shape the diversification of Anaeini butterflies. 1. Introduction The Neotropics are the most biodiverse region on Earth and have thereby captured the attention of biogeographers and macroevolutionary biologists alike (Hoorn et al., 2010; Antonelli and Sanmartín, 2011). Yet, our understanding of the origins of this biota is still fragmentary, although it is believed that abiotic events have had a profound impact on lineage diversification in the region (Hoorn et al., 2010; Antonelli and Sanmartín, 2011; Garzón-Orduña et al., 2014; Bacon et al., 2015a, 2015b; Antonelli et al., 2018a, 2018b). Two relatively well studied abiotic factors potentially shaping the evolution of numerous Neotropical clades are the Andean and Central American highland orogenies. Geological evidence suggests that present-day surface elevation in the Andes is the result of late Miocene tectonic activity resulting from deformation initiated in the EoceneOligocene (see review in Mora et al. (2010)). The rise of the Andes has https://doi.org/10.1016/j.ympev.2019.04.020 Received 7 April 2018; Received in revised form 3 April 2019; Accepted 19 April 2019 ⁎ Corresponding author. E-mail address: [email protected] (E.F.A. Toussaint). Molecular Phylogenetics and Evolution 137 (2019) 86–103 Available online 22 April 2019 1055-7903/ © 2019 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/). T been identified by several studies as a possible driver of diversification (e.g.,Antonelli et al., 2009; Elias et al., 2009; Hoorn et al., 2010; Sedano and Burns, 2010; Luebert et al., 2011; Perret et al., 2013; Chazot et al., 2016, 2018; De Silva et al., 2016; Lagomarsino et al., 2016). A global pattern emerging from these studies is the role of the Andean uplift as a species pump through allopatric speciation and ecological opportunity related to elevational gradients (e.g.,Willmott et al., 2001; Hall, 2005; Hughes and Eastwood, 2006). Landscape reconfiguration fostered by the orogeny in the Andes but also in Amazonia might have also played an important role in fueling diversification (e.g.,Condamine et al., 2012; De Silva et al., 2016). In the north of the Neotropics, the Central American highlands (CAH) stretch from the north of Mexico to Panama. This region is a composite mountainous chain of various temporal and geological origins (Mastretta-Yanes et al., 2015). The oldest block within the CAH is the Sierra Madre Oriental whose origins are tied to the Laramide orogeny, with an emergence in the Cretaceous (ca. 70 Ma) and the final stages of the orogeny in the Eocene (ca. 40 Ma). Although the exact geological sequence of its elevational gradient is not fully understood, nowadays it has summits up to > 3500 m (e.g., Cerro San Rafael). The Sierra Madre Occidental and Sierra Madre del Sur likely originated in the Eocene with intense tectonic activity up to the Pleistocene (Ferrari et al., 2007), while the Chiapan-Guatemalan highlands were formed in the late Miocene and Pliocene (Manea and Manea, 2006; Mora et al., 2007). The most recent and important geological stage in the emergence of the CAH is the orogeny of the Trans-Mexican volcanic belt from the Miocene to the present (Ferrari et al., 2012). The orogeny of the CAH has been shown to have fueled diversification in several lineages and is likely a key process governing biodiversity assembly in the Neotropics (e.g.,Gutiérrez-García and VázquezDomínguez, 2013). The closing of the Proto-Caribbean seaway (i.e., the formation of the Isthmus of Panama) also referred to as Central American seaway (Iturralde-Vinent, 2006; Montes et al., 2015), is another major geological remodeling of the region. It is thought to have had a significant impact on biotic evolution. The closure of the Proto-Caribbean seaway was originally proposed to have occurred some 3 Ma (Kegwin, 1978), and several early models have been proposed for the kinematics of this event (e.g.,Pindell et al., 1988; Iturralde-Vinent, 2006). However, a recent debate emerged relative to its timing. A recent geological model based on Eocene zircons found in Colombia and of hypothesized Panamanian origin, suggested that the formation of the Isthmus of Panama was completed in the mid-Miocene ca. 13–15 million years ago (Ma) (Montes et al., 2015). A meta-analysis of molecular phylogenies also supported this view of a Miocene land bridge favoring the Great American biotic interchange between Nearctic and Neotropical regions (Bacon et al., 2015a, 2015b; but see Lessios, 2015; Marko et al., 2015). Some recent molecular studies on marine lineages specifically addressing this question also found that vicariant patterns likely resulted from an earlier closure of the Proto-Caribbean seaway (e.g.,Stange et al., 2018). O’Dea et al. (2016), providing an extensive review of geological, paleontological, and molecular records, rejected this hypothesis and supported the older hypothesis of a Pliocene closure. Although there is still no current consensus on the exact geological sequence and timing of the Proto-Caribbean seaway closure (O’Dea et al., 2016; Jaramillo et al., 2017a; Molnar, 2017; Jaramillo, 2018), the literature suggests that dispersal between Central America and South America was increasingly facilitated as early as the mid-Miocene by the existence of island chains in the Caribbean seaway and ephemeral land-bridges (Iturralde-Vinent, 2006). Glaciation cycles during the Quaternary (2.6 Ma–present) are hypothesized to have had a major impact on species formation, by fostering habitat fragmentation and speciation in refugia (Haffer, 1969; Brown et al., 1974; Whitmore and Prance, 1987; Garzón-Orduña et al., 2014; Smith et al., 2014; but see Rull, 2015; Matos-Maraví, 2016). Under this scenario, populations of forest-dwelling lineages would have been separated repeatedly during Pleistocene glacial maxima and would eventually become genetically isolated before secondary contact. The study of Neotropical butterflies has largely contributed to shedding light on some of the above-mentioned evolutionary mechanisms explaining lineage diversification in the region (e.g.,Willmott et al., 2001; Elias et al., 2009; Condamine et al., 2012; Chazot et al., 2016, 2018; De Silva et al., 2016). The widespread subfamily Charaxinae comprises ca. 400 mostly tropical butterfly species organized in six tribes, the Old World Charaxini, Pallini and Prothoini, and the New World Anaeini, Anaeomorphini and Preponini, all comprising generally colorful butterflies with sometimes cryptic undersides, that as adults feed on carrion, oozing sap, rotten fruits and dung (DeVries, 1987; D’Abrera, 1988). Although these butterflies are charismatic and their taxonomy mostly well-known, the systematics of Charaxinae have only recently been the focus of comprehensive molecular phylogenetic studies (Aduse-Poku et al., 2009; Ortiz-Acevedo and Willmott, 2013; Toussaint et al., 2015; Toussaint and Balke, 2016; Ortiz-Acevedo et al., 2017). While Preponini recently received some attention (OrtizAcevedo and Willmott, 2013; Ortiz-Acevedo et al., 2017) and Anaeomorphini were placed with robust support as sister to Preponini (Espeland et al., 2018), the systematics and evolution of the Neotropical tribe Anaeini (ca. 100 described species; Fig. 1) remain to be explored. The phylogenetic relationships among and within its genera are still largely unresolved (but see Wahlberg et al., 2009), although species groups and an intuitive phylogenetic hypothesis were proposed by Comstock (1961). The taxonomy of the tribe is complex and has changed repeatedly (Rydon 1971; D’Abrera, 1988; Salazar and Constantino, 2001; Salazar, 2008). Here we follow the latest taxonomic arrangement of Lamas (2004) in addition to species and genera described or reinstated since this catalogue (Willmott and Hall, 2004; Choimet, 2009; Dottax and Pierre, 2009; Dias et al., 2012a, 2012b, 2015, 2019; Pierre and Dottax, 2013; Costa et al., 2014). See Table 1 for details on the classification. Following this arrangement, Anaeini comprises ca. 100 described species distributed across the Neotropics, from Andean plateaus (up to 3000 m) to Amazonian lowland forests. These butterflies are also found in Central America and a few species occur in the Caribbean Basin and southern Nearctic. Using anchored phylogenomics, Espeland et al. (2018) revisited the deeper-level phylogenetic relationships and dating among butterflies. In that study, Anaeini was inferred as sister to all other tribes in the subfamily, and the crown of Charaxinae was dated from the Eocene ca. 41.5 Ma (95% credibility interval, CI = 30.4–54.0 Ma). Because Anaeini butterflies are comparatively old, they represent a suitable model to test the impact of the large-scale abiotic changes shaping the geography of the Neotropical region as outlined above. Moreover, this offers the opportunity to also explore other potential drivers of lineage diversification such as host plant associations. Although host plants are not known for all species of the tribe, most caterpillars seem to feed on Malpighiales and particularly on species of the genus Croton Linnaeus, 1753 (Malpighiales, Euphorbiaceae, Crotonoideae), whereas only species of Consul Cramer, 1776 and some of Memphis Hübner, [1819] feed on other plant orders (Laurales and Piperales) (Beccaloni et al., 2008). Here, we present the first molecular phylogeny of Anaeini and use it to test the putative contribution of various factors to diversification. Specifically, we test the following hypotheses (H): - H1: The Isthmus of Panama dispersal (IPD) hypothesis where the closing of the Proto-Caribbean seaway would have enhanced the connectivity between Central America, the Nearctic region and South America, with subsequent diversification in these regions. Under this hypothesis, we expect a dynamic biogeographical pattern with most dispersal events between the North Andes and the Central American/Nearctic regions occurring after the mid-Miocene, a period that coincides with the beginning of the Proto-Caribbean seaway closure. We also expect an increase in diversification rate E.F.A. Toussaint, et al. Molecular Phylogenetics and Evolution 137 (2019) 86–103 87 (a) (c) (e) (g) (b) (d) (f) (h) (i) Fig. 1. Habitus pictures of various Anaeini leafwing butterfly lineages in natura. Pictures from Andrew Neild: (a) Coenophlebia archidona; (b) Siderone galanthis, (c) Zaretis isidora; (d) Consul fabius; (e) Anaea troglodyta; (f) Fountainea ryphea, (g) Memphis verticordia, (h) Memphis anna; (i) Memphis falcata. Table 1 Taxonomic arrangement of the Anaeini according to different authors. C1961 R1971 SC2001 S2008 L2004 Anaea (Coenophlebia) * Coenophlebia Coenophlebia Coenophlebia Anaea (Zaretis) * Zaretis Zaretis Zaretis Anaea (Siderone) * Siderone Siderone Siderone Anaea (Anaea)Anaea Anaea Anaea Anaea Anaea (Hypna)Hypna Hypna Hypna Hypna Anaea (Consul)Consul Consul Consul Consul Anaea (Polygrapha)Polygrapha Polygrapha Polygrapha Polygrapha Anaea (Polygrapha)Polygrapha Zikania** Prozikania Polygrapha Anaea (Polygrapha)Polygrapha Muyshondtia Muyshondtia Polygrapha Anaea (Polygrapha)Polygrapha Pseudocharaxes Pseudocharaxes Polygrapha Anaea (Memphis) I Memphis Fountainea Fountainea Fountainea Anaea (Memphis) II Memphis Rydonia Rydonia Memphis Anaea (Memphis) III Memphis Annagrapha Annagrapha Memphis Anaea (Memphis) IVA-B Fountainea Fountainea Fountainea Fountainea Anaea (Memphis) V Cymatogramma Fountainea Fountainea Fountainea Anaea (Memphis) VIA-B Cymatogramma Cymatogramma Cymatogramma Memphis Anaea (Memphis) VIIA-C Memphis Cymatogramma Cymatogramma Memphis Anaea (Memphis) VIIIA-D Memphis Memphis Memphis Memphis Notes: Comstock’s (1961) species groups are indicated with roman numerals and capital letters. C1961 – Comstock (1961), R71 – Rydon (1971), SC01 – Salazar and Constantino (2001), L2004 – Lamas (2004), and S08 – Salazar (2008); * not included in Anaeini ** preocc. Zikania Borgmeister, 1925 (Diptera). E.F.A. Toussaint, et al. Molecular Phylogenetics and Evolution 137 (2019) 86–103 88 following the colonization of these regions due to new potential ecological opportunities. - H2: The Andean and Central American highland diversity pump (ACD) hypothesis, where the uplift of the Andes and subsequent landscape rearrangements would have promoted diversification through allopatric and elevational parapatric speciation in the Andes and Central American highlands. Under this hypothesis, we expect shifts in diversification rate in Andean and/or Central American highland clades contemporaneous with the major phases of the Andean and Central American highland orogeny in the Miocene, and multiple occurrences of allopatric sister species in these mountain ranges. - H3: The Quaternary glaciation refugia (QGR) hypothesis where glaciation cycles during the Pleistocene would have fostered ecosystem fragmentation and isolation of populations in allopatry therefore fueling speciation in refugia. Under this hypothesis, we expect bursts in diversification in the Pleistocene, with potentially a significant number of Pleistocene allopatric splits across the Neotropics. - H4: The host plant shift (HPS) hypothesis, where a shift to a different plant order during the evolution of Anaeini would have triggered a diversification rate shift (increase or decrease) as a result of an adaptive process. Under this hypothesis, we expect the clustering of species whose caterpillar feed on the same plant orders, a diversification rate shift synchronous with the estimated ancestral host plant shift, and a statistical correlation between diversification rates and host plant preferences. 2. Material and methods 2.1. Taxon sampling and molecular biology Legs from freshly collected specimens were removed and preserved in 96% ethanol or sampled from dried museum specimens (Table S1). We gathered all known extant genera and 92 out of ca. 102 currently described Anaeini species (ca. 90% of the currently described species richness in Anaeini). We also included 10 specimens of infraspecific taxa that are likely valid species based on both molecules and morphology (see Dias, 2013), out of ca. 30 taxa that might represent valid species but are currently recognized as infraspecific taxa or are placed in synonymy. Most of these likely good species are located in the genera Fountainea Rydon, 1971 (ca. 13 putative species) and Memphis (ca. 8 putative species). In total, our dataset therefore included 102 species of Anaeini out of possibly ca. 130 valid species (ca. 80% of the currently estimated total species richness in Anaeini). Although the monophyly of Anaeini is not disputed (Espeland et al., 2018), we included several representatives from the five other described tribes of Charaxinae (Anaeomorphini, Charaxini, Pallini, Preponini and Prothoini) to permit the use of Bayesian relaxed clock molecular dating (see below). The tree was rooted with Morpho helenor (Cramer, 1776) based on the unequivocal sister-relationship of Satyrinae with Charaxinae (Espeland et al., 2018). DNA was extracted using the DNeasy kit (Qiagen, Hilden, Germany). We used the PCR protocols listed in Table S2 to amplify and sequence the following gene fragments: mitochondrial cytochrome coxidase subunit I (CO1, 657 bp) and NADH-ubiquinone oxidoreductase chain 5 (ND5, 420 bp), and nuclear ribosomal protein S2 (Rps2, 423 bp), ribosomal protein S5 (Rps5, 573 bp) and Wingless (408 bp). The DNA sequences were edited and aligned with MUSCLE (Edgar, 2004) in Geneious R11 (Biomatters, http://www.geneious.com/). New sequences were deposited in GenBank (accession Nos. MK850566–MK850817. 2.2. Molecular phylogenetics We used the maximum likelihood (ML) program IQ-TREE 1.6.7 (Nguyen et al., 2015) to infer phylogenetic relationships using the concatenated matrix. The dataset was initially divided by codon position for each protein coding gene fragment resulting in 15 initial partitions. The best partitioning scheme and models of substitution for each resulting partition were simultaneously selected in IQ-TREE using ModelFinder (Kalyaanamoorthy et al., 2017), with the greedy algorithm and based on the Akaike information criterion corrected (AICc). The optimal models of nucleotide substitution were determined across all available models in IQ-TREE including the FreeRate model (+R, Soubrier et al., 2012), that relaxes the assumption of gamma distributed rates. We conducted 500 tree searches starting from random parsimony topologies to avoid local optima and selected the resulting best ML tree by comparing log-likelihood scores. To assess nodal support, we performed 5000 ultrafast bootstrap replicates (UFBoot, Minh et al., 2013; Hoang et al., 2018) with the best ML tree using the command –bb, and SH-aLRT tests (Guindon et al., 2010) with 5000 replicates using the command -alrt. To reduce the risk of overestimating branch supports with UFBoot due to severe model violations, we used hill-climbing nearest neighbor interchange (NNI) to optimize each bootstrap tree. The UFBoot has been shown to be largely unbiased compared to standard or alternative bootstrap strategies, and the SH-aLRT to be as conservative as standard bootstrap (Minh et al., 2013; Hoang et al., 2018). Because initial analyses recovered inter-tribal phylogenetic relationships that differed from the most comprehensive phylogenomic study of butterflies to date (Espeland et al., 2018), we ran the final analyses constraining the inter-tribal relationships to match the ones of Espeland et al. (2018). In the latter study based on > 350 nuclear exons, Anaeini was recovered as sister to the remainder of Charaxinae, and Anaeomorphini + Preponini was recovered as sister to Prothoini +(Charaxini + Pallini) with maximal nodal support (Espeland et al., 2018). We believe this is the best approach considering the low nodal support in studies that relied on a few loci to estimate inter-tribal relationships within this subfamily (Aduse-Poku et al., 2009; Wahlberg et al., 2009; Ortiz-Acevedo and Willmott, 2013; this study). It is also noteworthy that the monophyly of tribes within Charaxinae and especially of Anaeini was never rejected in any of these studies, therefore even if the monophyly of Anaeini is not tested per se in this study, we wish to emphasize that it has never been and is not currently subject to controversy based on molecular and/or morphological grounds. Besides, the analysis of preliminary anchored phylogenomic data confirms the monophyly and intra-subfamilial placement of Anaeini (Toussaint unpublished data). 2.3. Divergence time estimation Divergence times were inferred in a Bayesian framework with BEAST 1.8.4 (Drummond et al., 2012). As for the phylogenetic analyses, the dataset was initially divided by codon position for each protein coding gene fragment resulting in 15 initial partitions. The best partitioning scheme and models of substitution were then selected in PartitionFinder2 (Lanfear et al., 2017) using the greedy algorithm and the Bayesian Information Criterion across all models included in BEAST (option models = beast). We tested different clock partitioning schemes by assigning either (i) a unique uncorrelated lognormal relaxed clock for all partitions; (ii) two uncorrelated lognormal relaxed clocks, one for all mitochondrial partitions and one for all nuclear partitions; or (iii) eight uncorrelated lognormal relaxed clocks, one for each partition. We also tested different tree models by using a Yule (pure birth) or a birthdeath model in different analyses. The rates of the uncorrelated lognormal relaxed clocks were set with an approximate continuous time Markov chain rate reference prior (Ferreira and Suchard, 2008). The analyses consisted of 20 million generations with a parameter and tree sampling every 1000 generations. We estimated marginal likelihood estimates (MLE) for each analysis using path-sampling and stepping–- stone sampling (Xie et al., 2011; Baele et al., 2012, 2013), with 1000 path steps, and chains running for one million generation with a log likelihood sampling every 1000 cycles. E.F.A. Toussaint, et al. Molecular Phylogenetics and Evolution 137 (2019) 86–103 89 Since there is no described fossil of the subfamily Charaxinae available, we relied on the large-scale fossil-based dating framework of Espeland et al. (2018) inferred for the butterfly superfamily Papilionoidea, where the crown of Charaxinae was dated to 41.5 Ma (95% CI = 30.4–54.0 Ma) and the split of Charaxinae and Satyrinae was dated to 63.8 Ma (CI = 48.5–79.5 Ma). Independent studies using different and/or overlapping fossil calibrations investigating the timeline of Nymphalidae evolution found very similar age estimates (Peña and Wahlberg, 2008; Wahlberg et al., 2009). As a result, we constrained the two nodes corresponding to the crown of the subfamily Charaxinae and to the split of Charaxinae and Satyrinae with two uniform priors encompassing the credibility intervals specified above. The tribal relationships were constrained as for the IQ-TREE analyses to avoid inferring unrealistic topologies and violating calibration priors. 2.4. Ancestral range estimation and geological rationale for model design We inferred the biogeographical history of Anaeini using the Rpackage BioGeoBEARS 1.1.1 (Matzke, 2018). We conducted the analyses under the Dispersal Extinction Cladogenesis (DEC) model (Ree and Smith, 2008). We used the BEAST Maximum Clade Credibility (MCC) tree from the best analysis (see Results) with outgroups pruned. The distribution of taxa in the Neotropics was extrapolated from the labels of ca. 9000 specimens deposited at various institutions (listed in Table S1) and published records (e.g.,Comstock, 1961). The estimation of ancestral ranges in Neotropical clades is challenging due to the very dynamic geological history of the landmasses involved. This is even more apparent in clades whose temporal origin predates to some extent the orogeny of the Andes and Central American highlands (i.e., Anaeini leafwing butterflies, see Results), and for which the subsequent definition of biogeographic areas is not trivial. In this study, we opted for a biogeographic regionalisation based on climatic and geological evidence following the reconstructions presented in different seminal studies focusing on the South American region (e.g.,Iturralde-Vinent, 2006; Wesselingh and Salo, 2006; Hoorn et al., 2010; Mora et al., 2010; Mastretta-Yanes et al., 2015; Montes et al., 2015; O’Dea et al., 2016). Therefore, the following areas were used in the analyses: N, Nearctic region corresponding to the lands north of Mexico, L, Central American lowlands from sea level to the Central American highland foothills, H, Central American highlands from their foothills (at about 500–1000 m) to their summits, this arrangement resulting in three disjunct areas, one in northern Mexico, one in southern Mexico, Guatemala, Honduras and Nicaragua, and one between Costa Rica and Panamá, R, the Caribbean archipelago, C, “Chocó” region corresponding to lands west of the Andes south of the Darién gap, from sea level to the Andean foothills, W, west Andean ranges and slopes including all of the western and central Andean mountain ranges draining to the Pacific or the Caribbean, from their foothills to their summits and the eastern Andean mountain ranges draining to the Pacific or the Caribbean, from their foothills to their watershed boundary; E, east Andean slopes (Yungas) including eastern Andean slopes draining to the Amazon and the Orinoco, from their foothills to their watershed boundary; A, the Amazon region and Guianas corresponding to lands east of the Andes draining to the Amazon or the Atlantic north coast, from sea level to the Andean foothills; and T, the Atlantic region including all remaining forested lands draining to the Atlantic east coast. We compared a null model ignoring geological evolution of the Neotropical region with a designed model taking into account knowledge of the tectonic history of the region with six time slices and differential dispersal rate scalers between the defined areas (Fig. S1). The six time slices were designed as follows; TS1 (root age–34 Ma), corresponding to the early stages of the Andean and Central American highland orogeny and the emergence of the Pozo embayment corresponding to a large marine incursion in present-day western Amazonia connected to both the Atlantic and Pacific Oceans and located east of the low to mid-elevation proto-Andes therefore possibly limiting dispersal between the proto-Andes and eastern Amazonia (Hoorn et al., 2010; Wesselingh and Hoorn, 2011), TS2 (34–32 Ma), corresponding to the existence of the ephemeral Greater Antilles and subaerial Aves Ridge (GAARlandia land bridge) facilitating dispersal between the Caribbean and Neotropical regions (Iturralde-Vinent and McPhee, 1999; Iturralde-Vinent, 2006), TS3 (32–23 Ma), corresponding to the disappearance of the GAARlandia land bridge and Pozo embayment (Iturralde-Vinent and McPhee, 1999; Iturralde-Vinent, 2006; Hoorn et al., 2010; Wesselingh and Hoorn, 2011), associated with reduced connectivity between the Caribbean archipelago and northern South America, and renewed terrestrial connectivity between the Andean and Amazonian regions, TS4 (23–15 Ma), corresponding to the acceleration of the Andean and Central American highland orogenies with the transformation of the paleo-Orinoco drainage system into the Pebas system, a large complex of shallow swamps and wetlands stretching from the Atlantic to the Pacific coasts and submerging most of the western Amazonian region (Wesselingh et al., 2001; Wesselingh and Salo, 2006; Antonelli et al., 2009; Hoorn et al., 2010; Wesselingh and Hoorn, 2011; Jaramillo et al., 2017b), thereby separating the northern Andes and western Neotropics from the rest of South America (Hoorn et al., 2010; Wesselingh and Hoorn, 2011), TS5 (15–7 Ma), corresponding to the appearance of the Acre system dividing the Amazonian region by a large aquatic system, therefore continuing to reduce dispersal between the Andean and Amazonian regions, as well as the early stages of the Proto-Caribbean seaway closure, progressively generating the formation of the Isthmus of Panama and associated with possible strings of islands between Central America and northern South America, facilitating dispersal between these two regions (Bacon et al., 2015a,2015b; Montes et al., 2015; Jaramillo et al., 2017a; Jaramillo, 2018), TS6 (7 Ma–present), corresponding to the disappearance of the Acre system replaced by the current Amazon river drainage system, thereby restoring connectivity between the Andean and Amazonian regions, as well as the full closure of the Proto-Caribbean seaway (e.g., O’Dea et al., 2016), and the formation of present-day Andean and Central American highland landscapes. The dispersal rate scaler values were selected according to terrain and water body positions throughout the timeframe of the group evolution. Dispersal between adjacent areas was not penalized while dispersal between areas separated by water barriers or another area was penalized using a dispersal rate scaler of dr = 0.75 (i.e., a penalty of 0.25 was applied). Penalties were summed as areas were progressively more distant from each other or separated by other barriers. The adjacency matrices were left unconstrained. 2.5. Ancestral altitudinal range estimation We estimated ancestral altitudinal ranges under the DEC model as implemented in Lagrange (Ree et al., 2005; Ree and Smith, 2008), to take into account the widespread distribution of some taxa (e.g., from low elevation to high elevation). We compiled elevational distribution for each species included in the topology based on our records and the literature (see above). We considered three different altitudinal zones: lowland (L, < 1000 m), premontane (M, 1000–2000 m) and montane (H, > 2000 m), based on our personal observations of Anaeini butterfly altitudinal patterns and vegetation transition zones across the Andes. The adjacency and dispersal rate scaler matrices were left unconstrained. 2.6. Ancestral host plant estimation We reconstructed ancestral host plant order preferences in a Bayesian framework using the R-package phytools 0.6 (Revell, 2012) based on the threshold model (Revell, 2014), to account for missing host plant data. We used the function ancThresh (Revell, 2014), to run a Bayesian Markov chain Monte Carlo (MCMC) analysis under the threshold model. We assumed a Brownian motion model for the E.F.A. Toussaint, et al. Molecular Phylogenetics and Evolution 137 (2019) 86–103 90 Fig. 2. Molecular phylogeny of Anaeini leafwing butterflies. Maximum likelihood topology of the best-scoring tree inferred in IQ-TREE. Nodal support expressed in SH-aLRT and ultrafast bootstrap (UFBoot) is given as indicated in the caption except for major nodes that are all labelled when SH-aLRT < 80 and/or UFBoot < 95. Habitus of some outgroups and Anaeini species marked with an asterisk are highlighted on the right of the figure and ordered from top to bottom. Picture credits: Emmanuel Toussaint. E.F.A. Toussaint, et al. Molecular Phylogenetics and Evolution 137 (2019) 86–103 91 evolution of the liability. The latter is an underlying, continuous, unobserved trait used in the threshold model to estimate discrete trait values of taxa included in the phylogeny (see Revell, 2014 for details about this model). The analysis consisted of 1 million generations sampled every 1000 generations, with a final burn-in of 25%. The host plant data was collected from our field notes as well as the literature (DeVries, 1986, 1987; Ackery, 1988; Queiroz, 2002; Beccaloni et al., 2008; Janzen and Hallwachs, 2017). To avoid having to select an ordering for the liability model, we assumed only two host plant states: Malpighiales or Laurales/Piperales (i.e., non-Malpighiales) (Table S1). A prior probability of 1.0 was placed on the state of terminals for which host plant observation data was available. An uninformative prior probability of 0.5 equivalent to a flat prior probability was placed on the state of the terminals for which we did not have host plant information (Revell, 2014). 2.7. Diversification rate analyses We used the program Bayesian Analysis of Macroevolutionary Mixtures (BAMM) to estimate putative diversification rates among and within clades (Rabosky, 2014). The analyses were conducted in BAMM 2.5.0 with four reversible jump MCMC running for 10 million generations and sampled every 1000 generations. Parameter priors were estimated through the setBAMMpriors command in R (expectedNumberOfShifts = 1.0; lambdaInitPrior = 2.108; lambdaShiftPrior = 0.0278; muInitPrior = 2.108). We used different values (0.1, 0.5, 1, 2, 5 and 10) for the parameter controlling the compound Poisson process that determines the prior probability of a rate shift along branches of the chronogram (expectedNumberOfShift, equivalent to the poissonRatePrior parameter in earlier versions of BAMM). Missing taxon sampling was considered by setting the sampling fraction for all major clades of the phylogeny, based on the recognized and presumed species richness of major clades in Anaeini (unpublished data and references hereinabove; see Table S3). The BAMM output files were then analyzed using the R-package BAMMtools 2.1.6 (Rabosky et al., 2014). The posterior distribution of the BAMM analysis was used to estimate the best shift configuration and the 95% credible set of distinct diversification models. To determine the impact of host plant specialization on the diversification of Anaeini leafwing butterflies, we used the Multiple State Speciation and Extinction (MuSSE; FitzJohn et al., 2009) model implemented in a ML framework in the R-package diversitree 0.9–10 (FitzJohn, 2012). The likelihood function was generated using the function ‘make.musse’, and optimized using the function ‘find.mle’. We built a series of models to test whether speciation (λ), extinction (µ), or transition rates (q) between host plant orders (Malpighiales:1, Piperales:2, Laurales:3) were dependent on trait evolution. The models were built by constraining the different parameters (λ1, λ2, λ3, µ1, µ2, µ3, q12, q21, q13, q31, q23, q32) to be free or equal in different combinations. Bayesian MCMC analyses running for 10,000 steps sampled every 100 steps were conducted to estimate posterior distributions of parameters for the best model (see Results). Although MuSSE analyses can provide interesting results relative to trait diversification, caution should be exercised when studying the results of SSE models as emphasized by several recent studies (e.g.,Rabosky and Goldberg, 2015; Beaulieu and O’Meara, 2016). Therefore, we complemented our diversification rate investigation with analyses relying on a hidden state speciation and extinction model (HiSSE; Beaulieu and O’Meara, 2016). The HiSSE model accounts for the presence of unmeasured factors that could impact diversification rate dynamics estimated for the states of the trait under scrutiny (i.e., host plant association). The HiSSE model therefore assumes “hidden” states that are related to each observed state in the model (Malpighiales-feeding and non-Malpighiales-feeding) and exhibit potentially distinct diversification dynamics than the observed states in isolation (Beaulieu and O’Meara, 2016). We used the R-package hisse 1.9.1 (Beaulieu and O’Meara, 2016) to compare different models including the original BiSSE model (Maddison et al., 2007), as well as characterindependent diversification models (CID-2 and CID-4). The states that we used were; 0 (association with Malpighiales) and 1 (association with a different host plant order). Dual transitions between both the observed trait and the hidden trait were not included and all transition rates were setup to be equal because they can be difficult to estimate (Beaulieu and O’Meara, 2016). 3. Results 3.1. Phylogenetic relationships Original unconstrained ML searches inferred poorly supported intertribal phylogenetic relationships, but the resolution within Anaeini was very similar to the one obtained with constrained ML searches. The ML tree searches conducted in IQ-TREE and the BEAST analyses with intertribal relationships constrained, yield very similar estimates with only slight topological changes (Figs. 2 and 3). The phylogeny reconstructed in the best ML tree (LnL = −24101.930) is well resolved and generally presents moderate (UFBoot ≥ 95 or SH-aLRT ≥ 80) to robust (UFBoot ≥ 95 and SH-aLRT ≥ 80) nodal support along the backbone and for major clades within Anaeini, although some of the most derived nodes have lower nodal support (Fig. 2). The BEAST topology inferred under the preferred model (see below) recovers high posterior probabilities (PP ≥ 0.95) along the backbone and for major clades (Fig. 3). Within Anaeini, we recover the monotypic Hypna Hübner, [1819] as sister to the rest of the tribe. We also recover Coenophlebia Felder & Felder, 1862, Phantos Dias 2019, Siderone Hübner, [1823] and Zaretis Hübner, [1819] as a clade CI with strong support in both IQ-TREE and BEAST analyses. Coenophlebia is recovered as sister to Phantos, which is in turn recovered as sister to a clade comprising Siderone and Zaretis (Figs. 2 and 3). Consul is recovered as paraphyletic with moderate support in IQ-TREE due to the placement of C. excellens (Bates, 1864) outside of clade CII, but as monophyletic with moderate support in BEAST (clade CII, PP = 0.63). In both ML and Bayesian analyses, we recover with strong support a clade CIII comprising the genera Anaea Hübner, [1819], Fountainea as well as Polygrapha cyanea Salvin & Godman, 1868 and P. tyrianthina Salvin & Godman, 1868. In clade CIII, P. cyanea is found as sister to Anaea and Fountainea, the latter including P. tyrianthina as sister to F. centaurus with moderate support in both ML and BI (Figs. 2 and 3). The genus Memphis is recovered as monophyletic with four main clades CIV, CV, CVI and CVII inferred with high nodal support (Fig. 2). However, interspecific relationships within clade CVII are moderately to poorly supported in IQ-TREE, albeit more robust nodal support is obtained in the BEAST topology (Figs. 2 and 3). 3.2. Divergence time estimates and ancestral character state estimations The BEAST dating analysis based on a Yule model and a unique uncorrelated lognormal relaxed clock has a better marginal likelihood than the other ones based on the birth-death model and/or additional uncorrelated relaxed clocks, although divergence time estimates are very similar (Table 2). The preferred BEAST analysis (Fig. 3) recovers an origin of the crown Anaeini in the late Eocene ca. 41 Ma (95% CI = 30.3–53.8 Ma) (see Fig. S2 for the full chronogram). The BioGeoBEARS ancestral range estimation analysis with a null model receives a significantly lower likelihood (LnL = −466) than the one implementing dispersal rate scalers based on paleogeographic considerations (LnL = −462.76). Therefore, we present in Fig. 3 the results of the latter analysis (see Fig. S3 for more details). Under the DEC model, the ancestor of Anaeini originated in Central American lowlands. We estimate a major colonization event from Central American lowlands to the Chocó region during the Eocene to Oligocene transition in clade CI, followed by a reverse colonization of Central America in the Miocene (Fig. 3). We also estimate a long-distance dispersal from Central America to the Amazonian region in clade CI followed by a E.F.A. Toussaint, et al. Molecular Phylogenetics and Evolution 137 (2019) 86–103 92 F. centaurus M. neidhoeferi M. praxias M. hedemanni M. verticordia M. artacaena M. lemnos M. arginussa M. herbacea M. appias P. xenocrates M. xenocles M. juliani M. anna M. aureola M. polyxo M. dia M. hirta M. otrere M. lyceus M. pasibula M. falcata M. lorna M. lineata M. alberta M. cluvia M. iphis M. forreri M. oenomais M. basilia M. mor. boisduvali M. polycarmes M. mor. moruus M. mor. stheno M. phantes M. editha M. acidalia M. philumena M. cleomestra M. beatrix M. leonida M. laertes M. catinka M. nenia M. pseudiphis M. maria M. anassa M. phoebe M. grandis M. iphimedes M. boliviana M. cerealia M. montesino M. offa offa M. laura M. proserpina M. mora annetta M. mora mora M. mora orthesia M. aulica Hyp. clytemnestra Coe. archidona S. syntyche Ph. callidryas S. galanthis Z. syene Z. falcis Z. strigosus Z. pythagoras Z. hurin C. excellens C. electra C. fabius C. panariste P. cyanea A. troglodyta F. nob. rayoensis F. eurypile F. gly. cratais F. ryphea F. gly. glycerium F. halice F. nob. nobilis P. tyrianthina F. sosippus F. nessus F. nob. pacifica F. nob. titan M. glauce M. perenna M. pithyusa Geological Time (Ma) 45 40 35 30 25 20 15 10 5 0 PPMioceneEocene Oligocene Elevational shift Lowland (<1000m) Montane (>2000m) * 95% CI BEAST BEAST PP 0.95 Central Amer. Lowlands (L) Central Amer. Highlands (H) Caribbean Archipelago (R) Western Andes (W) Nearctic (N) Eastern Andes (E) Amazon and Guianas (A) Atlantic (T) GAARlandia land bridge Pozo Emb. Pebas Wetlands Acre System Proto-Caribbean Seaway closure Ph. opalina Z. itylus Z. itys Z. elianahenrichae Z. isidora Z. mirandahenrichae Z. ellops Z. crawfordhillii Z. delassisei A. aidea A. andria 53.8 Ma 0.93 0.85 0.78 0.63 0.52 * * * * TS5TS4TS3TS2TS1 TS6 * * * ** * * * * * ** * * * ** 0.91 * * * * * * * * 0.87 * * 0.91 * * * ** * * 0.83 * * 0.5 * * 0.73 0.82 0.73 * * * * * 0.86 0.72 I II III IV V VI VII VIII A B Fig. 3. Divergence time estimates and historical biogeography of Anaeini leafwing butterflies. BEAST chronogram presenting the phylogenetic relationships, median ages and 95% credibility intervals among Anaeini, as inferred under a Yule model with a unique clock and best-fit partitioning scheme. The Bayesian posterior probabilities are given, with asterisks corresponding to PP ≥ 0.95, and unlabeled nodes to PP < 0.95 (the exact PP of major nodes with PP < 0.95 are given). Current geographic and altitudinal distributions of each species are provided on the right side of the figure. The most likely ancestral range for each node is given based on the results of the DEC model as estimated in BioGeoBEARS. Results of the altitudinal DEC model are given at the root and when a shift occurred. All daughter nodes following an altitudinal shift have the same state. Shifts in elevation are highlighted with triangles of the color of the state. A picture of Memphis anassa is presented (credit: Andrew Neild). E.F.A. Toussaint, et al. Molecular Phylogenetics and Evolution 137 (2019) 86–103 93 reverse colonization to the Chocó region in the Miocene. In clade CIII, the colonization of Eastern Andes from Central America is followed by a reverse colonization back to Central America in the Miocene (Fig. 3). Further dispersal events allowed the colonization of Central American highlands, Nearctic region and of Eastern and Western Andes in the late Miocene. In clade CIV, the Caribbean archipelago was colonized out of Central America in the Miocene. We estimate a colonization of the Amazonian region from Central America followed by a reverse colonization of the Chocó region in the early Miocene between clades CIV and CV. The colonization of the Chocó region is followed by dispersal into the Andes and back to the Amazonian region in clade CVII. The Atlantic region is mostly colonized in the Pliocene and Pleistocene from the Amazonian region. Multiple reverse colonization events from South America to Central America are estimated in clade CVII throughout the Miocene, Pliocene and Pleistocene (Fig. 3). Our DEC analyses significantly support lowland elevation (LnL = −170.3) as the most likely ancestral state for the altitudinal preference of the Anaeini ancestor, with premontane (LnL = −177.1) and montane (LnL = −178.0) elevations receiving lower likelihood scores. We recover several late Miocene shifts towards premontane elevation in clades CIII and CVII (Fig. 3). The distribution of species at montane elevation is inferred as the result of very recent range expansions. The ordering MalpighialesPiperales-Laurales receives a DIC = 1050.1329 (mean deviance across samples Dbar = 871.6413, mean parameter values from the posterior sample Dhat = 693.1496, effective number of parameters of the model pD = 178.4917), and the ordering Malpighiales-Laurales-Piperales receives a DIC = 1050.4235 (Dbar = 869.9298, Dhat = 689.4360, pD = 180.4938). The results of the ancestral host plant preference optimization using the ordering with the best DIC are given in Fig. 5. We recover Malpighiales as the ancestral host plant of the tribe, with a shift to Piperales in Consul (clade CII*). We also recover a shift from Malpighiales to Piperales in clade CVII (Fig. 5). Three late Neogene shifts from Piperales to Laurales are also inferred within Memphis (clade CVII). 3.3. Diversification analyses Regardless of the prior number of rate shift prior specified in the BAMM analyses, all rate shift configurations among the best credible configuration set for all analyses include a shift located on the node following the crown of clade CVII in Memphis in the late Miocene, corresponding to a net increase in speciation rate compared to the rest of the tribe (Table 3,Fig. 5). Overall, the net increase in speciation rate in Memphis is recovered in all BAMM best shift configurations, as well as in all alternative shift configurations. Other rate shifts are not recovered systematically across analyses. Apart from the speciation rate increase inferred in Memphis, we recover a somewhat constant background speciation rate through time, both for this specific clade and other Table 2 Divergence time estimates estimated in different BEAST analyses. Tree model Clock model MLE SS MLE PS Crown Anaeini A1 birth-death 1 ULRC −25233.038 −25232.540 40.613 (29.280–53.055) A2 Yule 1 ULRC −24972.673 −25078.023 41.408 (30.335–53.946) A3 birth-death 2 ULRC −25185.540 −25185.822 41.609 (30.869–53.085) A4 Yule 2 ULRC −25187.276 −25186.645 42.079 (31.349–53.690) A5 birth-death 8 ULRC −25226.000 −25224.090 41.034 (29.223–52.929) A6 Yule 8 ULRC −25227.394 −25227.095 41.771 (30.763–53.851) Notes: URLC, uncorrelated lognormal relaxed clock(s); MLE, marginal likelihood estimate based on the analysis of pathLikelihood.delta using either stepping-stone sampling (SS) or path sampling (PS). Table 3 Results of the BAMM analyses. Prior nb. Shifts ESS nb. shifts ESS LnL Nb. Config. Best Config. Shift Location 0.1 1162.694 813.2825 9 (7, 1 shift/1, 0 shift/1, 2 shifts 1 shift (f = 0.30) Memphis 0.5 2931.252 2120.345 9 (6, 1 shift/1, 0 shift/2, 2 shifts 1 shift (f = 0.29) Memphis 1 3856.962 2695.392 8 (6, 1 shift/1, 0 shift/1, 2 shifts 1 shift (f = 0.35) Memphis 2 3220.482 3518.893 9 (6, 1 shift/1, 0 shift/2, 2 shifts 1 shift (f = 0.33) Memphis 5 2828.662 4129.17 5 (4, 1 shift/1, 0 shift) 1 shift (f = 0.36) Memphis 10 3128.869 3911.6 5 (4, 1 shift/1, 0 shift) 1 shift (f = 0.37) Memphis Notes: Prior nb. Shifts, prior on the expectedNumberOfShift parameter; ESS, effective sample size; LnL, log-likelihood; Nb. config., number of shift configurations in the credibility set; Best config., highest probability shift configuration in the credibility set. Table 4 Results of the MuSSE analyses of diversification linked to host plant preference. Df lnLik AIC ChiSq Pr(> |Chi|) minimal 3 −337.99 681.97 – – all.lambda.free 5 −326.86 663.72 22.253 0.000 *** all.mu.free 5 −336.01 682.02 3.949 0.139 all.q.free 8 −331.22 678.44 13.535 0.019 * all.lambda.mu.free 7 −326.70 667.39 22.58 0.000 *** all.lambda.q.free 10 −319.56 659.11 36.861 0.000 *** all.mu.q.free 10 −327.66 675.33 20.647 0.004 ** all.lambda.mu.q.free 12 −318.94 661.87 38.102 0.000 *** lambda1.free 4 −326.97 661.93 22.041 0.000 *** mu1.free 4 −336.05 680.10 3.872 0.049 * q1.free 7 −331.55 677.09 12.879 0.012 * lambda1mu1.free 5 −326.97 663.93 22.041 0.000 *** lambda1q1.free 8 −319.59 655.17 36.803 0.000 *** mu1q1.free 8 −327.73 671.46 20.508 0.001 ** lambda1mu1q1.free 9 −319.58 657.17 36.804 0.000 *** lambda2.free 4 −335.40 678.80 5.169 0.023 * mu2.free 4 −337.96 683.93 0.043 0.836 q2.free 7 −334.38 682.77 7.207 0.125 lambda2mu2.free 5 −334.78 679.57 6.403 0.041 * lambda2q2.free 8 −320.23 656.46 35.513 0.000 *** mu2q2.free 8 −333.70 683.40 8.569 0.128 lambda2mu2q2.free 9 −320.23 658.46 35.512 0.000 *** lambda3.free 4 −331.00 670.00 13.975 0.000 *** mu3.free 4 −336.10 680.19 3.778 0.052 . q3.free 7 −331.22 676.44 13.535 0.009 ** lambda3mu3.free 5 −331.00 672.00 13.977 0.001 *** lambda3q3.free 8 −319.73 655.47 36.503 0.000 *** mu3q3.free 8 −329.31 674.61 17.359 0.004 ** lambda3mu3q3.free 9 −319.73 657.47 36.503 0.000 *** Notes: lambda, speciation rate; mu, extinction rate; q, transition rate; Df, degrees of freedom; lnLik, log-likelihood. 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