Molecular Phylogenetics and Evolution Hidden Diversity of Forest

Molecular Phylogenetics and Evolution 124 (2018) 16–26

Contents lists available at ScienceDirect

Molecular Phylogenetics and Evolution

journal homepage: www.elsevier.com/locate/ympev

Hidden diversity of forest birds in Madagascar revealed using integrative T taxonomy ⁎ Jane L. Youngera, , Lynika Stroziera, J. Dylan Maddoxb,c, Árpád S. Nyárid, Matthew T. Bonﬁttoa, Marie J. Raherilalaoe,f, Steven M. Goodmanb,e, Sushma Reddya a Department of Biology, Loyola University Chicago, 1032 W. Sheridan Road, Chicago, IL 60660, USA b Field Museum of Natural History, 1400 S. Lake Shore Drive, Chicago, IL 60605, USA c Environmental Sciences, American Public University System, Charles Town, WV 25414, USA d Department of Ecology and Evolutionary Biology, The University of Tennessee, 569 Dabney Hall, Knoxville, TN 37996, USA e Association Vahatra, BP 3972, Antananarivo 101, Madagascar f Mention Zoology and Animal Biodiversity, University of Antananarivo, BP 906, Antananarivo 101, Madagascar

ARTICLE INFO ABSTRACT

Keywords: Madagascar is renowned as a global biodiversity hotspot with high levels of microendemism. However, there are New species few molecular phylogenetic studies of Malagasy birds, particularly for forest-dwelling species, signifying a Species delimitation substantial gap in current measures of species diversity in the absence of genetic data. We evaluated species Phylogeography limits and explored patterns of diversification within the genus Newtonia (Family Vangidae), a group of forest- Phylogenetics dwelling songbirds endemic to Madagascar. Our modern systematics approach combined genomic, morpho- Songbirds metric, and ecological niche data to analyze the evolutionary history of the group. Our integrative analysis Passerines uncovered hidden species-level diversity within N. amphichroa, with two deeply divergent and morphologically distinct lineages isolated in different regions of humid forest. We describe the southern lineage as a new species. Conversely, N. brunneicauda, which we initially hypothesized may harbor cryptic diversity owing to its large distribution spanning a range of habitats, was found to have no distinct lineages and shared haplotypes across much of its distribution. The contrasting diversification patterns between Newtonia lineages may be the result of their elevational tolerances. Newtonia brunneicauda has a broad habitat tolerance and elevational range that appears to have facilitated population expansion and gene flow across the island, limiting opportunities for diversification. On the other hand, N. amphichroa is found predominantly in mid-elevation and montane humid forests, a restriction that appears to have promoted speciation associated with climatic fluctuations during the Pleistocene. Our findings indicate that species diversity of Malagasy forest-dwelling birds may be greater than currently recognized, suggesting an urgent need for further studies to quantify biodiversity in Madagascar’s rapidly disappearing native forests.

1. Introduction Phylogeographic studies of Malagasy avifauna are few, with no published genetic data for nearly half of the endemic species (Reddy, Madagascar is renowned as a global biodiversity hotspot (Myers 2014). Since species-level diversity is frequently underestimated in the et al., 2000), with a largely endemic biota that evolved over its esti- absence of genetic analysis (Yoder et al., 2005), the lack of phylogeo- mated 88 million years of geographic isolation (de Wit, 2003; Storey graphic studies of Malagasy forest-dwelling bird taxa signifies a po- et al., 1995). The island is home to many unique evolutionary lineages tential gap in our understanding of Madagascar’s biodiversity. Under- with high levels of microendemism, attributable to a broad diversity of estimates of biodiversity are particularly concerning in light of ongoing habitats separated by steep environmental gradients, and climatic forest fragmentation in Madagascar (Harper et al., 2007). Modern fluctuations experienced throughout its period of isolation (Vences systematic tools applied to other groups in Madagascar have uncovered et al., 2009; Wilmé et al., 2006). As such, Madagascar is fascinating to cryptic speciation and diversification patterns in terrestrial mammals evolutionary biologists and has been described as “a model region of (Everson et al., 2016; Hotaling et al., 2016), volant mammals (Christidis species diversification” (Vences et al., 2009). et al., 2014), reptiles (Florio et al., 2012), and amphibians (Brown et al.,

⁎ Corresponding author. E-mail address: [email protected] (J.L. Younger). https://doi.org/10.1016/j.ympev.2018.02.017 Received 23 September 2017; Received in revised form 15 January 2018; Accepted 15 February 2018 Available online 21 February 2018 1055-7903/ © 2018 Elsevier Inc. All rights reserved. J.L. Younger et al. Molecular Phylogenetics and Evolution 124 (2018) 16–26

2014). Our limited systematic knowledge of Malagasy bird taxa also re- presents a missing piece of the puzzle of the avian tree of life (Reddy, 2014). The few systematic studies of Malagasy birds have produced astounding findings, most prominently the discovery of the spectacular in situ radiation of the Malagasy Vangidae (Jønsson et al., 2012; Reddy et al., 2012). This monophyletic assemblage consists of at least 22 species, many of which were originally placed in other families, and is nearly as morphologically diverse as all passerines combined (Jønsson et al., 2012; Reddy et al., 2012; Yamagishi et al., 2001). Furthermore, a group of 11 species previously placed in three different families was found to represent another monophyletic avian assemblage endemic to Madagascar (Cibois et al., 2001), and now comprises the recently described family Bernieridae (Cibois et al., 2010). In light of recent phylogenetic discoveries and the ongoing deforestation of Madagascar (Harper et al., 2007), phylogenetic analysis of Madagascar’s unstudied avifauna, particularly forest-dependent Passeriformes, is of critical importance. In addition to systematic clarification, studies of avian diversification processes in biodiversity hotspots, such as Madagascar, may lead to new insights into how lineages respond to novel selective regimes and ecological opportunity over time, and help to identify traits that promote or constrain diversification. Several key diversification mechanisms have been proposed for Madagascar, based on biogeographic studies of primates, reptiles, and amphibians (Vences et al., 2009):

(1) According to the montane refugia mechanism, populations of a species that were widely distributed during glacial periods may have become isolated in the relatively cool montane forests during interglacials, leading to vicariant speciation (Raxworthy and Nussbaum, 1995; Wollenberg et al., 2008). (2) In the riverine barrier hypothesis, it is proposed that the formation of rivers may have divided previously continuous distributions, leading to vicariant divergence (Goodman and Ganzhorn, 2004; Fig. 1. Map of Madagascar showing simplified bioclimatic zones. Topography is depicted Pastorini et al., 2003). In Madagascar, rivers generally flow east or with gray shading, successively darker shades represent 500 m elevation gains. west from the Central Highlands, and the riverine barrier me- Bioclimatic zonation follows Schatz (2000). chanism is thought to be most applicable in the lowlands where rivers are at their widest. et al., 2005). Therefore, diversification patterns and levels of cryptic (3) The watershed mechanism proposes that during glacial (dry) per- speciation of forest-dependent taxa are largely unknown, and these iods the lowlands were largely arid, with gallery forest habitat re- previous studies are not appropriate to test the diversification me- stricted to the vicinity of rivers, and different organisms used these chanisms outlined above. corridors to reach more mesic conditions at higher elevations The genus Newtonia is a group of small, forest-dwelling songbirds (Wilmé et al., 2006). For rivers with low source elevations, this may endemic to Madagascar. Newtonia were originally classified as either have resulted in dispersal barriers to more upland habitats and Old World warblers (Sylviidae) or flycatchers (Muscicapidae), but are isolation. now known to belong to the Vangidae radiation (Reddy et al., 2012; (4) In the ecogeographic constraint mechanism, it is proposed that the Yamagishi et al., 2001). The current taxonomy delineates four species. abrupt bioclimatic transition between the humid east and arid west Two species, N. amphichroa and N. brunneicauda, have widespread facilitated ecologically mediated speciation, with niche divergence distributions and co-occur across several distinct forested habitats occurring across the ecotone (Vences et al., 2009; Yoder and (Fig. 1; Goodman and Raherilalao, 2013; Hawkins and Sartain, 2013). Heckman, 2006). Following initial adaptive divergence, further The other two species, N. fanovanae and N. archboldi, have restricted diversification could have proceeded within the eastern and wes- distributions in the eastern humid forests and southern and south- tern bioclimatic zones. western spiny bush formations, respectively (Hawkins and Sartain, (5) In general, ecologically mediated speciation is likely to have played 2013). The genus is morphologically conserved with two of the species a role on Madagascar, with niche divergence occurring as a result of (N. brunneicauda and N. amphichroa)difficult to differentiate in the adaptation to differing habitat types separated by steep environ- field. In groups with low morphological variation, species-level di- mental gradients (Raxworthy et al., 2008). versity is easily underestimated and genetic analysis may unveil cryptic species (Goodman et al., 2011; Weisrock et al., 2010; Yoder et al., Numerous studies have explored the applicability of these diversi- 2005). Hence, we consider the presence of cryptic forms within what is fication mechanisms to Madagascar’s terrestrial vertebrate lineages, currently referred to as N. brunneicauda to be a distinct possibility, including mammals (Weyeneth et al., 2010; Yoder et al., 2016), reptiles owing to its large distribution spanning a diverse range of habitats, (Florio et al., 2012), and amphibians (Brown et al., 2014). However, the from the southern spiny bush to the eastern and northern humid forests roles of these mechanisms in generating avian biodiversity on Mada- (Goodman and Raherilalao, 2013; Hawkins and Sartain, 2013). gascar remain unexplored. The few phylogeographic studies of Mala- Given the distribution of Newtonia spp. across a diversity of habitat gasy birds have focused on species that are not exclusively forest-de- types, a range of elevations, and the full latitudinal and longitudinal pendent (Fuchs et al., 2016; Fuchs et al., 2013; Fuchs et al., 2007; breadths of Madagascar, the genus provides a good system to in- Warren et al., 2012; Warren et al., 2003; Warren et al., 2006; Warren vestigate biogeographic barriers and diversification mechanisms for

17 J.L. Younger et al. Molecular Phylogenetics and Evolution 124 (2018) 16–26

Fig. 2. Study sampling localities for N. brunneicauda, N. amphichroa, and N. archboldi. Madagascar’s topography is depicted with gray shading, successively darker shades represent 500 m elevation gains. The dashed line in the N. amphichroa panel indicates the phylogenetic split found in our analyses.

Malagasy forest-dwelling avifauna. We synthesized genomic, morpho- 2.2. Sequencing metric, and ecological niche data in an integrative systematics approach to assess species limits and explore patterns of diversification within the DNA was extracted from the 163 tissue samples using a QIAGEN genus. We sequenced mitochondrial genes, nuclear introns, and over DNeasy Blood and Tissue Kit following the manufacturer’s protocol. We 4000 ultra-conserved element (UCE) loci for N. amphichroa, N. brun- amplifi ed and sequenced two mitochondrial genes – NADH dehy- neicauda, and N. archboldi, and examined their phylogeographic pat- drogenase 3 (ND3) and cytochrome b (CYTB), and three nuclear introns terns by reconstructing phylogenies and population demographics. We – intron 11 of glyceraldehyde-3-phosphate dehydrogenase (GAPDH), used ecological niche models to examine patterns of diversification in intron 5 of fibrinogen beta chain (FGB), and intron 3 of muscle asso- relation to palaeoclimatic events. Finally, we quantified morphological ciated receptor tyrosine kinase (MUSK), using standard PCR and Sanger variation among genetically distinct lineages to assess species limits. sequencing methods with the primers listed in Supplementary Table 2. Outgroup sequences were retrieved from GenBank (Supplementary Table 1). Geneious 7.1.5 was used for alignment and sequences de- 2. Materials and methods posited in GenBank (ND3: MH005250 - MH005403; CYTB: MG990941 - MG991098; GAPDH: MH005673 - MH005786; FGB: MH005546 - 2.1. Taxon sampling MH005672; MUSK: MH005404 - MH005545). A subset of 23 individuals were selected for UCE genotyping Our sampling scheme encompassed the entire geographic range of (Supplementary Table 1). These were chosen such that each of the each of the three species of Newtonia examined herein (N. amphichroa, occupied bioclimatic zones as outlined in Fig. 1 and Vences et al. (2009) N. archboldi, and N. brunneicauda), with a focus on sequencing multiple were represented, along with all divergent lineages observed in our individuals from each of the bioclimatic zones of Madagascar (Schatz, analysis of the full Sanger dataset. UCE libraries were prepared fol- 2000; Vences et al., 2009) in order to detect patterns of intraspecific lowing previously described methods with minor modifications variation and possible dispersal barriers (Fig. 2). For detailed location (Faircloth et al., 2012; McCormack et al., 2013). Purified DNA was information (bioclimatic zone, locality, latitude, longitude) please see normalized to 40 ng/μL and fragmented via sonication (Covaris, Model Supplementary Table 1. Tissue samples were associated with vouchered #M220) to approximately 550 base pairs (bp). Samples were end-re- specimens held by the Field Museum of Natural History (FMNH, Chi- paired, A-tailed and Illumina TruSeqHT adapters were ligated using cago) and the Mention Zoologie Biologie Animale, Université d’Anta- TruSeq DNA HT Sample Prep Kit (Illumina) following the manu- nanarivo (UADBA, Antananarivo, formerly Département de Biologie facturer’s instructions. Libraries were then amplified by limited-cycle Animale). Our analysis did not include any N. fanovanae specimens (16–18) PCR using Kapa HiFi DNA polymerase (Kapa Biosystems), because of the rarity of specimens of this species. We genotyped 160 normalized to 62.5 ng/μL, pooled into three sets consisting of eight li- individuals of Newtonia, including specimens of N. amphichroa (n = 75), braries, and enriched for 5060 UCE loci using MYbaits capture kits N. brunneicauda (n = 73), and N. archboldi (n = 12) (Supplementary (Tetrapods 5K v1, MYcroarray) following the manufacturer’s instruc- Table 1). The elevational ranges of the sites where genotyped samples tions. Enriched libraries were quantified by qPCR (Kapa Library were collected were: 720–1625 m (mean = 1260, SD = 222), plus one Quantification Kit), normalized, and pair-end sequenced (2 × 300 bp) outlier at 50 m, for N. amphichroa;10–1600 m (mean = 430, SD = 574) on the Illumina MiSeq v3 platform. DNA sequence reads are archived for N. brunneicauda; and 20–225 m (mean = 70, SD = 63) for N. arch- on NCBI SRA (http://www.ncbi.nlm.nih.gov/sra/SRP133771). boldi. Three outgroup species of Vangidae were also included in the dataset (Leptopterus chabert, Falculea palliata, and Vanga curvirostris).

18 J.L. Younger et al. Molecular Phylogenetics and Evolution 124 (2018) 16–26

2.3. UCE processing for phylogenetic analysis calculating the average standard deviation of split frequencies every 5000 iterations until the value was approximately 0.01, and (2) by We used the PHYLUCE 1.5 package (Faircloth, 2015) to extract and using Tracer v1.6 (Rambaut and Drummond, 2007) to visualize the prepare UCE loci for phylogenetic analysis. The reads were trimmed to sampling traces and to check the effective sample size values (ESS), remove adapters and low-quality bases using Illumiprocessor with, in this case, all ESS values > 1000. The first 25% of the posterior (Faircloth, 2013), then assembled using Trinity 2.0.4 (Grabherr et al., samples of trees were discarded, and then the post burn-in posterior 2011). UCE loci were extracted from among the contigs using PHYLUCE distributions of both runs were used to compute a maximum clade and then aligned with MAFFT 7 (Katoh et al., 2002; Katoh and credibility (MCC) consensus tree. Standley, 2013). The alignments were trimmed using two approaches; the edge-trimming algorithm available in PHYLUCE, and the more 2.5. Divergence time estimation stringent Gblocks method (Castresana, 2000; Talavera and Castresana, 2007) which also internally trims the alignments. We refer to the re- To estimate divergence times among the major Newtonia lineages, sultant alignments as edge-trimmed and internal-trimmed alignments, we performed time-calibrated Bayesian phylogenetic analyses on respectively. We then generated data matrices of 50%, 75%, and 95% mtDNA sequences for the 23 taxa represented in the UCE dataset using completeness using PHYLUCE, where ‘completeness’ refers to the BEAST 2.4.4 (Bouckaert et al., 2014). The mtDNA sequences were used minimum number of taxa sequenced for a locus to be included in the because these were found to resolve the same topology with respect to matrix. the well-supported clades as the full Sanger sequencing and UCE datasets, and because estimates of divergence rates in birds are available 2.4. Phylogenetic analysis for these loci (Lerner et al., 2011; Weir and Schluter, 2008). The datasets were partitioned into ND3 and CYTB, with nucleotide substitu- 2.4.1. UCE dataset tion models specified as HKY and TVM, respectively, to reflect the We inferred maximum likelihood (ML) phylogenies for the UCE optimal models selected by PartitionFinder 2 (Lanfear et al., 2016). We datasets. To explore the effects of matrix completeness, trimming used the Yule tree prior with a strict molecular clock. Analyses were method, and partitioning scheme on the topology recovered, we per- conducted with two different clock calibration strategies: (1) using the formed multiple ML analyses using RAxML 8.2.7 (Stamatakis, 2014), divergence rate of CYTB for Passeriformes of 2.07% ( ± 0.20) per including: unpartitioned concatenated analyses of 50%, 75%, and 95% million years (Weir and Schluter, 2008) as a reference rate (lognormal, complete datasets from edge-trimmed alignments; unpartitioned con- mean = 0.01035, SD = 0.05); and (2) using the 95% HPD for the catenated analyses of 75% and 95% complete datasets from internal- substitution rates estimated for ND3 and CYTB for Hawaiian honey- trimmed alignments; partitioned analysis of the 75% complete edge- creepers (Lerner et al., 2011) (ND3: lognormal, mean = 0.024, trimmed dataset using a partitioning scheme suggested by Parti- SD = 0.09; CYTB: lognormal, mean = 0.014, SD = 0.05). Two in- tionFinder 2 (Lanfear et al., 2014; Lanfear et al., 2016); and an analysis dependent analyses, from different random number seeds, were per- of the 75% complete edge-trimmed dataset partitioned by locus. For formed for each calibration scenario to ensure reproducibility of the each analysis, we conducted rapid bootstrapping analysis and a search posterior distributions (four analyses in total). The MCMCs were run for for the best-scoring ML tree in a single program run, using the MRE- 150 million generations and convergence of the posteriors confirmed based bootstopping criterion (Pattengale et al., 2010) to ascertain when using Tracer v1.6 (Rambaut and Drummond, 2007). A maximum clade sufficient bootstrap replicates had been generated. All searches were credibility tree with mean node heights was estimated from each pos- conducted under the GTR GAMMA site-rate substitution model, as the terior after removing the first 10% of samples as burn-in. most suitable model for nucleotide data available in RAxML. We also inferred a phylogeny under the multispecies coalescent with 2.6. Species delimitation a subset of the most informative UCE loci in the 75% complete edge- trimmed dataset. Gene-tree based coalescent methods have been shown We used a multi-species coalescent-based approach to test different to have reduced accuracy when poorly resolved gene trees are included, models of species delimitation within a Bayesian framework, as im- which can result from using loci with low phylogenetic signal (Gatesy plemented in BPP v3.1 (Yang, 2015). We used the joint species deli- and Springer, 2014; Meiklejohn et al., 2016; Xi et al., 2015). We mitation and species tree analysis in BPP to test if the clades in our therefore selected the 25% of UCE loci with the greatest number of phylogenetic analyses were statistically significant to be considered parsimony informative sites, a cut-off based on the findings of Hosner distinct lineages. There were four major clades that were consistent et al. (2016). This subset contained 1041 loci with ≥26 parsimony across combined and single gene analyses (see Section 3), therefore we informative sites each. A gene tree was estimated for each of these loci assigned individuals to hypothesized populations/species based on this with 100 ML searches under GTR GAMMA using RAxML, and these clade membership and used the five gene Sanger dataset for the BPP were then reconciled using ASTRAL-II 4.10.12 with default settings analysis. For population size parameters, we assigned the gamma prior (Mirarab and Warnow, 2015). G (2, 1000), with mean 2/2000 = 0.001. We ran each analysis at least twice to confirm consistency between runs. Each run was for 100,000 2.4.2. 5-gene Sanger dataset samples, sampling frequency was five, and the burn-in was set to We conducted multiple ML analyses of the Sanger sequencing data, 20,000. including: a partitioned analysis of the introns and mitochondrial sequences using a partitioning scheme suggested by PartitionFinder 2 2.7. Intraspecific genetic analyses (Lanfear et al., 2014, 2016); an unpartitioned analysis for each gene separately (ND3, CYTB, GAPDH, FGB, and MUSK); and a partitioned To investigate trends in the effective population size of N. brunnei- analysis for the introns and mitochondrial sequences including only the cauda we used the extended Bayesian skyline plot (EBSP) method in 23 taxa that were sequenced for UCE loci. Analyses were conducted in BEAST 2.4.4 (Bouckaert et al., 2014; Heled and Drummond, 2008). Our RAxML using the same strategy as for the UCE analyses. UCE dataset contained too few individuals for skyline analysis, there- We performed partitioned Bayesian analyses of the concatenated fore the full Sanger sequencing dataset for N. brunneicauda was used (73 intron and mitochondrial sequences with MrBayes 3.2 (Ronquist et al., taxa), and partitioned into ND3, CYTB, MUSK, FGB and GAPDH, with 2012). Two independent runs with one cold and two heated chains substitution models specified as per PartitionFinder 2 (Lanfear et al., were run for 40 million generations, with sampling every 500 genera- 2016). A strict clock model was calibrated using Weir and Schulter’s tions. We assessed convergence of the posterior distributions by (1) (2008) estimate of the divergence rate of CYTB for Passeriformes

19 J.L. Younger et al. Molecular Phylogenetics and Evolution 124 (2018) 16–26

(2.07% ± 0.20 per million years). The MCMC was run for 150 million Supplementary Table 4. Wing and tail lengths were measured with a generations and convergence of the posterior confirmed using Tracer wing rule to an accuracy of 1 mm, all other measurements were taken v1.6 (Rambaut and Drummond, 2007). Attempted analyses of the two with Mitutoyo Digital Calipers to an accuracy of 0.01 mm. All mea- N. amphichroa clades failed to converge, possibly because the smaller surements were repeated three times, checked for outliers (by con- sample sizes of these datasets did not contain enough demographic firming that all measurements were within one standard deviation), and signal to converge on a result. Three independent analyses of the N. then averaged. The summary statistics of these measurements for each brunneicauda dataset with different random number seeds were per- of the four clades are given in Supplementary Table 4. We log-trans- formed to ensure reproducibility of the posterior distribution. The po- formed and standardized all measurements and conducted a principal pulation size parameter of the demographic model (Ne*tau) was con- components analysis (PCA). We then conducted a MANOVA to test for verted to effective population size (Ne) by dividing the parameter by statistical differences in the centroids of each group. Additionally, we generation length (tau), which we approximate as four years (Ricklefs, conducted univariate analyses to examine the differences across vari- 2006). It should be noted that the estimate of generation length only ables in the two N. amphichroa clades (see below). We used R for all affects the absolute values of Ne and has no bearing on either the timing statistical analyses. or magnitude of the abundance increase reported. To examine mitochondrial patterns of intraspecific genetic variation we also con- 3. Results structed median-joining haplotype networks for CYTB sequences for N. amphichroa and N. brunneicauda using PopArt (Leigh, 2015). 3.1. Sequence capture of UCE loci

2.8. Ecological niche modeling After removal of adapters, low quality bases, and unpaired reads, an average of 329 million bp of sequence per individual remained We used all the unique latitude/longitude combinations for the N. (132–622 million bp). These reads were assembled into an average of amphichroa (n = 27) and N. brunneicauda (n = 37) individuals in our 11,457 contigs per individual, with a mean contig length of 719 bp. An genetic dataset as occurrence data (Supplementary Table 1). Only ge- average of 4075 UCE loci were recovered per individual (3950–4296), netically identified specimens were used, because our genotyping un- with 4942 UCE loci recovered across all taxa. The edge-trimmed and covered several instances of species misidentification within museum concatenated alignment was 4,960,021 bp in length, consisting of 4905 collections, leading to concerns that unverified occurrence records loci with a mean locus length of 1011 bp (95%CI: 5.83). Each locus had could confound data on species’ distributions. sequences for an average of 19 taxa. The 50%, 75%, and 95% data Bioclimatic variables for Madagascar were used to summarize as- matrices contained 4786, 4164, and 1892 loci, respectively. The 75% pects of temperature and precipitation from the latter half of the 20th complete data matrix, which we used for the majority of our analyses, century (Hijmans et al., 2005), as well as for the Last Glacial Maximum was 4,288,201 bp in length, and contained 81,728 parsimony in- (LGM; ∼21,000 years BP; under both Community Climate System formative sites (an average of 19.63 per locus). Model (CCSM) and Model for Interdisciplinary Research on Climate (MIROC) scenarios). We used bioclimatic GIS layers (http://www. 3.2. Phylogenetic relationships within Newtonia worldclim.org) at a spatial resolution of 2.5 arc-minutes. To account for dimensionality across environmental spaces and time scales, we Our phylogenetic analyses converged on a strongly supported to- used a subset of five of the 19 layers that showed highest relative pology for Newtonia that confirmed monophyly of N. amphichroa, N. contribution towards the models and were in common between these brunneicauda, and N. archboldi, and placed N. archboldi as sister to N. two species: isothermality (Bio3), temperature seasonality (Bio4), mean amphichroa and N. brunneicauda (Fig. 3). Within N. amphichroa there temperature of coldest quarter (Bio11), annual precipitation (Bio12), was a clear division into two well-supported, reciprocally monophyletic and precipitation seasonality (Bio15). We used MaxEnt v.3.3.3 (Phillips clades (Fig. 3), corresponding to a latitudinal break between southern et al., 2006) setting aside 25% of occurrences for model testing (six for and central/northern Madagascar (indicated by a dashed line in Fig. 2). N. amphichroa; nine for N. brunneicauda) and using standard para- The southern N. amphichroa clade was restricted to the area below 22°S, meters. The spatial extent of our model training was kept at the level of whereas members of the central/northern clade were found north of the entire island, such that layers were clipped within a rectangle 20°S. Within the N. brunneicauda clade the divergences were shallow, ranging from 42°20′E/10°45′S to 51°20′E/26°45′S. Models were run poorly supported, and inconsistent across analyses, with no evidence using climatic variables for the present time frame and then projected for well-supported phylogenetic splits associated with geography. These onto LGM past conditions (CCSM and MIROC scenarios). We applied a patterns were consistent between analyses of the 4164 UCE loci and the threshold of 10% omission of training presences to the continuous full Sanger dataset (Fig. 3a and b). model outputs, corresponding to the MaxEnt probability value at which The major clades in the topology recovered from ML analysis of the 10% of the training data were predicted as absent. To illustrate the UCE dataset were robust to trimming strategy, matrix completeness, variation of suitability within the area of predicted presence under this and partitioning scheme. The species tree recovered by ASTRAL-II for threshold, the range of MaxEnt probability values was divided further the 1041 most informative UCE loci supported the same topology and into four categories of suitability. had a normalized quartet score of 0.72 (Supplementary Fig. 1). Our analyses of the individual introns and mitochondrial genes were all 2.9. Morphological variation compatible with this topology, but less well resolved. A ML analysis of the introns and mitochondrial genes for the 23 taxa in the UCE dataset We measured Newtonia skin specimens at the Field Museum of resolved the same overall topology, but with decreased support and Natural History to examine morphological variation. These analyses resolution compared to the phylogenies estimated using UCE data were limited to individuals for which we also had genetic data (Supplementary Fig. 2). (n = 33), in order to avoid potential confounding effects of mis- Our estimates of lineage divergence times within Newtonia indicated identified specimens. One of us (MB), took standard linear measure- that N. archboldi split from N. amphichroa and N. brunneicauda ca. ments of bill length from nares (BL), bill length to tip (BLT), bill width 4.04 Ma, followed by the divergence of N. amphichroa and N. brunnei- at nares (BW), bill depth at nares (BD), tarsus length (TL), tarsus width cauda ca. 2.81 Ma and, finally, the division of N. amphichroa into (TW), hallux length (HL), tail length (Tail), and wing length (WL). southern and northern clades (Figs. 2 and 3) approximately These measurements followed the methods of Baldwin et al. (1931) 820,000 years ago (Table 1). These estimates are based on substitute with further details, including plate numbers, available in rates in Hawaiian honeycreepers (Lerner et al., 2011), which are small

20 J.L. Younger et al. Molecular Phylogenetics and Evolution 124 (2018) 16–26

Fig. 3. Phylogenetic relationships of Newtonia. Maximum-likelihood trees of (A) 4164 concatenated UCE loci (4,288,201 bp), and (B) a partitioned analysis of two mitochondrial genes (ND3, CYTB) and three nuclear introns (GAPDH, FGB, MUSK). Support values are shown for nodes that received > 70% bootstrap support, with Bayesian posterior probabilities also indicated for (B), where * indicates 1.0. Triangles in (B) indicate tips that were also included in the UCE dataset. ML trees with tip labels and all branch support values are included in the supplementary material (Supplementary Figs. 3 and 4). Taxa are colored by their general region of collection in Madagascar, where green is southern (including the southern subarid zone and southern part of the eastern humid forest), blue is the western dry deciduous forest, purple is the northeastern humid forest, orange is the central sector of the eastern humid forest, and gray are regions where specimens were not collected. For details on specimen localities including latitudes and longitudes please refer to Supplementary Table 1. (For interpretation of the references to colour in this ﬁgure legend, the reader is referred to the web version of this article.)

Table 1 Table 2 Estimated timing of divergence events. Median estimates for the time to the most recent Comparison of species delimitation models for Newtonia using BPP. common ancestor in millions of years with the 95% highest posterior density interval shown in brackets. Analyses were calibrated using the substitution rates in Lerner et al. Rank Model Number of Posterior probability (2011). For comparison, Supplementary Table 1 shows estimates using the Weir and species Schluter (2008) rate. 1 Split N. amphichroa 4 0.972 Lineage divergence Timing estimate (Ma) 2 Lump all Newtonia 1 0.02728 3 Lump N. amphichroa/N. 2 0.00071 Newtonia and Vanga curvirostris 4.51 (3.79–5.31) brunneicauda N. archboldi and N. amphichroa/N. brunneicauda 4.04 (3.37–4.75) 4 Current taxonomy 3 0.00001 N. amphichroa and N. brunneicauda 2.81 (2.28–3.37) N. amphichroa – southern and central/northern clades 0.820 (0.586–1.10) N. amphichroa – central and northern clades (mtDNA) 0.244 (0.127–0.383) sharing of haplotypes among these regions (Supplementary Fig. 5). Our Bayesian phylogenetic analysis also recovered the same three mitochondrial clades (branch support = 1, 0.86) and placed the diver- passerine birds that are part of an adaptive radiation. We also estimated gence of the northern and central mitochondrial clades at 244 ka (95% lineage divergence times using the often-cited calibration of Weir and HPD: 0.127–0.383; Table 1). The recovery of two nuclear and three Schluter (2008) for all Passeriformes, which yielded slightly older es- mitochondrial clades suggests incomplete sorting of the nuclear timates (Supplementary Table 3). lineages, which is unsurprising given that the rate of lineage sorting is While the division within N. amphichroa was relatively recent, our expected to be four times faster for mitochondrial DNA (Pamilo and Bayesian analysis of alternate species delimitation models over- Nei, 1988). Overall, we find evidence for an initial divergence in the N. whelmingly rejected the current taxonomy (posterior prob- amphichroa complex between populations in the southeastern region vs. ability = 0.00001) and gave high support for the splitting of N. am- the rest of the humid forest in the mid-Pleistocene, followed by a more phichroa into two distinct groupings (posterior probability = 0.972; recent divergence between northern and central populations. Table 2). Networks of N. brunneicauda CYTB haplotypes did not indicate any clear genetic structure, with many haplotypes widespread across 3.3. Phylogeography Madagascar and shared among different biogeographic regions (Supplementary Fig. 6). For example, one haplotype was found in the A network analysis of CYTB haplotypes indicated a further division southeast humid forest, the Central Highlands, and the northeast humid of the central/northern N. amphichroa clade into two haplogroups, for a forest, with closely related haplotypes (one mutational difference) total of three evolutionary lineages (Supplementary Fig. 5). Each of the found in the northwest deciduous forest, the Northern Highlands, and three haplogroups was geographically distinct, with members of the the eastern humid forest (Supplementary Fig. 6b). The southern spiny southern lineage found below 22°S, the central lineage found between bush and the southern sector of the western deciduous forest appear to 16°S and 20°S, and the northern lineage north of 14.5°S. There was no be the most genetically distinct, but were not strongly supported as a

21 J.L. Younger et al. Molecular Phylogenetics and Evolution 124 (2018) 16–26

tneserP MSCCMGL CORIMMGL Newtonia amphichroa

0.7 > 0.5 - 0.7 0.3 - 0.5 0.1 - 0.3 absent Newtonia brunneicauda

Fig. 4. Ecological niche models for N. amphichroa and N. brunneicauda, demonstrating suitable habitat in the present and at the Last Glacial Maximum based on two alternate climate scenarios (CCSM and MIROC). Inset legend depicts ranges of suitability probability from lower (light green) to higher (dark blue). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) distinct clade in phylogenetic analyses. Together, the shallow phylo- the LGM and today, suggesting the spiny bush may have been occupied genetic divergences and the sharing of haplotypes across much of the by this species throughout recent geological time. This is further sup- species’ distribution suggest either ongoing gene flow across its range, ported by the networks, which showed the highest diversity of haplo- or a recent range expansion that has carried genetic variants into new types from the southern spiny bush (Supplementary Fig. 6b). regions. Our analysis of demographic history supports the latter, with evidence of a sustained period of population growth in N. brunneicauda 3.5. Morphological variation commencing around 400 ka, in the midst of Pleistocene climate fluctuations (Supplementary Fig. 7; Petit et al., 1999). The effective po- The PC analysis resulted in eight PCs of which PC1 encompassed pulation size increased approximately 10-fold over this period (Sup- 52.97%, PC2 13.53%, and PC3 11.96% of the variance (see plementary Fig. 7). Supplementary Table 5 for loadings). The remaining components each explained less than 1% of variance and were therefore not examined 3.4. Ecological niche modeling further. The three Newtonia spp. formed distinct clusters (Fig. 5). N. brunneicauda and N. amphichroa clearly differed in morphospace along Our ecological niche models for N. amphichroa and N. brunneicauda PC1, while N. brunneicauda and N. archboldi separated along PC2 both provided a good fit to the species’ known contemporary dis- (Fig. 5). The northern and southern clades of N. amphichroa also sepa- tributions (Goodman and Raherilalao, 2013; Hawkins and Sartain, rated along PC1 (Fig. 5). A box plot of PC1 scores show that all four 2013). Both climate models (CCSM and MIROC) indicated suitable groups have non-overlapping means and inter-quartile ranges (Sup- habitat for N. amphichroa spanning the eastern humid forest during the plementary Fig. 8). The MANOVA determined that the centroids of all LGM (Fig. 4). Since the LGM, the distribution of N. amphichroa has been four groups are significantly diff( erent p < 0.0001). fragmented into three disjunct regions, corresponding geographically with the mitochondrial N. amphichroa clades. 4. Discussion The area of suitable habitat for N. brunneicauda has expanded since the LGM, with new habitat availability in the west and northwest in- 4.1. Cryptic diversity within Newtonia dicated by both models, and in the northeast by the CCSM model (Fig. 4). Increase of suitable habitat could have facilitated a recent Our integrative approach has uncovered two deeply divergent range expansion in N. brunneicauda, and the evidence for an increase in lineages within N. amphichroa, which was previously regarded as effective population size coupled with the lack of phylogeographic monotypic (Clements et al., 2017; Hawkins and Sartain, 2013). These structure supports this scenario. The niche models for N. brunneicauda lineages are associated with distinct highland regions in eastern Ma- also indicated a high occurrence probability in the southwest both at dagascar, form reciprocally monophyletic clades in all of our analyses,

22 J.L. Younger et al. Molecular Phylogenetics and Evolution 124 (2018) 16–26

Fig. 5. Principal components analysis of morphometric comparisons across Newtonia. Biplot of PC1 versus PC2. Points indicate individuals in multivariate space with 95% confidence ellipses in shaded areas. Arrowed lines show direction and magnitude of the coefficients of each variable (abbreviations in text). Colors indicate species or distinct lineage: N. amphichroa northern clade in purple (n = 13), N. amphichroa southern clade in green (n = 7), N. brunneicauda in orange (n = 10), and N. archboldi in blue (n = 3). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) and are morphologically distinct. On the other hand, we found no 4.2. Diversification mechanisms evidence for genetically distinct lineages within N. brunneicauda, despite its occupation of a diversity of habitats and biogeographic zones, 4.2.1. Phylogeographic patterns and previous description of a subspecies (N. b. monticola; Salomonsen, N. amphichroa and N. brunneicauda shared a most recent common 1934). Contrary to our initial hypothesis that it may harbor cryptic ancestor ca. 2.81 Ma. While the reasons for the observed differences in species-level diversity, we conclude that N. brunneicauda is a wide- their subsequent diversification patterns are unknown, two factors that spread, eurytopic species that has recently expanded in range and po- may have contributed are their degrees of forest dependence, and their pulation size. respective elevational distributions. A study of forest usage found that The southern clade of N. amphichroa is sufficiently distinct to war- N. brunneicauda was present in forest fragments as small as 4 ha, rant recognition as a new species. While species delimitation using whereas N. amphichroa only occupied fragments of at least 52 ha genomic data alone is problematic (Sukumaran and Knowles, 2017), (Langrand and Wilmé, 1997). The restriction of N. amphichroa to larger the northern and southern N. amphichroa lineages are also morpholo- patches of forest is likely to restrict its movement around Madagascar, gically distinct, and taxonomic revision is therefore required. In Sup- and hence gene flow. N. brunneicauda has a wide elevational range, plement 2 we provide a full species description of Newtonia lavarambo spanning 10–1600 m in our dataset, with most frequent occurrence in sp. nov., detailing morphometric and plumage differences from N. am- lowland and mid elevation forests (mean = 430 m). On the other hand, phichroa. The distinctiveness of these two species should be considered N. amphichroa is found predominantly in mid elevation and montane in future conservation planning (Funk et al., 2012), and we -propose forests, with an elevational range of 720 to 1625 m (mean = 1260 m). that by conserving the full spectrum of genetic and morphological This restriction of N. amphichroa to a relatively narrow elevational variation, the evolutionary and adaptive potential of Newtonia could be range could have been a contributing factor in the divergence of N. maximized (D’Amen et al., 2013). lavarambo sp. nov, by restricting populations to fragments of favorable Madagascar covers only 0.01% of Earth’s land-surface area, yet is habitat. home to nearly 5% of the planet’s species-level biodiversity (Yoder Our results suggest that the divergence of N. amphichroa into et al., 2016). Despite this astonishing diversity, Madagascar’s avifauna northern and southern lineages occurred during the Pleistocene. has been described as species-poor for its size, at just over 200 species Throughout this period a common speciation mode in the tropics was (Goodman and Benstead, 2003). Our discovery of cryptic species-level intermittent altitudinal range shifts in response to climate oscillations diversity within Newtonia, coupled with a similar discovery within the (Hewitt, 2004). While the timing of Pleistocene climate fluctuations in Bernieridae (Block, 2012), suggests that the ‘true’ avian species richness Madagascar is not well documented (Hughen et al., 2004), there were of the island may only be revealed after more phylogeographic studies thought to be changes of > 4 °C (Burney et al., 2004), and during cooler are completed. Cryptic species-level diversity has been uncovered in periods the humid forest habitat preferred by N. amphichroa descended other Malagasy vertebrate taxa, including mouse lemurs (Hotaling slopes to lower elevations (Gasse and Van Campo, 1998; Wilmé and et al., 2016), tenrecs (Everson et al., 2016), chameleons (Florio et al., Goodman, 2003). The division between N. amphichroa sensu stricto and 2012), bats (Christidis et al., 2014), rodents (Carleton and Goodman, N. lavarambo sp. nov.,at20–22°S, falls in the region of a high plateau 2007), and frogs (Wollenberg et al., 2008). Given the alarming rates of connecting two mountain ranges to the north and south. The plateau deforestation on Madagascar (Harper et al., 2007), it is crucial that is > 1500 m in elevation and may have been uninhabitable by N. am- efforts to comprehend the full breadth of biodiversity of forest-dwelling phichroa during much of the Pleistocene if humid forest was shifted to birds continue. lower elevations, potentially acting as a dispersal barrier (Betsch,

23 J.L. Younger et al. Molecular Phylogenetics and Evolution 124 (2018) 16–26

2000). If populations were isolated on either side of this divide in mid- spanning both the western portion of the southern spiny bush, and the elevation habitat this may have led to vicariant speciation. Following southeastern littoral forest. The range of N. archboldi also spans two the transition into the warm Holocene, the now isolated populations major rivers – the Mangoky and Onilahy – suggesting that the diversi- could have shifted in distribution slightly to track the upward eleva- fication hypotheses (2) riverine barrier (Goodman and Ganzhorn, 2004; tional shift of preferred montane habitat. Pastorini et al., 2003) and (3) watershed (Wilmé et al., 2006) are un- In an alternative speciation scenario, the original zone of separation likely to have played a role in this system. for N. amphichroa may have been further south than the present division, and associated with the low-lying Menaharaka Divide, which 5. Concluding remarks drops to less than 900 m. During Pleistocene interglacials the montane humid forest habitat was located at greater elevations than today, and Many factors have been previously identified as drivers of diversi- N. amphichroa populations may have become isolated on either side of fication patterns in other groups in Madagascar (Vences et al., 2009), the low elevation divide, leading to vicariant speciation. Subsequent but the broad applicability of these for forest-dwelling birds is as yet periods of cooling may have then caused latitudinal distribution shifts, unclear. Our study of Newtonia has highlighted the possibility of further bringing the apparent separation zone between the lineages further hidden species-level diversity within the avifauna of Madagascar. Fu- north to its modern position. This second scenario is consistent with ture genetic studies will likely continue to expand the documented hypothesis (1) the montane refugia speciation mechanism (Raxworthy avian biodiversity. Our research also suggests that rates of micro- and Nussbaum, 1995; Wollenberg et al., 2008). endemism of forest-dwelling Malagasy birds may be greater than cur- Two other phylogeographic studies of Malagasy forest birds placed rently documented, suggesting an urgent need for further studies to in another adaptive radiation, the Family Bernieridae, also found evi- quantify biodiversity in Madagascar’s forests in order to implement dence for distinct clades within the eastern region. Bernieria mada- necessary conservation actions. gascariensis contains divergent clades to the north and south of 21°S (Block, 2012), coinciding with the division of N. amphichroa lineages. Xanthomixis zosterops also has divergent clades in this region, but the Data accessibility separation appears to be altitudinal rather than latitudinal (Block et al., 2015), and may be an example of ecologically mediated speciation The Illumina short reads are available from the NCBI sequence read (Raxworthy et al., 2008). archive (http://www.ncbi.nlm.nih.gov/SRP133771) and Sanger se- The broad elevational and habitat tolerance of N. brunneicauda may quences are available from GenBank (Accessions: have facilitated its gene flow and population expansion, with no ap- MH005250–MH005786 and MG990941–MG991098). parent dispersal barriers for the species. Extraordinarily, there is no genetic divergence between east and west Madagascar, even though Author contributions these regions are separated by an abrupt bioclimatic transition between the humid east and arid west that is thought to promote ecologically JY analyzed the data, interpreted the data, wrote the manuscript, mediated speciation (Vences et al., 2009; Yoder and Heckman, 2006). carried out bioinformatics, assisted with the new species description, While longitudinal dispersal across the island is unlikely for forest- and participated in designing the study. LS carried out molecular la- dwelling taxa now, it may have been possible throughout much of the boratory work and participated in interpreting the data. DM carried out Pleistocene, facilitated by wooded savanna habitat (Goodman and UCE library preparation and sequencing. AN conducted ecological Ganzhorn, 2004; Yoder et al., 2016). Our findings for N. brunneicauda niche modeling and participated in data interpretation. MB collected are congruent with those of the only two other phylogeographic studies morphometric data. MR collected genetic samples and participated in of widespread Malagasy bird species with broad habitat tolerance, Di- interpreting the data. SG wrote the species description, collected ge- crurus forficatus and Nesillas typica (Fuchs et al., 2016, 2013). For all netic samples, and participated in interpreting the data and conceiving three species, there was a lack of phylogeographic structure and evi- the study. SR conceived and designed the study, participated in ana- dence for population expansion, consistent with a lack of barriers to lyzing and interpreting the data, and assisted with the new species gene flow. Interestingly, N. brunneicauda can be considered a true description. All authors reviewed and commented on the manuscript. forest-dwelling species tolerant of certain levels of natural and anthropogenic perturbation, whereas D. forficatus and N. typica are able to Acknowledgements occupy human-modified environments. It appears that N. brunneicauda’s ability to tolerate small patches of forest (ca. 4 ha; Langrand and Funding: This work was supported by the National Science Wilmé, 1997) has facilitated gene flow to a similar extent as D. for- Foundation (DEB-1457624 awarded to SR); and the Pritzker Laboratory ficatus’ and N. typica’s ability to occupy degraded habitat. for Molecular Systematics and Evolution, operated with support from the Pritzker Foundation. 4.2.2. Interspecific diversification patterns We gratefully acknowledge the Field Museum of Natural History The evolutionary relationships among N. archboldi, N. amphichroa, and the Mention Zoology and Animal Biodiversity, University of and N. brunneicauda resolved by our phylogenomic analyses of 4164 Antananarivo for specimen loans. We thank David E. Willard and UCE loci confirmed those found in the six loci analysis of Jønsson et al. Thomas Gnoske for their help in the field, and Sarah Kurtis for her (2012), with greater support. Our analysis did not include any material assistance in the lab. Sylke Frahnert and Pascal Eckhoff of the Museum of N. fanovanae because of the rarity of the species. Originally described für Naturkunde, Berlin, kindly provided information on the type series from a single specimen collected in the central eastern humid forest, N. of Newtonia amphichroa. Finally, we are very grateful to the Field fanovanae was not seen for many years, until rediscovery in 1989 Museum of Natural History bird study group for their feedback on the (Evans, 1991; Goodman and Schulenberg, 1991). Future genotyping of manuscript, and to the two anonymous reviewers whose thoughtful N. fanovanae individuals, perhaps using toe pads, may yield new in- comments improved the final version. sights into the evolution of Newtonia. The mechanism of the divergence of N. archboldi from N. brunneicauda and N. amphichroa between 3.37 and 4.75 Ma is unclear. N. Appendix A. Supplementary material archboldi is sympatric across its range with N. brunneicauda and there is no evidence of a biogeographic barrier between the two. N. archboldi Supplementary data associated with this article can be found, in the consists of a single, well-supported clade, despite its distribution online version, at https://doi.org/10.1016/j.ympev.2018.02.017.

24 J.L. Younger et al. Molecular Phylogenetics and Evolution 124 (2018) 16–26

References genetic variation in the Mentocrex kioloides complex (Aves: Gruiformes: Rallidae) from Madagascar, with the description of a new species. Zootaxa 2776, 49–60. Goodman, S.M., Schulenberg, T.S., 1991. The rediscovery of the Red-tailed Newtonia Baldwin, S.P., Oberholser, H.C., Worley, L.G., 1931. Measurements of birds. Sci. Publ. Newtonia fanovanae in south-eastern Madagascar with notes on the natural history of – Cleveland Museum Nat. History 2, 1 165. the genus Newtonia. Bird Conservation International 1 (01), 33–45. Betsch, J-M., 2000. Types de spéciation chez quelques collemboles Symphypléones Grabherr, M.G., Haas, B.J., Yassour, M., Levin, J.Z., Thompson, D.A., Amit, I., et al., 2011. Sminthuridae (Aptérygotes) de Madagascar. In: Lourenço, W.R., Goodman, S.M. Full-length transcriptome assembly from RNA-Seq data without a reference genome. (Eds.), Diversity and Endemism in Madagascar. Société de Biogéographie, MNHN, Nat. Biotechnol. 29 (7), 644–652. – Paris, France, pp. 295 306. Harper, G.J., Steininger, M.K., Tucker, C.J., Juhn, D., Hawkins, F., 2007. Fifty years of Block, N., 2012. Cryptic diversity and phylogeography in the Bernieridae, an endemic deforestation and forest fragmentation in Madagascar. Environ. Conserv. 34 (04), Malagasy passerine radiation (PhD). University of Chicago, Chicago, USA. 325–333. Block, N., Goodman, S.M., Hackett, S.J., Bates, J.M., Raherilalao, M.J., 2015. Potential Hawkins, F., Sartain, A., 2013. Newtonia. In: Safford, R., Hawkins, F. (Eds.), The Birds of merger of ancient lineages in a passerine bird discovered based on evidence from Africa. Volume VIII: The Malagasy Region. Christopher Helm, London, UK, pp. fi – host-speci c ectoparasites. Ecol. Evol. 5 (17), 3743 3755. 802–807. Bouckaert, R., Heled, J., Kühnert, D., Vaughan, T., Wu, C.-H., Xie, D., et al., 2014. BEAST Heled, J., Drummond, A.J., 2008. Bayesian inference of population size history from 2: a software platform for Bayesian evolutionary analysis. PLoS Comput. Biol. 10 (4), multiple loci. BMC Evol. Biol. 8 (1), 289. e1003537. Hewitt, G., 2004. Genetic consequences of climatic oscillations in the Quaternary. Philos. Brown, J.L., Cameron, A., Yoder, A.D., Vences, M., 2014. A necessarily complex model to Trans. Royal Soc. London B: Biol. Sci. 359 (1442), 183–195. explain the biogeography of the amphibians and reptiles of Madagascar. Nat. Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P.G., Jarvis, A., 2005. Very high re- Commun. 5, 5046. solution interpolated climate surfaces for global land areas. Int. J. Climatol. 25 (15), Burney, D.A., Burney, L.P., Godfrey, L.R., Jungers, W.L., Goodman, S.M., Wright, H.T., 1965–1978. Jull, A.T., 2004. A chronology for late prehistoric Madagascar. J. Hum. Evol. 47 (1), Hosner, P.A., Faircloth, B.C., Glenn, T.C., Braun, E.L., Kimball, R.T., 2016. Avoiding – 25 63. missing data biases in phylogenomic inference: an empirical study in the landfowl Carleton, M.D., Goodman, S.M., 2007. A new species of the Eliurus majori complex (Aves: Galliformes). Mol. Biol. Evol. 33 (4), 1110–1125. (Rodentia: Muroidea: Nesomyidae) from south-central Madagascar, with remarks on Hotaling, S., Foley, M.E., Lawrence, N.M., Bocanegra, J., Blanco, M.B., Rasoloarison, R., – emergent species groupings in the genus Eliurus. Am. Mus. Novit. 3547, 1 21. et al., 2016. Species discovery and validation in a cryptic radiation of endangered Castresana, J., 2000. Selection of conserved blocks from multiple alignments for their use primates: coalescent-based species delimitation in Madagascar's mouse lemurs. Mol. – in phylogenetic analysis. Mol. Biol. Evol. 17 (4), 540 552. Ecol. 25 (9), 2029–2045. Christidis, L., Goodman, S.M., Naughton, K., Appleton, B., 2014. Insights into the evo- Hughen, K.A., Eglinton, T.I., Xu, L., Makou, M., 2004. Abrupt tropical vegetation response lution of a cryptic radiation of bats: dispersal and ecological radiation of Malagasy to rapid climate changes. Science 304 (5679), 1955–1959. Miniopterus (Chiroptera: Miniopteridae). PLoS ONE 9 (3), e92440. Jønsson, K.A., Fabre, P.-H., Fritz, S.A., Etienne, R.S., Ricklefs, R.E., Jørgensen, T.B., et al., Cibois, A., Normand, D., Gregory, S.M., Pasquet, E., 2010. Bernieridae (Aves: 2012. Ecological and evolutionary determinants for the adaptive radiation of the Passeriformes): a family-group name for the Malagasy sylvioid radiation. Zootaxa Madagascan vangas. Proc. Natl. Acad. Sci. 109 (17), 6620–6625. – 2554 (1), 65 68. Katoh, K., Misawa, K., Kuma, K.i., Miyata, T., 2002. MAFFT: a novel method for rapid Cibois, A., Slikas, B., Schulenberg, T.S., Pasquet, E., 2001. An endemic radiation of multiple sequence alignment based on fast Fourier transform. Nucleic Acids Res. 30 Malagasy songbirds is revealed by mitochondrial DNA sequence data. Evolution 55 (14), 3059–3066. – (6), 1198 1206. Katoh, K., Standley, D.M., 2013. MAFFT multiple sequence alignment software version 7: ff Clements, J.F., Schulenberg, T.S., Ili , M.J., Roberson, D., Fredericks, T.A., Sullivan, B.L., improvements in performance and usability. Mol. Biol. Evol. 30 (4), 772–780. Wood, C.L., 2017. The eBird/Clements checklist of birds of the world: v2016. Lanfear, R., Calcott, B., Kainer, D., Mayer, C., Stamatakis, A., 2014. Selecting optimal ’ D Amen, M., Zimmermann, N.E., Pearman, P.B., 2013. Conservation of phylogeographic partitioning schemes for phylogenomic datasets. BMC Evol. Biol. 14 (1), 82. – lineages under climate change. Glob. Ecol. Biogeogr. 22 (1), 93 104. Lanfear, R., Frandsen, P.B., Wright, A.M., Senfeld, T., Calcott, B., 2016. PartitionFinder 2: de Wit, M.J., 2003. Madagascar: heads it's a continent, tails it's an island. Annu. Rev. new methods for selecting partitioned models of evolution for molecular and mor- – Earth Planet. Sci. 31 (1), 213 248. phological phylogenetic analyses. Mol. Biol. Evol. 34, 772–773. Evans, M.I., 1991. The Red-tailed Newtonia Newtonia fanovanae in the Ambatovaky re- Langrand, O., Wilmé, L., 1997. Effects of forest fragmentation on extinction patterns of – serve, north-east Madagascar. Bird Conserv. Int. 1 (1), 47 52. the endemic avifauna on the Central High Plateau of Madagascar. In: Goodman, S.M., Everson, K.M., Soarimalala, V., Goodman, S.M., Olson, L.E., 2016. Multiple loci and Patterson, B.D. (Eds.), Natural Change and Human Impact in Madagascar. complete taxonomic sampling resolve the phylogeny and biogeographic history of Smithsonian Institution Press, Washington DC, USA. tenrecs (Mammalia: Tenrecidae) and reveal higher speciation rates in Madagascar's Leigh, J., 2015. PopArt. – humid forests. Syst. Biol. 65 (5), 890 909. Lerner, H.R., Meyer, M., James, H.F., Hofreiter, M., Fleischer, R.C., 2011. Multilocus Faircloth, B.C., 2013. illumiprocessor: a trimmomatic wrapper for parallel adapter and resolution of phylogeny and timescale in the extant adaptive radiation of Hawaiian quality trimming. honeycreepers. Curr. Biol. 21 (21), 1838–1844. Faircloth, B.C., 2015. PHYLUCE is a software package for the analysis of conserved McCormack, J.E., Harvey, M.G., Faircloth, B.C., Crawford, N.G., Glenn, T.C., Brumfield, – genomic loci. Bioinformatics 32, 786 788. R.T., 2013. A phylogeny of birds based on over 1,500 loci collected by target en- fi Faircloth, B.C., McCormack, J.E., Crawford, N.G., Harvey, M.G., Brum eld, R.T., Glenn, richment and high-throughput sequencing. PLoS ONE 8 (1), e54848. T.C., 2012. Ultraconserved elements anchor thousands of genetic markers spanning Meiklejohn, K.A., Faircloth, B.C., Glenn, T.C., Kimball, R.T., Braun, E.L., 2016. Analysis of – multiple evolutionary timescales. Syst. Biol. 61, 717 726. a rapid evolutionary radiation using ultraconserved elements: evidence for a bias in Florio, A., Ingram, C., Rakotondravony, H., Louis, E., Raxworthy, C., 2012. Detecting some multispecies coalescent methods. Syst. Biol. 65, 612–627. cryptic speciation in the widespread and morphologically conservative carpet cha- Mirarab, S., Warnow, T., 2015. ASTRAL-II: coalescent-based species tree estimation with – meleon (Furcifer lateralis) of Madagascar. J. Evol. Biol. 25 (7), 1399 1414. many hundreds of taxa and thousands of genes. Bioinformatics 31 (12), 44–52. Fuchs, J., Lemoine, D., Parra, J.L., Pons, J.-M., Raherilalao, M.J., Prys-Jones, R., et al., Myers, N., Mittermeier, R.A., Mittermeier, C.G., Da Fonseca, G.A., Kent, J., 2000. 2016. Long-distance dispersal and inter-island colonization across the western Biodiversity hotspots for conservation priorities. Nature 403 (6772), 853–858. fi Malagasy Region explain diversi cation in brush-warblers (Passeriformes: Nesillas). Pamilo, P., Nei, M., 1988. Relationships between gene trees and species trees. Mol. Biol. – Biol. J. Linn. Soc. 119 (4), 873 889. Evol. 5 (5), 568–583. Fuchs, J., Parra, J., Goodman, S.M., Raherilalao, M.J., Vanderwal, J., Bowie, R.C., 2013. Pastorini, J., Thalmann, U., Martin, R.D., 2003. A molecular approach to comparative Extending ecological niche models to the past 120,000 years corroborates the lack of phylogeography of extant Malagasy lemurs. Proc. Natl. Acad. Sci. 100 (10), fi strong phylogeographic structure in the Crested Drongo (Dicrurus for catus)on 5879–5884. – Madagascar. Biol. J. Linn. Soc. 108 (3), 658 676. Pattengale, N.D., Alipour, M., Bininda-Emonds, O.R., Moret, B.M., Stamatakis, A., 2010. Fuchs, J., Pons, J.-M., Pasquet, E., Raherilalao, M.J., Goodman, S.M., 2007. Geographical How many bootstrap replicates are necessary? J. Comput. Biol. 17 (3), 337–354. structure of genetic variation in the Malagasy Scops-Owl inferred from mitochondrial Petit, Jouzel, J., Raynaud, D., Barkov, N.I., Barnola, J.M., Basile, I., et al., 1999. Climate – sequence data. The Condor 109 (2), 408 418. and atmospheric history of the past 420,000 years from the Vostok ice core, Funk, W.C., McKay, J.K., Hohenlohe, P.A., Allendorf, F.W., 2012. Harnessing genomics Antarctica. Nature 399 (6735), 429–436. – for delineating conservation units. Trends Ecol. Evol. 27 (9), 489 496. Phillips, S.J., Anderson, R.P., Schapire, R.E., 2006. Maximum entropy modeling of species Gasse, F., Van Campo, E., 1998. A 40,000-yr pollen and diatom record from Lake geographic distributions. Ecol. Model. 190 (3), 231–259. – Tritrivakely, Madagascar, in the southern tropics. Quat. Res. 49 (3), 299 311. Rambaut, A., Drummond, A.J., 2007. Tracer v1. 4. Gatesy, J., Springer, M.S., 2014. Phylogenetic analysis at deep timescales: unreliable gene Raxworthy, C., Nussbaum, R., 1995. Systematics, speciation and biogeography of the trees, bypassed hidden support, and the coalescence/concatalescence conundrum. dwarf chameleons (Brookesia; Reptilia, Squamata, Chamaeleontidae) of northern – Mol. Phylogenet. Evol. 80, 231 266. Madagascar. J. Zool. 235 (4), 525–558. Goodman, S.M., Benstead, J.P., 2003. The Natural History of Madagascar. University of Raxworthy, C., Pearson, R., Zimkus, B., Reddy, S., Deo, A., Nussbaum, R., Ingram, C., Chicago Press, Chicago, USA. 2008. Continental speciation in the tropics: contrasting biogeographic patterns of Goodman, S.M., Ganzhorn, J.U., 2004. Biogeography of lemurs in the humid forests of divergence in the Uroplatus leaf-tailed gecko radiation of Madagascar. J. Zool. 275 Madagascar: the role of elevational distribution and rivers. J. Biogeogr. 31 (1), (4), 423–440. – 47 55. Reddy, S., 2014. What’s missing from avian global diversification analyses? Mol. Goodman, S.M., Raherilalao, M.J., 2013. Birds or the class Aves. In: Goodman, S.M., Phylogenet. Evol. 77, 159–165. Raherilalao, M.J. (Eds.), Atlas of Selected Land Vertebrates of Madagascar. Reddy, S., Driskell, A., Rabosky, D., Hackett, S., Schulenberg, T., 2012. Diversification Association Vahatra, Antananarivo, Madagascar. and the adaptive radiation of the vangas of Madagascar. Proc. Royal Soc. B: Biol. Sci. Goodman, S.M., Raherilalao, M.J., Block, N.L., 2011. Patterns of morphological and 279, 2062–2071.

25 J.L. Younger et al. Molecular Phylogenetics and Evolution 124 (2018) 16–26

Ricklefs, R.E., 2006. The unified neutral theory of biodiversity: do the numbers add up? Weir, J.T., Schluter, D., 2008. Calibrating the avian molecular clock. Mol. Ecol. 17 (10), Ecology 87 (6), 1424–1431. 2321–2328. Ronquist, F., Teslenko, M., Van Der Mark, P., Ayres, D.L., Darling, A., Höhna, S., et al., Weisrock, D.W., Rasoloarison, R.M., Fiorentino, I., Ralison, J.M., Goodman, S.M., 2012. MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice Kappeler, P.M., Yoder, A.D., 2010. Delimiting species without nuclear monophyly in across a large model space. Syst. Biol. 61 (3), 539–542. Madagascar's mouse lemurs. PLoS ONE 5 (3), e9883. Salomonsen, F., 1934. On a hitherto unknown fauna of montane birds in central Weyeneth, N., Goodman, S.M., Ruedi, M., 2010. Does the diversification models of Madagascar. Novitates Zoologicae 39, 207–215. Madagascar’s biota explain the population structure of the endemic bat Myotis goudoti Schatz, G.E., 2000. Endemism in the Malagasy tree flora. In: Lourenço, W.R., Goodman, (Chiroptera: Vespertilionidae)? J. Biogeogr. 38, 44–54. S.M. (Eds.), Diversity and Endemism in Madagascar. Société de Biogéographie, Wilmé, L., Goodman, S.M., 2003. Biogeography, guild structure, and elevational variation MNHN, Paris, France. of Madagascar’s forest birds. In: Goodman, S.M., Benstead, J.P. (Eds.), Natural Stamatakis, A., 2014. RAxML version 8: a tool for phylogenetic analysis and post-analysis History of Madagascar. The University of Chicago Press, Chicago, USA. of large phylogenies. Bioinformatics 30, 1312–1313. Wilmé, L., Goodman, S.M., Ganzhorn, J.U., 2006. Biogeographic evolution of Storey, M., Mahoney, J.J., Saunders, A.D., Duncan, R.A., 1995. Timing of hot spot-related Madagascar's microendemic biota. Science 312 (5776), 1063–1065. volcanism and the breakup of Madagascar and India. Science 267 (5199), 852. Wollenberg, K.C., Vieites, D.R., Van Der Meijden, A., Glaw, F., Cannatella, D.C., Vences, Sukumaran, J., Knowles, L.L., 2017. Multispecies coalescent delimits structure, not spe- M., Nice, C., 2008. Patterns of endemism and species richness in Malagasy cophyline cies. Proc. Natl. Acad. Sci. 114 (7), 1607–1612. frogs support a key role of mountainous areas for speciation. Evolution 62 (8), Talavera, G., Castresana, J., 2007. Improvement of phylogenies after removing divergent 1890–1907. and ambiguously aligned blocks from protein sequence alignments. Syst. Biol. 56 (4), Xi, Z., Liu, L., Davis, C.C., 2015. Genes with minimal phylogenetic information are pro- 564–577. blematic for coalescent analyses when gene tree estimation is biased. Mol. Vences, M., Wollenberg, K.C., Vieites, D.R., Lees, D.C., 2009. Madagascar as a model Phylogenet. Evol. 92, 63–71. region of species diversification. Trends Ecol. Evol. 24 (8), 456–465. Yamagishi, S., Honda, M., Eguchi, K., Thorstrom, R., 2001. Extreme endemic radiation of Warren, B.H., Bermingham, E., Bourgeois, Y., Estep, L.K., Prys-Jones, R.P., Strasberg, D., the Malagasy Vangas (Aves: Passeriformes). J. Mol. Evol. 53, 39–46. Thébaud, C., 2012. Hybridization and barriers to gene flow in an island bird radia- Yang, Z., 2015. The BPP program for species tree estimation and species delimitation. tion. Evolution 66 (5), 1490–1505. Curr. Zool. 61 (5), 854–865. Warren, B.H., Bermingham, E., Bowie, R.C., Prys-Jones, R.P., Thébaud, C., 2003. Yoder, A.D., Campbell, C.R., Blanco, M.B., dos Reis, M., Ganzhorn, J.U., Goodman, S.M., Molecular phylogeography reveals island colonization history and diversification of et al., 2016. Geogenetic patterns in mouse lemurs (genus Microcebus) reveal the western Indian Ocean sunbirds (Nectarinia: Nectariniidae). Mol. Phylogenet. Evol. 29 ghosts of Madagascar's forests past. Proc. Natl. Acad. Sci. 113 (29), 8049–8056. (1), 67–85. Yoder, A.D., Heckman, K.L., 2006. Mouse lemur phylogeography revises a model of Warren, B.H., Bermingham, E., Prys-Jones, R., Thebaud, C., 2006. Immigration, species ecogeographic constraint in Madagascar. In: Fleagle, J., Lehman, S.M. (Eds.), Primate radiation and extinction in a highly diverse songbird lineage: white-eyes on Indian Biogeography: Progress and Prospects. Kluwer Press, Dordrecht, Netherlands, pp. Ocean islands. Mol. Ecol. 15 (12), 3769–3786. 255–268. Warren, B.H., Bermingham, E., Prys-Jones, R.P., Thebaud, C., 2005. Tracking island co- Yoder, A.D., Olson, L.E., Hanley, C., Heckman, K.L., Rasoloarison, R., Russell, A.L., et al., lonization history and phenotypic shifts in Indian Ocean bulbuls (Hypsipetes: 2005. A multidimensional approach for detecting species patterns in Malagasy ver- Pycnonotidae). Biol. J. Linn. Soc. 85 (3), 271–287. tebrates. Proc. Natl. Acad. Sci. 102, 6587–6594.

26 Supplemental Information for:

Hidden diversity of forest birds in Madagascar revealed using integrative taxonomy

Jane L. Younger, Lynika Strozier, J. Dylan Maddox, Árpád S. Nyári, Matthew T. Bonfitto, Marie J. Raherilalao, Steven M. Goodman and Sushma Reddy.

Description of the southern clade of Newtonia amphichroa as a new species to science

We have taken measurements from museum study skins following the techniques described by Baldwin et al. (1931) and explicitly defined in Supplementary Table 4 and the Morphological variation section of Materials and Methods. Other data were extracted from the field notes of different field biologists. Specimens discussed herein are held in the collections of the Field Museum of Natural History, Chicago (FMNH), and the Mention Zoology and Animal Biodiversity, University of Antananarivo, Antananarivo (UADBA, formerly Department of Animal Biology). Color terminology (first letters capitalized) and codes (in parentheses) follow Smithe (1976).

Newtonia lavarambo, sp. nov. Goodman, Younger, Raherilalalo & Reddy Southern Dark Newtonia (English) Newtonia sombre du Sud (French) Katekateka Atsimo (Malagasy)

Zoobank Registry : urn:lsid:zoobank.org:pub:EB6D0A7B-0DF3-4596-99F8-723F9D67424A

Holotype. FMNH 438751. Adult female collected by D. E. Willard at Madagascar, Province de Fianarantsoa, Parc National de Midongy-Sud, NE slope of Mt. Papango, 3.5 km SW of Befotaka, 23.8383°S, 46.9583°E, 1250 m, on 3 November 2003. The specimen was prepared as a standard museum flat skin, bears the field number DW 5510, and was used in both the morphological and molecular analyses. The name of the protected area has been more recently changed to Parc National de Befotaka-Midongy Sud.

Paratypes. Specimens used in the molecular analyses have the museum number in bold and in the morphological analyses underlined. Madagascar, Province de Fianarantsoa: FMNH 363855, 363858, ~38 km S of Ambalavao, Réserve Naturelle Intégrale-5, Andringitra, on ridge east of Volotsangana River, 22.1941°S, 46.9711°E, 1625 m, 26 October 1993; FMNH 363856, ~45 km S of Ambalavao, east bank Iantara River, along Ambalamanenjana-Ambatomboay Trail, 22.2222°S, 47.0247°E, 720 m, 28 September 1993; FMNH 393382, 393383, 393384, 393387 -

1 Forêt de Manambolo, 19.5 km SE of Sendrisoa, western slope of Vohipia, 22.163°S, 47.042°E, 1600 m, 2 December 1999; FMNH 393389, Forêt de Manambolo, along Andohabatotany River, 17.5 km SE of Sendrisoa, 22.148°S, 47.024°E, 1300 m, 25 November 1999; FMNH 438748, 438750, Parc National de Midongy-Sud, NE slope of Mt. Papango, 3.5 km SW of Befotaka, 23.833°S, 46.9583°E, 1250 m, 3 November 2003 (same locality as holotype); UADBA 31213 (MJR 0624), Parc National de Midongy-Sud, Andramiramy Forest, 6 km N of Befotaka, 23.778°S, 47.023°E, 815 m, 4 February 2008; UADBA 31260 (MJR 0676), Parc National de Befotaka- Midongy, Forêt d’Andranomigodro, 11.5 km SO du village de Befotaka, 23.888°S, 46.897°E, 1055 m, 28 February 2008. Madagascar, Province de Toliara: FMNH 384791, Réserve Naturelle Intégrale d’Andohahela [now Parc National], 15.0 km NW of Eminiminy, 24.567°S, 46.717°E, 1500 m, 22 November 1995; FMNH 352930, Fivondronana de Tolagnaro, Forêt de Marovony, 19 km NNE of Manantenina, 24.1°S, 47.367°E, 50 m, 3 November 1990.

Etymology. The name lavarambo is a compound word derived from the Malagasy, lava (long) and rambo (tail), which refers to this species’ distinctive long tail. This character, among others, distinguishes it from its sister species N. amphichroa. As we propose herein the English vernacular name Southern Dark Newtonia for N. lavarambo, we suggest the vernacular name Northern Dark Newtonia for N. amphichroa.

Diagnosis. Excluding aspects of molecular genetics mentioned in the main portion of this paper that clearly differentiate N. lavarambo from its sister species N. amphichroa, the former has a statistically significantly longer tail (mean of 44.204 and 42.424 mm, respectively; p = 0.0034) and narrower bill width (mean of 3.891 and 4.226 mm, respectively; p = 0.0082) than the latter (Supplementary Table 6 in this document). N. lavarambo tends to have a less saturated dark brown back, slightly more rufus along the flanks, and more saturated rufus crural feathers than N. amphichroa.

Description of holotype. Lores, forehead, crown, ear-coverts, and upper nape Olive-Brown (28). The balance of the dorsal surface, including the back, rump, and posterior to the dorsal surface of the tail Olive-Brown (28). The flight feathers, scapulars, and wing coverts Olive- Brown (28), with the latter having Amber (36) edging. Chin and upper throat dull Drab (27) and slightly darker along lateral portions. The middle and lower central portion of breast Cream Color (54) and laterally with a more saturated Clay Color (26) coloration. The flanks are Drab (27) proximally and Tawny (38) laterally; and underwing and undertail coverts Clay Color (26). Feathering of upper tarsus (crural) Tawny (38).

Measurements of holotype. See Materials and Methods section and Supplementary Table 4 for definitions of variables. Bill length (to tip): 13.9 mm; bill length (from nares): 6.9 mm; bill width

2 (at nares): 3.8 mm; bill depth (at nares): 3.6 mm; tarsus length: 21.5 mm; tarsus width: 1.7 mm; hallux length: 13.0 mm; tail length: 43.3 mm; and wing length: 53.7 mm.

Other aspects associated with the holotype. The following details are as noted on the specimen label of the holotype (FMNH 438751), which is an adult female: iris – orange-brown; mandible – black; maxilla – black; tarsus – dark gray; habitat – “netted [in] undisturbed humid montane forest”; skull -- fully ossified; fat: none; molt: none; and gonads (ovary) – 4 x 3 mm, granular.

Description of paratypes. Little intraspecific variation was found in specimens referable to N. lavarambo that were genotyped and falling within the southern clade as defined in the main portion of this paper. This variation can be summarized as: maxilla and mandible: uniformly black; crown: Olive-Brown (28) to Brownish Olive (29); back: Olive-Brown (28) to Brownish Olive (29); dorsal and ventral surfaces of tail: Olive-Brown (28); throat: Drab (27); central breast: Smoke Gray (45) to Clay Color (26); flanks: Cream Color (54); outer wing coverts and flight feather: Olive-Brown (28) to Brownish Olive (29); and crural feathers: Tawny (38).

Comparisons. With the description of N. lavarambo herein, the other four recognized members of the genus Newtonia include N. amphichroa, N. brunneicauda, N. archboldi, and N. fanovanae. The latter two species can be easily differentiated from the others based on external measurements and plumage characters (Goodman & Schulenberg, 1991; Hawkins & Sartain, 2013). N. archboldi has a distinct plumage with a rufus forehead and rufus washed upper breast contrasting with the distinctly white remaining underparts, as well as on average shorter wings. Further, this species occurs in the spiny bush formation of southwestern Madagascar and with a completely allopatric range from the other four members of this genus. N. fanovanae is distinguished by its rufus tail; dark iris, which is yellow-brown to orange-brown in the balance of Newtonia spp.; and distinctly short tarsus. N. brunneicauda resembles in many ways N. amphichroa and N. lavarambo, but has been distinguished from these two species based on its pale gray upperparts and less color saturated underparts, as well as some mensural differences. However, as discussed in the main portion of the paper, based on the molecular results, a number of field identifications of Newtonia in the hand and from humid forest sites were incorrect and the morphological characters used to differentiate N. brunneicauda from N. amphichroa/lavarambo need to be reevaluated. Morphologically, N. lavarambo is best differentiated from N. amphichroa based on tail and bill measurements (Supplementary Table 6, Supplementary Figure 9). The average tail length in N. lavarambo is 44.2 mm ± 1.00 (n = 7, range 42.5-45.1 mm) and in N. amphichroa is 42.4 ± 1.24 (n = 13, range 40.5-44.0), and these differences are statistically significant (Welch’s t-test, p = 0.0034). Further, the average bill width in N. lavarambo is 3.9 mm ± 0.24 (n = 7, range

3 3.6-4.2 mm) and in N. amphichroa is 4.2 ± 0.18 (n = 13, range 3.9-4.6 mm), and these differences are statistically significant (Welch’s t-test, p = 0.0082).

Molecular genetics. For full details on this aspect see main body of manuscript. Briefly, N. lavarambo and N. amphichroa formed reciprocally monophyletic clades in all of our phylogenetic analyses based on both Sanger sequencing of three nuclear introns (intron 11 of glyceraldehyde-3-phosphate dehydrogenase (GAPDH), intron 5 of fibrinogen beta chain (FGB), and intron 3 of muscle associated receptor tyrosine kinase (MUSK)) and two mitochondrial genes (NADH dehydrogenase 3 (ND3) and cytochrome b (CYTB)), and a dataset of 4,164 ultraconserved element (UCE) loci. A model comparison of species delimitation scenarios gave overwhelming support for the division of N. amphichroa and N. lavarambo (posterior probability = 0.972; Table 2 of main document).

Distribution. Newtonia lavarambo is known to occur in southeastern Madagascar from the Andringitra region south to forested areas in the vicinity of Tolagnaro. The majority of records confirmed via genotyping are in montane forest formations, generally above 1200 m. There are a few records from distinctly lower forest formations that span transitional montane-lowland forest habitats (FMNH 363856 at 720 m and UADBA 31213 at 815 m), and lowland forests (FMNH 352930 at 50 m). Hence, the designation of N. amphichroa/lavarambo as a strictly montane forest species is incorrect. On the basis of current data, N. lavarambo and N. amphichroa are allopatric, with the former found in the south central and southeast Madagascar and the latter in more northerly central and northeastern areas. There are several sites in eastern Madagascar that have three species of sympatric Newtonia, which in many cases are syntopic, including N. brunneicauda and N. fanovanae that occur across this region, and co-occurring either with N. amphichroa or N. lavarambo.

Nomenclatural considerations. The type locality of Newtonia amphichroa is ambiguous and presented as “Madagaskar Interior meridionalis” (Reichenow, 1891), which we interpret as the central interior of the island and falling within the southern portion of our northern clade. Further, Büttikofer (1896) described the species N. olivacea, which has been treated as a synonym of N. amphichroa (Watson et al., 1986), from “Savary” in northeastern Madagascar. The precise position of Savary is slightly ambiguous, but is certainly in the northeastern portion of the island (Carleton et al., 2014) and, hence, falling in the geographical region encompassed by the northern clade. We have not found any synonyms that are applicable to the southern clade and for this reason it is named herein as a new species, N. lavarambo.

Conservation status. As Newtonia lavarambo is forest-dwelling and the natural forests of the complete eastern latitudinal swath of Madagascar are under considerable threat associated

4 with different anthropogenic factors (Harper et al., 2007), there is rightfully some concern associated with the conservation status of this species. Within the eastern humid forests, the zone under the greatest threat is lowland habitats, and given the occurrence of this species in part in that elevational zone, its middle and long-term future is not assured. In contrast, montane forests are less impacted by human pressures and it is assumed under present conditions that this species’ long-term perseverance in that habitat is somewhat assured.

Supplementary Table 6. Univariate analysis of morphological variation between N. amphichroa and N. lavarambo. Mean, standard deviation (sd), minimum (min), and maximum (max) measurements for each species. The statistical significance of morphological differences between N. amphichroa (n = 13) and N. lavarambo (n = 7) was evaluated using Welch’s t-tests. Full description of the morphological measurements taken is available in Supplementary Table 4. N. amphichroa N. lavarambo Measurement mean sd min max mean sd min max p-value Bill length (to tip) 14.990 0.560 14.123 15.890 14.712 0.723 13.763 15.897 0.3972 Bill length (from nares) 7.744 0.430 7.067 8.380 7.607 0.371 6.907 8.007 0.4692 Bill width (at nares) 4.226 0.175 3.943 4.590 3.891 0.235 3.580 4.210 0.0082 Bill depth (at nares) 3.439 0.155 3.270 3.847 3.316 0.175 3.113 3.577 0.1480 Tarsus length 21.990 0.654 21.097 23.000 21.706 0.539 20.987 22.467 0.3137 Tarsus width 1.818 0.157 1.553 2.207 1.736 0.126 1.530 1.860 0.2216 Hallux length 13.160 0.551 12.357 14.400 13.013 0.633 11.933 13.997 0.6158 Tail length 42.424 1.236 40.523 43.973 44.204 1.003 42.507 45.107 0.0034 Wing length 56.474 2.119 54.000 61.667 54.571 2.515 51.667 58.333 0.1174

5 a) b) 4.6 45 4.4 44 4.2 43 Bill width (cm) Bill width (cm) 4.0 Tail length (cm) Tail Tail length (cm) 42 3.8 41 3.6

N. amphichroaN. amphichroa N. lavaramboN. lavarambo N. amphichroaN. amphichroa N. N.lavarambo lavarambo

Supplementary Figure 9. Statistically significant morphological differentiation between N. amphichroa and N. lavarambo. Box plots representing variation in specimens’ tail lengths are shown in panel a), and bill width at the nares in panel b).

References

Baldwin, S.P., Oberholser, H.C. & Worley, L.G. 1931. Measurements of birds. Scientific Publications of the Cleveland Museum of Natural History, 2: 1–165. Büttikofer, K. 1896. On a probably new species of Newtonia from Madagascar. Notes from the Leyden Museum, 18: 199–200. Carleton, M. D., Smeenk, C., Angermann, R. & Goodman, S. M. 2014. Taxonomy of nesomyine rodents (Muroidea: Nesomyidae: Nesomyinae): Designation of lectotypes and restriction of type localities for species-group taxa in the genus Nesomys Peters. Proceedings of the Biological Society of Washington, 126(4): 414–455. Goodman, S. M. & Schulenberg, T. S. 1991. The rediscovery of the Red-tailed Newtonia Newtonia fanovanae in south-eastern Madagascar with notes on the natural history of the genus Newtonia. Bird Conservational International, 1: 33–45. Harper, G. J., Steininger, M. K., Tucker, C. J., Juhn, D. & Hawkins, F. 2007. Fifty years of deforestation and forest fragmentation in Madagascar. Environmental Conservation, 34: 325–333.

6 Hawkins, A. F. A. & Sartain, A. 2013. Genus Newtonia Schlegel 1867. In Safford, R. J. and A. F. A. Hawkins, eds. The birds of Africa. Volume VIII: The Malagasy Region. Christopher Helm, London, pp. 802–807. Reichenow, A. 1891. Allgemeine Deutsche Ornithologishe Gesellschaft zu Berlin. Bericht über die Februar-Sitzung. Journal für Ornithologie, 1891, 210. Watson, G. E., Traylor, M. A. & Mayr, E. 1986. Family Sylviidae, Old World Warblers. In: E. Mayr & G. W. Cottrell, eds. Check-list of birds of the world, Volume XI. Museum of Comparative Zoology, Cambridge, Massachusetts, pp. 3-294. Smithe, F.B. 1976. Naturalist’s color guide. American Museum of Natural History, New York.

7 Supplemental Information for:

Hidden diversity of forest birds in Madagascar revealed using integrative taxonomy

Jane L. Younger, Lynika Strozier, J. Dylan Maddox, Árpád S. Nyári, Matthew T. Bonfitto, Marie J. Raherilalao, Steven M. Goodman and Sushma Reddy.

1 1 N. archboldi

N. brunneicauda 0.95

N. amphichroa 0.97

0.8

Supplementary Figure 1. Species tree estimated using ASTRAL-II from the gene trees of the 1,041 most informative UCE loci. Normalized quartet score = 0.72. Branch support values are for quadripartitions (rather than bipartitions) and are shown for internal nodes with > 70% support . Branch lengths are in coalescent units.

2 100 N. archboldi

100

100 81

89 N. brunneicauda

100 81

87 100 N. amphichroa

0.07

0.003

Supplementary Figure 2. Maximum-likelihood phylogeny of two mitochondrial genes (ND3, CYTB) and three nuclear introns (GAPDH, 0.07FGB, MUSK) for the subset of Newtonia that were included in our UCE analyses. Support values are shown for nodes that received > 70% bootstrap support.

N.archboldi_FMNH434463 100

N.archboldi_FMNH436446

N.brunneicauda_FMNH436444 100

N.brunneicauda_FMNH434458

100 N.brunneicauda_FMNH427347

N.brunneicauda_FMNH393381 99 96

N.brunneicauda_FMNH396202

90 N.brunneicauda_FMNH436526 83

N.brunneicauda_FMNH436523 69

N.brunneicauda_MJR0312 85 100 N.brunneicauda_FMNH396064

N.amphichroa_FMNH393382 73

N.amphichroa_FMNH393387 100

N.amphichroa_FMNH352930 73

N.amphichroa_FMNH384791

N.amphichroa_FMNH396208 100 29 N.amphichroa_FMNH384721 86 50 N.amphichroa_FMNH396203

N.amphichroa_FMNH393366 44 100 N.amphichroa_FMNH395989

N.amphichroa_FMNH393365 52

N.amphichroa_FMNH429706

Vanga_curvirostris_FMNH352878

0.003

Supplementary Figure 3. Maximum-likelihood tree of 4,164 concatenated UCE loci (4,288,201 bp) as in Figure 3a, but with tips labeled with specimen numbers and all bootstrap support values shown.

85 Falculea_palliata Vanga_curvirostris FMNH436447 MJR0330 45 MJR0952 100 21MJR0959

47 FMNH434463 10 47 FMNH352944 51 65 MJR0957 12 FMNH438519 FMNH436446 Newtonia archboldi 62 MJR0958 54 FMNH436438 FMNH438520 FMNH434458 100 FMNH434459 25 MJR0332

6 FMNH434462 MJR0908 5 FMNH434460 57 24 FMNH434461 4 2 MJR0318

35 FMNH352933 MJR0344 MJR01038 1 FMNH345887

4 MJR0938 FMNH352938 4 11 44 MJR0936 MJR0502 1 21 MJR0317

43 4 MJR0909 94 MJR0487 90 23 MJR0497 FMNH427347 4 66 MJR0501 43 MJR0499 FMNH436437 FMNH396205

93 MJR0543 47 MJR0544

15FMNH396206 FMNH436441 1 99 42 FMNH436445 FMNH436439 7 FMNH436444 9 52 FMNH436442 1 FMNH436443 59 49 FMNH436435 95 FMNH436440

98 FMNH436436 36 MJR0951 9 MJR0963

92 MJR0872 MJR0869 MJR0524 FMNH396204 15 52 FMNH427345 21 Newtonia brunneicauda 5 MJR0528 FMNH436523 1 97 62 17 FMNH436522 MJR0469 FMNH393376 FMNH352943 1 FMNH352941

59 FMNH436527 10 13 1 FMNH345886 MJR01068 3 FMNH436524

46 FMNH352932 0 2 7 FMNH393375 4 1 44 FMNH436525 26 4 FMNH393378

0 FMNH396064 48 FMNH352931 FMNH345885 0 FMNH393381 37 39 MJR0312 14 MJR0774 MJR0743 MJR0370 FMNH436526 FMNH427346 98 MJR0580 57 55 MJR0561 63 MJR0798 FMNH396202 FMNH438748

662 FMNH438751 MJR0676

216FMNH363855 2028 FMNH363858 17 FMNH352930 FMNH393387 68 FMNH438750

51 MJR0624

11 FMNH393384 83 FMNH393383 48 FMNH393389 43 50 FMNH393382 FMNH384791 FMNH363856

50 MJR0752 FMNH429707 MJR0821 9 21 MJR0367 100 1 FMNH396201

13FMNH429705 7 MJR0455 MJR0751 MJR0394 MJR0358

5 MJR0411 0 0 MJR0434 85 0 MJR0771 0 10 MJR0707 3 MJR0464 02 0 MJR0526 MJR0416 FMNH429706 MJR0375

39 MJR0362 MJR0366 FMNH384721 MJR0716 1 27 45 MJR0770 11 14 Newtonia amphichroa MJR0562B 2 0 MJR0820 MJR0415 0 MJR0753 30 12 MJR0563A MJR0894 FMNH393377

13 FMNH396207 38 FMNH396208 FMNH431265

46 FMNH393366 FMNH431266 FMNH393373 1 8 FMNH393369 0 FMNH395989 0 45 2 70 FMNH395990 3 FMNH393380

2 MJR0264 1 56 FMNH393367 0 6 MJR0270 1 55 FMNH393370 1 FMNH393368

1 FMNH393372 3 3 MJR01061 0 1 FMNH396209

0 FMNH393371 12 FMNH393374

9FMNH393364

0 63 MJR01079 MJR01080 FMNH393379 FMNH393365 MJR0688

4FMNH396203 MJR0418 FMNH396200 Leptopterus_chabert

0.05 Supplementary Figure 4. Maximum-likelihood tree of two mitochondrial genes (ND3, CYTB) and three nuclear introns (GAPDH, FGB, MUSK) as in Figure 3b, but with tips labeled with specimen numbers and all bootstrap support values shown.

Supplementary Figure 5. Median joining network of Newtonia amphichroa cytochrome b haplotypes. Network is colored by the region of collection in Madagascar.

A B

Supplementary Figure 6. Median joining network of Newtonia brunneicauda cytochrome b haplotypes. Networks are colored by the region of collection in Madagascar: a) by four general regions of north east, central east, south, west, and b) by the bioclimatic zones Schatz (2000) / zones of endemism described in Vences et al., (2009).

7 4,000,000 ) e N 3,000,000

2,000,000 Eﬀec-ve popula-on size (

1,000,000

0 0 500,000 1,000,000 1,500,000 2,000,000

Years before present

Supplementary Figure 7. Abundance trend of Newtonia brunneicauda over the last two million years. Extended Bayesian skyline plot showing the change in effective population size (Ne), with the black line indicating the median estimate and dashed lines showing the 95% highest posterior density interval.

8 4 4 4 3 3 2 2 2 PC1 score PC1 score 1 1 0 0 0 −1 −1 −2 −2 2 − −3 −3

N. amphichroaN. amphichroaam2 S SN. amphichroaN. amphichroaam3 N N N. archboldiN.ar archboldi N. brunneicaudaN. brbrunneicauda

Supplementary Figure 8. Box plot of PC1 scores for morphometric comparison of the northern and southern N. amphichroa clades, N. archboldi, and N. brunneicauda. All four groups have non-overlapping means and inter-quartile range.

9 Supplementary Table 1. Taxon sampling for this study, with specimen identifier, bioclimatic zone, collection locality, latitude (Lat), longitude (Long), sequencing methods used, and clade membership. FMNH = Field Museum of Natural History; MJR = uncatalogued field collections of Marie- Jeanne Raherilalao held in the Mention Zoologie Biologie Animale, Université d’Antananarivo. Bioclimatic zones are based on the zonation in Figure 1 and Schatz (2000), with further subdivision into north (N), south (S), east (E), and central (C) where a bioclimatic zone spans the latitudinal breadth of Madagascar. Members of the southern N. amphichroa clade are described herein as a new species.

Species Specimen ID Bioclimatic Locality Lat Long ND3 CTYB GAPDH Musk FIB5 UCEs Clade N. amphichroa FMNH 352930 SE humid Marovony Forest -24.100 47.367 X X X X X X Southern N. amphichroa N. amphichroa FMNH 363855 SE montane Andringitra -22.000 46.967 X X X X X Southern N. amphichroa N. amphichroa FMNH 363856 SE montane Andringitra -22.000 47.017 X X X Southern N. amphichroa N. amphichroa FMNH 363858 SE montane Andringitra -22.000 46.967 X X X X X Southern N. amphichroa N. amphichroa FMNH 384721 C montane Andranomay -18.467 47.960 X X X X X Northern N. amphichroa N. amphichroa FMNH 384791 SE humid Andohahela -24.567 46.717 X X X X X X Southern N. amphichroa N. amphichroa FMNH 393364 NE humid Betaolana Forest -14.538 49.438 X X X X Northern N. amphichroa N. amphichroa FMNH 393365 NE humid Betaolana Forest -14.538 49.438 X X X X Northern N. amphichroa N. amphichroa FMNH 393366 NE humid Betaolana Forest -14.543 49.425 X X X X X Northern N. amphichroa N. amphichroa FMNH 393367 NE humid Betaolana Forest -14.543 49.425 X X X X X Northern N. amphichroa N. amphichroa FMNH 393368 NE humid Betaolana Forest -14.543 49.425 X X X X X Northern N. amphichroa N. amphichroa FMNH 393369 NE humid Betaolana Forest -14.543 49.425 X X X Northern N. amphichroa N. amphichroa FMNH 393370 NE humid Betaolana Forest -14.543 49.425 X X X X Northern N. amphichroa N. amphichroa FMNH 393371 NE humid Betaolana Forest -14.543 49.425 X X X X Northern N. amphichroa N. amphichroa FMNH 393372 NE humid Betaolana Forest -14.543 49.425 X X X X X Northern N. amphichroa N. amphichroa FMNH 393373 NE humid Anjanaharibe-Sud -14.750 49.417 X X X X X Northern N. amphichroa N. amphichroa FMNH 393374 NE humid Anjanaharibe-Sud -14.750 49.417 X X X X X Northern N. amphichroa N. amphichroa FMNH 393377 NE humid Anjanaharibe-Sud -14.750 49.417 X X X X Northern N. amphichroa N. amphichroa FMNH 393379 NE humid Anjanaharibe-Sud -14.750 49.417 X X X X X Northern N. amphichroa N. amphichroa FMNH 393380 NE humid Anjanaharibe-Sud -14.750 49.417 X X X X X Northern N. amphichroa N. amphichroa FMNH 393382 SE montane Manambolo Forest -22.163 47.042 X X X X X X Southern N. amphichroa N. amphichroa FMNH 393383 SE montane Manambolo Forest -22.163 47.042 X X X X X Southern N. amphichroa N. amphichroa FMNH 393384 SE montane Manambolo Forest -22.163 47.042 X X X X Southern N. amphichroa N. amphichroa FMNH 393387 SE montane Manambolo Forest -22.163 47.042 X X X X X Southern N. amphichroa N. amphichroa FMNH 393389 SE montane Manambolo Forest -22.148 47.024 X X X X X Southern N. amphichroa N. amphichroa FMNH 395989 NE humid Anjanaharibe-Sud -14.750 49.417 X X X X X Northern N. amphichroa 10 N. amphichroa FMNH 395990 NE humid Anjanaharibe-Sud -14.750 49.417 X X X X Northern N. amphichroa N. amphichroa FMNH 396200 C montane Mahatsinjo Forest -19.667 47.767 X X X X Northern N. amphichroa N. amphichroa FMNH 396201 C montane Mahatsinjo Forest -19.667 47.767 X X X X X Northern N. amphichroa N. amphichroa FMNH 396203 C montane Mahatsinjo Forest -19.667 47.767 X X X X Northern N. amphichroa N. amphichroa FMNH 396207 N montane Manongarivo -13.999 48.428 X X X X Northern N. amphichroa N. amphichroa FMNH 396208 N montane Manongarivo -13.999 48.428 X X X X X X Northern N. amphichroa N. amphichroa FMNH 396209 N montane Manongarivo -13.999 48.428 X X X X Northern N. amphichroa N. amphichroa FMNH 429705 C montane Andranomay Forest -18.480 47.955 X X X Northern N. amphichroa N. amphichroa FMNH 429706 C montane Andranomay Forest -18.480 47.955 X X X X X Northern N. amphichroa N. amphichroa FMNH 429707 C montane Andranomay Forest -18.480 47.955 X X X X X Northern N. amphichroa N. amphichroa FMNH 431265 NE humid Marojejy -14.433 49.795 X X X X X Northern N. amphichroa N. amphichroa FMNH 431266 NE humid Marojejy -14.433 49.795 X X X X X Northern N. amphichroa N. amphichroa FMNH 438748 SE humid Midongy-Sud -23.833 46.950 X X X Southern N. amphichroa N. amphichroa FMNH 438750 SE humid Midongy-Sud -23.833 46.950 X X X Southern N. amphichroa N. amphichroa FMNH 438751 SE humid Midongy-Sud -23.833 46.950 X X X X X Southern N. amphichroa N. amphichroa MJR 0264 E subhumid Marotandrano -16.280 48.802 X X X X Northern N. amphichroa N. amphichroa MJR 0270 E subhumid Marotandrano -16.280 48.802 X X X X Northern N. amphichroa N. amphichroa MJR 0358 C montane Antsahabe -18.422 47.943 X X X X X Northern N. amphichroa N. amphichroa MJR 0362 C montane Antsahabe -18.422 47.943 X X X X X Northern N. amphichroa N. amphichroa MJR 0366 C montane Antsahabe -18.422 47.943 X X X X X Northern N. amphichroa N. amphichroa MJR 0367 C montane Antsahabe -18.422 47.943 X X X X Northern N. amphichroa N. amphichroa MJR 0375 C montane Andasin'i Saotra -18.425 47.953 X X X Northern N. amphichroa N. amphichroa MJR 0394 C montane Ambohimanga -18.473 47.960 X X X X Northern N. amphichroa N. amphichroa MJR 0411 C montane Iaban'Ikoto -18.522 47.973 X X X Northern N. amphichroa N. amphichroa MJR 0415 C montane Iaban'Ikoto -18.522 47.973 X X Northern N. amphichroa N. amphichroa MJR 0416 C montane Iaban'Ikoto -18.522 47.973 X X X X X Northern N. amphichroa N. amphichroa MJR 0418 C montane Iaban'Ikoto -18.522 47.973 X X X X X Northern N. amphichroa N. amphichroa MJR 0434 C montane Anorana -18.305 48.015 X X X X X Northern N. amphichroa N. amphichroa MJR 0455 C montane Andasin'i Tovo -18.643 47.942 X X X X X Northern N. amphichroa N. amphichroa MJR 0464 C montane Andasin'i Tovo -18.643 47.942 X X X X X Northern N. amphichroa N. amphichroa MJR 0526 C montane Ambohitantely -18.172 47.282 X X X X Northern N. amphichroa N. amphichroa MJR 0562B E humid Sahambaky -19.065 48.340 X X X X X Northern N. amphichroa

11 N. amphichroa MJR 0563A E humid Sahambaky -19.065 48.340 X X X X X Northern N. amphichroa N. amphichroa MJR 0624 SE humid Befotaka-Midongy -23.778 47.023 X X X X Southern N. amphichroa N. amphichroa MJR 0676 SE humid Andranomigodo -23.888 46.897 X X X X X Southern N. amphichroa N. amphichroa MJR 0688 E humid Maromiza -18.976 48.458 X X X X X Northern N. amphichroa N. amphichroa MJR 0707 E humid Sahambaky -19.065 48.340 X X X X X Northern N. amphichroa N. amphichroa MJR 0716 E humid Maromiza -18.976 48.458 X X X X X Northern N. amphichroa N. amphichroa MJR 0751 E humid Analamay -18.799 48.323 X X X X Northern N. amphichroa N. amphichroa MJR 0752 E humid Analamay -18.799 48.323 X X X X X Northern N. amphichroa N. amphichroa MJR 0753 E humid Analamay -18.799 48.323 X X X X X Northern N. amphichroa N. amphichroa MJR 0770 E humid Analamay -18.793 48.334 X X X X X Northern N. amphichroa N. amphichroa MJR 0771 E humid Analamay -18.793 48.334 X X X X X Northern N. amphichroa N. amphichroa MJR 0820 E humid Analamay -18.806 48.361 X X X X X Northern N. amphichroa N. amphichroa MJR 0821 E humid Analamay -18.806 48.361 X X X X Northern N. amphichroa N. amphichroa MJR 0894 E humid Lakato -19.044 48.349 X X X Northern N. amphichroa N. amphichroa MJR 01061 N montane Bemanevika -14.346 48.582 X X X X Northern N. amphichroa N. amphichroa MJR 01079 N montane Bemanevika -14.383 48.588 X X X X Northern N. amphichroa N. amphichroa MJR 01080 N montane Bemanevika -14.383 48.588 X X Northern N. amphichroa N. archboldi FMNH 352944 SE humid Ankapoky Forest -24.000 46.517 X X X X X N. archboldi N. archboldi FMNH 434463 S subarid Tsimanampetsotsa -24.000 43.883 X X X X X X N. archboldi N. archboldi FMNH 436438 S subarid Mikea Forest -22.767 43.517 X X X X X N. archboldi N. archboldi FMNH 436446 S subarid Mikea Forest -22.767 43.517 X X X X X X N. archboldi N. archboldi FMNH 436447 S subarid Mikea Forest -22.800 43.433 X X X X N. archboldi N. archboldi FMNH 438519 S subarid Mikea Forest -22.767 43.517 X X X X N. archboldi N. archboldi FMNH 438520 S subarid Mikea Forest -22.767 43.517 X X X X X N. archboldi N. archboldi MJR 0330 S subarid Vohondava -24.687 46.453 X X X X X N. archboldi N. archboldi MJR 0952 S subarid Salary-Bekodoy -22.510 43.295 X X X X X N. archboldi N. archboldi MJR 0957 S subarid Salary-Bekodoy -22.510 43.295 X X X X X N. archboldi N. archboldi MJR 0958 S subarid Salary-Bekodoy -22.510 43.295 X X X X X N. archboldi N. archboldi MJR 0959 S subarid Salary-Bekodoy -22.510 43.295 X X X X X N. archboldi N. brunneicauda FMNH 345885 SE humid Analalava Forest -24.000 47.283 X X X X X N. brunneicauda N. brunneicauda FMNH 345886 SE humid Analalava Forest -24.000 47.283 X X X X N. brunneicauda N. brunneicauda FMNH 345887 SE humid Marosohy Forest -24.000 46.800 X X X X X N. brunneicauda

12 N. brunneicauda FMNH 352931 SE humid Cascade Forest -24.000 46.933 X X X X N. brunneicauda N. brunneicauda FMNH 352932 SE humid Cascade Forest -24.000 46.933 X X X X N. brunneicauda N. brunneicauda FMNH 352933 SE humid Ankapoky Forest -24.000 46.517 X X X N. brunneicauda N. brunneicauda FMNH 352938 SE humid Ankapoky Forest -24.000 46.517 X X X X N. brunneicauda N. brunneicauda FMNH 352941 SE humid Itapera Forest -24.000 47.117 X X X X X N. brunneicauda N. brunneicauda FMNH 352943 SE humid Marovony Forest -24.000 47.367 X X X X N. brunneicauda N. brunneicauda FMNH 393375 NE humid Betaolana Forest -14.543 49.425 X X X X X N. brunneicauda N. brunneicauda FMNH 393376 NE humid Betaolana Forest -14.543 49.425 X X X X X N. brunneicauda N. brunneicauda FMNH 393378 NE humid Anjanaharibe-Sud -14.750 49.417 X X X X X N. brunneicauda N. brunneicauda FMNH 393381 NE humid Anjanaharibe-Sud -14.750 49.417 X X X X X X N. brunneicauda N. brunneicauda FMNH 396064 E humid Tampolo Forestry Station -17.283 49.417 X X X X X X N. brunneicauda N. brunneicauda FMNH 396202 C montane Mahatsinjo Forest -19.667 47.767 X X X X X N. brunneicauda N. brunneicauda FMNH 396204 C montane Mahatsinjo Forest -19.667 47.767 X X X X X N. brunneicauda N. brunneicauda FMNH 396205 N montane Manongarivo -14.022 48.418 X X X X N. brunneicauda N. brunneicauda FMNH 396206 S subarid Isalo -22.540 45.380 X X X N. brunneicauda N. brunneicauda FMNH 427345 SE montane Andringitra -22.200 46.833 X X X X X N. brunneicauda N. brunneicauda FMNH 427346 SE montane Andringitra -22.200 46.833 X X X X X N. brunneicauda N. brunneicauda FMNH 427347 SE montane Andringitra -22.200 46.833 X X X X X N. brunneicauda N. brunneicauda FMNH 434458 S subarid Tsimanampetsotsa -24.050 43.750 X X X X X X N. brunneicauda N. brunneicauda FMNH 434459 S subarid Tsimanampetsotsa -24.050 43.750 X X X X N. brunneicauda N. brunneicauda FMNH 434460 S subarid Tsimanampetsotsa -24.000 43.883 X X X X N. brunneicauda N. brunneicauda FMNH 434461 S subarid Tsimanampetsotsa -24.050 43.750 X X X X X N. brunneicauda N. brunneicauda FMNH 434462 S subarid Tsimanampetsotsa -24.050 43.750 X X X X X N. brunneicauda N. brunneicauda FMNH 436435 S subarid Mikea Forest -22.767 43.517 X X X X N. brunneicauda N. brunneicauda FMNH 436436 S subarid Mikea Forest -22.767 43.517 X X X X X N. brunneicauda N. brunneicauda FMNH 436437 S subarid Mikea Forest -22.767 43.517 X X X X X N. brunneicauda N. brunneicauda FMNH 436439 S subarid Mikea Forest -22.767 43.517 X X X X N. brunneicauda N. brunneicauda FMNH 436440 S subarid Mikea Forest -22.800 43.433 X X X X N. brunneicauda N. brunneicauda FMNH 436441 S subarid Mikea Forest -22.800 43.433 X X X X X N. brunneicauda N. brunneicauda FMNH 436442 S subarid Mikea Forest -22.800 43.433 X X X X X N. brunneicauda N. brunneicauda FMNH 436443 S subarid Mikea Forest -22.800 43.433 X X X X X N. brunneicauda N. brunneicauda FMNH 436444 S subarid Mikea Forest -22.800 43.433 X X X X X X N. brunneicauda

13 N. brunneicauda FMNH 436445 S subarid Mikea Forest -22.800 43.433 X X X N. brunneicauda N. brunneicauda FMNH 436522 NW dry Namoroka -16.433 45.400 X X X X N. brunneicauda N. brunneicauda FMNH 436523 NW dry Namoroka -16.433 45.400 X X X X N. brunneicauda N. brunneicauda FMNH 436524 NW dry Namoroka -16.433 45.400 X X X X X N. brunneicauda N. brunneicauda FMNH 436525 NW dry Namoroka -16.433 45.400 X X X X N. brunneicauda N. brunneicauda FMNH 436526 NW dry Namoroka -16.433 45.400 X X X X X N. brunneicauda N. brunneicauda FMNH 436527 NW dry Namoroka -16.433 45.400 X X X X X N. brunneicauda N. brunneicauda MJR 0312 NW dry Belambo -14.887 47.732 X X X X X N. brunneicauda N. brunneicauda MJR 0317 S subarid Tongaenoro -24.737 44.030 X X X N. brunneicauda N. brunneicauda MJR 0318 S subarid Tongaenoro -24.737 44.030 X X X X N. brunneicauda N. brunneicauda MJR 0332 S subarid Vohondava -24.687 46.453 X X X X X N. brunneicauda N. brunneicauda MJR 0344 S subarid Mahavelo -24.765 46.153 X X X X N. brunneicauda N. brunneicauda MJR 0370 C montane Antsahabe -18.422 47.943 X X X X N. brunneicauda N. brunneicauda MJR 0469 C montane Andasin'i Tovo -18.643 47.942 X X X N. brunneicauda N. brunneicauda MJR 0487 W dry Ambalimby -19.615 44.768 X X X X N. brunneicauda N. brunneicauda MJR 0497 W dry Ambalimby -19.615 44.768 X X X X N. brunneicauda N. brunneicauda MJR 0499 W dry Ambalimby -19.612 44.743 X X X N. brunneicauda N. brunneicauda MJR 0501 W dry Ambalimby -19.612 44.743 X X X X N. brunneicauda N. brunneicauda MJR 0502 W dry Ambalimby -19.612 44.743 X X X X X N. brunneicauda N. brunneicauda MJR 0524 NW dry Ankarafantsika -16.303 46.930 X X X X X N. brunneicauda N. brunneicauda MJR 0528 C montane Ambohitantely -18.172 47.282 X X X N. brunneicauda N. brunneicauda MJR 0543 S subarid Kirindy Mite -20.788 44.102 X X X N. brunneicauda N. brunneicauda MJR 0544 S subarid Kirindy Mite -20.788 44.102 X X X X N. brunneicauda N. brunneicauda MJR 0561 E humid Sahambaky -19.065 48.340 X X X X N. brunneicauda N. brunneicauda MJR 0580 E humid Sahambaky -19.065 48.340 X X X X X N. brunneicauda N. brunneicauda MJR 0743 C montane Ambohitantely -18.229 47.285 X X X X X N. brunneicauda N. brunneicauda MJR 0774 E humid Analamay -18.793 48.334 X X X X N. brunneicauda N. brunneicauda MJR 0798 E humid Analamay -18.808 48.337 X X X X X N. brunneicauda N. brunneicauda MJR 0869 W dry Fivondronana Morondava -19.825 44.474 X X X X N. brunneicauda N. brunneicauda MJR 0872 S subarid Andranomena -20.175 44.536 X X X X N. brunneicauda N. brunneicauda MJR 0908 S subarid Analasoa -24.027 43.737 X X N. brunneicauda N. brunneicauda MJR 0909 S subarid Analasoa -24.027 43.737 X X X X X N. brunneicauda

14 N. brunneicauda MJR 0936 W dry Beanka -17.940 44.468 X X X X N. brunneicauda N. brunneicauda MJR 0938 W dry Beanka -17.940 44.468 X X X N. brunneicauda N. brunneicauda MJR 0951 S subarid Salary-Bekodoy -22.510 43.295 X X X X N. brunneicauda N. brunneicauda MJR 0963 S subarid Salary-Bekodoy -22.510 43.295 X X X X X N. brunneicauda N. brunneicauda MJR 01038 S subarid Tsimanampetsotsa -24.027 43.743 X X X X X N. brunneicauda N. brunneicauda MJR 01068 N montane Bemanevika -14.346 48.582 X X X X X N. brunneicauda Leptopterus chabert JQ239271 JQ239215 JQ713418 JQ713392 Outgroup Falculea palliata JQ239266 JQ239210 JQ713416 Outgroup Vanga curvirostris FMNH 352878 JQ239285 JQ239228 JQ713434 JQ713403 X Outgroup

Supplementary Table 2. Primers

Marker Primer name Primer sequence 5’ – 3’

ND3 ND3-L10751 GAC TTC CAA TCT TTA AAA TCT GG ND3 ND3-H11151 GAT TTG TTG AGC CGA AAT CAA C CYTB CB-L14851 CCT ACT TAG GAT CAT TCG CCC T CYTB CB-H15563 GCG TAT GCG AAT AGG AAA TA GAPDH GapdL ACC TTT AAT GCG GGT GCT GGC ATT GC GAPDH GapdH CAT CAA GTC CAC AAC ACG GTT GCT GT FGB Fib5F CGC CAT ACA GAG TAT ACT GTG ACA T FGB Fib6R GCC ATC CTG GCG ATT CTG AA MUSK Musk-13F CTT CCA TGC ACT ACA ATG GGA AA MUSK Musk-13R CTC TGA ACA TTG TGG ATC CTC AA

15 Supplementary Table 3. Estimated timing of divergence events. Median estimates for the time to the most recent common ancestor in millions of years with the 95% highest posterior density interval shown in brackets. Analyses calibrated using the substitution rates in Weir & Schluter (2008).

Split Timing estimate (Ma) Newtonia and Vanga curvirostris 6.66 (5.38—8.03) N. archboldi and N. amphichroa/N. brunneicauda 5.93 (4.82—7.14) N. amphichroa and N. brunneicauda 4.14 (3.28—5.06) N. amphichroa - southern and central/northern clades 1.21 (0.849—1.64) N. amphichroa - central and northern clades 0.36 (0.183—0.568)

16 Supplementary Table 4. Summary statistics of morphological measurements. Full description of measurement, plate in Baldwin et al., (1931) detailing the measurement, mean, standard deviation (std dev), minimum (min), and maximum (max) measurements for each clade of Newtonia.

Newtonia amphichroa N (n = 13) Newtonia amphichroa S (n = 7) Newtonia archboldi (n = 3) Newtonia brunneicauda (n = 10) Measurement Description Plate in Baldwin et al. (1931) mean std dev min max mean std dev min max mean std dev min max mean std dev min max Bill length (to tip)* Notch on the forehead p .11, Fig. 3 14.990 0.560 14.123 15.890 14.712 0.723 13.763 15.897 14.043 0.660 13.507 14.780 13.842 1.194 11.110 15.080 where the base of the culmen meets the skull to the bill tip Bill length (from nares) Anterior edge of nostril p. 16, Fig. 8 7.744 0.430 7.067 8.380 7.607 0.371 6.907 8.007 7.341 0.278 7.020 7.513 7.534 0.612 6.067 8.270 to bill tip Bill width (at nares) Width of bill at anterior N/A 4.226 0.175 3.943 4.590 3.891 0.235 3.580 4.210 3.757 0.453 3.367 4.253 3.739 0.388 3.217 4.527 end of nares, at widest part Bill depth (at nares) Height of bill from p. 20, Fig. 11 3.439 0.155 3.270 3.847 3.316 0.175 3.113 3.577 3.187 0.078 3.100 3.250 3.184 0.255 2.750 3.573 culmen to lower edge of mandible Tarsus length Length of the tarsus p. 107, Fig. 136 21.990 0.654 21.097 23.000 21.706 0.539 20.987 22.467 17.806 0.173 17.607 17.920 18.474 0.805 17.383 19.763 measured from middle point of the joint between the tibia and metatarsus behind to the lower edge of the lowest undivided scute Tarsus width Height of tarsus at widest p. 108, Fig 137 1.818 0.157 1.553 2.207 1.736 0.126 1.530 1.860 1.483 0.084 1.387 1.533 1.694 0.092 1.557 1.827 point, close to tibia/tarsus joint Hallux length Length of hallux from modified p. 114, 13.160 0.551 12.357 14.400 13.013 0.633 11.933 13.997 9.957 0.534 9.597 10.570 10.912 0.598 10.010 12.263 where it joins the Fig. 144 metatarsus to distal tip of claw Tail length From base of feathers to p. 92, Fig. 120 42.424 1.236 40.523 43.973 44.204 1.003 42.507 45.107 43.912 0.999 42.797 44.723 46.148 2.743 40.897 49.797 tip of the longest tail feather when the tail is closed Wing length Length of closed wing p. 76, Fig. 100 56.474 2.119 54.000 61.667 54.571 2.515 51.667 58.333 48.333 0.577 48.000 49.000 54.383 2.175 51.667 59.000 chord * excluded from PCA due to redundancy with following measurement

17 Supplementary Table 5. Loadings, variance, and eigenvalues from principal components analysis (PCA) of morphological data.

Loadings Character PC1 PC2 PC3 Bill length from nares (BLN) -0.29 -0.37 -0.47 Bill width at nares (BW) -0.37 0.17 -0.44 Bill depth at nares (BD) -0.36 -0.07 -0.41 Tarsus length (TL) -0.43 0.12 0.21 Tarsus width (TW) -0.31 -0.33 0.49 Hallux length (HL) -0.42 0.16 0.28 Tail length (Tail) 0.24 -0.75 -0.05 Wing length (WL) -0.36 -0.34 0.22 Proportion of variance explained 0.53 0.14 0.12 Eigenvalue 2.06 1.04 0.98