A new antshrike (Aves: Thamnophilidae) endemic to the Caatinga and the role of climate oscillations and drainage shift in shaping cryptic diversity of Neotropical seasonal dry forests

Zoologica Scripta. 2024;53:487–508. | 487 wileyonlinelibrary.com/journal/zsc Received: 18 December 2023 | Revised: 19 March 2024 | Accepted: 23 May 2024 DOI: 10.1111/zsc.12672 ORIGINAL ARTICLE A new antshrike (Aves: Thamnophilidae) endemic to the Caatinga and the role of climate oscillations and drainage shift in shaping cryptic diversity of Neotropical seasonal dry forests PabloCerqueira1,2,3 | Gabriela R.Gonçalves1,2 | Tânia F.Quaresma3,4 | MarceloSilva4 | MauroPichorim5 | AlexandreAleixo3,4 This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2024 The Author(s). Zoologica Scripta published by John Wiley & Sons Ltd on behalf of Royal Swedish Academy of Sciences. Cover plate: Illustration of Sakesphoroides niedeguidonae (female MPEG 84680, male MPEG 84480). Illustration by Eduardo Brettas. 1Programa de Pósgraduação Em Zoologia, Museu Paraense Emílio Goeldi/Universidade Federal do Pará, Belém, Pará, Brazil 2Laboratório de Biogeografia da Conservação e MacroecologiaBIOMACRO, Instituto de Ciências Biológicas, Universidade Federal do Pará, Belém, Pará, Brazil 3Instituto Tecnológico Vale, Belém, Pará, Brazil 4Programa de Pósgraduação Em Biodiversidade e Evolução, Museu Paraense Emílio Goeldi, Belém, Pará, Brazil 5Departamento de Botânica e Zoologia, Universidade Federal Do Rio Grande Do Norte, Natal, Brazil Correspondence A. Aleixo, Instituto Tecnológico Vale – ITV, Rua Boaventura da Silva, 95566055090, Belém, PA, Brazil. Email: [email protected] Funding information Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Grant/ Award Number: 1537057 and 1537056; Financiadora de Estudos e Projetos, Grant/Award Number: 0118003100 Abstract The Caatinga is the largest patch of Seasonal Dry Tropical Forest in the Neotropics, located in northeastern Brazil and characterized mainly by deciduous vegetation and extreme rainfall seasonality. It has historically been treated as a biologically impoverished domain, but recent studies uncovered new diversification patterns and several new taxa of frogs, mammals, insects, and fishes. Here we employed a dense sampling regime to evaluate whether the São Francisco River (SFR) would have promoted genetic diversification and fixed phenotypic differences and how Quaternary climatic oscillations shaped distribution and population sizes in a Caatinga endemic species, the Silverycheeked Antshrike (Sakesphoroides cristatus). We adopted an integrative approach using multilocus genetic, plumage, vocal data, and ecological niche modelling (ENM) to characterize evolutionary units and niche suitability in past scenarios. We recovered strong genetic structure across the SFR that was congruent with plumage and vocal variation, revealing a yet undescribed species named herein as Sakesphoroides niedeguidonae, sp. nov. (urn:lsid:zoobank.org:act:2B9FC637008A4E9AB92B69ED7FE23823s). The splitting time estimated between the newly described species and S. cristatus is consistent with the establishment of the modern course of SFR, with a more recent course shift apparently promoting the secondary contact between the two species in the Raso da Catarina region. After their split, both species experienced increases in population sizes and range sizes at similar times during the Last Glacial Maximum. We expect other Caatinga avian endemic lineages to show similar patterns of genetic differentiation across the SFR that were enhanced by Quaternary climatic oscillations. 488 | CERQUEIRA etal. 1 | INTRODUCTION Seasonally Dry Tropical Forests (hereafter SDTFs) are treedominated ecosystems with a more or less continuous canopy in which grasses are a minor element and thorny species are prominent. The vegetation is mostly deciduous during the dry season, with deciduousness increasing as rainfall declines in volume, although in the driest forests there is a marked increase in evergreen and succulent species (Mooney etal.,1995; Pennington etal.,2000). The SDTFs has currently a discontinuous distribution with very heterogeneous patches, including formations as diverse as tall forest on moister sites to cactus scrub on the driest. In South America this heterogeneity prompted the recognition of distinct core areas throughout SDTFs such as the ‘Caatinga nucleus' in northeastern Brazil, the ‘Misiones nucleus' in the ParanáParaguay basin, and the ‘Subandean Piedmont nucleus' in southwestern Bolivia and northwestern Argentina (Pennington et al., 2000, 2006; Prado,2000; Prado & Gibbs,1993; Ratter etal.,1978; Silva & Bates,2002). The Caatinga is the largest area of SDTFs and encompasses heterogeneous arid and semiarid formations surrounded by more mesic formations, extending for ~800 km2 and representing 11% of the Brazilian territory (IBGE,1985). The geomorphology of this region plays an important role in its biogeographic history, with altitudes ranging from sea level in the north, an average 400–700 m through Bahia and Minas Gerais states in the central part, to over 1000 m on the slopes of the Espinhaço range (Taylor & Zappi,2004). In addition to geological processes in the Paleogene−Neogene, Quaternary climatic oscillations also contributed to the high levels of observed endemism (Werneck,2011). The biogeographic history and diversification patterns of SDTFs have received relatively less attention than those of Neotropical rain forests (Amazonia and Atlantic Forest). This is in part because Caatinga was historically treated as a species impoverished domain with low endemism, a concept falsified by recent studies (Mooney etal.,1995; Pennington et al., 2000; Werneck, 2011). Many studies have analysed Caatinga taxa under phylogenetic, phylogeographic and genetic population dynamics approaches, including insects (CoutinhoAbreu et al., 2008; Franco & Manfrin, 2013), lizards (Oliveira et al., 2015; Passoni etal.,2008; Siedchlag etal.,2010; Werneck etal.,2015), frogs (Thomé etal.,2016), mammals (Faria etal.,2013; Nascimento etal.,2011, 2013), fishes (Costa etal.,2018), and trees (Caetano et al., 2008). Despite the recent increase in the number of studies focusing on Caatinga diversification patterns, additional studies are necessary to address the existence of congruent spatiotemporal histories across taxa. In this sense, birds are one of the least sampled taxa by phylogenetic studies directed at Caatinga endemic lineages, in strong contrast to other domains such as Amazonian and the Atlantic Forest (do Amaral etal.,2013; Silva etal.,2019). Herein, we present the first multicharacter systematic study integrating genetic, morphological, vocal, and ecological data on a Caatinga endemic bird species, the Silverycheeked Antshrike Sakesphoroides cristatus (de WiedNeuwied, 1831). Until recently, this species was placed in the genus Sakesphorus, but novel genetic and morphological data recovered it as nonmonophyletic, prompting the transfer of S. cristatus to the separate genus Sakesphoroides (Bravo etal.,2021; Grantsau,2010). The endemic Sakesphoroides cristatus is widely distributed in the Caatinga domain, being currently regarded as monotypic. Based on our field observations and the examination of female specimens, which led to the first insights on plumage and song variation in Sakesphoroides, coupled with published evidence on vocal variation detected across the São Francisco River (Capelli etal.,2020), herein we evaluated whether genetic differentiation and fixed phenotypic differences would also be found on opposite banks of the São Francisco River (hereafter SFR). We also tested with the molecular data whether any differentiation across the SRF would correlate temporally with the establishment of its modern course. Finally, we carried out ecological niche modelling and historical demography analyses to evaluate any congruences in distribution and population sizes for S. cristatus across the Caatinga domain mediated by Quaternary climatic oscillations. 2 | METHODS 2.1 | Sampling We studied and analysed plumage and morphometric variation in a total of 1079 Sakesphoroides cristatus specimens (818 males, 261 females) including study skins (n = 92) and digital photographs available in online databases (n = 987; TableS1). To investigate song variation, we analysed a total of 115 different sound recordings (n = 95 loudsongs, n = 29 calls; more than one vocalization type KEYWORDS bioacoustics, biogeography, integrative taxonomy, niche modelling, São Francisco River 14636409, 2024, 5, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/zsc.12672 by Capes, Wiley Online Library on [25/06/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License | 489 CERQUEIRA etal. could be present in the same recording) available in online databases (TableS2). We sequenced 58 tissue samples from throughout S. cristatus range (TableS3), 39 of them belonging to the left bank and 19 to the right bank of the SFR. As outgroups, we used sequences of 29 Thamnophilidae species closest related to the S. cristatus from GenBank based on topologies of phylogenies inferred by Brumfield and Edwards(2007) and Bravo etal.(2021; see TableS4 for species names and GenBank accession numbers). We gathered all available occurrence records of S. cristatus (n = 568) for Environmental Niche Modelling (ENM) from the Species Link database (http:// splink. cria. org. br), Sound archive Xenocanto (http:// www. xenocanto. org), Wikiaves (http:// www. wikia ves. com. br), Vertnet (http:// www. vertn et. org/ index. html), Ebird (http:// www. ebird. org/ ), and museum specimens deposited at Museu Paraense Emílio Goeldi (MPEG), Museu de Zoologia da Universidade de São Paulo (MZUSP), Universidade Federal de Pernambuco (UFPE), Universidade Federal do Rio Grande do Norte (UFRN), Universidade Estadual de Feira de Santana (UEFS), and personal observations gathered during fieldwork. We inspected all occurrences for errors in locality names and geographic coordinates by comparison with the Brazilian ornithological gazetteer (Paynter Jr & Traylor Jr.,1991). 2.2 | Plumage and morphometric analyses To document geographic variation in plumage patterns, we analysed study skins and digital photographs. We used characters with discrete variation such as colours of the crown, back, throat, breast, tail, and presence of barring and streaks. All colour standardizations were based on Smithe(1975). We studied the type series of S. cristatus through high quality digital photos, which include an adult male (AMNH 6819), an adult female (AMNH 6820) and a juvenile female (AMNH 6821) held at the American Museum of Natural History, New York, USA. We used a digital calliper (nearest 0.1 mm) to measure the following characters in study skins of 24 females and 54 males (TableS1): (1) length of flattened wing (LW), (2) tarsus length (TarL), (3) tail length (TaiL), (4) bill length from the skull insertion (BL1), (5) bill length from anterior edge of nostrils (BL2), (6) bill width at anterior edge of nostrils (BW), and (7) bill depth at anterior edge of nostrils (BD). We tested for significant differences in these measurements using ANOVA with a Tukey test for a posteriori comparison using a dataset composed of males and females. Given their overall plumage conservatism, males were assigned to different groups following the geographic location of females. We tested all measurements for homogeneity of variance and normality before ANOVA, and performed statistical analyses using the package ‘stats' in R software version 4.3.1 (R Core Team,2023). To support our interpretations of the degree of genetic and phenotypic differentiation in Sakesphoroides, we inferred its dispersal ability in comparison to other Thamnophilidae species occurring in dry open and humid forest vegetation types. To do so, we used morphometric data from the AVONET dataset (Tobias etal.,2022) to extract measurements and indices related to wing size and shape variation (see TableS5 for the species and number of individuals analysed), which are regarded as good proxies of flight efficiency and dispersal ability in birds (Claramunt,2021; Claramunt & Wright,2017). We considered the following wing attributes: (1) wing Length (length from the carpal joint to the tip of longest primary in millimetres); (2) Kipp's Distance (length from the tip of the first secondary feather to the tip of the longest primary in millimetres); (3) secondary1 (length from the carpal joint to the tip of the first secondary in millimetres); and (4) HandWing Index (100*DK/Lw, where DK is Kipp's distance and Lw is wing length). We used the HandWing Index (HWI) and raw measurements reflecting wing shape and size to perform a Principal Component Analysis (PCA) to determine whether these variables can explain dispersal ability variation between Sakesphoroides and other antbird species with inferred low dispersal ability. We further tested for significant differences in mean HWI between Sakesphoroides and other antbird species as a direct comparison of dispersal capacity, also considering different taxonomic and ecological groupings (i.e. genera and environment type, see TableS5). We checked for normality and homogeneity of variance prior to a Kruskal– Wallis test and a pairwise Wilcox test (Mann–Whitney) if differences in HWI existed. We performed all statistical analyses using the package ‘stats' in R software version 4.3.1 (R Core Team,2023). 2.3 | Vocal analyses We used vocalizations to explore putative differentiation across the SFR. Initially, we searched for qualitative characters by visualizing spectrograms of loudsongs, which are characterized as short series of ca. 10 notes, with the initial notes being sharp and strident, followed by a series of raspy notes (Zimmer etal., 2003). We could not assign homologies among calls due to the small number of recordings across different locations in our sample and the high degree of variation of this vocal type in different stress contexts (i.e. playback, mate contact, presence of predators). 14636409, 2024, 5, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/zsc.12672 by Capes, Wiley Online Library on [25/06/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 490 | CERQUEIRA etal. All sound recordings were standardized before visualization. We converted all files to ‘.WAV’ format, with a sampling rate of 44,100 Hz and bit depth of 16 bits in the mono pattern. Spectrograms were generated and analysed on software Raven Pro 1.5 (Cornell Laboratory of Ornithology) with a Hamming window type, window size of 512 samples, a time grid 90% overlap, and DFT size of 2048 samples. We analysed the syntax and note structure qualitatively through a blind inspection and grouping printed sonograms, followed by an assessment of whether the groupings matched the patterns under study, following the procedure in Carneiro etal.(2012). We also measured some parameters based on spectrograms and oscillograms: number of sharp notes (NN1), duration of all sharp notes including the intervals between notes in seconds (s; DS1), pace of sharp notes section (dividing NN1 by DS1; Pace1), highest and lowest frequency of all sharp notes in hertz (Hz; HighF1 and LowF1), delta frequency of all sharp notes in hertz (difference between HighF1 and LowF1; DF1), peak frequency of all sharp notes in hertz (the frequency at which maximum power occurs within the selection; PeakF1), number of raspy notes (NN2), duration of all raspy notes including the intervals between notes in seconds (DS2), pace of raspy notes section (dividing NN2 by DS2; Pace2), peak frequency of all raspy notes in hertz (PeakF2), number of notes along the entire song (NN), duration of total song including the intervals between notes in seconds (DTS), pace of total song (dividing NN by DTS; Pace), and peak frequency along the entire song in hertz (PeakF). We investigated significant differences in these measurements using an ANOVA with a Tukey test for a posteriori comparison. We tested all measurements for homogeneity of variance and normality before performing ANOVA, we performed statistical analysis using the package ‘stats' in R software version 4.3.1 (R Core Team,2023). 2.4 | DNA extraction, amplification, and sequencing We extracted DNA samples from muscle tissues to sequence two mitochondrial (NADH dehydrogenase subunit 2– ND2 and Cytochrome b – Cytb) and one nuclear markers (Glyceraldehyde 3Phosphate Dehydrogenase – G3PDH). Total DNA was extracted using standard procedures with the phenolchloroform technique (Sambrook et al., 1989). We performed amplifications using a Polymerase Chain Reaction (PCR) under the following amplification profile: 12.5 μL of Master Mix 1x, 8.5 μL of H2O, 1.0 μL (200 ng/μL) of each primer (forward and reverse) for all genes (see TableS6) and 2.0 μL (20 ng) of genomic DNA. Procedures for genes Cytb and G3PDH included an initial cycle of 5 min at 94°C, followed by 35 cycles of 1 min at 94°C, 1 min at 57°C for Cytb and 55°C for G3PDH (annealing temperature), and 1 min at 72°C, with a final extension of 5 min at 72°C. For the ND2 fragment, the PCR reaction consisted of an initial cycle of 5 min at 94°C, followed by 35 cycles of 30 s at 94°C, 1 min at 55°C (annealing temperature), and 30 s at 72°C, with a final extension of 5 min at 72°C. An aliquot of each amplification was loaded in 1% agarose gel to check for the amplification products. Then, the amplified products were purified using PEG8000 (Polietilenoglicol8000) to remove PCR residues. We sequenced the amplicons with a Big Dye Terminator Cycle Sequencing Standard Version 3.1 kits in an automated sequencer model ABI 3130 (Applied Biosystems). Sequences generated in this study were deposited in GenBank (www. ncbi. nlm. nih. gov; Accession Numbers PP842021–PP842121). 2.5 | Phylogenetic analyses and genetic distances We edited and inspected sequences for any insertions, deletions and stop codons, using the software BioEdit 7.1.3 (Hall, 1999). The alignment was performed using ClustalW algorithm implemented in the same software BioEdit 7.1.3. Heterozygous sites of nuclear markers were translated following the IUPAC code. We estimated the evolutionary model that best explained the obtained sequences in jModelTest 2.1.4 (Darriba etal.,2012), and subsequently used in a Bayesian Inference (BI) to estimate phylogenetic relationships among the specimens sequenced with MrBayes 3.1.2 (Ronquist & Huelsenbeck, 2003). Analyses of the concatenated dataset were partitioned by gene. Four parallel simultaneous runs of 3 × 106 generations each were carried out, sampling one tree every 1000 generations. We used the Software TRACER 1.5 (Rambaut & Drummond,2009) to verify consistency of results and to check whether Effective Sample Size (ESS) values were greater than 200 (Drummond etal.,2007). Trees obtained before the Markov chain reached stable and convergent likelihood values were discarded as burnin. To estimate genetic distances between and within lineages recovered in phylogenies we obtained uncorrected pairwise pdistances based on the mtDNA dataset using the software MEGA 5.2 (Tamura etal.,2011). We also compared the genetic divergence between Sakesphoroides lineages with those observed between closely related/sister species pairs of other Neotropical Suboscine passerines (mainly Thamnophilidae; see TableS7). This set of species include both those whose ranges are limited by major Amazonian rivers as well as some species living in sympatry or with 14636409, 2024, 5, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/zsc.12672 by Capes, Wiley Online Library on [25/06/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License | 491 CERQUEIRA etal. allopatric or parapatric ranges not separated by a major river (TableS7). We used sequences of the ND2 marker obtained from this study and GenBank, and analysed them with the software MEGA 5.2 (Tamura etal.,2011) based on uncorrected pairwise pdistances. 2.6 | Coalescencebased species delimitation (BPP) To test for interspecific limits and genetic differentiation within S. cristatus we used the software Bayesian Phylogenetics and Phylogeography (BPP; version 2.2). BPP uses a Bayesian approach to generate probabilities of speciation between closely related taxa, using multilocus sequence data and a phylogenetic hypothesis as a guide tree (Rannala & Yang,2003, 2013; Yang & Rannala,2010). We performed BPP analysis using both algorithms 0 and 1 with different finetuning parameters (ε for 0, and α and m for 1) following the software's recommendations to verify consistency of results. To assess variation of population size parameters, we simulated three scenarios of prior combinations representing different ancestral population sizes and different ages of separation between lineages: (1) large effective population size (Ne) and deep divergence with gamma distribution priors for θ (population size) and τ (divergence time) – G(1, 10) and G(1, 10); (2) small Ne and shallow divergences with gamma distribution priors for θ and τ – G(2, 2000) and G(2, 2000); and (3) large Ne and shallow divergences, with gamma distribution priors for θ and τ – G(1, 10) and G(2, 2000) (Smith etal.,2013). As a guide tree, we used the phylogenetic hypothesis generated by BI described above, running Markov chains for 100,000 generations, and sampling every five generations. BPP tests different topologies, collapsing nodes of the guide tree and counting support values. Speciation probabilities are estimated from the sum of the probabilities of all models for speciation events at each node of the tree guide. Daughter lineages (terminal taxa) from nodes that had speciation probabilities >0.95 under all three prior scenarios were classified as species (Smith etal.,2013). 2.7 | Molecular dating and species tree To estimate the divergence time among S. cristatus lineages revealed by the BI phylogeny estimates, we carried out a species tree approach using the multilocus dataset (mt and nucDNA) in *BEAST (Heled & Drummond,2010). We also estimated a separate time tree using mtDNA in the BEAST 2.4.7 package (Bouckaert etal.,2014). For each multilocus and mitochondrial time tree, we performed two independent runs of 1 × 107 generations, sampling the parameters of the Markov chain every 10,000 generations, until the ESS of all parameters reached scores of 200. We set for the mtDNA dataset (Cytb and ND2) the mutation rate of 2.1% of nucleotide substitutions per million years (Weir & Schluter,2008), whereas that of the nuclear locus (G3PDH) was estimated in comparison to that of the mtDNA rate under relaxed clock and uncorrelated lognormal options and a Yule process as a speciation prior. Based on the obtained results, the first 1000 samples of each run were discarded as burnin. We estimated values of posterior probability and divergence times through a majority rule consensus of the remaining samples. 2.8 | Historical demography To investigate the historical demography of S. cristatus lineages we used the Extended Bayesian Skyline Plot (EBSP; Heled & Drummond,2008) under a linear model in BEAST 2.4.7 (Bouckaert etal.,2014). EBSP estimates changes in effective population sizes over time under a multilocus approach by using the times of coalescent events among gene trees. We used this method to test demographic predictions expected under the Refugia Hypothesis of Pleistocene climatic oscillations and to evaluate for congruence between historical demography and range size changes scenarios predicted by ecological niche modelling for each lineage during the driest periods. We ran the analysis for 1 × 107 generations under an uncorrelated lognormal molecular clock with a substitution rate of 2.1% per million years applied to the mtDNA dataset (Weir & Schluter,2008), using this rate to estimate comparatively that of the nuclear locus. 2.9 | Ecological niche modelling (ENM) To estimate the climatic niche dynamics of the different S. cristatus lineages in the last 120 ka we used 19 bioclimatic layers at 30 arcseconds (~1 km2) for the following temporal window scenarios (see TableS8 for details of bioclimatic layers): (1) current climatic scenario available from the WordClim database (http:// www. world clim. org/ current, Hijmans etal.,2005); (2) Middle Holocene (~6 ka) and Last Glacial Maximum (LGM, ~21 ka) obtained from Ecoclimate (http:// www. ecocl imate. org/ , LimaRibeiro etal.,2015; Varela etal.,2015); and (3) Last Interglacial (LIG, ~120 ka) data obtained following procedures described in OttoBliesner etal.(2006). The climatic data used was based on the same general circulation model (GCM) available for all paleoscenarios: the Community Climate System Model (CCSM). We performed a Pearson's correlation test for all bioclimatic 14636409, 2024, 5, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/zsc.12672 by Capes, Wiley Online Library on [25/06/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 492 | CERQUEIRA etal. variables and removed the most highly correlated (r > 0.8) to avoid collinearity and model overfitting. Thereafter, we selected six bioclimatic variables to use in models: Mean Diurnal Range (BIO2), Temperature Seasonality (BIO4), Annual Precipitation (BIO12), Precipitation Seasonality (BIO15), Precipitation of Warmest Quarter (BIO18) and Precipitation of Coldest Quarter (BIO19). Our occurrence data was partitioned following the ‘checkerboard’ method (Muscarella etal.,2014; Valavi etal.,2018), whereby the occurrence data is divided in geographic grids to maximize the environmental independence and similarity among subsets. We used a ROC's threshold to cut the suitability matrices modelled, which equalizes the omission and commission errors (BarbetMassin etal.,2012). We evaluated the ENMs using the True Skill Statistic (TSS; Allouche et al., 2006), a threshold dependent method ranging from −1 to 1. Negative and positive values close to zero are not better than expected by chance; values between 0.6 and 0.8 denote reasonable fit models, whereas good fit models are indicated by values greater than 0.8, with 1 denoting best model fit (Allouche etal.,2006; Coetzee etal.,2009). We used a combined result of the following four different algorithms to model the species distribution and obtain a more reliable estimate of the environmental niche (Rocchini et al., 2011): Generalized Linear Model (GLM), Maximum Entropy (Maxent), Support Vector Machines (SVM) and Random Forest (RF; Guo et al., 2005, Phillips et al., 2006, Prasad et al., 2006, Schölkopf etal.,2001, Tax & Duin,2004). The final model for current time and those projected for each paleoclimate scenario were obtained using a consensus model for each S. cristatus lineage. We considered only results with TSS values higher than 0.6 across the four algorithms used, presenting maps with the suitability mean of the estimated environmental niche, named ‘ensemble’. We performed all procedures and model fitting described above using the package ‘ENMTML’ (de Andrade etal.,2020) in R software version 4.3.1 (R Core Team, 2023), available at GitHub (https:// github. com/ andre faa/ ENMTML). To test for niche divergence, we performed a niche overlap analysis between the two recovered Sakesphoroides lineages to verify whether climate has influenced their Grinnellian niches (Soberón,2007). We used the same 19 bioclimatic variables and occurrence data from the ENM analysis and performed a calibrated PCA (PCAenv) on the environmental space of both lineages, including all occurrences. We calculated the niche overlap using Schoener's D similarity metric ranging from 0 (no overlap) to 1 (total overlap; Broennimann etal.,2012). We also performed an identity test to check the statistical significance of the obtained niche overlap metrics through 1000 replicates to generate a null distribution through similarity and equivalency tests. If the values of niche overlap metrics ranged within 95% of the simulated null distribution, the null hypothesis (niche overlap) cannot be rejected. We carried out the analysis using a set of packages (‘ecospat’, ‘rgeos', ‘raster’, ‘tidyverse’ and ‘geodata’) in R software version 4.3.1 (R Core Team,2023). 3 | RESULTS 3.1 | Plumage and morphometric analyses Of the 1079 individuals (skins and photographs) analysed, we could not identify any diagnostic plumage differences among males (n = 818), but two main plumage patterns in females (n = 261) were diagnosed mostly across the SFR (Figure1). The first pattern (hereafter plumage pattern 1) is characterized by females with tails showing large black and white bands and some ‘rufouschestnut’ only on the edges of rectrices and near the white bands, in addition to an Amber crest and olive brown back. In contrast, females sharing the second pattern (hereafter plumage pattern 2) have entirely ‘rufouschestnut’ tails, with weak dark brown marks, plus Chestnut crests and CinnamonBrown backs (Table1; FigureS1). We could not detect sexual dimorphism in S. cristatus for the morphometric characters measured according to ANOVA tests. However, when both female and male specimens belonging to the two distinct groups defined based on the plumage of females are contrasted, tail length (TaiL) and bill length from cranium insertion (BL1) were the only morphometric characters that varied significantly (p < .05; Table2). Despite these statistical differences neither measurement can be regarded as diagnostic between the two groups due to broad overlap (Table2). Based on wing size and shape attributes, we found no differences in inferred dispersal ability between Sakesphoroides and other antbird species from both dry and wet environments (FigureS2), including species with recognized low dispersal features and genetic differentiation across Amazonian rivers (FigureS2). The PCA analysis explained 99.8% of total variance in the first two axes (PC1: 65.28%, PC2: 34.51%), with Sakesphoroides having a great overlap in space with other species from both dry and wet environments (FigureS2a–c). While variables related 14636409, 2024, 5, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/zsc.12672 by Capes, Wiley Online Library on [25/06/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License | 493 CERQUEIRA etal. to wing size were positively correlated with PC1, the Handwing index was highly and negatively correlated with PC2 (TableS9). Specimens of Sakesphoroides clustered on the top left corner of the PCA graph and, therefore, were characterized by smaller wing size and Handwing Index values, typically associated with species of lower dispersal capacity. To reinforce this pattern, we found a significant difference in Handwing Index between taxa from distinct dry and wet habitats (p < .05; FigureS2f), with dry habitat species (which includes Sakesphoroides) showing significantly smaller Handwing Index values than wet habitat species (FigureS2d,e). 3.2 | Vocal analyses Based on spectrograms of 95 sound recordings classified as loudsongs, we also detected two diagnosable vocal patterns roughly separated by the SFR in both males and females, consistent with differences detected in female plumage patterns (Figure2). No sexual dimorphism was identified in spectrograms of recordings relative to sound structure and note shape. The first diagnostic loudsong type (hereafter vocal pattern 1), is characterized by an initial series of sharp notes with frequency modulation (rapid increase and decrease, like an FIGURE 1 Geographic distribution of diagnostic plumage characters in Sakesphoroides cristatus females. Green and blue circles represent diagnostic patterns numbered 1 and 2, respectively, recovered from plumage analyses using study skins and digital photographs (see text for details). The darkblue line represents the modern course of the São Francisco River (SFR), with the red dashed lines representing the estimated position of abandoned meanders of a Late Pleistocene paleocourse of the SFR. The colour gradient represents altitudinal variation. Credit photos: Rocílio Ribeiro Rocha (pattern 1) and Oberdan Nunes (pattern 2). Pattern 1 Pattern 2 Crown Amber (Colour 36) Chestnut (Colour 32) Back Olive brown (Colour 28) CinnamonBrown (Colour 33) Throat Pale horn Colour (Colour 92) Pale horn Colour (Colour 92) Breast Buff (Colour 124) Buff (Colour 124) Belly Buff (Colour 124) Buff (Colour 124) Tail Jet Black (Colour 89), White and Amber (Colour 36) bands Amber (Colour 36) and dark Amber TABLE 1 Diagnostic bodypart colour comparisons of female skins belonging to two distinct plumage patterns recovered in Sakesphoroides cristatus. Colour nomenclature follows Smithe(1975). 14636409, 2024, 5, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/zsc.12672 by Capes, Wiley Online Library on [25/06/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 494 | CERQUEIRA etal. Charactersa Pattern 1 Pattern 2 (n = 59) (n = 19) Mean SD MinMax Mean SD Min–Max LW 66.95 (a) 2.06 63–72 67.79 (a) 1.65 64–71 TarL 25.28 (a) 0.93 23.46–26.85 25.32 (a) 1.04 23.69–27.33 TaiL 57.03 (b) 4.04 48–68 61.74 (a) 2.86 56–67 BL1 17.75 (a) 0.73 15.14–19.23 16.87 (b) 0.9 14.63–18.59 BL2 10.09 (a) 0.53 9.08–11.81 10.02 (a) 0.39 9.09–10.67 BW 4.08 (a) 0.38 3.4–4.95 4.26 (a) 0.32 3.61–4.75 BD 5.18 (a) 0.31 4.71–6.08 5.29 (a) 0.28 4.77–5.80 Note: Males were assigned to each group based on the geographic location of females (Figure1). All measurements are in millimetres (mm), with reported sample sizes (n), mean plus standard deviation (±SD), followed by minimummaximum values. Mean values followed by different letters in parenthesis on the same line differ significantly by p < .05 (in bold). aMorphometric characters: BD, bill depth at anterior edge of nostrils; BL1, bill length from cranium insertion; BL2, bill length from anterior edge of nostrils; BW, bill width at anterior edge of nostrils; LW, length of flattened wing; TaiL, tail length; TarL, tarsus length. TABLE 2 Measurements of morphometric characters and statistical comparisons among male and female specimens of Sakesphoroides cristatus belonging to two distinct plumage groups diagnosed only in females (see text for details). FIGURE 2 Geographic distribution of diagnostic loudsong types of Sakesphoroides cristatus recovered during vocal analyses. Green and blue triangles represent the distribution of patterns 1 and 2, respectively. (a) Spectrogram of type 1 loudsong showing the sharp notes with ascending–descending frequency modulation (inverted ‘U' shape), accession number: XC320806; see detailed views of both sharp and raspy notes under the spectrogram; (b) Spectrogram of type 2 loudsong showing the sharp notes with ascending–descendingstabledescending frequency modulation (turned ‘S' shape), accession number: XC229164; see under the spectrogram detailed views of both sharp and raspy notes. The darkblue line represents the current course of the São Francisco River (SFR), with red dashed lines representing the estimated position of abandoned meanders of a late Pleistocene paleocourse of the SFR. The colour gradient represents altitudinal variation. 14636409, 2024, 5, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/zsc.12672 by Capes, Wiley Online Library on [25/06/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License | 495 CERQUEIRA etal. inverted ‘U’ in shape), followed by a short series of final raspy notes (Figure2). The second loudsong type recovered (hereafter vocal pattern 2), has the initial series of sharp notes with a different type of frequency modulation (i.e. rapid increase, decrease, short duration stable and decrease again, in a sigmoid shape), and short final raspy notes (Figure2). Comparisons using ANOVA test revealed seven vocal characters with statistically significant differences between loudsong patterns 1 and 2: number of notes in total song (NN), duration of total song (DTS), pace of total song (PTS), number of sharp notes (NN1), duration of all sharp notes (DS1), highest frequency of all sharp notes (HF1), and delta frequency of all sharp notes (DF1) (Table3). Despite these statistical differences, none of the vocal characters above can be used as diagnostic between the two vocal types due to overlap (Table3). In summary, loudsong pattern 1 is significantly longer, yet slower and lower pitched than loudsong pattern 2. 3.3 | Phylogenetic analyses Our results based on BI phylogenies of the combined mtDNA and nuclear datasets recovered with high statistical support that Sakesphoroides cristatus is not related to other Sakesphorus species, consistent with the topologies in Brumfield and Edwards (2007) and Bravo etal.(2021). Despite the overall uncertainty with respect to the true S. cristatus outgroup, our phylogeny estimates recovered this species as monophyletic (Figure3). Within the monophyletic S. cristatus, two statistically well supported independent genetic groups were recovered roughly replacing each other across the SFR (Figure3; FigureS3), with clade 1 found for the most part west and north of the river and clade 2 mostly east and south of it. Both clades are in close and direct contact on the west bank of the middle SFR in Western Bahia. The uncorrected genetic distance between clades 1 and 2 is 1.8% (standard error ± 0.3%), whereas that within each clade is 0.2% (standard error ± 0.1%). This average pairwise genetic distance is similar to those found between some pairs of closely related ‘biological’ species of antbirds such as Rhegmatorhina berlepschi/Rhegmatorhina hoffmannsi (1%) and Herpsilochmus atricapillus/Herpsilochmus pileatus (1.7%; see TableS7 for complete comparison). TABLE 3 Variation in loudsong characters and statistical comparisons between two song types in Sakesphoroides cristatus. Measurementa Pattern 1 Pattern 2 (n = 19) (n = 30) Mean SD Min–Max Mean SD Min–Max NN 12.74 (a) 1.33 10–15 11.1 (b) 1.42 08–14 DTS 3.04 (a) 0.39 2.35–3.56 2.47 (b) 0.29 1.76–3.06 Pace 4.21 (b) 0.37 3.65–5.09 4.51 (a) 0.39 3.61–5.42 PeakF 1707.94 (a) 97.38 1485.8–1938.0 1669.55 (a) 117.35 1442.7–1894.9 NN1 10 (a) 1.10 08–12 8.8 (b) 1.54 06–13 DS1 2.37 (a) 0.34 1.69–2.87 1.95 (b) 0.28 1.37–2.52 Pace1 4.25 (a) 0.45 3.58–5.20 4.51 (a) 0.47 3.64–5.62 HighF1 2186.44 (b) 210.78 1817.2–2626.0 2380.9 (a) 188.74 1964.4–2778.0 LowF1 576.12 (a) 141.29 368.5–934.2 553.11 (a) 125.85 341.9–788.9 DF1 1610.32 (b) 216.54 1110.0–1975.0 1834.84 (a) 232.75 1175.6–2243.5 PeakF1 1707.94 (a) 97.38 1485.8–1938.0 1662.37 (a) 119.20 1442.7–1894.9 NN2 2.74 (a) 0.93 1–4 2.3 (a) 0.84 1–5 DS2 0.6 (a) 0.22 0.22–1.06 0.6 (a) 0.76 0.14–4.51 Pace2 4.69 (a) 0.92 2.66–6.04 5.07 (a) 1.23 0.22–7.41 PeakF2 1712.46 (a) 198.96 1162.8–1981.1 1689.65 (a) 107.85 1507.3–1938.0 Note: Frequency is presented in hertz (Hz) and duration variables in seconds (s). Pace of notes per second is the total number of notes counted within a particular time interval. Sample sizes (n), mean ± SD, followed by minimummaximum values are presented for each character. For each character, any means in bold followed by different letters in parenthesis depict significant differences at p < .05. aMeasurement keys: DF1, delta frequency of sharp note section (HighF1 − LowF1); DS1, duration of all sharp notes including interval notes; DS2, duration of all raspy notes including interval notes; DTS, duration of total song; HighF1, highest frequency of sharp note section; LowF1, lowest frequency of sharp note section; NN, number of notes along the entire song; NN1, number of sharp notes; NN2, number of raspy notes; Pace, pace of total song; Pace1, pace of sharp notes section; Pace2, pace of raspy notes section; PeakF, peak frequency along the whole song; PeakF1, peak frequency of sharp notes section; PeakF2, peak frequency of raspy notes section. 14636409, 2024, 5, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/zsc.12672 by Capes, Wiley Online Library on [25/06/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 502 | CERQUEIRA etal. confidence intervals do not rule out a Late Pleistocene date (1.313–0.366 Mya), particularly that obtained with the coalescent species tree approach (Figure3). During the Middle Pleistocene, the SFR course became interrupted to the north, where it connected to the Piauí and Parnaíba rivers, and turned into a lacustrine/palustrine system (Mabesoone,1994; Potter,2003). According to the paleolacustrine hypothesis, during the Middle Pleistocene, the SFR became an endorheic drainage emptying into a fluviolacustrine environment in its middle portion between Remanso and Petrolina (Mabesoone, 1994; Rodrigues, 1986, 2006; Tricart, 1974). The changing paleoSFR course and the large swampy environment in the Remanso – Petrolina area could have played a role in isolating the ancestor of S. cristatus and S. niedeguidonae in two populations. Subsequently, during the Mindel glaciation (~450 kya), the paleoSFR course shifted radically southeastward into the Atlantic Ocean, eventually reaching its current position after some extensive meandering south of the modern mouth, as revealed by several surfaces interpreted as paleochannels (King,1956; Mabesoone,1994). The confidence intervals of our estimate for the splitting times between both Sakesphoroides species match this period of extensive changes in the SFR course and could be related to their origin. Indeed, the configuration of the lower SFR Late Pleistocene course south of its modern position is congruent with the geographic variation in phenotypic characters documented between S. cristatus and S. niedeguidonae, such as loudsong and plumage, known to be important features in mate recognition (Isler etal.,1998, 2007; Remsen Jr.,1984). Subsequent to its major shift southeastward, a second drainage shift event probably mediated by erosional processes and climate change moved the SFR lowermost course northward to its current position; evidence found in sediments suggests the estimated position of this recent paleocourse between the modern courses of the Itapicuru and VazaBarris rivers (King,1956). This led to the establishment of a rather recent secondary contact zone between S. niedeguidonae populations from ‘Raso da Catarina’ region (which could have been passively transferred from the left to the right bank of the SFR) and those of S. cristatus, which were prevalent on the right bank of the river (for similar pattern in other species see also Werneck etal.,2015). This pattern of putative recent secondary contact of the two Sakesphoroides species is corroborated by our molecular phylogeny (mainly based on the mitochondrial dataset, with the only nuclear gene sequenced providing inconclusive evidence), which groups specimens S. niedeguidonae from Raso da Catarina in the S. cristatus clade. The incongruence between genotype and phenotype can result either from mitochondrial introgression due recent secondary contact or retention of ancestral polymorphism due to incomplete lineage sorting (Dias etal.,2018; Ferreira etal.,2018). We did not obtain any evidence of actual gene flow analysing plumage and vocal patterns, but either a former selective mitochondrial sweep or past/current gene flow might explain the observed mismatch between genetic and phenotypic characters in S. niedeguidonae Raso da Catarina populations. Future studies should address the dynamics of this contact zone by increasing the number of molecular loci and individuals sampled. Both S. cristatus and S. niedeguidonae are also in apparent contact in Western Bahia Region (WBR, see FigureS6 for detailed views), where S. cristatus has ‘crossed’ onto the left bank of the middle SFR probably mediated by changes in river flow caused by erosion and sedimentation (Barreto,1996; Tricart,1974). This process created forsaken meanders that transferred populations across riverbanks or even connected both banks in drier periods during the establishment of a lacustrine system downriver in the Middle Pleistocene (Barreto,1996; see also below). Our sampling from this particular area indicates congruency between molecular and phenotypic variation in both S. cristatus and S. niedeguidonae, in contrast to what we documented in the Raso da Catarina region. Additionally, we found that S. cristatus and S. niedeguidonae are not syntopic in WBR, but instead separated by ca. 40 km across an area dominated by Cerrado and an anthropogenic landscape resembling a former riparian vegetation. Cerrado /Caatinga ecotones are common in this region, and we could not find any suitable habitat and individuals of both species on this narrow Cerrado patch, concluding that it could work as an environmental barrier preventing their direct contact and possibly gene flow. Nevertheless, occurrence of hybrids or introgression events in these regions cannot be completely ruled out. Recently, some studies have found patterns congruent with genetic structure mediated by the SFR in mammals, lizards, insects, and frogs (Bruschi et al., 2019; CoutinhoAbreu etal.,2008; Faria etal.,2013; Werneck etal.,2015). The role of rivers as barriers and speciation drivers is better understood in the Amazon Forest, and the SFR represents a new system to study complex patterns of speciation with mechanisms including multiple changes in river courses, Quaternary climate change, and neo tectonism. In our comparisons using the Handwing index as a proxy for dispersal ability, we verified that Sakesphoroides spp. are low vagility antbirds like other species living in the understory of Amazonian forest, which is congruent with their habitat selection and behaviour patterns (e.g. small territories and movements through short flights in middle of dense low vegetation). The genetic, phenotypic, and morphometric 14636409, 2024, 5, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/zsc.12672 by Capes, Wiley Online Library on [25/06/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License | 503 CERQUEIRA etal. evidence shown here support the hypothesis that the SFR establishment played a very important role in the diversification of Sakesphoroides by acting as a strong barrier for dispersion, whose effects varied in time and different locations. 4.2 | The influence of quaternary climatic oscillations We also evaluated the influence of Quaternary climatic oscillations in Sakesphoroides using paleodistribution modelling and inferences of past population sizes through time (EBSP). Our results are partially consistent with predictions of the Refugia Hypothesis for Dry Forests (Haffer,1969; Haffer & Prance,2001), supporting both demographic and paleodistribution range expansions during and shortly after the LGM (~22 kya), preceded by smaller population sizes and more restricted distribution ranges during LIG (~120 kya; Figure4). The recovered pattern of sympatry between both species in WBR was likely a secondary contact as supported by paleoenvironmental evidence indicating a reduction in water levels of the middle SFR resulting in increasing sand deposition during hot and dry periods that could have promoted connections and a steppingstone dispersion across opposite banks (Barreto,1996). So, we hypothesized that climatic oscillations after diversification events mediated by the SFR could have shifted the ranges of both Sakesphoroides species, possibly promoting secondary contact by expansion during drier periods and isolation again by retraction during mesic periods, reinforcing their genetic and phenotypic differentiation in areas of sympatry, as in WBR (Bruschi etal.,2019). The Quaternary climatic oscillations promoted niche evolution in some species, mainly in organism with fast life cycles like bees (Silva etal.,2014). But we did not find evidence for Grinnellian niche evolution or divergence between both species of Sakesphoroides, the small niche overlap recovered was not statistically significant indicating that both species cannot be differentiated by occupied niche. Speciation is not commonly associated with an ecological innovation or niche evolution and appears to be more noticeable farther into the past as in genera or family levels (Peterson,2011; Peterson etal.,1999). The Refugia Hypothesis has been tested in the Neotropical region mostly using humid forest taxa (BatalhaFilho etal.,2013; BatalhaFilho & Miyaki,2016; Menezes et al., 2017; Santos et al., 2018; Solomon etal.,2008). Studies focused on Caatinga taxa found evidence of population and/or range expansions as we did for Sakesphoroides (Caetano etal.,2008; CoutinhoAbreu et al., 2008; Faria et al., 2013; Nascimento et al., 2013; Oliveira etal.,2015; Thomé etal.,2016). Recently, Gehara etal.(2017) recovered a strong signal of synchronous population expansion in the Late Pleistocene for reptiles and amphibians with quite different ecological adaptations and life history strategies, indicating a strong role of climatic oscillations in promoting effective population size changes after diversification events in the Caatinga fauna. Both Sakesphoroides species have also expanded at congruent times in the Late Pleistocene, as found in Gehara etal.(2017). Future studies should test these same spatiotemporal patterns of expansion in other Caatinga birds to evaluate for shared responses to climate change among Caatinga organisms. ACKNOWLEDGEMENTS We thank the curators and curatorial assistants for allowing us the use of skins and tissues held in the following institutions: Museu Paraense Emílio Goeldi (MPEG), Universidade Federal de Pernambuco (UFPE), Universidade Federal do Rio Grande do Norte (UFRN), Universidade Estadual de Feira de Santana (UEFS) and Museu de Zoologia da Universidade de São Paulo (MZUSP). We thanks Paul R. Sweet and Thomas J. Trombone from the American Museum of Natural History (AMNH) for providing high quality photographs of the type specimens. Instituto Chico Mendes de Conservação da Biodiversidade (ICMBio) issued collecting permits (#523493). We are especially grateful to Gustavo Gonsioroski, Ciro Albano, Cristine Prates, Chico Rasta, Firmino Filho, André Adeodato and ‘Seu' Carmelo for all support during our fieldwork. To Fernando Pacheco for the valuable information and rich discussion about Wied's itinerary and Gustavo Bravo for discussions and sharing unpublished data during the early stages of this project. Thanks to Marcos Pérsio for the valuable material collected in the Caatinga during many years and all support before and during the project and to Andy and Gill Swash for discussions and suggestion of English names. We also thank field recordists and birders who shared sound recordings and photographs in the following citizen science platforms: WikiAves, Xenocanto and Macaulay Library (Cornell University). PC warmly thanks all bird watchers that acquired his birding tours services making possible the realization of fieldwork, as they indirectly funded this research. Laboratory work related to this paper was funded by a FINEp grant (# 0118003100). PC and GRG were supported by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) Doctoral fellowships (#1537057 and #1537056, respectively). AA is supported by a productivity fellowship from CNPq (309243/20238). 14636409, 2024, 5, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/zsc.12672 by Capes, Wiley Online Library on [25/06/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 504 | CERQUEIRA etal. ORCID Pablo Cerqueira https://orcid.org/0000-0002-7311-6229 Gabriela R. Gonçalves https://orcid. org/0000-0002-3581-4392 Tânia F. Quaresma https://orcid. org/0000-0001-8192-064X Marcelo Silva https://orcid.org/0000-0003-0642-8246 Mauro Pichorim https://orcid. org/0000-0002-9340-9010 Alexandre Aleixo https://orcid. org/0000-0002-7816-9725 REFERENCES Allen, J. A. (1889). On the Maximilian types of south American birds in the American Museum of Natural History. Bulletin of the American Museum of Natural History, 2(19), 68. https:// digit allib rary. amnh. org/ handle/ 2246/ 690 Allouche, O., Tsoar, A., & Kadmon, R. (2006). Assessing the accuracy of species distribution models: Prevalence, kappa and the true skill statistic (TSS). Journal of Applied Ecology, 43(6), 1223– 1232. https:// doi. org/ 10. 1111/j. 13652664. 2006. 01214. x BarbetMassin, M., Jiguet, F., Albert, C. H., & Thuiller, W. (2012). Selecting pseudoabsences for species distribution models: How, where and how many? Methods in Ecology and Evolution, 3(2), 327–338. https:// doi. org/ 10. 1111/j. 2041210X. 2011. 00172. x Barreto, A. M. F. (1996). Interpretação Paleoambiental do Sistema de Dunas Fixadas do Médio Rio São Francisco. Universidade de São Paulo. BatalhaFilho, H., Fjeldså, J., Fabre, P.- H., & Miyaki, C. Y. (2013). Connections between the Atlantic and the Amazonian forest avifauna represent distinct historical events. Journal of Ornithology, 154(1), 41–50. https:// doi. org/ 10. 1007/ s1033 601208667 BatalhaFilho, H., & Miyaki, C. Y. (2016). Late Pleistocene divergence and postglacial expansion in the Brazilian Atlantic Forest: Multilocus phylogeography of Rhopias gularis (Aves: Passeriformes). Journal of Zoological Systematics and Evolutionary Research, 54(2), 137–147. https:// doi. org/ 10. 1111/ jzs. 12118 Bouckaert, R., Heled, J., Kühnert, D., Vaughan, T., Wu, C.- H., Xie, D., Suchard, M. A., Rambaut, A., & Drummond, A. J. (2014). BEAST 2: A software platform for Bayesian evolutionary analysis. PLoS Computational Biology, 10(4), e1003537. https:// doi. org/ 10. 1371/ journ al. pcbi. 1003537 Bravo, G. A., Whitney, B. M., BelmonteLopes, R., Bornschein, M. R., Aristizábal, N., Beco, R., Battilana, J., Naka, L. N., Aleixo, A., Pie, M. R., Silveira, L. F., Derryberry, E. P., & Brumfield, R. T. (2021). Phylogenomic analyses reveal nonmonophyly of the antbird genera Herpsilochmus and Sakesphorus (Thamnophilidae), with description of a new genus for Herpsilochmus sellowi. Ornithology, 138, 1–16. https:// doi. org/ 10. 1093/ ornit hology/ ukab025 Broennimann, O., Fitzpatrick, M. C., Pearman, P. B., Petitpierre, B., Pellissier, L., Yoccoz, N. G., Thuiller, W., Fortin, M.- J., Randin, C., Zimmermann, N. E., Graham, C. H., & Guisan, A. (2012). Measuring ecological niche overlap from occurrence and spatial environmental data. Global Ecology and Biogeography, 21, 481–497. https:// doi. org/ 10. 1111/j. 14668238. 2011. 00698. x Brumfield, R. T., & Edwards, S. V. (2007). Evolution into and out of the Andes: A Bayesian analysis of historical diversification in Thamnophilus antshrikes. Evolution, 61(2), 346–367. https:// doi. org/ 10. 1111/j. 15585646. 2007. 00039. x Bruschi, D. P., Peres, E. A., Lourenço, L. B., De Macedo Bartoleti, L. F., SobralSouza, T., & ReccoPimentel, S. M. (2019). Signature of the paleocourse changes in the São Francisco river as source of genetic structure in neotropical Pithecopus nordestinus (Phyllomedusinae, Anura) treefrog. Frontiers in Genetics, 10(JUL), 1–16. https:// doi. org/ 10. 3389/ fgene. 2019. 00728 Buainain, N., Gaspar, M. L., & de Assis, C. P. (2016). Detailed description and seasonal variation in the diet of the silverycheeked Antshrike Sakesphorus cristatus (Wied, 1831) (Aves: Thamnophilidae) in a Brazilian semiarid forest. Revista Brasileira de Ornitologia, 23(4), 405–416. Caetano, S., Prado, D., Pennington, R. T., Beck, S., OliveiraFilho, A., Spichiger, R., & Naciri, Y. (2008). The history of seasonally dry tropical forests in eastern South America: Inferences from the genetic structure of the tree Astronium urundeuva (Anacardiaceae). Molecular Ecology, 17(13), 3147–3159. https:// doi. org/ 10. 1111/j. 1365294X. 2008. 03817. x Capelli, D., BatalhaFilho, H., & Japyassú, H. F. (2020). Song variation in the Caatinga suboscine silverycheeked Antshrike (Sakesphorus cristatus) suggests latitude and São Francisco River as drivers of geographic variation. Journal of Ornithology, 161(3), 873–884. https:// doi. org/ 10. 1007/ s1033 602001779 - 4 Carneiro, L. S., Gonzaga, L. P., Rêgo, P. S., Sampaio, I., Schneider, H., & Aleixo, A. (2012). Systematic revision of the spotted Antpitta (Grallariidae: Hylopezus macularius), with description of a cryptic new species from Brazilian Amazonia. The Auk, 129(2), 338–351. https:// doi. org/ 10. 1525/ auk. 2012. 11157 Claramunt, S. (2021). Flight efficiency explains difference in natal dispersal distances in birds. Ecology, 102(9), 1–12. https:// doi. org/ 10. 1002/ ecy. 3442 Claramunt, S., & Wright, N. A. (2017). Using museum specimens to study flight and dispersal. In M. S. Webster (Ed.), Emerging frontiers in collectionsbased ornithological research: The extended specimen. Studies in avian biology 50 (pp. 127–141). American Ornithological Society. Coetzee, B. W. T., Robertson, M. P., Erasmus, B. F. N., van Rensburg, B. J., & Thuiller, W. (2009). Ensemble models predict important bird areas in southern Africa will become less effective for conserving endemic birds under climate change. Global Ecology and Biogeography, 18(6), 701–710. https:// doi. org/ 10. 1111/j. 14668238. 2009. 00485. x Costa, W. J. E. M., Amorim, P. F., & Mattos, J. L. O. (2018). Synchronic historical patterns of species diversification in seasonal aplocheiloid killifishes of the semiarid Brazilian Caatinga. PLoS One, 13, 1–10. https:// doi. org/ 10. 1371/ journ al. pone. 0193021 CoutinhoAbreu, I. V., Sonoda, I. V., Fonseca, J. A., Melo, M. A., Balbino, V. Q., & RamalhoOrtigão, M. (2008). Lutzomyia longipalpis s.l. in Brazil and the impact of the Sao Francisco River in the speciation of this sand fly vector. Parasites & Vectors, 1(1), 16. https:// doi. org/ 10. 1186/ 17563305116 Da Silva, J. M. C., Barbosa, L. C. F., Leal, I. R., & Tabarelli, M. (2017). The Caatinga: Understanding the challenges. In J. M. C. da Silva, I. R. Leal, & M. Tabarelli (Eds.), Caatinga the largest 14636409, 2024, 5, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/zsc.12672 by Capes, Wiley Online Library on [25/06/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License | 505 CERQUEIRA etal. tropical dry Forest region in South America (pp. 3–19). Springer International Publishing. https:// doi. org/ 10. 1007/ 978331968339 - 3 Darriba, D., Taboada, G. L., Doallo, R., & Posada, D. (2012). jModelTest 2: More models, new heuristics and parallel computing. Nature Methods, 9(8), 772. de Andrade, A. F. A., Velazco, S. J. E., & De Marco Júnior, P. (2020). ENMTML: An R package for a straightforward construction of complex ecological niche models. Environmental Modelling and Software, 125(December 2019), 104615. https:// doi. org/ 10. 1016/j. envso ft. 2019. 104615 De Araujo, H. F. P., & Da Silva, J. M. C. (2017). The avifauna of the Caatinga: Biogeography, ecology, and conservation. In J. M. C. da Silva, I. R. Leal, & M. Tabarelli (Eds.), Caatinga the largest tropical dry Forest region in South America. Springer International Publishing. https:// doi. org/ 10. 1007/ 978331968339 - 3 de WiedNeuwied, M. (1831). Thamnophilus cristatus – Der Batara mit schwarzer Haube. In Beiträge zur Naturgeschichte von Brasilien (3rd ed., pp. 1002–1006). Biodiversity Heritage Library. de WiedNeuwied, M. (1940). Viagem ao Brasil (1st ed.). Companhia Editora Nacional. Dias, C., Lima, K. A., Araripe, J., Aleixo, A., Vallinoto, M., Sampaio, I., Schneider, H., & Rêgo, P. S. (2018). Mitochondrial introgression obscures phylogenetic relationships among manakins of the genus Lepidothrix (Aves: Pipridae). Molecular Phylogenetics and Evolution, 126, 314–320. https:// doi. org/ 10. 1016/j. ympev. 2018. 04. 017 do Amaral, F. R., Albers, P. K., Edwards, S. V., & Miyaki, C. Y. (2013). Multilocus tests of Pleistocene refugia and ancient divergence in a pair of Atlantic Forest antbirds (Myrmeciza). Molecular Ecology, 22(15), 3996–4013. https:// doi. org/ 10. 1111/ mec. 12361 Drummond, A. J., Ho, S. Y. W., Rawlence, N., & Rambaut, A. (2007). A Rough Guide to BEAST 1.4. http:// code. google. com/p/ beast - mcmc/ downl oad/ list Faria, M. B., Nascimento, F. F., Oliveira, J. A., & Bonvicino, C. R. (2013). Biogeographic determinants of genetic diversification in the mouse opossum Gracilinanus agilis (Didelphimorphia: Didelphidae). Journal of Heredity, 104(5), 613–626. https:// doi. org/ 10. 1093/ jhered/ est039 Ferreira, M., Fernandes, A. M., Aleixo, A., Antonelli, A., Olsson, U., Bates, J. M., Cracraft, J., & Ribas, C. C. (2018). Evidence for mtDNA capture in the jacamar Galbula leucogastra/chalcothorax species complex and insights on the evolution of whitesand ecosystems in the Amazon basin. Molecular Phylogenetics and Evolution, 129, 149–157. https:// doi. org/ 10. 1016/j. ympev. 2018. 07. 007 Franco, F. F., & Manfrin, M. H. (2013). Recent demographic history of cactophilic drosophila species can be related to quaternary palaeoclimatic changes in South America. Journal of Biogeography, 40(1), 142–154. https:// doi. org/ 10. 1111/j. 13652699. 2012. 02777. x Gehara, M., Garda, A. A., Oliveira, E. F., da Fonseca, E. M., Camurugi, F., Magalhães, F. M., Lanna, F. M., Sites, J. W., Jr., Marques, R., SilveiraFilho, R., São Pedro, V. A., Colli, G. R., Costa, G. C., & Burbrink, F. T. (2017). Estimating synchronous demographic changes across populations using hABC and its application for a herpetological community from northeastern Brazil. Molecular Ecology, 26(May), 4756–4771. https:// doi. org/ 10. 1111/ mec. 14239 Gill, F. (2014). Species taxonomy of birds: Which null hypothesis? Auk, 131, 150–161. https:// doi. org/ 10. 1642/ auk13206. 1 Gonçalves, G. S. R., Cerqueira, P. V., Silva, D. P., Gomes, L. B., Leão, C. F., de Andrade, A. F. A., & Santos, M. P. D. (2023). Multitemporal ecological niche modeling for bird conservation in the face of climate change scenarios in Caatinga, Brazil. PeerJ, 11, e14882. https:// doi. org/ 10. 7717/ peerj. 14882 Grantsau, R. (2010). Guia completo para identificação das aves do Brasil (Vol. 2). Vento Verde. Guo, Q., Kelly, M., & Graham, C. H. (2005). Support vector machines for predicting distribution of sudden oak death in California. Ecological Modelling, 182(1), 75–90. https:// doi. org/ 10. 1016/j. ecolm odel. 2004. 07. 012 Haffer, J. (1969). Speciation in Amazonian forest firds. Science, 165, 131–137. Haffer, J., & Prance, G. T. (2001). Climatic forcing of evolution in Amazonia during the Cenozoic: On the refuge theory of biotic differentiation. Amazoniana, 16(3), 579–607. Hall, T. A. (1999). BioEdit: A userfriendly biological sequence alignment editor and analysis program for windows 95/98/NT. Nucleic Acids Symposium Series, 41, 95–98. Heled, J., & Drummond, A. J. (2008). Bayesian inference of population size history from multiple loci. BMC Evolutionary Biology, 8, 289. https:// doi. org/ 10. 1186/ 147121488289 Heled, J., & Drummond, A. J. (2010). Bayesian inference of species trees from multilocus data. Molecular Biology and Evolution, 27(3), 570–580. https:// doi. org/ 10. 1093/ molbev/ msp274 Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G., & Jarvis, A. (2005). Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 25(15), 1965–1978. https:// doi. org/ 10. 1002/ joc. 1276 IBGE. (1985). Atlas Nacional do Brasil. IBGE. Isler, M. L., Isler, P. R., & Whitney, B. M. (2007). Species limits in antbirds (Thamnophilidae): The warbling Antbird (Hypocnemis cantator) complex. The Auk, 124(1), 11–28. https:// doi. org/ 10. 1642/ 00048038(2007) 124% 5B11: SLIATT% 5D2.0. CO% 3B2 Isler, M. L., Isler, P. R., & Whitney, B. M. (1998). Use of vocalizations to establish species limits in antbirds (Passeriformes: Thamnophilidae). The Auk, 115(3), 577–590. https:// doi. org/ 10. 2307/ 4089407 King, L. C. (1956). A geomorfologia do Brasil Oriental. Revista Brasileira de Geografia, 2, 147–265. Lima, P. C., Grantsau, R., Cássia, R., Lima, F. R., LimaNeto, T. N. C., & Silva, L. E. S. (2010). Ninhos de espécies ameaçadas, endêmicas e outras de comportamento reprodutivo pouco conhecido, na pátria da AraraAzuldeLear (Anodorhynchus leari) (Psittaciformes: Psittacidae), destacandose novos dados sobre o comportamento reprodutivo do besourinhodecaudalarga (Phaethornis gounellei) (Apodiformes: Trochilidae) a descrição do ninho da chocadonordeste (Sakesphorus cristatus) (Passeriformes: Thamnophilidae) e do jacucaca (Penelope jacucaca) (Galliformes: Cracidae). Atualidades Ornitológicas, 153, 69–161. LimaRibeiro, M. S., Varela, S.,GonzálezHernández, J.,Oliveira, G.,DinizFilho, J. A. F., &Terribile, L. C. (2015). EcoClimate: A database of climate data from multiple models for past, present, 14636409, 2024, 5, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/zsc.12672 by Capes, Wiley Online Library on [25/06/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 506 | CERQUEIRA etal. and future for macroecologists and biogeographers. Biodiversity Informatics, 10, 1–21. https:// doi. org/ 10. 17161/ bi. v10i0. 4955 Mabesoone, J. M. (1994). Sedimentary basins of Northeast Brazil. Federal University of Pernambuco. Menezes, R. S. T., Brady, S. G., Carvalho, A. F., Del Lama, M. A., & Costa, M. A. (2017). The roles of barriers, refugia, and chromosomal clines underlying diversification in Atlantic Forest social wasps. Scientific Reports, 7(1), 7689. https:// doi. org/ 10. 1038/ s4159 801707776 - 7 Mooney, H. A., Bullock, S. H., & Medina, E. (1995). Introduction. In S. H. Bullock, H. A. Mooney, & E. Medina (Eds.), Seasonally dry tropical forests (pp. 1–8). Cambridge University Press. Muscarella, R., Galante, P. J., SoleyGuardia, M., Boria, R. A., Kass, J. M., Uriarte, M., & Anderson, R. P. (2014). ENMeval: An R package for conducting spatially independent evaluations and estimating optimal model complexity for MAXENT ecological niche models. Methods in Ecology and Evolution, 5(11), 1198– 1205. https:// doi. org/ 10. 1111/ 2041210X. 12261 Nascimento, F. F., Lazar, A., Menezes, A. N., Durans Ada, M., Moreira, J. C., SalazarBravo, J., D'Andrea, P. S., & Bonvicino, C. R. (2013). The role of historical barriers in the diversification processes in open vegetation formations during the Miocene/ Pliocene using an ancient rodent lineage as a model. PLoS One, 8(4), e61924. https:// doi. org/ 10. 1371/ journ al. pone. 0061924 Nascimento, F. F., Pereira, L. G., Geise, L., Bezerra, A. M. R., D'Andrea, P. S., & Bonvicino, C. R. (2011). Colonization process of the brazilian common vesper mouse, Calomys expulsus (Cricetidae, Sigmodontinae): A biogeographic hypothesis. Journal of Heredity, 102(3), 260–268. https:// doi. org/ 10. 1093/ jhered/ esr012 Oliveira, E. F., Gehara, M., SãoPedro, V. A., Chen, X., Myers, E. A., Burbrink, F. T., Mesquita, D. O., Garda, A. A., Colli, G. R., Rodrigues, M. T., Arias, F. J., Zaher, H., Santos, R. M., & Costa, G. C. (2015). Speciation with gene flow in whiptail lizards from a Neotropical xeric biome. Molecular Ecology, 34, 5957–5975. https:// doi. org/ 10. 1111/ mec. 13433 OttoBliesner, B. L., Marshall, S. J., Overpeck, J. T., Miller, G. H., & Hu, A. (2006). Simulating Arctic climate warmth and Icefield retreat in the last Interglaciation. Science, 311(5768), 1751– 1753. https:// doi. org/ 10. 1126/ scien ce. 1120808 Passoni, J. C., Benozzati, M. L., & Rodrigues, M. T. (2008). Phylogeny, species limits, and biogeography of the Brazilian lizards of the genus Eurolophosaurus (Squamata: Tropiduridae) as inferred from mitochondrial DNA sequences. Molecular Phylogenetics and Evolution, 46(2), 403–414. https:// doi. org/ 10. 1016/j. ympev. 2007. 10. 022 Paynter, R. A., Jr., & Traylor, M. A., Jr. (1991). Ornithological gazetteer of Brazil. Museum of Comparative Zoology, Cambridge. Pennington, R. T., Lewis, G. P., & Ratter, J. A. (2006). An overview of the plant diversity, biogeography and conservation of Neotropical savannas and seasonally dry forests. In R. T. Pennington, G. P. Lewis, & J. A. Ratter (Eds.), Neotropical savannas and seasonally dry forests: Plant diversity, biogeography and conservation (pp. 1–29). CRC Press. Pennington, R. T., Prado, D. E., & Pendry, C. A. (2000). Neotropical seasonally dry forests and quaternary vegetation changes. Journal of Biogeography, 27, 261–273. https:// doi. org/ 10. 1046/j. 13652699. 2000. 00397.x/ full Peterson, A. T. (2011). Ecological niche conservatism: A timestructured review of evidence. Journal of Biogeography, 38, 817–827. https:// doi. org/ 10. 1111/j. 13652699. 2010. 02456. x Peterson, A. T., Soberón, J., & SánchezCordero, V. (1999). Conservatism of ecological niches in evolutionary time. Science, 285, 1265–1267. https:// doi. org/ 10. 1126/ scien ce. 285. 5431. 1265 Phillips, S. J., Anderson, R. P., & Schapire, R. E. (2006). Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190(3–4), 231–259. https:// doi. org/ 10. 1016/j. ecolm odel. 2005. 03. 026 Potter, P. E. (2003). Potter 1997 the Mesozoic and Cenozoic paleodrainage of South America a natural history. Journal of South American Earth Sciences, 10(5), 331–344. https:// doi. org/ 10. 1016/ S0895 - 9811(97) 00031 - X Prado, D. E. (2000). Seasonally dry forests of tropical South America: From forgotten ecosystems to a new phytogeographic unit. Edinburgh Journal of Botany, 57(3), 437–461. http:// journ als. cambr idge. org/ abstr act_ S0960 42860 000041X Prado, D. E., & Gibbs, P. E. (1993). Patterns of species distributions in the dry seasonal forests of South America. Annals of the Missouri Botanical Garden, 80(4), 902–927. http:// www. jstor. org/ stable/ 2399937 Prasad, A. M., Iverson, L. R., & Liaw, A. (2006). Newer classification and regression tree techniques: Bagging and random forests for ecological prediction. Ecosystems, 9(2), 181–199. https:// doi. org/ 10. 1007/ s1002 100500541 R Core Team. (2023). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https:// www. Rproje ct. org/ Rambaut, A., & Drummond, A. (2009). TRACER, Version 1.5. http:// beast. bio. ed. ac. uk/ Tracer Rannala, B., & Yang, Z. (2003). Bayes estimation of species divergence times and ancestral population sizes using DNA sequences from multiple loci. Genetics, 164, 1645–1656. Rannala, B., & Yang, Z. (2013). Improved reversible jump algorithms for Bayesian species delimitation. Genetics, 194, 245–253. Ratter, J. A., Askew, G. P., Montgomery, R., & Gifford, D. R. (1978). Observations on forests of some mesotrophic soils in central Brazil. Revista Brasileira de Botânica, 1, 47–58. Remsen, J. V., Jr. (1984). Geographic variation, zoogeography and possible rapid evolution in some Cranioleuca spinetails (Furnariidae) of the Andes. The Wilson Bulletin, 96(4), 515–523. Ribas, C. C., Aleixo, A., Gubili, C., d'Horta, F. M., Brumfield, R. T., & Cracraft, J. (2018). Biogeography and diversification of Rhegmatorhina (Aves: Thamnophilidae): Implications for the evolution of Amazonian landscape during the quaternary. Journal of Biogeography, 45(4), 917–928. https:// doi. org/ 10. 1111/ jbi. 13169 Rocchini, D., Hortal, J., Lengyel, S., Lobo, J. M., JiménezValverde, A., Ricotta, C., Bacaro, G., & Chiarucci, A. (2011). Accounting for uncertainty when mapping species distributions: The need for maps of ignorance. Progress in Physical Geography: Earth and Environment, 35(2), 211–226. https:// doi. org/ 10. 1177/ 03091 33311 399491 Rodrigues, M. T. (1986). Um novo Tropidurus com crista dorsal do Brasil com comentários sobre suas relações, distribuição e origem (Sauria, Iguanidae). Papeis Avulsos de Zoologia. São Paulo, 36(17), 171–179. 14636409, 2024, 5, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/zsc.12672 by Capes, Wiley Online Library on [25/06/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License | 507 CERQUEIRA etal. Rodrigues, M. T. (2006). Lizards, snakes, and Amphisbaenians from the quaternary sand dunes of the middle Rio Sao Francisco, Bahia, Brazil. Journal of Herpetology, 30(4), 513. https:// doi. org/ 10. 2307/ 1565694 Ronquist, F., & Huelsenbeck, J. P. (2003). MrBayes 3: Bayesian phylogenetic inference under mixed models. Bioinformatics, 19(12), 1572–1574. Sambrook, J., Fritsch, E. F., & Maniatis, T. (1989). Molecular cloning: A laboratory manual (2nd ed.). Cold Spring Harbor Laboratory Press. Santos, B. F., Scherrer, M. V., & Loss, A. C. (2018). Neither barriers nor refugia explain genetic structure in a major biogeographic break: Phylogeography of praying mantises in the Brazilian Atlantic Forest. Mitochondrial DNA Part A DNA Mapping, Sequencing, and Analysis, 29, 1284–1292. https:// doi. org/ 10. 1080/ 24701 394. 2018. 1445242 Santos, M. P. D., Santana, A., Soares, L. M., & Sousa, S. (2012). Avifauna of Serra Vermelha, southern Piauí, Brazil. Revista Brasileira de Ornitologia, 20(3), 199–214. Schölkopf, B., Platt, J. C., ShaweTaylor, J., Smola, A. J., & Williamson, R. C. (2001). Estimating the support of a highdimensional distribution. Neural Computation, 13(7), 1443–1471. https:// doi. org/ 10. 1162/ 08997 66017 50264965 Siedchlag, A. C., Benozzati, M. L., Passoni, J. C., & Rodrigues, M. T. (2010). Genetic structure, phylogeny, and biogeography of Brazilian eyelidless lizards of genera Calyptommatus and Nothobachia (Squamata, Gymnophthalmidae) as inferred from mitochondrial DNA sequences. Molecular Phylogenetics and Evolution, 56(2), 622–630. https:// doi. org/ 10. 1016/j. ympev. 2010. 04. 027 Silva, D. P., Vilela, B., De Marco, P., & Nemésio, A. (2014). Using ecological niche models and niche analyses to understand speciation patterns: The case of sister neotropical orchid bees. PLoS One, 9, 1–17. https:// doi. org/ 10. 1371/ journ al. pone. 0113246 Silva, J. M. C., & Bates, J. M. (2002). Biogeographic patterns and conservation in the south American Cerrado : A tropical savanna hotspot. Bioscience, 52(3), 225–233. Silva, S. M., Peterson, A. T., Carneiro, L., Burlamaqui, T. C. T., Ribas, C., SousaNeves, T., Miranda, L. S., Fernandes, A. M., d'Horta, F. M., AraújoSilva, L. E., Batista, R., Bandeira, C. H. M. M., Dantas, S. M., Ferreira, M., Martins, D. M., Oliveira, J., Rocha, T. C., Sardelli, C. H., Thom, G., … Aleixo, A. (2019). A dynamic continental moisture gradient drove Amazonian bird diversification. Science Advances, 5(7), eaat5752. https:// doi. org/ 10. 1126/ sciadv. aat5752 Smith, B. T., Ribas, C. C., Whitney, B. M., HernándezBaños, B. E., & Klicka, J. (2013). Identifying biases at different spatial and temporal scales of diversification: A case study in the Neotropical parrotlet genus Forpus. Molecular Ecology, 22, 483–494. https:// doi. org/ 10. 1111/ mec. 12118 Smithe, F. B. (1975). Naturalist's color guide. American Museum of Natural History. Soberón, J. (2007). Grinnellian and Eltonian niches and geographic distributions of species. Ecology Letters, 10, 1115–1123. https:// doi. org/ 10. 1111/j. 14610248. 2007. 01107. x Solomon, S. E., Bacci, M., Martins, J., Vinha, G. G., & Mueller, U. G. (2008). Paleodistributions and comparative molecular phylogeography of leafcutter ants (Atta spp.) provide new insight into the origins of Amazonian diversity. PLoS One, 3(7), e2738. https:// doi. org/ 10. 1371/ journ al. pone. 0002738 Tamura, K., Peterson, D., Peterson, N., Stecher, G., Nei, M., & Kumar, S. (2011). MEGA5: Molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony Methods. Molecular Biology and Evolution, 28(10), 2731–2739. https:// doi. org/ 10. 1093/ molbev/ msr121 Tax, D. M. J., & Duin, R. P. W. (2004). Support vector data description. Machine Learning, 43(54), 45–66. Taylor, N., & Zappi, D. C. (2004). Cacti of eastern Brazil. Royal Botanic Gardens. Royal Botanic Gardens. Thomé, M. T. C., Sequeira, F., Brusquetti, F., Carstens, B., Haddad, C. F. B., Rodrigues, M. T., & Alexandrino, J. (2016). Recurrent connections between Amazon and Atlantic forests shaped diversity in Caatinga foureyed frogs. Journal of Biogeography, 43(5), 1045–1056. https:// doi. org/ 10. 1111/ jbi. 12685 Tobias, J. A., Sheard, C., Pigot, A. L., Devenish, A. J. M., Yang, J., Sayol, F., NeateClegg, M. H. C., Alioravainen, N., Weeks, T. L., Barber, R. A., Walkden, P. A., MacGregor, H. E. A., Jones, S. E. I., Vincent, C., Phillips, A. G., Marples, N. M., MontañoCentellas, F. A., LeandroSilva, V., Claramunt, S., … Schleuning, M. (2022). AVONET: Morphological, ecological and geographical data for all birds. Ecology Letters, 25, 581–597. https:// doi. org/ 10. 1111/ ele. 13898 Tomotani, B. M., & Silveira, L. F. (2016). A reassessment of the taxonomy of Crypturellus noctivagus (Wied, 1820). Revista Brasileira de Ornitologia, 24(1), 34–45. https:// doi. org/ 10. 1007/ bf035 44327 Tricart, T. (1974). Existence de periodes seches au quaternaire en Amazonie et dans les regions voisines. Revue de Géomorphologie Dynamique, 4, 125–158. Valavi, R., Elith, J., LahozMonfort, J. J., & GuilleraArroita, G. (2018). BLOCKCV: An R package for generating spatially or environmentally separated folds for kfold crossvalidation of species distribution models. Methods in Ecology and Evolution, 10(2), 225–232. https:// doi. org/ 10. 1111/ 2041210X. 13107 Varela, S., LimaRibeiro, M. S., & Terribile, L. C. (2015). A short guide to the climatic variables of the last glacial maximum for biogeographers. PLoS One, 10(6), e0129037. https:// doi. org/ 10. 1371/ journ al. pone. 0129037 Weir, J. T., & Schluter, D. (2008). Calibrating the avian molecular clock. Molecular Ecology, 17, 2321–2328. https:// doi. org/ 10. 1111/j. 1365294X. 2008. 03742. x Werneck, F. P. (2011). The diversification of eastern south American open vegetation biomes: Historical biogeography and perspectives. Quaternary Science Reviews, 30, 1630–1648. https:// doi. org/ 10. 1016/j. quasc irev. 2011. 03. 009 Werneck, F. P., Leite, R. N., Geurgas, S. R., & Rodrigues, M. T. (2015). Biogeographic history and cryptic diversity of saxicolous Tropiduridae lizards endemic to the semiarid Caatinga. BMC Evolutionary Biology, 15(1), 94. https:// doi. org/ 10. 1186/ s1286 201503683 Yang, Z., & Rannala, B. (2010). Bayesian species delimitation using multilocus sequence data. Proceedings of the National Academy of Sciences of the United States of America, 107, 9264–9269. 14636409, 2024, 5, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/zsc.12672 by Capes, Wiley Online Library on [25/06/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 508 | CERQUEIRA etal. Zimmer, K., Isler, M. L., & de Juana, E. (2003). Silverycheeked Antshrike (Sakesphorus cristatus). In J. del Hoyo, A. Elliott, J. Sargatal, D. A. Christie, & E. de Juana (Eds.), Handbook of the birds of the world alive. Linx Edicions. http:// www. hbw. com/ node/ 56656 SUPPORTING INFORMATION Additional supporting information can be found online in the Supporting Information section at the end of this article. How to cite this article: Cerqueira, P., Gonçalves, G. R., Quaresma, T. F., Silva, M., Pichorim, M., & Aleixo, A. (2024). A new antshrike (Aves: Thamnophilidae) endemic to the Caatinga and the role of climate oscillations and drainage shift in shaping cryptic diversity of Neotropical seasonal dry forests. Zoologica Scripta, 53, 487–508. https://doi. org/10.1111/zsc.12672 14636409, 2024, 5, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/zsc.12672 by Capes, Wiley Online Library on [25/06/2025]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License