Molecular Phylogenetics and Evolution 197 (2024) 108111

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Molecular Phylogenetics and Evolution
journal homepage: www.elsevier.com/locate/ympev

Phylogeny and historical biogeography of the swallow family(Hirundinidae) inferred from comparisons of thousands of UCE lociDrew R. Schield a, b, *, 1, Clare E. Brown c, 1, Subir B. Shakya c, d, Gina M. Calabrese a, Rebecca
J. Safran a, Frederick H. Sheldon caDepartment of Ecology and Evolutionary Biology, University of Colorado, Boulder, CO, USA
Department of Biology, University of Virginia, Charlottesville, VA, USA
Museum of Natural Science and Department of Biological Sciences, Louisiana State University, Baton Rouge, LA, USAd
Department of Organismic and Evolutionary Biology and Museum of Comparative Zoology, Harvard University, Cambridge, MA, USAbc

A R T I C L E I N F O

A B S T R A C T

Keywords:
Ancestral reconstruction
Biogeography
Passerines
Species tree
Trait evolution
Ultraconserved elements

Swallows (Hirundinidae) are a globally distributed family of passerine birds that exhibit remarkable similarity inbody shape but tremendous variation in plumage, sociality, nesting behavior, and migratory strategies. As aresult, swallow species have become models for empirical behavioral ecology and evolutionary studies, andvariation across the Hirundinidae presents an excellent opportunity for comparative analyses of trait evolution.
Exploiting this potential requires a comprehensive and well-resolved phylogenetic tree of the family. To address
this need, we estimated swallow phylogeny using genetic data from thousands of ultraconserved element (UCE)loci sampled from nearly all recognized swallow species. Maximum likelihood, coalescent-based, and Bayesian
approaches yielded a well-resolved phylogenetic tree to the generic level, with minor disagreement among in­ferences at the species level, which likely reflect ongoing population genetic processes. The UCE data wereparticularly useful in helping to resolve deep nodes, which previously confounded phylogenetic reconstruction
efforts. Divergence time estimates from the improved swallow tree support a Miocene origin of the family,
roughly 13 million years ago, with subsequent diversification of major groups in the late Miocene and Pliocene.
Our estimates of historical biogeography support the hypothesis that swallows originated in the Afrotropics andhave subsequently expanded across the globe, with major in situ diversification in Africa and a secondary majorradiation following colonization of the Neotropics. Initial examination of nesting and sociality indicates that theorigin of mud nesting – a relatively rare nest construction phenotype in birds – was a major innovation coincident
with the origin of a clade giving rise to over 40% of extant swallow diversity. In contrast, transitions betweensocial and solitary nesting appear less important for explaining patterns of diversification among swallows.

1. Introduction
Swallows (Hirundinidae) are a globally distributed passerine family
containing roughly 88 species. All swallows are aerial insectivores thatshare a common morphology with aerodynamic bodies, long pointed
wings, and short broad bills (see illustrations in Fig. 2). Beyond this basic
shape, however, swallows vary in traits such as plumage, sociality andterritoriality, migratory strategy, and nesting behavior (Turner andRose, 1989; Turner, 2018; Billerman et al., 2020). This variation, against
the background of conserved morphology and basic life history, makes
swallows a valuable system for comparative analyses of trait evolution.

However, the effectiveness of such studies requires a comprehensive,well-resolved phylogenetic tree with which to study trait change overtime, and no such resource is available for swallows despite a substantial
body of phylogenetic inquiry.
Although swallows are nearly globally distributed, the majority oftaxa have breeding distributions that occur in the Afrotropics or Neo­tropics (32 and 19 species, respectively). In contrast, few swallows breedin Australia (four species, three of which are endemic) or Oceania (twospecies, neither of which is endemic). The Nearctic, Panamanian, Ori­
ental, and Palearctic realms each contain between 10 and 13 breeding
species. Only one species, the barn swallow (Hirundo rustica), occupies a* Corresponding author at: Department of Biology, University of Virginia, Charlottesville, VA 22903, USA.
E-mail address: drew.schield@virginia.edu (D.R. Schield).
1
Authors contributed equally.
https://doi.org/10.1016/j.ympev.2024.108111
Received 9 February 2024; Received in revised form 13 May 2024; Accepted 18 May 2024
Available online 25 May 2024
1055-7903/© 2024 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

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Molecular Phylogenetics and Evolution 197 (2024) 108111

breeding distribution that includes more than three geographic realms(Palearctic, Nearctic, and Neotropical), and only two species, H. rustica
and the bank swallow (Riparia riparia), occur in both the Old and New
World. Understanding the development of this geographic distribution
will illuminate not only the family’s geographic origins, but also theevolutionary innovations that have facilitated swallow diversification.
With respect to nesting, swallows can be grouped into three broad
categories (Supplementary Fig. S1; Winkler and Sheldon, 1993): species
that excavate burrows (e.g., Riparia), species that adopt burrows, holes,
or tree cavities (e.g., Tachycineta), and species that build mud-nests.
Mud-nests can be subdivided further into open mud cups (e.g., Hir­undo), enclosed mud cups (e.g., Delichon), and retort-shaped mud-nests,
which have an enclosed cup with an entrance tunnel (e.g., Cecropis).
Mud nesting and cavity adoption generally correspond to geographic
distribution; most African swallows are mud-nesters and mostNeotropical swallows adopt cavities. Swallows also vary in breedingsociality, with some species exhibiting solitary breeding (i.e., only asingle breeding pair at a nesting site), some breeding in small groups,
and others being highly colonial, forming large aggregations of hun­dreds to thousands of breeding pairs (Turner, 2018). As with historicalbiogeography, understanding the evolution of sociality and nesting
behavior will provide substantial insight into the forces responsible forswallow diversification.
Before now, the phylogeny of Hirundinidae has been reconstructed
three times using molecular data. Sheldon and Winkler (1993)
compared single-copy DNA of 21 species in 19 putative genera using
DNA-DNA hybridization. This was followed by comparisons of cyto­
chrome b sequences from the same taxa (Sheldon et al., 1999). Finally,using sequences at three genetic loci, Sheldon et al. (2005) then inferred
relationships among 75 swallow species. These studies provided signif­
icant insight into swallow phylogeny but left several deeper relation­
ships, and relationships of species that were not sampled, unresolved.
Beyond these intergeneric comparisons, multiple phylogenetic andphylogeographic studies have examined more recent patterns of diver­gence within various swallow subgroups, including: cave swallows(Petrochelidon fulva; Kirchman et al., 2000); tree swallows (Tachycineta;
Whittingham et al., 2002; Cerasale et al., 2012; Dor et al., 2012); NewWorld martins (Progne; Moyle et al., 2008); sand martins (Riparia riparia
and R. diluta; Pavlova et al., 2008); the barn swallow subspecies complex(Hirundo rustica) and Hirundo sensu stricto (Zink et al., 2006; Dor et al.,2010); saw-wings (Psalidoprocne; Barrow et al., 2016); rough-winged
swallows (Stelgidopteryx; Babin, 2005); and forest swallows (Atronanus
fuliginosus [previously Petrochelidon fuliginosa]; de Silva et al., 2018).
These studies have addressed inter- and intraspecific relationships but
have not provided insight on deeper relationships within Hirundinidae.
Our objectives in this study were to reconstruct a well-supported,comprehensive phylogenetic hypothesis for Hirundinidae, and to thenuse this tree to estimate historical biogeography and examine character
trait evolution. We addressed the first objective by producing a phylo­
genomic dataset of thousands of ultraconserved element (UCE) se­
quences from at least one individual of the majority of swallow species(82 species and numerous subspecies) and all genera, Next, we recon­
structed the tree using a combination of maximum likelihood inference
from a concatenated data matrix, as well as coalescent-based gene-treesummary methods and Bayesian inference. We then used this phyloge­
netic hypothesis to infer the evolution of sociality, nest type, andgeographic breeding distribution across the swallow family.

(Fry and Smith, 1985), or the rufous-bellied swallow (Cecropis badia),
which has a very restricted range. In most cases we sampled a single
individual per species, but included multiple individuals for species
when prior work (e.g. Sheldon et al., 2005; Moyle et al., 2008; Pavlova
et al., 2008; Dor et al., 2010; Barrow et al., 2016) suggested significant
intraspecific divergence, or when authorities disagree on classification(e.g., the red-rumped swallow [Cecropis daurica] complex). We obtained
DNA from frozen or ethanol preserved tissue samples when possible. For
taxa for which preserved tissues were not available, we sampled frommuseum skins (i.e., ‘historic DNA’). Because swallows are small birds
with tiny toe pads, from which historic DNA samples are typicallysampled, we took pieces of skin from the apteria of the breast to avoid
excessive damage to specimen feet. Such samples have been shown to
produce usable DNA for UCE sequencing (Tsai et al., 2020). In total, we
acquired samples from 122 individuals (99 tissues and 23 skins) repre­
senting 113 distinct species, subspecies, or populations (Supplementary
Table S1). We included other sylvioid species, lanceolated warbler(Locustella lanceolata) and chestnut-capped flycatcher (Erythrocercus
mccallii), as outgroups, using previously generated sequence data from
Moyle et al. (2016).
2.2. DNA extraction, target enrichment, and sequencing
We extracted genomic DNA from frozen and ethanol preserved tissue
samples using QIAGEN DNeasy Blood and Tissue kits following the
manufacturer’s protocol, and from skin samples using a phenol–­chloroform purification and ethanol precipitation protocol optimized
for historic DNA extraction (Tsai et al., 2020). Prior to purification, we
washed skin samples in 100 % ethanol and 1X STE buffer, and digested
them in a solution of buffer ATL, IM DTT, and proteinase K. We wereable to obtain usable DNA from all skin samples with the exception of
the pied-winged swallow (Hirundo leucosoma). We quantified DNA ex­
tracts using a Qubit 2.0 fluorometer (Life Technologies, Inc.). We me­
chanically sheared tissue samples using an Episonic Multi-Functional
Bioprocessor to approximately 500 bp on average, which we assessedusing gel electrophoresis. Historic DNA typically suffers some degree ofdegradation and is sufficiently fragmented to not require further
shearing. This was the case for all but the two Peruvian martin (Progne
murphyi) samples, which we mechanically sheared. We used a KAPA
HyperPrep Kit (Roche Sequencing Systems) to prepare a barcoded li­
brary for Illumina sequencing from each sample by ligating dual indexed
iTru adapters (Glenn et al. 2016) to the fragmented DNA. We followed
the kit protocol but used half reagent volumes for the end-repair and Atailing, adapter ligation, and post-ligation cleanup steps. Tissue libraries
were amplified with nine PCR cycles, while historic DNA libraries were
amplified with twelve cycles. We combined the amplified, barcoded li­
braries into equimolar pools of between seven and nine samples each,comprising 11 tissue pools and three historic DNA pools.
We used hybrid capture to enrich each pool for 5,060 UCE loci. We
first denatured the libraries and hybridized a set of 5,472 biotinylated
RNA probes (Tetrapods-UCE-5Kv1 sold by MYcroarray; Faircloth et al.,2012) to their target sequences on the single-stranded DNA and captured
the resulting probe-target hybrids on streptavidin coated magnetic
beads. This allowed unhybridized, non-target DNA to be washed away.
We then released and amplified the target DNA, following the protocolin the MYbaits manual v3.0.1 through bait-target hybridization, hybrid
binding, and bead washing steps. Tissue libraries were hybridized at
65 ◦ C, and historic DNA libraries at 55 ◦ C. After washing the beads toremove non-target DNA, we resuspended the enriched libraries alongwith the beads in 10 mM Tris-Cl with 0.05 % TWEEN and performed 15
cycles of limited-cycle PCR on the suspension with KAPA HiFi HotStart
polymerase. We purified the PCR product with a 1.2 × or 3.0 × AMPure
bead cleanup for tissue libraries and historic DNA libraries, respectively,
and verified the absence of adapter dimers using an Agilent Bioanalyzer.
We quantified libraries with qPCR using a KAPA Library Quantification
Kit and sequenced the final libraries using 150 bp paired-end reads on an

2. Materials and methods
2.1. Sampling
We obtained samples from 82 of the 88 swallow species recognizedby (Clements et al., 2023), including representatives of all 20 genera(Supplementary Table S1). We were unable to sample the Red Sea
swallow (Petrochelidon perdita), which is known from only one specimen
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bootstrap convergence with the autoMRE criterion with a cutoff of 0.3.
The bootstrapped trees were used to calculate support values for thenodes of the best scoring tree from the initial tree searches. We thenanalyzed the reduced dataset using the same procedure for comparison
to the inferred phylogeny from the full dataset.
We used two coalescent-based approaches to estimate the Hir­undinidae species tree. We first implemented SVDquartets (Chifman andKubatko, 2014,2015) to analyze the full and reduced datasets for directcomparison with concatenated ML analyses. SVDquartets uses a coa­lescent framework to analyze quartets of taxa from site patterns in thealignment, then employs a supertree approach to estimate a species tree
from these quartets. We ran SVDquartets in PAUP* v4.0 (Swofford,2003) to perform species tree inference, specifying L. lanceolata andE. mccallii as a monophyletic outgroup and 100 bootstrap replicates in
the analysis. We then used ASTRAL v5.6.1 (Mirarab et al., 2014; Zhang
et al., 2017) to perform coalescent-based species tree inference on afurther reduced dataset consisting of only tissue samples (i.e., without
Pseudochelidon) to enable broad comparison of deeper topological re­lationships within Hirundininae across analyses. ASTRAL estimates a
species tree from a set of gene trees under the multispecies coalescentmodel. We used PHYLUCE together with RAxML v8.2.11 (Stamatakis,2014) on individual UCE alignments to conduct multi-locus boot­strapping, by which loci, and then sites within loci, are sampled withreplacement (Seo, 2008). We generated 500 multi-locus bootstrappedalignments for each UCE locus and estimated bootstrapped gene trees
from those alignments. We then ran ASTRAL to estimate species trees
from each set of 500 bootstrapped gene trees and constructed a 50 %majority-rule consensus tree from the species trees using SumTrees
v4.4.0 (DendroPy v4.4.0; Sukumaran and Holder, 2010). We performedplotting and annotation of resulting trees in R v4.3.1 (R Core Team,2023) using the packages ape v5.7.1 (Paradis and Schliep, 2019), phy­tools v1.9.16 (Revell, 2012), and treeio v1.25.4 (Wang et al., 2020).

Illumina NovaSeq 6000.
2.3. Processing of sequence data and generation of datasets forphylogenetic inference
We evaluated the quality of demultiplexed sequences using FastQC
v0.11.7(https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) and removed adapter sequences and low quality bases from theraw reads using Illumiprocessor v2.0.9 (Faircloth et al., 2013). Illumi­
processor is a wrapper program for Trimmomatic v0.36 (Bolger et al.,2014), which we implemented with default settings. This included
trimmed leading and trailing bases with Phred33 scores below 5 and 15,
respectively, and scanning reads with a four bp sliding window, trim­
ming the remainder of a read when the average Phred33 score was
below 15. We also removed reads below 40 bp after trimming.
We then generated UCE datasets for phylogenetic inference from thetrimmed read data using PHYLUCE v1.6.3 (Faircloth, 2016). We first
assembled reads for each sample into contigs with SPAdes v3.12.0(Bankevich et al., 2012), implemented with phyluce_assembly_assem­
blo_spades, running SPAdes in single-cell mode with the default k-mer
sizes of 21, 33, and 55 and a coverage threshold of 5. Prior to assembly,
we used the insilico_read_normalization.pl script from Trinity v2.6.6(Grabherr et al., 2011) to normalize reads of four historic DNA samples
which had more than 10 million read pairs. Preliminary analysis
revealed long terminal branch lengths for the majority of skin samples.
To mitigate the effect of low quality data on terminal branch lengths, weused the mapping and correction steps implemented using phyluce_­
workflow to map read data to the assembled contigs of each skin sample
and filter low depth, low quality base calls, using default settings. We
then extracted assembled contigs that matched the UCE loci in the
Tetrapods-UCE- 5Kv1 probe set (available at https://ultraconserved.
org/). We aligned loci matching the probes using Mafft v7.130 (Katoh
et al., 2002; Katoh and Standley, 2013), implemented using phyluce_a­lign_seqcap_align, then trimmed the resulting alignments with Gblocks
v0.91b(Castresana,2000),
using
phyluce_align_get_g­
blocks_trimmed_alignments_from_untrimmed. We used default settings,
with the exception of relaxing the minimum number of sequences
required for a flank position to 65 %. We then generated datasets forphylogenetic analysis by excluding loci that were not recovered in ≥95% of samples. Four historic DNA samples (Congo martin [Riparia cong­ica], one Galápagos martin [Progne modesta], and two Cuban martins[Progne cryptoleuca]) had many fewer recovered UCE loci than theremaining samples, resulting in spurious placement in preliminary
phylogenetic analyses. The remaining P. modesta sample fell within theclade containing the outgroup taxa, a potential result of contamination.
These five samples were removed from downstream analyses, yielding a‘full’ dataset including 118 samples (Supplementary Table S1). For
comparison, we also generated a ‘reduced’ dataset consisting of only
tissue samples and Pseudochelidon species (103 samples). Here, we
explicitly included Pseudochelidon species because a previous analysis
inferred Pseudochelidon to be sister to all other extant swallows (Sheldon
et al., 2005), and it was critical to assess support for this ancestral split
using the current dataset. Removing low quality samples from the ‘full’dataset and further pruning in the ‘reduced’ dataset did not affect the
number of genera represented in analyses.

2.5. Divergence time estimation
We used Bayesian inference to estimate divergence times within
Hirundinidae and to provide a time-calibrated phylogeny for analyses ofancestral character evolution and historical biogeography. Bayesiananalysis of large multi-locus datasets is computationally expensive, so tobalance robust inference with efficiency we sampled five sets of 50 UCEloci at random for analysis. We performed analyses using BEAST2 v2.7.4(Bouckaert et al., 2014), specifying the HKY substitution model with
empirical site frequencies and the optimized relaxed clock model withthe default mean clock rate of 1. We used default priors for additionalsite and clock model parameters, and further specified two normally
distributed most recent common ancestor (MRCA) prior constraints
based upon estimates from Oliveros et al. (2019). We first constrained
the split between outgroup and ingroup taxa to 22 million years ago(MYA) with a standard deviation = 2.5, based on the previously inferreddivergence time between Locustella and swallow taxa (Hirundo andProgne). Second, we set a prior MRCA constraint on the clade containing
all ingroup swallow taxa excluding the saw-wings (Psalidoprocne) andriver martins (Pseudochelidon) to 9 MYA with a standard deviation = 1.5,
based on the previously estimated divergence between Hirundo andProgne; this prior distribution also encompasses late Miocene fossils forputative Hirundo, Delichon, and Riparia species described by Kessler(2013). We applied these priors to each locus set and performed two
independent runs for each using 10 million MCMC generations. Afterassessing chain mixing and convergence among independent runs using
Tracer (Rambaut et al., 2018), we combined posterior samples using
LogCombiner (Bouckaert et al., 2014) and used TreeAnnotator to
generate a maximum clade credibility tree, discarding the first 20 % ofsamples as burn in. Finally, to focus downstream ancestral reconstruc­tion analyses, we pruned the time-calibrated tree to 88 representative
ingroup taxa for which data on geographic range, nest type, and sociality
were available. The majority of remaining tips correspond to species,

2.4. Phylogenetic analysis
We performed phylogenetic inference using concatenated maximum
likelihood (ML) and coalescent-based approaches. For ML, we per­formed 40 independent tree searches (20 random and 20 parsimony
starting trees) using RAxML-NG v0.7.0 (Kozlov et al., 2019) on the
concatenated alignment and selected the best scoring tree. We analyzed
the alignment as a single partition and specified a GTR + GAMMA
substitution model. We assessed support for the topology using 100
bootstrap replicate trees, also generated using RAxML-NG, and verified
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although in a few cases we either grouped clades into a single tip (e.g.,
non-African Cecropis daurica/striolata), or included multiple subspecies
or geographic variants (e.g., subspecies of the plain martin [Riparia
paludicola]), again based on the availability of trait data.

dispersal between the Afrotropical and the Australian or Oceanian
realms, and between the Old World and the New World (other thanbetween the Nearctic and Palearctic). We used AIC to select the bestfitting model to the data and to produce the best reconstruction ofswallow geographic range evolution.

2.6. Historical biogeography and analyses of trait evolution

2.6.2. Ancestral character estimation of sociality and nest type
We performed ancestral character estimation of sociality and nest
type (1) to examine shifts in solitary versus colonial nesting, (2) todetermine the most likely ancestral nest type and the sequence of mudnest evolution, and (3) to relate shifts in nest type to swallow diversi­
fication and geographic range evolution. We reviewed species accounts
in Turner (2018), categorizing sociality and nest type as discrete traits
with the following categories for sociality: strictly solitary breeders,small-group breeders (which includes species that are facultatively sol­
itary or breed in small assemblages), and colonial breeders; and thefollowing categories for nest type: burrow-excavating, cavity- or
burrow-adopting, constructing open-cup mud nests (e.g., Hirundo),
constructing closed-cup mud-nests (e.g., Delichon), and constructing
retort mud-nests (enclosed mud-nests with entrance tunnels: e.g.,
Cecropis). The Mascarene martin (Phedina borbonica) and mountain sawwing (Psalidoprocne fuliginosa) place a nest made of plant material on aledge, in a crevice, or in a similar fashion, and were classified as cavityadopters. We excluded eight taxa from the analysis that are of unknown
sociality, one of which (white-eyed river martin, Pseudochelidon sir­intarae) was also the only species of unknown nest type. We recon­
structed character evolution of sociality and nest type simultaneously on
the Bayesian time-calibrated tree, pruned to remove the eight taxa withmissing trait data, using hidden Markov models in the package corHMM(Beaulieu et al., 2013) in R v4.3.1 (R Core Team, 2023). We allowed alltransition rate parameters in the model to differ, and fit models with 0, 1
and 2 hidden traits, and used AICc scores to select the best model among
these. Such hidden traits allow rate heterogeneity across the phylogeny
to be modeled without necessarily ascribing all observed heterogeneity
to the traits of interest (i.e., sociality and nest type), thereby relaxing theassumption that there is a single transition rate between two statesacross the entire tree (Beaulieu et al., 2013). We then visualized theancestral reconstruction using a stochastic character map of the bestmodel, with posterior probabilities of each character state plotted oninternal nodes.

2.6.1. Ancestral geographic range estimation
We reconstructed the evolution of geographic breeding range acrossHirundinidae, which includes species that breed on every continent
other than Antarctica. We included eight biogeographic realms in theanalysis, modified from Holt et al. (2013). The eight realms are: (A)Afrotropical (including Madagascar); (B) Palearctic, a combination ofHolt et al.’s Palearctic, Sino-Arabian, and Saharo-Arabian realms,
excluding northern North America and Greenland; (C) Oriental; (D)Australian, including New Zealand; (E) Oceanian, including New
Guinea; (F) Nearctic, including northern North America and Greenland;(G) Panamanian, including the Caribbean; and (H) Neotropical. We
downloaded a digitized map of these biogeographic realms (available
from https://macroecology.ku.dk/resources/wallace), and applied
modifications as described above. We then built a presence/absence
matrix describing the breeding range overlap of each swallow taxon
with the eight realms, using digitized distribution maps obtained from
BirdLife International (https://www.birdlife.org) and del Hoyo et al.
(2004). These procedures were conducted in R v4.3.1 (R Core Team,2023) using the packages sp v1.3-1 (Pebesma and Bivand, 2005; Bivand
et al., 2013), rgdal v1.3.6 (Bivand et al., 2018), rgeos v0.4-2 (Bivand andRundel, 2018), maptools v0.9-4 (Bivand and Lewin-Koh, 2018), rasterv2.8-4 (Hijmans, 2018), rworldmap v1.3-6 (South, 2011), and rnatur­alearth v0.1.0 (South, 2017).
To infer the biogeographic history of Hirundinidae, we fit a series ofmodels of geographic range evolution to the pruned time-calibrated
swallow tree and geographic range data using the R package Bio­
GeoBEARS (Matzke, 2018). For a global-scale system such as the Hir­undinidae, the assumptions made by the dispersal, local extinction, andcladogenesis model (DEC; Ree and Smith, 2008) are likely the most
realistic. The DEC model allows two anagenetic processes, dispersal andextinction, and two types of cladogenetic processes, sympatry andvicariance. In both cladogenetic processes, one daughter lineage is al­ways assumed to have a range of only one area, meaning that in vicar­
iant cladogenesis the ancestral range cannot be split evenly between
daughter lineages. This is a reasonable assumption for Hirundinidae, as
the occupied biogeographic realms are large enough for divergence tooccur within a single area. The dispersal-vicariance analysis model(DIVA; Ronquist, 1997; Yu et al., 2010) is broadly similar to the DEC
model, but allows equal division of the ancestral range under vicariant
cladogenesis, and requires that daughter lineages occupy completely
overlapping ranges under sympatric cladogenesis. The BAYAREA model(Landis et al., 2013) allows the same anagenetic processes of dispersal
and extinction as the DIVA and DEC models, but does not allow range
evolution to occur during cladogenesis, meaning that daughter lineages
must inherit a range identical to their ancestor. This assumption renders
the BAYAREA model less plausible for Hirundinidae than the DEC andDIVA models. Both DIVA and BAYAREA are implemented in Bio­
GeoBEARS as likelihood interpretations of the models (i.e., DIVALIKE
and BAYAREALIKE). BioGeoBEARS also expands each model to allow
founder event speciation, in which range expansion into a newgeographic area accompanies cladogenesis (Matzke, 2014). This process
is incorporated by adding a parameter (J) that allows one daughter
lineage to inherit the ancestral range, while the other disperses to
occupy a new area outside of the ancestral range. We compared the fit of
the three models to the data, with and without founder event speciation.
No taxa in the dataset have breeding ranges including more than four
realms, so we set this as the maximum range size. We used dispersal
multipliers to constrain dispersal among regions; we assume that swal­
lows do not disperse directly across vast ocean distances, disallowing

3. Results
3.1. Sequencing results, phylogenetic inference, and divergence dating
Characteristics of sequences produced from skin and preserved tissue
samples differed (Supplementary Table S1). After trimming adaptersand low-quality bases from raw reads, we obtained 2.71–43.82 (mean ±SD = 11.86 ± 11.18) million reads per skin sample and 2.0–19.57 (8.53± 3.33) million reads per tissue sample, with mean trimmed read lengthsof 115 bp and 146 bp among skin and tissue samples, respectively. The
higher read counts for skin samples were driven by an extremely highnumber of reads from four samples (Supplementary Table S1). The
proportion of reads removed during trimming was higher and morevariable among skin samples (0.26 %–28.09 %) than tissue samples,
which had at most 0.16 % reads removed. Trimmed reads were assem­
bled into 1352–512,718 (mean ± SD = 86,392 ± 136,204) contigs per
skin sample and 8323–223,554 (26,579 ± 35,283) contigs per tissue
sample. The number of UCE loci successfully enriched in tissue samples,
including outgroups, ranged from 4503–4830 (mean ± SD = 4767 ± 44)with mean lengths from 705–1521 bp (1,072 ± 132 bp). We recovered
544–4851 (3713 ± 1480) UCE loci from the 16 skin samples retained
after preliminary analysis.
Following the mapping and correction steps, mean locus lengths
from the skin samples range from 161–1087 bp (385 ± 273 bp). The full
118 sample dataset with 95 % complete data per locus includes 4,009
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aligned loci ranging 416–1591 bp in length (mean = 976 bp) and con­taining 0–414 (mean = 106) informative sites, an average of 11 %missing characters, and 35 % GC content. The reduced dataset consistingof only tissue samples and Pseudochelidon (103 samples) with 95 %complete data per locus includes 4,518 aligned loci ranging 394–1973
bp in length (mean = 946 bp) and containing 0–402 (mean = 99)
informative sites, an average of 5 % missing characters, and 37 % GC
content. The further reduced dataset of only tissue samples (101 sam­ples; used for species tree inference within Hirundininae) with 95 %complete data includes 4565 loci ranging 394–1973 bp in length (mean= 943 bp) with 0–400 informative sites (mean = 99), an average of 4 %missing characters, and 37 % GC content. The total aligned sequencelengths for the three datasets are 3.9 Mbp, 4.3 Mbp, and 4.3 Mbp,
respectively. UCE locus dataset summaries are also provided in Table 1.
ML phylogenetic reconstruction using RAxML on the concatenatedalignment yielded a well resolved tree, with strong support for mostrelationships to the species level (Fig. 1). Further, there is complete
support (i.e., bootstrap support = 100) for the monophyly of each genus,
except for the sister relationship between Brazza’s martin (Phedina
brazzae) and banded martin (Neophedina cincta), rendering P. brazzae
and P. borbonica paraphyletic. Most historic DNA samples are charac­terized by long terminal branch lengths, even after correction for low
data quality during UCE locus processing. This is an expected result for
decades-old skin samples with comparatively degraded DNA (McCor­
mack et al., 2016). However, the branch lengths for these samples do notappear to have strongly influenced the overall estimate of the tree to­pology, and there is strong support for their placement within respective
genera, with the only exceptions being Progne murphyi and the Sinaloa
martin (P. sinaloae; bootstrap support = 42 and 35, respectively). The
coalescent-based estimate using SVDquartets is similarly well resolved,
albeit with lower support at several deeper nodes, including the split
between the river martins (Pseudochelidoninae) and Hirundininae andthe split between Psalidoprocne and remaining Hirundininae (Supple­
mentary Fig. S2). The inferred topology is also largely congruent withthe concatenation estimate at the species level, with conflicting re­lationships concentrated at shallower nodes (14 %), the majority ofwhich had low support (i.e., bootstrap support < 70) estimated from one
or both approaches (Supplementary Fig. S3). We performed an enrich­ment test to determine if these conflicting relationships are influenced
by the inclusion of historic DNA samples but find no evidence ofenrichment for conflicting nodes relative to tissue samples (Fisher’s
Exact Test, P-value = 0.314). The concatenation and coalescent esti­mates are nearly completely concordant at the genus level, with the only
exception being the placement of the red-throated swallow (Petrocheli­
don rufigula; a historic DNA sample) as sister to the Petrochelidon +Cecropis clade in the coalescent analysis; P. rufigula is strongly supported
as sister to Preuss’s swallow (P. preussi) in the concatenated analysis. The
concatenation and coalescent topologies inferred from the reduced
dataset are nearly identical to those from the full dataset (Supplemen­tary Figs. S4-S5), except for minor disagreement at shallow nodes within
Hirundo and Riparia and Psalidoprocne and Hirundo in the concatenatedand coalescent analyses, respectively (all of which have relatively low
support values in both full and reduced analyses). The Hirundininae
species tree topology inferred using ASTRAL is further congruent withthe genus-level relationships recovered from the other approaches(Supplementary Fig. S6), with strong local branch posterior probability
support at the majority of deeper nodes.
Consensus from the concatenation and coalescent approaches (aswell as Bayesian inference; Supplementary Fig. S7) provides clear sup­port for the ancestral split between the subfamilies Pseudochelidoninae
and Hirundininae (Fig. 2). Further, there is strong support for four major
clades within Hirundininae, including the saw-wing clade (Psalido­
procne), the mud-nesting clade (Ptyonoprogne, Hirundo, Atronanus, Deli­chon, Petrochelidon, and Cecropis), the clade containing the monotypic
genera Pseudhirundo and Cheramoeca, and finally the clade containing
Old World excavators (Phedina, Neophedina, and Riparia) and New
World endemics (Tachycineta, Progne, Stelgidopteryx, Atticora, Pygoche­lidon, Orochelidon, and Alopochelidon). Here, Psalidoprocne is supported
as sister to the remaining clades and the Pseudhirundo/Cheramoeca cladeis sister to the Old World excavators/New World endemics. The mudnesting clade comprises three subclades, with an initial divergence be­
tween Ptyonoprogne + Hirundo and the other genera followed by a split
between Atronanus + Delichon and Petrochelidon + Cecropis. At shallower
timescales, the consensus among approaches suggests additional lineage
diversity within some clades that is not captured by the present classi­
fication. Examples include the nesting of Psalidoprocne fuliginosa and thewhite-headed saw-wing (P. albiceps) within the black saw-wing(P. pristoptera) clade, rendering P. pristoptera subspecies paraphyletic,
the non-sister relationship between house martin (Delichon urbicum)
subspecies, and the nesting of the striolated swallow (Cecropis striolata)
within C. daurica (Fig. 1; Supplementary Figs. S2, S6).
The Bayesian time-calibrated tree supports a mid-late Miocene originof Hirundinidae, with a median posterior divergence time estimate be­
tween Pseudochelidoninae and Hirundininae of 12.83 MYA (Supple­
mentary Fig. S7). Other major splits are estimated to have occurred
during the late Miocene, including between the saw-wings and otheringroup Hirundininae (median posterior estimate = 11.07 MYA), be­tween mud-nesters and the clade containing Pseudhirundo/Cheramoeca+ Old World excavators/New World endemics (10.31 MYA), and be­
tween Pseudhirundo/Cheramoeca and Old World excavator/New World
endemic clades (9.7 MYA). Subsequent diversification of most genera
occurred during the Pliocene–Pleistocene, though median estimates
within Pseudochelidon and Phedina/Neophedina are comparatively
ancient (6.06 and 7.19 MYA, respectively), during the very late
Miocene.
3.2. Estimation of historical biogeography and trait evolution
We investigated the evolution of geographic breeding ranges acrossHirundinidae by evaluating support for three alternative biogeographic
models, with and without an additional founder event speciation
parameter (J). The inclusion of this parameter significantly increases thelikelihood of the data under all three models (Table 2). The DEC + J andDIVALIKE + J models have similar support on the basis of AIC and
Akaike Weights, and are each better fitting than the BAYAREALIKE + J
model. The DEC model is appropriate for analysis of range evolution inswallows due to the global scale of the system and large geographic
regions contained within the eight biogeographic realms considered in
our analysis. Because the DEC + J is a similarly good fit to the data as the
DIVALIKE + J model and has fewer underlying assumptions, we focus on
the ancestral range reconstructions under the DEC + J model, eventhough results of both models are highly concordant (Supplementary
Fig. S8).
Ancestral range estimation under the DEC + J model supports the
hypothesis that swallows originated in Africa and reached the Palearctic
through multiple independent colonization events (e.g., by the common

Table 1
Summary of UCE locus datasets used in this study under various sampling schemes. Mean values are shown for locus length, informative sites, and missing characters.
Datasetn taxan loci

Locus length

Informative sites

Missing bp

Total Mbp

Full
Reduced
Reduced (no Pseudochelidon)

118
103
101

4009
4518
4565

976
946
943

106
99
99

11 %
5%
4%

3.9
4.3
4.3

5

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Molecular Phylogenetics and Evolution 197 (2024) 108111

Fig. 1. Phylogenetic relationships among Hirundinidae estimated using maximum likelihood on a concatenated matrix of 4009 UCE loci with 95 % complete data
among 118 taxa. Nodal values indicate bootstrap support, and only values below 100 % are shown. Outgroup taxa are not shown. Historic DNA samples are denotedwith dashed terminal branches.

6

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Molecular Phylogenetics and Evolution 197 (2024) 108111

Fig. 2. Consensus phylogenetic relationships among swallow genera based on concatenated maximum likelihood, coalescent species tree, and Bayesian approaches.
The relationships shown are strongly supported across most, if not all approaches. Genera belonging to the two subfamilies Pseudochelidoninae and Hirundininae arelabeled. Phedina and Neophedina form a clade, yet species-level relationships render Phedina paraphyletic, so this branch is labeled (Neo)Phedina. Swallow illus­
trations by Hilary Burn © Lynx Edicions.
Table 2
Support for models of geographic range evolution fitted to the time-calibrated Hirundinidae tree, based on classification of presence or absence of taxa across eightbiogeographic realms. Three basic models are compared: 1) dispersal, local extinction, and cladogenesis (DEC), 2) likelihood interpretations of dispersal-vicarianceanalysis (DIVALIKE), and 3) BAYAREA (BAYAREALIKE). All models were fitted with and without an additional founder event speciation parameter (J). The num­
ber of free parameters, parameter estimates (i.e., rates of range expansion, d, range contraction, e, and jump dispersal weight, j), Akaike information criterion score(AIC), and Akaike weights are given for each model.
Model

Parameters

LnL

d

e

j

AIC

Akaike weight

DIVALIKE + J
DEC + JBAYAREALIKE + J
DIVALIKEDECBAYAREALIKE

3
3
3
2
2
2

− 175.6− 175.9− 177.2− 190.8− 193.9–223.3

0.037
0.032
0.026
0.06
0.05
0.049

0.00690.00670.0072
0.01
0.015
0.17

0.078
0.089
0.1
0
0
0

357.2
357.8
360.4
385.6
391.8
450.7

0.5
0.39
0.11
3.6 × 10-07
1.6 × 10-08
2.6 × 10-21

ancestors of Delichon, Petrochelidon, and Riparia + New World endemics,
respectively, and multiple times within Hirundo; Fig. 3; Supplementary
Fig. S8). Dispersal into the Australian and Oceanian realms also occurredmultiple times (e.g., within Hirundo, Petrochelidon, and Cheramoeca),
although there has not been a substantial degree of subsequent diver­sification within these regions. In contrast, much of extant swallow di­versity resulted from in situ diversification within the Afrotropics,
including the African-endemic Psalidoprocne and within Hirundo andCecropis. Our reconstructions support an African origin of mud nesting.
Major colonization of the New World from the Palearctic occurred
during the late Miocene (~7.5 MYA), with subsequent (primarily
Neotropical) diversification giving rise to Tachycineta, Progne,

Stelgiopteryx, Atticora, Pygochelidon, Orochelidon, and Alopochelidon.
Later colonizations of the New World from the Palearctic occurred
within Hirundo rustica, Riparia riparia, and Petrochelidon species during
the Pliocene and Pleistocene.
We explored the evolution of swallow sociality and nest type by
testing models of trait evolution and reconstructing trait histories acrossthe Hirundinidae phylogeny (Fig. 4). The model including one hidden
trait (AICc = − 180.1) was a better fit than the model with no hidden
traits (AICc = 12619.6) but adding a second hidden trait (AICc − 108.3)
did not result in an improved fit over one hidden trait. We therefore
report the results from the model with one hidden trait.
Sociality appears to be a much more evolutionarily labile trait than7

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Molecular Phylogenetics and Evolution 197 (2024) 108111

Fig. 3. Historical biogeography of Hirundinidae estimated under a DEC + J model based on the time-calibrated Bayesian inference topology. In the model, dispersal
is constrained to not occur between the Afrotropical and either Australian or Oceanian realms or between the Old and New World, except for between the Palearctic
and Nearctic realms. The observed ranges of extant taxa are shown at the tips of the topology, with estimated ancestral ranges shown at the internal nodes. The redand blue arrows indicate the origin of mud nesting and the colonization of the New World, respectively. The eight biogeographic realms in the analysis areabbreviated: A, Afrotropical; B, Palearctic; C, Oriental; D, Australian; E, Oceanian; F, Nearctic; G, Panamanian; H, Neotropical. (For interpretation of the references tocolor in this figure legend, the reader is referred to the web version of this article.)8

D.R. Schield et al.

Molecular Phylogenetics and Evolution 197 (2024) 108111

Fig. 4. Ancestral reconstruction of A) sociality and B) nest type in the Hirundinidae for 80 taxa for which trait data are available. Branches are color-coded by trait toshow a stochastic character map based on the ancestral reconstruction model. Pies at internal nodes show posterior probabilities of each trait; pies at the tips show thetrait data for extant taxa.

nest type (Fig. 4). The root ancestral sociality phenotype is uncertain,
with high probabilities of both coloniality and small group nesting in theswallow common ancestor. Following the split from Pseudochelidoni­nae, the common ancestor of Hirundininae was likely small-group
nesting (Fig. 4A). Our results support that solitary nesting has arisen
at least six times independently, and coloniality at least three times.
However, we note that ancestral node probabilities are equivocal be­
tween two states in some areas of the tree (e.g., solitary and small group

nesting in the Tachycineta clade). There was overall more uncertainty inthe ancestral estimation of sociality than nest type, with the lowest
maximum posterior probability at a node being 49.5 %, and 16 of the 79
nodes having < 80 % maximum posterior probability.
The ancestral character estimation of nest type recovers burrow
excavation as the ancestral state (Fig. 4B). Overall, there are a few majortransitions in nest type, and the trait is otherwise relatively evolution­arily stable. We recover a single transition to building mud-nests, with
9

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Molecular Phylogenetics and Evolution 197 (2024) 108111

open cup mud-nests being the likely ancestral state. Retort mud-nests
likely first occurred in the ancestor of Delichon + (Petrochelidon +Cecropsis), while enclosed mud-nests originated once in the ancestor ofAtronanus + Delichon. Petrochelidon fulva reverted to open cup nestingfrom a mud-retort ancestor, this being the only other origin of open cup
mud nesting. Burrow and cavity adoption appears to be comparatively
labile, having originated four times independently. We infer that thefirst origin of cavity adoption was from a burrow-excavating lineage
following the divergence between Riparia and New World endemics.
Cavity adoption also originated in the Phedina borbonica lineage (froman excavating ancestor), the Tree Martin (Petrochelidon nigricans) lineage(from a mud retort ancestor), and the Psalidoprocne fulginosa lineage(from an excavating ancestor). Although P. nigricans, as a member of the
mud nesting clade, is unique in adopting natural cavities for nestingsites, it nevertheless uses mud to dam the entrance to its nest hole. In
general, our reconstructions estimate high certainty for nest type inancestral nodes, with maximum posterior probabilities at each node
>70 % in all cases, and >95 % in most cases.

bootstraps of 100; Bayesian posterior probabilities of 100 %). The only
exception was ASTRAL analysis using preserved tissue samples only
(posterior probability = 0.52; Supplementary Fig. S6). Broadly, the re­sults from our UCE dataset provide a major advance in resolving re­lationships at deep nodes that have been previously problematic.
Within the major clades of Hirundininae, all genera (except Phedina)
are supported as monophyletic. Moreover, we confirm that the African
mud-nesting forest swallow (Atronanus fuliginosus) is sister to Delichon
rather than the cliff swallows (Petrochelidon). The generic assignment of
this taxon was in doubt until the recent acquisition of modern speci­
mens, and subsequent comparisons of three genes by de Silva et al.
(2018) led to the designation of a new genus, Atronanus, and discovery
of its sister relationship to Delichon. At the intrageneric level, relation­
ships among some taxa can be complicated by population genetic pro­
cesses, such as ongoing or recent gene flow, and poor geographic
sampling, and we experienced mixed results in resolving some of these
problems. The saw-wings (Psalidoprocne) are paramount in this respect.
Our branching pattern disagrees with established classifications (Fig. 1;
Supplementary Figs. S2-S7), as does that of Barrow et al. (2016), which
is based on better taxonomic (if not genomic) sampling. Although thesquare-tailed saw-wing (P. nitens) is clearly sister to other saw-wing
species, based on both morphology and molecules (Barrow et al.,2016; our study), relationships among many other taxa, among them the
12 subspecies of black saw-wing (P. pristoptera), remain uncertain.
Another problematic genus is Cecropis, the group that makes enclosed
mud-nests with long entrance tunnels. Our findings, for example,
contradict the division of C. daurica into red-rumped swallow(C. daurica) and striated swallow (C. striolata), as suggested by Dickinson
and Christidis (2014). Although our sampling of these taxa is notextensive, all analyses indicate that C. striolata is nested within
C. daurica (Fig. 1). With respect to some other intrageneric splits, ourtree supports the division of Delichon urbicum into western house martin(D. urbicum) and Siberian house martin (D. lagopodum) (del Hoyo et al.,2023), and the separation of Ridgway’s rough-winged swallow (Stelgi­
dopteryx ridgwayi) from the northern rough-winged swallow(S. serripennis), as done originally by Ridgway (1904) and subsequently
by Phillips (1986).

4. Discussion
4.1. Phylogeny
We reconstructed the phylogeny of the swallow family, Hir­undinidae, using the most comprehensive taxonomic sampling to date
and a genome-scale dataset including thousands of UCE loci. We foundbroad consensus among concatenated ML, coalescent-based, andBayesian trees in branching to the genus level (Figs. 1-2; SupplementaryFigs. S2-S7). These trees agree both when historic DNA samples areincluded and excluded. Perhaps most importantly, the consensus
phylogenetic hypothesis clarifies swallow relationships at deeper nodes,
which have proved especially problematic in previous analyses (Sheldon
and Winkler, 1993; Sheldon et al., 2005).
The structure of the swallow phylogeny is as follows. Pseudocheli­doninae, comprising the two river martin species (Pseudochelidon), issister to all other swallows (Hirundininae). These two species have arelictual distribution, one in west-central Africa (P. eurystomina) and theother in Indochina (P. sirintarae). Pseudochelidon eurystomina nests in
excavated burrows; nesting of P. sirintarae is unknown. Hirundininae isdivided into four main clades. (1) The saw-wings (Psalidoprocne), of
which there are 5 species and 16 subspecies, are the sister group to therest of Hirundininae. They are restricted to sub-Saharan Africa and nest
in excavated burrows. (2) A clade of largely Old World species that
construct mud-nests. This group includes 39 species in four genera(Hirundo, Delichon, Cecropis, and Petrochelidon). (3) A clade consisting of
the white-backed swallow (Cheramoeca leucosterna) of Australia and thegray-rumped swallow (Pseudhirundo griseopyga) of sub-Saharan Africa.
These two species are nest-hole excavators with a presumably relictual
distribution (i.e., not the result of dispersal across the Indian Ocean).
And (4) an eclectic group comprising the Mascarene species Phedina
borbonica, the African species Neophedina cinta and Phedina brazzae, thelargely Old World genus Riparia (comprising five species), and seven
genera endemic to the Nearctic and Neotropics (Tachycineta, Atticora,
Pygochelidon, Alopochelidon, Orochelidon, Stelgidopterys, and Progne). The
New World endemics build their nests in existing holes or crevices. The
Ripara species, Phedina brazzae, and Neophedina excavate nest burrows,
and P. borbonica builds its nest in crevices or on ledges.
Resolution of all generic relationships within the Hirundininae isnotable because the branching pattern among some groups was unclear
in previous molecular studies. In particular, while earlier studies
discovered the remarkable long-distance relationship between Cher­
amoeca and Pseudhirundo, the position of this clade in the swallow tree
was equivocal, with alternative data and analyses yielding sister re­lationships between it and saw-wings, or mud-nesters, or the New World
endemics (Sheldon and Winkler, 1993; Sheldon et al., 2005). In most of
our analyses, the latter relationship was strongly supported (e.g., ML

4.2. Origins and diversification of the swallow family
Of 88 total taxa included in our biogeographic analyses, 39 (44 %)breed in the Afrotropics and 36 breed exclusively in Africa. Our com­
parisons indicate that this concentration of diversity results from sub­stantial in situ diversification, with major pulses during the Miocene andPliocene. These events include diversification within the saw-wings, aswell as the origin of the common ancestor of Cheramoeca + Pseudhirundo
and the clade containing Phedina, Neophedina, Riparia and New World
endemics. Perhaps the most notable case of in situ diversification in
Africa is the origin and evolution of mud-nesting species, with mud
nesting itself representing a major innovation in swallow evolution(Winkler and Sheldon, 1993; Sheldon et al., 2005) which we discuss inmore detail below. Nearly 60 % of the species breeding in the Afro­tropics are mud-nesters, and there are particularly high rates of African
endemism within Hirundo and Cecropis. Several mud-nesting lineages
subsequently dispersed independently to Eurasia, then into South andSoutheast Asia (Fig. 3). A few of these lineages reached Australia andOceania, which are currently occupied by two species each of Pet­rochelidon and Hirundo; the only other species within the Australian
realm is Cheramoeca leucosterna, resulting from what was likely a muchearlier independent expansion into this region during the Pliocene.
The second most species-rich biogeographic realm is the Neotropics,in which 18 swallow species have breeding distributions, roughly halfthat of the Afrotropics. Most of these species constitute the clade of New
World endemics, the exceptions being Petrochelidon ruficollaris and
Hirundo rustica. We infer that swallow diversity in the Neotropics arose
following the colonization of the Nearctic from the Palearctic. We note10

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Molecular Phylogenetics and Evolution 197 (2024) 108111

that in our biogeographic models we constrained dispersal between the
Old and New World to occur only between the Palearctic and Nearctic
realms. While mid-oceanic dispersal of avian species is possible, as
observed famously in Cattle Egrets (Crosby, 1972), this is a rare phe­nomenon. In contrast, a land connection or near-connection between
North America and Siberia across the Bering Strait was present duringmuch of the Miocene (Hopkins, 1959), and the colonization of the
Nearctic by multiple bird families from the Palearctic has long beenrecognized (Mayr, 1946) and supported in subsequent analyses (e.g.,
Moyle et al., 2016; Sangster et al., 2022). Moreover, because modern
swallows rarely migrate or disperse over long over-water distances(Turner, 2018), the Palearctic-Nearctic dispersal constraint is a reason­
able assumption. With this constraint in place, we estimate that the
major dispersal event to the Nearctic occurred during the late Miocene
roughly 7.5 MYA, giving rise to Tachycineta, Progne, and other lineages
largely endemic to the Neotropics. Dispersal events from the Palearctic
within Petrochelidon and in Hirundo rustica and Riparia riparia occurredmuch later (Zink et al., 2006; Pavlova et al., 2008).
Colonization of the Neotropics within the cavity adopting clade ap­
pears to have been by Nearctic rather than Panamanian ancestors. The
direct colonization of the Neotropics from the Nearctic realm is plau­
sible, based both on seasonal migration of numerous Nearctic-breedingtaxa to Neotropical non-breeding regions, and on the recent establish­
ment of a breeding population of Hirundo rustica in Argentina (Martínez,1983; Winkler et al., 2017). We infer that dispersal into the Panamanianregion by swallows represents secondary independent colonization
events from the Neotropics (e.g., by Tachycineta and Stelgidopteryx) ordirect dispersal by Nearctic ancestors, as in the colonization of the
Carribbean by the Caribbean Martin (Progne dominicensis) (Fig. 3). The
beginning of the Pliocene, at 5.3 MYA, is roughly coincident with thegradual uplift of the Isthmus of Panama, which completed the landconnection between North and South America by about 3 MYA (Smith
and Klicka, 2010; O’Dea et al., 2016). This timing approximately
matches the inferred dispersal to the Panamanian region by cavityadopting lineages.
The location and timing of mud-nester and cavity-adopter radiations
are straightforward to detect because they are consolidated geographi­
cally and a large number of species are involved. Identifying the centerof origin of the swallow family, however, is more difficult. No closely
related sylviid lineages exist for comparison (Oliveros et al., 2019), andthere are only two species of river martins, which have disjunct, relictual
distributions in Africa and Indochina. Recognizing these limitations, ourestimates of divergence time and historical biogeography support
swallow origination in the Afrotropics during the Miocene, roughly 13
MYA (Fig. 3; Supplementary Fig. S7). Alternative hypotheses haveconsidered the possibility that the geographic range of the swallow
ancestor may have been more expansive, covering Eurasia as well as
Africa, with the center of origin at any point in this range. Sheldon et al.
(2005), for example, hypothesized a broad range for ancestral swallow
populations based on the distribution of the two river-martins in Africa
and Indochina and the apparently relictual distribution of the relatively
old, sister genera Cheramoeca and Pseudhirundo in Australia versus Af­
rica. This ancestral distribution would have encompassed Africa andsouthern Asia, leading to the invasion of Australia. Moyle et al. (2016)
also inferred a broad ancestral distribution for the swallow common
ancestor, encompassing much of Africa and Asia. Their inference,
however, was based on sampling of only two swallow species, one ofwhich was Hirundo rustica, which has the largest breeding distribution of
all swallows.
The distribution of Pseudochelidon species presents an especiallyintriguing alternative to an Afrotropical origin. With its extant species incentral Africa and southern Asia, a common ancestor in the Palearctic is
a possible inference. Yet, it seems equally plausible that there was anindependent expansion out of the Afrotropics in the ancestor of Pseu­
dochelidon and extinction of geographically intermediate populations.
We also note that P. sirintarae was very rarely observed and only at asingle locality in Thailand during the putative non-breeding season(Thonglongya, 1968); thus, there is some uncertainty about the extent of
its range and a reasonable possibility that this species is now extinct(Turner, 2018). The Cheramoeca + Pseudhirundo clade, as a member ofthe Hirundininae, is younger than Pseudochelidon, and thus unlikely tohave played a role in the origin of swallows. However, it holds aninteresting ancestral position in the hirundinine tree, having branchedsoon after the saw-wings as sister to the large clade of older African
lineages (Phedina Neophedina, and Riparia) and all New World groups.
This hints at a broad early distribution. Given that our current analysis
dissects the historical biogeography of swallows using data from the
majority of swallow species, we consider it to be the most robust
assessment in support of an African origin. Nevertheless, we recognizethat African and south Asian passerines moved back and forth acrossthat part of the world (Fuchs et al., 2012; Fjeldså 2013), and even into
the New World (Sangster et al., 2022), essentially instantaneously ingeological time, and that our analysis is strongly influenced by the
preponderance of swallow species currently residing in Africa. Thismodern distribution may not have been the situation in the past.
4.3. Major innovations and the evolutionary lability of traits
Our reconstruction of nesting behavior is largely concordant with
Winkler and Sheldon (1993): nest-building behavior is generally highly
conserved; the ancestral state is burrowing; there was one major origin
each of mud nesting (probably in Africa) and cavity adopting (in the
New World endemics); and three independent shifts to cavity adopting
in single-species lineages. Evolutionary conservation of broad nest-type
categories (e.g., cavity, cup, or burrow) is typical at the family level inall birds (Sheldon and Winkler, 1999; Turner, 2018), with some notable
exceptions, as in the ovenbirds (Furnariidae; Zyskowski and Prum,
1999). Our findings suggest that the origin of mud nesting – a relatively
rare nest-construction phenotype – was a key innovation (Heard andHauser, 1995; Sheldon and Whittingham, 1997) coincident with thefounding of the clade comprising over 40 % of extant swallow species.
Both the ancestral swallow nest type (burrow or cavity excavation) andmud nesting are unusual in passerines, which typically build a vegeta­tive cup nest or, less commonly, adopt cavities. While other passerines
incorporate mud into their nests to varying degrees, pure mud pellet
nests of the type constructed by swallows are unique (Winkler and
Sheldon, 1993).
The mud nesting clade appears to have originated during the midMiocene in the Afrotropics. Appropriate nesting sites for burrowexcavating swallows, which require sandy soil, are inherently limited(Silver and Griffin, 2009), and the evolutionary innovation of mud-nest
construction likely allowed swallows to escape that limitation andexpand into areas and habitats where appropriate burrow sites were
scarce. The availability of mud, which is often collected from puddles,
depends on sufficient rainfall during the nest building period, but
excessively wet and humid conditions make nest construction moredifficult, and may even cause completed nests to crumble (Emlen, 1954).
The mid- to late Miocene saw a decrease in rainfall in much of Africa(Feakins and Demenocal, 2010), and this drying trend may have facili­tated the radiation of the mud-nesting clade. This period was alsocharacterized by a worldwide expansion of open, C4-dominated habi­tats, such as grasslands (Cerling et al., 1997), in which swallows thrive.
The origins and transitions between different nesting types alsopresents the opportunity to consider selective pressures and behaviors
associated with nest morphology in a phylogenetic context. When nest
construction behavior is viewed as a genetic process, nest morphology is
a complex phenotype characterized by some combination of shape,material, and site or substrate. As such, categorization tends to differ
across studies (Hall et al., 2013; Price and Griffith, 2017; Nagy et al.,2019) and becomes complicated at large taxonomic scales that neces­sarily include more diverse nest phenotypes (Fang et al., 2018). Nest
type is also subject to a variety of evolutionary pressures, including: egg
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Molecular Phylogenetics and Evolution 197 (2024) 108111

and clutch traits (Nagy et al., 2019); predators, parasites, and broodparasites; sexual selection; availability and competition for sites andmaterials; and the effects of climate on nest materials and nest micro­
climate (Perez et al., 2020). Little is known about the genetic mecha­
nisms or evolutionary development of nest building and morphology(reviewed in Healy et al., 2023) to help provide context for hypotheses
about the frequency or direction of evolutionary transitions in nest type.
However, these trajectories exist (Winkler and Sheldon, 1993; Sheldon
and Winkler, 1999). Studies have found a genetic basis for the complex
burrowing behavior of mice during nest construction (Weber et al.,2013), and this may provide a starting point for genetic studies of nest
construction behavior in other animals.
We find that the original mud-nest was likely the open-cup form
(Fig. 4). Our results differ from Winkler and Sheldon (1993) in that we
found the retort nest likely evolved from the open-cup and preceded theenclosed-cup nest. However, this difference relies upon character esti­
mation at a single node (the common ancestor of retort and enclosed
cup-nesting clades). Enclosed mud-nests differ from retort nests in thatthey lack an entrance tunnel; thus, the transition to enclosed nesting in
Delichon + Atronanus could be viewed as a loss of tunnel building. Suchan evolutionary trajectory of nest ‘simplification’ may not be unusual;for example, open cup nesting repeatedly evolved from enclosed dome
nesting in early passerines (Price and Griffith, 2017). More research on
the genetic and developmental mechanisms of nest construction isneeded to understand whether these transitions can be understood asgains or losses of behavioral modules.
The major dispersal event to the New World took place in the latterpart of the Miocene by the common ancestor of Tachycineta, Progne, andthe other Neotropical endemics, coincident with the inferred transitionof nest type from burrow excavation to secondary cavity adoption. As
with mud nesting in the Afrotropics, the transition from burrow exca­
vation to cavity adoption possibly facilitated the radiation of swallows in
the Nearctic and Neotropics. Winkler and Sheldon (1993) suggested that
secondary cavity adopters were able to exploit the region’s widespread
forests and the cavities of their rich primary cavity-excavating avifauna,and that the formation of major mountain ranges and resulting disjunctareas during the Miocene provided conditions conducive to diversifi­
cation. Also, some taxa (e.g., Orochelidon, Alopochelidon, and Pygocheli­don) build their nests in crevices and niches in rock faces, rather thanadopting tree holes. These would have further benefited from mountainbuilding. Extant richness of primary cavity excavators (relative to sec­
ondary cavity adopters) is high in the Nearctic, but less so in the Neo­tropics (van der Hoek et al., 2020), where most of the New Worldswallow diversity is currently found. It is possible that ecological op­
portunity for cavity adopters in the Neotropics was higher in the late
Miocene than today due to subsequent niche filling. Further, the ratio ofprimary:secondary cavity nesters is also very high in central Africa, yetcavity adoption occurs in only one swallow species there (Psalidoprocne
fuliginosa). The circumstances surrounding the Neotropical swallow ra­
diation are intriguing and merit further study.
In contrast to nest construction, transitions in sociality were common
within major swallow clades. This is consistent with high evolutionary
lability of coloniality found across birds (Rolland et al., 1998). In
particular, solitary nesting frequently evolved from small-group nesting,and once from colonial nesting at the origin of Cecropis. Small-group
nesting also evolved multiple times from solitary ancestors (twice
within Hirundo). Interestingly, coloniality evolved directly from solitarynesters, evidently without transitioning through small group nesting in
the ancestor of Delichon and Petrochelidon + Cecropis and possibly also in
the ancestor of Riparia (although certainty of the solitary ancestor islower in this case). Colonial nesting is most common in the mud-nesters,
although burrow excavators (Riparia and Pseudochelidon eurystomina)
and one cavity-adopter (Tachycineta euchrysea) also nest colonially.
Burrowing species may have also tended to nest in groups due to scarcity
of suitable vertical nesting sites, limited by both landscape and soil
types. Coloniality is rare among secondary cavity adopters in many bird

species (Eberhard, 2002), presumably because this would require theavailability of a highly clumped distribution of cavities provided byprimary excavators.
4.4. Future directions
Although we find strong support for generic relationships, we also
observe several instances of discordance between concatenated ML andcoalescent-based species tree approaches at the species level (Supple­
mentary Fig. S3). In some cases, conflicting relationships were highly
supported in both approaches. These discrepancies point to interesting
avenues of future inquiry, especially into ongoing population genetic
processes (e.g., incomplete lineage sorting and introgression) in suchgroups as saw-wings, several mud-nesting groups, rough-wings (Stelgi­
dopteryx), and tree swallows (Tachycineta). An additional considerationis that data from UCEs may be less helpful at resolving relationships atvery shallow evolutionary timescales (Carter et al., 2023).
The highly supported, time-calibrated species level phylogenetic treepresented here provides the opportunity for future comparative studiesof trait evolution. Swallows are an excellent system in which to explore
trait innovation and its relationship to diversification, due to their global
distribution and radiations in both Africa and the Neotropics. The evo­lution of migratory strategy is of particular interest in this group; there
are multiple independent origins of long-distance migration in the Hir­undinidae, as well as intraspecific variation in migration behavior (e.g.,
migratory divides on three continents in the Hirundo rustica species
complex [Hobson et al., 2012,2015; Scordato et al., 2020; Turbek et al.,2022], and the migratory falloff and seasonal breeding reversal in
Argentine H. rustica erythrogaster [Garcia-Perez et al., 2013]). It is
plausible that variation in migratory traits (e.g., timing, route, anddistance) has had a substantial influence on swallow diversification,with long-distance migration presenting a means for dispersal andcolonization of new geographic regions followed by in situ speciation
events. Hirundinidae also includes numerous non-migratory species or
species that exhibit short-distance dispersal, and natural variation
among swallows in sedentary versus migratory life histories presents a
useful framework for testing whether migration is a catalyst or deterrent
to diversification. The detailed biogeographic hypotheses provided here
lend important context for the evolution of migratory behavior that canbe leveraged in future studies.
5. Data Accessibility
Data supporting the conclusions of this study are available from the
NCBI short-read archive (accession PRJNA1117501). The computa­
tional workflow and associated analysis scripts used in this work areavailable at https://github.com/drewschield/hirundinidae_phylogeny.
CRediT authorship contribution statement
Drew R. Schield: Writing – review & editing, Writing – originaldraft, Visualization, Validation, Supervision, Software, Resources,
Project administration, Methodology, Investigation, Funding acquisi­
tion, Formal analysis, Data curation, Conceptualization. Clare E.
Brown: Writing – review & editing, Writing – original draft, Visualiza­
tion, Software, Resources, Project administration, Methodology, Inves­tigation, Funding acquisition, Formal analysis, Data curation,
Conceptualization. Subir B. Shakya: Writing – review & editing, Soft­ware, Methodology, Formal analysis, Data curation. Gina M. Calabrese:
Writing – review & editing, Writing – original draft, Visualization,
Software, Methodology, Investigation, Funding acquisition, Formal
analysis, Data curation. Rebecca J. Safran: Writing – review & editing,Writing – original draft, Supervision, Project administration, Funding
acquisition, Conceptualization. Frederick H. Sheldon: Writing – review& editing, Writing – original draft, Supervision, Resources, Project
administration, Methodology, Investigation, Funding acquisition, Data
12

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Molecular Phylogenetics and Evolution 197 (2024) 108111

curation, Conceptualization.

Bouckaert, R., Heled, J., Kuhnert, D., Vaughan, T., Wu, C.H., Xie, D., Suchard, M.A.,
Rambaut, A., Drummond, A.J., 2014. BEAST 2: a software platform for Bayesianevolutionary analysis. PLoS Comput. Biol. 10, e1003537.
Carter, J.K., Kimball, R.T., Funk, E.R., Kane, N.C., Schield, D.R., Spellman, G.M.,
Safran, R.J., 2023. Estimating phylogenies from genomes: a beginners review ofcommonly used genomic data in vertebrate phylogenomics. J. Hered. 114, 1–13.
Castresana, J., 2000. Selection of conserved blocks from multiple alignments for their use
in phylogenetic analysis. Mol. Biol. Evol. 17, 540–552.
Cerasale, D.J., Dor, R., Winkler, D.W., Lovette, I.J., 2012. Phylogeny of the Tachycineta
genus of New World swallows: Insights from complete mitochondrial genomes. Mol.
Phylogenet. Evol. 63, 64–71.
Cerling, T.E., Harris, J.M., MacFadden, B.J., Leakey, M.G., Quade, J., Eisenmann, V.,
Ehleringer, J.R., 1997. Global vegetation change through the Miocene/Pliocene
boundary. Nature 389, 153–158.
Chifman, J., Kubatko, L., 2014. Quartet inference from SNP data under the coalescentmodel. Bioinformatics 30, 3317–3324.
Chifman, J., Kubatko, L., 2015. Identifiability of the unrooted species tree topology
under the coalescent model with time-reversible substitution processes, site-specificrate variation, and invariable sites. J. Theor. Biol. 374, 35–47.
Clements, J.F., Rasmussen, P.C., Schulenberg, T.S., Iliff, M.J., Fredericks, T.A.,
Gerbracht, J.A., Lepage, D., Spencer, A., Billerman, S.A., Sullivan, B.L., Wood, C.L.,
2023. The eBird/Clements checklist of Birds of the World v2023.
Crosby, G.T., 1972. Spread of the cattle egret in the Western Hemisphere. Bird-Banding
205–212.
de Silva, T.N., Fernando, S.W., Robbins, M.B., Cooper, J.C., Fokam, E.B., Peterson, A.T.,
2018. Recognition of a new generic-level swallow taxon from central Africa. J. Avian
Biol. 49, e01698.
del Hoyo, J., Elliott, A., Christie, D.A. (Eds.), 2004. Handbook of the Birds of the World.
Vol. 9. Cotingas to Pipits and Wagtails. Lynx Edicions, Barcelona.
del Hoyo, J., Turner, A., Kirwan, G.M., Collar, N., Boesman, P.F.D., 2023. WesternHouse-Martin (Delichon urbicum), version 1.0.
Dickinson, E.C., Christidis, L., 2014. The Howard and Moore complete checklist of thebirds of the world, 4th ed., vol. 2. Eastbourne, UK Aves Press. Sch.
Dor, R., Safran, R.J., Sheldon, F.H., Winkler, D.W., Lovette, I.J., 2010. Phylogeny of thegenus Hirundo and the Barn Swallow subspecies complex. Mol Phylogenet Evol 56,
409–418.
Dor, R., Carling, M.D., Lovette, I.J., Sheldon, F.H., Winkler, D.W., 2012. Species trees forthe tree swallows (Genus Tachycineta): an alternative phylogenetic hypothesis to themitochondrial gene tree. Mol. Phylogenet. Evol. 65, 317–322.
Eberhard, J.R., 2002. Cavity adoption and the evolution of coloniality in cavity-nesting
birds. Condor 104, 240–247.
Emlen, J.T., 1954. Territory, nest building, and pair formation in the cliff swallow. Auk71, 16–35.
Faircloth, B.C., 2016. PHYLUCE is a software package for the analysis of conserved
genomic loci. Bioinformatics 32, 786–788.
Faircloth, B.C., McCormack, J.E., Crawford, N.G., Harvey, M.G., Brumfield, R.T.,
Glenn, T.C., 2012. Ultraconserved elements anchor thousands of genetic markers
spanning multiple evolutionary timescales. Syst. Biol. 61, 717–726.
Faircloth, B.C., Sorenson, L., Santini, F., Alfaro, M.E., 2013. A phylogenomic perspectiveon the radiation of ray-finned fishes based upon targeted sequencing of
ultraconserved elements (UCEs). PLoS One 8, e65923.
Fang, Y.-T., Tuanmu, M.-N., Hung, C.-M., 2018. Asynchronous evolution ofinterdependent nest characters across the avian phylogeny. Nat. Commun. 9, 1863.
Feakins, S.J., Demenocal, P.B., 2010. Global and African regional climate during the
Cenozoic. Cenozoic Mamm. Africa 45–56.
Fjeldså, J., 2013. The global diversification of songbirds (Oscines) and the build-up of the
Sino-Himalayan diversity hotspot. Avian Res. 4, 132–143.
Fry, C.H., Smith, D.A., 1985. A new swallow from the Red Sea. Ibis 127, 1–6.
Fuchs, J., Irestedt, M., Fjeldså, J., Couloux, A., Pasquet, E., Bowie, R.C.K., 2012.
Molecular phylogeny of African bush-shrikes and allies: tracing the biogeographic
history of an explosive radiation of corvoid birds. Mol. Phylogenet. Evol. 64, 93–105.
Garcia-Perez, B., Hobson, K.A., Powell, R.L., Still, C.J., Huber, G.H., 2013. Switchinghemispheres: a new migration strategy for the Disjunct Argentinean breeding
population of Barn Swallow (Hirundo rustica). PLoS One 8, e55654.
Grabherr, M.G., Haas, B.J., Yassour, M., Levin, J.Z., Thompson, D.A., Amit, I.,
Adiconis, X., Fan, L., Raychowdhury, R., Zeng, Q., 2011. Full-length transcriptome
assembly from RNA-Seq data without a reference genome. Nat. Biotechnol. 29, 644.
Hall, Z.J., Street, S.E., Healy, S.D., 2013. The evolution of cerebellum structure correlateswith nest complexity. Biol. Lett. 9, 20130687.
Healy, S.D., Tello-Ramos, M.C., Hébert, M., 2023. Bird nest building: visions for the
future. Philos. Trans. R. Soc. B 378, 20220157.
Heard, S.B., Hauser, D.L., 1995. Key evolutionary innovations and their ecologicalmechanisms. Hist. Biol. 10, 151–173.
Hijmans, R.J., 2018. raster: Geographic data analysis and modeling. R package.
Hobson, K.A., Møller, A.P., Van Wilgenburg, S.L., 2012. A multi-isotope (δ13C, δ15N,
δ2H) approach to connecting European breeding and African wintering populationsof barn swallow (Hirundo rustica). Animal Migration 1, 8–22.
Hobson, K.A., Kardynal, K.J., Van Wilgenburg, S.L., Albrecht, G., Salvadori, A.,
Cadman, M.D., Liechti, F., Fox, J.W., 2015. A Continent-Wide Migratory Divide in
North American Breeding Barn Swallows (Hirundo rustica). PLoS One 10, e0129340.
Holt, B.G., Lessard, J.-P., Borregaard, M.K., Fritz, S.A., Araújo, M.B., Dimitrov, D.,
Fabre, P.-H., Graham, C.H., Graves, G.R., Jønsson, K.A., 2013. An update ofWallace’s zoogeographic regions of the world. Science 339, 74–78.
Hopkins, D.M., 1959. Cenozoic History of the Bering Land Bridge: the seaway between
the Pacific and Arctic basins has often been a land route between Siberia and Alaska.
Science 129, 1519–1528.

Declaration of Competing Interest
The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to influence
the work reported in this paper.
Data availability
The data and code used in this study are freely available via public
repositories (NCBI and GitHub).
Acknowledgments
The specimens and tissues used in this study were collected bydedicated field workers from the Academy of Natural Sciences of Phil­
adelphia, American Museum of Natural History, Cornell University
Museum of Vertebrates, Field Museum of Natural History, Louisiana
State University Museum of Natural Science, Museum of Vertebrate
Zoology, Natural History Museum of Los Angeles County, Smithsonian
Institution, University of Kansas Natural History Museum, University ofMichigan Museum of Zoology, University of Washington Burke Museum,and Yale Peabody Museum, with essential help from colleagues in theAmericas, Europe, Africa, Asia, and Australia. Data collection for thiswork was supported by the OpenWings project (https://www.openw­
ings.org/) and associated National Science Foundation (NSF) grants(DEB-1655559, DEB-1655624, DEB-1655683, and DEB-1655736). The
project was also supported by NSF grants DBI-1906188 to DRS, DBI2209166 to GMC, IOS 1856266 to RJS, DEB 1241059 to FHS, and by
OpenWings, Louisiana Board of Regents, American Ornithologists
Union, LSU Biograds, and LSU Museum of Natural Science grants to CEB.
We are grateful to David Winkler for providing the early inspiration forthis work and helping to collect many of the swallows used in the study.
We are also grateful to Anna Hiller, Brant Faircloth, Jessie Salter, andCarl Oliveros for assistance with data generation and suggestions foranalyses. We thank Daniel Field and Daniel Ksepka for information
about swallow fossils and suggestions for calibrations in divergence time
estimation.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.
org/10.1016/j.ympev.2024.108111.
References
Babin, M.J., 2005. Geographic Variation and Speciation in Roughwinged Swallows(Hirundinidae: Stelgidopteryx). Louisiana State University and Agricultural &Mechanical College.
Bankevich, A., Nurk, S., Antipov, D., Gurevich, A.A., Dvorkin, M., Kulikov, A.S., Lesin, V.
M., Nikolenko, S.I., Pham, S., Prjibelski, A.D., 2012. SPAdes: a new genome assembly
algorithm and its applications to single-cell sequencing. J. Comput. Biol. 19,
455–477.
Barrow, L.N., Dalton, D.L., Kotze, A., Evans, S.W., 2016. Geographically widespread
mitochondrial lineages of the African saw-wings inconsistent with species
boundaries. Ostrich 87, 271–275.
Beaulieu, J.M., O’Meara, B.C., Donoghue, M.J., 2013. Identifying hidden rate changes inthe evolution of a binary morphological character: the evolution of plant habit inCampanulid Angiosperms. Syst. Biol. 62, 725–737.
Billerman, S.M., Keeney, B.K., Rodewald, P.G., Schulenberg, T.S., 2020. Swallows(Hirundinidae).
BirdLife International. 2021. IUCN Red List for birds. http://www.birdlife.org.
Bivand, R., Lewin-Koh, N., 2018. maptools: Tools for handling spatial objects. R package.
Bivand, R., Rundel, C., 2018. rgeos: Interface to geometry engine - Open source (’GEOS’).
R package.
Bivand, R., Keitt, T.H., Rowlingson, B., 2018. rgdal: Bindings for the Geospatial Data
Abstraction Library. R package.
Bivand, R.S., Pebesma, E., Gómez-Rubio, V., Bivand, R.S., Pebesma, E., Gómez-Rubio, V.,2013. Spatial data import and export. Appl. Spat. Data Anal. with R 83–125.
Bolger, A.M., Lohse, M., Usadel, B., 2014. Trimmomatic: a flexible trimmer for Illumina
sequence data. Bioinformatics 30, 2114–2120.

13

D.R. Schield et al.

Molecular Phylogenetics and Evolution 197 (2024) 108111
Sangster, G., Cibois, A., Reddy, S., 2022. Pteruthiidae and Erpornithidae (Aves:
Corvides): two new family-group names for babbler-like outgroups of the vireos(Vireonidae). Bull. Br. Ornithol. Club 142, 239–243.
Scordato, E.S.C., Smith, C.C.R., Semenov, G.A., Liu, Y., Wilkins, M.R., Liang, W.,
Rubtsov, A., Sundev, G., Koyama, K., Turbek, S.P., Wunder, M.B., Stricker, C.A.,
Safran, R.J., 2020. Migratory divides coincide with reproductive barriers acrossreplicated avian hybrid zones above the Tibetan Plateau. Ecol. Lett. 23, 231–241.
Seo, T.-K., 2008. Calculating bootstrap probabilities of phylogeny using multilocus
sequence data. Mol. Biol. Evol. 25, 960–971.
Sheldon, F.H., Whittingham, L.A., 1997. Phylogeny in studies of bird ecology, behavior,and morphology. Avian Mol. Evol. Syst. 279–299.
Sheldon, F.H., Whittingham, L.A., Winkler, D.W., 1999. A comparison of cytochrome band DNA hybridization data bearing on the phylogeny of swallows (Aves:
Hirundinidae). Mol. Phylogenet. Evol. 11, 320–331.
Sheldon, F.H., Winkler, D.W., 1999. Nest Architecture and Avian Systematics. Auk 116,
875–877.
Sheldon, F.H., Whittingham, L.A., Moyle, R.G., Slikas, B., Winkler, D.W., 2005.
Phylogeny of swallows (Aves: Hirundinidae) estimated from nuclear andmitochondrial DNA sequences. Mol. Phylogenet. Evol. 35, 254–270.
Sheldon, F.H., Winkler, D.W., 1993. Intergeneric phylogenetic relationships of swallows
estimated by DNA-DNA hybridization. Auk 110, 798–824.
Silver, M., Griffin, C.R., 2009. Nesting habitat characteristics of bank swallows andbelted kingfishers on the Connecticut River. Northeast. Nat. 16, 519–534.
Smith, B.T., Klicka, J., 2010. The profound influence of the Late Pliocene Panamanian
uplift on the exchange, diversification, and distribution of New World birds.
Ecography 33, 333–342.
South, A., 2011. rworldmap: A new R package for mapping global data. R J. 3. R
package.
South, A., 2017. rnaturalearth: world map data from natural earth. R package.
Stamatakis, A., 2014. RAxML version 8: a tool for phylogenetic analysis and post-analysisof large phylogenies. Bioinformatics 30, 1312–1313.
Sukumaran, J., Holder, M.T., 2010. DendroPy: a Python library for phylogenetic
computing. Bioinformatics 26, 1569–1571.
Swofford, D.L., 2003. PAUP*. Phylogenetic Analysis Using Parsimony (*and Other
Methods). Version 4.
Thonglongya, K., 1968. A new martin of the genus Pseudochelidon from Thailand. Applied
Scientific Research Corporation of Thailand.
Tsai, W.L.E., Schedl, M.E., Maley, J.M., McCormack, J.E., 2020. More than skin andbones: Comparing extraction methods and alternative sources of DNA from avian
museum specimens. Mol. Ecol. Resour. 20, 1220–1227.
Turbek, S.P., Schield, D.R., Scordato, E.S.C., Contina, A., Da, X.-W., Liu, Y., Liu, Y.,
Pagani-Núñez, E., Ren, Q.-M., Smith, C.C.R., Stricker, C.A., Wunder, M., Zonana, D.
M., Safran, R.J., 2022. A migratory divide spanning two continents is associated withgenomic and ecological divergence. Evolution 76, 722–736.
Turner, A., 2018. Swallows and Martins (Hirundinidae). In: del Hoyo, J., Elliott, A.,
Christie, D., de Juana, E. (Eds.), Handbook of the Birds of the World. Lynx Edicions,
Barcelona.
Turner, A.K., Rose, C., 1989. Swallows & martins: an identification guide and handbook.
Houghton Mifflin, Boston.
van der Hoek, Y., Gaona, G.V., Ciach, M., Martin, K., 2020. Global relationships between
tree-cavity excavators and forest bird richness. R. Soc. Open Sci. 7, 192177.
Wang, L.-G., Lam, T.-T.-Y., Xu, S., Dai, Z., Zhou, L., Feng, T., Guo, P., Dunn, C.W.,
Jones, B.R., Bradley, T., 2020. Treeio: an R package for phylogenetic tree input andoutput with richly annotated and associated data. Mol. Biol. Evol. 37, 599–603.
Weber, J.N., Peterson, B.K., Hoekstra, H.E., 2013. Discrete genetic modules are
responsible for complex burrow evolution in Peromyscus mice. Nature 493, 402–405.
Whittingham, L.A., Slikas, B., Winkler, D.W., Sheldon, F.H., 2002. Phylogeny of the treeswallow genus, Tachycineta (Aves: Hirundinidae), by Bayesian analysis of
mitochondrial DNA sequences. Mol. Phylogenet. Evol. 22, 430–441.
Winkler, D.W., Gandoy, F.A., Areta, J.I., Iliff, M.J., Rakhimberdiev, E., Kardynal, K.J.,
Hobson, K.A., 2017. Long-distance range expansion and rapid adjustment of
migration in a newly established population of barn swallows breeding in Argentina.
Curr. Biol. 27, 1080–1084.
Winkler, D.W., Sheldon, F.H., 1993. Evolution of nest construction in swallows(Hirundinidae): a molecular phylogenetic perspective. Proc. Natl. Acad. Sci. USA 90,
5705–5707.
Yu, Y., Harris, A.J., He, X., 2010. S-DIVA (Statistical Dispersal-Vicariance Analysis): a
tool for inferring biogeographic histories. Mol. Phylogenet. Evol. 56, 848–850.
Zhang, C., Sayyari, E., Mirarab, S., 2017. ASTRAL-III: increased scalability and impacts ofcontracting low support branches. In: RECOMB International Workshop on
Comparative Genomics. Springer International Publishing, Cham, pp. 53–75.
Zink, R.M., Pavlova, A., Rohwer, S., Drovetski, S.V., 2006. Barn swallows before barns:
population histories and intercontinental colonization. Proc. R. Soc. B Biol. Sci. 273,
1245–1251.
Zyskowski, K., Prum, R.O., 1999. Phylogenetic analysis of the nest architecture ofneotropical ovenbirds (Furnariidae). Auk 116, 891–911.

Katoh, K., Misawa, K., Kuma, K., Miyata, T., 2002. MAFFT: a novel method for rapid
multiple sequence alignment based on fast Fourier transform. Nucleic Acids Res. 30,
3059–3066.
Katoh, K., Standley, D.M., 2013. MAFFT multiple sequence alignment software version 7:
improvements in performance and usability. Mol. Biol. Evol. 30, 772–780.
Kessler, E., 2013. Neogene songbirds (Aves, Passeriformes) from Hungary. Hantkeniana
8, 37–149.
Kirchman, J.J., Whittingham, L.A., Sheldon, F.H., 2000. Relationships among caveswallow populations (Petrochelidon fulva) determined by comparisons of
microsatellite and cytochrome b data. Mol. Phylogenet. Evol. 14, 107–121.
Kozlov, A.M., Darriba, D., Flouri, T., Morel, B., Stamatakis, A., 2019. RAxML-NG: a fast,scalable and user-friendly tool for maximum likelihood phylogenetic inference.
Bioinformatics 35, 4453–4455.
Landis, M.J., Matzke, N.J., Moore, B.R., Huelsenbeck, J.P., 2013. Bayesian analysis ofbiogeography when the number of areas is large. Syst. Biol. 62, 789–804.
Martínez, M.M., 1983. Nidificación de Hirundo rustica erythrogaster (Boddaert) en laArgentina (Aves, Hirundinidae). Neotropica 29, 83–86.
Matzke, N.J., 2014. Model selection in historical biogeography reveals that founderevent speciation is a crucial process in island clades. Syst. Biol. 63, 951–970.
Matzke, N.J., 2018. BioGeoBEARS: BioGeography with Bayesian (and likelihood)
evolutionary analysis with R scripts.
Mayr, E., 1946. History of the North American bird fauna. Wilson Bull. 58, 3–41.
McCormack, J.E., Tsai, W.L.E., Faircloth, B.C., 2016. Sequence capture of ultraconserved
elements from bird museum specimens. Mol. Ecol. Resour. 16, 1189–1203.
Mirarab, S., Reaz, R., Bayzid, M.S., Zimmermann, T., Swenson, M.S., Warnow, T., 2014.
ASTRAL: genome-scale coalescent-based species tree estimation. Bioinformatics 30,
i541–i548.
Moyle, R.G., Slikas, B., Whittingham, L.A., Winkler, D.W., Sheldon, F.H., 2008. DNA
sequence assessment of phylogenetic relationships among New World martins(Hirundinidae: Progne). Wilson J. Ornithol. 120, 683–691.
Moyle, R.G., Oliveros, C.H., Andersen, M.J., Hosner, P.A., Benz, B.W., Manthey, J.D.,
Travers, S.L., Brown, R.M., Faircloth, B.C., 2016. Tectonic collision and uplift ofWallacea triggered the global songbird radiation. Nat. Commun. 7, 12709.
Nagy, J., Hauber, M.E., Hartley, I.R., Mainwaring, M.C., 2019. Correlated evolution ofnest and egg characteristics in birds. Anim. Behav. 158, 211–225.
O’Dea, A., Lessios, H.A., Coates, A.G., Eytan, R.I., Restrepo-Moreno, S.A., Cione, A.L.,
Collins, L.S., de Queiroz, A., Farris, D.W., Norris, R.D., Stallard, R.F., Woodburne, M.
O., Aguilera, O., Aubry, M.-P., Berggren, W.A., Budd, A.F., Cozzuol, M.A.,
Coppard, S.E., Duque-Caro, H., Finnegan, S., Gasparini, G.M., Grossman, E.L.,
Johnson, K.G., Keigwin, L.D., Knowlton, N., Leigh, E.G., Leonard-Pingel, J.S.,
Marko, P.B., Pyenson, N.D., Rachello-Dolmen, P.G., Soibelzon, E., Soibelzon, L.,
Todd, J.A., Vermeij, G.J., Jackson, J.B.C., 2016. Formation of the Isthmus ofPanama. Sci. Adv. 2, e1600883.
Oliveros, C.H., Field, D.J., Ksepka, D.T., Barker, F.K., Aleixo, A., Andersen, M.J.,
Alström, P., Benz, B.W., Braun, E.L., Braun, M.J., 2019. Earth history and thepasserine superradiation. Proc. Natl. Acad. Sci. USA 116, 7916–7925.
Paradis, E., Schliep, K., 2019. ape 5.0: an environment for modern phylogenetics andevolutionary analyses in R. Bioinformatics 35, 526–528.
Pavlova, A., Zink, R.M., Drovetski, S.V., Rohwer, S., 2008. Pleistocene evolution ofclosely related sand martins Riparia riparia and R. diluta. Mol. Phylogenet. Evol. 48,
61–73.
Pebesma, E., Bivand, R.S., 2005. S classes and methods for spatial data: the sp package.
R News 5, 9–13.
Perez, D.M., Gardner, J.L., Medina, I., 2020. Climate as an evolutionary driver of nest
morphology in birds: a review. Front. Ecol. Evol. 8, 566018.
Phillips, A.R.,1986. The known birds of North and Middle America: Distributions andVariation, Migration, Changes, Hybrids, Etc. Part 1, Hirundinidae to Mimidae;
Certhiidae.
Price, J.J., Griffith, S.C., 2017. Open cup nests evolved from roofed nests in the earlypasserines. Proc. r. Soc. B Biol. Sci. 284, 20162708.
R core Team. 2023. R: A language and environment for statistical computing.
Rambaut, A., Drummond, A.J., Xie, D., Baele, G., Suchard, M.A., 2018. Posterior
summarization in Bayesian phylogenetics using Tracer 1.7. Syst. Biol. 67, 901–904.
Ree, R.H., Smith, S.A., 2008. Maximum likelihood inference of geographic range
evolution by dispersal, local extinction, and cladogenesis. Syst. Biol. 57, 4–14.
Revell, L.J., 2012. phytools: an R package for phylogenetic comparative biology (andother things). Methods Ecol. Evol. 3, 217–223.
Ridgway, R., 1904. The birds of North and Middle America, Part III. Bull. U.S Natl. Mus.
50, 1–801.
Rolland, C., Danchin, E., de Fraipont, M., 1998. The evolution of coloniality in birds inrelation to food, habitat, predation, and life-history traits: a comparative analysis.
Am. Nat. 151, 514–529.
Ronquist, F., 1997. Dispersal-vicariance analysis: a new approach to the quantification ofhistorical biogeography. Syst. Biol. 46, 195–203.

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