bioRxiv preprint doi: https://doi.org/10.1101/2021.07.12.452121; this version posted July 13, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
1 Genetic, bioacoustic and morphological analyses reveal cryptic speciation in the warbling
2 vireo complex (Vireo gilvus: Vireonidae: Passeriformes)
3
4 AM Carpenter1, BA Graham1, GM Spellman2, J Klicka3, & TM Burg1
5 1University of Lethbridge, 4401 University Drive, Lethbridge, AB T1K 3M4, Canada
6 2 Denver Museum of Nature and Science, Denver, CO 80205, USA
7 3 Burke Museum of Natural History and Culture, University of Washington, Box 351800, Seattle,
8 WA 98195, USA
9
10 Corresponding author: [email protected]
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11 ABSTRACT
12 Cryptic species are closely related taxa that are difficult to separate morphologically, but are
13 reproductively isolated. Here we examine the warbling vireo complex (Vireo gilvus), a
14 widespread songbird speculated to be comprised of more than one cryptic species. We included
15 three taxa within the complex: two of the western (Vireo gilvus swainsonii and V. g. brewsteri)
16 subspecies and the single eastern (V. g. gilvus) subspecies. We used mtDNA and microsatellite
17 loci to assess the congruence of genetic data to the current subspecies boundaries. We then
18 incorporated bioacoustic, morphometric, and ecological niche modeling analyses to further
19 examine differences. We found two genetic groups with mtDNA analysis. Microsatellite
20 analyses revealed four genetic groups: an eastern group, a Black Hills group and two western
21 groups that do not agree with current western subspecies boundaries based on phenotypic data.
22 Our results suggest that eastern and western warbling vireos have been reproductively isolated
23 for a long period of time and therefore, may be best treated as separate species; however, more
24 research into areas of contact to examine the presence of hybridization is advised before making
25 a taxonomic revision. Differences between the two western genetic groups appear less clear,
26 requiring additional research.
27 Keywords: bioacoustics, cryptic species, microsatellites, molecular systematics, mtDNA,
28 population genetics
29
30
2 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.12.452121; this version posted July 13, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
31 INTRODUCTION
32 Under the biological species concept, “species” are defined as groups of natural
33 interbreeding populations that are reproductively isolated from other such groups (Mayr, 1942).
34 The process of speciation occurs when reproductive isolating barriers accrue to the extent that
35 gene flow between closely related populations greatly diminishes or becomes absent altogether
36 (Coyne & Orr, 2004). Isolation is caused by numerous factors, including behavioral (mating
37 displays), temporal (timing of migration or breeding), and habitat differences (Irwin, 2000;
38 Delmore et al., 2016; Cristescu et al., 2012). Our understanding of the various forces driving
39 speciation is important in identifying how biodiversity is generated, particularly in the case of
40 cryptic speciation.
41 Cryptic species were first recognized by Derham (1718) and later defined as closely
42 related taxa that are difficult to separate morphologically, but are reproductively isolated from
43 one another (Lincoln et al., 1998; Winker, 2005). Such subtleties in morphological characters
44 between populations leads to subspecies designations within a single species complex, yet the
45 significance of this taxonomic category has been questioned (Ball & Avise, 1992; Zink, 2004).
46 One result is underestimating biological diversity, as one widespread species complex could be
47 in fact multiple, geographically restricted species (Eme et al., 2017). Research delimiting species
48 boundaries has become very active over the past decade with advances in technology (Flot,
49 2015). Specifically, the prevalence of molecular techniques has aided in the identification of
50 cryptic species across diverse taxa (Delić et al., 2017; Silva et al., 2018), including birds (Isler &
51 Whitney, 2011; Irwin et al., 2011). Such genetic studies have played a crucial role in
52 ascertaining phylogenetic relationships and gene flow between subspecies populations, factors
53 that are of consideration when elevating groups to species status which has both biological
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54 (Toews & Irwin, 2008) and conservation (Mace, 2004; Murphy et al., 2011) importance. Other
55 explanatory variables including acoustic structure (Irwin et al., 2008; Toews & Irwin, 2008),
56 ecological niche modeling (Berzaghi et al., 2018), and morphological data (Alström et al., 2011)
57 have been incorporated to further clarify the taxonomic status of cryptic avian species.
58 The genus Vireo (Vieillot, 1808) (Order: Passeriformes; Family: Vireonidae) contains 34
59 species and is found throughout the New World (Gill & Donsker, 2019). Thirteen species breed
60 in North America, occupying a mosaic of habitats including temperate and boreal forests,
61 shrublands, and woodland edges (Gill & Donsker, 2019; Mejías et al., 2020). Reduction of
62 morphological divergence and similar plumage patterns have been recognized among most
63 species (Hamilton, 1962), postulating that ecological differences could have been a mode of
64 speciation in Vireo (Hamilton, 1959; 1962; Barlow 1980). Additionally, a recent study found
65 phylogenetic history strongly shapes song structure and morphology among vireos (Mejías et al.,
66 2020). Several cryptic species have been rectified from species complexes within Vireo,
67 including Hutton’s vireo, Vireo huttoni (Cassin, 1851) (Cicero & Johnson, 1992), blue-headed
68 vireo, Vireo solitarius (Wilson, 1810) (Johnson, 1995; Cicero & Johnson, 1998), and red-eyed
69 vireo, Vireo olivaceus (Linnaeus, 1766) (Slager et al., 2014; Battey & Klicka, 2017). The
70 discovery of these previously unrecognized cryptic species suggests Vireo may contain
71 additional cryptic species, so further scrutiny of other complexes within the genus is suggested
72 (Johnson, 1995).
73 The warbling vireo (Vireo gilvus Vieillot 1808) complex taxonomy follows subtle
74 geographic variation of morphological and plumage characters to recognize five subspecies
75 (Phillips, 1991) divided into two groups (AOU, 1998): a western swainsonii group containing the
76 subspecies Vireo gilvus swainsonii (Baird, 1858), Vireo gilvus brewsteri (Ridgway, 1903), Vireo
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77 gilvus sympatricus (Phillips, 1991), and Vireo gilvus victoriae (Sibley, 1940), and an eastern
78 group gilvus with the single subspecies Vireo gilvus gilvus (Vieillot, 1808). Two of the western
79 subspecies, V. g. sympatricus and V. g. victoriae, are endemic to regions of Mexico, which fall
80 out of the scope of this study. The remaining three, two of the western (swainsonii and brewsteri)
81 and the eastern (gilvus), subspecies (referred to herein by their subspecies epithet) are
82 Neotropical-Nearctic migrants that breed throughout large parts of Canada and the United States,
83 with sympatric distributions in western North America (Fig. 1) (Phillips, 1991; AOU, 1998). The
84 eastern subspecies is diagnostic from these two western subspecies by its larger size, longer (7.5-
85 8.8 mm) and deeper bills (3.6-4.1 mm) with a paler upper mandible, brighter plumage, and p10 is
86 longer vs the primary covert feathers (by 2-8 mm) in western warbling vireos only (Phillips,
87 1991; Pyle, 1997). Between the two western subspecies, diagnoseable characters are more
88 overlapping; swainsonii is a smaller bird than brewsteri, but both of their plumages are dull with
89 variations of olive and gray color, and wing and bill morphologies are similar (Phillips, 1991;
90 Pyle, 1997). It has been postulated that gilvus and swainsonii groups are two separate species
91 (Sibley & Monroe, 1990; AOU, 1998), but more study across the range is sought after (Gardali
92 & Ballard, 2020). Limited analyses of mitochondrial DNA (mtDNA) show divergence of 2.6%
93 for ND2 (Slager et al., 2014), 3.0 – 3.5% for cytochrome b (Murray et al., 1994; Lovell et al.,
94 2021), and ≥ 3.7% for COI (Hebert et al., 2004). Differences in morphology (Lovell, 2010), song
95 (Howes-Jones, 1985; Lovell, 2010), habitat (Semenchuk, 1992; Lovell et al., 2021), molt and
96 migratory behavior (Voelker & Rohwer, 1998), and nuclear DNA (Lovell et al., 2021) have also
97 been discovered. The applicability of some of these results has been queried, however, as
98 limitations of these previous studies include small sample sizes and restricted sampling of
99 geographical areas and subspecies (e.g., swainsonii and gilvus) (Gardali & Ballard, 2020).
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100 Our study aims to fill the knowledge gap about the geographic variation in population
101 genetics across the range of the warbling vireo complex. The use of both mitochondrial and
102 nuclear markers allows for the elucidation of evolutionary history and contemporary genetic
103 patterns, avoiding the limitations of single marker inferences. We implement bioacoustic and
104 morphometric analyses in the context of the subspecies designations and genetic groups to
105 determine the levels of variation among them independently. Finally, the range boundaries
106 between genetic groups are visualized using contemporary ecological niche modeling to compare
107 to the subspecies boundaries. This approach can be powerful when investigating the distributions
108 and differences between cryptic species (Rissler & Apodaca, 2007). Specifically, we ask:
109 1. Are mtDNA and microsatellite genetic groups congruent to the swainsonii, brewsteri,
110 and gilvus subspecies boundaries?
111 2. Are there differences in acoustic and morphological characters among eastern and
112 western subspecies? Among eastern and western genetic groups? And
113 3. Are there differences in acoustic and morphological characters between the western
114 subspecies? Between the western genetic groups?
115 METHODS
116 Sample Collection
117 From 2007 – 2019, we collected 194 warbling vireo samples from adult birds in 18
118 populations. Birds were sampled during the breeding season, end of May through to early July,
119 to avoid migrants and reduce the capture of family groups. Each bird was caught by mist net
120 using song playbacks, banded, and a small blood sample (< 50 µL) was taken from the brachial
121 vein for genetic analyses. Four morphological measurements were collected from each bird using
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122 calipers to 0.1 mm (bill length, bill depth, bill width, and tarsus length), wing chord was
123 measured using a wing ruler to the nearest millimeter, and birds were weighed in grams (g) to
124 one decimal point. Additionally, we obtained 184 blood or tissue samples, and corresponding
125 morphological data, if available, from museum collections (Table 1). All blood and tissue
126 samples were stored in 95% ethanol. DNA was extracted using a modified Chelex procedure
127 (Walsh et al., 1991; Burg & Croxall, 2001).
128 DNA Amplification
129 mtDNA. We amplified two mtDNA genes: cytochrome b (cyt b) and ATPase 6 and 8. The
130 915 bp (base pair) cyt b fragment was amplified using the primers H15944 (Lovell et al., 2021)
131 and L14990 (Sorenson et al., 1999) in 65 warbling vireos from populations of all three
132 subspecies (Table 1). The second gene, a 503 bp fragment of ATPase 6 and 8, was amplified
133 using the primers ATP H534ch (Lait & Burg, 2013) and L8929 COII (Sorenson et al., 1999) in
134 44 warbling vireos from only populations of the two western subspecies, swainsonii and
135 brewsteri, to further examine their evolutionary histories (Table 1). The 25 µL polymerase chain
136 reaction (PCR) mixture was the same for both mtDNA genes using 5x Green GoTaq® Flexi
137 buffer (Promega), 0.2 mM dNTPs, 2 mM MgCl2 (Promega), 0.5 µM of each H and L primer, and
138 0.5 U GoTaq® Flexi polymerase (Promega). The following thermocycling profile was used to
139 amplify DNA for both mtDNA genes: two minutes at 94°C, 45 seconds at 58°C, one minute at
140 72°C; 37 cycles of 30 seconds at 94°C, 45 seconds at 58°C, one minute at 72°C, concluding with
141 an extension period of five minutes at 72°C. Sequencing for both cyt b and ATPase 6 and 8
142 genes were completed by NanuQ (McGill University, Montreal, QC, Canada).
143 Microsatellites. A subset of warbling vireo samples (N = 6) from geographically distant areas
144 were screened with 57 passerine microsatellite loci. A total of 30 microsatellite loci optimized
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145 successfully, 14 of which were polymorphic and used in our study: BCV2-6, BCV4-5, BCV4-
146 6New (Barr et al., 2007), Ck.1B5D, Ck.4B6D, Ck.2A5A, Ck.1B6G (Tarr & Fleischer, 1998),
147 Hofi5 (Hawley, 2005), Pocc1 (Bensch et al., 1997), ApCo46 (Stenzler & Fitzpatrick, 2002), Lox1
148 (Piertney et al., 1998), Ase18 (Richardson et al., 2000), Ppi2New (Martinez et al., 1999), and
149 CmAAAG30 (Williams et al., 2004) (see Supporting Information, Table S1). All PCRs were
150 conducted in a 10 µL volume using FroggaBio buffer, 0.2 mM dNTPs, 0.5 µM of forward
151 primer, 1 µM of the reverse primer, 0.05 µM of the M13 fluorescently labeled primer, and 1 U of
152 FroggaBio Taq. The following thermocycling profile was used to amplify DNA: one cycle for
153 one minute at 94°C, 45 seconds at T1, and one minute at 72°C; seven cycles of one minute at
154 94°C, 30 seconds at T1, and 45 seconds at 72°C; 25 cycles for 30 seconds at 94°C, 30 seconds at
155 T2, and 45 seconds at 72°C; and one cycle for 72°C at five minutes. Five loci (BCV4-6New,
156 Hofi5, ApCo46, Lox1, and Ppi2New) were amplified using T1=50°C and T2=52°C, five loci
157 (BCV2-6, BCV4-5, Ck.1B5D, Ck.2A5A, and Ck.4B6D) were amplified using T1=52°C and
158 T2=54°C, and four loci (Pocc1, Ase18, CmAAAG30, and Ck.1B6G) were amplified using
159 T1=55°C and T2=57°C. For three loci (BCV4-5, ApCo46, and Ppi2New) the second step was
160 increased from 25 to 31 cycles. PCR products were run on a 6% acrylamide gel on a LI-COR
161 4300 DNA Analyzer (LI-COR Inc., Lincoln, NE, USA). To maintain consistency of scoring
162 alleles, the same three positive controls of known sizes were amplified and run with each load
163 for each locus. All alleles were scored manually by visual inspection and checked independently
164 by a second person. Samples from each load was re-run at a later date to ensure the accuracy of
165 allele scores.
166
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167 Genetic Analyses
168 MtDNA. Sequences were checked and aligned using MEGA X 10.1 (Kumar et al., 2018). Cyt b
169 sequences were compared to a reference warbling vireo sequence from GenBank (AY030111).
170 We constructed minimum spanning haplotype networks from variable sites at both genes to
171 examine historic genetic differences among subspecies. Minimum spanning haplotype networks
172 were created for ATPase 6 and 8 and cyt b using default settings in Population Analysis with
173 Reticulate Trees 1.7 (PopART) software (Bandelt et al., 1999).
174 We estimated coalescence times between the eastern and western genetic groups,
175 between the two western genetic groups, and between these genetic groups and the Black Hills
176 group (see results) by applying a molecular clock of 2% per million years (Brown et al., 1979) to
177 our cyt b data, a rate used in Passeriformes (Weir & Schluter, 2008). Additionally, we estimated
178 a second coalescence time between the two western genetic groups using data from ATPase 6
179 and 8 with the same 2%/Myr rate (Brown et al., 1979).
180 Microsatellites. A total of 378 individuals from 37 populations were included in microsatellite
181 analyses (Table 1). Expected (HE) and observed (HO) heterozygosities and the average number of
182 alleles per locus were calculated in GenAlEx 6.5 (Peakall & Smouse, 2006; 2012) (Supporting
183 Information, Table S1). Deviations from Hardy-Weinberg equilibrium and linkage
184 disequilibrium were tested with Genepop 4.7 (Raymond & Rousset, 1995; Rousset, 2008).
185 Pairwise FST values were calculated in GenoDive (Meirmans & van Tienderen, 2004) to
186 examine genetic differentiation among populations with more than five individuals. P-values
187 were corrected post hoc with the Benjamini-Hochberg (B-H) method to account for multiple
188 comparisons and avoid type I errors (Benjamini & Hochberg, 1995). We chose the B-H method
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189 because Bonferroni corrections have been suggested as too severe, often underestimating the
190 number of significant comparisons (Garamszegi, 2006).
191 We used the program STRUCTURE 2.3.4 (Pritchard et al., 2000; Hubisz et al., 2009) to
192 examine the number of genetic groups present in the warbling vireo complex using the following
193 settings: admixture model with correlated allele frequencies, sampling locations set as locpriors,
194 and a burn-in of 50 000 followed by 100 000 Monte Carlo Markov Chains (McMC) for ten
195 iterations for each K from 1 to 5. We calculated ΔK (Evanno et al., 2005) in Structure Harvester
196 (Earl & von Holdt, 2012) and examined posterior probabilities with Bayes rule (Pritchard et al.,
197 2000) to determine the optimal K. We tested for the presence of hierarchal structure by running
198 subsequent analyses for each genetic group identified in the initial STRUCTURE runs. Final
199 outputs for each optimal value of K were averaged among the ten iterations and represented
200 graphically using Structure Plot 2.0 (Ramasamy et al., 2014).
201 Bioacoustic Analyses
202 To explore acoustic differences, we compared songs from the Xeno-canto repository
203 (www.xeno-canto.org) for three out of the four microsatellite genetic groups (excluding the
204 Black Hills group). Of the 336 song recordings originally downloaded, we measured songs from
205 47 audio files. When deciding which audio files to measure, we looked for songs with a high
206 signal-to-noise ratio and no overlap from other species; we chose to examine one file for each
207 site to avoid measuring songs from the same bird, thereby avoiding pseudoreplication. For each
208 song, we checked the location where the song was recorded and then assigned it to a genetic
209 group based on our microsatellite genotyping results. Of the 47 audio files 13 were north-
210 western, 26 were south-western, and eight were eastern. From each audio file, up to seven songs
211 were analyzed for five fine-scale measurements: song length (s), minimum frequency (Hz),
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212 maximum frequency (Hz), peak frequency (Hz; the frequency of the song with the maximum
213 power), and the syllable delivery rate of each song (syllables/second). To calculate syllable
214 delivery rate, we counted the average number of syllables in each song and then divided this
215 number by the average song length. All values were tested for intercorrelations and, although we
216 originally measured bandwidth (Hz) for each song, this measurement was highly correlated (r =
217 0.95) with maximum frequency and removed from our analyses. All sound files were converted
218 to WAVE files, as WAVE files can produce different results with respect to fine-scale
219 measurements (Araya-Salas et al., 2017). All measurements were done in RavenPro 1.4 (Cornell
220 lab of Ornithology, Ithaca, New York, USA) using the following settings: 50% Hahn window
221 and 256 kHz sampling with 16-bit accuracy. For audio files where more than one song was
222 measured, we averaged all of the songs to produce a single data point for that audio file.
223 To determine whether the songs of the northwestern, southwestern, and eastern genetic
224 groups are acoustically different based on these five fine-scale measurements, we carried out a
225 discriminate function analysis (DFA). We used the leave-one out classification analysis and
226 reported the percentage of songs that were correctly assigned to each group. We used this same
227 DFA to examine whether there were also acoustic differences among the subspecies. Songs were
228 measured using the same settings as mentioned above for the genetic groups, but each song was
229 assigned to a subspecies based on the information associated with the audio file. In those
230 instances where a subspecies rank was not included with the file (N = 22), we assigned it to a
231 subspecies based on the geographic location of where the audio file was recorded in respect to
232 the subspecies boundaries as described by Phillips (1991). Of the 47 audio files 24 were
233 swainsonii, 11 were brewsteri, and 12 were gilvus. DFAs were performed in SPSS 23.0 (SPSS
234 Inc., Chicago, IL, USA).
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235 Lastly, songs were compared among the subspecies and among the genetic groups
236 independently using a multivariate analysis of variance (MANOVA) in SPSS 23.0 (SPSS Inc.,
237 Chicago, IL, USA). The first and second canonical axes were used our dependent variables and
238 either genetic groups or subspecies was used as our independent variable. A Tukey’s post hoc
239 test was done to evaluate whether songs were different among the subspecies and among the
240 genetic groups.
241 Morphometric Analyses
242 Using the genetic groups from our microsatellite data, we did a MANOVA in SPSS 23.0
243 to test for morphological differences between them. Six morphological measurements were
244 compared: mass, wing chord, bill length (from nares to tip), bill depth, bill width (posterior end
245 of nostrils), and tarsus length among 179 individuals assigned to a genetic group (88 north-
246 western, 56 south-western, 35 eastern) (excluding the Black Hills group) (Table 1).We included
247 the genetic groups as our dependent variable, and latitude and bird bander as covariate variables
248 in our model due to the potential of bird bander biases and effects of latitude on morphology.
249 These same 179 individuals were also assigned to one of the three subspecies (108 swainsonii,
250 36 brewsteri, and 35 gilvus) to compare morphological differences. For this analysis, we used
251 subspecies as our dependent variable and again used latitude and bird bander as covariates in our
252 model. A least-squared difference test was used to examine the significance of morphological
253 differences among the genetic groups and among the subspecies independently.
254 Similar to our methodology of assessing acoustic differences, we also performed a DFA
255 on morphological traits. The six morphological characters were used as our dependent variables,
256 and we used the leave-one out classification analysis to report the percentage of individuals that
257 were correctly assigned to each genetic group and subspecies based on morphology. The use of
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258 DFA to diagnose vocal and morphological differences between subspecies follows techniques
259 outlined in Demko et al. (2020).
260 Ecological Niche Modelling
261 We ran ecological niche models for three of the four genetic groups (Black Hills was not
262 included) to project each of their ranges and explore the role of climate variables involved in
263 their distributions. Using Maxent 3.4.1 (Phillips et al., 2006) with WorldClim BioClim rasters
264 (Hijmans et al., 2005), predictive models output estimates of suitable areas of habitat for a
265 species based on the environmental conditions from occurrence datasets of that species (Elith &
266 Leathwick, 2009). Occurrence records were comprised of sampling locations from this study (N
267 = 105) and eBird datasets (www.ebird.org; Cornell Lab of Ornithology, 2019) (N = 4593). To
268 restrict occurrences to breeding populations, only observations from late May to early August
269 were included and occurrences points were assigned to a genetic group based on our
270 microsatellite data. Wallace 1.0.6 in R (Kass et al., 2017) was used to spatially thin occurrence
271 points by 10 km to avoid over representation of a given area. Final occurrence sets for each
272 genetic group was north-western group N = 590, south-western group N = 718, and eastern group
273 N = 1114.
274 Nineteen variables at 2.5 arcmin resolution were downloaded from the WorldClim
275 BioClim dataset and tested for correlations. Once we removed all but one variable with strong
276 correlations (> 0.7), we were left with 8 – 12 variables depending on each genetic group’s model;
277 BIO4 and BIO19 were not used in any model. Ten replicates were run for each genetic group’s
278 occurrence points and specific set of BioClim rasters using the 1.0 regularization multiplier with
279 auto features, 10000 background points, and a cross-validation method in Maxent.
280
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281 RESULTS
282 MtDNA
283 A 915 bp fragment of cyt b was successfully amplified in 65 warbling vireos from 22
284 populations across all three subspecies ranges (GenBank accession numbers MZ020223 -
285 MZ020287). We identified two mtDNA lineages, separating eastern and western groups by 31
286 fixed nucleotide differences (Fig. 1). One population, SEAB, contained birds with haplotypes
287 from both groups (six of the 22 individuals had eastern haplotypes). Overall, we identified 35
288 haplotypes, of which ten haplotypes were exclusive to the eastern lineage. Average sequence
289 divergence for cyt b between the eastern genetic group and both western genetic groups and the
290 Black Hills was 4.0% (± 0.1), between the two western genetic groups was 0.4% (± 0.01), and
291 between each of the two western genetic groups and the Black Hills was 0.3% (± 0.01).
292 Applying a 2%/Myr molecular clock places an estimated coalescence time of 2 Mya between the
293 eastern group and the two western groups and the Black Hills, 0.2 Mya between the two western
294 groups, and 0.15 Mya between the two western groups and the Black Hills.
295 ATPase 6 and 8 was successfully amplified in 44 warbling vireos from 11 populations
296 across the two western subspecies ranges (GenBank accession numbers MZ020288 -
297 MZ020331). We found a single mtDNA lineage with no clear partitioning between subspecies
298 (Fig. 1). We identified 15 haplotypes, one of which is shared by 13 of the 44 individuals (30%).
299 Average sequence divergence was 0.3% (± 0.01) between the two western genetic groups: north-
300 western, formerly swainsonii, (N = 24) and south-western, formerly brewsteri, (N = 21).
301 Applying a 2%/Myr molecular clock, this places an estimated coalescence time of 150,000 years
302 between them.
303
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304 Microsatellites
305 Observed and expected heterozygosities were comparable across thirteen of the fourteen
306 loci. BCV4-6New had lower HO (0.59) than HE (0.71), which could be attributed to an excess of
307 homozygotes genotyped at this locus. The average number of alleles per locus ranged from 2 to
308 15 (Supporting Information, Table S1). We found no significant departures from Hardy-
309 Weinberg equilibrium or linkage disequilibrium at any of the 14 microsatellite loci.
310 STRUCTURE identified two genetic groups on the initial run supported by Bayes rule
311 (0.11) and ΔK (-13458). We found a distinct west – east split along the Great Plains dividing
312 western populations from all eastern populations, with the exception of central Montana (CMT)
313 and southeast Alberta (SEAB) (Fig. 2A; Fig. 3). Within the SEAB population, seven out of 24
314 individuals assigned to the eastern genetic group. All eastern populations, and the seven eastern
315 individuals within the SEAB population, were removed to test for additional substructure among
316 western populations independently.
317 Among the western populations, K = 2 separated all western populations from the Black
318 Hills (Bayes rule = 0.27; ΔK = -11021) (Fig. 2B). A subsequent run was executed after removing
319 the Black Hills population, with two additional genetic groups detected among the remaining
320 western populations (Bayes rule = 1.0; ΔK = 9785). The majority of individuals from each
321 population were assigned Q ≥ 60% to a specific western genetic group, but do not follow the
322 current western subspecies range distributions. For this reason, we will refer to swainsonii as the
323 north-western genetic group and brewsteri as the south-western genetic group. The north-western
324 group contains seven populations from the swainsonii range (NWBC, CBC, JASPER, BANFF,
325 CASTLE, WLNP, SWBC), in addition to one population from the gilvus range (SEAB), while
326 the south-western group contains eleven populations from the swainsonii range (NEWA,
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327 NWWA, VI, CWA, NEOR, SEOR, CoOR, CoCA, NECA, SECA, SWNV), eight populations
328 from the brewsteri range (NENV, UT, NM, SWCO, CCO, CWY, NWWY, SWMT), and one
329 population from the gilvus range (CMT) (See Table 1 for abbreviation names; Fig. 2C).
330 Altogether, STRUCTURE identified four genetic clusters: an eastern group, two western groups
331 (north-western and south-western), and the Black Hills (Fig. 3).
332 Based on the microsatellite genetic groups, we split the southeast Alberta (SEAB)
333 population into two separate populations, Cypress Hills (C HILLS) and Medicine Hat (M HAT)
334 for the pairwise FST analysis. We found high levels of population genetic structure for warbling
335 vireos based on pairwise FST comparisons. Of the 23 populations examined, 152 of the 253
336 comparisons were significant (Table 2). Ninety of the significant comparisons separated the
337 eastern group from both the north-western and south-western groups (P ≤ 0.01). Three south-
338 western populations, north-east Oregon (NEOR), south-west Nevada (SWNV), and New Mexico
339 (NM), were significantly different from all five northwestern populations (P ≤ 0.01) in British
340 Columbia and Alberta: central British Columbia (CBC), Jasper National Park (JASPER), Banff
341 National Park (BANFF), Castle Provincial Park (CASTLE), Waterton Lakes National Park
342 (WLNP). Overall, pairwise FST comparisons found little genetic differentiation within
343 conspecific populations.
344 Bioacoustics
345 For our analysis of song variation in the context of genetic groups, the first canonical
346 function examining syllable delivery rate and song length explained 83% of the observed
347 variance (Wilks’ lambda = 0.55, χ2 = 25.3, P < 0.001) and songs were significantly distinct
348 among the three genetic groups (Wilks’ lambda = 0.55, F4,86 = 5.5, P < 0.001) (Fig. 4). Of note
349 are three southwestern birds from Wyoming and Colorado that cluster with the eastern birds.
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350 The areas where the songs were recorded is near a contact zone; these could have been
351 recordings from eastern birds and were misidentified. Eastern birds sang longer songs with a
352 higher syllable delivery rate than birds from the two western genetic groups (F2,44 = 12.2, P <
353 0.001) (Fig. 5). Songs from the two western genetic groups were not distinct based on the first
354 canonical analysis (P = 1). We also found no differences among the three genetic groups for the
355 second canonical function (F2,44 = 0.3, P = 0.74); 68.1% of the songs were assigned to the correct
356 microsatellite genetic group following cross-validation. Overall, 50% of eastern songs were
357 correctly classified to the eastern genetic group, 84.6% of north-western songs were correctly
358 assigned to the north-western genetic group, and 73.1% of south-western songs were correctly
359 classified to the south-western genetic group.
360 For our analysis using subspecies designations to classify song variation, the first
361 canonical function explained 86% of the observed variance (Wilks’ lambda = 0.50, χ2= 29.5, P <
362 0.001). Similar to our analysis using the genetic groups, songs were statistically significant and
363 distinct among subspecies (Wilks’ lambda = 0.5, F4,86 = 9.0, P < 0.001). Songs from the eastern
364 subspecies are longer and have a higher syllable delivery rate than songs from both of the
365 western subspecies based on the first canonical function (F2,44= 17.4, P < 0.001). Between the
366 two western subspecies, swainsonii songs were shorter and slower paced than brewsteri songs (P
367 = 0.06). We found no song differences among the subspecies based on the second canonical
368 function (F2,44 = 2.8, P = 0.08). Overall, 70.2% of the songs were assigned to the correct
369 subspecies following cross-validation. Both swainsonii (79.2%) and gilvus (72.7%) had high
370 assignment to the correct subspecies, while only 58.3% were correctly assigned as brewsteri
371 songs; of note, 25% of brewsteri songs were classified as swainsonii songs.
372
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373 Morphometrics
374 Morphological differences were found among the three genetic groups (Wilks’ lambda =
375 0.27, F12,338 = 25.8, P < 0.001) at five of the six measurements: mass, wing chord, bill depth, bill
376 width, and tarsus; bill length was not significant (see Supporting Information, Table S2). The
377 eastern genetic group is heavier (14.16 g ± 0.19), with longer wings (69.96 mm ± 0.36) and
378 deeper bills (3.96 mm ± 0.05) than north-western (mass: 11.61 g ± 0.13; wing chord: 67.04 mm
379 ± 0.24; bill depth: 3.37 mm ± 0.04; P < 0.001) and south-western (mass: 11.35 g ± 0.16; wing
380 chord: 68.09 mm ± 0.30; bill depth: 3.62 mm ± 0.05; P < 0.001) populations. North-western
381 populations have smaller tarsi (17.6 mm ± 0.13) and narrower bills (3.94 mm ± 0.06) than south-
382 western (tarsi: 18.25 mm ± 0.16; bill width: 4.61 mm ± 0.08; p < 0.001) and eastern (tarsi: 18.30
383 mm ± 0.19; bill width: 4.53 mm ± 0.09; p < 0.001) populations. The first canonical analysis
384 examining mass and bill depth explained 77.6% of the variance (Wilks’ lambda = 0.22, χ2 =
385 263.8, P < 0.001), and the second discriminant analysis examining differences in tarsus length
386 and bill width accounted for the remaining 22.4% of the variance (Wilks’ lambda = 0.64, χ2 =
387 76.9, P < 0.001). Discriminant function analysis assigned 81% of birds to the correct genetic
388 group following cross-validation; 92% of north-western birds and 82.9% of eastern birds were
389 correctly assigned. Among south-western birds, 62.5% of birds were assigned correctly, while
390 33.9% of south-western birds were assigned to the north-western genetic group.
391 Differences in morphology were also reported among the subspecies designations (Wilks’
392 lambda = 0.25, F12,340 = 27.5, P < 0.001), but rather across all six morphological characters in
393 comparison to the genetic groups (Supporting Information, Table S2). A similar result between
394 the eastern subspecies and eastern genetic group was found: gilvus are heavier (14.2 g ± 0.19),
395 have longer wings (69.9 mm ± 0.35), and deeper bills (3.95 mm ± 0.06) than swainsonii (mass:
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396 11.6 g ± 0.11; wing chord: 66.9 mm ± 0.20; bill depth: 3.42 mm ± 0.03; P < 0.001) and brewsteri
397 (mass: 11.3 g ± 0.19; wing chord: 68.9 mm ± 0.35; bill depth: 3.60 mm ± 0.06; P < 0.001)
398 populations. The two morphological characters that were diagnostic to the north-western genetic
399 group were also found to be the same in swainsonii, with swainsonii having smaller tarsi (17.7
400 mm ± 0.11), and narrower bills (width: 4.06 mm ± 0.06) than both gilvus (tarsus: 18.3 mm ±
401 0.19; width: 4.50 mm ± 0.10; P < 0.001) and brewsteri (18.4 mm ± 0.19; width: 4.70 mm ± 0.10;
402 P < 0.001). One main difference between genetic groups and subspecies comparisons was that
403 the bill length of brewsteri is longer (9.74 mm ± 0.22) than both swainsonii (8.89 mm ± 0.13; P
404 < 0.001) and gilvus (9.00 mm ± 0.22; P < 0.001). The first canonical analysis examining mass
405 and bill depth explained 81.8% of the variance (Wilks’ lambda = 0.24, χ2 = 247.5, P < 0.001),
406 and the second discriminant analysis examining differences in tarsus length and bill width
407 accounted for the remaining 18.2% of the variance (Wilks’ lambda = 0.70, χ2 = 61.6, P < 0.001).
408 Discriminant function analysis assigned 82.7% of birds to the correct genetic group following
409 cross-validation; 90.7% of swainsonii individuals and 82.9% of gilvus were correctly assigned.
410 Among brewsteri, 58.3% of birds were assigned correctly, while 36.1% of brewsteri birds were
411 assigned to swainsonii.
412 Overall, our morphological analyses reveal that the eastern genetic group and subspecies gilvus
413 differ significantly from the two western genetic groups and subspecies swainsonii and
414 brewsteri. Among the two western genetic groups and subspecies swainsonii and brewsteri, there
415 is considerable overlap in both contexts indicating that morphological differences are less
416 pronounced between them.
417
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418 Ecological Niche Modelling
419 Each genetic group’s model from Maxent was evaluated using the area under the curve
420 (AUC) value: north-western AUC = 0.97 (± 0.004), south-western AUC = 0.96 (± 0.003), and
421 eastern AUC = 0.95 (± 0.004). These high AUC values (in proximity to the value of 1), along
422 with test omission curves close to the predicted omission curve, shows that each model
423 performed well. Climatic variables that contributed most were different across each genetic
424 group’s model: eastern (BioClim18 = 35%, BioClim7 = 18%, BioClim11 = 17.5%; precipitation
425 of warmest quarter, annual temperature range, and mean temperature of coldest quarter,
426 respectively), north-western (BioClim14 = 28.8%, BioClim12 = 25.6%, and BioClim11 =
427 21.5%; precipitation of driest month, annual precipitation, and mean temperature of coldest
428 quarter, respectively), and south-western (BioClim3 = 37.4%, BioClim2 = 22.7%, BioClim1 =
429 17.5%; isothermality, mean diurnal range, and annual mean temperature, respectively).
430 Based on our model, the distribution (Fig. 6; bottom) for the eastern genetic group overall
431 resembles the current subspecies boundaries for gilvus (Fig. 1), with its range extending west to
432 the Rocky Mountain range. Between the north-western and south-western genetic groups, their
433 predicted distributions in western North America are a little less clear with an abundance of
434 niche overlap (Fig. 6; top and middle). Unlike the cohesion between the eastern genetic group
435 and gilvus, the two western genetic groups and the two western subspecies boundaries do not
436 agree based on climatic variables.
437 DISCUSSION
438 Taken together, we have conducted the first extensive range-wide population genetic
439 study on the warbling vireo complex to test the congruence of the subspecies designations to
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440 genetic data and provide evidence for another potential case of cryptic speciation within the
441 genus Vireo. We found a main west – east division for both mtDNA (cyt b) and microsatellites, a
442 pattern observed in other widely distributed North American passerines (Milot et al., 2000;
443 Clegg et al., 2003; Lait & Burg, 2013; Graham et al., 2020). The large genetic distances in
444 mtDNA (4.0%) and abrupt split along the Great Plains suggest that the eastern genetic group was
445 isolated in a separate glacial refugium from the two western genetic groups during the
446 Pleistocene (Rising, 1983). Our estimated coalescence time dates 2 Mya, which corresponds to
447 the early Pleistocene (2.5 Mya – 11.5 Kya) (Gibbard et al., 2010); however, the timing and role
448 of glaciation in speciation remains controversial (Klicka & Zink, 1997; 1999; Weir & Schluter,
449 2004; Johnson & Cicero, 2004).
450 Species in other vireo complexes were found to have split in the early to mid-Pleistocene,
451 including Hutton’s vireo (1.5 Mya) and the solitary vireo (1.3 Mya) (Cicero & Johnson, 1992;
452 1998). The American Ornithologists’ Union (Banks et al., 1997) elevated three subspecies of the
453 solitary vireo complex to species (blue-headed vireo Vireo solitarius (Wilson, 1810), Cassin’s
454 vireo Vireo cassinii (Xantus de Vesey, 1858) and plumbeous vireo Vireo plumbeus (Coues,
455 1866)) based on cyt b sequences (Murray et al., 1994) and allozyme variation (Johnson, 1995).
456 Similarly, cryptic populations of eastern and western winter wrens [formerly Troglodytes
457 troglodytes (Linnaeus, 1758)] were recognized as two distinct species (winter wren Troglodytes
458 hiemalis (Vieillot, 1819) and Pacific wren Troglodytes pacificus (Baird, 1864)) following
459 detailed analyses using a range of genetic, acoustic, and morphometric characters (Toews &
460 Irwin, 2008). The genetic distance in cyt b between populations of eastern and western warbling
461 vireos in our study (0.040) and previous studies (Murray et al., 1994; Lovell et al., 2021) is
462 comparable to the distance used when describing species (0.044) rather than subspecies (0.0048)
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463 (Nei, 1978; Barrowclough, 1980). Integrated approaches to assess reproductive isolation are
464 increasingly being favored and applied before taxonomic revision. Our general conclusion that
465 the eastern genetic group has experienced prolonged genetic isolation from the two western
466 genetic groups is supported by multiple types of data including mitochondrial and nuclear DNA,
467 morphology, and song.
468 Within the western populations, the nuclear DNA showed clear separation into two
469 groups, but, morphological and song differences were not as clear, and the two groups observed
470 with this genetic data did not correspond to current distributions of the two western subspecies.
471 The western subspecies morphological characters are described as similar, with overlapping bill
472 and wing morphologies, minor size differences, and dull plumage (Phillips, 1991; Pyle, 1997).
473 MtDNA at both cyt b and ATP genes revealed a single western lineage with one common
474 haplotype and several haplotypes differing by one to four nucleotide changes. Dividing the
475 western subspecies populations into their respective genetic groups (north-western, south-
476 western, or the Black Hills) provided no additional clarification between the two haplotype
477 networks. Our estimated coalescence times at both mtDNA genes between the north-western and
478 south-western genetic groups, 200,000 – 150,000 years ago, correspond to the last interglacial
479 period or the beginning of the Wisconsin glaciation (Dawson, 1992). Given this recent
480 divergence, the probability of complete lineage sorting to accrue fixed differences in mtDNA and
481 form distinct phylogroups is reduced (Peters et al., 2005). Our north-western and south-western
482 genetic groups are distributed north – south, coming into contact in southern Canada and the
483 north-western United States, areas at the southern edge of two ice sheets during the Pleistocene
484 glaciations (Remington, 1968; Swenson & Howard, 2004; 2005). Similar patterns have been
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485 observed in other high latitude species (Van Els et al., 2012; Chavez et al., 2011) and attributed
486 to Pleistocene glacial vicariance.
487 Our bioacoustic results between both genetic groups and subspecies designations were
488 similar. The eastern genetic group and subspecies gilvus produce longer songs with a higher
489 syllable delivery rate, two diagnostic characters from both the western genetic groups and
490 subspecies songs. Between the western subspecies, diagnostic characters in acoustic differences
491 were more muddled, but swainsonii songs are shorter and contain fewer syllables than brewsteri
492 songs, which reflects our example song spectrograms between the western genetic groups (Fig.
493 5). A greater proportion of songs were also correctly assigned to each of the western genetic
494 groups rather than to each of the western subspecies, particularly for brewsteri. Songs of gilvus
495 have been previously described as complex (rhythmic structure; Howes-Jones, 1985) and it has
496 been suggested that complex songs encode species information (Marler, 1960). For example, the
497 complexity at the start of gilvus songs were comparable to indigo bunting (Passerina cyanea)
498 songs, which gain attention of conspecifics (Shiovitz, 1976; Howes-Jones, 1985). Acoustic
499 divergence has been recognized as a mode of speciation in other cryptic avian species (Irwin et
500 al., 2008; Toews & Irwin, 2008), while undifferentiated in others (Garg et al., 2016). Song
501 playback experiments in areas of sympatry, or contact zones, would help to resolve the role of
502 singing type as a behavioral and reproductive isolating barrier between eastern and western
503 warbling vireos.
504 The findings from our morphological analyses were significant in both the subspecies and
505 genetic group comparisons, but the variation in morphology is complex and does not always
506 agree with previous studies. The western subspecies, brewsteri, has the longest bill among the
507 three subspecies, which contradicts previous comments of gilvus having the longest bill (Phillips,
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508 1991; Lovell, 2010). Minor size differences between swainsonii (smaller) and brewsteri are also
509 criteria used to define subspecies boundaries (Phillips, 1991), but we found the opposite result
510 with our data; swainsonii and the north-western genetic group are slightly heavier (11.59 g and
511 11.61 g, respectively) than both brewsteri and the south-western genetic group (11.25 g and
512 11.35 g, respectively). While this difference was not statistically significant, it reinforces that
513 morphological differences between the western groups are more subtle. Eastern birds are
514 significantly larger (~ 2.5 g heavier), have longer wings, and deeper bills than western birds.
515 These differences in size could be attributed to habitat. In Alberta, the eastern birds have been
516 found primarily in open deciduous forest and aspen parkland whereas the western subspecies,
517 swainsonii, occurs in mixed forest and boreal forest habitats in the foothills of the Rocky
518 Mountains (Semenchuk, 1992; Lovell et al., 2021).
519 Ecological differences represent barriers for many avian species, including Phylloscopus
520 (F. Boie, 1826) warblers (Richman & Price, 1992), Pycnonotus (F. Boi, 1826) bulbul species
521 (Lloyd et al., 1997), Empidonax (Cabanis, 1855) flycatchers (Johnson & Cicero 2002), and other
522 Vireo species (Cicero & Johnson, 1998). Grant and Grant (1997) attested that considerable
523 habitat and climate differences maintain species boundaries. Our ecological niche models
524 support a well-defined split between western and eastern genetic groups, corresponding to
525 different precipitation and temperature variables. Several other songbird species pairs with west
526 – east distributions have similar population structure because of local adaptation to refugial
527 temperatures during the Pleistocene glacial cycles (Swenson, 2006), a scenario also observed by
528 Hargrove & Hoffman (2004) in other fauna and flora.
529 Our study revealed two unique populations: a disjunct western population in the Cypress
530 Hills, located in the south-eastern corner of Alberta and the south-western corner of
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531 Saskatchewan, and a population in the Black Hills, located in western South Dakota and north-
532 eastern Wyoming. Based on pollen evidence, both areas were unglaciated during the last glacial
533 maximum and supported boreal forest species (Froiland, 1978; Strong & Hills, 2005).
534 Accompanied by geological processes that created these elevated features among the Great
535 Plains, boreal species became isolated in the Cypress Hills and the Black Hills as the surrounding
536 areas were rapidly replaced with grassland flora with rising temperatures at the start of the
537 Holocene (Strong & Hills, 2005). While both of these locations are embedded within the eastern
538 subspecies range, what little we do know about its preferred habitat (Semenchuk, 1992; Lovell et
539 al., 2021) is a plausible explanation for why gilvus are not found in these montane areas.
540 Comparisons of allele frequencies from both surrounding south-western (SWCO, CCO, CWY,
541 and NWWY) and eastern (SK, ND, MN, and IL) populations show that genotypes in the Black
542 Hills are more similar to the south-western genetic group, and it is not a hybrid population of the
543 south-western and eastern genetic groups. Additionally, observed heterozygosity between the
544 Black Hills and the south-western and eastern populations does not show a loss in genetic
545 diversity characteristic of a population bottleneck. Disjunct western populations in the Cypress
546 Hills (Chilton, 2003; Metheny et al., 2008; Lumley & Sperling, 2011; Dempsey et al., 2019) and
547 genetically distinct populations in the Black Hills (Smith, 1963; Weaver et al., 2006) have been
548 found across multiple taxonomic groups.
549 Conclusions
550 This study demonstrates that molecular methods are invaluable to bring clarification to
551 taxonomic relationships among taxa with little phenotypic diversity, but also a reminder that
552 each marker (mitochondrial vs nuclear) is limited in the information they provide about
553 evolutionary history. Our main goal was to see if genetic data corroborated subspecies
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554 designations in the warbling vireo complex. Secondly, we demonstrated the utility of combining
555 bioacoustic, morphological and ecological niche models to help characterize the variation of
556 cryptic species. We found that overall, our genetic data supported the distribution of the eastern
557 subspecies, gilvus, but our microsatellite genetic groups did not support the western subspecies,
558 swainsonii and brewsteri. More sampling needs to be done to fill the gaps between our north-
559 western and south-western populations to better determine where they come into contact. The
560 warbling vireo complex is comprised of at least two highly divergent genetic groups (eastern and
561 western) that also possess diagnostic acoustic, ecological, and morphological characters in
562 allopatry. Although the observed genetic differentiation between eastern and western warbling
563 vireos is equal to, or greater than, 33 other pairs of North American avian sister taxa that are
564 recognized as separate species (Johnson & Cicero, 2004), it is argued that genetic data alone are
565 weak evidence to imply reproductive isolation (Winker, 2009). Therefore, additional study in
566 western North America of all three genetic groups in areas of sympatry, or contact zones, to
567 evaluate reproductive isolation is proposed before taxonomic revision.
568 ACKNOWLEDGMENTS
569 We thank all of the graduate students and field assistants that helped with field sample
570 collection. A special thanks to the following museums whose voucher sample contributions
571 made this range-wide research possible: the Denver Museum of Nature and Science, the Burke
572 Museum of Natural History and Culture, the Natural History Museum University of Oslo, the
573 University of Michigan Museum, the Field Museum of Natural History, the Cleveland Museum
574 of Natural History, and the Royal Alberta Museum. We would like to acknowledge the work of
575 the Cornell Lab of Ornithology, and all of its collaborators, in the eBird database. We also thank
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576 the editor and the three anonymous reviewers for their comments that helped improve the
577 manuscript.
578 Samples were collected under the appropriate provincial, state, and federal permits. This work
579 was funded by the Natural Sciences and Engineering Research Council of Canada (NSERC
580 Discovery Grant RGPIN-2019-05068) (T.M.B.) and the National Science Foundation
581 (DEB0814841) (G.M.S). The authors declare they have no conflicts of interest.
582 DATA AVAILABILITY
583 The sequence data underlying this article are available in GenBank with the following accession
584 numbers: MZ020223 - MZ020331.
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863 SUPPORTING INFORMATION
864 Table S1. Microsatellite primer names and sequences, average number of alleles per locus (N), 865 size range (bp), annealing temperature (TA), average expected and observed heterozygosity 866 (HE/HO), and source with the species the primers were originally designed for. Sequences 867 marked with an asterisk were modified from the original source.
Locus Primers (5’ – 3’) Alleles (N) Range (bp) TA (°C) HE HO Source and species F CTTGGATAGAGCAGCCTCTG Barr et al. 2007 BCV2-6 R CAGTCTTATCATTGCAGGATAGC 4 204-220 52/54 0.50 0.44 Vireo atricapilla F TACGAGGATGTCACCGTATG Barr et al. 2007 BCV4-5 R CGGTTACTCAACACAGACCTC 13 257-350 52/54 0.88 0.87 V. atricapilla *F GCGCAGACAAAAGGATCTA Barr et al. 2007 BCV4-6 New R ATGGAGGTGGGAGGGAATA 7 174-220 50/52 0.71 0.59 V. atricapilla F ACTGCGTGTCCTGAATACGC Tarr & Fleischer 1998 Ck.1B5D R ACAAGACCAGAGCTTCAGCT 3 116-124 52/54 0.34 0.36 Corvus kubaryi F TTGCATCCCTGATTTATGGC Tarr & Fleischer 1998 Ck.4B6D R CTAGGAAGCAATCCAGAGTC 2 162-171 52/54 0.36 0.40 C. kubaryi F TGCTAAGCACAGTTAGAGAC Tarr & Fleischer 1998 Ck.2A5A R GAAGACAGGCAGGAGAGTTG 4 155-171 52/54 0.30 0.30 C. kubaryi F ACTGCAGAAAGCGATCACATTACG Hawley 2005 Hofi5 R GGCCCTCATTCCTCCTGCTTAC 10 348-378 50/52 0.85 0.82 Carpodactus mexicanus F TTCTGTGCTGCAATCACACA Bensch et al. 1997 Pocc1 R GCTTCCAGCACCACTTCAAT 9 226-250 55/57 0.77 0.80 Phylloscopus occipitalis F GGGAGCCTAGTATGTTAAGATGCT Stenzler & Fitzpatrick 2002 ApCo46 R TTCCAGGTGAGGTGATTCAGC 4 143-175 50/52 0.52 0.57 Aphelocoma coerulescens F ATGATGGTAAGTCTAATGAAAGC Piertney et al. 1998 Lox1 R CCACACACATTCACTCTATTG 4 274-286 50/52 0.31 0.28 Loxia scotica F ATCCAGTCTTCGCAAAAGCC Richardson et al. 2000 Ase18 R TGCCCCAGAGGGAAGAAG 4 210-230 55/57 0.54 0.56 Acrocephalus sechellensis F GGGATCTGTATTCATAGCATAAC Williams et al. 2004 CmAAAG30 R AATGGTAGAAACAGGAATTAGTG 15 250-400+ 55/57 0.90 0.93 Cyanocorax morio F CACAGACCATTCGAAGCAGA Martinez et al. 1999 Ppi2New *R GGCTGTGAGCAGTGTCTGAA 5 192-202 50/52 0.59 0.58 Pica pica F ATGGAGTGGAGGGAGAGATG Tarr & Fleischer 1998 Ck.1B6G R AGTACTACCAGTTCACCTGC 3 150-160 55/57 0.35 0.37 C. kubaryi 868
41 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.12.452121; this version posted July 13, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
869 Table S2. Values for mean, standard error (SE) and 95% confidence intervals (CI) lower bound (LB) and upper bound (UB) from the 870 morphological comparisons among subspecies and genetic groups. Significant comparisons (Sig) are bolded.
Variable Subspecies Mean SE Sig 95% CI LB 95% CI UB Genetic Group Mean SE Sig 95% CI LB 95% CI UB Mass (g) swainsonii 11.59 ± 0.11 a 11.38 11.81 North-western 11.61 ± 0.13 a 11.35 11.86 brewsteri 11.25 ± 0.19 a 10.87 11.63 South-western 11.35 ± 0.16 a 11.04 11.67 gilvus 14.16 ± 0.19 b 13.79 14.54 Eastern 14.16 ± 0.19 b 13.78 14.54 Wing Chord swainsonii 66.98 ± 0.20 a 66.59 67.38 North-western 67.04 ± 0.24 a 66.57 67.52 (mm) brewsteri 68.85 ± 0.35 b 68.17 69.54 South-western 68.09 ± 0.30 b 67.49 68.68 gilvus 69.96 ± 0.35 c 69.27 70.64 Eastern 69.96 ± 0.36 c 69.24 70.67 Tarsus swainsonii 17.68 ± 0.11 a 17.46 17.89 North-western 17.60 ± 0.13 a 17.35 17.85 (mm) brewsteri 18.40 ± 0.19 b 18.03 18.78 South-western 18.26 ± 0.16 b 17.94 18.57 gilvus 18.29 ± 0.19 b 17.92 18.66 Eastern 18.30 ± 0.19 b 17.93 18.68 Bill Length swainsonii 8.89 ± 0.13 a 8.63 9.15 North-western 8.93 ± 0.15 a 8.63 9.23 (mm) brewsteri 9.75 ± 0.23 b 9.30 10.19 South-western 9.38 ± 0.19 a 9.00 9.76 gilvus 9.00 ± 0.23 a 8.56 9.45 Eastern 9.00 ± 0.23 a 8.55 9.46 Bill Depth swainsonii 3.42 ± 0.03 a 3.36 3.49 North-western 3.37 ± 0.04 a 3.30 3.44 (mm) brewsteri 3.60 ± 0.06 b 3.50 3.71 South-western 3.62 ± 0.05 b 3.53 3.71 gilvus 3.95 ± 0.06 c 3.84 4.06 Eastern 3.96 ± 0.05 c 3.85 4.07 Bill Width swainsonii 4.06 ± 0.06 a 3.95 4.17 North-western 3.94 ± 0.06 a 3.82 4.07 (mm) brewsteri 4.66 ± 0.10 b 4.47 4.85 South-western 4.61 ±0.08 b 4.46 4.77 gilvus 4.51 ± 0.10 b 4.32 4.70 Eastern 4.53 ± 0.09 b 4.35 4.72 871
1 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.12.452121; this version posted July 13, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
872 Table 1. Population abbreviations and the number of individuals (N) used in cytochrome b 873 (cyt b), ATPase 6 and 8 (ATP), microsatellite (msat), and morphometric analyses. Populations 874 with an asterisk include some museum samples. 875 Population ID cyt b ATP msat morphometric NWBC (North-west British Columbia) 3 5 4 6 CBC (Central British Columbia) 2 4 24 24 JASPER (Jasper National Park, Alberta) 2 2 13 10 BANFF (Banff National Park, Alberta) - - 15 11 CASTLE (Castle Provincial Park, Alberta) 1 8 17 9 WLNP (Waterton Lakes National Park, Alberta) - 4 9 8 NEWA (North-east Washington) 3 - 14 14 SWBC (South-west British Columbia) 2 - 5 5 NWWA (North-west Washington)* - - 1 - VI (Vancouver Island)* 1 - 4 - CWA (Central Washington)* - - 20 - NEOR (North-east Oregon) * 3 3 10 3 SEOR (South-east Oregon)* - - 1 - CoOR (Coastal Oregon) 1 2 2 - CoCA (Coastal California)* - - 3 - NECA (North-east California) - - 3 3 SECA (South-east California)* - - 4 - SWNV (South-west Nevada)* 1 - 10 - NENV (North-east Nevada)* - - 10 - UT (Utah) 1 4 4 4 NM (New Mexico)* 1 - 8 1 SWCO (South-west Colorado)* 1 1 13 - CCO (Central Colorado)* 2 3 13 4 CWY (Central Wyoming)* 1 - 6 - NWWY (North-west Wyoming)* 1 1 10 1 SWMT (South-west Montana) - 7 29 26 CMT (Central Montana)* - - 4 - B HILLS (Black Hills)* 9 - 36 - SEAB (South-east Alberta) 22 - 24 22 CAB (Central Alberta)* 1 - 1 - SK (Saskatchewan) - - 10 11 ND (North Dakota) 4 - 16 17 SESD (South-east South Dakota)* 1 - 1 - MN (Minnesota)* - - 4 - IL (Illinois)* - - 8 - OH (Ohio)* - - 5 - ON (Ontario)* 2 - 17 - Total number of samples (N) 65 44 378 179 876
1 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.12.452121; this version posted July 13, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
877 Table 2. Pairwise FST comparisons for 23 populations (N > 5) based on 14 microsatellite loci genotypes. FST values are below 878 the diagonal line, with corresponding P-values above the diagonal line and significant values bolded.
CBC JASPER BANFF CASTLE WLNP NEWA CWA NEOR SWNV NENV NM SWCO CCO CWY NWWY SWMT HILLS B HILLSC HAT M SK ND IL ON CBC -- 0.29 0.02 0.06 0.18 0.17 <0.01 <0.01 <0.01 0.07 <0.01 <0.01 0.21 0.13 0.06 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 JASPER 0.00 -- 0.03 0.26 0.04 0.13 0.01 <0.01 0.01 0.04 <0.01 0.01 0.16 0.12 0.06 0.06 <0.01 0.06 <0.01 <0.01 <0.01 <0.01 <0.01 BANFF 0.02 0.02 -- 0.13 0.60 0.43 0.01 0.01 <0.01 0.04 0.01 0.03 0.15 0.28 0.04 0.03 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 CASTLE 0.01 0.01 0.01 -- 0.27 0.05 0.12 <0.01 <0.01 0.37 0.01 0.15 0.50 0.37 0.41 0.13 <0.01 0.03 <0.01 <0.01 <0.01 <0.01 <0.01 WLNP 0.01 0.02 0.00 0.01 -- 0.18 0.01 0.01 <0.01 0.08 <0.01 <0.01 0.20 0.12 0.21 0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 NEWA 0.01 0.01 0.00 0.02 0.01 -- 0.43 0.13 0.64 0.60 0.02 0.39 0.70 0.38 0.19 0.44 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 CWA 0.02 0.03 0.02 0.01 0.02 0.00 -- 0.45 0.03 0.76 0.01 0.70 0.49 0.76 0.30 0.03 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 NEOR 0.03 0.04 0.03 0.04 0.04 0.01 0.00 -- 0.14 0.26 0.02 0.05 0.35 0.52 0.15 0.04 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 SWNV 0.05 0.04 0.05 0.04 0.05 0.00 0.02 0.02 -- 0.08 0.03 0.08 0.09 0.22 0.18 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 NENV 0.02 0.02 0.02 0.00 0.02 0.00 0.00 0.01 0.02 -- 0.15 0.73 0.78 0.68 0.85 0.37 0.03 0.09 <0.01 <0.01 <0.01 <0.01 <0.01 NM 0.04 0.06 0.04 0.03 0.04 0.04 0.03 0.04 0.05 0.01 -- 0.27 0.32 0.78 0.20 0.06 0.22 0.02 <0.01 <0.01 <0.01 <0.01 <0.01 SWCO 0.03 0.03 0.02 0.01 0.03 0.00 0.00 0.02 0.02 0.00 0.01 -- 0.90 0.77 0.51 0.56 0.11 0.05 <0.01 <0.01 <0.01 <0.01 <0.01 CCO 0.01 0.01 0.01 0.00 0.01 0.00 0.00 0.00 0.02 0.00 0.01 0.00 -- 0.89 0.25 0.83 <0.01 0.02 <0.01 <0.01 <0.01 <0.01 <0.01 CWY 0.02 0.02 0.01 0.00 0.02 0.00 0.00 0.00 0.02 0.00 0.00 0.00 0.00 -- 0.89 0.65 0.94 0.52 <0.01 <0.01 <0.01 <0.01 <0.01 NWWY 0.02 0.02 0.02 0.00 0.01 0.01 0.00 0.02 0.02 0.00 0.01 0.00 0.01 0.00 -- 0.28 0.24 0.19 <0.01 <0.01 <0.01 <0.01 <0.01 SWMT 0.02 0.01 0.02 0.01 0.03 0.00 0.01 0.02 0.04 0.00 0.02 0.00 0.00 0.00 0.01 -- <0.01 0.04 <0.01 <0.01 <0.01 <0.01 <0.01 B HILLS 0.04 0.04 0.04 0.03 0.03 0.03 0.03 0.04 0.06 0.02 0.01 0.01 0.02 0.00 0.01 0.02 -- <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 C HILLS 0.03 0.02 0.04 0.02 0.04 0.05 0.03 0.04 0.05 0.02 0.03 0.02 0.02 0.00 0.01 0.02 0.02 -- <0.01 <0.01 <0.01 <0.01 <0.01 M HAT 0.10 0.10 0.11 0.10 0.11 0.10 0.13 0.18 0.09 0.09 0.09 0.10 0.08 0.09 0.09 0.11 0.09 0.10 -- 0.64 0.18 0.06 0.56 SK 0.12 0.10 0.13 0.10 0.14 0.12 0.13 0.17 0.10 0.11 0.09 0.10 0.08 0.08 0.08 0.10 0.08 0.09 0.00 -- 0.02 0.29 0.06 ND 0.13 0.12 0.13 0.12 0.13 0.12 0.15 0.21 0.10 0.14 0.12 0.13 0.12 0.12 0.11 0.13 0.10 0.12 0.01 0.03 -- 0.01 0.03 IL 0.17 0.13 0.18 0.14 0.19 0.19 0.19 0.25 0.14 0.17 0.16 0.17 0.14 0.16 0.16 0.15 0.14 0.13 0.04 0.01 0.04 -- 0.03 ON 0.16 0.16 0.18 0.16 0.19 0.16 0.19 0.25 0.14 0.16 0.14 0.14 0.13 0.15 0.14 0.15 0.13 0.14 0.00 0.02 0.02 0.03 -- 879
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880 881 Figure 1. Range distributions of the three warbling vireo subspecies in this study based on 882 Phillips (1991) and AOU (1998). Circles on the map show sampling locations included in the cyt 883 b analysis (top inset). Black circles are eastern haplotypes, whereas white circles are western 884 haplotypes. The eastern (Medicine Hat; M HAT) and western (Cypress Hills; C HILLS) groups 885 from the SEAB population are shown separately. The ATPase 6 and 8 results are not on the map 886 (bottom inset) and do not include the eastern group. Colors in the haplotype networks correspond 887 to our microsatellite genetic groups: eastern (black), north-western (grey), south-western (white), 888 and the Black Hills (striped). Each circle is a haplotype, and its size is proportional to how many 889 individuals share that haplotype. Cross hatches in the haplotype networks represent more than 890 one nucleotide difference. Refer to Table 1 for population abbreviations and sample sizes. 891
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892 893 894 Figure 2. Hierarchical STRUCTURE plots (K = 2) based on genotypes from 14 microsatellite 895 loci. Each bar represents a single individual, and the Q value is the percent ancestry of that 896 individual to each genetic group. Populations with additional hierarchical structure are shown in 897 yellow. (A) All populations (red = eastern group), (B) Western populations and the Black Hills 898 (orange), (C) Remaining western populations (north-western = green; south-western = blue). 899 Refer to Table 1 for population abbreviations and sample sizes. 900
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901 902 Figure 3. Thirty-seven warbling vireo populations genotyped at 14 microsatellite loci. Colors 903 correspond to the four genetic groups from STRUCTURE: eastern (red), north-western (green), 904 south-western (blue), and the Black Hills (orange) (see Figure 2). The eastern (Medicine Hat; M 905 HAT) and north-western (Cypress Hills; C HILLS) groups from the SEAB population are shown 906 separately. Refer to Table 1 for population abbreviations and sample sizes. 907
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908
909 Figure 4. Plots of the first two canonical axes based on discriminate function analysis of 910 warbling vireo songs. Colors and shapes correspond to three of the four microsatellite genetic 911 groups (Black Hills are not included): eastern (red/circle), north-western (green/square), and 912 south-western (blue/triangle). The largest shape represents the mean centroid for each genetic 913 group. 914
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915 916 Figure 5. Example song spectrograms and photos for each of the three warbling vireo genetic 917 groups used in our discriminate function analysis of songs. The colors of the outlines of the 918 spectrograms and photos correspond to DFA results in Figure 4. Photos were taken by the first 919 author. 920
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924 925 Figure 6. Contemporary ecological niche models for three of the four warbling vireo 926 microsatellite genetic groups (Black Hills are not included): north-western (top), south-western 927 (middle), and eastern (bottom). The logarithmic scale on the left depicts the percent likelihood 928 of habitat suitability based on climate variables.
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