Phylogenomics of arboreal alligator lizards shed light on the geographical diversification of cloud forest-adapted biotas

Abstract

Aim: The proximate ecological and evolutionary processes underlying the high biodiversity of neotropical montane cloud forests are still very poorly understood. Climatic oscillations may have contributed to vicariance and cladogenesis, but also promoted secondary contact and erosion of genetic divergence. Here we tested whether geographical diversification-or its lack thereof-in a complex of arboreal alligator lizards is explained by range shifts during Quaternary climatic oscillations.

Location: Pine-oak and cloud forests, central Mexico.

Taxon: Abronia taeniata-graminea species complex (Squamata: Anguidae: Gerrhonotinae).

Methods: We generated genomic data (ddRADseq) to infer patterns of geographical diversification in the complex, reconstruct its demographic history, estimate the timing of lineage split, and test for the presence of contemporary and/or historical hybridization. We evaluated whether the tempo and mode of diversification (i.e. strict isolation vs. secondary contact with introgression) are explained by the contemporary distribution of suitable habitats and/or range shifts experienced by the complex since the Last Glacial Maximum (LGM), as inferred from environmental niche modelling (ENM).

Results: Genomic data supported a marked genetic structure within the complex, and phylogenomic and dating analyses revealed cryptic lineage diversification starting at the onset of the Pleistocene followed by secondary contact with limited introgression. ENM pointed to considerable range expansions of the complex during the LGM and a marked fragmentation and scarce connectivity among contemporary populations , which was supported by genomic-based demographic reconstructions.

Main Conclusions: The geographical diversification of the complex has been moulded by vicariant events promoted by Pleistocene geologic and climatic changes impacting the distribution of their pine-oak and cloud forest habitats. Our data supported a model of divergence with introgression, indicating that pulses of population fragmentation and expansion during the Quaternary have led to multiple opportunities for both allopatric isolation and secondary contact.

Full text

Journal of Biogeography. 2022;00:1–15.
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1wileyonlinelibrary.com/journal/jbi
Received: 23 October 2021
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Revised: 13 April 2022
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Accepted: 30 April 2022
DOI: 10.1111/jbi.14 461
RESEARCH ARTICLE
Phylogenomics of arboreal alligator lizards shed light on the
geographical diversification of cloud forest- adapted biotas
Jorge Gutiérrez- Rodríguez1,2 | Adrián Nieto- Montes de Oca1 | Joaquín Ortego2 |
Alejandro Zaldívar- Riverón3
This is an open access article under the terms of the Creative Commons Attribution- NonCommercial- NoDerivs License, which permits use and distribution in
any medium, provided the original work is properly cited, the use is non- commercial and no modifications or adaptations are made.
© 2022 The Authors. Journal of Biogeography published by John Wiley & Sons Ltd.
1Laboratorio de Herpetología,
Departamento de Biología Evolutiva,
Facultad de Ciencias, Universidad
Nacional Autónoma de México, Ciudad
Universitaria, Ciudad de México, Mexico
2Departamento de Ecología Integrativa,
Estación Biológica de Doñana, EBD- CSIC ,
Sevilla, Spain
3Colección Nacional de Insectos,
Instituto de Biología, Universidad
Nacional Autónoma de México, Ciudad
Universitaria, Ciudad de México, Mexico
Correspondence
Jorge Gutiérrez- Rodríguez, Departamento
de Ecología Integrativa, Estación Biológica
de Doñana, EBD- CSIC , Avda. Américo
Vespucio 26, E- 41092 Sevilla, Spain.
Email: j.gutierrez@csic.es
Funding information
Consejo Nacional de Ciencia y Tecnología;
Dirección General de Asuntos del
Personal Académico, Universidad
Nacional Autónoma de México, Grant/
Award Number: IN218522 and IN201119;
CONACyT, Grant/Award Number: 58548
Handling Editor: Greer Dolby
Abstract
Aim: The proximate ecological and evolutionary processes underlying the high biodi-
versity of neotropical montane cloud forests are still very poorly understood. Climatic
oscillations may have contributed to vicariance and cladogenesis, but also promoted
secondary contact and erosion of genetic divergence. Here we tested whether geo-
graphical diversification – or its lack thereof – in a complex of arboreal alligator lizards
is explained by range shifts during Quaternary climatic oscillations.
Location: Pine– oak and cloud forests, central Mexico.
Tax o n: Abronia taeniata– graminea species complex (Squamata: Anguidae: Gerrhonotinae).
Methods: We generated genomic data (ddRADseq) to infer patterns of geographi-
cal diversification in the complex, reconstruct its demographic history, estimate the
timing of lineage split, and test for the presence of contemporary and/or historical
hybridization. We evaluated whether the tempo and mode of diversification (i.e. strict
isolation vs. secondary contact with introgression) are explained by the contempo-
rary distribution of suitable habitats and/or range shifts experienced by the complex
since the Last Glacial Maximum (LGM), as inferred from environmental niche model-
ling (ENM).
Results: Genomic data supported a marked genetic structure within the complex, and
phylogenomic and dating analyses revealed cryptic lineage diversification starting at
the onset of the Pleistocene followed by secondary contact with limited introgres-
sion. ENM pointed to considerable range expansions of the complex during the LGM
and a marked fragmentation and scarce connectivity among contemporary popula-
tions, which was supported by genomic- based demographic reconstructions.
Main Conclusions: The geographical diversification of the complex has been moulded
by vicariant events promoted by Pleistocene geologic and climatic changes im-
pacting the distribution of their pine– oak and cloud forest habitats. Our data sup-
ported a model of divergence with introgression, indicating that pulses of population

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1 | INTRODUC TION
Neotropical montane oak forests extend from central Mexico to
Andean Colombia in northern South America (Kappelle, 2006).
A particular type of montane oak forests are cloud forests, which
are characterized by the persistent presence of clouds and mists.
These forests have a remarkable vascular plant diversity, accom-
panied by an extraordinary richness of non- plant species (Espejo-
Serna, 2014), such as gall- forming insects (Oyama et al., 2006), bats
(Sánchez- Cordero, 2001), amphibians (Gual- Díaz & Goyenechea
Mayer- Goyenechea, 2014; Wake, 1987) and reptiles (Goyenechea
Mayer- Goyenechea & Gual- Díaz, 2014; Wilson et al., 2010), among
many other taxa. The geographical distribution of these cloud for-
ests has been conditioned by the geological and climatic history
of the American continent and the evolution of its flora (Kappelle
et al., 1992). Cloud forests present a highly fragmented distribution
forming a ‘sky- island archipelago’ (Flantua et al., 2020), which makes
them well- suited for vicariance modelling and analysing the geo-
logical and climatic drivers of diversification (Gutiérrez- Rodríguez
et al., 2011; Luna- Vega et al., 2004). The remarkable high biodiver-
sity associated with cloud forests has been hypothesized to be pro-
moted by the volcanic activity and climate changes occurring during
the late Pliocene and Pleistocene (Ferrusquía- Villafranca, 1993;
Ornelas et al., 2013; Rzedowski, 1993). Environmental changes pro-
moted the fragmentation and expansion of these habitats during
Quaternary climatic oscillations, being of particular importance to
some species associated with the cloud forest ecosystem (Jaramillo-
Correa et al., 2009; Ramírez- Barahona & Eguiarte, 2013). The dis-
tributions of these species likely contracted and fragmented during
interglacial periods and expanded into the lowlands during gla-
cial cycles (Colinvaux et al., 2000), which is expected to have led
to the progressive isolation of populations, shaped its spatial pat-
terns of genetic variation and contributed to processes of species
diversification.
The major centre of oak species diversity is located in the high-
lands of central and eastern Mexico (Nixon, 1993) and overlaps in
distribution with the centre of diversification of Abronia Gray, 1838
(Anguidae: Gerrhonotinae), a genus of alligator lizards endemic to
Mesoamerica. The genus Abronia currently contains 40 recognized
taxa that form multiple independent clades of arboreal and ter-
restrial species distributed from northeastern Mexico to southern
Honduras (Clause et al., 2020; Gutiérrez- Rodríguez et al., 2021;
Solano- Zavaleta & Nieto- Montes de Oca, 2018). Most species of
arboreal Abronia have allopatric distributions and usually occur in
montane habitats with cloud and seasonally dry pine– oak forests
(Campbell & Frost, 1993). Here we focus on the Abronia taeniata-
graminea species complex, which currently comprises two closely
related species surrounded by considerable taxonomic uncertainty:
Abronia taeniata (Wiegmann, 1828) and A. graminea (Cope, 1864).
Phylogenetic analyses indicate that A. graminea is paraphyletic with
respect to A. taeniata (Gutiérrez- Rodríguez et al., 2021) and recent
studies have also suggested that the two taxa might be sympatric
and potentially interbreed in contact zones (Clause et al., 2018;
Woolrich- Piña et al., 2017).
The geographical distribution of the A. taeniata– graminea spe-
cies complex is of considerable biogeographical interest because it
lies at the confluence of three physiographic provinces (Ferrusquía-
Villafranca, 1993): Sierra Madre Oriental (SMO), Trans- Mexican
Volcanic Belt (TMVB) and Sierra Madre del Sur (SMS). Few studies
have focused on the analysis of diversification processes of arboreal
taxa inhabiting this region, being mainly restricted to small mam-
mals and other organisms (Almendra et al., 2014; León- Paniagua
et al., 20 07; Ornelas et al., 2010; Rocha- Méndez et al., 2019; Vallejo
& González- Cózatl, 2012). Most of these studies have shown that
diversification among currently extant species occurred during the
Pliocene– Pleistocene and phylogenetic inferences point to a colo-
nization from the SMS to the SMO through the eastern end of the
TMVB. Mexican physiographic provinces have a complex geological
history. The SMO and SMS provinces mainly originated after de-
formation of Mesozoic rocks that were raised during the Laramide
orogeny 40 to 20 million years ago (Ma) (De Antuñano et al., 2000;
Nieto- Samaniego et al., 2006), and its current geomorphological
configuration was not completed until the early Holocene (Brouillet
& Whetstone, 1993; Maldonado- Koerdell, 1964). On the other
hand, the TMVB has a relatively more recent origin dating from
the Neogene (Ferrusquía- Villafranca, 1993; Ferrusquía- Villafranca
et al., 2005). The intricate confluence of the above three physio-
graphic provinces makes of this region one of the most important
montane biodiversity hotspots in Mexico, especially for oak– pine
cloud forests (Rzedowski, 2006).
In this study, we integrated genomic data and environmental
niche modelling (ENM) to shed light on the historical processes
shaping geographical diversification in the A. taeniata– graminea spe-
cies complex. Specifically, we tested whether the tempo and mode
of diversification (strict isolation vs. secondary contact with intro-
gression) are explained by the contemporary distribution of suitable
habitats and/or range shifts experienced by the complex linked to
Pleistocene glacial– interglacial cycles. To this end, we first charac-
terized the genetic structure of populations across the geographi-
cal distribution of the complex and employed diverse phylogenomic
fragmentation and expansion during the Quaternary have led to multiple opportuni-
ties for both allopatric isolation and secondary contact.
KEY WORDS
hybridization, introgression, Mesoamerica, Reptilia, Squamata

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GUTIÉRR EZ- RODRÍGUE Z ET al.
approaches to reconstruct the relationships among main recovered
lineages and assess the support for current taxonomic classification.
In the second step, we used Bayesian clustering analyses to infer
contemporary hybridization (or its lack thereof) among lineages in
putative contact zones and performed phylogenetic network tests
to evaluate alternative scenarios of post- divergence gene flow that
might explain uncertain phylogenetic relationships and distinguish
incomplete lineage sorting from introgression events. Third, we
employed the multispecies coalescent model to estimate the timing
of lineage split and determine whether the onset of diversification
within the complex could be explained by geological and climatic
changes during the Quaternary or if, alternatively, divergences
largely predate the Pliocene– Pleistocene boundary. Finally, we used
ENM and reconstructed changes in effective population size through
time to evaluate whether shifting distributions and the demographic
history experienced by the species complex explain geographical di-
versification and are compatible with processes of historical and/or
contemporary gene flow inferred from genomic data.
2 | MATERIALS AND METHODS
2.1 | Taxon sampling
We generated ddRADseq data for a total of 38 specimens of A.
taeniata and A. graminea. We used two specimens of A. fuscolabi-
alis (Tihen, 1944) as an outgroup for phylogenomic analyses. This
species was recovered as sister to A. taeniata + A. graminea in a re-
cent study carried out for the genus Abronia (Gutiérrez- Rodríguez
et al., 2021). Tissue samples of A. graminea and A. taeniata were col-
lected across most of their respective geographical distributions, in-
cluding specimens sampled near the respective type localities of the
two taxa (Table S1; Figure 1a). We also sampled populations from the
putative contact zone in the states of Puebla and Veracruz proposed
by Clause et al. (2018) to test whether there has been gene flow
between the two species. Specimens were identified following the
morphological key to species in Clause et al. (2018) and Campbell
and Frost (1993). We followed the classification of Mexican physi-
ographic provinces proposed by Ferrusquía- Villafranca (1993).
2.2 | ddRADseq libraries
Genomic DNA was extracted using the EZ- 10 Spin Column Genomic
DNA Miniprep kit (BIO BASIC) and purified using 1.5× S e r a - M a g
Magnetic Speed- beads (Thermo Fisher®). We assessed DNA quality
by means of agarose gel electrophoresis and quantified DNA using a
Qubit Fluorometer (Thermo Fisher Scientific®).
We followed the ddRADseq protocol described by Peterson
et al. (2012). In brief, genomic DNA from each sample was digested
with the restriction enzymes SbfI (restriction site 5′- CCTGCAGG- 3′)
and MspI (restriction site 5′- CCGG- 3′). These fragments were pu-
rified with 1.5× Sera- Mag Magnetic Speed- beads. Subsequently,
specific adapters for the enzymes Sbf I and MspI were ligated to the
DNA fragments. DNA ligands were purified with 1.5× S e r a - M a g
Magnetic Speed- beads before amplification of the libraries. An en-
richment PCR of each sample was performed using a KAPA Long
Range DNA Polymerase (Kapa Biosystems) and specific adapters for
the Illumina sequencer. We purified the ddRADseq libraries using
1.5× Sera- Mag Magnetic Speed- beads and performed DNA size
selection at 500 ± 50 bp using a Pippin Prep automated size selec-
tor (Sage Science®). Libraries were sequenced on an Illumina HiSeq
2500 platform (single- read, 150 bp) at the University of Georgia
(USA).
2.3 | ddRADseq bioinformatic processing
Quality of raw Illumina reads was assessed using the software
program fastqc 0.11.5 (Andrews, 2010). ddRADseq datasets were
subsequently processed using the pipeline ipyrad 0.7.19 (Eaton &
Overcast, 2016). Reads were filtered using the default phred Q score
offset for quality of 33, and sequences with more than 10 ambigu-
ous (N) sites were discarded. We used the trimming option for re-
moving all lllumina adapters. A de novo clustering was performed
using vsearch 1.1.3 (Rognes et al., 2016), and the resulting clusters
were aligned with muscle 3.8.31 (Edgar, 2004). The level of sequence
similarity was selected following Ilut et al. (2014) to avoid the use of
an arbitrar y clustering threshold and to minimize false homozygosity
and heterozygosity. To this end, we ran custom scripts developed
by Ilut et al. (2014) for each sample at different thresholds (from
0.80 to 0.99). The optimal clustering threshold (the inflection point
of the linear plateau) was selected using the r package ‘easynls’ 5.0
(Arnhold, 2017). We generated nine different sequence alignment
matrices with increments of ~10% in minimum number of samples
with data per locus (Table S2). Analyses of these matrices allowed
us to explore the effect that different percentages of missing data
have on the robustness of phylogenetic analyses. We estimated the
percentage of missing data in each matrix with the program vcftools
0.1.14 (Danecek et al., 2011).
2.4 | Phylogenetic analyses
We reconstructed the phylogenetic relationships among main
lineages within the complex using two methods: the Maximum
Likelihood (ML) method based on concatenated data implemented in
raxml 8.0 (Stamatakis, 2014) and the coalescent- based species- tree
approach implemented in astral- iii 5.6.3 (Zhang et al., 2018).
We performed ML phylogenetic analyses in raxml using the nine
matrices at different minimum percentages of samples with data for
a locus to be included in the alignment (i.e. different proportions of
missing data; Table S2). The matrices included all concatenated loci
with single nucleotide polymorphisms (SNPs) and invariant sites to
improve branch length and topological accuracy in phylogenetic
reconstructions (Leaché et al., 2015). All analyses were run on the

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GU TIÉRRE Z- RODRÍGUEZ ET al.
CIPRES Science Gateway 3.3 (Miller et al., 2010). We carried out a
simultaneous search to obtain the best- scoring ML tree. Rapid boot-
strap analyses were also conducted with the GTR- GAMMA model,
using 1000 bootstrap replicates starting from random seeds.
We used the software astral- iii a nd th e most in form ative genom ic
dataset (matrix F96m80; see Table S2 and Section 3) to reconstruct
a coalescent- based species tree. First, ML gene trees were esti-
mated for each locus with the pipeline magnet 0.1.9 (Bagley, 2019a,
2019b) using the software raxml. Rapid bootstrap analyses were
also conducted with the GTR- GAMMA model and using 100 boot-
strap replicates starting from random seeds. We collapsed branches
with considerably low support (below 10% bootstrap support) in
each gene tree using newick 1.6 (Junier & Zdobnov, 2010), which
can improve accuracy of species trees by reducing noise (Zhang
et al., 2018). The species tree was then inferred in astral- iii using as
input 1404 ML gene trees. Phylogenetic trees were edited using the
software figtree 1.4.4 (Rambaut, 2018) and adobe illustrator cs5.
2.5 | Phylogenetic network analyses
We used phylonetworks 0.12.0 (Solís- Lemus et al., 2017) to assess
whether a strictly bifurcating phylogenetic tree (i.e. no hybridization)
or a phylogenetic network (i.e. one or more introgression events)
better explains the evolutionary histor y of the A. taeniata– graminea
species complex. First, we obtained quartet concordance factors for
within- species four- taxon sets from previously obtained raxml gene
trees (as detailed above for species tree analyses). The species tree
reconstructed in astral- iii (see above) was used as the starting tree
and the snaq method (Species Networks Applying Quartets; Solís-
Lemus & Ané, 2016) was used to infer the best phylogenetic network
testing a varying number of reticulation events (h from 0 to 5), each
optimized with 15 independent runs. The optimal number of re-
ticulation events was chosen using a heuristic approach by plotting
negative pseudolikelihood scores against h- values, as recommended
by Solís- Lemus et al. (2017).
FIGURE 1 (a) Geographical distribution of the samples of arboreal alligator lizards of the Abronia taeniata– graminea species complex from
central Mexico included in this study. Dot colours represent the five lineages recovered in phylogenomic analyses using raxml and astral- iii.
Background shows the main physiographic subprovinces within the physiographic provinces of Sierra Madre Oriental (SMO), Trans- Mexican
Volcanic Belt (TMVB) and Sierra Madre del Sur (SMS), following Ferrusquía- Villafranca (1993). White (A. taeniata) and black (A. graminea)
asterisks indicate the type locality of each species. (b) Results of Bayesian clustering analyses in structure. Pie charts show the probability
of assignment of individuals to each genetic cluster for K = 3. Background shows main geological periods. Specimen codes as described in
Table S1 and maps in Plate Carrée projection.

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GUTIÉRR EZ- RODRÍGUE Z ET al.
2.6 | Divergence times
We estimated divergence times among the main lineages (i.e. species
tree) using analyses A00 in software bpp 4.3.8 (Flouri et al., 2018). The
.loci file from ipyrad was edited, converted into a bpp input file and fil-
tered using custom r scripts (J- P. Huang, https://github.com/airbu gs/;
for details, see Huang et al., 2020). Since the examined sequences dif-
fer in length due to insertion– deletion polymorphisms (indels) at some
loci, we trimmed them to 142 bp and excluded those that were not
represented in at least one individual per lineage (i.e. loci with missing
taxa/lineages were removed). The resulting input file contained 1000
loci. We performed two A00 analyses in bpp. The first analysis was
performed under the multispecies coalescent (MSC) model (Rannala
& Yang, 2003), using as fixed topology the species trees obtained
with astral- iii. Because phylonetworks analyses inferred an introgres-
sion event from A. graminea into Abronia sp. nov. L1 (see Section 3),
we also ran a second analysis under the multispecies- coalescent- with-
introgression (MSci) model (Flouri et al., 2020). We applied an auto-
matic adjustment of fine- tune parameters and used the ‘diploid’ option
to indicate that the input sequences are unphased (Flouri et al., 2018).
To ensure the convergence of the analyses (effective sample size
>200), we ran two independent replicates for 1,000,000 generations
each, sampling every two generations, after a burn- in of 200,000 gen-
erations. We estimated divergence times using the equation 𝜏 = 2𝜇t,
where 𝜏 is the divergence in substitutions per site estimated by bpp, 𝜇
is the per site mutation rate per generation, and t is the absolute diver-
gence time in years (Walsh, 2001). We considered a mutation rate per
site per year of 5.60 × 10−10 , which was previously estimated for glass
lizards (Anguidae Ophisaurus; Perry et al., 2018).
2.7 | Analyses of genetic structure and admixture
We used structure 2.3.4 (Pritchard et al., 2000) to investigate the
genetic structure and admixture among samples of A . taeniata and
A. graminea. We ran these analyses using a dataset of 1644 unlinked
SNPs generated for the 38 specimens of the A. taeniata– graminea
species complex (i.e. excluding the outgroup A. fuscolabialis). We
ran structure under the admixture model, with 200,000 iterations
and discarding the first 100,000 as burn- in. We evaluated K ge-
netic clusters (from K = 1 to K = 10), with 15 independent repli-
cates for each value of K. We used the ΔK statistic to interpret
the number of genetic clusters (K) that best describes our data
(Evanno et al., 2005). We used the ‘greedy’ algorithm in clumpp 1.1.2
(Jakobsson & Rosenberg, 2007) to align multiple runs for the same
K value and visualized the results using structurly 0.1.0 (Criscuolo &
Angelini, 2020).
2.8 | Historical demography
We assessed historical changes in effective population size (Ne)
through time for each lineage using stairway plot 2 (Liu & Fu, 2020),
a method based on the site frequency spectrum (SFS) that does not
require whole- genome sequence data or reference genome informa-
tion (Liu & Fu, 2015). To calculate the SFS for each lineage, remove
all missing data, minimize errors with allele frequency estimates
and maximize the number of variable SNPs retained, we downsam-
pled each population group (lineage) to 75% of individuals using the
easySFS.py script (I. Overcast, https://github.com/isaac overc ast/
easySFS). Final site frequency spectra contained between 1863 (A.
taeniata L1) and 3014 (Abronia sp. nov. L1) variable SNPs. In analy-
ses, we considered a 3- year generation time (Clause et al., 2016),
assumed a mutation rate per site per year of 5.60 × 10−1 0 (Perry
et al., 2018) and performed 200 bootstrap replicates to estimate
95% confidence intervals (Liu & Fu, 2015).
2.9 | Environmental niche modelling
Occurrence records of A. taeniata and A. graminea were obtained
from voucher specimens deposited in natural history museums
(Clause et al., 2018; García- Vázquez et al., 2022) and collected dur-
ing the course of this study. To reduce the effects of sampling bi-
ases across geographical space, we ran our dataset using the ‘spThin’
package 0.2.0 in r (Aiello- Lammens et al., 2015) with 100 iterations
and 10 km between localities (Boria et al., 2014; Merow et al., 2013).
We obtained a final thinned dataset with 30 retained localities. To
build the ENM, we used the 19 bioclimatic variables based on modi-
fied versions of the CHELSA dataset 1.2 (available at https://chels a-
clima te.org/; Karger et al., 2017) available at Paleoclim (www.paleo
clim.org; Brown et al., 2018) with a resolution of 30 arcsec (ca. 1 km)
(Table S3). Models were calibrated applying a buffer of 0.5° of radius
around the thinned localities, thus likely including every area within
the species' dispersal capabilities. We built the models using wallace
1.1.0 (Kass et al., 2018) with the presence- background algorithm
maxent 3.4.1 (Phillips et al., 2006, 2017), which allows to select spe-
cific model settings approximating optimal levels of complexity using
the ‘ENMeval’ 2.0.0 r package (Muscarella et al., 2014). We tested
different combinations of feature classes (FC: Linear; Quadratic;
Linear and Quadratic; Hinge; Linear, Quadratic, and Hinge) and
regularization multipliers (RM: 1.0– 5.0, with 0.5 intervals). The op-
timal model was selected based on the Akaike information criterion
corrected for small sample sizes (AICc; Warren & Seifert, 2011).
Complementary to this, we evaluated the performance of the mod-
els using the ‘block’ method for data partitioning into training and
testing datasets (Muscarella et al., 2014). Specifically, we calculated
the area under the receiver- operating characteristic plot on the test-
ing data (AUCTEST) and the minimum training presence omission rate
(ORMTP). An AUCTEST value >0.9 suggests a high discriminatory abil-
ity of the model (Peterson et al., 2011), whereas an ORMTP close to
zero is indicative of a low degree of model overfitting (Radosavljevic
& Anderson, 2014). The ENM was projected to the present and the
Last Glacial Maximum (LGM) climate conditions using the r package
‘dismo’ (Hijmans et al., 2011). Projection to the LGM (ca. 21 ka) was
based on layers derived from the implementation of the CHELSA

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algorithm on PMIP3 data (CHELSA; Karger et al., 2017) and available
with a resolution of 30 arcsec at Paleoclim.
2.10 | Comparison of climatic niches
We compared the climatic niches between species pairs using the
occurrence records previously applied to estimate the ENM for the
species complex. We assigned species membership based on the
genetic distribution of the three delineated species (A. graminea, A.
taeniata and Abronia sp. nov.; see below) and discarding occurrences
located close to the borders between them. We used the same four
bioclimatic variables retained for ENM to calculate niche overlap
and perform niche equivalency and niche similarity tests based on
a principal component analysis (PCA- env, described in Broennimann
et al., 2012; Warren et al., 2008) with the r package ‘ecospat’ 3.2.1
(Di Cola et al., 2017). We quantified niche overlap between each pair
of species using occurrence density grids and the metric Schoener's
D (Schoener, 1968). Finally, we performed niche equivalency and
niche similarity tests between all pairs of species (Broennimann
et al., 2012; Warren et al., 2008). We used the option ‘alternative’
to test for niche conservatism (alternative = ‘higher’; i.e. the niche
overlap is more equivalent/similar than random) or for niche diver-
gence (alternative = ‘lower’; i.e. the niche overlap is less equivalent/
similar than random). We performed 1000 permutations to test each
hypothesis.
3 | RESULTS
3.1 | Genomic dataset
We obtained a total of 55,710,569 single- end sequence reads from
our 40 genotyped specimens, with an average of 1,392,764 reads per
sample (range = 197,331– 3,100,078; SD = 847,955; Table S1). The
levels of homozygosity and heterozygosity at different clustering
thresholds (from 0.80 to 0.99) are shown in Figure S1. The homozy-
gosity and heterozygosity levels increased and decreased, respec-
tively, when the clustering threshold increased. The percentage of
candidate paralogous loci (i.e. with more than two alleles) decreased
with higher clustering thresholds (Figure S1). The optimal clustering
threshold estimated with ‘easynls’ was 0.96. The optimal minimum
taxon coverage for the dataset was selected based on the number
of loci retained, percentage of missing data and phylogenetic signal
obtained in ML phylogenetic analyses in raxml. The most informative
matrix was the one in which each locus had data for a minimum of
80% of the samples in the alignments (hereafter, F96m80 dataset;
Table S2). A total of 644,836 clusters were obtained for the F96m80
dataset using 10 or more reads for majority rule base calling. The
number of parsimony- informative characters and unlinked SNPs for
the dataset were 5087 and 1373, respectively (Table S2). The ipy-
rad analyses estimated a mean heterozygosity of 0.0 057 and a mean
error rate of 0.0021.
3.2 | Phylogenetic analyses
Concatenated raxml analyses that employed different minimum
taxon coverage values had virtually identical topologies (Figure 2),
with the exception of the analyses based on the matrix in which
each locus had data for a minimum of 70% of the samples (hereafter,
F96m70 dataset; Figure S2). Abronia graminea and A. taeniata were
not recovered as reciprocally monophyletic in any analysis. The to-
pology recovered by most analyses comprises five main clades with
a clear geographical pattern. Of these main clades, two exclusively
contained specimens of A. graminea and A. taeniata, respectively,
whereas the remaining clades included intermingled samples as-
signed to the two taxa (Figure 2). Of the five main clades, one con-
tains specimens from the northernmost distribution of A. taeniata
in the Gran Sierra Plegada and Carso Huasteco subprovinces of the
SMO (hereafter, A. taeniata L1). This clade is sister to a clade with
intermingled specimens of A. taeniata and A. graminea from central
Veracruz and northern Puebla in the Carso Huasteco subprovince
(hereafter, A. taeniata L2). The se two ma in clades are sister to a clade
composed of specimens of A. graminea from central Veracruz and a
specimen of A. taeniata from Quimixtlán in central Puebla (hereafter,
A. graminea lineage), both in the TMVB. The above three main clades
are sister to two clades composed by specimens from localities in
the northern portion of the SMS, one with samples exclusively as-
signed to A. graminea and restricted to Puerto del Aire in Veracruz
(hereafter, Abronia sp. nov. L1) and a second with specimens as-
signed to A. graminea from southern Puebla and northern Oaxaca
(hereafter, Abronia sp. nov. L2). Coalescent- based gene tree analyses
in astral- iii recovered the same five main clades that were obtained
in the concatenated ML analysis with the F96m80 matrix (Figure 2),
although with higher branch support values (Figure S3).
3.3 | Phylogenetic network analyses
phylonetworks analyses showed a marked increase in the pseudolike-
lihood score from h = 0 to h = 1 (−13.375 vs. −9.931; Figure S4a),
supporting one hybridization event as the scenario best fitting the
genomic data. The hybridization event involved the introgression
from A. grami nea into Abronia sp. nov. L1, wi th ca. 24% of the genom e
of this lineage (γ = 0.244) originated from A . graminea (Figure S4b).
3.4 | Divergence times
Time- calibrated species trees under the MSC and MSci models are
shown in Figure 3. The analysis under the MSci model estimated
that the split between A. fuscolabialis and the A. taeniata−graminea
species complex occurred 2.82 Ma (95% highest posterior densities
[HPD]: 2.64– 3.00 Ma; Figure 3b). The divergence between Abronia
sp. nov. and the most recent common ancestor of A. taeniata and A.
graminea took place 1.46 Ma (95% HPD: 1.36– 1.56 Ma; Figure 3b)
and the divergence between A. taeniata and A. graminea dates back

|
7
GUTIÉRR EZ- RODRÍGUE Z ET al.
914 ka (95% HPD: 846– 983 ka; Figure 3b). The introgression from A.
graminea into Abronia sp. nov. L1 occurred 367 ka (95% HPD: 304–
429 ka; Figure 3b), slightly later than the separation of the two line-
ages of Abronia sp. nov. (416 ka; 95% HPD: 344– 492 ka; Figure 3b).
The introgression probability (ϕ) estimated by bpp for the introgression
event from A. graminea into Abronia sp. nov. L1 was 0.302 (Figure 3b),
which is similar to the inheritance parameter estimated by phylonet-
works (γ = 0.244; Figure S4b). The split between the two lineages of
FIGURE 2 Maximum likelihood consensus tree based on raxml analyses of arboreal alligator lizards of the Abronia taeniata– graminea species
complex from central Mexico. Analyses are based on the F96m80 matrix, that is, minimum number of samples with data for a locus to be included
in the alignment = 80%. Bootstrapping support values are indicated next to their respective branches. Individual codes as described in Table S1.
8.0E-4
A. fuscolabialis (MVZ177806)
A. taeniata (ERIC1)
A. taeniata (ANMO4593)
A. graminea (WSB)
A. graminea (Ab16)
A. graminea (AGC764)
A. graminea (AGC761)
A. fuscolabialis (ANMO2300)
A. taeniata (SNPuebla)
A. taeniata (ANMO4595)
A. taeniata (MVZ191071)
A. graminea (RSP41)
A. taeniata (AT2368)
A. taeniata (ANMO4594)
A. taeniata (AGC723)
A. taeniata (Ab9)
A. taeniata (ANMO4592)
A. taeniata (ERIC2)
A. taeniata (ISZ739)
A. graminea (MVZ191068)
A. taeniata (ISZ200)
A. taeniata (ISZ579)
A. graminea (CNAR1725)
A. graminea (ISZ738)
A. taeniata (ISZ245)
A. taeniata (WSB815)
A. graminea (ISZ544)
A. taeniata (FMQ3236)
A. taeniata (ISZ740)
A. graminea (RSP31)
A. graminea (MVZ191067)
A. graminea (UTA-R52861)
A. graminea (ART91)
A. taeniata (MVZ191072)
A. graminea (CNAR4954)
A. graminea (ISZ971)
A. taeniata (MVZ191074)
A. taeniata (CHJ1029)
A. graminea (ISZ545)
A. graminea (ISZ583)
57
99
100
99
86
100
100
97
100
54
65
100
96
77
87
100
100
96
100
100
65
51
74
94
100
56
99
61
82
100
100
83
85
100
A. taeniana L1
A. taeniana L2
A. graminea
A. sp. nov. L1
A. sp. nov. L2
FIGURE 3 Time- calibrated species trees of Abronia taeniata– graminea complex from central Mexico estimated using bpp under (a) the
multispecies coalescent (MSC) model and (b) the multispecies coalescent model with introgression (MSci). Bars on nodes indicate 95%
highest posterior densities (HPD) for divergence time estimates. Geologic ages within the Pliocene (Piacenzian) and Quaternary (Gelasian,
Calabrian, Middle and Upper) periods are indicated in the right y- axis.

8
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GU TIÉRRE Z- RODRÍGUEZ ET al.
A. taeniata took place 429 ka (95% HPD: 401– 461 ka; Figure 3b). As
expected, the divergence time between the two lineages of Abronia
sp. nov. was considerably overestimated (median = 667 ka; 95% HPD:
606– 737 ka; Figure 3a) under the MSC model without considering the
introgression event.
3.5 | Analyses of genetic structure and admixture
Bayesian clustering analyses performed with structure suppor ted an
optimal clustering solution for K = 2 according to the ΔK criterion.
At K = 2, one cluster included the specimens of the A. taeniata L1
and L2, and the second cluster grouped populations of Abronia sp.
nov. L1 and L2 (Figure S5). Specimens from Pico de Orizaba in cen-
tral Veracruz and from central Puebla (A . graminea) were identified
to have an admixed ancestry. structure analyses for K = 3 detected
an additional hierarchical level of genetic structuring, showing that
the admixed individuals of A. graminea detected at K = 2 form a new
genetic cluster (Figure 1b; Figure S5).
3.6 | Historical demography
stairway plot 2 analyses revealed declines of effective population
size (Ne) from the LGM to present for each analysed lineage of
the A. taeniata−graminea species complex (Figure 4). In the case
of A. taeniata L1 and A. taeniata L2, Ne peaked around the LGM
followed by an abrupt demographic decline from the LGM to pre-
sent (Figure 4). Analyses for the rest of the lineages (A. graminea,
Abronia sp. nov. L1, and Abronia sp. nov. L2) suggested a contin-
uous decline of Ne from the onset of the last glacial period to
present, but they must be interpreted with extreme caution due
to small sample sizes (n = 4– 5 genotyped specimens per lineage;
Figure 2).
3.7 | Environmental niche modelling
The optimal ENM according to the AICc was that with the settings
LQH 4.5 (FC = Linear, Quadratic and Hinge; beta multiplier = 2.5;
Figure S6). The high AUCTEST (AUCTEST = 0.887) and low ORMTP
(ORMTP = 0.05) estimates for the model with the highest support
indicate that it has high discriminatory power and a low degree of
overfitting, respectively. The full summary of model comparisons is
presented in Table S4. The four variables with the highest permuta-
tion importance retained in the model were precipitation of driest
quarter (BIO16: 62.6%), minimum temperature of coldest month
(BIO05: 31.0%), temperature annual range (BIO6: 5.7%) and mean
temperature of wettest quarter (BIO07: 0.7%). The predicted po-
tential distribution of the A. taeniata−graminea species complex was
largely congruent with its distribution based on available records
(Figure 5a). The model predicted that the distribution of the complex
is almost continuous from the southern portion of the SMO (Carso
Huasteco subprovince) to the SMS, with a small disjunct suitable
area in the northern portion of the SMO (Gran Sierra Plegada sub-
province) (Figure 5a). The projection of the ENM to LGM bioclimatic
conditions predicted an expanded distribution for the complex dur-
ing glacial periods in comparison to its current potential distribution,
with a large area of continuous suitable habitat from SMO to SMS
(Figure 5b).
3.8 | Comparison of climatic niches
The first two principal components of the environmental analysis
explained 92.18% of the variation (54.06% and 32.43%, respec-
tively). The niche equivalency test rejected the null hypothesis
of niche identity for all pairwise comparisons (p < 0.05; Table S5).
However, no pairwise comparison showed significant niche di-
vergence based on similarity tests (Table S5), indicating that the
environmental niches of the species are not more different than
expected by chance.
4 | DISCUSSION
Mesoamerican cloud forests are a centre of endemism for a large
number of organisms (Harris et al., 2000; Rocha- Méndez et al., 2019).
We have focused here on the confluence of the SMO, TMVB and
SMS provinces from Central Mexico, a region with a complex
FIGURE 4 Demographic history of each lineage of Abronia
taeniata– graminea species complex from central Mexico estimated
using stairway plot 2. Panels show median effective population sizes
(Ne) over time (x- axis in a logarithmic scale).

|
9
GUTIÉRR EZ- RODRÍGUE Z ET al.
geological, geographical and climatic history (Caballero et al., 2019;
De Cserna, 1989; Morrone, 2010; Sosa et al., 2016). Our results
consistently supported the existence of three main genetic lineages
within the A. taeniata−graminea complex, with a hierarchical north-
to- south distribution linked to the physiographic provinces that
they occupy and no evidence of sympatry between them (Figure 1).
Pleistocene geologic and climatic changes have conditioned the nat-
urally fragmented pine– oak and cloud forests inhabited by arboreal
Abronia, which has probably limited population connectivity through
extended periods of time and resulted in vicariant events within this
species complex.
4.1 | Diversification associated with geological
events during the Pliocene– Pleistocene
Neotropical cloud forests have experienced an archipelago- like
fragmentation process, making them highly suitable for studying
geographical diversification and allopatric speciation processes
(Luna- Vega et al., 2006). Our analyses indicated that the origin and
diversification of the A. taeniata– graminea species complex has
been most likely shaped by the complex geologic history of the re-
gion and distributional changes of the pine– oak forests that they
inhabit. Other groups of organisms inhabiting these cloud forests
share similar cladogenesis patterns, including rodents (Ávila- Valle
et al., 2012; Hardy et al., 2013; León- Paniagua et al., 2007), amphib-
ians (Caviedes- Solis & Leaché, 2018; García- Castillo et al., 2018;
Parra- Olea et al., 2020), lizards (Bryson et al., 2012) and birds (Mota-
Vargas et al., 2017).
Palaeogeographical events associated with the formation of the
low- elevation valley of the Santo Domingo River in the Papaloapan
basin likely explain the split of the ancestor of the A. taeniata– graminea
complex from A. fuscolabialis in the late Pliocene (2.82 Ma; 95% HPD:
2.64– 3.00 Ma; Figure 3b). The age of this divergence is concordant
with the radiation of arboreal mice species of the genus Habromys,
where a vicariant speciation event was proposed to take place in this
region ca. 3.92 Ma (León- Paniagua et al., 2007). Previous biogeograph-
ical studies have documented that the Papaloapan basin has played
an important role promoting allopatric speciation in highland organ-
isms with low vagility, such as small mammals (Carleton et al., 2002;
Guevara & Sánchez- Cordero, 2018; Rogers et al., 2007; Sullivan
et al., 1997; Vallejo & González- Cózatl, 2012), lizards (A. antauges
FIGURE 5 Present (a) and LGM (b) projections of the environmental niche model (ENM) in maxent for arboreal alligator lizards of
the Abronia taeniata– graminea species complex from central Mexico. Dots represent all known localities of specimens deposited in
herpetological collections. Maps in Plate Carrée projection. LGM, Last Glacial Maximum.
Potential Distribution
0
0.2
0.4
0.6
0.8
1
Literature Records
Potential Distribution
0
0.2
0.4
0.6
0.8
1
Literature Records
Present (a) LGM (b)

10
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GU TIÉRRE Z- RODRÍGUEZ ET al.
and A . juarezi; Solano- Zavaleta et al., 2017; Xenosaurus grandis and X.
manipulus; Nieto- Montes de Oca et al., 2022), pine– oak forest birds
(Mota- Vargas et al., 2017) and troglobiotic scorpions (Santibáñez-
López et al., 2014). In the same line, our results suggest that climati-
cally unfavourable areas across these low- elevation areas during both
the LGM and pr esent (Figure 5) limited and cont inue to limit second ary
contact between populations at both sides of the valley of the Santo
Domingo River (Sierra Mazateca and Sierra de Juárez).
Our dating analyses indicate that the diversification within the
A. taeniata– graminea complex took place during the Pleistocene.
The split between Abronia sp. nov. and A. taeniata + A. graminea
occurred ca. 1.46 Ma (95% HPD: 1.36– 1.56 Ma; Figure 3b), proba-
bly associated with the climatic conditions and orogenic processes
of the TMVB. The topographic evolution of the TMVB began in
the early- to mid- Miocene and finished in the late Pliocene and
Pleistocene, changing considerably the region over the last 3 Ma
(Mastretta- Yanes et al., 2015). At the end of the Pliocene, and be-
cause of a higher temperature, the geographical distribution of the
A. taeniata- graminea complex was probably more restricted than
today (Salzmann et al., 2011). At the same time, the volcanic ac-
tivity of the Cofre de Perote- Citlaltépetl Volcanic Range (eastern
TMVB) began in the Pliocene and continued during the Holocene,
shifting southwards more recently (Negendank et al., 1985; Schaaf
& Carrasco- Núñez, 2010) and promoting phylogenetic breaks in
other taxa between the Sierra Mazateca and southern SMO associ-
ated with the Blanco River basin (Parra- Olea et al., 2020; Streicher
et al., 2014). In this context, alternative biogeographical hypotheses
have been proposed for the Oaxacan highlands. Based on vascu-
lar plants from cloud forests, the Sierra Mazateca could be a mix-
ture between the SMO and the Sierra de Juárez (SMS; Luna- Vega
et al., 1999). Alternatively, based on distributional patterns of ver-
tebrate taxa, the Sierra Mazateca could be more closely related
to the SMO than to the Sierra de Juárez (SMS) (León- Paniagua &
Morrone, 2009). Our analyses support a biogeographical scenario in
line with León- Paniagua and Morrone (2009)'s hypothesis.
Regarding the divergence event between A. graminea and A. tae-
niata, it was estimated to date back to ca. 914 ka (95% HPD: 846–
983 ka; Figure 3b). According to geological records, the formation of
basal structure of Cofre de Perote volcano began around 1.3– 0.51 Ma
(Carrasco- Núñez et al., 2010), probably limiting gene flow between
populations of the common ancestor of A. graminea + A. taeniata. This
biogeographical break is shared with species of anguid lizards of the
genus Celestus. Celestus enneagrammus has a similar distribution than
A. graminea, occurring in Xalapa and Orizaba in the state of Veracruz,
whereas its sister species, C. legnotus, is distributed in the SMO of
Puebla (Campbell & Camarillo, 1994; Werler & Campbell, 2004).
Finally, within A. taeniata, the split between the lineages A.
taeniata L1 and A. taeniata L2 probably took place around Middle
Pleistocene, ca. 429 ka (95% HPD: 401– 461 ka; Figure 3b). Over the
last 600 ka, fragmentation of species distributions was intensely
favoured by climatic oscillations every ~100 ka between warm in-
terglacial and cold glacial periods (Huybers, 2007). Besides, in the
confluence zone between both lineages, situated in the Acoculco
caldera (between Hidalgo and Puebla states), the volcanic activity
had an explosive event around 600 ka (Avellán et al., 2020), coincid-
ing with the divergence between both lineages.
4.2 | Pleistocene climatic oscillations as an
engine of speciation
Although it is clear that the high biodiversity in Mesoamerican high-
lands has been fuelled by a series of geological and climatic events
occurred during the Pleistocene (Ferrusquía- Villafranca, 1993;
Graham, 1999; Rzedowski, 1993), antagonistic hypotheses have been
proposed to explain it. One hypothesis proposes that montane taxa
associated with cloud forests were isolated in high- elevation refu-
gia during Pleistocene glacial periods (Haffer, 1969; Toledo, 1982;
Wendt, 1987). However, another hypothesis suggested a relict dis-
tribution of highland taxa during interglacial periods, with expan-
sions to the lowlands during the coldest stages of the Pleistocene
(Bush & Colinvaux, 1990; Colinvaux et al., 2000). In the case of the
A. taeniata– graminea species complex, past climate model projec-
tions fit the second hypothesis. The confinement of contemporary
populations to high elevations and their limited connectivity based
on the projection of the distribution model to current bioclimatic
conditions indicates that the species complex has probably expe-
rienced range contractions during interglacial periods. In contrast,
ENM projections to the LGM inferred an increase in suitable habi-
tats towards lowlands during the cooler stages of the Pleistocene
(Figure 5). Inferences from ENM were supported by genomic- based
reconstructions of the past demographic history of the complex,
which showed a decrease in effective population size (Ne) from LGM
to present in all lineages (Figure 4). These results agree with genetic
diversification of Moussonia deppeana (Gesneriaceae), a cloud forest
shrub co- distributed with the A. taeniata– graminea species complex
(Ornelas & González, 2014). During interglacial periods, warm cli-
mate would have led to the contraction and fragmentation of the
cloud forest shrub populations and their displacement to higher el-
evations. In contrast, during the glacial periods with colder and wet-
ter climates, populations of M. deppeana expanded downhill likely
contributing to increased connectivity of associated arboreal lizard
populations (Ornelas & González, 2014).
4.3 | Limited historical hybridization
Our genome- wide sequence data consistently showed no evidence
for contemporary hybridization among the main lineages that inte-
grate the A. taeniata– graminea species complex, which rejects the
hypothesis of ongoing or recent hybridization between A. graminea
and A. taeniata in a putative contact zone in the Sierra Norte de
Puebla (Clause et al., 2018). The current habitat fragmentation and
low connectivity among populations and the allopatric distribution
of the different lineages (Figure 1a) are expected to have consid-
erably limited the opportunity for contemporary hybridization.

|
11
GUTIÉRR EZ- RODRÍGUE Z ET al.
However, phylogenetic network analyses revealed the existence
of an introgression event (ca. 367 ka) from A. graminea into Abronia
sp. nov. L1, with ca. 24% of the genome of the introgressed lineage
originated from A. graminea (Figure 3b; Figure S4). In the same local-
ity, a potential contact zone was described between two subspe-
cies of the Sumichrast's harvest mouse (Reithrodontomys sumichrasti
sumichrasti and R. s. luteolus; Hardy et al., 2013). Although the pro-
jection of the ENM to LGM bioclimatic conditions supported range
expansions, considerable connectivity among populations, and likely
secondary contact during the coldest stages of the Pleistocene, our
results indicate that historical hybridization was limited to an an-
cient introgression event only involving two lineages with parapatric
distributions. Different factors could explain limited evidence for
historical gene flow. First, secondary contact between cloud forest-
adapted lineages could have been limited by volcanic activity dur-
ing glacial periods. This activity in the highlands from the eastern
TMVB fragmented cloud forest habitats (Ferrari et al., 2012), which
could have facilitated sky- island dynamics and promoted and main-
tained lineage divergence through the Pleistocene. Second, diverg-
ing lineages might have evolved reproductive isolation mechanisms
preventing hybridization during periods of secondary contact, which
might be particularly relevant considering the limited environmental
niche divergence among the different species (i.e. lack of evidence
for niche divergence; Table S5). Accordingly, the estimated timing
of the introgression event suggests that the two lineages have not
experienced gene flow during the last ca. 350 ka, despite several
glacial– interglacial cycles have likely promoted shifting distributions
since then and provided opportunity for secondary contact and
gene flow. Thus, these two lineages could have developed reproduc-
tive isolation in allopatry or via reinforcement (i.e. selection against
hybrids) during secondary contact (e.g. Tonzo et al., 2020).
The full- fledged species status of the three lineages is strength-
ened by the absence of contemporary gene flow between them
and limited evidence for historical hybridization. In case of the ex-
istence of interbreeding between these taxa, it must be very lim-
ited geographically. The findings obtained in this study indicate the
existence of three taxa that are genetically well differentiated and
whose divergence dates back to >914 ka (Figure 3). The morphologi-
cal characters used so far for species identification within this group,
that is, adult dorsal coloration and the number of transverse dorsal
and longitudinal nuchal scale rows (Clause et al., 2018), must there-
fore be reviewed based on our genomic- based inferences.
ACKNOWLEDGEMENTS
We thank A. G. Clause and W. Schmidt Ballardo for the donation of
specimens and tissues. This study was funded by grants from UNAM
(PAPIIT- DGAPA, proyecto no. IN218522) to A.N.- M.d.O., and grants
from CONACyT (Convoctoria Ciencia de Frontera 2019 no. 58548)
and UNAM (PAPIIT- DGAPA, proyecto no. IN201119) to A.Z.- R. We
also thank the Dirección General de Cómputo y de Tecnologías de
Información y Comunicación (DGTIC, UNAM) for resources pro-
vided to run some of the analyses in the Miztli super- computer
(Proyecto de investigación regular LANCAD UNAM- DGTIC- 339).
J.G.- R. was supported by a post- doctoral grant from the Dirección
General de Asuntos del Personal Académico (DGAPA), Universidad
Nacional Autónoma de México. Specimens were collected under a
research permit issued to A.N.- M.d.O. by the Mexican government
(SEMARNAT, permit no. SGPA/DGVS/003072/18).
CONFLICTS OF INTEREST
The authors have no conflict of interest to declare.
DATA AVA ILAB ILITY STATE MEN T
Raw Illumina reads have been deposited at the NCBI Sequence
Read Archive (SRA) under BioProject PRJNA825505. Input files
for all analyses are available for download on Dryad (ht t p s: //doi .
org/10.5061/dryad.6m905 qg28).
ORCID
Jorge Gutiérrez- Rodríguez https://orcid.
org/0000-0003-3968-5257
Adrián Nieto- Montes de Oca https://orcid.
org/0000-0002-8150-8361
Joaquín Ortego https://orcid.org/0000-0003-2709-429X
Alejandro Zaldívar- Riverón https://orcid.
org/0000-0001-5837-1929
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BIOSKETCH
Jorge Gutiérrez- Rodríguez is a post- doctoral researcher at
Estación Biológica de Doñana (CSIC, Spain). His research inter-
ests include the study of diversification processes, comparative
phylogeography and landscape genetics of diverse organisms.
Author contributions: Jorge Gutiérrez- Rodríguez, Alejandro
Zaldívar- Riverón and Adrián Nieto- Montes de Oca designed
the research; Jorge Gutiérrez- Rodríguez and Joaquín Ortego
performed the analyses; Jorge Gutiérrez- Rodríguez drafted the
paper, with contributions of all authors in the final version. All
authors gave final approval for publication.
SUPPORTING INFORMATION
Additional supporting information can be found online in the
Supporting Information section at the end of this article.
How to cite this article: Gutiérrez- Rodríguez, J., Nieto-
Montes de Oca, A., Ortego, J., & Zaldívar- Riverón, A. (2022).
Phylogenomics of arboreal alligator lizards shed light on the
geographical diversification of cloud forest- adapted biotas.
Journal of Biogeography, 00, 1–15. https://doi.org/10.1111/
jbi.14461