ORIGINAL RESEARCH
published: 19 October 2021
doi: 10.3389/fpls.2021.724057
Biogeography of Argylia D. Don
(Bignoniaceae): Diversification,
Andean Uplift and Niche
Conservatism
Nataly S. Glade-Vargas 1,2* , Carla Rojas 1,2 , Paola Jara-Arancio 2,3 , Paula Vidal 1,2 ,
Mary T. Kalin Arroyo 1,2 and Luis Felipe Hinojosa 1,2*
1
Departamento de Ciencias Ecológicas, Facultad de Ciencias, Universidad de Chile, Santiago, Chile, 2 Instituto de Ecología
y Biodiversidad, Santiago, Chile, 3 Departamento de Ciencias Biológicas, Departamento de Ecología y Biodiversidad,
Facultad de Ciencias de la Vida, Universidad Andrés Bello, Santiago, Chile
Edited by:
Stefan Wanke,
Technische Universität Dresden,
Germany
Reviewed by:
Maximilian Weigend,
University of Bonn, Germany
Marie-Stéphanie Samain,
Instituto de Ecología (INECOL),
Mexico
*Correspondence:
Nataly S. Glade-Vargas
Nataly.glade@ug.uchile.cl
Luis Felipe Hinojosa
lfhinojosa@uchile.cl
Specialty section:
This article was submitted to
Plant Systematics and Evolution,
a section of the journal
Frontiers in Plant Science
Received: 11 June 2021
Accepted: 20 September 2021
Published: 19 October 2021
Citation:
Glade-Vargas NS, Rojas C,
Jara-Arancio P, Vidal P, Arroyo MTK
and Hinojosa LF (2021) Biogeography
of Argylia D. Don (Bignoniaceae):
Diversification, Andean Uplift
and Niche Conservatism.
Front. Plant Sci. 12:724057.
doi: 10.3389/fpls.2021.724057
Andean uplift and the concomitant formation of the Diagonal Arid of South America
is expected to have promoted species diversification through range expansions into
this novel environment. We evaluate the evolution of Argylia, a genus belonging to the
Bignoniaceae family whose oldest fossil record dates back to 49.4 Ma. Today, Argylia
is distributed along the Andean Cordillera, from 15◦ S to 38.5◦ S and from sea level up
to 4,000 m.a.s.l. We ask whether Argylia’s current distribution is a result of a range
expansion along the Andes Cordillera (biological corridor) modulated by climatic niche
conservatism, considering the timing of Andean uplift (30 Ma – 5 Ma). To answer this
question, we reconstructed the phylogenetic relationships of Argylia species, estimated
divergence times, estimated the realized climatic niche of the genus, reconstructed the
ancestral climatic niche, evaluated its evolution, and finally, performed an ancestral
range reconstruction. We found strong evidence for climatic niche conservatism for
moisture variables, and an absence of niche conservatism for most of the temperature
variables considered. Exceptions were temperature seasonality and winter temperature.
Results imply that Argylia had the capacity to adapt to extreme temperature conditions
associated with the Andean uplift and the new climatic corridor produced by uplift.
Ancestral range reconstruction for the genus showed that Argylia first diversified in a
region where subtropical conditions were already established, and that later episodes of
diversification were coeval with the of Andean uplift. We detected a second climatic
corridor along the coastal range of Chile-Peru, the coastal lomas, which allowed
a northward range expansion of Argylia into the hyperarid Atacama Desert. Dating
suggests the current distribution and diversity of Argylia would have been reached during
the Late Neogene and Pleistocene.
Keywords: Andes, diversity, phylogeny, niche conservatism, Bignoniaceae
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Biogeography of Argylia
Kozak and Wiens, 2007; Donoghue, 2008; Little et al., 2010;
Wiens et al., 2010; Hinojosa et al., 2016). Therefore, when new
environments appear, the latter would be occupied by lineages
that possess the relevant adaptations for these new conditions
and thus manage to colonize these areas by tracking their original
climatic niches.
The large family Bignoniaceae Juss. comprises trees, shrubs
and vines that are distributed largely in tropical areas and
to a lesser extent in temperate zones (Gleisner and Ricardi,
1969; Gentry, 1980; Olmstead, 2013). The oldest fossil record
attributed to Bignoniaceae dates to 49.4 Ma (Pigg and Wehr,
2002). Molecular analyses subdivide the family into nine clades
made up of 82 genera and 860 species (Lohmann, 2006). The
genus Argylia D. Don belongs to the Tecomeae clade (Olmstead,
2013) which together with the Tourrettieae and Jacarandeae
clades are the earliest branching clades of the family (Olmstead
et al., 2009). Argylia is exclusively distributed from southern Peru
(coastal lomas) to the Central Andes of Chile and Argentina.
Following the Arid Diagonal of South America, Argylia occurs
along the Andes ranges, on the western and eastern slopes but
mostly on the western slopes, from 15◦ S to 38.5◦ S, from sea level
to 4,000 m.a.s.l. Species commonly are found above 1,200 m.a.s.l.
A notable exception is Argylia radiata which is distributed mainly
along the Pacific coast (Figure 2).
Argylia is unusual in the Bignoniaceae for its perennial herb to
subshrub habit and presence of thick woody roots. The palmate
leaves with a long petiole are alternate to subopposite. The leaf
arrangement also distinguishes Argylia from other genera of
Bignoniaceae (Figure 3; Gentry, 1992). The large bell-shaped
flowers are cream to brick-red (including within the same
species). They appear adapted to bee-pollination. The genus has
wind-dispersed seeds.
Argylia is an excellent model for understanding the role
of the Andean uplift as promoter of arid environments on
plant evolution, and for evaluating the hypothesis of climatic
niche conservation in these new environments. In this study we
propose: Argylia initially diversified in an area subjected to the
South Pacific Subtropical High, the ancestral niche was arid, and
the lineage is characterized by niche conservatism in moisture
variables. This implies that the current distribution of Argylia
was attained over the period of Andean uplift and consequently
would have been affected by it. Specifically, we: (1) we establish
the phylogenetic relationships of species of the genus Argylia,
(2) determine the climatic conditions under which the genus
originated, (3) evaluate climatic niche conservatism during its
diversification, and finally, (4) evaluate the Andean uplift on the
diversification of the genus.
INTRODUCTION
Southern South America exhibits a wide range of climates that
results in an extraordinary diversity of biomes including forest,
grassland, steppe, alpine, and desert (Ortega et al., 2012). The
current distribution of these biomes reflects the interaction
of climatic factors and historical processes at different time
scales. These include past climate change, plate tectonics and
mountain building.
One of the most defining features of South America
biogeography is a large arid region with annual rainfall below
500 mm that crosses the western side of the continent diagonally
from northwest to southeast, beginning at coastal equatorial
latitudes (4◦ S) and culminating on the Atlantic coast at latitude
55◦ S. This region has been defined as the South American
Arid Diagonal (SAD, Veit and Garleff, 1995; Villagrán and
Hinojosa, 1997; Garreaud et al., 2010; Figure 1). SAD developed
gradually during the Oligocene and Miocene as a consequence
of the Andean uplift and the establishment of the current
equatorial-polar temperature gradient (Hinojosa and Villagrán,
1997; Zachos et al., 2001; Dunai et al., 2005; Hinojosa, 2005).
Arid conditions have been postulated for latitudes affected by
the anticyclonic influence of the South America Subtropical High
(24◦ S) in the absence of the Andes since the Late Jurassic (150 Ma,
Hartley et al., 2005; Garreaud et al., 2010). The final uplift of
the Andes during the Miocene defined the current pattern of
rainfall distribution in the area through the rain shadow effect
of the Andes blocking moist air brought by winds from the
east in its northern extreme and conversely, from the west in
its southern extreme. The coeval emergence of the Humboldt
Current during the Neogene further intensified aridity leading
to the development of the current hyperarid Atacama Desert on
the Pacific coast, a region considered one of the most arid in the
world (Hinojosa and Villagrán, 1997; Latorre et al., 1997; Hartley
et al., 2005; Garreaud et al., 2010).
The Central Andes (4◦ S–46◦ S, Ramos, 1999) orogeny is
considered to have occurred in different uplift pulses since ca.
30 Ma. The region between 14◦ S and 16◦ S reached its current
elevation around ca. 5 Ma, Garzione et al. (2017) with the
development of a rain shadow blocking off easterly flow today
to around 27◦ S. In contrast, in the southernmost part (from 39◦ S
south), uplift produced a rain shadow effect on the westerlies at
16 Ma (Ramos and Ghiglione, 2008). At a continental scale, the
development of SAD led to the disjunction of the forest biome
in South America, with several tree/shrub genera distributed
today in South American tropical and temperate forests:
Azara, Blepharocalyx, Crinodendron, Escallonia, Myrteola, and
Myrceugenia (Villagrán and Hinojosa, 1997).
However, the development of SAD associated with Andean
uplift would have also promoted diversification of taxa adapted
to arid conditions and low temperatures, configuring the
development of an arid/semi-arid biogeographic corridor.
This corridor would have favored northward expansion and
the evolution of Andean-Patagonian taxa. Recognition of
a biogeographic corridor necessarily implies that expansion
following the SAD would occur when lineages tend to
retain their climatic niche requirements (Eldredge et al., 2005;
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METHODOLOGY
Taxon Sampling
DNA for Argylia and other species used in this study was
obtained from leaf material of individuals collected in the field
and from herbarium material stored CONC (Herbarium of
the Department of Botany, University of Concepción), SGO
(Herbarium of the National Museum of Natural History), and
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Biogeography of Argylia
FIGURE 1 | (A) Distribution of the genus Argylia in relation to the South American Arid Diagonal (SAD) (shown in yellow) and elevation (B). The SAD is defined by less
than or equal to 500 mm annual precipitation. The red circles are occurrences for all species in the genus.
contained 4 µl DNA (25 ng/µl), 8.35 µl distilled water, 3 µl
MgCl2 (25 mM), 6 µl buffer, 2.4 µl of dNTP (1 mM), 1.8 µl of
each primer (10x ITS4-ITS5 y trnLF), 2.4 µl BSA (25 mM), and
0.25 µl GoTaq (5 U/µl). DNA was denatured at 95◦ C for 5 min,
followed by 35 amplification cycles of 45 s at 94◦ C, annealing
for 1 min at 52◦ C, elongation for 1.5 min at 72◦ C and a final
extension of 7 min at 72◦ C. In the case of rpL32-F-trnL, the
thermal cycler protocol was modified: DNA was denatured at
80◦ C for 5 min, followed by 35 amplification cycles of 30 s
at 94◦ C, annealing for 1 min at 56◦ C, elongation temperature
change of 0.3◦ per second to the elongation temperature for
5 min at 69◦ C and a final extension of 7 min at 72◦ C. Samples
were sent to Macrogen (Seoul, South Korea) for purification and
sequencing. Sequences were loaded, edited and aligned using
ChromasPro 2.33 (Technelysium, Brisbane, QLD, Australia) and
BioEdit 7.0 (Hall, 1999). All new sequences have been deposited
in GenBank (Table 2).
HULS (Herbarium of de University of La Serena). We obtained
DNA of the 13 taxa of the genus Argylia: 10 taxa endemic to
Chile [Argylia adscendens DC. var. adscendens; A. adscendens
DC. var. viridis (Phil.) Gleisner & Ricardi adscendens; Argylia
bifrons Phil.; Argylia checoensis (Meyen) I.M. Johnst.; Argylia
farnesiana Gleisner & Ricardi; Argylia geranioides DC.; Argylia
glutinosa Phil.; Argylia potentillifolia DC.; A. radiata (L.) D. Don,
and Argylia tomentosa Phil.], two species which also occur in
Argentina (Argylia bustillosii Phil.; Argylia uspallatensis DC.), and
one which is endemic to Argentina (Argylia robusta Sandwith)
(Table 1; Gleisner and Ricardi, 1969; Zuloaga et al., 2008). We
incorporated several representatives of the family Bignoniaceae
as an outgroup; Tecoma capensis (Thunb.) Lindl., Campsidium
valdivianum (Phil.) Skottsb., four taxa of the genus Fridericia
Mart. and one member of the Verbenaceae [Glandularia laciniata
(L.) Schnack & Covas.]. A representative of Verbenaceae was
included given that the Verbenaceae is the plant family closest
to the Bignoniaceae (Stevens et al., 2001; Table 2). We used more
than one individual per taxon initially to verify the positions of
Argylia species in the topology.
Phylogenetic Analysis and Estimation of
Divergence Times
We performed a combined rDNA and cpDNA analysis with a
total of 3,149 nuclear characters (913 ITS, 1099 trnF-trnL, and
1495 rpL32-F-trnL, Table 2). Phylogenetic reconstruction was
performed with Bayesian inference in the MrBayes version 3.2
program (Ronquist et al., 2012). Three partitions were used for
each gene; the evolutionary models for each were: GTR + G in
DNA Extraction, Amplification, and
Sequencing
Genomic DNA was extracted with the DNeasy Plant Kit (Qiagen,
Valencia, CA, United States). We amplified the DNA using the
primers listed in Table 1. PCR used a final volume of 30 µl, which
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Biogeography of Argylia
FIGURE 2 | Distribution of species of Argylia. A and B indicate the clade to which a species belongs.
ITS; GTR + I + G in trnL-trnF; and GTR + I in rpL32-F-trnL,
which were obtained with the MrModeltest program version
2.2 (Nylander, 2004). Runs appeared stationary prior to 206
generations, and we conservatively excluded the first 2.0 × 106
generations of each run as burn-in. The effective sample size
(ESS) value was greater than 200 in a range between 1,174,899 and
1,623,107. Nodes with >0.95 were considered to be supported for
posterior probabilities (Ronquist and Huelsenbeck, 2003).
Divergence times were estimated assuming a relaxed
molecular clock with evolutionary models for each partition in
the Beast program (version 1.4.8; Drummond and Rambaut,
2007). We used the estimated age of the genus Fridericia,
sister clade of Argylia, 30.9 Ma (Lohmann et al., 2013) as a
calibration point.
with each species distribution reported in the bibliography
(Gentry, 1992; Rodriguez et al., 2018) eliminating doubtful
georeferences that did not correspond to what was established
or, that corresponded to the location of the herbarium and not
to the area where species were sampled. From the CHELSA data
base, we obtained 19 bioclimatic variables with approximately
1 km2 resolution (Karger et al., 2017). For niche modeling,
we performed a principal component analysis on the 19
bioclimatic variables selecting 11 which retained 78% of the total
variance (Supplementary Figure 1): Mean Annual Temperature
(MAT), Temperature Seasonality (TS), max. Temperature of the
Warmest Month (maxTWaM), min. Temperature of the Coldest
Month, mean Temperature of the Warmest Quarter (minTCQ),
mean Temperature of the Coldest Quarter (mTCQ), Annual
Precipitation (AP), Precipitation of the Driest Month (PDM),
Precipitation Seasonality (PS), Precipitation of the wettest
Quarter (PWeQ), and Precipitation of the Driest Quarter (PDQ).
The climatic niche for each species was modeled using the
maximum entropy algorithm Maxent (Phillips et al., 2006).
We used a total of 50 replicates, 25% of the data as a
training set and, in order to avoid model overfitting, we
defined a species-specific setting selected for Maxent using the
Realized Climatic Niche of Extant Argylia
Species
We used 371 occurrences for 13 specimens of Argylia obtained
from herbarium species stored at CONC (Universidad de
Concepción) and from records in the Global Biodiversity
Information Facility (GBIF). These occurrences were verified
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FIGURE 3 | Images of four species of Argylia showing the range of habits found in the genus. (A) A. adscendens van adscendens. (B) A. checoensis. (C) A. radiata.
(D) A. tomentosa. Image credits: Maria Teresa Eyzaguirre, Fundación R. A. Philippi.
the R packages Phyloclim (Heibl, 2011), Ape (Paradis et al., 2004),
and Phytools (Revell, 2012).
To evaluate the evolution of the climatic niche in Argylia,
we tested phylogenetic signal estimating Pagel’s lambda (Pagel,
1994), which ranges from zero to one. Lambda (λ) is a scaling
parameter for correlations between the phylogenetic similarity
matrix and the trait matrix. λ = 0 signifies that trait correlations
between species are independent of phylogeny. Conversely,
λ = 1 indicates similarity between species equal to the Brownian
motion model of evolution expectation in which case trait
evolution is strongly influenced by phylogeny (Pagel, 1999).
The λ parameter was estimated for each bioclimatic variable
using the phylosig function from the R-package Phytools (Revell,
2012). To evaluate the fit of climatic niche we used the Akaike
Information Criterion for three evolutionary models: (a) a
Brownian motion (BM) model of gradual and continuous drift,
(b) an Ornstein-Uhlenbeck (OU) model which can be thought of
as a stabilizing selection model of evolution with one optimum,
and (c) a White Noise (WN) model of random variation, in
which climatic niche variation is independent of phylogenetic
relationships (Hansen et al., 2008; Hawkins et al., 2014). Fits
to these alternative models was made using the fitContinuous
function from the R package Geiger (Harmon et al., 2008). All
the analyses were conducted with R v. 3.3.3 (R Core Team,
2021).
To infer the climatic history of Argylia, we used the
projection of our phylogenetic tree in environmental (each
bioclimatic variable) and temporal space assuming Brownian
TABLE 1 | Primers used to amplify and sequence rDNA and cpDNA.
Primer
Sequence (50 -30 )
References
ITS4
TCCTCCGCTTATTGATATGC
White et al., 1990
ITS5
GGAAGTAAAAGTCGTAACAAGG
White et al., 1990
trnL
CGAAATCGGTAGACGCTACG
Taberlet et al., 1991
trnF
ATTTGAACTGGTGACACGAG
Taberlet et al., 1991
rpL32-F
CAGTTCCAAAAAAACGTACTTC
Shaw et al., 2007
trnL(UAG)
CTGCTTCCTAAGAGCAGCGT
Shaw et al., 2007
“ENMeval” (Muscarella et al., 2014) R package. The approach
implemented in ENMeval runs successively several MAXENT
models using different combinations of parameters to select the
settings that optimize the trade-off between goodness of fit and
overfitting. We selected the parameters with the lowest AIC
values (Supplementary Table 1).
Climatic Niche Evolution
The predicted niche occupancy (PNO) profiles were used to
calculate the maximum likelihood estimate and 95% confidence
intervals (95% CI) for each climate variable at each interior
node of the phylogeny, assuming Brownian motion evolution
(Evans et al., 2009). To obtain PNO profiles with respect to the
bioclimatic variables selected, we used the raw probability (RP)
distribution of each species derived from Maxent. Confidence
intervals were calculated using an unbiased estimate of the
variance of the Brownian motion. Analyses were conducted using
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TABLE 2 | Collection localities, herbarium voucher numbers, and GenBank accession numbers of taxa.
Taxa
Localities
GenBank
Country
Region/Location
Lat
Long
Voucher
ITS
rpL32F-trnL
trnLF
A. adscendens var.
adscendens DC.
Chile
Santuario de la
Naturaleza Yerba Loca,
RM
33.21
70.2
CONC 166983
MZ312464
MZ327968
MZ327983
A. adscendens var.
viridis DC.
Chile
Ovalle, Coquimbo
30.46
70.43
CONC 103063
MZ312465
MZ327969
MZ327984
A. bifrons Phil.
Chile
Copiapó, Atacama
27.3
69.37
CONC 30120
–
MZ327970
–
A. bustillosii Phil
Argentina
Mendoza, Mendoza
35.82
70.17
CONC 30124
MZ312466
MZ327971
MZ327985
A. checoensis (Meyen)
I.M. Johnst.
Chile
Copiapó, Atacama
27.09
69.52
CONC 107165
MZ312467
MZ327972
MZ327986
A. farnesiana Gleisner &
Ricardi
Chile
Cuesta de Pajonales,
Coquimbo
29.09
70.58
CONC 30436
MZ312468
MZ327973
MZ327987
A. geranioides DC.
Chile
Río Elqui, Coquimbo
29.53
71.15
CONC 103066
MZ312469
MZ327974
MZ327988
A. glutinosa Phil.
Chile
Quebrada Doña Ines
Chica, Atacama
26.07
69.34
CONC 168434
MZ312470
MZ327975
MZ327989
A. potentillifolia DC.
Chile
Quebrada la Totora,
Atacama
28.42
70.12
CONC 156276
MZ312471
MZ327976
MZ327990
A. radiata (L.) D. Don
Chile
Lomas de taltal,
Antofagasta
25.27
70.26
CONC 157513
MZ312472
MZ327977
MZ327991
A. robusta Sandwith
Argentina
San rafael, Mendoza
36.99
69.89
CONC 30130
MZ312473
MZ327978
MZ327992
A. tomentosa Phil.
Chile
Conchi Viejo y San
Pedro, Antofagasta
21.58
68.36
CONC 139888
MZ312474
MZ327979
MZ327993
A. uspallatensis DC.
Argentina
Quebrada de Ciénaga
Colgada, Argentina
31.79
70.03
CONC 75331
MZ312475
MZ327980
MZ327994
Campsidium
valdivianum (Phil.) W.
Bull
Chile
Isla Esmeralda,
Magallanes y la
Antártica Chilena
49.06
75.3
CONC 175000
MZ312477
MZ327981
MZ327996
Fridericia cinnamomea
(DC.) L. G. Lohmann
Brazil
Duke Reserve
2.9
59.92
Vicentini 809
(INPA, MO)
–
KP757329
–
Fridericia erubescens
(DC.) L. G. Lohmann
Brazil
Chapada Diamantina
11.54
41.17
Lohmann 359
(MO, SPF)
–
KP757328
–
Fridericia sp. nogueira
Brazil
Delphinópolis
20.34
46.85
350 (SPF)
–
KP757359
–
Fridericia speciosa
Mart.
Brazil
PE Do Rio Doce
19.66
42.53
Lombardi 2521
(BHCB, MO)
–
KC914604
–
Tecoma capensis
(Thunb.) Lindl.
United
States
Botanical Garden, UC
Berkeley
37.8
122.2
UC Berkeley
Botanical
Garden
(50-1870)
MW854072
–
–
Chile
Farellones
33.35
70.3
CONC 185096
MZ312478
–
MZ327997
Argylia Genus
Outgroups
Bignoniaceae Genera
Verbenaceae Genera
Glandularia laciniata (L.)
Schnack & Covas
motion evolution (BM; Schluter et al., 1997; Evans et al., 2009),
using the R package Phytools (Revell, 2012).
range evolution (e.g., Ree and Smith, 2008), but it includes
an additional parameter of cladogenetic speciation mediated
by founder events: the jump parameter “j.” This parameter
allows daughter species to instantaneously “jump” outside
the geographical range of parental species by long distance
dispersal or dispersalism. A likelihood ratio test was performed
to reject the null hypothesis that the incorporation of the
parameter “J” in each model confer equal likelihoods on data.
Finally, the Akaike Information Criterion (AIC) was used to
compare the relative fit of the six models and choose the
best model of ancestral range reconstruction (Matzke, 2014).
Ancestral Range Distribution
Reconstruction
We inferred ancestral distributions across the Argylia phylogeny
by comparing models that considered anagenetic evolutionary
process (i.e., dispersal, extinction), with cladogenetic process (i.e.,
sympatry and vicariance). BioGeoBEARS R package (Matzke,
2014; R Core Team, 2021) implements widely used models of
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FIGURE 4 | Bayesian inference phylogenetic tree based on combined analysis (rDNA and cpDNA) for 13 taxa of the genus Argylia and seven taxa belong to the
Bignoniaceae and Verbenaceae. Posterior probability values are found above the branches. Estimation of divergence times are found below the branches. The
principal lineages are indicated by clade A and clade B, and subclades SCI, SCII, and SCIII.
The models compared were: Dispersal extinction cladogenesis
(DEC) and DEC + J; a likelihood dispersal-vicariance analysis
(DIVAlike) and DIVALIKE + J and Bayesian biogeographical
inference model (BAYAREALIKE) and BAYAREALIKE + J,
a likelihood version where no particular cladogenetic events
occurred. Our analysis considered four areas for ancestral
range reconstruction, taking into account the altitudinal and
latitudinal characteristics of the present distribution of Argylia
species: Pacific Coast (A), Central Andes between 20◦ S and
33◦ S (B), Central Andes south 33◦ S, southern limit of Central
Andes flat slab (C), Patagonia (D). These areas were defined
according to a geological definition for Central Andes (Ramos,
1999) and according to current distribution of the genus. This
region was divided into north of 33◦ S and south of 33◦ S.
The latter corresponds to the Central Andes Flat Slab region,
segment where there is an absence of volcanic activity (Charrier
et al., 2007). Central Andes, the main area of our study, also
corresponds to the Ecoregion of Central Andes according to
Olson et al. (2001). On the other hand, South of 33◦ S is an
area where precipitation occurs during winter and is associated
to the Southern Andean Steppe Ecoregion (Olson et al., 2001).
Finally, we defined the area “Pacific coast” to represents the
distribution of the Atacama-Sechura desert Ecoregion (Olson
et al., 2001). And finally, we defined the “Patagonia” area, to
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describe the distribution along the Patagonian Pampa Ecoregion
(Olson et al., 2001).
We constrained our analysis to the Andean uplift. For this
we divided our multiplier matrix (Supplementary Figure 2) into
four time periods: (1) 50-35 My defined by the global cooling
event; (2) 35-15 My defined by the glaciation of east Antarctica;
(3) 15-5 MY defined by Andean uplift prior to modern elevation;
5–0 My defined by the culmination of Andean uplift.
Finally, we estimated the number and type of biogeographical
events that account for the present distribution of Argylia.
For this we used biogeographical stochastic mapping (BSM)
implemented in “BioGeoBEARS” (Matzke, 2015).
RESULTS
Phylogenetic Analysis and Divergence
Times
The results show that Argylia is a monophyletic group with an
estimated minimum date of origin of ∼38.21 Ma (Figure 4).
It is composed of two main clades and four subclades. Clade
A comprises eight taxa. It diverged ∼28.04 Ma to further
subdivide into two subclades: SC I, formed by the two ChileanArgentinean taxa A. uspallatensis and A. bustillosii, with a
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TABLE 3 | Bioclimatic variables for species of the genus Argylia, along with the corresponding phylogenetic clade and subclade (see Figure 4).
Clade
A
Subclade
I
II
B
III
Species
MAT
TS
maxTWaM
minTCM
mTWaQ
mTCQ
AP
PDM
PS
PWeQ
PDQ
AUC
1.00
A. bustillosii
8.95
550.98
22.47
−3.14
16.46
1.44
296.82
9.92
46.43
138.73
34.37
A. uspallatensis
6.85
461.27
18.93
−5.12
12.84
0.29
231.12
4.25
76.38
136.33
15.67
0.99
A. bifrons
9.07
362.02
19.67
−2.44
13.63
3.71
65.73
1.80
107.59
38.14
6.48
1.00
A. checoensis
12.55
339.44
22.74
0.75
16.69
7.39
68.57
0.79
130.34
45.95
2.70
1.00
A. farnesiana
14.5
396.2
24.7
3
19.5
8.8
73
0
129
65
0
–
A. geranioides
13.84
388.00
24.40
1.78
18.64
8.04
57.76
0.01
120.07
45.15
1.98
1.00
A. glutinosa
11.20
339.74
21.16
0.28
15.51
6.16
56.69
1.69
102.23
29.73
6.18
1.00
A. tomentosa
8.80
318.30
19.20
−3.22
12.64
3.89
43.43
0.57
131.25
31.36
1.92
1.00
A. potentillifolia
8.48
421.00
19.68
−3.58
13.77
2.37
78.80
0.28
128.18
65.66
1.10
1.00
A. radiata
16.45
319.33
25.34
6.38
20.50
11.80
80.74
0.21
122.80
62.40
1.25
0.99
A. robusta
13.63
548.34
26.32
1.09
21.03
5.90
450.47
13.53
47.25
193.85
45.57
0.97
A. ads. var. viridis
10.70
468.84
22.41
−1.98
16.63
3.88
220.93
0.53
102.68
152.15
5.45
1.00
A. ads. var. adscendens
7.83
537.23
20.92
−4.73
14.92
0.55
332.44
0.97
105.72
237.26
6.21
1.00
Values are the weighted mean of each bioclimatic variable derived from predicted niche occupancy. AUC, area under the curve; MAT, Mean Annual Temperature; TS,
Temperature Seasonality; maxTWaM, maximum Temperature of the Warmest Month; minTCM, minimum Temperature of the Coldest Month; mTWaQ, mean Temperature
of the Warmest Quarter; mTCQ, mean Temperature of the Coldest Quarter; AP, Annual Precipitation; PDM, Precipitation of the Driest Month; PS, Precipitation Seasonality;
PWeQ, Precipitation of the Wettest Quarter; PDQ, Precipitation of the Driest Quarter.
minimum age of ∼9.76 Ma, and SC II, composed of six Chilean
taxa: A. tomentosa, A. bifrons, A. glutinosa, A. geranioides,
A. checoensis, A. farnesiana, with a minimum age of ∼19.25 Ma.
Clade B, with a minimum age of ∼25.77 Ma, comprises five taxa.
This clade is separated into A. robusta, which occurs exclusively in
Argentina (Mendoza, Neuquén, and Río Negro) is sister to SC III
subclade, which is formed by the Chilean species A. potentillifolia,
A. radiata, A. adscendens var. adscendens and A. adscendens var.
viridis, with a minimum age of ∼16.33 Ma.
indicated by λ significantly different from zero and equal to
1 (p ≤ 0.05, Table 4). The rest of the temperature bioclimatic
variables fit better to the null model of evolution (White Noise),
suggesting phylogenetic independence in the evolutionary
history of these traits. Exceptionally, Temperature Seasonality
(Bio4) and mean Temperature of the Coldest Quarter (Bio11),
shows phylogenetic niche conservatism. Winter temperature
(mean Temperature of the Coldest Quarter) showed marginally
significant niche conservatism (p = 0.055, Table 4).
Realized Climatic Niche and Niche
Evolution
Ancestral Range Distribution
Reconstruction
Climatic niche models obtained with Maxent performed
consistently well. The average training AUC for 50-replicate
runs were all above 0.9 (Table 3). Extant species of Argylia
are primarily found in microthermal climatic conditions with a
Mean Annual Temperature ranging from 7◦ C to 13.4◦ C and an
Annual Precipitation ranging from 20 to 477 mm (Figure 5 and
Table 3). Exceptionally, A. radiata and A. farnesiana are found in
marginally mesothermal conditions, as shown by Mean Annual
Temperature above 14◦ C.
Traitgrams associated with precipitation in Argylia show that
sister species are more similar to one another than to their more
distant relatives, suggesting phylogenetic niche conservatism of
these variables (Figure 5C and Supplementary Figures 3A–
D). On the contrary, bioclimatic variables associated with
temperature generally show no phylogenetic niche conservatism.
In this case, species grouping along the temperature axes
show multiple crossing between the two clades (Figure 5A
and Supplementary Figures 3E–G). Exceptionally, traitgrams
for Temperature Seasonality and winter temperature (mean
Temperature of the Coldest Quarter) shows niche conservatism
(Figures 5B,D).
Pagel’s phylogenetic signal test shows the same pattern.
Precipitation variables presented strong phylogenetic signal,
Ancestral range estimations under the best fit model
(BAYAREALIKE + j, Table 5) showed that the most probable
ancestral area for extant species of Argylia is the Central
Andes (B, Figure 6). A summary of Biogeographical Stochastic
Mappings (BSMs) revealed that most biogeographical events
comprise within-area speciation (64.2%) and cladogenetic
dispersal (21.4%), with few areal expansions (14.4%) (Table 6
and Supplementary Figure 4).
The inclusion of the “j” parameter consistently improved
model fit, suggesting that range expansions alone are not
sufficient to account for movement into new areas (Table 5).
Three founder events were identified. The first was defined by
dispersal from the Central Andes 20◦ S to 33◦ S (B) to Patagonia
(D), indicated in red (Figure 6). The second founder event
developed from Central Andes 20◦ S to 33◦ S (B) to Central Andes
33◦ S south (C), indicated with yellow in A. bustillosii (Figure 6).
A range expansion was detected, from Central Andes 22◦ S to 33◦ S
to Central Andes 33◦ S south, defining the current distribution
of A. adscendens clade (BC, Figure 6), between Middle and
Upper Miocene. The last founder event involved the Central
Andes 22◦ S–33◦ S (B) to the Central Andes 33◦ S south (C) with
later range expansion toward the Pacific Coast (A), defining the
current distribution of A. radiata (indicated in gray in Figure 6).
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FIGURE 5 | Traitgram of ancestral states of Argylia climatic niche. White lines correspond to a projection of the phylogenetic tree in a space defined by each
bioclimatic variable. (A) Mean annual temperature (◦ C); (B) Temperature Seasonality; (C) Annual Precipitation (mm); (D) mean Temperature of de Coldest Quarter
(◦ C). Blue shade areas correspond to the 95% of confidence interval. Dashed lines to phylogenetic tree tips link the names of Argylia species. Clades of species are
shown in parenthesis: (A) and (B) as in Figure 4.
Two main clades are distinguished in the Argylia phylogeny
(Figure 4). Clade A diversified during the Oligocene at ∼28.0 Ma,
while clade B diversified around 25.8 Ma.
Extant species of Argylia are distributed mainly on
microthermal (11◦ C in average) and arid conditions (below
500 mm of annual precipitation), as shown by our climatic
niche model, apart from A. radiata which inhabits mesothermal
conditions (16◦ C, Table 3). This species has a very large
latitudinal distribution (15◦ S–33◦ S).
DISCUSSION
Phylogeny and Climatic Niche Evolution
According to Lohmann et al. (2013), the Bignoniaceae node
where Argylia occurs in the family Bignoniaceae has a date of
origin of ∼49.8 Ma, while Olmstead et al. (2009) indicated that
Argylia is one of the earliest-branching clades of the family. This
agrees with the ages we obtained in this study, which show a
minimum origin time for Argylia of ∼38.2 Ma (Late Eocene).
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TABLE 4 | Results of phylogenetic signal (Pagel’s Lambda) and Weighted Akaike, based on exp (−0.5 × 1AIC) to compare the best fit between a Brownian Motion (BM)
model, an Ornstein-Uhlenbeck (OU) model and a White Noise (WN) null model of evolution.
Bioclimatic variable
WAIC
Phylogenetic signal
BM
OU
WN
λ
MAT
0.35
0.107
0.543
7.77E-05
1
TS
0.768
0.136
0.096
1.055
0.039
maxTWaM
0.355
0.13
0.515
7.77E-05
1
minTCM
0.375
0.103
0.523
7.77E-05
1
mTWaQ
0.351
0.132
0.517
7.77E-05
1
mTCQ
0.462
0.094
0.444
1.174
0.055
AP
0.807
0.143
0.051
1.158
0.006
PDM
0.776
0.137
0.087
1.134
0.018
PS
0.662
0.117
0.221
0.96
0.135
PWeQ
0.815
0.144
0.041
1.169
0.004
PDQ
0.775
0.137
0.088
1.126
0.02
p
MAT, Mean Annual Temperature; TS, Temperature Seasonality; maxTWaM, maximum Temperature of the Warmest Month; minTCM, minimum Temperature of the Coldest
Month; mTWaQ, mean Temperature of the Warmest Quarter; mTCQ, mean Temperature of the Coldest Quarter; AP, Annual Precipitation; PDM, Precipitation of the Driest
Month; PS, Precipitation Seasonality; PWeQ, Precipitation of the Wettest Quarter; PDQ, Precipitation of the Driest Quarter.
TABLE 5 | Comparative statistical analyses to compare the best fit between biogeographical models: DEC, dispersal-extinction-cladogenetic model; DIVALIKE,
likelihood dispersal-vicariance model; BAYAREALIKE: Bayesian biogeographical inference model.
Alternative model
DEC + J
DIVALIKE + J
BAYAREALIKE + J
Null model
LnL
Chi-squared
Alt. model
Null model
AIC
p
Alt. model
AICw
Null model
Alt. model
Null model
DEC
−20.73
−19.55
1
47.45
43.1
0.1
0.9
DIVALIKE
−20.11
−20.61
0.32
46.22
45.22
0.38
0.62
BAYAREALIKE
−19.32
−23.41
0.0043
44.64
50.81
0.96
0.044
“j” parameter incorporates the occurrence of founder event in each model. Chi-square test was performed to compare between nested models (alternative versus null).
FIGURE 6 | Results for the Ancestral Range Reconstruction. (A) Range distribution of the four areas defined by the ancestral range reconstruction A: Pacific Coast,
B: Central Andes 20◦ S–33◦ S, C: Central Andes 33◦ S south and D: Patagonia. (B) Maximum likelihood ancestral range estimation, using the best model
BAYAREALIKE+j. The pie diagrams at nodes show the relative probability of the possible states (areas or combinations of areas). The boxes on the right show the
native ranges of taxa within these clades, as in (A). The asterisks mark founder events and the small numbers in gray indicate node numbers.
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Ancestral Range Reconstruction
TABLE 6 | Summary of biogeographical stochastic mapping counts for Argylia
using the BAYAREALIKE + j model.
Mode
Within area speciation
Dispersal
Vicariance
Type
Mean (SD)
%
62.2
Speciation
9 (0)
speciation – subset
0
0
Founder event
3 (0)
21.4
Range expansion
2.02 (0.14)
14.4
Range contraction
0
0
Vicariance
0
0
14 (0.14)
100
Total
The timing of Andean uplift and late Cenozoic global climate
change can be observed in the biogeographical reconstruction of
Argylia (Figure 6 and Ramos and Ghiglione, 2008; Giambiagi
et al., 2016; Garzione et al., 2017). Our result suggests that
the Central Andes between 20◦ S and 33◦ S would be the area
were Argylia initially diversified. Three founder effects were
found in our biogeographical model (Table 6, Figure 6, and
Supplementary Figure 4).
The first, allowed the colonization of the Extra Andean area,
located south of 32◦ S at 25.77 Ma. This limit has been previously
recognized as a distributional boundary for some Argylia species
(Gentry, 1992) and has also been recognized as the southern
part of the Central Andean Flat Slab (Ramos and Folguera,
2009). During the Oligocene, both isotopic and fossil evidence
show a drop of temperature and precipitation (Zachos et al.,
2001; Hinojosa, 2005), coeval with the uplift of Patagonian
Andes (Ramos and Ghiglione, 2008; Figure 7), suggesting semiarid conditions on Patagonia by the time of this colonization.
Aridity would also be reinforced by the effect of the anticyclonic
subsidence and global temperature decline, which in turned
increased equator-pole climatic gradient (Zachos et al., 2001;
Hartley et al., 2005).
The last two founder events occurred independently in the
evolutionary history of Argylia, resulting in colonization of
Central Andes 33◦ S south from the ancestral area (Central
Andes 22◦ S–33◦ S, Figure 6). These dispersal events occurred
between 15 and 5 Ma, by which time the Andean uplift pulses
had already begun (Figures 6, 7; Ramos and Ghiglione, 2008;
Giambiagi et al., 2016; Garzione et al., 2017). This period
corresponds to the modern climate in South America stemming
from the establishment of the Antarctic circumpolar current,
the modern atmospheric circulation pattern and reinforcement
of the Humboldt Current in the Pacific Ocean (Hinojosa and
Villagrán, 1997; Hartley et al., 2005; Garreaud et al., 2010). These
events are a sign of the birth of the Andean corridor, allowing
north-south dispersal of species (Luebert and Weigend, 2014).
This corridor has been considered as an explanation for plant
diversification patterns in South America, such as in: Azorella,
Chuquiraga; Laretia, Leucheria, Mulinum, and Perezia (Ezcurra,
2002; Simpson et al., 2009; Nicolas and Plunkett, 2012, 2014;
Pérez et al., 2020). Apparently, this holds true also for Argylia,
where dispersal and cladogenetic events occurred mainly during
a period when arid and semi-arid altitudinal belts were formed.
However, formal climatic niche analyses, as performed here, are
lacking for the above-mentioned genera.
Two range expansion were detected within B clade (Figure 6).
The first expansion occurred from Central Andes 22◦ S to 33◦ S
(ancestral area, B) to Central Andes 33◦ S south (C), between
Middle and Upper Miocene during the Andes Mountain building
(Figure 7; Giambiagi et al., 2016), allowing a climatic corridor
between both areas and range expansion of A. adscendens Clade
(var. adscendens and var. viridis). The second expansion occurred
from Central Andes 33◦ S south to Pacific Coast (A), which
allowed A. radiata to colonize the coastal area as far north
as southern Peru (Figure 2; Gentry, 1992; Rodriguez et al.,
2018). Argylia’s northward expansion (Figure 6) suggest a second
Mean numbers of the different types of events estimated are shown here along with
standard deviations.
Lack of phylogenetic signal in most of the temperature
variables indicates that evolution in Argylia is mediated by
temperature adaptation associated. The broad current altitudinal
distribution of the genus, where most of Argylia species are
distributed between 2,000 and 4,500 m.a.s.l., reflects adaptation
to progressively lower temperatures over steep elevational
gradients. Exceptionally, Temperature Seasonality had a strong
phylogenetic signal (λ = 1, Table 4), indicating that throughout its
evolutionary history, Argylia species tracked annual contrasting
climatic conditions. Winter temperature (mean Temperature of
the Coldest Quarter), which strongly determine temperature
variation (or seasonality), also showed phylogenetic signal,
although it was only marginally significant (see Table 4).
Ancestral reconstruction for temperature seasonality shows
that Argylia must have been distributed in regions with
a significant thermal amplitude (Supplementary Table 2).
This condition is associated with continentally, where annual
temperature fluctuation increases from coastal to inland areas
(Driscoll and Fong, 1992). The current distribution of Argylia
seems to correlate broadly with this pattern (Supplementary
Figure 5), reinforcing the idea that Argylia’s evolution was driven
by the emergence of the Arid Diagonal, as we hypothesized.
The requirement of seasonality condition for Argylia’s climatic
niche can also be observed with precipitation variables that
presented a strong phylogenetic signal, such as winter and
summer precipitation (Precipitation Seasonality, Precipitation
of the Driest Month, Precipitation of the Wettest Quarter and
Precipitation of the Driest Quarter, Figure 5, Table 4, and
Supplementary Figure 3). Even though, climatic seasonality is
not the only determinant requirement for the genus, but also the
availability of moisture seems to have a strong effect over Argylia’s
evolution and diversification, given by the strong phylogenetic
conservatism of Annual Precipitation (Figure 5A and Table 4).
These results are especially important under current climate
change scenarios. Especially in northern and central Chile, where
there is a 30% of precipitation deficit and a historic increase in
temperatures (Center for Climate and Resilience Research [CR2],
2015). Considering the projection of a decrease in precipitation
for the 2100 year (Qin et al., 2014), high Andean genera with
strong precipitation conservation, such as Argylia, could be at
risk. Indeed, a reduction in precipitation is likely to have much
more severe consequences that an increase in temperature.
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FIGURE 7 | Schematic diagram of the time of uplift along the Northern Central Andes, Central Andes (20◦ S–33◦ S and 33◦ S south) and Patagonian Andes based on
Ramos and Ghiglione (2008), Garzione et al. (2017), and Giambiagi et al. (2016). The geological timeline is shown in Ma. Red stars provide an estimation of when the
rain shadow associated with elevation came into force.
All the above expansions were mediated by the last pulse of
Andean uplift (5 Ma, Figures 6, 7), as well by the emergence of
hyper arid conditions along with the birth of the Atacama Desert
(Villagrán and Hinojosa, 1997; Hartley et al., 2005), as clearly
shown by the current pattern of the northernmost distribution
of the genus, which presents an east-west disjunction among the
species distributed in this region.
Diversification and development of novel adaptations
promoted by arid conditions have been widely established
in other South American plant genera: Chaetanthera,
Malesherbia, Cristaria, Heliotropium sect. cochranea, Leucheria,
and Leucocoryne (Gengler-Nowak, 2002; Guerrero et al.,
2013; Jara-Arancio et al., 2014, 2017; Böhnert et al., 2019;
Pérez et al., 2020), in accordance with the idea that arid
regions are strong drivers of lineage diversification (Stebbins,
1952).
According to Luebert and Weigend (2014), high elevation taxa
showed divergence times that correspond mainly with Andean
uplift in the late Miocene and early Pliocene, with some taxa
also diversifying in Quaternary times. The authors also highlight
a north to south trend for high-Andean lineages, with lineages
with more recent origin in the north and older lineages in the
south. Additionally, in Chile from 18◦ S to 35◦ S, phylogenetic
diversity increases from north to south, following a precipitation
gradient. Both patterns could be explained by the presence of a
corridor along the Pacific Coast at the end of Cenozoic and during
the Quaternary as suggested by its distribution. Today, this
species is distributed from 33◦ S to 15.8◦ S, occupying the coastal
range along the subtropical West of South America (Figure 2),
where moisture comes mainly from the interception of low
coastal clouds, a phenomenon known as the “Camanchaca.”
Coastal topography (Rundel et al., 1991; Garreaud et al., 2008)
associated with the Camanchaca has allowed the development
of high species richness in the coastal Atacama and Sechura
Deserts comprising the Lomas Formation (Hueck and Seibert,
1972; Rundel et al., 1991). The main drivers of the Camanchaca
are the strong air subsidence associated with the South American
Subtropical High (SASH), the annual variability of SASH,
the constant temperature inversion by the cool Humboldt
Current and the uplift of the coastal topography (Rundel
et al., 1991; Garreaud et al., 2008, 2010). The age of the
Humboldt Current and elevated coastal topography dates to
Middle/Upper Neogene and Pleistocene, respectively (Hinojosa
and Villagrán, 1997; Villagrán et al., 2004; Hartley et al., 2005;
Garreaud et al., 2010; Regard et al., 2021). These ages are
consistent with our ancestral range reconstruction and the strong
phylogenetic signal on moisture variables found in this study.
It would be worthwhile testing this phylogeographic hypothesis
at the population level over the entire distributional range
A. radiata.
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Biogeography of Argylia
phylogenetic signal in these environmental variables. At the end
of the Neogene and during the Pleistocene, the Argylia lineage
would have reached its modern distribution and associated
species diversity.
Finally, Argylia’s biogeographic history highlights the
value of niche conservatism studies where the availability
of climatic corridors and moisture environmental filters are
essential for species range expansions in the context of
modern climate change.
younger arid environment that favored the diversification in this
new biome (Scherson et al., 2017; Böhnert et al., 2019).
Finally, the proposition of range expansion of A. radiata
through a corridor from Central Andes south 33◦ S to Pacific
Coast up to 15◦ S in Peru, by the Late Miocene (Figure 6), would
be associated with what Guerrero et al. (2013) described as a
widespread temporal lag between the establishment of arid and
hyperarid climates and a later diversification through AtacamaSechura Desert, recorded in genera Nolana, Chaetanthera, and
Malesherbia. This temporary lag may be a consequence of the
later establishment of the second climatic corridor that we
propose in this study, the coastal lomas, between the Upper
Miocene and early Quaternary (Regard et al., 2021).
DATA AVAILABILITY STATEMENT
The original contributions presented in the study are publicly
available. This data can be found here: https://www.ncbi.nlm.
nih.gov/genbank/. Accession number(s) can be found in the
article/Supplementary Material.
CONCLUSION
In this work we evaluated the role of the Andean uplift and
consequently the development of the Arid Diagonal in the
evolution of the Argylia lineage. We postulated that: (a) an
early diversification of Argylia in an ancestral area under arid
conditions (given by the presence of the high-pressure system
of the South Pacific Subtropical High), (b) Phylogenetic niche
conservatism of climatic requirements, and (c) dispersal and later
diversification of Argylia modulated by the Andean uplift and its
role as a biological corridor.
That all precipitations variables considered were highly
conserved indicates that the distribution of Argylia is strongly
determined by moisture availability. Our results also showed
that Argylia’s climatic niche is determined by annual temperature
fluctuations, indicating that the ancestral range of Argylia must
have been in a region where the Andes was uplifting.
The striking difference between temperature and precipitation
variables is a novel finding and one that should be looked for
in other Andean genera. Is this a general tendency, or variable
among taxa? If it is a general condition, it requires an intrinsic
physiological explanation.
On the other hand, the ancestral area of distribution for
the genus was north of 32◦ S along the Andean range. At
the time of the origin of Argylia, this would have been a
region where subtropical conditions were already present. Later
dispersal and diversifications occurred coeval with Andean
uplift acting as a “corridor.” A second climatic corridor is
postulated by our analysis, where the northward expansion into
the hyperarid zone in the coast is associate with an extra moisture
supply by the marine low clouds Camanchaca. Thus, Argylia
tracked its moisture requirements as suggested by the strong
AUTHOR CONTRIBUTIONS
NG-V, MA, LH, PJ-A, and CR: conception and design of the
study. NG-V, PJ-A, PV, and CR: acquisition of the data. NG-V,
LH, and PJ-A: analysis and/or interpretation of the data. NG-V,
LH, and MA: drafting and revising the manuscript. All authors
contributed to the article and approved the submitted version.
FUNDING
This research was funded by the ANID PIA APOYO CCTE
AFB170008 and ACE210006 to the Instituto de Ecología
y Biodiversidad (IEB), FONDECYT 1140541, 1180454 and
1211765, and Anillo ACT172099 (PIA, ANID).
ACKNOWLEDGMENTS
We are very grateful to the Fundación R. A. Philippi, Santiago,
Chile for permission to use their images of the four illustrated
Argylia species.
SUPPLEMENTARY MATERIAL
The Supplementary Material for this article can be found
online at: https://www.frontiersin.org/articles/10.3389/fpls.2021.
724057/full#supplementary-material
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