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R E S E A R C H A R T I C L E Open Access
Why do different oceanic archipelagos
harbour contrasting levels of species
diversity? The macaronesian endemic genus
Pericallis (Asteraceae) provides insight into
explaining the ‘Azores diversity Enigma’
K. E. Jones
1*
, S. Pérez-Espona
2
, J. A. Reyes-Betancort
3
, D. Pattinson
4,5
, J. Caujapé-Castells
6
, S. J. Hiscock
7
and M. A. Carine
4
Abstract
Background: Oceanic archipelagos typically harbour extensive radiations of flowering plants and a high proportion
of endemics, many of which are restricted to a single island (Single Island Endemics; SIEs). The Azores represents an
anomaly as overall levels of endemism are low; there are few SIEs and few documented cases of intra-archipelago
radiations. The distinctiveness of the flora was first recognized by Darwin and has been referred to as the ‘Azores
Diversity Enigma’(ADE). Diversity patterns in the Macaronesian endemic genus Pericallis (Asteraceae) exemplify the
ADE. In this study we used morphometric, Amplified Length Polymorphisms, and bioclimatic data for herbaceous
Pericallis lineages endemic to the Azores and the Canaries, to test two key hypotheses proposed to explain the
ADE: i) that it is a taxonomic artefact or Linnean shortfall, ie. the under description of taxa in the Azores or the
over-splitting of taxa in the Canaries and (ii) that it reflects the greater ecological homogeneity of the Azores,
which results in limited opportunity for ecological diversification compared to the Canaries.
Results: In both the Azores and the Canaries, morphological patterns were generally consistent with current
taxonomic classifications. However, the AFLP data showed no genetic differentiation between the two currently
recognized Azorean subspecies that are ecologically differentiated. Instead, genetic diversity in the Azores was
structured geographically across the archipelago. In contrast, in the Canaries genetic differentiation was mostly
consistent with morphology and current taxonomic treatments. Both Azorean and Canarian lineages exhibited
ecological differentiation between currently recognized taxa.
Conclusions: Neither a Linnean shortfall nor the perceived ecological homogeneity of the Azores fully explained
the ADE-like pattern observed in Pericallis. Whilst variation in genetic data and morphological data in the Canaries
were largely congruent, this was not the case in the Azores, where genetic patterns reflected inter-island geographical
isolation, and morphology reflected intra-island bioclimatic variation. The combined effects of differences in (i)
the extent of geographical isolation, (ii) population sizes and (iii) geographical occupancy of bioclimatic niche
space, coupled with the morphological plasticity of Pericallis, may all have contributed to generating the contrasting
patterns observed in the archipelagos.
Keywords: Ecological variation, Genetic diversity, Macaronesia, Morphological diversity, Pericallis, Population genetics
* Correspondence: k.jones@bgbm.org;kteeejones@gmail.com
1
Botanischer Garten und Botanisches Museum Berlin-Dahlem, Dahlem Centre
of Plant Sciences, Freie Universität Berlin, Königin-Luise Str. 6-8, Berlin 14195,
Germany
Full list of author information is available at the end of the article
© 2016 The Author(s). Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Jones et al. BMC Evolutionary Biology (2016) 16:202
DOI 10.1186/s12862-016-0766-1
Background
A key question for biologists is: why do different
geographic regions harbour contrasting levels of bio-
diversity? [1–4]. Oceanic archipelago floras provide
striking examples of flowering plant lineages that have
undergone extensive adaptive and allopatric diversifica-
tion, with a high proportion of Single Island Endemics
(hereafter SIEs) for example, the Lobelioids in the
Hawaiian archipelago [5] and the Aeonium alliance in
the Canary Islands [6]. However, the Azores archipelago,
part of the Macaronesian region sensu Dansereau [7] that
also comprises the Cape Verde, Canaries, Salvagems and
Madeira, represents an anomaly and shows a much lower
proportion of SIEs when compared to other archipelagos
[8]. Furthermore, in the Azores there are few examples of
taxa that have diverged in situ, with 80 % of endemic line-
ages containing just a single endemic taxon; in the Canar-
ies, this figure is 56 % [8–10]. This phenomenon was first
alluded to by Darwin in a letter to Joseph Hooker dated
Christmas Day, 1844, where he commented on a recently
published enumeration of the Azores flora [11] and noted:
“Watson’s paper on [the] Azores has surprised me much;
do you not think it odd, the fewness of peculiar species…?”
[12]. Carine and Schaefer [8] coined the term the ‘Azores
Diversity Enigma’(ADE henceforth) to collectively refer to
these two distinctive features of the Azores flora, i.e. the
limited incidence of evolutionary radiations and paucity of
SIEs in the flora.
Hypotheses to explain the ADE have included the
proposal that the Azorean islands, or the lineages inhabit-
ing them, are too young for extensive radiations to have
occurred - with ca. 62 % of the land area being less than 1
million years old [13–15], that they are too small in land
surface area [15] or that, in contrast to other archipelagos,
the Azorean islands are too ecologically homogeneous to
have facilitated extensive diversification [15, 16]. Carine
and Schaefer [8] suggested that these hypotheses do not
satisfactorily explain the distinctive patterns in the Azores,
highlighting potential influence of inconsistent taxonomic
effort or different palaeo-climate conditions on the evolu-
tion of their floras. Schaefer et al. [10] subsequently inves-
tigated genetic diversity patterns in ca. 20 % of Azorean
endemic lineages using the Internal Transcribed Spacer
region of nuclear ribosomal DNA (ITS) sequences and
found higher levels of molecular diversity and molecular
SIEs compared to current taxonomic concepts. The
authors concluded that the ADE could indeed be a
taxonomic artefact (Linnean shortfall).
The genus Pericallis (Senecioneae, Asteraceae) is
endemic to Macaronesia. With sixteen species and a
distribution spanning the Azores, Canaries and Madeira,
it exemplifies the ADE, since diversity in this genus is
unevenly distributed across the region: 14 taxa occur in
the Canaries, 11 of which are SIEs, two SIEs occur in
the Madeira archipelago [17] and one species with two
multi-island endemic (MIE) subspecies occurs in the
Azores (Fig. 1).
Jones et al. [18] identified two herbaceous lineages,
namely the Azorean lineage and a lineage comprising
five SIE species in the Canaries that diverged recently
(ca. 0.89 Ma (0.09–2.9 Highest Posterior Density (HPD))
and ca. 1.32 Ma (0.007–3.24 HPD) respectively). Despite
being of a similar age, the Azorean and Canarian line-
ages exhibit marked differences in their diversity pat-
terns. The five SIEs of the Canarian lineage (P. cruenta,
P. papyracea, P. murrayi, P. steetzii and P. echinata) all
exhibit broad and overlapping altitudinal and habitat
ranges (Fig. 1; see [18]). In contrast, the two Azorean
endemic taxa are ecologically differentiated MIEs with
overlapping island distributions: P. malvifolia subsp.
malvifolia is restricted to low altitudes (<300 m) on
Santa Maria, São Miguel, Pico, Faial and São Jorge; P.
malvifolia subsp. caldeirae is restricted to higher
altitudes (>500 m) and is found on São Miguel, Faial,
Terceira and Pico [19]; see Fig. 1. The Azorean and
Canarian groups thus exhibit markedly different
patterns that reflect the ADE.
Phylogenetic analyses of chloroplast and nuclear
ribosomal ITS data provided only limited resolution
within these clades but they did not support current
taxonomic treatments in the Azorean clade [18]. The
two ecologically distinct Azorean subspecies were not
distinguished and the data were rather consistent with
a pattern of geographic structuring across the Azores.
In the Canarian lineage, little genetic differentiation was
observed between the five currently recognized taxa with
sharing of haplotypes evident between some taxa accord-
ing to some of the markers used. Whilst high morpho-
logical divergence with low sequence diversity is common
in island radiations [20], morphology-based species
delimitation in the Canarian lineage has been called into
question with both Nordenstam [21] and Swenson and
Manns [22] suggesting that taxonomic concepts for
Pericallis need to be re-assessed.
The goal of this study is to understand the contrasting
diversity patterns observed in the Azores and Canaries,
focussing specifically on herbaceous Pericallis lineages
endemic to each archipelago. Using morphology, Ampli-
fied Fragment Length Polymorphisms (AFLPs) and bio-
climate data we test two hypotheses to explain the ADE
(Table 1): (i) that differences are the result of taxonomic
artefact or Linnean shortfall resulting from the under
description of taxa in the Azores or the over-splitting
of taxa in the Canaries [8] and (ii) that differences
are related to the greater ecological homogeneity of
the Azores [15]. We specifically assess patterns of
morphological and molecular variation in the Azorean
and Canarian herbaceous lineages, and investigate the
Jones et al. BMC Evolutionary Biology (2016) 16:202 Page 2 of 15
relationship between morphological and molecular
patterns of variation and geographical and ecological
distance.
Results
Morphological variation
In both the Azores and Canaries morphological analyses
were generally consistent with current taxonomic classifica-
tions (Fig. 2a, d). In the Azores, Factor Analysis for Mixed
Data (FAMD) of twelve variable morphological characters
and 125 individuals revealed the separation of the two
subspecies across dimensions one and two, although some
overlap between ssp. malvifolia from the central islands
and ssp. caldeirae was evident (Fig. 2a; see Additional file 1:
Figure S1 for FAMD plots with points coloured by islands).
The first dimension described 21.93 % of the variation and
the characters that contributed most significantly to this di-
mension (with a factor loading > 0.3) were the length of the
highest bract and the indumentum of the disc cypselae
(Additional file 4: Tables S1 and Additional file 5:
Table S2 for morphological data and factor loadings,
respectively). The second described 19.07 % of the
variation; the most significant character contributing
to this dimension was the length of the disc floret
Fig. 1 Geographic setting of the study archipelagos: Azores and Canaries in Macaronesia (above) and islands of occupancy of Pericallis lineages
used in this study. Islands: F, Faial; P, Pico; SJ, São Jorge; T, Terceira; SM, São Miguel; SA, Santa Maria; LP, La Palma; EH, El Hierro; LG, La Gomera; Te,
Tenerife. Island ages are maximum ages in Myr taken from Caujapé-Castells (2010). Taxa: MA, P. malvifolia subsp. malvifolia; CA, P. malvifolia subsp.
caldeirae; PA, P. papyracea; MU, P. murrayi; ST, P. steetzii; EC, P. echinata; CR, P. cruenta. A black circle is used to indicate the presence of the island
Graciosa, which does not host any populations of P. malvifolia and, therefore, was not sampled in this analysis. Photos (left to right): P. malvifolia
subsp. caldeirae, Azores, São Miguel, Lagoa do Fogo, photo credit: H. Schaefer; P. malvifolia subsp. malvifolia, Azores, São Miguel, Madrugada,
collection: Jones et al. 282, photo credit: José Martins; P. echinata, Canaries, Tenerife, Teno, collection: Jones et al. 195, photo credit: KE Jones; P.
cruenta, Canaries, Tenerife, La Orotava, collection: Jones et al. 243, photo credit: KE Jones
Jones et al. BMC Evolutionary Biology (2016) 16:202 Page 3 of 15
corolla. There were also trends suggesting some
geographic structuring within P. malvifolia subsp.
malvifolia, since individuals from Santa Maria and
São Miguel showed some separation along the second
dimension (Fig. 2a). However, individuals from the
central islands overlapped with both Santa Maria and
São Miguel individuals. Subsequent dimensions pro-
vided no useful information regarding differences
among the populations investigated.
In the Canaries, the results of the FAMD analysis of
23 variable morphological characters and 89 individuals
broadly agreed with current taxonomic treatments, al-
though there was considerable overlap of P. steetzii and
P. murrayi individuals and some overlap of P. echinata
and P. steetzii accessions (Fig. 2c). The first dimension
described 17.14 % of the variation and mainly separated
P. echinata from all other taxa. The characters that
contributed most to this dimension are related to capit-
ulum size and length of scales on the phyllary bracts: P.
echinata exhibits longer disc and ray floret corolla tubes
with longer and more abundant scales on the phyllary
bracts compared to all other taxa. Pericallis papyraceus
was also separated from all other taxa along the first
dimension; the character that distinguished it along this
dimension was the smaller capitulum width. Pericallis
cruenta was separated from P. papyraceus, P. steetzii
and P. murrayi along the second dimension, which
described 12.15 % of the variation (Fig. 2c). The charac-
ter that contributed most significantly to this dimension
and separated P. cruenta from all other taxa was abaxial
leaf indumentum colour: P. cruenta typically exhibits
purple abaxial leaf indumentum, whereas P. papyraceus,
P. steetzii and P. murrayi are green to white. With the
exception of a strong contribution of the number of the
ray florets to the differentiation of P. papyraceus (7–8
ray florets) from all other taxa (>10 florets), subsequent
ab
cd
Fig. 2 Factor Analyses of Mixed Data of morphological variation (a,c), and Principal Component Analyses of 19 bioclimatic variables for collection
points (b,d) in each archipelago; Azores (a,b) and Canaries (c,d). Each point represents an individual
Table 1 Hypotheses to explain the Azores Diversity Enigma
Hypotheses Justification
1. Linnean shortfall The differences in diversity patterns of
Pericallis between the Azores and the
Canaries are explained by differences in
taxon concepts and/or taxonomic effort
applied between the archipelagos. Recent
studies have shown that there is potentially
greater diversity in the Azores compared to
current species circumscriptions [10,18,30]
2. Ecological
homogeneity
Adaptive diversification plays a key role in
the evolution of island lineages [43]. There is
more limited opportunity for diversification in
the Azores because they are more ecologically
homogenous, compared to the Canaries [15].
Jones et al. BMC Evolutionary Biology (2016) 16:202 Page 4 of 15
dimensions provided no useful information regarding
the differences amongst the populations investigated.
Non-parametric permutational multivariate analyses of
variance (perMANOVA) of morphological data in the
Azores revealed a significant difference between taxa
and islands (P= 0.001). R
2
values were 0.19 and 0.35 for
the analyses of variation between species and between
islands, respectively (Table 2). perMANOVA of Pericallis
morphological data in the Canaries revealed a significant
difference between taxa and islands (P= 0.001). R
2
values
were 0.65 and 0.43 for analyses between species and
between islands respectively (Table 2).
Bioclimatic variation
Nineteen bioclimatic variables from the geographic loca-
tions of 125 individuals in the Azores available through
Worldclim (http://www.worldclim.org/) were analysed
using Principal Component Analysis (PCA). A number
of clusters were separated along the first and second axis
(Fig. 2b). These corresponded to (i) Santa Maria subsp.
malvifolia (ii) São Miguel subsp. malvifolia (iii) central
sub-archipelago subsp. malvifolia, (iv) São Miguel subsp.
caldeirae and (v) central sub-archipelago subsp. cal-
deirae (including one accession of subsp. malvifolia from
Pico). PC1 explained a much higher percentage of the
variation than PC2 (76.89 % vs. 10.87 %, respectively).
The most significant ecological variables that contrib-
uted to PC1 were all related to precipitation (precipita-
tion of the warmest quarter, wettest quarter and wettest
month); those contributing to PC2 were precipitation of
the driest quarter and the driest month and isothermal-
ity (annual mean temperature range/mean diurnal range:
a measure of temperature “evenness”throughout the
year; Additional file 5: Table S5).
The PCA of bioclimatic variation in the Canaries for
89 georeferenced individuals showed some separation of
the currently recognized taxa: P. cruenta and P. murrayi
were distinguished, although P. echinata individuals
overlapped with some individuals of P. cruenta. Signifi-
cant overlap was found between P. steetzii and P. murrayi
accessions (Fig. 2d). The most significant ecological
variables that contributed to PC1, which explained
78.06 % of the variation were all related to temperature
(mean temperature of the coldest quarter, annual mean
temperature and maximum temperature of the warmest
month); those contributing to PC2 (17.48 %) were iso-
thermality, mean diurnal range and annual temperature
range (Additional file 6: Table S3).
Spatial structuring of genetic variation
Seventy-six samples of the Azorean P. malvifolia were
used for AFLP fingerprinting analysis, 51 of which were
also used in the morphometric analysis. This sampling
encompassed populations of both subspecies on all
islands where they occur. A Discriminant Analysis of
Principal Components (DAPC) was used to assign indi-
viduals to genetic clusters [23, 24] with selection of the
optimal number of clusters based on the Bayesian Infor-
mation Criterion (BIC; [24]). The results of the K-means
clustering analyses of the Azorean AFLP data suggested
that the best Kvalue was 3 (Additional file 2: Figure S2).
No genetic differentiation between P. malvifolia subsp.
malvifolia and subsp. caldeirae was apparent (Fig. 3a).
Rather, there was geographical structuring with the
three groups largely restricted to the central sub-
archipelago, São Miguel, and Santa Maria, respectively;
albeit with some genetic material shared between the
groups. Hierarchical analyses of molecular variance
(AMOVA) [25, 26] were used to investigate partitioning
of variation within and among the groups defined by
the DAPC analysis. The AMOVA results suggested that
there was greater variation within than between groups
(Table 3).
For the Canarian dataset, 69 samples were used to rep-
resent the five taxa recognised. Forty-four of the samples
were also used in the morphometric analysis. In the DAPC
analysis, the most likely Kvalues were K=3–5 (Additional
file 2: Figure S2) but the differences between the BIC
values for these were marginal. We present the DAPC
plot for K= 5 to reflect the number of taxa currently
recognized and the results from cp and ITS sequence
data in Jones et al. (2014b); this reveals a pattern that
broadly corresponded to the currently accepted taxa
but with more sharing of genetic material between taxa
than in the Azorean dataset (Fig. 3). For K=4, geo-
graphic structuring between islands was observed and for
K= 3, very little geographic structure was apparent (Add-
itional file 3: Figure S3). As with the Azorean dataset,
AMOVA suggested that there was greater variation within
groups defined by the DAPC analysis than between groups
but genetic differentiation between groups was lower in
the Canaries than for the Azorean data set (Table 3).
In the Azores, a full distance-based redundancy ana-
lyses (dbRDA) revealed a significant positive correlation
between geographic distance and genetic distance but no
significant correlation between geographical and mor-
phological distance (Table 4). There were significant cor-
relations between genetic distance and climate PC1 and
Table 2 Results of permutational analysis of variance of Pericallis
morphological data to assess significant differences between
islands and taxa in the Azores and Canaries
Archipelago Grouping d.f. R
2
P-value
Azores Taxa 1 0.19 0.001
Islands 5 0.35 0.001
Canaries Taxa 4 0.65 0.001
Islands 3 0.43 0.001
Jones et al. BMC Evolutionary Biology (2016) 16:202 Page 5 of 15
PC2. However, partial dbRDA, which allows for the fit-
ting of covariates to account for potential confounding
effects of these values [27], suggested that climate PC1
and PC2 were not significant for AFLP data variation in
the Azores when geographic distance was taken into
account. Morphological distance was not correlated with
climate PC1 in the full dbRDA analysis, but was corre-
lated with climate PC2. In the partial analysis where
a
b
Fig. 3 Discriminant Analysis of Principal Components showing the genetic clustering of populations of Pericallis lineages analysed in the Azores
and Canaries based on AFLP data. Each bar represents one individual plant. (a) 76 individuals from the Azores (K= 3). Pericallis malvifolia subsp.
malvifolia is separated into different island groupings: Central island subsp. malvifolia and Eastern island subsp. malvifolia. Taxon names and island
groupings are indicated above the plot. Island names are indicated below the plot and separated by bold lines. (b) 69 individuals from the
Canaries (K= 5). Taxon names are indicated above the plots and island names are indicated below the plot separated by bold lines
Jones et al. BMC Evolutionary Biology (2016) 16:202 Page 6 of 15
geographic distance was taken into account, significant
correlations were observed between morphological vari-
ation and both climate PC1 and PC2 (Table 4).
In the Canaries, full dbRDA revealed significant posi-
tive correlations between both geographic distance and
genetic distance, and geographical distance and morpho-
logical distance (Table 4). Full dbRDA suggested signifi-
cant correlations between genetic distance and climate
PC1. A significant correlation between morphological
distance and climate PC1 and climate PC2 was also
observed. However, when geographic distance was taken
into account in the partial dbRDA, no significant corre-
lations between genetic distance and morphological or
bioclimatic variables were observed.
Discussion
The low numbers of SIEs in the Azores relative to other
oceanic islands was noted by Darwin [12], and was
recently termed the ‘Azores Diversity Enigma’[8]. We
aimed to test hypotheses that explain the ADE by
comparing patterns of endemicity observed in Azorean
and Canarian Pericallis lineages that are endemic to
each archipelago. We specifically tested two hypotheses
(Table 1): (i) the Linnean shortfall hypothesis [8, 28] and
(ii) the environmental homogeneity hypothesis [15].
Hypothesis 1: linnean shortfall in the Azores
The Linnean shortfall hypothesis –the failure to recog-
nise morphologically differentiated taxa in the Azores or
over-splitting of taxa in the Canaries –does not ad-
equately explain the ADE for Pericallis, contrary to the
suggestion of Schaefer et al. [10] and Carine et al. [8]
that this may explain the distinctive patterns in the
Azores flora more generally. Differences between taxa
significantly explained morphological variation of
Table 3 Hierarchical partitioning of AFLP variation based on
Analyses of Molecular Variance of Pericallis species in the Azores
and Canaries. P< 0.001
Archipelago Source of variation d.f. Percentage of
variation
Azores (K = 3) Among groups 2 21.08
Among populations
within groups
11 0.77
Within populations 69 78.14
Canaries (K = 5) Among groups 4 10.37
Among populations
within groups
9 2.34
Within populations 57 87.28
Table 4 Relationships between genetic and morphological diversity of Pericallis and geographic distance (metres) and PC1 and PC2
of the principle coordinate analysis of bioclimatic data using distance-based redundancy analyses. Left: full tests of individual sets.
Right: partial tests
Marginal tests Partial tests (geographic distance)
Canaries: Euclidean distance matrix (AFLPs)
Variable FP Variance Variable FP Variance
Distance 1.14 0.005**
Climate PC1 0.906 0.009** 0.906 Climate PC1 1.0263 0.385 0.589
Climate PC2 0.711 0.124 0.711 Climate PC2 0.9573 0.544 0.549
Canaries: Morphology distance matrix
Variable FP Variance Variable FP Variance
Distance 3.234 0.005**
Climate PC1 6.495 0.002** 0.5239 Climate PC1 1.1738 0.276 0.047
Climate PC2 3.357 0.004** 0.1679 Climate PC2 0.8745 0.544 0.035
Azores: Euclidean distance matrix (AFLPs)
Variable FP Variance Variable FP Variance
Distance 4.913 0.005**
Climate PC1 4.886 0.002** 1.5171 Climate PC1 0.339 0.188 1.14
Climate PC2 3.285 0.002** 1.0201 Climate PC2 0.288 0.534 0.97
Azores: Morphology distance matrix
Variable FP Variance Variable FP Variance
Distance 1.055 0.568
Climate PC1 0.103 0.094‘1.7331 Climate PC1 0.1606 0.006** 3.072
Climate PC2 0.161 0.008** 2.7107 Climate PC2 0.1537 0.008** 2.941
Significance: *** 0.001, ** 0.01, * 0.05, ‘0.1
Jones et al. BMC Evolutionary Biology (2016) 16:202 Page 7 of 15
Pericallis in the Canaries (65 % of the variation) with
species circumscriptions in the Canaries also broadly
supported by FAMD analysis of morphological variation.
However, P. steetzii and P. murrayi were not differenti-
ated in the FAMD analysis, which suggests some level of
over-splitting (Fig. 2c) but not enough to adequately
explain the ADE. We also observed a significant correl-
ation between morphological and geographical distance,
with differences between islands explaining 43 % of the
morphological variation. This is consistent with the
recognition of SIEs, even though considerable morpho-
logical variation exists within islands, as is evident from
the space occupied by taxa in the FAMD analysis
(Fig. 2c). Similarly, the FAMD analysis of morphological
variation in the Azores broadly supported current taxon
delimitation, largely differentiating between the low
altitude subsp. malvifolia and the high altitude subsp.
caldeirae (Fig. 2a). The perMANOVA analysis revealed
that morphological variation was better explained by
differences between islands (35 %) than by differences
between subspecies (19 %). However, there are two
morphological characters that are markedly distinct
between subspecies, namely disc cypselae indumentum
and length of the highest bract. Populations of subsp.
malvifolia from Santa Maria and São Miguel show some
morphological differentiation according to the FAMD
that is not reflected in current treatments (Fig. 2a: see
supporting information S4 for FAMD plots with points
coloured by islands) and that largely reflects differences
in disc floret corolla length and stamen length. However,
this variation is subsumed within the range of morpho-
logical variation exhibited by the central group subsp.
malvifolia, which precludes its taxonomic recognition.
The larger morphological variation found between
islands in the Azores according to perMANOVA
may reflect the combined effect of 1. the morphological
differences between Santa Maria and São Miguel and 2.
the morphological differences between subspecies
caldeirae restricted to the central islands and subsp.
malvifolia that occurs on both central and Eastern island
groups.
In contrast to the situation in the Canaries, there was
no correlation between morphological and geographical
distance in the Azores (Table 4). This is in contrast to
the situation in some other Azorean plant groups, where
recent taxonomic revision has resulted in the recogni-
tion of geographically restricted endemic taxa (e.g.
Platanthera, Bateman [29]; Leontodon [30]; Aichryson
[31]). Analyses of patterns of morphological variation in
Pericallis therefore suggest that past failures to recognise
morphologically distinct taxa in the Azores do not
appear to be an explanation for the lack of SIEs in
Azorean Pericallis even though it may be significant in
other groups.
Hypothesis 2: ecological homogeneity in the Azores
Ecology would appear to be an important factor associ-
ated with diversification in both archipelagos. Both
Azorean and Canarian lineages exhibited ecological
differentiation between currently recognized taxa, al-
though differentiation was greater between the Azorean
taxa (Figs. 2b and d). Furthermore, variation in morph-
ology was correlated with climate and geographical
distance in both the Canaries and the Azores (Table 4).
In the Canarian lineage, species exhibited broad
ecological ranges but ecological differentiation between
species is nevertheless observed in the PCA analysis
(Fig. 2d). Morphology was correlated with both PC1
and PC2 of the climate analysis, although this result
was highly influenced by the effect of geographical
distance (Table 4). The Azorean pattern of climatic
differentiation was similarly consistent with morpho-
logical differentiation, yet with greater clustering in the
bioclimatic PCA compared to the FAMD based on
morphological data (Fig. 2a and b). It is notable that
most of the variation in climate (76.89 %) was explained
by the first axis of the PCA analysis. Along axis PC1, all
subsp. caldeirae individuals, with the exception of one
individual from São Miguel were differentiated from
subsp. malvifolia. Populations of subsp. malvifolia from
Santa Maria, São Miguel and the central group were
also differentiated in the PCA of climatic data. Whilst
morphology showed no correlation with geographical
distance, it was correlated with climate PC2, and
strongly so according to the partial dbRDA when
geographical distance was taken into account (Table 4).
The results therefore suggest that shifts in bioclimatic
preference across an ecologically heterogeneous island
system are associated with the morphological diversifi-
cation of Pericallis groups in both the Azores and the
Canaries. In both archipelagos, there are more floral
than leaf characteristics accounting for the morpho-
logical differentiation between the bio-climatically
distinct Pericallis taxa, for example, cypselae indumen-
tum of the disc florets between the ecologically and
attitudinally distinct P. malvifolia subspecies in the
Azores. These traits are not obviously adaptive, a
situation in contrast to some other island radiations
studied wherein variation has been observed in leaf
characters, for example, Plantago in Hawaii [32] and
Lavandula intheCanaryIslands[33].TheWorldClim
model interpolates from weather station observations
using latitude, longitude and elevation. Therefore,
there may be limitations in the reliability of the bio-
climatic data, particularly in regions with varied top-
ography such as oceanic archipelagos [34, 35]. Despite
this, we identify clear bioclimatic patterns in the case
of Pericallis in the Azores and Canaries at odds with
the ecological homogeneity hypothesis [14]. In order
Jones et al. BMC Evolutionary Biology (2016) 16:202 Page 8 of 15
to further test the ecological homogeneity hypothesis
put forward by Triantis et al. [14], it would be
informative to measure and compare the levels of
ecological opportunity between taxa in the Azores
and Canaries and test the associations with adaptive
radiations. This would, for example, require an assess-
ment of potential key innovations and the colonization
of new habitats and subsequent ecological release such as
in the form of increased population size or broader habitat
use [36]. These measures are difficult to obtain but
mechanistic frameworks that simulate these processes
are currently been developed (see Wellborn and
Langerhans [37]).
What does explain the ADE-like pattern for Pericallis?
A key difference between Pericallis diversity patterns in
the two archipelagos concerns the relationship between
morphological and molecular (AFLP) data. We observe
isolation by distance (IBD) for AFLP data in both archi-
pelagos (Table 4). In the Canary Islands AFLP data
showed some congruence with current taxonomic treat-
ments although with sharing of genetic material evident
between taxa. In the Azores, three AFLP groups were
defined, broadly corresponding to the central group, São
Miguel, and Santa Maria (thus two genetic SIEs are
defined; Fig. 3a), a pattern that was incongruent with the
recognised subspecies. These findings are similar to
Schaefer et al. [10] who observed genetically differentiated
SIEs in a suite of apparently widespread Azorean endemic
lineages.
A smaller proportion of the AFLP variation was
explained by between-island differences in the Canaries
than in the Azores (Table 3), and there was greater
sharing of genetic material between islands in the
Canaries than between Santa Maria, São Miguel and the
Central island group in the Azores. Thus, AFLP data
suggest a stronger geographical signal in the Azores than
in the Canaries, and the AFLP pattern in the Azores is
at odds with the pattern observed with morphology
whereas AFLP data and morphology are broadly congru-
ent in the Canaries. Several factors may explain the differ-
ences. The generally smaller population sizes in the
Azores than in the Canaries, partly influenced by an-
thropogenic factors such as habitat destruction, may have
led to stronger genetic structuring. While populations in
Santa Maria and, to a lesser extent, São Miguel may be
large, those in the central group of the Azores are typic-
ally comprised of less than 100 individuals; in the Canar-
ies, populations are often extensive. Geographic isolation
between populations is a second factor that may explain
the greater geographical structuring of AFLP data in the
Azores. Colonization of a new island is the result of a
combination of dispersal and establishment. Pericallis
achenes are wind dispersed (anemochorous) that likely
facilitates long distance dispersal to islands [38], yet the
predominant dispersal syndromes observed in different
island floras appear to be highly idiosyncratic [39]. Geo-
graphic distance is critical in the process of colonization
and therefore, greater geographic distance between
islands may facilitate inter-island diversification [35]. In
the Canaries, the maximum distance between two
neighbouring islands on which herbaceous Pericallis
occur is ~60 km. In the Azores, the distances between
Santa Maria and São Miguel (~80 km) and between São
Miguel and the central group (~120 km) are both greater,
and this is likely to promote greater genetic differenti-
ation by geographic isolation (Fig. 1; [40, 41]). Within the
Azorean central island group, wherein all except one ac-
cession are placed in the same genetic cluster, the islands
are generally in closer proximity than in the Canaries
(minimum distance: 6–19 km) and this may explain the
lack of differentiation between populations on these
islands. Terceira is a notable exception; at 39 km from
São Jorge it is more isolated than the islands of Tenerife
and La Gomera in the Canaries (28 km). The lack of dif-
ferentiation of Terceira populations from other central
sub-archipelago populations was also observed in genetic
diversity analyses of the endemic Picconia azorica [42],
but the island has been found to harbour distinct genetic
lineages in other taxa [10].
In the Canaries, molecular and morphological diversity
were both correlated with geographical distance and
climatic variation (Table 4). However, geographical dis-
tance and climate were themselves correlated (r = 0.21,
P= 0.001 for geographic distance vs PC1; r = 0.3, P= 0.001
for geographic distance vs. PC2). Thus, morphologically
differentiated clusters in the Canarian lineage tend to be
both geographically isolated and climatically differentiated
(Fig. 2d). The group may therefore be considered to be an
example of a classic island adaptive radiation, within which
geographical isolation and ecological differentiation have
acted in concert in the diversification of the group [43, 44].
In a review of molecular phylogenies of island lineages,
Baldwin et al. [45] concluded that inter-island allopatry
was an important driver of diversification in the Canaries
given that closely related taxa often occupy apparently
similar habitats but on different islands. Our results for
Canarian Pericallis suggest that the closely related and
recently diverged taxa occupy broadly similar habitats
but there is some evidence for bio-climatically differen-
tiation between taxa that may have further contributed
to their diversification. Other putative examples of ‘in-
ter-island allopatry’in the Canaries may also involve
ecological differentiation (e.g. Gonosperminae, [46];
Lotus,[47]orBystropogon [48]).
In the Azores, morphology showed no correlation with
geographical distance but was correlated with climate
Jones et al. BMC Evolutionary Biology (2016) 16:202 Page 9 of 15
when the possible noise caused by geographical distance
was taken into account in the partial dbRDA (Table 4).
In contrast, AFLP data were not correlated with climate
when geographical distance was taken into account.
Thus, molecular patterns appear to reflect island isola-
tion and genetic drift (inter-island allopatry) whereas the
morphological patterns reflect ecological differentiation.
The latter has involved shifts between climatic zones
that have occurred within islands or island groups at
least twice in parallel in the central group and in São
Miguel. Therefore, in contrast to the Canaries, the
effects of geographic isolation and ecological differenti-
ation in Azorean Pericallis are uncorrelated.
The independent origins of the high altitude subsp.
caldeirae ‘morphotype’on separate islands in the central
group and São Miguel may reflect underlying phenotypic
plasticity, i.e. the property of a genotype to express
distinct phenotypes in different environments [49]. The
role of phenotypic plasticity in diversification is widely
debated (see [50] and references therein). However,
phenotypic plasticity provides opportunities for diversifi-
cation, including ecological adaptation and speciation
[50]. The maintenance of morphological differences in
spite of limited genetic differentiation between taxa
could also reflect strong ecological selection on few loci
of large effect that are not detected by the AFLP analyses
due to limited genome coverage [51–54]. Recent studies
have also provided evidence for ecological divergence
correlating with epigenetic changes in DNA methylation
[55]. The potential role of epigenetics in generating
phenotypic plasticity in the diversification of recently
evolved oceanic island lineages has yet to be explored
and may be significant.
Incongruence between molecular and morphological
patterns may reflect a more general pattern in the
Azorean flora. For example, Euphorbia stygiana subsp.
stygiana shows geographical structuring of molecular data
yet morphological differences to support this have not
been identified [10]. Molecular studies of the Azorean
Ammi lineage [10] and Azorean Juniperus [56] have
demonstrated geographically structured patterns that are
incongruent with morphology. It is important to note that
although our sampling ensured a broad distributional
range and included almost all known Pericallis popu-
lations in both archipelagos, the number of samples
with both morphological and genetic data was limited
(Additional file 4: Table S1). Therefore, future studies
with an increased number of individuals per popula-
tion may help further explain the patterns.
Conclusions
Overall, our results suggest that the paucity of morpho-
logically defined SIEs in Azorean Pericallis when
compared to the Canaries is not simply the result of a
Linnean shortfall. Furthermore, ecological diversification
of taxa is observed in both archipelagos. In the Canar-
ies, the correlation between isolation and ecological
differentiation results in a classic island adaptive radi-
ation in which we observe geographically isolated
morphologically differentiated taxa, even though the
molecular data suggest some gene flow. The Azorean
lineage, within which morphology and molecular data
are not congruent, does not conform to this pattern.
The results of this study are at odds with the recent
discovery of new endemic taxa in other Azorean plant
lineages [29, 30, 57]. Taken together, recent work on
the Azores flora suggest that its distinctiveness that
was first commented on by Darwin reflects both a
lack of taxonomic effort but also differences between
archipelagos in the geographical and ecological con-
text for diversification.
Methods
Sampling, sites and plant material
Individuals from both the Azorean (P. malvifolia subsp.
malvifolia and subsp. caldeirae) and Canarian (P. cruenta,
P. echinata, P. murrayi, P. papyracea and P. steetzii) line-
ages were sampled across the distribution ranges of each
taxon, as recommended by Caujapé-Castells et al. [58]. In
Tenerife, P. cruenta and P. echinata are known to
hybridize [59]. We used morphometric analyses to identify
putative hybrids. Individuals that showed intermediate
morphological characteristics between the two taxa were
excluded from the analysis since they were not the
focus of this study. Leaf material was dried in silica gel
for DNA analyses. Herbarium specimens were made
and deposited at AZU, BM and ORT (Additional file 4:
Table S1). Capitula were stored in 30 % alcohol for
morphological analyses.
In the present study it was necessary to select samples
that provided the full range of morphological characters
for morphometric analysis and high quality DNA
material for AFLP analyses, whilst also ensuring good
geographic sampling across the distribution of taxa. In
total, we sampled 150 and 114 individuals in the Azores
and Canaries respectively. Some samples did not possess
the morphological characters that were necessary for
morphometric analyses; however, they provided high
quality DNA and represented a locality that was import-
ant to sample, and they were therefore included only in
the AFLP analyses. On the other hand, a number of sam-
ples possessed the full range of morphological characters
for morphometric analyses yet for different reasons they
could not be used for AFLP analyses. Herbarium samples,
for example, typically provided poorer quality DNA than
was necessary for AFLP analyses. In other cases, financial
constraints limited the depth of sampling for AFLP ana-
lyses from a particular locality. Our sampling was
Jones et al. BMC Evolutionary Biology (2016) 16:202 Page 10 of 15
selected to ensure a broad distributional range and to
include as many known populations of Pericallis as
possible (See Additional file 4: Table S1 for details of
samples and populations). A compromise between broad
geographic and taxon sampling ensuring high quality
sample material whilst accounting for financial con-
straints was necessary for the AFLP analyses.
Morphometric analyses
A total of 125 individuals from the Azores and 89 indi-
viduals from the Canaries were included in the morpho-
metric analyses (Fig. 1 and Additional file 4: Table S1).
For both Canarian and Azorean lineages, the same 30
vegetative and floristic characters were initially scored
(Additional file 5: Table S2 for list of morphological
characters and Additional file 1: Figure S1 for illustra-
tions of characters measured). Analyses, however, were
restricted to those characters that showed some
variation within lineages (Additional file 6: Table S3).
Continuous characters were standardised using the
function “scale”in the R v 3.0.1 package base, which
transforms variables to achieve a mean of zero and a
standard deviation of one [60]. Median values were
taken for categorical characters that used multiple (a
minimum of three) observations or counts.
FAMD, a principal component method which can
assess the variation and balance the influence of both
continuous and categorical variables [61], was performed
in R. Missing data were accounted for using the R pack-
age missMDA and the combined (continuous and
categorical) dataset was imputed using the function
“imputeFAMD”. The function “FAMD”from the package
FactoMineR was used on the imputed combined dataset
[61]. To further test for morphological differences
between taxa and between islands, the combined datasets
were transformed to dissimilarity matrices for each archi-
pelago using the “Gower”method and the function daisy
in the package cluster (72, 73). Subsequently, non-
parametric permutational multivariate analysis of variance
(perMANOVA) were conducted using the function “ado-
nis”from the package Vegan [62], using taxa and islands
as factors, a Euclidean distance method and 999
permutations.
Bioclimatic data
Whilst bioclimatic datasets from the WorldClim
(http://www.worldclim.org/) model may not account
for the complex topological variation and micro-climatic
conditions and climate predictions in regions with poor
station density and varied topography [63], such data has
been informative in previous studies to analyse the biocli-
matic characteristics of islands [35]. We, therefore,
extracted values from 19 bioclimatic variables at 30 s.
resolution available from Worldclim, for each collection
locality using DIVA-GIS v. 7.5 (http://www.diva-gis.org/;
Additional file 6: Table S3 for a list of bioclimatic vari-
ables). To assess ecological variation among localities
within each archipelago, all bioclimatic variables were
standardized using the same method as described for con-
tinuous morphological variables, and Principal Compo-
nent Analyses (PCA) were carried out using the function
“PCA”of the FactoMineR package [61].
AFLP data
The genetic markers used to date for Pericallis have
shown very low levels of variation [18], emphasizing
the need for more polymorphic genetic markers such as
AFLPs. These versatile markers do not require the
development of individual markers de novo for each
species [2] and are a good choice for taxa in which little
prior genomic information is available [64]. AFLPs are
also an appropriate marker system when studying taxa
that are polyploid, as is the case with hexaploid Pericallis
[2, 59, 65, 66]. AFLPs have also already been used success-
fully to investigate hybridization between Pericallis taxa
on Tenerife [59].
Seventy-six samples of the Azorean P. malvifolia were
used for AFLP fingerprinting analysis, 51 of which were
used in the morphometric analysis. This sampling
encompassed populations of both subspecies on all
islands on which they occur. Since P. malvifolia subsp.
caldeirae has a more restricted distribution, only ten in-
dividuals were sampled for AFLP fingerprinting. A total
of 69 samples were used for the AFLP fingerprinting
analysis of the five Canarian taxa, 44 of which were used
in the morphometric analysis, selected to represent
the distribution range of taxa in each case (Additional
file 4: Table S1).
DNA extraction followed the protocol in [18], with ap-
proximately 300 ng of genomic DNA obtained from the
leaf material of each sample. Amplified fragments were
obtained following the protocol of Vos et al. [67]. The
restriction-ligation reaction was performed in two separ-
ate steps using the LI-COR kit (BioSciences, UK). Total
genomic DNA was digested using two endonucleases:
EcoRI-A/MseI-C. Selective amplifications were carried
out using fluorescent dye-labelled markers with six primer
combinations. Fluorescent dye-labelled selective primers
(Applied-Biosystems, Invitrogen, UK) and MyTaq™
(Bioline, UK) were used during the selective amplification
phase (Additional file 7: Table S4). Polymerase Chain
Reactions were conducted using a Veriti Thermal Cycler
(Applied Biosystems-Invitrogen, UK). Amplified frag-
ments were separated on an ABI 3500 Genetic Analyser at
the University of Bristol using dye set DS-30 and ROX size
standards (Applied Biosystems, UK). Electropherograms
were scored using GeneMapper v. 3.7 (Applied Biosys-
tems, UK). Amplified fragments of 80–500 base pairs were
Jones et al. BMC Evolutionary Biology (2016) 16:202 Page 11 of 15
scored as having present (1) or absent (0) peaks in the out-
put traces. The threshold for allele calling was set at 50
relative fluorescent units (RFU) and if a bin contained a
peak above this threshold the allele was considered to be
present. Before the allele frequency data were used in sub-
sequent analyses, the results were reviewed manually
using the criteria of Karudapuram & Larson [68]; we
checked the size quality, genotype quality, bin assignment,
allele calls and ambiguous calls.
To assess the reproducibility and reliability of AFLP
fragments, we replicated 5–7 % of the individuals (6 in-
dividuals in the Canaries and 4 individuals in the
Azores) at all stages from DNA isolation to AFLP pro-
duction, according to the recommendations of Bonin et
al. [69] and Holland et al. [70]. Duplicate analyses exhib-
ited 85 and 90 % reproducibility of the bands for the
Azores and the Canaries, respectively. We removed all
loci that were not reproducible. We also removed loci
and samples with >50 % missing data. The geo-
referenced genotype matrices used in this paper and
other relevant information can be found in the genetic
diversity digests coded D-AFLP-94 and D-AFLP-97
[71, 72] in the Demiurge information system (http://
www.demiurge-project.org/).
Estimating genetic relationships and population genetic
structure
Population genetic analyses of polyploids such as
Pericallis are challenging due to the various assump-
tions of statistical analyses linked with the difficulty in
characterising the allelic variation within each individual,
and the differing inheritance patterns between loci [73].
Furthermore, it is impossible to calculate allelic frequency
using AFLP data.
A Discriminant Analysis of Principal Components
(DAPC) was used to assign individuals to genetic clus-
ters [23, 24]. This is an appropriate alternative to Bayes-
ian analysis of assignment such as STRUCTURE [74], as
it does not assume Hardy-Weinberg equilibrium or
make assumptions about the inheritance of each locus
[73, 75]. DAPC requires the construction of prior
groups, therefore we characterised the most likely num-
ber of clusters in each archipelago by running the se-
quential K-means clustering algorithm (all PCs retained)
using the “find.clusters”function in the R package ade-
genet, based on the Bayesian Information Criterion
(BIC; [24]). The analyses were run for K=1–20. DAPC
was then run using values of Karound the most likely
numbers of a priori clusters. The DAPC procedure con-
sists of two steps: first, the original data are transformed
and submitted to a PCA. Second, the PCs are passed to
a Linear Discriminant Analysis based on the groups
identified during the preliminary K-means clustering
analysis. Retaining too many PCs with respect to the
number of populations can lead to over-fitting the dis-
criminant functions, meaning that membership probabil-
ities may become drastically inflated for the best-fitting
cluster, resulting in apparent perfect discrimination [75].
Considering this, we used the “optim.a.score”function
that assesses the quality of discrimination between
groups by looking at re-assignment of individuals to
their prior group. The a-score can serve as a criterion
for choosing the optimal number of PCs in the PCA step
of DAPC [24].
For each archipelago, we used hierarchical analyses
of molecular variance (AMOVA) [25, 26] to investi-
gate partitioning of variation within and among the
groups defined by the DAPC analysis. The distance
between individuals was calculated from the AFLP
presence/absence matrix using Dice dissimilarity index
in R and the package ade4 (Dray & Dufour 2007).
The Dice dissimilarity coefficient is commonly used
to calculate genetic distance in polyploids [76, 77].
Significance levels were tested using 999 permutations
following the procedure given by [26] and imple-
mented in the package ade4 in R [78].
Distance-based redundancy analyses
To investigate IBD for each archipelago, we regressed
geographic distances against morphological and gen-
etic distances by carrying out full dbRDA using the
Vegan package in R [62] and calculated the signifi-
cance using 1000 random permutations. Morpho-
logical distance matrices were produced following the
method used for the perMANOVA analyses, using the
function “daisy”and Gower’s coefficient [79] in the
Cluster package in R [80]. Classic Euclidean genetic
distance matrices (or Roger’s distance) were calculated
from the AFLP presence/absence datasets using the
“distgen.pop”function of the adegenet package [81].
Geographic distance matrices (in metres) were calcu-
lated from latitude and longitude data using the
“earth.dist”function of the Fossil package [82] in R.
The values were standardized using a logarithmic
transformation and converted to continuous rectangu-
lar datasets using the function “npcm”of the Vegan
package.
The first two PCs (PC1 and PC2) from the PCA ana-
lyses of bioclimatic variables were used as a measure of
bioclimatic conditions to avoid autocorrelation between
individual bioclimatic variables, and a full dbRDA was
used to test for any correlation between bioclimate and
morphological variation, and genetic variation as above.
We used partial dbRDA to test the influence of
geographical distance on the relationship between (i)
genetic diversity and bioclimate and (ii) morphology and
bioclimate.
Jones et al. BMC Evolutionary Biology (2016) 16:202 Page 12 of 15
Additional files
Additional file 1: Figure S1. Factor Analyses of Mixed Data of
morphological variation in the Azores, different symbols represent
subspecies and islands. Each point represents an individual. (DOCX 27 kb)
Additional file 2: Figure S2. Graphs from find.clusters indicating the
best Kvalues for DAPC (a) Azores and (b) Canary Islands. (DOCX 265 kb)
Additional file 3: Figure S3. Discriminant Analysis of Principal
Components showing the genetic clustering of populations of Pericallis
lineages analysed in the Canaries for K=3(a) and K= 4 (b). Each bar
represents one individual plant (69 individuals from the Canaries). (PDF 90 kb)
Additional file 4: Table S1. Sample information for accessions used in
the AFLP and morphological analyses (collector’s name(s), collection
number, collection date, island, locality, altitude, latitude, longitude,
analysis/es applied to sample, well number (AFLP), population code for
AMOVA (AFLP) and morphometric data for each sample analysed
(imputed and standardized)). (XLSX 81 kb)
Additional file 5: Table S2. List of morphological traits initially scored
with details of their transformations (Table A). List of morphological traits
scored for (Table B) Azorean P. malvifolia specimens and (Table C)
Canarian specimens with details of their transformations. Factor loadings
of each character for the first two dimensions of the FAMD analysis are
provided. Characters are sorted by values of Dimension 1. Morphological
measurements referring to the list of morphological traits are indicated
by figures: (Fig. A) Leaf, ray floret and disc floret measurements (refer to
Table A for key and the legend); (Fig. B) Terminal peduncle; (Fig. C) Apical
inflorescence bract. (DOCX 493 kb)
Additional file 6: Table S3. List of bioclimatic variables analysed and
factor loadings in the (a) Azores and (b) Canary Islands. (DOCX 19 kb)
Additional file 7: Table S4. AFLP primer and labelled-dye information.
(XLSX 8 kb)
Acknowledgements
The authors thank the following collaborators for contributing to fieldwork:
F. Rumsey (Natural History Museum, London); M. Padrón-Mederos and A.
Santos-Guerra (Jardín de Aclimatación de La Oratava); M. Sequeira (University
of Madeira); M. Soto-Medina, A. Marrero-Rodríguez, and M. Olangua Corral
(Jardín Botánico Canario “Viera y Clavijo”-UA CSIC); M. Moura, L. Silva, and J.
Martins (University of the Azores, São Miguel); H. Schaefer (Technische Universität
München, Germany) and A. Mills (National Trust, UK). We also thank the Cabildos
of Tenerife, Gran Canaria, La Palma, El Hierro and La Gomera for permission to
collect research material in the Canaries and the Azorean Regional Government
for permission to collect research material in the Azores. Kai Winkelmann (Natural
History Museum, London) provided support and advice during AFLP lab work.
Funding
This work was supported by a Natural History Museum Scholarship to
KJ. The Royal Horticultural Society and the Royal Society of Biology are
acknowledged for further financial contributions towards fieldwork. A
Departmental Innovation Fund grant from the Life Sciences Department
at the Natural History Museum, London and a Genetic Society Training
Grant from the Genetic Society also contributed towards laboratory
training and consumable costs for KJ.
Availability of data and materials
The datasets supporting the conclusions of this article are available in the
Figshare repository provided here: [83] [NB: this is currently a private link and
a public DOI will be made available].
Authors’contributions
KJ gathered, analysed and interpreted the data. DP gathered the morphological
data for Pericallis in the Canaries as part of his MSc thesis supervised by MC and
KJ. KJ was the main contributor in writing the manuscript with large
contributions and discussions with MC throughout. SP contributed to
discussions regarding AFLP and statistical data analyses and to the
manuscript writing phase. SH provided advice on statistical analyses and
contributions to the manuscript. JAR contributed to discussions regarding
morphological data and taxon sampling, and was involved in much of the field
work in the Canaries. JC was involved in field work and advice on sampling in
the field. All authors read and approved the final manuscript.
Competing interests
The authors declare that they have no competing interests.
Consent for publication
We have been given consent for publication of images used in Fig. 1.
Ethics approval and consent to participate
Not applicable.
Author details
1
Botanischer Garten und Botanisches Museum Berlin-Dahlem, Dahlem Centre
of Plant Sciences, Freie Universität Berlin, Königin-Luise Str. 6-8, Berlin 14195,
Germany.
2
Estación Biológica de Doñana, CSIC, C./ Américo Vespucio s/n,
Sevilla E-41092, Spain.
3
Jardín de Aclimatación de La Oratava (ICIA), C/Retama
2, Puerto de la Cruz, Tenerife 38400, Spain.
4
Natural History Museum,
Cromwell Road, London SE7 5ED, UK.
5
Present address: Department of
Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK.
6
Jardín Botánico Canario “Viera y Clavijo”-Unidad Asociada al CSIC (Cabildo
de Gran Canaria), Camino del palmeral 15 (Tafira Alta), Las Palmas de Gran
Canaria 35017, Spain.
7
Department of Plant Sciences, University of Oxford,
South Parks Road, Oxford OX1 3RB, UK.
Received: 20 June 2016 Accepted: 27 September 2016
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