Next Article in Journal
Successful In Vitro Shoot Multiplication of Quercus robur L. Trees Aged up to 800 Years
Next Article in Special Issue
Spergularia hanoverensis (Caryophyllaceae): Validation and Recircumscription of a Misinterpreted Species from South Africa
Previous Article in Journal
Plant-Produced Nanoparticles Based on Artificial Self-Assembling Peptide Bearing the Influenza M2e Epitope
Previous Article in Special Issue
Nomenclature Survey of the Genus Amaranthus (Amaranthaceae): 12 Questions about Amaranthus caudatus
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Plants
Volume 12
Issue 11
10.3390/plants12112229
plants-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Integrative Taxonomy of Armeria Taxa (Plumbaginaceae) Endemic to Sardinia and Corsica

by
Manuel Tiburtini
1,*,
Gianluigi Bacchetta
2,
Marco Sarigu
2,
Salvatore Cambria
3,
Paolo Caputo
4,
Daniele De Luca
4,
Gianniantonio Domina
5,
Alessia Turini
1 and
Lorenzo Peruzzi
1
1
PLANTSEED Lab, Department of Biology, University of Pisa, Via Derna 1, 56126 Pisa, Italy
2
Centre for Conservation of Biodiversity (CCB), Department of Life and Environmental Sciences, University of Cagliari, V.le S. Ignazio da Laconi 13, 09123 Cagliari, Italy
3
Department of Biological, Geological and Environmental Sciences, University of Catania, Via Antonino Longo 19, 95125 Catania, Italy
4
Department of Biology, University of Naples Federico II, Via Cinthia 26, 80100 Naples, Italy
5
Department of Agricultural, Food and Forest Sciences, University of Palermo, Viale delle Scienze 4, 90128 Palermo, Italy
*
Author to whom correspondence should be addressed.
Plants 2023, 12(11), 2229; https://doi.org/10.3390/plants12112229
Submission received: 3 May 2023 / Revised: 24 May 2023 / Accepted: 2 June 2023 / Published: 5 June 2023
(This article belongs to the Special Issue Taxonomy and Nomenclature of Caryophyllales)
Browse Figures
Review Reports Versions Notes

Abstract

:
Sardinia and Corsica are two Mediterranean islands where the genus Armeria is represented by 11 taxa, 10 out of which are endemic. An integrative approach, using molecular phylogeny, karyology, and seed and plant morphometry was used to resolve the complex taxonomy and systematics in this group. We found that several taxa are no longer supported by newly produced data. Accordingly, we describe a new taxonomic hypothesis that only considers five species: Armeria leucocephala and A. soleirolii, endemic to Corsica, and A. morisii, A. sardoa, and A. sulcitana, endemic to Sardinia.

1. Introduction

Island biodiversity attracted the attention of many biologists since the mid-XIX century [1,2,3,4]. Islands have been historically classified according to their geological history into two large groups: oceanic and continental [5,6]. In the Mediterranean, among the largest (>5000 km2) islands—Sicily, Sardinia, Cyprus, Crete, and Corsica—only Cyprus can be considered an oceanic island [7], whereas all the others are continental islands. Speciation processes in the two types of islands are different [8,9,10].
Sardinia and Corsica share a similar Oligocenic–Miocenic (ca. 30 to 16 Ma) geological history [11,12] that played a role in shaping the current biodiversity. In fact, some authors consider them as a single biogeographic unit [13,14]). More recently, the Messinian salinity crisis (5.96–5.3 Mya) led to a high rate of extinction of the tertiary flora, followed by the onset of the Mediterranean climate [7].
It is generally assumed that continental islands should possess a higher rate of palaeoendemics. However, Cheikh Albassatneh et al. [15] failed to find any evidence supporting this idea for the flora endemic to Sardinia and Corsica. Irrespective of its origin, this flora shows a much higher rate of endemism than the mainland [16] due to isolation processes, reduced gene flow and adaptation, resulting in a higher rate of speciation [17]. The current floristic diversity of Sardinia and Corsica [18] is one of the highest in the Mediterranean. Indeed, 485 out of the 4572 plant species native to Sardinia and Corsica are endemic, and the Corso-Sardinian biogeographic province is currently considered a hotspot for plant diversity in the Mediterranean Basin [13,19,20,21].
Despite the Corsican-Sardinian flora is well known from a floristic point of view, the taxonomy of many endemic species is still unclear. One of the genera showing the highest number of endemic taxa for the region is certainly Armeria (DC.) Willd. (Plumbaginaceae). It is a genus of perennial, diploid (2n = 2x = 18) herbs, currently including 95 accepted species [22].
In Sardinia and Corsica, 11 Armeria taxa are reported, including the easily recognizable western Mediterranean A. pungens Hoffmanns. & Link, whose occurrence in the area could be explained by an event of long-distance dispersal from Portugal [23]. The other 10 taxa are all endemic to Sardinia and Corsica [24,25]. Arrigoni [24] considered all these endemics (except A. morisii Boiss.) as neoendemics, speculating about their origin and affinities with Sicily, Spain, and mainland Italy.
Speciation (and, in a broad sense, the rate of endemism) depends on our understanding of the meaning and the value of the taxonomic hypotheses that we assume as the outcome of the speciation events [26]. Accordingly, it is evident that systematics is a fundamental tool to unveil the distribution and boundaries of the variability of nature that we want to encapsulate in a name and a hierarchy using nomenclature and taxonomy [27]. However, the accuracy of systematic inferences depends upon the techniques used and the available resources [28]. Turrill [29] distinguished three levels of taxonomy. The first one is alpha-taxonomy, an approach that relies only on morphological data. When cytogenetic characters and/or anatomical characters are added, we can talk about beta-taxonomy. Lastly, omega-taxonomy refers to the ideal case of a taxonomic circumscription made using a high number of different sources of systematic information. Schlick-Steiner et al. [28] showed that when multiple sources of data are added (i.e., moving from alpha- to omega-taxonomy), the error rate in taxonomic circumscriptions steadily decreases. This is desirable, especially in a taxonomically difficult genus such as Armeria. Most of the species are still circumscribed on the basis of the sole morphology (i.e., at the alpha-taxonomic level). However, integrative taxonomic approaches (moving towards an omega-taxonomy) proved their effectiveness in resolving taxonomic uncertainties in A. maritima Willd. [30], A. pubigera Boiss. [31], A. trianoi Nieto Fel. [32], and A. arenaria (Pers.) F.Dietr. [33] or in detecting hybridization [34,35].
The latest taxonomic treatment of Armeria taxa endemic to Sardinia and Corsica dates back to Arrigoni [24], who relied only on morphology and chromosome counts. Thus, his taxonomic hypotheses could be potentially biased. Arrigoni [24] recognized six species and then four subspecies. For example, he circumscribed A. multiceps Wallr. subsp. multiceps and A. sardoa Spreng. subsp. genargentea Arrigoni as high elevational ecotypes, whereas he considered as low-elevational ecotypes A. multiceps subsp. meridionalis Arrigoni and A. sardoa subsp. sardoa. Similar infraspecific variations are described for A. leucocephala Salzm. ex W.D.J.Koch, endemic to Corsica, for which the author reported three subspecies [36]. Bernis [37] already highlighted morphological similarities among A. leucocephala, A. multiceps, and A. soleirolii (Duby) Godr. in Corsica. Doubts about the taxonomic value of the Corsican endemic taxa were already expressed by Tison and de Foucault [38]. Specifically, these authors consider the subspecies of A. leucocephala and A. multiceps as morphological variations at the individual level. Accordingly, moving towards an omega-taxonomic level for this group is crucial to reach a more stable taxonomy, which is an essential prerequisite for supporting conservation practices and clarifying the evolutionary processes that shaped the current diversity in Mediterranean islands.
Using an approach integrating molecular phylogeny, karyology, seed and plant morphometry, this study aims to (1) experimentally check the currently available taxonomic hypotheses (10 taxa, Figure 1) or alternatively, (2) propose a new taxonomic circumscription better fitting the newly produced systematic data with a new taxonomic scheme.

2. Results

2.1. Karyological Analysis

All populations were diploid showing 2n = 2x = 18 medium-sized (4.65 ± 0.81 μm) chromosomes. Centromeres were mostly median (50.21%), submedian (49.54%), and rarely subterminal (0.2%) (Table S1, Figure S1). We occasionally observed terminal satellites on short arms (9 out of 98 metaphasic plates). No significant difference (at α = 0.01 level) was found among the currently accepted taxa. Selected plates are shown in Figure 2.

2.2. Molecular Phylogenetic Analysis

The results of the ILD test are shown in Table S2 and allow us to perform the concatenation of plastidial and nuclear markers. In total, the concatenated matrix contained 2384 characters: the nuclear marker (ITS) showed only seven polymorphic sites, whereas the plastidial markers showed 51 polymorphic sites (trnH-psbA: 12; trnL-rpl32: 28; trnL-trnF: 5; trnQ-rps16: 6), the ITS and plastidial trees are shown in Figure S2. The phylogenetic tree (Figure 3) shows a rather complex scenario, with many evolutionary grades and admixtures between populations and even individuals. The chosen outgroup is formed by two populations of A. pungens, whereas the other branches of the tree are mostly collapsed. Armeria leucocephala and A. multiceps populations form together a scattered paraphyletic group. One population, BI, is found in two completely different grades. Concerning A. sardoa Spreng. subsp. sardoa and A. sardoa subsp. genargentea Arrigoni, they form a well-supported clade (0.98) together; however, the latter subspecies is paraphyletic. Lastly, A. morisii and A. sulcitana Arrigoni from the type locality form a clade closely related to A. soleirolii and to part of the A. leucocephala accessions.

2.3. Seed Morphometric Analysis

According to Random Forest mean decreased accuracy, the five most important seed morphometric features are, in decreasing order: CHull, MBCRadius, Feret, Concavity, and MaxR (Tables S3 and S4). The overall accuracy of the final model on the current species circumscription was quite low (50.47%), albeit the AUC (Area Under the ROC Curve) was 0.859. The highest per class errors were found among the subspecies of Armeria leucocephala and A. multiceps (class error >66%) (Table S6). On the contrary, the lowest values of misclassification were obtained by A. sardoa subsp. sardoa and A. morisii (27.09% and 30.1%, respectively). According to the tuned HDBSCAN* model, the whole dataset contains only two true clusters (Figure S3) for values ranging from 20 to almost zero, obtaining cluster scores (i.e., the sum of the stability scores for each salient flat cluster) of 59.40 (first cluster) and 315.54 (second cluster). The first cluster contains all the seeds from the GO and FO populations pertaining to A. sulcitana and A. sardoa subsp. genargentea, respectively. These two populations show much lower values for the five most important morphometric features found by Random Forest with respect to all others (Table S5).
The second cluster contains all the remaining populations. A finer structure is found within this latter cluster, given that two unsupported subclusters can be observed. PCoA applied to the same dataset confirmed this pattern. The first two axes captured more than 86% of the total variability of the distance matrix (Figure S3). The KMO test returned a MSA = 0.5.

2.4. Plant Morphometric Analysis

The two first axes of the PCoA explain 58.4% of the total variance (Figure 4). All of the populations largely overlap in the morphometric space. Both A. leucocephala and A. multiceps show a large overlap among their respective subspecies, whereas some degree of separation is present between A. sardoa subsp. sardoa and A. sardoa subsp. genargentea, especially concerning the populations from Badde Urbara (BU), Monte Limbara (ML), and Aritzo (AR). Armeria morisii (TH) shows a clear separation from all other taxa (Figure 4 and Figure S4). The overall pattern is maintained when comparing the first and the third axis, but A. soleirolii shows an almost complete separation in the morphospace (Figure S5).
The best k value for kNN when applied to the current taxonomic hypothesis (Table S7) at species level was k = 3. The multiclass AUC was 0.958, whereas the balanced accuracy was 92.8%.
The lowest values of balanced accuracy were obtained by the three subspecies within A. leucocephala (A. leucocephala subsp. breviaristata 69.15%; A. leucocephala subsp. leucocephala 60%; A. leucocephala subsp. pubescens 89.43%) followed by A. multiceps subsp. multiceps (88.6%). Moving to the univariate data, a heatmap (Figure 5) shows that the highest number of pairwise significant differences occurs between A. sardoa subsp. genargentea and A. morisii (29), whereas there is no difference between the subspecies within A. leucocephala and A. multiceps. Again, A. morisii shows the highest number of pairwise differences, followed by A. sardoa subsp. genargentea (135) and A. sardoa subsp. sardoa (104). In general, all subspecies within A. multiceps and A. leucocephala show <50 pairwise differences.
There is a high similarity among taxa, especially A. sulcitana, A. leucocephala and its subspecies, A. multiceps and its subspecies, A. sardoa and its subspecies. Accordingly, we tested two alternative taxonomic hypotheses based on the phylogenetic results and on morphometric comparisons. Hypothesis 1 consists in just lumping the subspecies under their respective species, while hypothesis 2 consists in also lumping A. leucocephala and A. multiceps. A tuned kNN model under hypothesis 1 showed a balanced accuracy of 97.87% with k = 5 (Table S8), whereas a tuned kNN model for hypothesis 2 yielded a final balanced accuracy of 99.01% with k = 4 and AUC = 0.994 (Table S9). In the Canonical Variate Analysis morphospace, where individuals were grouped according to hypothesis 2, A. sardoa is distinct from A. sulcitana, A. leucocephala, and A. soleirolii following the first and second discriminant functions, whereas A. sulcitana is distinct from other taxa when the first and third discriminant functions are plotted. These distinctions are confirmed by the lack of overlap of the 95% confidence ellipses (Figure S4).

3. Discussion

The currently accepted taxonomic hypothesis [24] is no longer supported by the new evidence produced in this study. Specifically, neither morphological nor molecular or karyological data is able to support the grouping hypothesis currently accepted for Armeria in Sardinia and Corsica (Figure 6).
Seed shape and size are under natural selection and may play a role in the adaptation of the population to different ecological conditions, leading to genetically fixing some characters and shaping the evolution of a species [39,40]. However, this is not the case for the Armeria taxa endemic to Sardinia and Corsica, in which we highlighted a high homogeneity in seed features. From a karyological point of view, there is no significant difference among taxonomic units, either arranging the taxa according to the current hypothesis or according to the alternative grouping hypotheses 1 or 2. Accordingly, there is a high degree of karyological homogeneity, suggesting that evolution in Sardinia and Corsica did not imply any relevant chromosomal rearrangement.
It is well known that homoploid hybrid speciation is frequent in Armeria [41,42]. Indeed, the karyotype is very stable with 2x = 2n = 18 [24,43], as also confirmed by our data, despite in other cases slight differences in karyotype structure can be observed [33]. The overall karyological homogeneity and the reduced prezygotic barriers, limited to the sole pollen-stigma dimorphism [44,45,46], may have facilitated the hybridization/introgression and reticulate evolution of these plants in Sardinia and Corsica [25,47,48]. Indeed, hybridization is common in Armeria [34,49], despite the low signal provided by ITS (Figure S2), which may be due to concerted evolution [47]. Accordingly, the phylogenetic signal found in the concatenated tree is largely dominated by the information coming from the cpDNA (Figure S2), which in Armeria is maternally inherited [50]. Hybridization/introgression, incomplete lineage sorting and concerted evolution could all explain the observed pattern in the Armeria clade containing all the taxa endemic to Sardinia and Corsica. There, some individuals belonging to the same population are sometimes scattered all over the tree (i.e., GO, MO, BI). Genomic data and more sophisticated models, such as coalescent network-like models, may be needed to disentangle among these possible events [51].
Nevertheless, we can see that the subspecies of A. leucocephala and A. multiceps are mixed and form a grade. This evidence is corroborated by the low number of univariate morphological features that separate these taxa, and supports the view by Tison & de Foucault [38], who did not recognize the taxonomic value of what they considered just altitudinal variations. Moreover, there is no possibility to morphologically separate neither the two species in their traditional concept, nor the two clades found by molecular phylogeny (Figure 6). Accordingly, we do think that the only sound taxonomic solution is to merge A. leucocephala and A. multiceps into a single species. In this respect, the name Armeria leucocephala Salzm. ex W.D.J.Koch has priority over A. multiceps Wallr. Concerning A. sardoa, A. sardoa subsp. sardoa is phylogenetically included within A. sardoa subsp. genargentea. Morphologically, the two subspecies show only six statistically significant differences, possibly due to adaptation to different altitudes. Accordingly, we deem more opportune not to distinguish subspecies within A. sardoa. Armeria soleirolii is narrowly endemic to the northwestern part of the rocky coast of Corsica, ranging from Calvi to Galeria [24]. Interestingly, this taxon is phylogenetically isolated within a grade composed of taxa both from Sardinia and Corsica. The unique habitat and morphological features (i.e., the presence of papillate epidermal cells on leaves that are also canaliculate and stiff) support the autonomy of this taxon, which indeed shows no misclassification by kNN. Lastly, A. morisii shows the highest number of unique morphological features. Armeria morisii and A. soleirolii are easily distinguished from all other taxa by a set of character states, and their position in the phylogenetic tree is better defined than in other cases. Our findings are partially in contrast with the observations published by Bernis [37], particularly for A. soleirolii. Finally, A. sulcitana is different from A. sardoa in having longer inner involucral bracts, longer awns and being taller (Table S10), whereas it is slightly different from A. leucocephala in possessing mainly dimorphic leaves with exclusively smooth margins (Table S11). Accordingly, considering the currently available systematic data together (Figure 6), we deem the alternative taxonomic hypothesis 2 (i.e., five species) the best possible solution. Thus, we can conclude that there was an overestimation of plant diversity for this genus in the biogeographical region of Sardinia and Corsica. Interestingly, this is not an isolated case. Indeed, other studies that used an integrative taxonomic approach focusing on taxa endemic to this region found a similar pattern in Santolina L. (Asteraceae) and other taxa ([52] and literature cited therein). A similar reduction in the number of taxa following integrative taxonomic approaches has been documented in Ophrys L. (Orchidaceae) [53] and Pulmonaria L. (Boraginaceae) [54] from elsewhere.
To facilitate the identification of the five species endemic to Sardinia and Corsica as newly circumscribed here (plus A. pungens), their morphological differences are summarized in an identification key (Section 4.1).

4. Taxonomic Setting

Armeria leucocephala Salzm. ex W.D.J.Koch, Flora 6: 712. 1823.
Type (neotype designated here): FRANCE. Corsica: Monte d’Oro, s.d., Salzmann (G00440097 photo! https://www.ville-ge.ch/musinfo/bd/cjb/chg/adetail.php?id=298304 (accessed on 31 December 2022)).
Note: Koch [55] provided a description in German, also citing a collector (“Salzmann”) and the provenance “in den Corsischen”. Herbarium and types of Johann Friedrich Wilhelm Koch are unknown [56]. We found two herbarium specimens, one in G and one in MPU, where Salzmann’s herbarium is preserved [56,57]. The sheet barcode G00440097 bears two plants (part of the same collection) and the labels (bottom-left corner of the sheet) “Armeria leucocephala Koch v. alpina [manu Boissier]” and “Statice leucocephala Koch Bot. Beit. 1823, m. Salzmann, Monte d’oro (Corsica) [manu Salzmann]”. The sheet barcode MPU828624 bears five plants (part of the same collection), and the labels (bottom-left corner of the sheet) “Statice | Montagnes de Corse” and “Statice leucocephala| Armeria leucocephala Koch in … | Montagnes de Corse” (Salzmann’s handwriting; C. Loup pers. comm.). Unfortunately, both specimens lack the date of collection. In many sheets, Salzmann did not annotate the date (C. Loup pers. comm.). Despite this, it seems prudential to designate the specimen G00440097 as neotype of the name Armeria leucocephala. This specimen corresponds to the protologue and to the application of this name in this study.
= Armeria leucocephala subsp. pubescens (Salis) Arrigoni, Webbia 25: 160. 1970 ≡ Statice armeria var. pubescens Salis, Flora 17(2): 13. 1834.
Type (neotype designated here): FRANCE. Corsica: Monts di Cagna, pentes de Fontanella, Juin 1917, P. Cousturier 2515 (P05063114 photo! https://science.mnhn.fr/institution/mnhn/collection/p/item/p05063114 (accessed on 31 December 2022)); isotypes: (P05093398 photo!; MPU1065617 photo!)
Note: Salis-Marschlins [58] described Statice armeria var. pubescens providing a Latin diagnosis and the following provenance in “Monte Cagna supra Portovecchio. 4000’ s. m.” No original material was found. Therefore, a neotype was designated with a specimen concurring with the diagnosis and coming from the type locally. This specimen agrees with the protologue and the data presented in this study and definitely allows us to consider this name as a heterotypic synonym of A. leucocephala.
= Armeria multiceps Wallr., Beitr. Bot.: 196. 1842.
Type (lectotype designated here): FRANCE. Corsica: Mt. Rotondo, 1828. Soleirol 3555 (P05386918 photo!, http://mediaphoto.mnhn.fr/media/1441385834889C0cZ4gyBPy7VI0iR (accessed on 31 December 2022)).
Note: In the protologue, Wallroth [59], reported “Armeria montana Soleir. In herb. amic. Lucae” and “Auf dem monte d’oro in Corsica (Eschenlohr.)”. We traced at P a specimen (barcode P05386918) bearing five plants and three labels, i.e., “3555/Statice montana/Corse/Soleirol 1828”, “Soleirol, herb. Cors./3555. Statice montana/Mont. Rotondo”, and “HERB. MUS. PARIS/Armeria multiceps Wallr.”. Both the collector (Soleirol) and the locality of the collection (“Corse” and “Mont. Rotondo”) match Wallroth’s protologue. The specimen collection date (1828) predates the protologue. This specimen is part of the original material for A. multiceps, and it is here designated as the lectotype. The lectotype agrees with protologue and the data presented in this study and definitively allowed us to consider this name as a heterotypic synonym of A. leucocephala.
= Armeria leucocephala subsp. breviaristata Arrigoni, Webbia 25: 159. 1970.
Type (holotype): FRANCE. Corsica: Monte Stello, rochers élevés, 1881, Chabert (FI!)
= A. multiceps Wallr. subsp. meridionalis Arrigoni, Webbia 25(1): 152 (1970)
Type (holotype): FRANCE. Corsica: Coldi Bavella: pascoli alberati a Sud con Pinus laricio m 1300–1450, substrato granitico, 1969, P.V. Arrigoni (FI!).
Other specimens seen: FRANCE, Corsica: Vette di M. d’Oro, 24 July 1907, U. Martelli (FI!)*; Massif du Monte Corvo, au S du Bocca di San Giuvanni (Col de Saint-lean) (Corse, dép. Haute-Corse, crête du Cap Corse à hauteur d’Ogliastro et de Sisco), alt. env. 980 m, rochers schisteux de la crête, avec Anthyllis hermanniae, Hypochaeris robertia, Galium corsicum, 4 June 1997, J. Lambinon & G. Van Den Sande (FI!); montis Cinto, Calacuccia 2000–2200 m, 15 July 1880, E. Levier (FI!); Localité Haute vallèe d’Asco riva gauche Cima della Statoja, roches des aretes silice 2200 m, 26 July 1906, Voyage botanique en corse de E. Burnat, J. Briquet, A. Saint-Yves, F. Cavillier et E. Abrezol (FI!); Capo Aggiorio près Evisa 1200 m, 31 May 1906; Voyage botanique en corse de E. Burnat, J. Briquet, A. Saint-Yves, F. Cavillier et E. Abrezol (FI!); s. loc., June 1849, July 1847, Requien (FI!); Corsica, July 1907, U. Martelli (FI!); Col di Bavella Isola Corsica 1200 m, 9 June 1914, F. Spencer (FI!); Rochers élevés, Monte Fosco au (unclear word) de S.ta Maria di Lota Corse, 12 July 1881, A. Chabert (FI!); Le Pigno, pic au-dessus de Farinola, 4 July 1866, P. Marbille (FI! two specimens); ibidem (PI!, three specimens); Corsica, 1881, Groves (FI!); Monte Renoso, July 1847, s. coll. (FI!); Corse Coscione, s.d., Jordan (FI!); Monte Coscione (Corsica), September 1933, G. Massucci (FI!); M.te Rotondo, in pascuis subalpinis inter ovilia “Del Timozzo” a Caccun (?) d’Argentis 18–1900 m, 11 July 1880, E. Levier (FI!); Vallum mayen de L’anghione prés de Vizzavona rochers silice 1300 m, 21 July 1906, Voyage botanique en corse de E. Burnat, J. Briquet, A. Saint-Yves, F. Cavillier et E. Abrezol (FI!); Paturages de la région alpine Mt. Rotondo Corse, 16 September 1880, A. Chabert (FI)!; lungo i torrenti nella foresta di Vizzavona, 7 July 1907, U. Martelli (FI!); M.te Rotondo, in rupestribus subalpinis iter vallis Restonica et ovilia “del Timozzo”, 11 July 1880, E. Levier (FI!); M.te Rotondo, in saxosis alpinis ad radices montis Muffrone supra lacum d’Argentu (?), 8 July 1880; E. Levier (FI!); Monte d’Oro versant W. panton rocheuses silice 2200, 11 Jun 1904, F. Cavallier (FI!)*; Corsica Vette del M.te d’Oro, 24 July 1907, U. Martelli (FI!); M.te d’Oro, 24 July 1907, U. Martelli (FI!)*; Vette di Monte Rotondo, July 1907, U. Martelli (FI!); Corsica Monte Rotondo, 30 July 1907, U. Martelli (FI!); Corsica Monte Rotondo, 30 July 1907, U. Martelli (FI!); Mont Incudine Graviers silice 1750–2130m, 18 July 1906, Voyage botanique en corse de E. Burnat, J. Briquet, A. Saint-Yves, F. Cavillier et E. Abrezol (FI!); Rupi alle vette del M.te d’Oro, July 1907, U. Martelli (FI!)*; Corsica, July 1907, U. Martelli (FI!); M.te rotondo, […] in rupestribus alpinis montis Muffrone supra lacum d’Argentu 2000m, 8 July 1880, E. Levier (FI!); M.te rotondo, in clivis saxosis supra lacum d’Argentu 2000m, 8 July 1880, E. Levier (FI!); Sommet du Rotondo, 2500 m, 2 August 1866, P. Mabille (FI!); Sommet du Rotondo, 2500 m, 2 August 1866, P. Mabille (FI!); Rochers au vettes de Bétotre (?) montagne de la Cagna (Corse), 10 June 1890, Hefacci (FI!)*; Gajou de rochers du la région alpine M. Rotondo Corse, 16 September 1880, A. Chabert (FI!); Bastélica Mont Renoso, 24 June 1878, Reverchon (FI!).
Armeria morisii Boiss. in DC., Prodr. 12: 687. 1848.
Type (lectotype designated here):—ITALY. Sardinia, s.d., Moris s.n. (G00440188 photo!, http://www.ville-ge.ch/musinfo/bd/cjb/chg/adetail.php?id=300301&lang=en (accessed on 31 December 2022)).
Note: In the protologue, Boissier [60] provided a detailed description of the provenance and collector, adding “v.s.” [vidi specimen] and cited “Armeria latifolia Moris fl. sard. elench. fasc. 3, p. 10 non W. [Willdenow]” referring to Stirpium sardoarum elenchus by Moris (1827), where the author listed Willdenow’s A. latifolia and the locality “inter rupes calcareas Oliena”. In addition, Boissier [60] reported in synonymy “Statice cephalotes Bertol. fl. ital. v. 3, p. 511, quoad pl. sardoum” (see Bertoloni 1837, “ex rupibus d’Oliena in Sardinia ab Eq. Prof. Morisio”). At G, there is a specimen (barcode G00440188) bearing parts of the same plant and seven labels, of which one reports Moris’s annotation “Armeria latifolia Willd./Sardinia/Moris” and another one states “Armeria morisii! Boiss”. This specimen reports both Moris and Boissier handwritings and is clearly original material, here designated as the lectoype. It matches the original description and corresponds to the data and application of this name in this study.
Armeria sardoa Spreng., Syst. Veg., ed. 16, 4(2): 127. 1827.
Type (neotype here designated): ITALY, Sardinia: Massif du Gennargentu, Monte Spada (Sardaigne, prov. Nuoro, extrémité nord du massif du Gennargentu), alt. 1240–1280 m, pentes granitiques à exposition ouest, lande herbeuse à Genista corsica, Carlina macrocephala, Cerastium boissierianum, 8 June 1981, J. Lambinon 81/176 & J. Rousselle (L2643496 Photo!; https://medialib.naturalis.nl/file/id/L.2643496/format/large (accessed on 31 December 2022)); isotype: (BR0000027279212V Photo!).
Note: Sprengel [61] described this species as an addition to those already listed in volume 1 of Sprengel’s Systema vegetabilium [62]. He provided a short diagnosis (“16. A. [Armeria] foliis filiformibus canaliculatis scapoque glabris, foliolis involucri obtusis”) and the two generic localities of Sardinia and Corsica. Plumbaginaceae of Sprengel’s herbarium were housed in B, but a large part of it was destroyed during the Second World War [56,63]. No original material was found in the main European herbaria consulted; therefore, a neotype was selected. This specimen corresponds to the protologue and to the data and application of this name in this study.
= Armeria sardoa subsp. genargentea Arrigoni, Webbia 25(1): 166. 1970.
Type (holotype): ITALY. Sardinia: da Bruncu Spina a P. Paolina e dintorni del Rifugio Lamarmora, 6 July 1969, Arrigoni s.n. (FI!).
Armeria soleirolii (Duby) Godr. in Gren. & Godr., Fl. France 2: 737. 1853. ≡ Statice soleirolii Duby in DC., Bot. Gall. 2: 1032. 1830.
Type (lectotype here designated):—CORSICA: 3559 Statice littoralis? Calvi, Soleirol dedit 1828 (MPU021638 photo!).
Note: Statice soleirolii was published in Candolle’s Botanicon Gallicum (1830: 1032) [64] on the basis of an unpublished manuscript by Duby, as reported in the protologue before the diagnosis: “S. soleirolii (Dub. mss. [manuscript])”; provenance and collector were provided (“Ad rupes maritimas Corsicae circa Calvi (cl. Soleirol)”). We found four specimens in MPU and one in P collected in Calvi: P00326603, including the printed label “Soleirol, herb. cors., Statice Soleirolii Duby Bot. gall t. 2. p. 1032, H. prope Calvi.–Soleirol”; MPU021636 has the same label; MPU021637 bears the handwritten label “Armeria Soleirollii nob., Statice Soleirollii Duby bot. gall. suppl. p. 1032!, Mi Requien 1843, Corse Calvi juin 1822”; MPU021639 bears the handwritten label “3559 Statice fasciculata De Calvi, Corse, Soleirol” and MPU021638 bears the handwritten label “3559 Statice littoralis? Calvi, Soleirol dedit 1828”. The specimens P0032603, MPU021636 and MPU021639 lack the collection date. The specimen MPU021637 was collected before the publication of the name but did not include the name of the collector. Thus, we selected as lectotype the specimen MPU021638 because it is the only one including both the collection date and collector. It fits the original description and corresponds to the data and the application of this name in this study.
Other specimens seen: FRANCE, Corsica: Galeria (Corse, côte occidentale), rochers granitiques en bord de mer, a l’ouest du village, alt. env. 20–30 m, 3 June 1981, J. Lambinon & J. Rousselle (FI!)*; Corsica NW Isola Gargalu, 6 August 1975, B. lanza & M. Borri (FI!); Corsica NW Scoglio di Capo Mursetta, 5 August 1975, B. lanza (FI!); Corsica NW–Golfo di Girolata Scoglio di Soleiroil, 6 August 1975, B. lanza & M. Borri (FI!); Corsica–Calvi penisola de La Revellata rupi costiere granitiche, 3 June 1968, P.V. Arrigoni & C. Ricceri (FI!)*; Corsica–Calvi penisola de La Revellata rupi costiere granitiche, 3 June 1968, P.V. Arrigoni & C. Ricceri (FI!)*; Corsica–Calvi penisola de La Revellata rupi costiere granitiche, 8 September 1987, P.V. Arrigoni, B. Corrias, S. Diana (FI!)*; Corse: Rochers maritimes à Calvi (1), 28–29 June 1937, J. Chevalier (FI!); Corsica–da Calvi a Porto Torre di Galeria, 9 September 1987, P.V. Arrigoni, B. Corrias, S. Diana (FI!); Corsica –Calvi Costa rocciosa in Loc. Portu Vecchiu Esp. SW, 20 September 1990, P.V. Arrigoni, P.L. Di Tommaso, S. Diana (FI!).
Armeria sulcitana Arrigoni, Webbia 25(1): 169. 1970.
Type (holotype): ITALY. Sardinia: Com. Pula, Monte Santo, rocce di Punta sa Crescia, 3 July 1969, P.V. Arrigoni s.n. (FI!).

4.1. Identification Key to Armeria in Sardinia and Corsica

Before starting the identification, refer to the supplementary material published by Tiburtini et al. [33], where calyx and leaf apex characters are graphically exemplified. We also recommend taking several measures and computing the mean values of the mentioned characters. The key was built using herbarium material. Descriptive statistics and contingency tables for the newly circumscribed taxa are provided in Tables S10 and S11.
1.
Interfloral bracts absent; involucral bracts leathery and ferruginous; calyx showing a long spur (>1 mm) at the base; plants of sand dunes …………………………. A. pungens
1.
Interfloral bracts present; involucral bracts not leathery and light brown; calyx with indistinct spur; plants not from sand dunes ………………………………………………… 2
2.
Leaves stiff and canaliculate with evidently papillate epidermal cells (Figure S6); flowers pink; width of the inner involucral bract 3.8 ± 0.5 mm …………… A. soleirolii
2.
Leaves smooth, without evidently papillate epidermal cells; flowers pink or white; inner involucral bract 2.4 ± 0.9 mm ………………………………………………………… 3
3.
Summer leaves oblong-lanceolate, 5 ± 1.31 mm wide, flat; flowers pink; intermediate involucral bract 10.1 ± 1.3 mm long……………………………………………. A. morisii
3.
Summer leaves linear, <2.5 mm wide, flat or canaliculate; flower pink or white; intermediate involucral bract <8 mm long…………………………………………………… 4
4.
Outer spikelet bracteole 5.0 ± 0.9 mm long; limb 2.38 ± 0.40 mm; inner spikelet bract 6.6 ± 1.2 mm long; leaves homomorphic.…………………………………… A. leucocephala
4.
Outer spikelet bracteole 4.2 ± 0.7 mm long; limb 2 ± 0.56 mm; inner spikelet bract 5.7 ± 0.9 mm long; leaves mostly dimorphic…………………………………………………… 5
5.
Leaf margin smooth (microscope!); inner involucral bract 3.1 ± 0.7 mm wide; calyx awn 0.8 ± 0.2 mm long; calyx pleurotrichous ………………………………… A. sulcitana
5.
Leaf margin smooth or dentate (microscope!); inner involucral bract 1.8 ± 0.5 mm wide; calyx awn 0.4 ± 0.2 mm long; calyx holotrichous or pleurotrichous …………………………………………………………………………………………… A. sardoa

5. Materials and Methods

5.1. Sampling

We selected 15 populations (Table 1) across Sardinia and Corsica. The populations studied were selected based on three criteria: (1) to include all the type localities of the taxa considered in this study (BS, CB, MCA, ML, MO, MR, MS, RE, SP, and TH—acronyms as in Table 1); (2) to include other populations explicitly cited by Arrigoni [27]: AR, BU, GO, and BI; (3) to include other populations for those taxa showing a distribution range relatively larger than others (FO).
In total, we studied 197 herbarium specimens stored either in FI or in PI. Digitized specimens stored in the Herbarium Horti Botanici Pisani (PI) are freely available for consultation at http://erbario.unipi.it/ (codes in Table 1), whereas herbarium specimens stored in FI are listed in the specimina visa and marked with an asterisk (*). Concerning molecular systematics, dried leaves were collected from a subset of three individuals for each population and put in a paper bag with silica gel. Unfortunately, specimens from the BI population were unavailable for the morphometric analysis and were used only for the phylogenetic reconstruction. Ripen fruits were also collected from the same populations. The seeds were dried, cleaned, selected, and stored at −25 °C in the Sardinian Germplasm Bank (BG-SAR), Cagliari, Italy.
Table
Table 1. Taxa and populations of Armeria taxa endemic to Sardinia and Corsica sampled in this study, according to the currently accepted taxonomic hypothesis [24]. * = type locality; (n) = specimens used for plant morphometry.
Table 1. Taxa and populations of Armeria taxa endemic to Sardinia and Corsica sampled in this study, according to the currently accepted taxonomic hypothesis [24]. * = type locality; (n) = specimens used for plant morphometry.
Current Taxonomic HypothesisCodePopulationVoucher(n)
A. leucocephala Salzm. ex W.D.J.Koch subsp. breviaristata ArrigoniMS *France, Corsica, Monte Stello (Brando) [WGS84: 42.7890 N, 9.418194 E], 1290 mG. Bacchetta, S. Cambria, 23 June 2021 (PI 062283–062288)6
A. leucocephala subsp. leucocephalaMR *France, Corsica, Monte Renoso (Ghisoni) [WGS84: 42.074306 N, 9.148889 E], 1724 mG. Bacchetta, S. Cambria, 23 July 2021 (PI 062281–062282); FI5
A. leucocephala subsp. pubescens (Salis) ArrigoniMCA *France, Corsica, Monte Cagna (Sotta) [WGS84: 41.597000 N, 9.130611 E], 1061 mG. Bacchetta, S. Cambria, 20 July 2021 (PI 062289–062292); FI5
A. leucocephala subsp. pubescens (Salis) ArrigoniBIFrance, Corsica, Bocca Illarata (Zonza) [WGS84 41.702861 N, 9.210111 E], 967 mG. Bacchetta, S. Cambria, 21 July 2021 (CAG 64/21)0
A. morisii Boiss.TH *Italy, Sardinia, Monte Corrasi–Thutturreli (Oliena) [WGS84: 40.249189 N, 9.426167 E], 1200–1240 mG. Bacchetta, S. Cambria, P. De Giorgi, A. Giacò, 17 June 2020 (PI 062293–062302)10
A. multiceps Wallr. subsp. meridionalis ArrigoniCB *France, Corsica, Col di Bavella (Quenza) [WGS84: 41.798111 N, 9.218611 E], 1367 mG. Bacchetta, S. Cambria, 22 July 2021 (PI 062424–062429!)6
A. multiceps subsp. multicepsMO *France, Corsica, Monte d’Oro (Vivario) [WGS84: 42.121250 N, 9.107167 E], 1255 mG. Bacchetta, S. Cambria, 22 July 2021 (PI 062275–062280!); FI9
A. sardoa Spreng. subsp. genargentea ArrigoniBS *Italy, Sardinia, Bruncu Spina (Fonni) [WGS84: 40.014564 N, 9.189225 E], 1810–1825 mG. Bacchetta, S. Cambria, P. De Giorgi, A. Giacò, 16 June 2020 (PI 062436–062450)15
A. sardoa subsp. genargenteaFOItaly, Sardinia, Monte Spada (Fonni) [WGS84: 40.058586 N, 9.291667 E], 1330–1370 mG. Bacchetta, S. Cambria; 27 June 2021 (PI 062303–062322)20
A. sardoa subsp. sardoaML *Italy, Sardinia, Monte Limbara (Berchidda) [WGS84: 40.852222 N, 9.183611 E], 1300–1330 mG. Calvia, 13 June 2021 (PI 062404–062423)20
A. sardoa subsp. sardoaBUItaly, Sardinia, Badde Urbara (Santu Lussurgiu) [WGS84: 40.157342 N, 8.626297 E], 940–950 mG. Bacchetta, S. Cambria, P. De Giorgi, A. Giacò, 18 June 2020 (PI 062323–062342)20
A. sardoa subsp. sardoaARItaly, Sardinia, Valico Sa Casa (Aritzo) [WGS84: 44.401250 N, 9.994250 E], 970–980 mG. Bacchetta, S. Cambria, P. De Giorgi, A. Giacò; 15 June 2020 (PI 062344–062363)20
A. soleirolii (Duby) Godr.RE *France, Corsica, La Revellata (Calvì) [WGS84: 42.581111 N, 8.720000 E], 50 mG. Bacchetta, S. Cambria, 22 July 2021 (PI 062430–062435); FI!15
A. sulcitana ArrigoniSP *Italy, Sardegna, Monte Santo (Pula) [WGS84: 39.028983 N, 8.908394 E]G. Bacchetta, 30 May 2021 (PI 062384–062403)20
A. sulcitanaGOItaly, Sardinia, Genn’e Spina (Gonnosfanadiga) [WGS84: 39.445444 N, 8.657167 E]M. Porceddu, M. Sarigu, 3 June 2021 (PI 062516–062535)20

5.2. Karyological Data

We followed the protocol described by Tiburtini et al. [39] to obtain metaphasic plates. Seeds germinated easily in Petri dishes with agar-agar at 1%, without any pretreatment, in 4–6(8) days. Chromosomes were observed with a Leitz Diaplan microscope, and pictures were taken with a Leica MC-170HD camera through Leica LAS-EZ 3.0 imaging software. From all the pictures taken, at least four metaphase plates for each population were selected and measured. Chromosome number and karyological parameters such as THL (Total Haploid Length), MCA (Mean Centromeric Asymmetry), CVCL (Coefficient of Variation of the Chromosome Length), and CVCI (Coefficient of Variation of the Centromeric Index) were obtained from each plate with MATO 1.1 (version 20210101) [65]. All the statistical analyses, excluding the molecular systematics, were conducted in RStudio IDE [66]. Data were managed using the tidyverse package (version 2.0.0) [67], and pairwise permutation tests from the rcompanion package(version 2.4.26) [68] were used to test statistical significance reporting only p-values corrected with Benjamini–Hochberg procedure [69] (BH step-up procedure) to control the False Discovery Rate (FDR) at level = 0.01.

5.3. DNA Extraction and Molecular Systematics

We followed the protocol described by Tiburtini et al. [33] for DNA extraction, primer selection for internal transcribed spacers (ITS1 + 5.8S + ITS2) and four chloroplast intergenic spacers (trnF–trnL, trnH–psbA, trnL–rpl32, trnQ–rps16), their amplification, sequencing, and data analysis. ITS sequences and chloroplast intergenic spacers were submitted to DDBJ (ITS: LC757034-LC757084; trnF–trnL: LC757325-LC757375; psbA–trnH: LC757085-LC757135; trnL–rpl32: LC757226-LC757273; trnQ–rps16: LC757274-LC757324). Sequences were visually inspected and aligned using the ClustalW algorithm Sequences were visually inspected and aligned using the ClustalW algorithm [70] implemented in BioEdit (version 7.2.5) [71] with the default values. An incongruence length difference (ILD) test was carried out in Nona (version 2.0) [72] as a daughter process of Winclada (version 1.00.08) [73] to test the putative incongruence of nuclear and chloroplast partitions prior to combination; default values were used for the analysis. A nucleotide evolution model was calculated for each of the five sequenced regions using jModelTest (version 2.1.10) [74], and the best-fitting model was chosen over the others using the Bayesian Information Criterion (BIC) [75]. Bayesian phylogenetic trees for concatenated and nuclear markers were inferred in MrBayes (version 3.2.6) [76] in two simultaneous, independent runs with the following settings: 2,000,000 generations of MCMC sampling every 2000 generations and four runs (three cold and one hot). For the cpDNA, convergence was reached in 3,000,000 generations sampled every 3000 generations. Convergence and mixing were evaluated in Tracer (version 1.7.2) [77]. The consensus Bayesian tree was visualized in FigTree (version 1.4.2) [78] as implemented in BioEdit (version 7.2.5) with the default values. The best evolution models were JC for ITS and F81 for chloroplast markers, except for trnL-rpl32, which was F81+G. We were unable to amplify this plastidial marker from A. soleirolii. The tree was rooted using A. pungens (BM: Italy, Sardinia, Badesi Mare, (Badesi) [WGS84 41.127786 N, 9.085444E], 4 m, G. Calvia, 27 May 2021, PI 062536-062555; PL: Italy, Sardinia, Lu Riu de li Saldi, (Aglienu) [WGS84 41.127786 N, 9.085444E], 1 m, G. Calvia, 27 May 2021, PI 062364–062383).

5.4. Seed Morphometric Analysis

Seeds were selected and prepared for image analysis. The seeds were dried at the Sardinian Germplasm Bank (BG-SAR) of Cagliari (Italy) based on established international protocols down to 3–5% of internal moisture content, which guarantees homogeneity and regularity in seed size and weight and allows an effective long-term conservation [79]. Digital images of 100 seeds for each accession were acquired using a flatbed scanner (Epson Perfection V550 photo) with a digital resolution of 1200 dpi. When an accession had fewer than 100 seeds, the analysis was carried out on the whole batch available. Seeds were randomly placed on the scanner tray so that they did not touch one another: each accession was scanned using a light blue background to avoid interference from environmental light. Images were processed using the software package ImageJ v. 1.53v [(http://rsb.info.nih.gov/ij) (accessed on 28 December 2022)], and the plugin Particles8, freely downloadable on the official website [(https://blog.bham.ac.uk/intellimic/g-landini-software/) (accessed on 28 December 2022)], was used to measure 26 morphometric features (Table S4). The raw final matrix was 1445 × 26 variables. We explored, visualized, and preprocessed the data through centering and scaling using the tidyverse package [67]. We build a Random Forest model using the caret package (version 6.0-93) [80] with 750 trees with a depth of 3. To both maximize model performance and reduce the effect of correlation, we tuned the hyperparameter mtry for 1 to 20. The dataset was split at each iteration in 75% training and 25% testing, and within the training set, we cross-validated the training data using the LGOCV method with 10 individuals left out at each iteration and applied it to the testing data. We selected the model that maximized ROC-AUC values instead of accuracy as a model performance metric to avoid the accuracy paradox. From the tuned model (mtry = 15), we extracted the most important morpho-colorimetric variables and the confusion matrix. Finally, we applied HDBSCAN* (Hierarchical Density-Based Spatial Clustering of Applications with Noise) [81,82], an unsupervised clustering algorithm. Classical clustering techniques such as K-mean are limited by the fact that (1) the number of clusters must be known a priori, (2) each point, even outliers, must belong to a cluster, and lastly (3) they assume some known probability density function (PDF) that may have generated the observed data. HDBSCAN* is a non-parametric, density-based clustering algorithm that resolves these problems and can be used both as a nonhierarchical and hierarchical clustering algorithm. The Manhattan distance was computed from the standardized matrix and used as input to HDBSCAN* from the dbscan package (version 1.1-11) [83]. The sole hyperparameter of the model, minPoints, was tuned by fitting 49 models with minPoints ranging from 2 to 50 and selecting the model that had the least number of dimensions (26) plus one [83,84] and minimized both the number of clusters and the points considered as noise points. We picked the value of 30 minPoints as the best model. After testing for suitability to factor analysis with the KMO test, PCoA from ape package (version 5.6-2) [85] corrected with Cailliez correction [86] based on the same distance matrix was used to visualize both the nonhierarchical clustering and the membership probability calculated from the estimated PDF.

5.5. Plant Morphometric Analysis

In total, 49 qualitative and quantitative morphological characters (Table 2) were studied, with a resulting dataset of 192 individuals × 49 variables. Macroscopic measures were taken with a digital caliper (error ± 0.1 mm) under a Leica A60 stereomicroscope, while microscopic measurements were taken through bar-scaled pictures in Fiji 2.1.0 [87]. To have a more objective way to count the number of leaf veins, free-handed transversal sections of leaves were carried out. We considered as a “vein,” each fascicule composed of xylem and phloem surrounded by sclerenchyma. The anatomy of summer leaves was surveyed under a Leitz Diaplan light microscope at 40×.
We used the tidyverse package [67] for data exploration, preparation and description, while we used the nearZeroVar function from the caret [88] package (version 6.0-93) for preprocessing, removing zero and near-zero variance variables. We tested the suitability of the data for factor analysis with the Kaiser–Meyer–Olkin test (MSA = 0.89, psych (version 2.2.9) [89] and Bartlett sphericity test (p < 0.001, REdaS package (version 0.9.4) [90]. Both were performed successfully on the numeric correlate matrix. PCoA (Principal Coordinate Analysis) was performed using the pcoa function in the FD package (1.0-12.1) [91], while the Cailliez correction [86] was applied due to the violation of the triangle inequality (i.e., the matrix was not Euclidean). Lastly, 95% confidence ellipses were calculated assuming a t-distribution of individuals in a morphometric space using the function stat_ellipse of ggplot2 package (version 3.4.2) at the species level for the Canonical Variable Analysis (CVA) [67,92]. Categorical data were binary encoded using the encode_binary function from the cleandata package (version 0.3.0) [93]. To test the alternative taxonomic hypotheses, we applied the kNN algorithm from the caret package (version 6.0-93) [88]. We decided to use kNN, a non-parametric, powerful [94] supervised machine learning model, because, for some populations, a low number of individuals was available. The model was tuned using the caret package for the sole hyperparameter k applying LOOCV for a range of k values from 1 to 20 (i.e., the maximum number of individuals per population) and retaining the model that maximizes the multiclass, cross-validated, balanced accuracy value. We followed the separating or merging scheme proposed by Xiong et al. [95] in case of overlapping regions in the morphospace between classes (i.e., a priori groups to be tested) or propose new alternative hypotheses. Each character was statistically tested, comparing each species. For all the quantitative characters, a pairwise permutation test was applied (10,000 permutations for each test), while for qualitative variables, Fisher’s Exact test was used. Both functions derive from the rcompanion package (version 2.4.26) [68]. We used the Benjamini & Yekutieli [96] procedure to control the family-wise error rate due to multiple testing setting the α at 0.01. We obtained a 10 × 10 matrix containing the number of characters showing statistically significant differences for each pair of taxa. Based on this matrix, we created a heatmap from the plotly package (version 2.4.26) [97]. To build the identification key, we used the combination of the most representative decision tree from the Random Forest tuned model (mtry = 5.64, 1000 trees) extracted using the ReprTree function of the reprtree package (version 0.6) [98] and the comparisons of the effect size of each character through Cohen’s D and mosaic plots for qualitative variables. We selected those characters that maximized the pairwise Cohen’s D values given the species or group species pairs.

5.6. Nomenclature

Information about currently accepted names, basionyms, and homotypic synonyms was obtained from the Euro+Med-Checklist [99] and Peruzzi et al. [100]. Information about the herbaria in which the original material of these names could be stored was derived from Stafleu and Cowan [56]. Accordingly, we digitally examined the following herbaria: BR, COI, G, K, L, MPU, and P (herbarium acronyms follow Thiers [101] in search of potential original material. This allowed us to typify the names A. leucocephala, A. morisii, A. multiceps, A. sardoa, Statice armeria var. pubescens, and Statice soleirolii.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/plants12112229/s1, Table S1, Mean and standard deviation of the karyological parameters in Armeria taxa endemic to Sardinia and Corsica; Table S2, Results of IDL tests for all the molecular markers used in the study of Armeria taxa endemic to Sardinia and Corsica; Table S3, Mean Decrease Accuracy of Random Forest for each of the 26 seed morphological variables of Armeria taxa endemic to Sardinia and Corsica considered in the model; Table S4, List of the 26 seed morphometric features measured in Armeria taxa endemic to Sardinia and Corsica; Table S5, Descriptive statistics of the five most important seed morphometric features in Armeria taxa endemic to Sardinia and Corsica, found by Random Forest; Table S6, Confusion matrix from the tuned Random Forest model on the current taxonomic hypothesis for the seed morphometric data in Armeria taxa endemic to Sardinia and Corsica; Table S7, Confusion matrix for Armeria taxa endemic to Sardinia and Corsica, based on the current taxonomic hypothesis; Table S8, Confusion matrix of the morphometric data in Armeria taxa endemic to Sardinia and Corsica, according to the tuned kNN model under the alternative taxonomic hypothesis 1 (6 species, no subspecies); Table S9, Confusion matrix of the morphometric data in Armeria taxa endemic to Sardinia and Corsica, according to the tuned kNN model under the alternative taxonomic hypothesis 2 (five species, no subspecies); Table S10, Descriptive statistics for the continuous characters according to the new taxonomic circumscription of Armeria taxa endemic to Sardinia and Corsica; Table S11, Contingency tables of most significant categorical characters used in the identification key to Armeria taxa endemic to Sardinia and Corsica. Significance according to Fisher’s exact test. Figure S1, Haploid idiograms of the 15 populations of Armeria taxa endemic to Sardinia and Corsica considered in this study; Figure S2, Phylogenetic trees of Armeria taxa endemic to Sardinia and Corsica, based on the plastidial markers; Figure S3, PCoA based on the Manhattan distance of the 26 seed morphometric features in Armeria taxa endemic to Sardinia and Corsica, colored based on the results of HDBSCAN* clustering algorithm; Figure S4, Canonical Variate Analysis of the morphometric dataset of Armeria taxa endemic to Sardinia and Corsica, composed by numeric variables grouped based on the new taxonomic circumscription; Figure S5. PCoA illustrating the morphometric variation of the first and third axes in Armeria taxa endemic to Sardinia and Corsica, based on the Gower distance of the 49 characters measured; Figure S6. Leaf surface of Armeria soleirolii and its papillate epidermal cells.

Author Contributions

Conceptualization, L.P.; methodology, M.T., L.P., G.B. and P.C.; validation, L.P.; formal analysis, M.T. and D.D.L.; investigation, G.B. (field sampling), S.C. (field sampling and measurements), A.T. (karyological analysis), M.T. (karyological analysis and measurements), M.S., G.B. (seed morphometry), D.D.L. (molecular systematics), P.C. (molecular systematics), G.D. (nomenclature); data curation, M.T. and D.D.L.; writing—original draft preparation, M.T.; writing—review and editing, L.P.; visualization, M.T. and D.D.L.; supervision, L.P.; funding acquisition, L.P. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Progetto di Ricerca di Rilevante Interesse Nazionale” (PRIN) “PLAN.T.S–2.0—towards a renaissance of PLANt Taxonomy and Systematics” led by the University of Pisa, grant number 2017JW4HZK (Principal Investigator: Lorenzo Peruzzi).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

R Scripts used to perform the data analyses are available on GitHub: https://github.com/Bendlexane/data-analyses-in-R/tree/main/Tiburtini%20et%20al.%2C%202023.

Acknowledgments

We thank Giacomo Calvia, Paola De Giorgi, Antonio Giacò, and Marco Porceddu for their help with sampling activities. We thank Caroline Loup (MPU), and other curators of the herbaria consulted for their help with searching for the original material. We thank Lorenzo Lastrucci, Chiara Nepi, and Anna Donatelli for help in consulting the specimens stored in FI.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Darwin, C. On the Origin of Species by Means of Natural Selection, or the Preservation of Favoured Races in the Struggle for Life, 1st ed.; Routledge: London, UK, 1859. [Google Scholar]
  2. Wallace, A.R. Island Life or the Phenomena and Causes of Insular Faunas and Floras, Including a Revision and Attempted Solution of the Problem of Geological Climates; Macmillan: London, UK, 1880. [Google Scholar]
  3. MacArthur, R.H.; Wilson, E.O. The Theory of Island Biogeography; Princeton University Press: Princeton, NJ, USA, 1967. [Google Scholar]
  4. Whittaker, R.J.; Fernández-Palacios, J.M.; Matthews, T.J.; Borregaard, M.K.; Triantis, K.A. Island Biogeography: Taking the Long View of Nature’s Laboratories. Science 2017, 357, eaam8326. [Google Scholar] [CrossRef] [Green Version]
  5. Wallace, A.R. The Geographical Distribution of Animals: With a Study of Living and Extinct Faunas as Elucidating the Past Changes of the Earth’s Surface, 1st ed.; Macmillan: London, UK, 1876. [Google Scholar]
  6. Whittaker, R.J. Island Biogeography: Ecology, Evolution, and Conservation; Island Biogeography: Ecology, Evolution, and Conservation; Oxford University Press: Oxford, UK, 1998. [Google Scholar]
  7. Thompson, J.D. Plant Evolution in the Mediterranean: Insights for Conservation, 2nd ed.; Oxford University Press, USA: New York, NY, USA, 2020. [Google Scholar]
  8. Comes, H.P.; Tribsch, A.; Bittkau, C. Plant Speciation in Continental Island Floras as Exemplified by Nigella in the Aegean Archipelago. Phil. Trans. R. Soc. B 2008, 363, 3083–3096. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  9. Stuessy, T.F.; Takayama, K.; López-Sepúlveda, P.; Crawford, D.J. Interpretation of Patterns of Genetic Variation in Endemic Plant Species of Oceanic Islands: Genetic Variation in Island Plants. Bot. J. Linn. Soc. 2014, 174, 276–288. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  10. Nogales, M.; Heleno, R.; Traveset, A.; Vargas, P. Evidence for Overlooked Mechanisms of Long-distance Seed Dispersal to and between Oceanic Islands. New Phytol. 2012, 194, 313–317. [Google Scholar] [CrossRef] [PubMed]
  11. Carmignani, L.; Conti, P.; Cornamusini, G.; Meccheri, M.; Crescenti, U. The Internal Northern Apennines, the Northern Tyrrhenian Sea and the Sardinia-Corsica Block. In Geology of Italy; Special Volume; Italian Geological Society, IGC: Rome, Italy, 2004; Volume 32, pp. 59–77. [Google Scholar]
  12. Oggiano, G.; Funedda, A.; Carmignani, L.; Pasci, S. The Sardinia-Corsica Microplate and Its Role in the Northern Apennine Geodynamics: New Insights from the Tertiary Intraplate Strike-Slip Tectonics of Sardinia. Ital. J. Geosci. 2009, 128, 527–539. [Google Scholar]
  13. Bacchetta, G.; Farris, E.; Pontecorvo, C. A New Method to Set Conservation Priorities in Biodiversity Hotspots. Plant Biosyst. 2012, 146, 638–648. [Google Scholar] [CrossRef]
  14. Fenu, G.; Fois, M.; Cañadas, E.M.; Bacchetta, G. Using Endemic-Plant Distribution, Geology and Geomorphology in Biogeography: The Case of Sardinia (Mediterranean Basin). Syst. Biodivers. 2014, 12, 181–193. [Google Scholar] [CrossRef]
  15. Cheikh Albassatneh, M.; Escudero, M.; Monnet, A.; Arroyo, J.; Bacchetta, G.; Bagnoli, F.; Dimopoulos, P.; Hampe, A.; Leriche, A.; Médail, F.; et al. Spatial Patterns of Genus-level Phylogenetic Endemism in the Tree Flora of Mediterranean Europe. Divers. Distrib. 2021, 27, 913–928. [Google Scholar] [CrossRef]
  16. Kier, G.; Kreft, H.; Lee, T.M.; Jetz, W.; Ibisch, P.L.; Nowicki, C.; Mutke, J.; Barthlott, W. A Global Assessment of Endemism and Species Richness across Island and Mainland Regions. Proc. Natl. Acad. Sci. USA 2009, 106, 9322–9327. [Google Scholar]
  17. Losos, J.B. Adaptive Radiation, Ecological Opportunity, and Evolutionary Determinism: American Society of Naturalists E. O. Wilson Award Address. Am. Nat. 2010, 175, 623–639. [Google Scholar] [CrossRef]
  18. Médail, F.; Verlaque, R. Ecological Characteristics and Rarity of Endemic Plants from Southeast France and Corsica: Implications for Biodiversity Conservation. Biol. Conserv. 1997, 80, 269–281. [Google Scholar] [CrossRef]
  19. Médail, F.; Quézel, P. Hot-Spots Analysis for Conservation of Plant Biodiversity in the Mediterranean Basin. Ann. Mo. Bot. Gard. 1997, 84, 112–127. [Google Scholar] [CrossRef]
  20. Bacchetta, G.; Pontecorvo, C. Contribution to the Knowledge of the Endemic Vascular Flora of Iglesiente (SW Sardinia-Italy). Candollea 2005, 60, 481–501. [Google Scholar]
  21. Fois, M.; Farris, E.; Calvia, G.; Campus, G.; Fenu, G.; Porceddu, M.; Bacchetta, G. The Endemic Vascular Flora of Sardinia: A Dynamic Checklist with an Overview of Biogeography and Conservation Status. Plants 2022, 11, 601. [Google Scholar] [CrossRef] [PubMed]
  22. POWO—Plants of the World Online. Facilitated by the Royal Botanic Gardens, Kew. Available online: http://www.plantsoftheworldonline.org/ (accessed on 15 November 2022).
  23. Piñeiro, R.; Aguilar, J.F.; Munt, D.D.; Feliner, G.N. Ecology Matters: Atlantic–Mediterranean Disjunction in the Sand-Dune Shrub Armeria pungens (Plumbaginaceae). Mol. Ecol. 2007, 16, 2155–2171. [Google Scholar] [CrossRef]
  24. Arrigoni, P.V. Contributo alla conoscenza delle Armerie Sardo-Corse. Webbia 1970, 25, 137–182. [Google Scholar] [CrossRef]
  25. Fuertes Aguilar, J.; Nieto Feliner, G. Additive Polymorphisms and Reticulation in an ITS Phylogeny of Thrifts (Armeria, Plumbaginaceae). Mol. Phylogenet. Evol. 2003, 28, 430–447. [Google Scholar] [CrossRef]
  26. Rabosky, D.L. Reproductive Isolation and the Causes of Speciation Rate Variation in Nature. Biol. J. Linn. Soc. 2016, 118, 13–25. [Google Scholar] [CrossRef] [Green Version]
  27. Arrigoni, P.V. Il Concetto Di Specie e La Crisi Della Tassonomia; Mucchi Editore: Modena, Italy, 1985. [Google Scholar]
  28. Schlick-Steiner, B.C.; Steiner, F.M.; Seifert, B.; Stauffer, C.; Christian, E.; Crozier, R.H. Integrative Taxonomy: A Multisource Approach to Exploring Biodiversity. Annu. Rev. Entomol. 2010, 55, 421–438. [Google Scholar] [CrossRef]
  29. Turrill, W.B. The Expansion of Taxonomy with Special Reference to Spermatophyta. Biol. Rev. 1938, 13, 342–373. [Google Scholar] [CrossRef]
  30. Lefèbvre, C.; Vekemans, X. A Numerical Taxonomic Study of Armeria maritima (Plumbaginaceae) in North America and Greenland. Can. J. Bot. 1995, 73, 1583–1595. [Google Scholar] [CrossRef]
  31. Blanco-Dios, J.B. Estudio morfométrico de una zona híbrida entre Armeria beirana y A. pubigera (Plumbaginaceae) en el noroeste de la Península Ibérica. An. Jard. Bot. Madr. 2007, 64, 7. [Google Scholar] [CrossRef]
  32. Nieto Feliner, G.; Aguilar, F.A.; Rosselló, J.A. A New Species of Armeria (Plumbaginaceae) from Southern Spain with Molecular and Morphometric Evidence on Its Origin. Bot. J. Linn. Soc. 2001, 135, 71–84. [Google Scholar]
  33. Tiburtini, M.; Astuti, G.; Bartolucci, F.; Casazza, G.; Varaldo, L.; De Luca, D.; Bottigliero, M.V.; Bacchetta, G.; Porceddu, M.; Domina, G.; et al. Integrative Taxonomy of Armeria arenaria (Plumbaginaceae), with a Special Focus on the Putative Subspecies Endemic to the Apennines. Biology 2022, 11, 1060. [Google Scholar] [CrossRef] [PubMed]
  34. Nieto Feliner, G. Natural and Experimental Hybridization in Armeria (Plumbaginaceae): Armeria salmantica. Int. J. Plant Sci. 1997, 158, 585–592. [Google Scholar] [CrossRef]
  35. Tauleigne-Gomes, C.; Lefèbvre, C. Natural Hybridisation between Two Coastal Endemic Species of Armeria (Plumbaginaceae) from Portugal. 1. Populational in Situ Investigations. Plant Syst. Evol. 2005, 250, 215–230. [Google Scholar] [CrossRef]
  36. Thiébaud, M.-A. Contribution à la connaissance de l’Armeria leucocephala Salzm. ex Koch en Corse; Contribution to the knowledge of Armeria leucocephala Salzm. ex Koch in Corsica. Candollea 1990, 45, 334–337. [Google Scholar]
  37. Bernis, F. Revisión del género Armeria Willd. con especial referencia a los grupos ibéricos. Anales Inst. Bot. Cavanilles 1954, 11, 5–287. [Google Scholar]
  38. Tison, J.-M.; de Foucault, B. Flora Gallica: Flore de France; Biotope: Mèze, France, 2014. [Google Scholar]
  39. Venable, D.L.; Dyreson, E.; Piñero, D.; Becerra, J.X. Seed Morphometrics and Adaptive Geographic Differentiation. Evolution 1998, 52, 344–354. [Google Scholar] [CrossRef]
  40. Larios, E.; Búrquez, A.; Becerra, J.X.; Lawrence Venable, D. Natural Selection on Seed Size through the Life Cycle of a Desert Annual Plant. Ecology 2014, 95, 3213–3220. [Google Scholar] [CrossRef] [Green Version]
  41. Tauleigne-Gomes, C.; Lefèbvre, C. Natural Hybridisation between Two Coastal Endemic Species of Armeria (Plumbaginaceae) from Portugal. 2. Ecological Investigations on a Hybrid Zone. Plant Syst. Evol. 2008, 273, 225–236. [Google Scholar] [CrossRef]
  42. Nieto Feliner, G.; Álvarez, I.; Fuertes-Aguilar, J.; Heuertz, M.; Marques, I.; Moharrek, F.; Piñeiro, R.; Riina, R.; Rosselló, J.A.; Soltis, P.S.; et al. Is Homoploid Hybrid Speciation That Rare? An Empiricist’s View. Heredity 2017, 118, 513–516. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Donadille, P. Etude caryologique du genre Armeria Willd. C. R. Acad. Sci. Paris 1967, 264, 813–815. [Google Scholar]
  44. Iversen, J. Blütenbiologische Studien. I. Dimorphie und Monomorphie bei Armeria. Details K. Dan. Vidensk. Selskab. Biol. Medd. 1940, 15, 1–39. [Google Scholar]
  45. Baker, H.G. Dimorphism and Monomorphism in the Plumbaginaceae: I. A Survey of the Family. Ann. Bot. 1948, 12, 207–219. [Google Scholar] [CrossRef]
  46. Costa, J.; Torices, R.; Barrett, S.C.H. Evolutionary History of the Buildup and Breakdown of the Heterostylous Syndrome in Plumbaginaceae. New Phytol. 2019, 224, 1278–1289. [Google Scholar] [CrossRef]
  47. Aguilar, J.F.; Rosselló, J.A.; Feliner, G.N. Molecular Evidence for the Compilospecies Model of Reticulate Evolution in Armeria (Plumbaginaceae). Syst. Biol. 1999, 48, 735–754. [Google Scholar] [CrossRef]
  48. Garcia, S.; Alegre, G.; Garnatje, T.; Kovařík, A.; Valle, S.; Nieto-Feliner, G. Consequences of Hybridization Processes in the Intergenic Spacer of Ribosomal DNA in Armeria (Plumbaginaceae). In Proceedings of the International Conference on Polyploidy, Hybridization and Biodiversity, Rovinj, Croatia, 11–14 May 2016. [Google Scholar]
  49. Nieto Feliner, G.; Izuzquiza, A.; Lansac, A.R. Natural and Experimental Hybridization in Armeria (Plumbaginaceae): A. villosa subsp. carratracensis. Plant Syst. Evol. 1996, 201, 163–177. [Google Scholar] [CrossRef]
  50. Nieto Feliner, G.; Fuertes, J.; Rosselló, J.A. Reticulation or Divergence: The Origin of a Rare Serpentine Endemic Assessed with Chloroplast, Nuclear and RAPD Markers. Plant Syst. Evol. 2002, 231, 19–38. [Google Scholar] [CrossRef]
  51. Degnan, J.H. Modeling Hybridization Under the Network Multispecies Coalescent. Syst. Biol. 2018, 67, 786–799. [Google Scholar] [CrossRef] [Green Version]
  52. De Giorgi, P.; Giacò, A.; Astuti, G.; Minuto, L.; Varaldo, L.; De Luca, D.; De Rosa, A.; Bacchetta, G.; Sarigu, M.; Peruzzi, L. An Integrated Taxonomic Approach Points towards a Single-Species Hypothesis for Santolina (Asteraceae) in Corsica and Sardinia. Biology 2022, 11, 356. [Google Scholar] [CrossRef] [PubMed]
  53. Joffard, N.; Buatois, B.; Arnal, V.; Véla, E.; Montgelard, C.; Schatz, B. Delimiting Species in the Taxonomically Challenging Orchid Section Pseudophrys: Bayesian Analyses of Genetic and Phenotypic Data. Front. Ecol. Evol. 2022, 10, 1058550. [Google Scholar] [CrossRef]
  54. Liu, L.; Astuti, G.; Coppi, A.; Peruzzi, L. Different Chromosome Numbers but Slight Morphological Differentiation and Genetic Admixture among Populations of the Pulmonaria hirta Complex (Boraginaceae). Taxon 2022, 71, 1025–1043. [Google Scholar] [CrossRef]
  55. Koch, W.D.J. Beobachtungen Über Die Gattung Armeria. Flora 1834, 17, 704–720. [Google Scholar]
  56. Stafleu, F.A.; Cowan, R.S. Taxonomic Literature: A Selective Guide to Botanical Publications and Collections with Dates, Commentaries and Types, 2nd ed.; Scheltema & Holkema: Bohn, Germany, 1976; Volume 1. [Google Scholar]
  57. HUH Index of Botanists. Available online: https://kiki.huh.harvard.edu/databases/botanist_search.php?mode=details&id=47839 (accessed on 4 April 2022).
  58. Salis-Marschlins, C.U. Von Aufzahlung Der in Korsica Und Zunachst Um Bastia von Mir Bemerkten Cotyledonarpflanzen. Flora 1834, 17, 1–86. [Google Scholar]
  59. Wallroth, C.F.W. Monographische Versuch Über Die Gewachs Gattung Armeria Willd. Beiträge Zur Botanik. In Beiträge zur Botanik: Eine Sammlung monographischer Abhandlungen über besonders schwierige Gewächs-Gattungen der Flora Deutschlands; Friedrich Hofmeister: Leipzig, Germany, 1842; Volume 1, pp. 168–218. [Google Scholar]
  60. Boissier, P.E. Armeria Willd. In Prodromus Systematis Naturalis Regni Vegetabilis; de Candolle, A.P., de Candolle, A., Eds.; Victoris Masson: Paris, France, 1848; Volume 12, pp. 674–689. [Google Scholar]
  61. Sprengel, K.P.J. Systema Vegetabilium, 16th ed.; Sumtibus Librariae Dietrichianae: Gottingae, Germany, 1827; Volume 4. [Google Scholar]
  62. Sprengel, K.P.J. Systema Vegetabilium, 16th ed.; Sumtibus Librariae Dietrichianae: Gottingae, Germany, 1827; Volume 1. [Google Scholar]
  63. Hiepko, P. The Collections of the Botanical Museum Berlin-Dahlem (B) and Their History. Englera 1987, 7, 219–252. [Google Scholar]
  64. De Candolle, A.P.; Duby, J.É. Botanicon Gallicum; Seu, Synopsis Plantarum in Flora Gallica Descriptarum, 2nd ed.; Desray: Paris, France, 1830; Volume 2. [Google Scholar]
  65. Altınordu, F.; Peruzzi, L.; Yu, Y.; He, X. A Tool for the Analysis of Chromosomes: KaryoType. Taxon 2016, 65, 586–592. [Google Scholar] [CrossRef]
  66. RStudio Team. RStudio: Integrated Development for R; RStudio Team: Boston, MA, USA, 2022. [Google Scholar]
  67. Wickham, H.; Averick, M.; Bryan, J.; Chang, W.; McGowan, L.; François, R.; Grolemund, G.; Hayes, A.; Henry, L.; Hester, J.; et al. Welcome to the Tidyverse. J. Open Source Softw. 2019, 4, 1686. [Google Scholar] [CrossRef] [Green Version]
  68. Mangiafico, S. rcompanion: Functions to Support Extension Education Program Evaluation; The Comprehensive R Archive Network: Vienna, Austria, 2016. [Google Scholar]
  69. Benjamini, Y.; Hochberg, Y. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. J. R. Stat. Soc. Series B Stat. Methodol. 1995, 57, 289–300. [Google Scholar] [CrossRef]
  70. Thompson, J.D.; Higgins, D.G.; Gibson, T.J. CLUSTAL W: Improving the Sensitivity of Progressive Multiple Sequence Alignment through Sequence Weighting, Position-Specific Gap Penalties and Weight Matrix Choice. Nucleic Acids Res. Spec. 1994, 22, 4673–4680. [Google Scholar] [CrossRef] [Green Version]
  71. Hall, T. BioEdit: A User-Friendly Biological Sequence Alignment Editor and Analysis Program for Windows 95/98/NT. Ibis Biosciences: Carlsbad, CA, USA, 1999; Volume 41, pp. 95–98. [Google Scholar]
  72. Goloboff, P. NONA (No Name) Ver. 2; Universidad Nacional de Tucumán: Tucumán, Argentina, 1999. [Google Scholar]
  73. Nixon, K. WinClada Ver. 1.0000; Cornell University: Ithaca, NY, USA, 2002. [Google Scholar]
  74. Darriba, D.; Taboada, G.L.; Doallo, R.; Posada, D. JModelTest 2: More Models, New Heuristics and Parallel Computing. Nat. Methods 2012, 9, 772. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  75. Schwarz, G. Estimating the Dimension of a Model. Ann. Stat. 1978, 6, 461–464. [Google Scholar] [CrossRef]
  76. Huelsenbeck, J.P.; Ronquist, F. MRBAYES: Bayesian Inference of Phylogenetic Trees. Bioinformatics 2001, 17, 754–755. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  77. Rambaut, A.; Drummond, A.J.; Xie, D.; Baele, G.; Suchard, M.A. Posterior Summarization in Bayesian Phylogenetics Using Tracer 1. 7. Syst. Biol. 2018, 67, 901–904. [Google Scholar] [CrossRef] [Green Version]
  78. Rambaut, A. FigTree 1.4. 2 Software; Institute of Evolutionary Biology, University Edinburgh: Edinburgh, UK, 2014. [Google Scholar]
  79. Porceddu, M.; Santo, A.; Orrù, M.; Meloni, F.; Ucchesu, M.; Picciau, R.; Sarigu, M.; Cuena Lombraña, A.; Podda, L.; Sau, S.; et al. Seed Conservation Actions for the Preservation of Plant Diversity: The Case of the Sardinian Germplasm Bank (BG-SAR). Plant Sociol. 2017, 54, 111–117. [Google Scholar]
  80. Kuhn, M. Building Predictive Models in R Using the Caret Package. J. Stat. Soft. 2008, 28, 1–26. [Google Scholar] [CrossRef] [Green Version]
  81. Stewart, G.; Al-Khassaweneh, M. An Implementation of the HDBSCAN* Clustering Algorithm. Appl. Sci. 2022, 12, 2405. [Google Scholar] [CrossRef]
  82. Campello, R.J.G.B.; Moulavi, D.; Zimek, A.; Sander, J. Hierarchical Density Estimates for Data Clustering, Visualization, and Outlier Detection. ACM Trans. Knowl. Discov. Data 2015, 10, 1–51. [Google Scholar] [CrossRef]
  83. Hahsler, M.; Piekenbrock, M.; Doran, D. dbscan: Fast Density-Based Clustering with R. J. Stat. Soft. 2019, 91, 1–30. [Google Scholar] [CrossRef] [Green Version]
  84. Sander, J.; Ester, M.; Kriegel, H.-P.; Xu, X. Density-Based Clustering in Spatial Databases: The Algorithm GDBSCAN and Its Applications. Data Min. Knowl. Discov. 1998, 2, 169–194. [Google Scholar] [CrossRef]
  85. Paradis, E.; Schliep, K. Ape 5.0: An Environment for Modern Phylogenetics and Evolutionary Analyses in R. Bioinformatics 2019, 35, 526–528. [Google Scholar] [CrossRef] [PubMed]
  86. Cailliez, F. The Analytical Solution of the Additive Constant Problem. Psychometrika 1983, 48, 305–308. [Google Scholar] [CrossRef]
  87. Schindelin, J.; Arganda-Carreras, I.; Frise, E.; Kaynig, V.; Longair, M.; Pietzsch, T.; Preibisch, S.; Rueden, C.; Saalfeld, S.; Schmid, B.; et al. Fiji: An Open-Source Platform for Biological-Image Analysis. Nat. Methods 2012, 9, 676–682. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  88. Kuhn, M. The Caret Package; R Package Version 6.0-93; The Comprehensive R Archive Network: Vienna, Austria, 2020. [Google Scholar]
  89. Revelle, W. Psych: Procedures for Psychological, Psychometric, and Personality Research; Northwestern University: Evanston, IL, USA, 2020. [Google Scholar]
  90. Johannes Maier, M. REdaS: Companion Package to the Book: “R: Einführung Durch Angewandte Statistik”; R Package Version 0.9.3; The Comprehensive R Archive Network: Vienna, Austria, 2015. [Google Scholar]
  91. Laliberté, E.; Legendre, P. A Distance-Based Framework for Measuring Functional Diversity from Multiple Traits. Ecology 2010, 91, 299–305. [Google Scholar] [CrossRef]
  92. Venables, W.N.; Ripley, B.D. Modern Applied Statistics with S; Statistics and Computing Book Series; Springer: New York, NY, 2002. [Google Scholar]
  93. Zhao, S. Cleandata: To Inspect and Manipulate Data; and to Keep Track of This Process; The Comprehensive R Archive Network: Vienna, Austria, 2018. [Google Scholar]
  94. Olson, R.S.; Cava, W.L.; Mustahsan, Z.; Varik, A.; Moore, J.H. Data-Driven Advice for Applying Machine Learning to Bioinformatics Problems. In Proceedings of the Pacific Symposium on Biocomputing 2018, Kohala Coast, HI, USA, 3–7 January 2018; pp. 192–203. [Google Scholar]
  95. Xiong, H.; Wu, J.; Liu, L. Classification with Class Overlapping: A Systematic Study. In Proceedings of the 2010 International Conference on E-Business Intelligence, Dordrecht, The Netherlands, 19–21 December 2010. [Google Scholar]
  96. Benjamini, Y.; Yekutieli, D. The Control of the False Discovery Rate in Multiple Testing under Dependency. Ann. Stat. 2001, 29, 1165–1188. [Google Scholar] [CrossRef]
  97. Sievert, C. Interactive Web-Based Data Visualization with R, Plotly, and Shiny; CRC Press: Boca Raton, FL, USA, 2020. [Google Scholar]
  98. Banerjee, M.; Ding, Y.; Noone, A.-M. Identifying Representative Trees from Ensembles. Statist. Med. 2012, 31, 1601–1616. [Google Scholar] [CrossRef] [Green Version]
  99. Domina, G. Armeria Willd. Available online: http://ww2.bgbm.org/EuroPlusMed/PTaxonDetail.asp?NameCache=Armeria&PTRefFk=7500000 (accessed on 20 March 2022).
  100. Peruzzi, L.; Domina, G.; Bartolucci, F.; Galasso, G.; Peccenini, S.; Raimondo, F.M.; Albano, A.; Alessandrini, A.; Banfi, E.; Barberis, G.; et al. An Inventory of the Names of Vascular Plants Endemic to Italy, Their Loci Classici and Types. Phytotaxa 2015, 196, 1–217. [Google Scholar] [CrossRef] [Green Version]
  101. Thiers, B. Index Herbariorum: A Global Directory of Public Herbaria and Associated Staff. Available online: http://sweetgum.nybg.org/science/ih/ (accessed on 4 March 2023).
Plants 12 02229 g001 550
Figure 1. Distribution of the 10 taxa and 15 populations of Armeria taxa endemic to Sardinia and Corsica sampled in this study. Asterisk = type locality.
Figure 1. Distribution of the 10 taxa and 15 populations of Armeria taxa endemic to Sardinia and Corsica sampled in this study. Asterisk = type locality.
Plants 12 02229 g001
Plants 12 02229 g002 550
Figure 2. Selected metaphasic plates of the 15 populations of Armeria taxa endemic to Sardinia and Corsica considered in this study. Arrows indicate the presence of satellites. Population codes as in Table 1.
Figure 2. Selected metaphasic plates of the 15 populations of Armeria taxa endemic to Sardinia and Corsica considered in this study. Arrows indicate the presence of satellites. Population codes as in Table 1.
Plants 12 02229 g002
Plants 12 02229 g003 550
Figure 3. Phylogenetic tree of Armeria taxa endemic to Sardinia and Corsica based on the concatenated dataset of nuclear (ITS) and plastidial markers (trnH-psbA, trnL-rpl32, trnL-trnF, trnQ-rps16). Population acronyms are as in Figure 1.
Figure 3. Phylogenetic tree of Armeria taxa endemic to Sardinia and Corsica based on the concatenated dataset of nuclear (ITS) and plastidial markers (trnH-psbA, trnL-rpl32, trnL-trnF, trnQ-rps16). Population acronyms are as in Figure 1.
Plants 12 02229 g003
Plants 12 02229 g004 550
Figure 4. PCoA illustrating the morphometric variation in Armeria species endemic to Sardinia and Corsica based on the Gower distance of the 49 characters measured. Symbols indicate the population acronyms (Table 1), whereas the colors indicate the taxa at species level. Asterisk = type localities.
Figure 4. PCoA illustrating the morphometric variation in Armeria species endemic to Sardinia and Corsica based on the Gower distance of the 49 characters measured. Symbols indicate the population acronyms (Table 1), whereas the colors indicate the taxa at species level. Asterisk = type localities.
Plants 12 02229 g004
Plants 12 02229 g005 550
Figure 5. Heatmap summarizing univariate statistically significant pairwise differences in Armeria taxa endemic to Sardinia and Corsica based on the 49 characters measured. Color intensity is related to the number of characters showing significant differences.
Figure 5. Heatmap summarizing univariate statistically significant pairwise differences in Armeria taxa endemic to Sardinia and Corsica based on the 49 characters measured. Color intensity is related to the number of characters showing significant differences.
Plants 12 02229 g005
Plants 12 02229 g006 550
Figure 6. Schematic and simplified representation of the different lines of evidence available for the circumscription of the Armeria taxa endemic to Sardinia and Corsica. Different shades of green indicate different groups suggested by every single line of evidence.
Figure 6. Schematic and simplified representation of the different lines of evidence available for the circumscription of the Armeria taxa endemic to Sardinia and Corsica. Different shades of green indicate different groups suggested by every single line of evidence.
Plants 12 02229 g006
Table
Table 2. Morphological characters used to study the Armeria taxa endemic to Sardinia and Corsica. QC = quantitative continuous, QD = quantitative discrete and, BI = binary.
Table 2. Morphological characters used to study the Armeria taxa endemic to Sardinia and Corsica. QC = quantitative continuous, QD = quantitative discrete and, BI = binary.
Character NameDescription of the CharacterTypeTool
1. SPINESpine presence on the calyx awn (yes/no)BIStereo
2. AWNAwn presence on the calyx’s limb (yes/no)BIStereo
3. PAPPresence of papillae on leavesBIStereo
4. CALYX_HAIRINESSCalyx hairiness (holotrichous/pleurotrichous)BIStereo
5. CALYX_VEINSNumber of calyx veins with hairs (10/5)BIStereo
6. DIMORPLeaf dimorphism (yes/no)BIStereo
7. INNER_BRACT_HAIRPresence of hairs on inner bract (yes/no)BIStereo
8. MAR_SUM_LEAFMargin of the summer leaf (hyaline/dentate)BIStereo
9. MAR_WIN_LEAFMargin of the winter leaf (hyaline/dentate)BIStereo
10. OUTER_BRACT_HAIRPresence of hairs on outer bract (yes/no)BIStereo
11. SUM_LEAF_APEXShape of the summer leaf apex (acute/cucullate)BIStereo
12. VEINS_HAIRS Presence of hairs along the leaf veins (yes/no)BIStereo
13. WIN_LEAF_APEXShape of the winter leaf apex (acute/cucullate)BIStereo
14. COL_PETPetal color (white/pink)BIStereo
15. ANG_SUM_TIPSummer leaf tip angle (°)QCFiji
16. ANG_WIN_TIPWinter leaf tip angle (°)QCFiji
17. AWN_LENGAwn length (mm)QCFiji
18. DIAM_CAPCapitulum diameter (mm)QCCalliper
19. HEIGTHPlant height (mm)QCRuler
20. LENG_CAL_PEDCalyx pedicel length (mm)QCFiji
21. LENG_CAL_TUBECalyx tube length (mm)QCFiji
22. LENG_INNER_INV_BRACTLength of the involucral inner bract (mm)QCCalliper
23. LENG_INNER_SPI_BRACLELength of the inner spikelet bracteole (mm)QCCalliper
24. LENG_INNER_SPI_BRACTLength of the inner spikelet bract (mm)QCCalliper
25. LENG_INTER_INV_BRACTLength of the involucral intermediate bract (mm)QC Calliper
26. LENG_OUT_INV_BRACTLength of the involucral outer bract (mm)QCCalliper
27. LENG_OUTER_SPI_BRACLELength of the outer spikelet bracteole (mm)QCCalliper
28. LENG_OUTER_SPI_BRACTLength of the outer spikelet bract (mm)QCCalliper
29. LENG_SUM_LEAFSummer leaf length (mm)QCRuler
30. LENG_WIN_LEAFWinter leaf length (mm)QCRuler
31. LIMB_LENGLimb length (mm)QCFiji
32. SCA_DIAMScape diameter at 1 cm from the base (mm)QCCalliper
33. SCA_LENGScape length (mm)QCRuler
34. SHEATH_LENGSheath length (mm)QCCalliper
35. WIDTH_CAL_TUBEWidth below the calyx tube limb (mm)QCFiji
36. WIDTH_IAL_SUM Width of the hyaline margin in summer leaf (mm)QCFiji
37. WIDTH_IAL_WIN Width of the hyaline margin in winter leaf (mm)QCFiji
38. WIDTH_INNER_INV_BRACTWidth of the involucral inner bract (mm)QCCalliper
39. WIDTH_INNER_SPI_ BRACTWidth of the inner spikelet bract (mm)QCCalliper
40. WIDTH_INNER_SPI_BRACLEWidth of the inner spikelet bracteole (mm)QCCalliper
41. WIDTH_INTER_INV_BRACTWidth of the involucral intermediate bract (mm)QCCalliper
42. WIDTH_OUT_INV_BRACTWidth of the involucral outer bract (mm)QCCalliper
43. WIDTH_OUTER_SPI_ BRACTWidth of the outer spikelet bract (mm)QCCalliper
44. WIDTH_OUTER_SPI_BRATLEWidth of the outer spikelet bracteole (mm)QCCalliper
45. WIDTH_SUM_LEAFWidth of the summer leaf at the middle (mm)QCCalliper
46. WIDTH_WIN_LEAFWidth of the winter leaf at the middle (mm)QCCalliper
47. N_INV_BRACTNumber of involucral bractQD
48. N_SUM_VEINSNumber of veins (with sclerenchyma) of summer leafQDMicroscope
49. SCAP_NUMNumber of scapesQD
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Tiburtini, M.; Bacchetta, G.; Sarigu, M.; Cambria, S.; Caputo, P.; De Luca, D.; Domina, G.; Turini, A.; Peruzzi, L. Integrative Taxonomy of Armeria Taxa (Plumbaginaceae) Endemic to Sardinia and Corsica. Plants 2023, 12, 2229. https://doi.org/10.3390/plants12112229

AMA Style

Tiburtini M, Bacchetta G, Sarigu M, Cambria S, Caputo P, De Luca D, Domina G, Turini A, Peruzzi L. Integrative Taxonomy of Armeria Taxa (Plumbaginaceae) Endemic to Sardinia and Corsica. Plants. 2023; 12(11):2229. https://doi.org/10.3390/plants12112229

Chicago/Turabian Style

Tiburtini, Manuel, Gianluigi Bacchetta, Marco Sarigu, Salvatore Cambria, Paolo Caputo, Daniele De Luca, Gianniantonio Domina, Alessia Turini, and Lorenzo Peruzzi. 2023. "Integrative Taxonomy of Armeria Taxa (Plumbaginaceae) Endemic to Sardinia and Corsica" Plants 12, no. 11: 2229. https://doi.org/10.3390/plants12112229

APA Style

Tiburtini, M., Bacchetta, G., Sarigu, M., Cambria, S., Caputo, P., De Luca, D., Domina, G., Turini, A., & Peruzzi, L. (2023). Integrative Taxonomy of Armeria Taxa (Plumbaginaceae) Endemic to Sardinia and Corsica. Plants, 12(11), 2229. https://doi.org/10.3390/plants12112229

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop