Diversity hotspots of the laurel forest on Tenerife, Canary Islands: a phylogeographic study of Laurus and Ixanthus

Abstract

Background and Aims Macaronesian laurel forest is among the worldwide hotspots of threatened biodiversity. With increasing evidence that woodland composition on the Canary Islands changed dramatically during the last few thousand years, the aim of this study was to find evidence for substantial recent population dynamics of two representative species from laurel forest.

Methods Amplified fragment length polymorphism (AFLP) was used to evaluate fine-scaled genetic variation of the paradigmatic tree Laurus novocanariensis (Lauraceae) and a long-lived herbaceous gentian from core laurel forest, Ixanthus viscosus (Gentianaceae), on Tenerife. Bioclimatic variables were analysed to study the respective climate niches. A chloroplast DNA screening was performed to evaluate additional genetic variation.

Key Results Genetic diversity of the laurel tree showed severe geographic partitioning. On Tenerife, fine-scaled Bayesian clustering of genetic variation revealed a western and an eastern gene pool, separated by a zone of high admixture and with a third major gene pool. Compared with genetic clusters found on the other Canary Islands, the East–West differentiation on Tenerife seems to be more recent than differentiation between islands. This is substantiated by the finding of extremly low levels of chloroplast DNA-based polymorphisms. Ixanthus showed no geographic structuring of genetic variation.

Conclusions Genetic data from Tenerife indicate contemporary gene flow and dispersal on a micro/local scale rather than reflecting an old and relic woodland history. In particular for Laurus, it is shown that this species occupies a broad bioclimatic niche. This is not correlated with its respective distribution of genetic variation, therefore indicating its large potential for contemporary rapid and effective colonization. Ixanthus is more specialized to humid conditions and is mostly found in the natural Monteverde húmedo vegetation types, but even for this species indications for long-term persistence in the respective bioclimatically differentiated regions was not find.

INTRODUCTION

The Canary Islands are an important Mediterranean biodiversity hotspot (Médail and Quézel, 1999); the Mediterranean biome contains 20 % of the world’s total floristic richness (Médail and Quézel, 1997) and has very high levels of endemism (38 % in the Canary Islands; Médail and Quézel, 1999). The species-rich flora of the Canarian Archipelago was able to establish for various reasons (de Paz and Caujapé-Castells, 2013), and the islands provided a unique opportunity for colonization from the mainland, which is frequently followed by species radiations (e.g. Losos and Ricklefs, 2009). Geo-climatic characteristics indicate (1) different ages of the various islands (20·6 to 1·1 million years ago, Mya) that provided multiple opportunities to colonize new areas; (2) moderate distances between neighbouring islands that range from 30 to 85 km and a minimum distance to mainland Africa that ranges from 90 to 375 km, which allows rapid and effective colonization; (3) climate changes during Pleistocene glaciation and deglaciation cycles (e.g. as revealed from sedimentological and geochemical proxies; Moreno et al., 2001; Ortiz et al., 2006); and (4) considerable changes in the insular landscape through geological time that resulted in high species richness (Whittaker et al., 2008). Consequently, the actual flora is made up of relict taxa with long evolutionary histories on the islands, and more modern taxa, which evolved during the Quaternary (Vargas, 2007; de Paz and Caujapé-Castells, 2013).

Similar hypotheses have also been proposed for the vegetation types of the Canarian Archipelago, which are made up of many species with presumably very different evolutionary histories. One of these vegetation types is laurel forest, which is dominated by evergreen trees that developed a ‘laurophyllous’ syndrome, which means their leaves are glossy, long-lived and frequently elongated. These woodlands also contain tremendous species diversity in the understorey at the margins and on rocky outcrops along the slopes (Lozano et al., 2010; Patinõ et al., 2014). Laurophyllous forest has been documented as widespread in large parts of Europe for >50 million years (from the Paleogene, 66·0–23·0 Mya, to the Mid-Miocene, 17–15 Mya), with subsequent rapid decline throughout the cooler and dryer Miocene and Pliocene. Consequently, only few refuge areas have been postulated around the Mediterranean (Rodríguez-Sánchez et al., 2009) at the end of the Pliocene and during the early Pleistocene. Therefore, Macaronesian laurel forest has traditionally been claimed to have the ancient ‘Tertiary relic’ vegetation type. This idea was recently tested (Kondraskov et al., 2015), and it was shown that present-day Macaronesian laurel forest partly evolved from pre-adapted taxa from the Mediterranean, Macaronesia and the tropics. Numerous taxa date back to only the Pleistocene, and that study provided convincing evidence of massive species turnover throughout the Pliocene and Pleistocene and/or a new assemblage through global recruitment rather than survival of relicts of old, widespread vegetation (Kondraskov et al., 2015). Today, the tree layer in the laurel forest of Tenerife is made up mainly by the four Lauraceae species Laurus novocanariensis, Persea indica, Apollonias barbujana and Ocotea foetens, and similar-looking members of other plant families such as Prunus lusitanica, Picconia excelsa, Ilex platyphylla and the more rare taxa Pleiomeris canariensis and Heberdenia excelsa. All of these taxa have similar laurel-shaped leaves which are characteristic of temperate rain forests. Also typical of the laurel forest are liana species and epiphytes (mosses and ferns), which grow on trunks and trees, and there is a rich understorey that contains many endemic species such as Ixanthus viscosus and Canarina canariensis (Wildpret de la Torre and Osorio, 1997). This laurel forest ecosystem has been described as the most diverse on the Canary Islands (del Arco Aguilar et al., 2010).

The actual vegetation of the Canary Islands differs significantly from the potential natural vegetation (PNV) because of human intervention over the past few thousands of years. The transfiguration of the potential natural vegetation started with the first inhabitants, the Guanches, a Berber ethnic group that arrived on the Canary Islands approx. 2000–3000 years ago (Parsons, 1981; de Nascimento et al., 2009). Even as a pastoral society, they started to change the vegetation substantially with grazing animals and need for firewood, as pollen analysis revealed (de Nascimento et al., 2009; Fernández-Palacios et al., 2011). However, del Carmen Machado Yanes et al. (1997) considered this impact as minor. Undoubtedly, a larger impact was the increase of land use and rapid deforestation that began with the conquest of the Castillians in 1402 and transition from a pastoral to an agriculture society (Wildpret de la Torre and Osorio, 1997). The wood from the laurel forest tree species was used for construction, firewood, coal, furniture, and poles for plantations. Similarly, other woodland vegetation types such as the Canarian pine forest declined, and the present-day distribution is the result of successive colonization–extinction processes caused by volcanic (Navascués et al., 2006) and human activity, and much of it has been planted (de Nascimento et al., 2009; de Heredia et al., 2010). Additionally, the deep soils and climate of laurel forest areas were ideal for agriculture (Pott et al., 2003).

Only 50 years ago, the main focus in economy shifted again, from agriculture to mass tourism; therefore, land use became increased in the coastal regions, whereas half of all agriculture land (50 000 ha) has become fallow since 1986 (Fernández-Palacios and Whittaker, 2008; Günthert et al., 2012). Today, most of the Canary Islands vegetation is shaped by human activities (del Arco Aguilar et al. 2010): only 26·7 % of the Canary Islands are covered with remnants of the potential natural vegetation, and most parts of the islands are dominated by substitution communities and more rural or urban areas without substantial vegetation. Well-preserved laurel forest communities currently cover 10 181 ha of the Canary Islands, which is only 11·8 % of their potential distribution range (86 624 ha). Compared with the other vegetation complexes on Tenerife, the laurel forest has lost most of its former area, and is second only in loss to the thermo-sclerophyllous woodlands (del Arco Aguilar et al., 2010). The massive impact of human activities on the natural vegetation has led to a situation in which approximately one-third of all endemic plant species are currently listed on the Red List of the Canary Islands (Reyes-Betancort et al., 2008). Consequently, for immediate conservation action, it is essential to know the genetic variation within a species to determine which areas should be protected; moreover, for any future long-term management approach (e.g. considering climate change), it is useful to know the evolutionary history of members of the vegetation type to determine if an ecosystem is composed of evolutionary ‘uniform’ taxa or taxa with quite different evolutionary histories.

There are only few detailed phylogeographic and fine-scale genetic studies for Canary Island laurisilva-associated plant taxa such as Canarina canariensis (Mairal et al., 2015). Most biogeography studies of laurisilva-associated plant taxa addressed former colonization routes and timing (e.g. Lavatera: Fuertes-Aguilar et al., 2002), speciation processes (e.g. Pericallis: Jones et al., 2014) or more general questions such as those about the evolution of the laurel forest vegetation as a whole (Kondraskov et al., 2015).

Therefore, we herein analysed the population structures, population dynamics and recent evolutionary histories of L. novocanariensis and I. viscosus, which are two characteristic species from the laurel forest of the Canary Islands, and particularly on Tenerife. Laurus novocanariensis is a canopy-building and dominant tree species, which can be seen as an indicator of former laurel forest vegetation communities, whereas I. viscosus is an endemic perennial understorey herb that seems to be restricted to the more intact primary laurel forest stands. Laurus novocanariensis plastid molecular data are also combining populations from Madeira, the Canary Islands and southern Morocco (Rodríguez-Sánchez et al., 2009), which is consistent with Pleistocene range expansion to the Canary Islands from the mainland and a young stem age of the present-day Laurus genus of approx. 1·39 Mya (Kondraskov et al., 2015). Conversely, I. viscosus (Gentianaceae) was inferred to have a stem age of approx. 9·4 Mya (Kondraskov et al., 2015). Ixanthus is a monotypic Canary Island endemic taxon; its early evolution is well correlated with optimal extension of Paleo-Macaronesia biota during the Mid-Miocene (Fernandéz-Palacios et al., 2011), and its crown diversification in different island lineages dates back to approx. 0·99 Mya (Kondraskov et al., 2015). Further phylogeographic studies on Macaronesian laurel forest species are sparse (e.g. Mairal et al., 2015). Consequently, for both species, there is plausible evidence that intraspecific differentiation all happened from the Pleistocene onwards.

Here, we reveal fine-scale genetic landscapes on Tenerife for L. novocanariensis and I. viscosus, with outgroup populations selected from other Canary Islands. Moreover, to identify environmental climatic factors that explain the distribution of present genetic diversity, regardless of population history and human influence, the ecological niches for both species were characterized from their current distribution range using relevant climate variables. Present-day distribution patterns were then compared with future climate change scenarios, which were shown to have a particularly strong influence on the survival of cloud-dependent laurel forest (Martín et al., 2012).

In this study, we tested for congruent patterns by comparing genetic diversity [amplified fragment length polymorphisms (AFLPs) and chloroplast DNA (cpDNA) sequence variation] with geographical distribution patterns using area-wide exhaustive sampling. We addressed the following three questions. (1) Did present-day genetic distribution patterns result from past evolutionary processes and old geomorphological and/or climatic constraints, or are they better explained by more recent and contemporary dynamics? (2) How prominent was the impact of climate variables on the actual distribution patterns of Laurus and Ixanthus? Conclusions from questions (1) and (2) will help to make some assumptions on future perspectives for the laurel forests on Tenerife and should provide some arguments to address question (3) as to what survival chance do laurel forests on Tenerife have and do they have a chance to expand their distributions gradually; accordingly, genetic hotspots were identified and analysed relative to geographically defined regions, gene flow and fragmentation.

MATERIALS AND METHODS

Taxon selection

Two Laurus species are traditionally considered: Laurus nobilis L. is found across the Mediterranean Basin and southern Black Sea, whereas Laurus azorica (Seub) Franco is assumed to be endemic to Macaronesia and southern Morocco (Barbero et al., 1981; Jalas and Suominen, 1991). A series of recent morphological and molecular/biogeographic analyses revealed that this traditional idea may be questioned, because Macaronesian populations (L. azorica) have been demonstrated to be more closely related to western Mediterranean populations (L. nobilis) than to any other Mediterranean L. nobilis population (morphology: Ferguson, 1974; Marques and Sales, 1999; cpDNA: Rodríguez-Sánchez et al., 2009; AFLPs: Arroyo-García et al., 2001). However, molecular data from the chloroplast genome in particular (e.g. Rodríguez-Sánchez et al., 2009) are in agreement to recognize a Laurus novocanariensis with populations from Madeira, the Canary Islands and southern Morocco (Rivas-Martinez et al., 2002). Therefore, herein we follow a concept recognizing L. novocanariensis as a separate species (Rivas-Martínez et al., 2002). This taxon was selected because it represents a structural–functional and widespread key element of the broad-leaved evergreen forest on the Canary Islands. This tree is a long-lived perennial and dioecious tree, and agamospermy has been ruled out (Forfang and Olesen, 1998). Effective pollination is performed by the two most frequent visitors: bees and flies (Tachina canariensis and Halictinae spp., respectively; Forfang and Olesen, 1998). Accordingly, we can assume strict outcrossing and high levels of at least local gene flow. Seeds are situated in one-seeded fleshy fruits and mostly dispersed by birds potentially even over long distances (Kubitzki and Kurz, 1984; Hampe, 2003). The outcrossing mating system and continuous distribution range make this species ideal for using AFLPs as a genetic marker system, because AFLPs provide only dominant marker information, and genetic diversity based on heterozygosity can be inferred accurately under the assumption that populations are close to Hardy–Weinberg equilibrium.

Ixanthus viscosus was included because it is a long-lived perennial herbaceous (with only basal woodiness) reference species that can be compared with L. novocanariensis, the laurel tree. In contrast to L. novocanariensis, which can grow in very different environments and vegetation types, Ixanthus is endemic to the core areas of broad-leaved evergreen laurel forest on Tenerife, Gran Canaria, La Palma, La Gomera and El Hierro (Thiv et al., 1999). Both L. novocanariensis and I. viscosus have their closest relatives or sister groups distributed in the Mediterranean region (Thiv et al., 1999; Rodríguez-Sánchez et al., 2009; Kondraskov et al., 2015).

Sampling strategy

Leaf material from L. novocanariensis and I. viscosus was collected in the wild and immediately dried on silica gel for subsequent DNA processing. In total, 690 L. novocanariensis and 199 I. viscosus individuals were sampled from 2010 to 2012. The main focus was on Tenerife, but other Canary Islands (La Gomera, La Palma, Gran Canaria and El Hierro) and Sao Miguel (Azores, L. azorica) were sampled for comparison.

To sample the complete area of extant laurel forest area on Tenerife exhaustively, a sampling grid of 350 × 350 m was used and plotted over maps of the actual distribution of the laurel forest on Tenerife (del Arco et al., 2003). Grid size was optimized based on the frequency of occurrence of L. novocanariensis in the respective vegetation types. Finally, for each single grid, we sampled at least one L. novocanariensis individual. Ixanthus viscosus populations are much more sparsely distributed on Tenerife, and we sampled all known occurrence sites. For each sample site, GPS co-ordinates (accuracy of 5 m) and elevation (accuracy of approx. 10 m at a minimum) were recorded. Identification of sampled individuals and their respective co-ordinates are provided in Supplementary Data Tables S1 and S2.

DNA extraction and AFLP fingerprinting

Genomic DNA was extracted based on the standard CTAB (cetyltrimethylammonium bromide) protocol (Doyle and Doyle 1987) with minor modifications as reported below. RNA was subsequently digested by 2 U of RNase for 1 h at 37 °C. DNA concentration was measured on a Nanodrop ND-1000 Spectrophotometer (Nanodrop Technologies, Wilmington, DE, USA) and diluted to a final concentration of 100 ng μL^–1.

Amplified fragment length polymorphism analysis followed protocols described by Vos et al. (1995), with some modifications as described in Koch et al. (2013). Using a slightly different protocol with a pre-genotyping Nucleofast-PCR cleanup step from Macherey-Nagel for each species, approx. 550 ng of genomic DNA for Laurus and 275 ng for Ixanthus were digested. Prior to analysis of all samples, 64 different primer combinations were tested for polymorphisms, their reproducibility and readability. For both species, three combinations were chosen for final genotyping (Laurus: FAM-EcoRI-ACA/MseI-CAC, HEX-EcoRI-ACC/MseI-CAG and FAM-EcoRI-ACA/MseI-CTA; and Ixanthus: FAM-EcoRI-ACA/MseI-CAC, TET-EcoRI-ACG/MseI-CTG and TAMRA-EcoRI-AGC/MseI-CTG). Genotyping was performed on a MegaBace 500/1000 capillary sequencer (Amersham Biosciences/GE Healthcare, Freiburg, Germany). Amplification products were multiplexed and mixed with 0·05 μL of ET-ROX550 size standard. To confirm the uniformity of the runs and for subsequent calculation of error rates, each 96-well plate contained one negative sample, three replicates (position chosen at random) and one standard sample.

Raw data were scored using GeneMarker 1.90 (SoftGenetics LLC, State College, PA, USA) scoring panels and with manual correction. Unclear peaks and large ranges in fluorescence intensity were excluded from analysis; furthermore, only fragment sizes that ranged from 60 to 545 bp were scored. Scored data were exported into a binary presence/absence matrix for further analysis.

High resolution melting (HRM) analysis of cpDNA

A previous phylogeographic analysis based on cpDNA sequence variation in Mediterranean Laurus included only seven individuals from the Canary Islands; these individuals shared the same chloroplast haplotype with a few other analysed individuals from Macaronesia and southern Morocco (Rodríguez-Sánchez et al., 2009). In that study, two marker regions were sequenced (trnK-matK and trnD-trnT, 2562 bp), but a pre-screen was also performed with another nine primer combinations that represented another approx. 8000 bp of contiguous sequence information from the plastid genome.

Consequently, we scanned for additional cpDNA variation in Tenerife Laurus populations, and also confirmed already known sequence data by sequencing using the methods described above. For the new sequences, five different and not yet widely analysed chloroplast regions were sequenced for ten arbitrarily selected individuals from genetically distinct regions as revealed by AFLP analysis and checked for single nucleotide polymorphisms (SNPs). Primers were chosen based on Shaw et al. (2005), and the following five markers were amplified and sequenced: rps16, matK/psbA (partial maturase K coding region and intergenic spacer), psbA/trnH (intergenic spacer), trnS/5'trnL (intergenic spacer) and trnL/trnF. Amplification was performed on a PTC Peltier thermal cycler (MJ Research, Waltham, MA, USA) with annealing temperatures that ranged from 54 to 64 °C, depending on the primer pairs used. PCR products were cleaned using the Wizard SV Gel & PCR Cleanup System (Promega, Mannheim, Germany) and custom sequenced with GATC Biotech (Konstanz, Germany). Although 3000 bp were added to 10 250 bp of pre-existing DNA sequence information, only one additional mutation was reliably detected, and it was found in the rps16 intron region (sequence position no. 726 in GenBank accession no. KT733564). Therefore, this region was further screened in detail in all 690 Laurus individuals using HRM analysis.

For HRM analysis, additional internal rps16 primers were designed: HRMrps16for (5′-ATG ACT CAA ATC ATA GTC TAA TTG ATG ATT TTG TGG A-3′ and HRMrps16rev 5′-TTT CGA GCC GTA CGA GGA GAA-3′) to screen the A/C polymorphism. HRM was performed using the SensiMix HRM kit (Bioline, Luckenwalde, Germany), in a total reaction volume of 12·5 μL with EvaGreen fluorescent dye in a RotorGene6000 real time cycler (Qiagen, Hilden, Germany). The HRM results were further validated by selecting PCR products from five individuals, which were re-sequenced to confirm the presence of the SNP. Respective DNA templates were included as standards in every HRM run.

Analysis of spatial structure of genetic variation

Data sets for both species were analysed with STRUCTURE 2.3.3 (Pritchard et al., 2000) using the option for dominant markers (Falush et al., 2007) and correlated allele frequencies (Falush et al., 2003). For Laurus, we analysed three data sets: (1) all Laurus samples including accessions from the Azores to test genetic distinctiveness; (2) all samples from Tenerife to test for spatial structure on Tenerife and define gene pools; and (3) a sub-data set that contained 15 individuals from the three defined main Tenerife gene pools (based on analysis of the complete Tenerife data set) and all samples from the other Canary Islands to prevent biased results caused by imbalances of varying sample numbers across different islands. In all cases, the admixture model with correlated allele frequencies was used. Analyses were run ten times, with K varying from 1 to 10 for Ixanthus and 1 to 15 for Laurus, with burn-ins of 200 k and 1000 k, respectively. The R-script STRUCTURE-Sum 2.2 (update 2009; Ehrich et al., 2007) was employed to determine the most likely K using Evanno’s deltaK (Evanno et al., 2005) and similarity as described by Rosenberg et al. (2002). To compare the different runs, CLUMPP 1.1.2b (Jakobsson and Rosenberg, 2007) was used to match up the clusters of replicate runs and calculate the average over all runs.

Amplified fragment length polymorphism genotype distance networks for both species were visualized in a neighbour-net analysis as implemented with the software Splitstree 4.12.3 (Huson and Bryant, 2006) with uncorrected P-values and equal-angle visualization. The software GenAlEx 6.5.3b was employed with calculating principal co-ordinate analysis (PCoA) scores based on a pairwise distance matrix using standardized covariances and visualized with IBM SPSS Statistics for Windows, Version 21.0 (IBM Corp., Armonk, NY, USA).

Mantel tests (Mantel, 1967) were carried out in the program Alleles in Space (AIS; Miller, 2005) to evaluate isolation-by-distance (IBD) effects. Barrier analysis was employed using Barrier 2.2 (Manni and Guérard, 2004; Manni et al., 2004) to illustrate putative barriers of genetic exchange between defined geographic regions.

AFLP genetic diversity and population differences

Population- and individual-based diversity analyses were performed. For the population-based analysis, populations were defined based on geographically defined sampling locations. The aim was to define populations of approximately the same sample size (about 20 individuals) in an area without putative barriers (population affiliation is provided in Tables S1 and S2 for Laurus and Ixanthus, respectively). The original 0/1 matrices for the scored AFLP fragments can be found in Supplementary Data Tables S3 and S4. The Shannon index and Nei’s diversity were calculated for all populations using Popgene 1.32 (Yeh et al., 1997) and AFLPdat (Ehrich, 2006). Descriptive statistical analyses (e.g. private loci, proportion of polymorphic alleles) were performed for all populations using GenAlEx (Peakall and Smouse, 2006, 2012) and AFLPdat. Population-pairwise F_ST and the distribution of the molecular variance within and between different populations with a non-hierarchical analysis of molecular variance (AMOVA) based on Euclidean pairwise square distances were evaluated in Arlequin 3.5.1.3 (Excoffier et al., 2005; Excoffier and Lischer, 2010).

For the individual-based genetic variation analysis, AIS (Miller, 2005) was employed using landscape shape interpolation to visualize the spatial pattern of genetic diversity and use Delauney triangulation with simple genetic distances, as originally used by Miller (2005). To avoid IBD effects, genetic distances between individuals that do not directly neighbour each other caused by the U-shape of Tenerife’s northern shore were manually deleted. Genetic distances (referred to as ‘surface heights’ in AIS) were plotted on a geographic map using a methodical approach in the Genetic Landscape GIS Toolbox similar to that introduced by Perry et al. (2010). Distance values from AIS were plotted in ArcMap (ESRI Inc., Redlands, CA, USA), interpolated across the topography of the potential laurel forest area to represent recent occurrence of the two model species using the inverse distance weight algorithm (Spatial Analyst Tool, ArcGis, ESRI Inc., Redlands, CA, USA), and classified for visualization.

Bioclimatic analysis

Our comprehensive area-wide sampling of both species and high sampling density substantially represents the occurrence of Laurus and Ixanthus within their current distribution ranges. Therefore, the 19 Bioclim values (with 11 temperature-related variables and eight precipitation-related variables) based on 30 arc-second grids were collected from the WORLDCLIM database (http://www.worldclim.org/) using DIVA-GIS 5.2 (Hijmans et al., 2005) to test which variables are related to the distribution of the genetic diversity of both species. Instead of using the elevation data from the WORLDCLIM database, elevation from our field GPS data was included, because of their higher accuracy.

For both species, PCoA was conducted in SPSS 21 with 20 values (19 Bioclim and elevation) to gain insight into the variables that most contribute to the variation in the data sets and might explain biogeographical patterns. The 19 Bioclim variables are: BIO1 = annual mean temperature, BIO2 = mean diurnal range [mean of monthly (max temp − min temp)], BIO3 = isothermality (BIO2/BIO7), BIO4 = temperature seasonality, BIO5 = max temperature of warmest month, BIO6 = min temperature of coldest month, BIO7 = temperature annual range (BIO5–BIO6), BIO8 = mean temperature of wettest quarter, BIO9 = mean temperature of driest quarter, BIO10 = mean temperature of warmest quarter, BIO11 = mean temperature of coldest quarter, BIO12 = annual precipitation, BIO13 = precipitation of wettest month, BIO14 = precipitation of driest month, BIO15 = precipitation seasonality, BIO16 = precipitation of wettest quarter, BIO17 = precipitation of driest quarter, BIO18 = precipitation of warmest quarter, and BIO19 = precipitation of coldest quarter.

RESULTS

AFLP and HRM analysis

Complete AFLP fingerprints were successfully achieved for 672 Laurus individuals and 180 Ixanthus individuals (249 and 121 clearly distinguishable fragments, respectively, that ranged in size from 60 to 545 bp). Of these bands, 94·4 and 56·2 %, respectively, were polymorphic. The error rate was calculated following the protocol described by Bonin et al. (2004) and yielded high reliability and reproducibility of the fingerprints (1·19 % of Laurus AFLP data with 45 observed differences in 3787 comparisons, and of 0·83 % of Ixanthus AFLP data with 18 observed differences in 2165 comparisons).

Consistent with the low sequence divergence level in Laurus chloroplast markers reported by Rodríguez-Sánchez et al. (2009), only one SNP in all analysed plastid markers was discovered; an A/C polymorphism was found in an intron of the rps16 gene, which encodes a 40S ribosomal protein. Melting temperature (T_m) was approximately 0·4 °C higher for individuals with the C-SNP chloroplast type compared with the A-SNP variant, which is consistent with the findings of Venter et al. (2001). This polymorphism could be clearly identified using a normalized plot (normalized fluorescence to temperature) and difference plot (normalized fluorescence minus A or C melting curve) following the manufacturer’s protocols (Corbett Research, 2006; now Qiagen, Hilden, Germany). Finally, only three individuals had the SNP, and they were all localized in western Tenerife in the Teno Mountains (610L, 611L and 615L, all from population 00). The distance between individuals was 300–750 m. Sequence information from the five selected plastid markers has been deposited in GenBank (accession numbers: KT733560–KT733564).

Population structure and geographic patterns

STRUCTURE analysis revealed that the Azores individuals were very genetically distinct from all other individuals of the complete Laurus data set (data not shown). The respective Splitstree analysis of Laurus showed very little differentiation within and among Canary Islands populations, but also supported the distinctiveness of the individuals from the Azores (Supplementary Data Fig. S1).

For Tenerife Laurus data, the most likely number of genetic clusters (deltaK) was K = 5 (Rosenberg et al., 2002; Evanno et al., 2005) and the similarity was also highest with K = 5. The results are shown in Fig. 1A; optimal K evaluation is shown in Supplementary Data Fig. S2. The Bayesian approach identified two major gene pools (indicated with green and red) that dominate the western and eastern part of Tenerife, respectively, and other gene pools were less well represented (green, 49 %; red, 36 %; blue, 9 %; violet, 5 %; and yellow, 2 %). There is a large region in between La Orotava Valley and south of Tacoronte, with an expanse of approx. 16 km, that has extensive admixture between the two major gene pools, and the major occurrence of a third major gene pool is indicated in blue. The data do not show a clear and significant gradient with a gradually declining contribution of the green pool from west to east and a respective increase in the contribution from the red gene pool, but rather two geographically distinct main clusters with a zone of admixture in between. Furthermore, if K was reduced to 3, the red and green clusters were combined and only the blue cluster persisted (data not shown). The majority of individuals showed admixture of various gene pools.

Fig. 1.

Genetic assignment of Laurus AFLP data. (A) Results from STRUCTURE analysis (Laurus novocanariensis) with K = 5 analysing the Tenerife only data set. The zone with the highest genetic admixture is indicated. (B) Results from the Canary Islands data set with K = 6 (upper diagrams) and K = 3 (lower diagrams). The ‘green’ Tenerife cluster consists of individuals from the admixture zone with varying proportions of the blue gene pool (>50 %), as demonstrated in (A).

Mixed individuals and populations were also present in the Bayesian clustering analysis of laurel populations that included accessions from all Canary Islands. Consequently, the admixture model was used, despite occurrence on a geographically isolated island; the non-admixture model was not capable of resolving this population structure. The highest deltaK value was K = 3, but K = 6 had a high similarity and deltaK value; therefore, both approaches are shown in Fig. 1B and Fig. S2.

The Tenerife data set STRUCTURE analysis revealed that the major gene pools on Tenerife (red and green) were not genetically separated, which indicates their close relatedness. The blue cluster was again recognized and shown to be almost unique to Tenerife. In total, the data indicate complex and reticulate connections between all islands. Hierro and La Gomera were the most similar to each other. La Palma and Gran Canaria also exhibited two main genetic clusters each, which was comparable with the results observed for Tenerife. However, La Palma and Gran Canaria are genetically intermediate between Tenerife and Hierro/La Gomera (K = 3). In PCoA analysis, 48 % of the variation in the genetic data was explained by the first two principal components (for both the total and Tenerife data sets). The PCoA revealed similar uniformity of data to that of the Splitstree analysis and did not show grouping in clear distinct clusters; grouping of the individuals was congruent with the clusters identified in the STRUCTURE analysis (data not shown).

Ixanthus showed a different pattern of population structure. The most likely K value was assigned as K = 2 in both analyses of total and Tenerife data sets (Supplementary Data Fig. S3). There is no obvious geographic structure of the two genetic clusters. Admixture on an individual level between the two gene pools was less pronounced compared with Laurus. Splitstree analysis of Tenerife Ixanthus differentiated five major groups (Fig. 2) that were distributed without significant geographic structure on Tenerife and corresponded to the STRUCTURE clusters when K = 5 was used.

Fig. 2.

SplitsTree analysis of the Ixanthus AFLP data and respective geographic distribution of individuals from genetic clusters I–V(VI) on Tenerife.

For both species, Barrier analyses did not identify distinct barriers to gene flow (graphs not shown) on either Tenerife or all of the Canary Islands. In Mantel tests, the correlation of genetic and geographical distances (r) on Tenerife was low for both species: r = 0·16 for Laurus and r = 0·18 for Ixanthus, both P ≤ 0·05); therefore, we can assume that there is only a slight IBD effect in both species that was detectable as fully consistent with missing genetic barriers.

Genetic diversity, population differences and genetic hotspots

Analysis of molecular variance of the Tenerife data sets detected most of the genetic variation within the respective populations for both species: 91·3 and 77·7 % for Laurus and Ixanthus, respectively. Similar geographic regions on Tenerife were revealed to be sources of genetic variance (Table 1). For populations with >10 individuals, pairwise F_ST values range between nearly 0 and 0·156 for Laurus and between 0·023 and 0·358 for Ixanthus. On Tenerife, pairwise population differentiation was lower overall, even between distant populations, compared with pairwise F_ST among islands (Fig. 3). Among populations on Tenerife, Shannon’s gene diversity and Nei’s gene diversity showed similar results compared with F_ST analysis (Table 2), and values for Laurus were consistently lower than those for Ixanthus. The Shannon’s gene diversity index of populations with >10 individuals ranged from 0·137 to 0·223 for Laurus and from 0·074 to 0·130 for Ixanthus. For Nei’s diversity, the lowest values were 0·091 for Laurus and 0·049 for Ixanthus; the highest values were 0·145 and 0·086, respectively. Comparability of the absolute numbers for the two species is not provided because of the different number of scored fragments.

Table 1.

AMOVA of genetic variation sorted for different geographic regions on Tenerife (as defined in Tables S1 and S2) and for their respective populations (as defined in Table 2)

Source of variation	d.f.	Sum of squares	Variance components	Fixation indices	Percentage variation
Laurus georegions				0·052
Among populations	11	638·31	0·84		5·23
Within populations	622	9483·45	15·25		94·77
Ixanthus georegions				0·186
Among populations	7	139·53	0·85		18·57
Within populations	156	583·02	3·74		81·43
Laurus populations				0·087
Among populations	38	1490·52	1·42		8·72
Within populations	633	9402·52	14·86		91·28
Ixanthus populations				0·223
Among populations	14	220·82	1·03		22·3
Within populations	165	595·02	3·60		77·7

Fig. 3.

Matrix of pairwise F_ST values for Laurus (upper panel) and Ixanthus (lower panel) geographically defined populations from Tenerife (no barriers to gene flow detected), and comparisons with other island samples.

Table 2.

Statistics and genetic diversity indices for meta-populations of Laurus and Ixanthus

Pop ID	No. of individuals	No. of polymorphic loci	Percentage of polymorphic loci	No. of private loci	Nei index	Shannon index
Laurus populations
00	20	87	34·66	0	0·1010	0·1549
01	20	92	36·65	0	0·1146	0·1747
02	19	104	41·43	2	0·1233	0·1883
03	21	108	43·03	0	0·1235	0·1899
04	20	117	46·61	0	0·1356	0·2089
05	20	122	48·61	1	0·1375	0·2113
06	20	106	42·23	0	0·1114	0·1731
07	15	99	39·44	2	0·1223	0·1867
08	20	114	45·42	0	0·1285	0·199
09	20	112	44·62	0	0·1275	0·1962
10	20	92	36·65	1	0·1009	0·1564
11	12	71	28·29	1	0·0928	0·1398
12	21	104	41·43	0	0·1204	0·1855
13	20	96	38·25	2	0·1138	0·1733
14	19	99	39·44	0	0·1133	0·1751
15	20	90	35·86	0	0·1011	0·1553
16	19	98	39·04	0	0·1174	0·179
17	19	103	41·04	2	0·1182	0·1817
18	21	110	43·82	0	0·1221	0·1891
19	20	96	38·25	0	0·1082	0·1663
20	16	92	36·65	0	0·1096	0·1673
21	23	103	41·04	2	0·1173	0·1803
22	22	109	43·43	1	0·1358	0·2064
23	20	114	45·42	1	0·1267	0·1966
24	21	129	51·39	2	0·1426	0·2205
25	20	118	47·01	0	0·1410	0·2146
26	21	95	37·85	0	0·1094	0·1669
27	20	91	36·25	1	0·1112	0·1701
28	20	110	43·82	0	0·1197	0·1843
29	21	105	41·83	2	0·1146	0·1781
30	20	95	37·85	1	0·1084	0·1667
31	21	109	43·43	0	0·1180	0·183
32	2	22	8·76	0	0·0363	0·053
33	2	19	7·57	0	0·0314	0·0458
35 (LP)	14	82	32·67	0	0·1020	0·1547
36 (LG)	6	41	16·33	0	0·0640	0·0938
37 (EH)	5	45	17·93	0	0·0659	0·0978
38(GC)	12	97	38·65	1	0·1112	0·1721
40 (AZ)	3	43	17·13	3	0·0723	0·1045
Ixanthus populations
01	17	27	22·31	1	0·065	0·1007
02	16	22	18·18	0	0·0586	0·0886
03	17	26	21·49	0	0·0779	0·116
04	21	27	22·31	2	0·0677	0·1041
05	16	27	22·31	1	0·0757	0·1139
06	15	32	26·45	2	0·0863	0·1295
07	18	27	22·31	0	0·077	0·1153
08	17	22	18·18	1	0·0607	0·0911
09	8	18	14·88	0	0·0494	0·0742
10	16	23	19·01	1	0·0623	0·0941
11	3	7	5·79	2	0·022	0·0326
12 GC)	2	3	2·48	0	0·0103	0·015
13 (LG)	5	20	16·53	0	0·0747	0·1058
14 (EH)	3	6	4·96	0	0·018	0·027
15 (LP)	6	9	7·44	0	0·0289	0·0422

LP, La Palma; LG, La Gomera; EH, El Hierro; GC, La Gomera; AZ, Azores.

Genetic hotspot analyses based on inter-individual genetic distances using AIS and associated maps are shown in Fig. 4. For Laurus, genetic hotspots were dispersed over the whole area of potential distribution of laurel forest vegetation (as defined by del Arco et al., 2003). Because of the sparse distribution of Ixanthus in some areas of the potential laurel forest, these areas were excluded from hotspot analysis. We chose this strategy, because over larger distances with no samples of one species, IBD effects overlay the existing diversity, and diversity variables should only be displayed for regions where the species is abundant. Genetic diversity hotspots were similar for both species, apart from regions where Ixanthus is not distributed.

Fig. 4.

Genetic hotspot analyses based on inter-individual genetic distances, which were determined using AIS, plotted using inverse distance weight interpolation. Interpolated areas represent potential laurel forest area (del Arco et al., 2003).

Bioclimatic analysis

Principal co-ordinate analysis with Bioclim and elevation data resulted in two main co-ordinates that explained >95 % of the total variation in the data set (Fig. 5A–D). The first co-ordinate, which was mainly explained by temperature-related values, explained 65, 66 and 65 % of the variation for Laurus data, Ixanthus data and both data sets combined, respectively. The second co-ordinate, which was mainly explained by precipitation-related values, explained 30 % of the total variation in all three data sets. Therefore, we do not show individual plots. By comparing Ixanthus and Laurus, it was shown that the distribution of both species was explained by similar bioclimatic variables (Fig. 5A). As exemplified for Laurus, the PCoA showed relationships between geographic regions and climate (Fig. 5B), but not between genetic diversity and climate conditions (Fig. 5C, D). Elevation data were related to the first co-ordinate (Fig. 5E) and, therefore, with the temperature-dependent Bioclim values.

Fig. 5.

Principal co-ordinate analysis based on 19 Bioclim variables and elevation data for all sample locations on Tenerife. (A) Comparison of Laurus (blue) and Ixanthus (orange). (B) Geographic regions indicated for Laurus sites. (C) Genetic diversity indicated for Laurus sites (see Fig. 4). (D) Genetic diversity indicated for Ixanthus sites (see Fig. 4). (E) Factor loading of the 19 Bioclim variables and elevation for the two main co-ordinates (temperature-related, red; precipitation-related, blue) for the combined data-set (Ixanthus and Laurus).

DISCUSSION

Laurus genetic differentiation

Our cpDNA data revealed very low levels of genetic diversity and are congruent with results of previous studies (Rohwer, 2000; Chanderbali et al., 2001; Ródriguez-Sánchez et al., 2009). The only SNP detected in our samples was locally distributed and found in three individuals (Supplementary Data Fig. S4) on western Tenerife (the Teno Mountains) with a distance of 300–750 m between individual trees. Interestingly, all three individuals are close to the Laurus upper tree line. This result might provide some evidence that maternal gene flow via seeds is hindered as long as dense and existing laurel forests prevent successful germination and subsequent establishment of young trees, and that long-distance dispersal remains a rare event (cf. Silvertown, 2004).

Although plastid DNA sequence information did not allow us to draw further conclusions regarding time scales, the very low levels of genetic diversity studying >13 500 bp is consistent with the hypothesis of a recent evolutionary history of Macaronesian Laurus, with a maximum age of 1·3 Mya since stem-group radiation started (Kondraskov et al., 2015). Low levels of plastid DNA sequence diversity have been reported earlier on the Lauraceae family level (Rohwer, 2000; Chanderbali et al., 2001), but genetic diversity was sufficient to reconstruct family-wide relationships and also Laurus was separated from related genera. There are no detailed population-based phylogeographic analyses of Mediterranean Lauraceae species. There a few examples of Lauraceae (e.g. from Taiwan; Machilus and Neolitsea), however, that revealed sufficient plastid DNA sequence variation to reconstruct Pleistocene phylogeographic–evolutionary patterns (Wu et al., 2006; Lee et al., 2013). A large-scale phylogeographic study on Laurus focused on single and selected individuals only, therefore not allowing detailed conclusions about Laurus Pleistocene evolutionary history, and the authors concluded that future detailed population-based studies are needed (Rodríguez-Sánchez et al., 2009).

Based on sequence data, we also cannot draw conclusions about the status of our outgroup accessions from the Azores, because they are also genetically identical based on our newly generated sequence data. However, it has to be considered that populations from the Azores can be distinguished from those from Madeira and the Canary Islands by a single SNP (Rodríguez-Sánchez et al., 2009).

Compared with plastid DNA sequence data, AFLP analyses demonstrate substantial genetic differentiation between and within islands. For Canary Island populations, there is strong support from Bayesian clustering analysis for three geographically structured major gene pools with K = 3 (Fig. 1B). The first gene pool, indicated in blue, was found more southernly (El Hierro, La Gomera, and part of La Palma and Gran Canaria); the second gene pool (red) was mainly distributed on the northern islands (Tenerife, and part of La Palma) and on Gran Canaria. A third and almost unique gene pool was found on Tenerife in a geographically intermediate position (e.g. La Orotava Valley). If this pattern is the oldest we can significantly detect with our AFLP marker system, then this split is probably not older than 1·39 Mya, as indicated by the stem-group age of present-day Laurus species (Kondraskov et al., 2015). Chloroplast DNA data do not contradict this timeline, because no sequence variation except one rare SNP was found, which might even indicate a much younger age.

Subsequent and secondary differentiation of gene pools is indicated, as we revealed six genetic clusters among islands (K = 6; Fig. 1B): the southern (blue) gene pool on El Hierro and Gran Canaria almost maintained unique geographic occurrence (two new clusters are indicated; greyish and violet clusters). La Gomera and La Palma still share the gene pool indicated in blue in the three-cluster results, which might indicate closer genetic contact between these two islands compared with El Hierro and Gran Canaria. Similarly, the red gene pools from La Palma and Tenerife were still united with K = 6; similarly to the blue gene pool, the red gene pool on Gran Canaria was considered a new and unique gene pool with K = 6 (dark blue).

In summary we found two old and widely spread gene pools on the Canary Islands with a broad-scale north–south division and a third almost endemic gene pool (green) on Tenerife. Subsequent genetic differentiation indicates that El Hierro and Gran Canaria are more separated from the other islands, but closer affinities exist between La Palma, La Gomera and Tenerife. This spatio-temporal genetic pattern is different compared with those of other laurel forest species. Canarina canariensis from the Canary Islands shows a more obvious east–west divide with K = 2. Consistently, AFLPs and plastid DNA sequence data revealed much closer affinities of Gran Canaria with Eastern Tenerife, La Gomera with Western Tenerife, and El Hierro with La Palma (Mairal et al., 2015); interestingly, the deep east–west divide of this Canary Island endemic taxon is dated to 0·84 Mya, and is therefore similar to the inferred timeline for early Laurus differentiation on the Canary Islands.

Different from the plastid DNA sequence data, AFLP analysis distinguished accessions from the Azores from all Canary Island populations (Fig. S1). Considering the results of both AFLP and plastid DNA sequence variation, we might tentatively conclude that L. azorica directly derived from northern Canary Island or Madeiran populations, which is consistent with the findings of Rodríguez-Sánchez et al. (2009). In summary, the broad-scale distribution pattern of Laurus genetic variation on the Canary Islands is surprising and not consistent with patterns of genetic differentiation between islands in other plant species such as C. canariensis, a laurel forest species (Mairal et al., 2015), or Rumex bucephalophorus from open sites (Talavera et al., 2013).

Ixanthus genetic differentiation

In strong contrast to Laurus, we found little spatial structure in the Ixanthus AFLP data set from across the Canary Islands, and genetic assignment tests revealed a significant K = 2 value (Fig. S3). Considering the various islands, pairwise F_ST data (Fig. 3) indicate some closer affinities between Tenerife and La Gomera, and thereby show some similarities with C. canariensis (Mairal et al., 2015). This is further substantiated by the fact that no barriers to gene flow were detected between Canary Islands.

On Tenerife, genetic assignment also revealed no significant spatial structure. However, genetic clusters based on Splitstree analysis revealed some spatial structure of different genetic clusters (Fig. 2): (a) the Teno Mountains in the north-west contained only genetic clusters II and V; (b) the Anaga Mountains contained individuals from all genetic clusters; and (c) La Orotava Valley showed an increased percentage of occurrence of genetic cluster IV compared with the Anaga and Teno Mountains. This pattern might also reflect some east–west differentiation, with La Orotava Valley as a genetic melting pot. However, based on the type and significance of our AFLP data, we cannot make further significant comments on the question of whether there is a simple genetic gradient from east to west, which indicates either (a) past migration which highlights the Anaga Mountains as the potential source region or (b) two source areas (Teno and Anaga Mountains), and present-day distribution reflects east–west and west–east colonization events. Taking into consideration genetic affinities between La Gomera and Tenerife and that La Orotava Valley represents a genetically intermediate location, the second hypothesis might be more likely; this hypothesis is consistent with the idea that both mountain ranges are important refuge areas for Tenerife biodiversity (Mairal et al., 2015).

One evolutionary hypothesis for different laurel forest species?

There are different (eco)temporal hypotheses that explain the evolution of laurel forest on the Canary Islands relative to present-day floristic composition: (1) the climate ‘Tertiary’ relict hypothesis (e.g. Hooker, 1867; Engler, 1879); (2) the paleo-islands hypothesis (Fernández-Palacios et al., 2011; Micromeria: Puppo et al., 2014); (3) intra-specific diversification in the Pleistocene (e.g. evidence from molecular dating of higher taxa; Kondraskov et al., 2015); (4) Late Pleistocene/Holocene diversification due to later volcanic activities, landslides and substantial Late Pleistocene climate changes (Carine and Schaefer, 2010); and (5) recent post-colonial human activities that led to a drastic decline in laurel forest and its biodiversity (Nogué et al., 2013). We are aware that any of these ideas or any combination thereof might explain the present-day patterns of distribution and genetic differentiation.

Considering recent results providing a stem-group age of L. novocanariensis/L. azoricus of about 1·3 million years and contributing further with herein confirmed low-level plastid DNA variation, we can reject hypotheses (1) and (2), and we also did not observe significant Pleistocene intra-specific differentiation between the Canary Islands (hypothesis 3), except for an old south–east/north–west divide (Fig. 1B; K = 3). Therefore, hypotheses (4) and maybe (5) are the most likely explanations for the present-day distribution patterns of Laurus. As demonstrated by STRUCTURE analysis, fine-scale genetic structure on Tenerife is considered to not be drastically influenced by ongoing inter-island gene flow and consequently do reflect in situ genetic differentiation. This result was also supported by counting the exclusively shared AFLP fragments between islands (Table 3). It is only Tenerife that shares unique AFLP alleles with single other islands, including the Azores. Remarkably and also reflecting the south–east/north–west divide are the highest numbers of alleles shared with Gran Canaria and La Palma. However, it is not that the Teno and Anaga Mountains shared significantly more alleles with La Palma and Gran Canaria, respectively. This is also indicative for later differentiation on Tenerife with its paleo-islands. These findings are consistent with those of STRUCTURE analysis (Fig. 1B).

Table 3.

Sumary of percentage shared unique AFLP alleles (fragments) among islands (Laurus, 249 fragments; Ixanthus, 121 fragments)

		Laurus
		Tenerife	La Palma	El Hierro	La Gomera	Gran Canaria	Azores
Ixanthus	Tenerife	–	2·8 (2·8/2·8)	0	0	7·2 (2·8/2·0)	0·8
	La Palma	0	–	0	0	0	0
	El Hierro	0	0	–	0	0	0
	La Gomera	1·6	0	0	–	0	0
	Gran Canaria	0	0	0	0	–	0
	Azores	0	0	0	0	0	–

Tenerife was considered as a single unit (x), but also with Anaga (y) and Teno (z) Mountains separately [x (y/z)].

The significant east–west differentiation observed for Laurus on Tenerife (Fig. 1A) is a classical pattern that is frequently observed for species on this island and has often been discussed in connection with the three paleo-islands on Tenerife (Roque del Conde in the south-west approx. 11·9–8·9 Mya; Teno in the north-west approx. 6·2–5·6 Mya; and Anaga in the northeast approx. 4·9–3·9 Mya), and which formed by fusion to present-day Tenerife approx. 3·5 Mya (Ancochea et al., 1990). Indeed, there are a few examples that indicate a biogeographic split among sister taxa or populations of a single species that date back to the Miocene (Juan et al., 1996; Dimitrov et al., 2008; Maciás-Hernández et al., 2013; Puppo et al., 2014); however, various documented and time-calibrated biogeographic splits have been placed in the Pleistocene (e.g. Kondraskov et al., 2015).

The Ixanthus data do not provide any significant evidence that supports hypotheses (1), (2) or (3) that account for present-day distribution patterns. Counting the exclusively shared AFLP fragments between islands, only La Gomera and Tenerife shared 1·6 % of their fragments (Table 3). All other pairwise island comparisons do not show any exclusively shared AFLP fragments. Because Ixanthus is a core laurel forest floristic element and long-lived perennial species, hypothesis (4 ) of a Late Pleistocene/Holocene diversification is the most likely scenario that is supported by the genetic diversity revealed by our results.

Comparing Laurus and Ixanthus, we suggest that east–west separation for both species was due to Late-Pleistocene/Holocene volcanic activities and landslides. A major landslide occurred in La Orotava Valley, west of the admixture zone of Laurus, in the late Pleistocene (Watts and Masson, 1995). We are cautious to trace the genetic variation to single events, because similar processes on the local scale might have been involved in the diversification patterns.

Bioclimatic data analyses support the idea of secondary east–west fragmentation and subsequent re-colonization and genetic admixture. Because we sampled Laurus over the entire range of the laurel forest on Tenerife, PCoA provides a comprehensive bioclimatic footprint of this particular vegetation type (Fig. 5). Based on these analyses, we do not see a difference between the occupied bioclimatic niches of Laurus and Ixanthus on Tenerife (Fig. 5A), which was also found for C. canariensis. Both Laurus and Ixanthus are distributed all over the laurel forest bioclimatic space. However, there are present-day bioclimatic differences between the Teno and Anaga Mountains (Fig. 5B). Interestingly, the Anaga and Teno Mountains differed, because the Anaga Mountains displayed broader ecological space that was explained by precipitation-related components and narrower ecological space explained by temperature-derived components, whereas the Teno Mountains showed the opposite pattern. Central Tenerife was almost completely covered by catastrophic events until as recently as 0·13 Mya (Ancochea et al., 1999), and the three paleo-islands of Teno, Anaga and Roque del Conde remained geologically stable since the Mid-Pliocene.

A recent study that focused on C. canariensis, which is a long-lived climbing perennial from laurel forest on the Canary Islands, argued that volcanic activities and respective landscape changes after the merging of the paleo-islands 3·5 Mya played a key role in generating boundaries within Tenerife, and these paleo-islands acted as refugia against loss of genetic variation, extinction and sources of genetic diversity during migration and expansion. The first divide of Tenerife into east and west (Anaga and Teno) was dated back to approx. 0·8 Mya (western Canarian clade vs. eastern Canarian clade). Later differentiation separated El Hierro + La Palma vs. west Tenerife + La Gomera between 0·41 and 0·31 Mya, which reflects an east–west division.

All three genetically studied examples of plant species from Canary Island laurel forest, Laurus, Ixanthus and Canarina, had considerably different deep evolutionary history patterns, as indicated by their stem node ages and spatial patterns in the archipelago. However, these species share similar time frames of intraspecific diversification. These processes are probably linked to Late-Pleistocene/Holocene volcanic activities, landslides and substantial Late Pleistocene climate changes.

Genetic landscapes on Tenerife and implications for conservation

Genetic hotspot analyses for Laurus and Ixanthus on Tenerife highlight the Teno and Anaga Mountains as important centres of genetic diversity. This result was unsurprising, because the two mountain ranges are well known for their unique biodiversity richness and thereby act as long-term paleo-island refugia for various organismal groups (see Mairal et al., 2015). Importantly, geographically intermediate regions such as La Orotava Valley toward the east (Las Lagunetas) show high levels of genetic diversity. Moreover, considering climatic differences, Laurus exhibited higher genetic diversity at the more central part of the bioclimatic space rather than at the bioclimatic edges (Fig. 5C). However, this pattern differs for Ixanthus (Fig. 5D). We found a much stronger clumping of high genetic diversity classes toward BioClim variables 14 (precipitation of driest month) and 17 (precipitation of driest quarter), which also largely characterizes the Anaga Mountains (Fig. 5D). These results indicate that Ixanthus has a narrower ecological niche compared with Laurus. Ixanthus, as a species from the understorey of core laurel forest and its genetic diversity, might therefore indeed be reflective of a long-term historical footprint.

Laurus is one of the most important structural components of the laurel forest on Tenerife, and its present-day distribution does reveal high genetic variation in the various ecologically (climatically) different regions. Optimistically, this finding highlights that current laurel forest may be able to persist, and also indicates the potential for future expansion of laurel forest. It can also be inferred that at least species such as Laurus might be able to react and adapt to future climate change, because high levels of genetic diversity have been preserved all over the islands. However, pessimistically, global warming might severely affect laurel forest in particular. A recent study demonstrated a significant trend of higher temperatures on Tenerife, and further impacts on trade winds and cloud formation on the northern side of Tenerife have to be considered in future analyses (Martin et al., 2012). Modelling of laurel forest distribution under a global scenario of a temperature increase of 3 °C indeed predicts the extirpation of laurel forest from the Anaga Mountains and a great reduction in the Teno Mountains. However, interestingly, the largest predicted area under the 3 °C increase scenario is along the northern flank of Tenerife (Martin-Esquivel, 2010) and exactly matches one of our centres of Laurus genetic diversity.

A preliminary analysis that compared old pastures from the last few centuries, which are currently colonized by Laurus, and local levels of genetic diversity also indicate that there is now a significant difference in genetic diversity levels between ‘original’ and ‘re-colonized’ areas (M. A. Koch et al., unpubl. res.), which thereby also highlights the dispersal potential of Laurus if appropriate habitats for colonization are available. In summary, we conclude that important primary target regions for conservation are indicated by the various genetic diversity hotspots, but laurel forests should be analysed by including neighbouring sites.

Conclusion

Laurus and Ixanthus show young intraspecific genetic diversification patterns, with different biogeographic histories and ecological impact widths. This further indicates that vegetation types such as Macaronesian laurel forest are composed of taxa with varying evolutionary patterns. The occurrence of Laurus, Ixanthus and Canarina in the Canarian Archipelago since at least the Pleistocene indicates their ability to react to permanent climatic changes, and their different genetic patterns might also indicate continuous turnover in species composition of Canary Island laurel forest. Consequently, considering laurel forest as a more dynamic vegetation type also has implications for future conservation strategies, and management activities may not solely focus on core regions and refuge areas in the future.

SUPPLEMENTARY DATA

Supplementary data are available online at www.aob.oxfordjournals.org and consist of the following. Tables S1 and S2: list of accessions studied for Laurus and Ixanthus, with detailed GPS-defined position and elevation information, and number of individuals analysed per population. Tables S3 and S4: AFLP 0/1 matrices for Laurus and Ixanthus (matrices provided as Excel files). Figure S1: NeighbourNet (SplitsTree program) for the complete Laurus AFLP data set. Figure S2: optimal K test for Laurus genetic clustering based on AFLP data (Tenerife and Canary Island data sets). Figure S3: Ixanthus STRUCTURE analysis and optimal K evaluation (AFLP data set). Figure S4: plastid DNA SNP distribution revealed from HRM analysis.