Spatial patterns of genus‐level phylogenetic endemism in the tree flora of Mediterranean Europe

The Mediterranean Basin is a major hotspot of plant biodiversity, including forest trees. Over the past centuries, Mediterranean forests have been fragmented and over‐exploited, to which the threats of climate change are now added. Our aim is to better understand patterns and processes of tree biodiversity in the Mediterranean and to provide indicators complementing the traditional approaches to biodiversity conservation based on species counts and occurrences, using georeferenced phylogenetic diversity and endemism analyses in a spatial ecological context.


| INTRODUC TI ON
Forests and woodlands harbour immense terrestrial and aquatic biodiversity and represent one of the most species-rich habitat type worldwide (Gibson et al., 2011;Lindenmayer, 2009). Forests provide a wide range of critically important ecosystem services such as climate regulation, biomass production, water supply and purification, pollination, and provision of habitats for forest species (Brockerhoff et al., 2013;Decocq et al., 2016;Liang et al., 2016;Mori et al., 2017;Thompson et al., 2011). Over the last centuries, forest habitats have been destroyed at rates much higher than ever observed in human history (Gaston, 2000;Johnson et al., 2017;Turvey & Crees, 2019).
As a result, a high number of species have become extinct and/ or suffered severe population declines (Mace et al., 2005), with many advancing at high speed to higher categories of threat every year, notably in the biodiversity hotspots of the world (Hoffmann et al., 2010;Le Roux et al., 2019). The forests of the Mediterranean Basin, a recognized hotspot of biodiversity, follow the same trend (Gauquelin et al., 2018;Médail & Quézel, 1997).
Where and how to prioritize biodiversity conservation is a key political, societal and scientific issue for modern societies.
Traditionally, biodiversity assessments have been based on species counts, valuing areas in terms of species richness and number of endemics and/or threatened species, mostly per spatial units (Kier et al., 2009;Myers et al., 2000;Norman, 2003). However, as species richness, endemism and threat can be influenced by many factors, such as the species concepts and taxonomic standards used, the spatial scale and the intensity of the sampling. Using such data can thus make biodiversity assessments and comparisons across taxonomic groups and sites limited in scope or misleading (Hillebrand et al., 2018;McKerrow et al., 2018;Van Jaarsveld et al., 1998).
Limitations may also arise when considering all species equal entities and ignoring their particular functional role in the ecosystem, their associated communities and/or their evolutionary history (e.g., Doxa et al., 2020).
The contribution of phylogenetic systematics to the biodiversity conservation debate stems from the very idea that species are not equivalent entities from an evolutionary point of view (Mishler, 2009). As tools to characterize species in terms of evolutionary history using DNA sequences became increasingly available, phylogenetic diversity (PD), the sum of branch lengths in a phylogeny connecting a set of taxa, was proposed as a measure to quantify the loss of evolutionary history (Faith, 1992;Nipperess et al., 2012). A major advantage of PD is that it is relatively resistant to changes in taxonomic status (not that we expect any here, as the genus-level taxonomy of Mediterranean trees is well known and accepted, see Médail et al., 2019) and, thus, allows direct comparisons among different taxonomic groups. Additionally, PD can be also compared with other diversity measurements, such as functional diversity, including the role of evolutionary history in assembly rules in communities. For instance, facilitation-mediated coexistence has been demonstrated to be driven by evolutionary history of interacting species (Valiente-Banuet & Verdú, 2007), as the functional syndromes of Mediterranean woody plants (Herrera, 1992;Verdú & Pausas, 2013) or the different niche response to fire in communities (Ojeda et al., 2010).
Phylogeny-based methods for measuring biodiversity have developed rapidly during the last decades, with one important area of development relating to endemism (Rosauer et al., 2009).
Endemism has always been a major consideration in biogeography and one of the most important criteria when defining conservation priorities (Bacchetta et al., 2012;Linder, 2001). The concept of endemism is implicitly and closely related to the idea of irreplaceability (Margules & Pressey, 2000), and therefore of conservation value. However, the traditional definition of endemism has been narrowly interpreted as the complete restriction of a taxon to a certain area (i.e. absolute endemism). Relative endemism, which refers to the degree of restriction of taxon-range on a quantitative scale ranging from 1 (absolute endemism) to 0 (ubiquitous), broadens the concept (Crisp et al., 2001). In order to integrate evolutionary information, the concept of relative endemism has been extended to the geographic restriction of clades at any taxonomic level, a metric called phylogenetic endemism (PE, Mishler et al., 2014;Rosauer et al., 2009).
Phylogenetic diversity and endemism are most often used to characterize alpha diversity (PD or PE) of given local sites. When entire geographical areas are considered, these estimators can be complemented by the quantification of phylogenetic beta diversity, that is, the turnover in PD among local sites (Graham & Fine, 2008). This estimator is similar to traditional measures of species turnover among sites with the exception that it refers to the shared and unshared branches of the phylogeny that are measured instead of the shared and unshared species. Turnover can also be measured for PE, by weighting range-restricted branches more heavily than common branches, and is termed "phylogenetic range weighted turnover" . All these measurements can enhance our understanding of biodiversity patterns and can be used for conservation assessment and planning .
Although many studies of the biodiversity of the Mediterranean Basin exist Thompson, 2020), surprisingly, a comprehensive spatial phylogeny is still lacking for this region, by far the largest Mediterranean climate region in the world and the second-largest terrestrial biodiversity hotspot of the world (Myers et al., 2000). Only spatially restricted phylogenies are available, notably in southern Spain (Molina-Venegas et al., 2015;Simon-Porcar et al., 2018). The most comprehensive phylogeny available to date for the region is the dated phylogeny at genus level for all tree taxa of the Euro-Mediterranean region of Cheikh .
Here, we combine the genus-level phylogeny of Cheikh  with the most exhaustive compilation of occurrence data for these tree genera across the European part of the Mediterranean Basin Monnet et al., 2020).
Our specific goal was to single out regions of high phylogenetic neo-and paleo-endemism, thereby increasing our knowledge of biodiversity spatial patterns and of the ecological factors that can explain their emergence, as well as contributing to prioritizing areas of high conservation value. For this aim, we (a) calculated a series of taxonomic and phylogenetic diversity indices for each of the

| Study area
Our study area is the Euro-Mediterranean-region defined by Médail et al. (2019), the North Mediterranean terrestrial ecoregion in the biogeographic classification scheme of Olson et al. (2001). These biogeographical limits of the Euro-Mediterranean region are similar to those proposed by Médail and Quézel (1997)

| Data sources for tree occurrences, environmental variables and the phylogeny
The woody vegetation of the Mediterranean is made of diverse types of shrublands (maquis, garrigue, phrygana) and forests, where tree morphology varies widely with environmental F I G U R E 1 Distribution of the 15 biogeographical provinces (sensu Rivas-Martínez et al., 2004) of the Euro-Mediterranean region constraints (climate, geology, geomorphology, soil type), habitat types and anthropogenic activities. We adopted the criteria elaborated by Médail et al. (2019) concerning tree definition and used their checklist of 64 native tree genera. For genus occurrence and their spatial distribution, we used the data compiled by Monnet et al. (2020).
We used a total of 643 grid cells of 50 × 50 km spatial resolution to completely cover the European Mediterranean Basin. The database of tree genus occurrence within each cell can be found in Appendix S1. The spatial resolution of environmental variables was originally 344 km 2 for current climate and paleoclimate data (worldclim, https://world clim.org/) and 250 km 2 for soil data (soilgrids, https://soilg rids.org/). To match our genus occurrence data, environmental data were aggregated to a 2,500 km 2 spatial resolution (50 × 50 km) using the package raster (Hijmans et al., 2015) so as to obtain one average value per cell. For our analysis, we used 30 different environmental variables (Appendix S2) which are further described below.
We used the dated genus-level phylogenetic tree of Cheikh . This phylogeny was built using sequence data of three chloroplast DNA regions commonly used for phylogenetic and taxonomic barcoding purposes: the protein-coding rbcL and matK genes, and the non-coding intergenic spacer trnH-psbA (Hollingsworth et al., 2009;Kress & Erickson, 2007)

| Relative environmental turnover-diversity among cells and correlation with the environment
To quantify among-cell variation and identify the main environmental factors explaining genus turnover, we estimated beta pairwise diversity using the betapart package in R (Baselga, 2012) and the following decomposition based on Sørensen's metric: sor = sim + sne , where sor is the total beta diversity, sim is beta turnover and sne is beta nestedness. This decomposition can be adapted to the calculation of beta taxonomic and phylogenetic diversities. We first computed incidence-based pairwise dissimilarities for the beta taxonomic (composition) diversity. The beta.
pair function estimates three distance matrices: (a) turnover (replacement), (b) nestedness and (c) total dissimilarity (the sum of both components). We then computed pairwise phylogenetic dissimilarities for beta phylogenetic diversity, using the phylo.beta.
pair function which similarly estimates three distance matrices: (a) phylogenetic turnover, (b) phylogenetic nestedness and (c) the sum of both values.
Phylogenetic dissimilarities are based on Faith's phylogenetic diversity. For our analyses, we retained Simpson's beta turnover dissimilarity index ( sim ) as the most relevant. Contrary to nestedness, spatial turnover implies the replacement of some taxa by others as a consequence of environmental sorting or spatial and historical constraints (Qian et al., 2005), our focus in this study. sim values were in a matrix format (pairwise distance matrix of dissimilarities) for the 643 grid cells covering the Euro Mediterranean area. The relationships between sim taxonomic and phylogenetic matrices were explored using Mantel tests and 999 permutations (Mantel, 1967). The diversity indices of the few cells that had a surface area less than 2,500 km 2 (border cells) were calculated in the same way as those of the other cells. The spatial coordinates of a cell were those of its centroid.
Relative environmental turnover (RET) was applied to examine the relationship between environmental variables and the tree genera of the Euro-Mediterranean area, using phylogenetic and taxonomic (composition) turnover .
As with previous studies (Buckley & Jetz, 2008), we used the term environmental turnover to explore rates of change of dissimilarity by taxonomic replacement in Mediterranean tree genera and their relationship to the environment depending on geographical distances.
Then, we employed the βsim matrix to compute Nonmetric Multidimensional Scaling using the metaMDS method implemented in the R vegan packages (Oksanen et al., 2012). The metaMDS method performs Nonmetric Multidimensional Scaling (NMDS), a reduced representation rank-order ordination, and tries to find a stable solution using several random starts. In addition, it standardizes the scaling in the result, so that the configurations are easier to interpret, and adds taxa scores to the grid cell ordination. We reduced the number of dimensions to two axes, as recommended. We then fitted the environmental vectors onto the βsim ordination using the vector fitting envfit function of the vegan package in R (Oksanen et al., 2012).
The environmental variables that best explained the patterns of turnover were then displayed as vectors only for the cases with high predictability (p < . All environmental variables used are described in Appendix S3. All computations and analyses were performed using the R statistical environment (R Core Team, 2018).

| Phylogenetic diversity and endemism analyses
Rao's phylogenetic diversity coefficient was calculated using the ade4 packages in R (Thioulouse et al., 1997). Biodiverse v.2.99 (Laffan et al., 2010)  Relative Phylogenetic Diversity (RPD) and Relative Phylogenetic Endemism (RPE) are calculated as the ratios between the PD and PE obtained from the original tree and a reference tree with the same topology but with all branches of equal length (Mishler et al., 2014).
Grid cells were assessed for their phylogenetic endemism using CANAPE (Mishler et al., 2014). CANAPE is a two-step process that assesses the contribution to PE from branches that are longer or shorter than expected, for locations that are first shown to be significantly high or low in PE. The process then assesses the significance of the RPE. All cells significant for one of these tests are classified into four non-overlapping categories Mishler et al., 2014;Thornhill et al., 2016): (a) cells corresponding to centres of paleo-endemism (few taxa with long branches, significantly high RPE), (b) cells corresponding to centres of neo-endemism (few taxa with short branches, significantly low RPE), (c) cells corresponding to mixed-endemism (rare long and rare short branches, not significant for RPE but significant denominator and significant numerator, p-value < .05) and iv) cells corresponding to centres of super-endemism (rare long and rare short branches, not significant for RPE but significant denominator and significant numerator, p-value < .01). In all cases, endemism is meant at genus level.
The significance of the observed PD, PE, RPD and RPE values was assessed using non-parametric tests based on a random reassignment of all the taxa into the grid cells. The distribution of the expected values of these indices under the null hypothesis was calculated from 999 trials of the randomization procedure. Indices in the highest 2.5% or the lowest 2.5% of the distribution were considered significant (two-tailed test).
For calculating the relationship between diversity indices and environmental factors, we used the factorial design of the PCA using the FactoMineR packages in R (Lê et al., 2008) and matrix of Spearman's Rank correlation coefficient using the Hmisc packages in R (Harrell & Harrell, 2019). We also calculated the relationship between the five CANAPE categories (neo-endemism, paleo-endemism, mixed- Groups of cells showing significant PE using CANAPE were identified using an agglomerative UPGMA cluster analysis in Biodiverse v.2.99 (Laffan et al., 2010), and the range-weighted phylogenetic turnover metric . By focusing on the shared range-restricted branches, this analysis highlights geographic regions within which the evolutionary makeup of the endemic flora is relatively homogeneous (Link-Pérez & Laffan, 2018;Thornhill et al., 2017).

| Taxonomic and phylogenetic beta turnoverbiodiversity among cells and correlation with environmental factors
There was a highly significant relationship between the beta turnover taxonomic diversity and beta turnover Faith's phyloge-

| Phylogenetic diversity and environmental drivers
The Spearman's Rank correlation coefficient (Appendix S7) and fac- All biodiversity indices were significantly correlated (Appendix S7). However, while TR was highly significantly related to PD (r = .97; Appendix S9a) without scatter (as in our beta diversity analysis), PE was less significantly related to PD (r = .45; Appendix S9b), and with high scatter, indicating that PE adds information to an analysis only focusing on TR (also see the maps of TR, PD, PE, PWE and Rao in Appendix S10).

| Categorical analysis of neo-and paleoendemism (CANAPE)
Relative phylogenetic diversity divided the study area into three broad parts (Figure 3). In its western part, significantly high RPD indicating a concentration of long phylogenetic branches was found in the south of Iberian Peninsula while significantly low RPD, indicating a concentration of short phylogenetic branches, was found in the north of Iberian Peninsula (north-eastern Portugal). In its central part, significantly high RPD was in the north-eastern Italian Peninsula while significantly low RPD was in the islands (Sicily, Sardinia and Corsica) and the edges of the Italian Peninsula. In its eastern part, significantly high RPD was scattered in the north of the The range-weighed phylogenetic turnover analysis showed that the greatest dissimilarity was observed between the coast of the southern and western Iberian Peninsula, north-eastern Sicily and Crete, and the rest of the Euro-Mediterranean region which formed a discrete cluster ( Figure 6).

| Taxonomic diversity, phylogenetic diversity and environmental factors
Our results demonstrate a strong overall congruence between phylogenetic diversity (sensu Faith, 1992) and taxonomic richness of the genera of European Mediterranean trees. Although there is an expected congruence between phylogenetic and taxonomic diversity overall, strong spatial congruence is often rare because the shape of phylogenetic trees results from evolutionary processes that are not accounted for at taxonomic levels and because locally, taxonomic assemblages result from non-random ecological processes acting on regional pools (Cadotte & Tucker, 2018).
Our analysis also highlighted areas of high beta turnover taxonomic diversity (and thus of high beta turnover phylogenetic diversity) within biogeographic provinces and pointed out the environmental factors that could explain their spatial structure. While the high diversity of the southernmost and northernmost cells of our study area were correlated with many relatively recent (Holocene F I G U R E 4 Map of the major centres of phylogenetic endemism in Mediterranean Europe. Green grid cells do not show any signal of phylogenetic endemism. Red grid cells contain significantly lower Relative Phylogenetic Endemism (RPE) than expected given random sampling of the same number of taxa from a null tree, termed "centers of neo-endemism." Blue grid cells contain significantly higher RPE than expected, termed "centers of paleo-endemism." Purple grid cells are a mixture of neo-endemism and paleo-endemism, the most highly significant of which (darker purple) are termed "centers of super-endemism." Note that due to the scale of the map, not all significantly high phylogenetic endemism cells are visible F I G U R E 5 Boxplot of the distribution of the environmental variables depending on CANAPE category of each of the 643 cells analysed. The six environmental variables displayed (Coords_X, Coords_Y, Tavg, Tmin, LIG_prec and SRAD) are significantly different (Kruskal-Wallis test, p < .05) among CANAPE categories (see Table S3: p < .05; pairwise comparison using Wilcoxon test with HB correction). For each box, the bold horizontal line corresponds to the median; the lower and upper bounds of the box correspond to first and third quartiles, respectively; the upper vertical line extends from the upper bound of the box to the highest value of the distribution, no further than 1.59 interquartile range (IQR, or the distance between the first and third quartiles); the lower vertical line extends from the lower bound of the box to the lowest value of the distribution, no further than 1.59 IQR; black dots are values beyond IQR ("outlier" values) Although rarely done, the Mediterranean, with its high diversity of soil types, could be a good model to further test and understand the importance of the comparatively lesser studied edaphic variables on plant differentiation (Kruckeberg, 2004).
Such spatial patterns are known in the Mediterranean and both north-south and west-east spatial biodiversity gradients have been described before (Conord et al., 2012;Médail & Diadema, 2009;Rodríguez-Sánchez & Arroyo, 2008). The fact that longer term and older environmental variables explain the east-west spatial structure of diversity possibly indicates a longer-lasting biodiversity structure than the one opposing southern and northern areas in Mediterranean Europe (Duggen et al., 2003;Krijgsman et al., 1999).
Worldwide, latitudinal patterns in taxonomic turnover are ubiquitous and have long been known to reflect a universal latitudinal climate gradient (Darwin, 1859 -chapter 11). In this part of world, there is a strong longitudinal variation in floristic regions (Macaronesian, Mediterranean, Irano-Turanian) which is tightly related to the paleogeographic and paleoclimatic history of the Tethyan Basin (Takhtajan, 1986). Past geological events, ecological factors and evolutionary history may all have contributed to the longitudinal biodiversity pattern found here. Disentangling their importance would require a comparison with other regions where longitudinal patterns also exist, such as in Eurasia (Takhtajan, 1986).

| Identifying regions of high phylogenetic neo-and paleo-endemism
Endemic plants can be relicts or newly formed, and these two categories of endemic taxa are commonly referred to as paleo-endemics or neo-endemics, respectively (Favarger & Contandriopoulos, 1961;Stebbins & Major, 1965;Thompson, 2020). Hence, paleo-endemic taxa are ancient or relict elements of a given taxonomic group, often systematically isolated from other taxa, and neo-endemic taxa are more recently evolved and have extant sister taxa. Extending the notion of endemism to phylogenetic diversity in a spatial context, a high representation of phylogenetic paleo-endemism can be indicative of an area that has been a long-term refugium while phylogenetic neo-endemism, with an over-representation of short branches that are rare on the F I G U R E 6 Range-weighted phylogenetic turnover among those cells found to be significant centres of endemism in CANAPE, showing that the greatest dissimilarity was observed between the coast of the southern and western Iberian Peninsula, north-eastern Sicily, and Crete and the rest of the Euro-Mediterranean region. These formed a grouped cluster whereas the rest of Mediterranean region formed a discrete cluster F I G U R E 7 Map in shaded relief (Becker et al., 2009) of the biogeographical limits of the Euro-Mediterranean region following the scheme of Olson et al. (2001). (a) The location of the 52 putative refugia (green) identified by Médail and Diadema (2009) and of the 10 regional hotspots of plant biodiversity (large broken line) identified by Médail and Quézel (1997) and Vela and Benhouhou (2007). 1, High and Middle Atlas; 2, Baetic-Rifan complex; 3, Maritime and Ligurian Alps; 4, Tyrrhenian islands; 5, south and central Greece; 6, Crete; 7, south Anatolia and Cyprus; 8, Syria-Lebanon-Israel; 9, Mediterranean Cyrenaic; 10, Kabylies-Numidie-Kroumirie. (b) The location of the 76 centres of phylogenetic endemism at genus level identified in this study. Red dots indicate centres of neo-endemism, blue dots centres of paleo-endemism, purple dots centres of mixed-endemism (both neo and paleo-endemism) and dark purple dots centres of super-endemism. Dashed black lines represent the contours of the six regional hotspots of plant biodiversity that occur in Mediterranean Europe landscape, can indicate a place of recent lineage divergence with close relatives occurring in the same communities (Mishler et al., 2014), possibly due to local conditions such as specific isolated substrates.
As we deal here with tree genera, thus rather deep time phylogenetic events, areas of paleo and neo-endemism are likely to result from deep time historical events, earlier than the Tertiary (see phylogenetic tree of Cheikh . And, consequently, we may have missed more recent neo-endemism patterns such as ones that could have been detected if we had used species-level data, although tree genera are not particularly speciose in the Euro-Mediterranean region. As mentioned by Mishler et al. (2020), when a lineage is widespread outside a study region, yet rare within it, CANAPE treats it as a range-restricted lineage in the region, increasing its contribution to the endemism analyses. This is possibly the case here at the southern and eastern edges of our study area were phylogenetic paleoand neo-endemism is high, as they mark the transition with other floristic regions (Saharo-Arabian, Irano-Turanian) while still harbouring an important part of Mediterranean flora. Sampling trees only and using an ad hoc phylogeny may also result in biased phylogenetic endemism estimates (Park et al., 2018), although we consider this risk limited here as the time-calibrated phylogeny used fits well with the APGIV global plant phylogeny (Chase et al., 2016;Cheikh Albassatneh et al., 2020). Any spatial phylogenetic study that is not worldwide will display edge effects, no matter how well-done the sampling is. Here, we consider that high PE cells located at the edge of our study area have a high conservation value per se and should not be considered as artefacts because our endemism study is relative to our study area. Mediterranean Europe habitat managers will target these areas of local phylogenetic endemism as relevant high priority conservation value. in the eastern Mediterranean Basin, which mostly match regions considered as regional hotspots of plant biodiversity (Médail & Quézel, 1997;Vela & Benhouhou, 2007) and are refugia-rich in the study of Médail and Diadema (2009) (Figure 7).
In addition, eastern Sicily can also be identified as a hotspot of Amorgos) were neither detected as regional hotspots of plant biodiversity by Médail and Quézel (1997) or as refugia by Médail and Diadema (2009 Centres of paleo-endemism are associated with wet and equable climatic conditions similar to those of ancient pre-Mediterranean climates (Anacker & Harrison, 2012;Herrera, 1992;Jansson, 2003;Médail & Diadema, 2009;Raven & Axelrod, 1978). These types of humid refugia can be found at the mid-altitude (approximately 400 to 800 m altitude) and in sea level ravines such as for Phoenix theophrasti in Crete. In northern Greece, mesic ravine forest community types that are putative Pleistocene refugia, showed significantly high phylogenetic diversity compared with other forest community types (Mastrogianni et al., 2019). Such areas, less arid than the surrounding dry plains and less cold than higher elevation or latitude sites may have allowed rapid altitudinal shifts in response to climate change, in situ persistence of species and the emergence of endemism (Beug, 1975;Jansson, 2003;Sandel et al., 2011;Tzedakis et al., 2002). This is the case in many regions such as in the mountains of southern Spain (Arroyo & Marañón, 1990;Cañadas et al., 2014), Balearic Islands (Contandriopoulos & Cardona, 1984) and Studies of the California flora concluded that neo-endemic centres were in regions with relatively young Mediterranean climate and high relative geomorphological heterogeneity (Lancaster & Kay, 2013;Raven & Axelrod, 1978;Stebbins & Major, 1965). From a phylogenetic point of view, neo-endemics result from recent in situ differentiation. Worldwide, closely related neo-endemics are usually found in the same area or in adjacent regions, often constituting groups of vicarious taxa (Cowling & Holmes, 1992;Kruckeberg, 2004). Thus, centres of neo-endemism are more related to harsher environmental conditions (Cacho & Strauss, 2014;Verdú & Pausas, 2013) and to high topographical relief encouraging spatial divergence (Crisp et al., 2001;Molina-Venegas et al., 2015Vetaas & Grytnes, 2002). We identified only a few areas of phylogenetic neo-endemism in the Euro-Mediterranean region, located in the high topographical relief and high geological activity zones of eastern Sicily and southern Corsica.

| CON CLUS ION
Low climate change velocity areas, with continuous warm-wet climates, contain high phylogenetic diversity and endemism in the Mediterranean. Using phylogenetic endemism as an indicator, we confirm the high conservation value of: (a) the Aegean islands where several types of phylogenetic endemism were found, demonstrating long-lasting evolutionary processes, (b) eastern Sicily as a cradle of neo-endemism, (c) Cyprus as a museum of paleo-endemism, and (d) coastal southwest Portugal, the southern and eastern regions of the Iberian Peninsula, and Crete for mixed-endemism.
We demonstrate that trees of the Euro-Mediterranean region show clear patterns in the spatial distribution of their evolutionary heritage. We confirm that the southern large peninsulas and the islands of this region are regional hotspots of taxonomic richness, phylogenetic diversity and phylogenetic endemism. We identify several islands of the Dodecane and Cyclades, the Belasca mountains in Bulgaria and northern Greece as areas of yet undetected high conservation value for their phylogenetic endemism. Future research should test whether protected areas actually fully encompass these phylogenetically rich areas.

CO N FLI C T O F I NTE R E S T
The authors have no competing interests to declare.

PE E R R E V I E W
The peer review history for this article is available at https://publo ns.com/publo n/10.1111/ddi.13241.

DATA AVA I L A B I L I T Y S TAT E M E N T
All data are available open access, as indicated in the manuscript.