Marion Chartier
email: chartier.marion@gmail.com

Maria Von Balthazar

Susanne Sontag

Stefan Löfstrand

Thomas Palme

Florian Jabbour

Hervé Sauquet

Jürg Schönenberger
email: schoenenberger@univie.ac.at

Global patterns and a latitudinal gradient of flower disparity: perspectives from the angiosperm order Ericales

Keywords: Angiosperms, biodiversity, Ericales, flower morphology, latitudinal gradient, morphospace, disparity, diversity

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Life on Earth is distributed unevenly due to varied geological and climatic conditions over time and space. In addition to these abiotic conditions, dynamics of speciation, extinction, migration and biotic interactions likely play important roles in shaping species richness and species composition in different regions and communities [START_REF] Gaston | Global patterns in biodiversity[END_REF][START_REF] Jablonski | Shaping the latitudinal diversity gradient: new perspectives from a synthesis of paleobiology and biogeography[END_REF][START_REF] Schluter | Speciation gradients and the distribution of biodiversity[END_REF]. Generally, species richness decreases with altitude, ocean depth, and latitude [START_REF] Vamosi | Key innovations within a geographical context in flowering plants: towards resolving Darwin's abominable mystery[END_REF][START_REF] Hillebrand | On the generality of the latitudinal diversity gradient[END_REF][START_REF] Kerkhoff | The latitudinal species richness gradient in New World woody angiosperms is consistent with the tropical conservatism hypothesis[END_REF][START_REF] Brown | Why are there so many species in the tropics?[END_REF][START_REF] Tomašových | Unifying latitudinal gradients in range size and richness across marine and terrestrial systems[END_REF][START_REF] Jablonski | Shaping the latitudinal diversity gradient: new perspectives from a synthesis of paleobiology and biogeography[END_REF]. In particular, the origin and unevenness of the latitudinal gradient of species richness has generated extensive debates, and many potential explanatory factors have been proposed including temperature, climate stability, biotic interactions, and available energy (e.g. mean summer temperature). As a general trend, all of these factors increase towards tropical latitudes [START_REF] Jablonski | Shaping the latitudinal diversity gradient: new perspectives from a synthesis of paleobiology and biogeography[END_REF][START_REF] Brown | Why are there so many species in the tropics?[END_REF][START_REF] Pianka | Latitudinal gradients in species diversity: a review of concepts[END_REF][START_REF] Rohde | Latitudinal gradients in species diversity: the search for the primary cause[END_REF][START_REF] Mittelbach | Evolution and the latitudinal diversity gradient: speciation, extinction and biogeography[END_REF][START_REF] Mannion | The latitudinal biodiversity gradient through deep time[END_REF][START_REF] Belmaker | Relative roles of ecological and energetic constraints, diversification rates and region history on global species richness gradients[END_REF][START_REF] Fine | Ecological and evolutionary drivers of geographic variation in species diversity[END_REF][START_REF] Pontarp | The latitudinal diversity gradient: novel understanding through mechanistic eco-evolutionary models[END_REF].

In addition to species number, biodiversity includes aspects such as phylogenetic diversity, morphological diversity, dominance and rarity of species as well as the diversity of their ecosystem functions [START_REF] Hillebrand | Biodiversity change is uncoupled from species richness trends: Consequences for conservation and monitoring[END_REF][START_REF] Stevens | A latitudinal gradient in dimensionality of biodiversity[END_REF]. On a global scale, our knowledge about these additional aspects is fragmentary at best [START_REF] Gaston | Global patterns in biodiversity[END_REF]. In particular, we still have only a very limited understanding of the geographic and ecological distribution of functional and of morphological diversities (for plants see e.g. [START_REF] Hillebrand | Biodiversity change is uncoupled from species richness trends: Consequences for conservation and monitoring[END_REF][START_REF] Lupia | Discordant morphological disparity and taxonomic diversity during the Cretaceous angiosperm radiation: North American pollen record[END_REF][START_REF] Swenson | The functional ecology and diversity of tropical tree assemblages through space and time: from local to regional and from traits to transcriptomes[END_REF][START_REF] Cornwell | Functional distinctiveness of major plant lineages[END_REF][START_REF] Chartier | The floral morphospace -a modern comparative approach to study angiosperm evolution[END_REF][START_REF] Zanne | Three keys to radiation of angiosperms into freezing environments[END_REF][START_REF] Chartier | How (much) do flowers vary? Unbalanced disparity among flower functional modules and a mosaic pattern of morphospace occupation in the order Ericales[END_REF][START_REF] Mander | The latitudinal distribution of morphological diversity among Holocene angiosperm pollen grains from eastern North America and the Neotropics[END_REF][START_REF] Weiser | Taxonomic decomposition of the latitudinal gradient in species diversity of North American floras[END_REF]. Functional diversity summarises traits predicting growth and survival rates (for plants: [START_REF] Cornwell | Functional distinctiveness of major plant lineages[END_REF][START_REF] Swenson | Ecological and evolutionary determinants of a key plant functional trait: wood density and its community-wide variation across latitude and elevation[END_REF][START_REF] Swenson | The biogeography and filtering of woody plant functional diversity in North and South America[END_REF], while morphological diversity, also called disparity, is used to quantify and compare the variability of organisms belonging to a clade, or a group of taxa [START_REF] Foote | Morphological diversity in the evolutionary radiation of Paleozoic and post-Paleozoic crinoids[END_REF][START_REF] Erwin | Disparity: morphological pattern and developmental context[END_REF][START_REF] Minelli | Species diversity vs. morphological disparity in the light of evolutionary developmental biology[END_REF].

Disparity is calculated from a multidimensional set of morphological traits and can be estimated by different indices such as, for example, the range (the largest difference between two taxa in a group), the total variance (the sum of variances of all characters), or the mean character difference (the average difference among taxa in a group; [START_REF] Erwin | Disparity: morphological pattern and developmental context[END_REF][START_REF] Foote | Morphological diversity in the evolutionary radiation of Paleozoic and post-Paleozoic crinoids[END_REF][START_REF] Wills | Disparity as an evolutionary index: a comparison of Cambrian and recent arthropods[END_REF][START_REF] Ciampaglio | Detecting changes in morphospace occupation patterns in the fossil record: characterization and analysis of measures of disparity[END_REF]. The choice of disparity index depends on sample size, number and type of traits, and on the proportions of missing data in the morphological matrix [START_REF] Ciampaglio | Detecting changes in morphospace occupation patterns in the fossil record: characterization and analysis of measures of disparity[END_REF].

Furthermore, the interpretation of disparity patterns strongly depends on the phylogenetic and geographic scale investigated, and, importantly, on the biological functions of the traits disparity estimates are based on.

For angiosperms, a central aspect of structural and functional diversity lies in the richness of biotic interactions and reproductive strategies, both of which are largely tied to their reproductive units, i.e. their flowers. Flowers produce and protect the gametes, they are the place for pollination and fertilization, and, finally, they produce fruits and seeds that disperse and propagate. Most angiosperms are pollinated by animals and their sexual reproduction is thus tightly linked to plantpollinator interactions. Changes in floral morphology, therefore, directly affect fitness and can also lead to speciation through reproductive isolation [START_REF] Grant | Modes and origins of mechanical and ethological isolation in angiosperms[END_REF]Harder & Barrett, 2006;[START_REF] Reyes | Presence in Mediterranean hotspots and floral symmetry affect speciation and extinction rates in Proteaceae[END_REF][START_REF] Baack | The origins of reproductive isolation in plants[END_REF].

Floral disparity and its distribution have rarely been quantified (reviewed in [START_REF] Chartier | The floral morphospace -a modern comparative approach to study angiosperm evolution[END_REF].

For the large, diverse, and globally distributed angiosperm order Ericales [START_REF] Rose | Phylogeny, historical biogeography, and diversification of angiosperm order Ericales suggest ancient Neotropical and East Asian connections[END_REF], we have earlier shown that, with some exceptions, clade disparity generally increases with clade species richness. We also found that floral disparity was not correlated with clade crown age [START_REF] Chartier | How (much) do flowers vary? Unbalanced disparity among flower functional modules and a mosaic pattern of morphospace occupation in the order Ericales[END_REF]. The two families accounting for most of the disparity in the order were Lecythidaceae (16% partial disparity; Brazil nut family) and Sapotaceae (14% partial disparity; shea tree family), corresponding to 3% and 9%, respectively, of the order's species richness [START_REF] Chartier | How (much) do flowers vary? Unbalanced disparity among flower functional modules and a mosaic pattern of morphospace occupation in the order Ericales[END_REF]. Plants in both tropical families typically grow as trees, the flowers of which are most probably pollinated by diverse types of animals [START_REF] Kubitzki | The families and genera of vascular plants[END_REF]. It is thus likely that, in addition to species richness, patterns of floral disparity in the order are partly shaped by ecological and geographical factors. Here, we investigate whether there is a latitudinal gradient of floral disparity in Ericales. As outlined above, we might expect such a gradient because biotic interactions are more diverse, and species richness is higher in the tropics. In addition, we investigate and compare the variation of floral disparity among climate types, geographic regions, ecosystems (type of habitat), and life modes (plant growth form) to find other potential factors explaining global patterns of floral disparity in Ericales.

Material and methods

All analyses were performed using the software R v.3.0.0 [START_REF] Core | R: A language and environment for statistical computing[END_REF]. Functions are referred to in the following format: function name{package name}. A more detailed version of these methods is available as Supplementary Information (SI).

Taxon sampling

We used the taxon sampling from [START_REF] Chartier | How (much) do flowers vary? Unbalanced disparity among flower functional modules and a mosaic pattern of morphospace occupation in the order Ericales[END_REF]. This dataset describes 380 species belonging to 274 genera (79.5 % of the 346 genera of Ericales), sampled across the 22 families of Ericales [START_REF] Rose | Phylogeny, historical biogeography, and diversification of angiosperm order Ericales suggest ancient Neotropical and East Asian connections[END_REF][START_REF] Schönenberger | Molecular phylogenetics and patterns of floral evolution in the Ericales[END_REF]. Our aim was to give the best representation possible of each taxonomic group, and of the morphological variation found in the whole order.

Morphological matrix

To estimate morphological diversity (disparity), we used the morphological dataset from [START_REF] Chartier | How (much) do flowers vary? Unbalanced disparity among flower functional modules and a mosaic pattern of morphospace occupation in the order Ericales[END_REF]. This dataset consists of 36 morphological characters describing the anthetic flower for all sampled species. The data were scored using the database PROTEUS [START_REF] Sauquet | PROTEUS: A database for recording morphological data and fossil calibrations[END_REF]. The morphological matrix contains a total of 12,512 data entries (13.4 % missing data) and is available in the online supplementary material of [START_REF] Chartier | How (much) do flowers vary? Unbalanced disparity among flower functional modules and a mosaic pattern of morphospace occupation in the order Ericales[END_REF].

Factor matrix

All sampled species were additionally coded for the four following factors: growth form, habitat, climate type, and region. In this manuscript, we use abridged expressions such as « floral disparity of trees », which should be understood as « floral disparity in species displaying an arborescent growth form ».

For each factor, the assignment of each species to one or more categories was made retrieving information from the literature cited in [START_REF] Chartier | How (much) do flowers vary? Unbalanced disparity among flower functional modules and a mosaic pattern of morphospace occupation in the order Ericales[END_REF], and by crossing this information with the maps and descriptions from [START_REF] Cox | The biogeographic regions reconsidered[END_REF], [START_REF] Peel | Updated world map of the Köppen-Geiger climate classification[END_REF], and [START_REF] Loarie | The velocity of climate change[END_REF]. This new dataset is available as SI ("Dataset.xlsx") and stored in the online database PROTEUS [START_REF] Sauquet | PROTEUS: A database for recording morphological data and fossil calibrations[END_REF], with at least one bibliographic reference linked to each entry. It contains 1,800 new data entries (3.6 % missing data).

We divided the factor growth form into the five categories occurring in Ericales [START_REF] Kubitzki | The families and genera of vascular plants[END_REF]): We defined habitat factor categories by taking the biome descriptions from [START_REF] Loarie | The velocity of climate change[END_REF], and simplifying them into the three habitat states: [1] forests, [2] open habitats, and [3] wet habitats (including mangroves and flooded forests/grassland/savannahs).

For the factor climate type (Fig. 1a), we used the Köppen-Geiger climate classification based on temperature and precipitation, applying the five main categories described in [START_REF] Peel | Updated world map of the Köppen-Geiger climate classification[END_REF]: and [5] polar (see SI section 1.2). Tropical high elevation species were coded as temperate.

[1] tropical, [2] arid, [3] temperate, [4] cold,
Finally, we divided the factor region into Pacific,and [6] Australia. We followed the revised biogeographical delimitations of Floral Kingdoms as suggested by [START_REF] Cox | The biogeographic regions reconsidered[END_REF] for continent delimitations. Each species was assigned to its native region(s) only.

[1] North America, [2] Eurasia, [3] South America, [4] Africa, [5] Indo-

Disparity

We computed floral disparity ( ) for the different factor categories of taxa (e.g. trees from factor growth form) using the morphological matrix. From this matrix, we first created a distance matrix by calculating a dissimilarity index for each pair of taxa: the mean character difference (D), following [START_REF] Sneath | Numerical taxonomy. The principles and practice of numerical classification[END_REF][START_REF] Sneath | Numerical taxonomy. The principles and practice of numerical classification[END_REF][START_REF] Foote | Morphological diversity in the evolutionary radiation of Paleozoic and post-Paleozoic crinoids[END_REF]. is a version of the Gower index, suited for datasets like ours that contain at the same time continuous, categorical ordered, categorical unordered, and binary data. The detailed calculation of is given in [START_REF] Chartier | How (much) do flowers vary? Unbalanced disparity among flower functional modules and a mosaic pattern of morphospace occupation in the order Ericales[END_REF].

Disparity ( ) was then estimated for a category as the mean pairwise dissimilarity ( = the average D) among all taxa from that category [START_REF] Foote | Morphological diversity in the evolutionary radiation of Paleozoic and post-Paleozoic crinoids[END_REF], by averaging distances in the distance matrix for all taxa belonging to that category. The mean pairwise dissimilarity is less sensitive to large differences in group sizes than other disparity estimations such as for example the range [START_REF] Ciampaglio | Detecting changes in morphospace occupation patterns in the fossil record: characterization and analysis of measures of disparity[END_REF]; this makes it well suited to our data.

There are two types of polymorphism in our data: [1] polymorphism in the morphological matrix (2.2 %), [2] polymorphism in the factor matrix (16.5 %). [1] As our calculation method of cannot take polymorphism into account in the morphological dataset, and since the percentage of polymorphism in this matrix is very low, a morphological matrix without polymorphism was randomly sampled and the distance matrix was re-computed prior to each computation of and each test (see below). This did not impact our results (data not shown). [2] Some species belong to several factor categories (for example, some species grow in temperate as well as in cold areas).

When computing disparity for these categories, such species were included in each of these categories (but not when performing tests, see below).

For each factor, we compared among factor categories (for example among all growth form categories) with one-way permutation ANOVAs (analyses of variance) on the morphological distance matrix. This analysis consists of comparing the F-ratio of the dataset to the distribution of the F-ratio calculated for 9,999 permutations of the dataset. For each permutation, a random morphology ˗ row in the matrix ˗ is assigned to each species without replacement. For the F-ratio formula, see Hawkins (2014 p. 167). In our case, a permutation test is preferable to an ANOVA or a Kruskal-Wallis test, because we compare pairwise distances whereby each species contributes to multiple distance values, creating a lack of independence among values and inflating the degrees of freedom. As post hoc tests, we made pairwise comparisons of among factor categories with permutation tests on central tendencies following Bonnini et al. (2014). This test consists, for a pair of categories, of calculating the difference (here noted T) between the average D of each category, and compare it to the distribution of T calculated for 9,999 permutations of the dataset without replacement (like described above). We applied a Bonferroni correction for multiple comparisons to these post hoc tests. To deal with polymorphism in the factor matrix (the grouping variables of these tests), a factor matrix without polymorphism was randomly sampled and each permutation ANOVA and corresponding post hoc tests performed 100 times; p-values and statistics for each test are thus presented as an average ± standard deviation (SD) over these 100 calculations. To save execution time, calculations were ran in parallel on multiple computer cores using packages foreach (Microsoft Corp. & Weston, 2020), parallel (R Core Team 2016) and doParallel (Microsoft Corp. & Weston, 2019). Finally, for these tests, we excluded the category root parasitic (n = 2) from factor growth form.

Associations among factor categories

We performed a series of chi-squared tests to investigate associations among categories belonging to different factors and detect ecological/biogeographic trends in Ericales (e.g. do arborescent species more often grow in tropical areas?, i.e. is there an association between categories tree from factor growth form, and tropical from factor climate?).

To meet the chi-squared test criteria, and for these analyses only, we merged the categories polar (n = 7 species) and cold (n = 56) from factor climate, and excluded the category root parasitic (n = 2) from factor growth form. Associations were not tested among categories belonging to the same factors.

We performed the chi-squared tests using chisq.test{stats}. For significant tests (p < 0.05), the strength of the association was estimated from the Pearson residuals (PR; [START_REF] Hawkins | Biomeasurement: a student's guide to biological statistics[END_REF]. Multiple correlations are usually visualized using a correlation table (SI section 1.3). To visualize multiple correlations more easily and detect clusters of associated factor categories, we plotted these categories with a non-metric multidimensional scaling (nMDS) applied to a distance matrix computed from the PR values among categories, using metaMDS{vegan} with the Bray-Curtis distance [START_REF] Anderson | A new method for non-parametric multivariate analysis of variance[END_REF][START_REF] Oksanen | vegan: Community; Ecology Package. R package version 2[END_REF]; SI sections 1.3). This allowed us to draw an association network in which significantly positively associated categories fall close to each other and are linked by red lines, whereas significantly negatively associated categories fall far from each other and are linked by blue lines (Fig. 3). Inter-correlated categories appear linked together on that graph (clusters).

Variation of disparity accounting for associations among factor categories

Some factor categories are significantly associated with one another (see Results). Comparing disparity among categories for each factor independently might thus lead to ambiguous interpretations about the link between these factors and variation in disparity.

We solved this issue by first (i) keeping one factor constant while looking at the variation of disparity for the others (e.g. is there a difference among the climate categories if we look at trees only?). This was, however, only possible in a few cases that we report in the text, since category sizes become small once splitand once polymorphism is sampled; all trends are shown in SI section 2.3. We furthermore (ii) calculated disparity for the two clusters of associated factor categories identified from the association network representation (Fig. 3). was in that case calculated for a given cluster by including all species belonging to the intersection of each factor and, within factors, the union of each category. For example, if a cluster is composed of the categories tropical and temperate (from factor climate), and shrub (from factor growth form), all tropical shrubs and temperate shrubs were included in the calculation of for that cluster. This is a strict representation of these clusters as more species might present some of but not all the characteristics of each cluster. We compared disparity between the two clusters with a permutation test on central tendencies as described above, with 99,999 permutations without replacement.

Latitudinal distribution of species and disparity

We estimated the latitudinal distribution of the species from the dataset by extracting location records (latitude and longitude) from the Global Biodiversity Information Facility online database (GBIF, https://www.gbif.org/) using occ_search{rgbif} [START_REF] Chamberlain | rgbif: Interface to the Global[END_REF]; SI section 1.4).

Distribution maps (SI section 3) were then plotted using the package maptools [START_REF] Bivand | maptools: Tools for Reading and Handling Spatial Objects[END_REF] and manually checked for atypical and non-native records by using data from the literature and online trustworthy websites (such as the IUCN website, http://www.iucnredlist.org/). This allowed us to estimate the presence/absence of 347 (91 %) of the study species in each tendegree latitude interval across the globe (see also SI section 2.5).

Disparity ( ) was then calculated for the species occurring in each given latitude interval. Finally, we tested for the correlations between latitude and species richness, latitude and disparity, and species richness and disparity (for each latitudinal interval) with Pearson correlation tests using cor.test{stats} and lm{stats}. For these tests, latitude values were treated as absolute values, to represent distances (north or south) from the Equator.

An additional permutation test was performed to show that the observed latitudinal variation in disparity was not due to the latitudinal variation in species number (SI section 2.4).

Results

Variation of floral disparity

Floral disparity ( ) significantly differed among categories of growth forms (excluding the two root parasitic species from the analysis; permutation ANOVA: F = 485.43 ± SD92.59, p = 7.00•10 -5 ± SD1.43•10 -4 ), habitat types (F = 366.00 ± 75.26, p = 9.55•10 -4 ± 1.50•10 -3 ), climate types (F = 382.51 ± 67.98, p = 7.00•10 -5 ± 1.26•10 -4 ), and regions (F = 101.43 ± 67.98, p = 0.017 ± 0.008).

Post hoc tests are summarized by red letters in Fig. 2 and the main trends of variation are described below.

Growth form. Overall (i.e. when including the entire dataset in the analysis), disparity decreased slightly from trees ( = 0.225 ± SD 0.090) to herbs and aquatic herbs ( = 0.201 ± 0.101), lianas and climbers ( = 0.189 ± 0.101) and shrubs ( = 0.182 ± 0.082; Fig. 2a). The two root parasitic species sampled (Mitrastemon matudae and M. yamamotoi) were not included in the analyses and only differed from each other in their number of carpels. To get around potential correlations among factors (e.g. growth form and climate), we compared the disparity of growth forms within each category of the other factors. For example, we investigated whether, when looking at tropical species only, trees were still showing more disparity than the other growth form categories. We did so for each category of the factors climate, habitat and region (SI section 2.3). The general pattern of disparity variation among growth forms was recovered within categories forest (from factor habitat) and South America (from factor region). Although not significantly, the tendency for trees to display the highest disparity was retreaved within all factor categories (SI section 2.3).

Habitat. Overall, floral disparity was highest in forests ( = 0.231 ± SD 0.093), intermediate in wet habitats ( = 0.211 ± 0.091), and lowest in open habitats ( = 0.192 ± 0.085; Fig. 2b). This result was only recovered within category South America (from factor region; SI section 2.3).

Climate: Overall, tropical species ( = 0.238 ± SD 0.097) displayed the highest level of floral disparity, followed by species distributed in arid ( = 0.196 ± 0.101) and temperate ( = 0.196 ± 0.085) areas (Fig. 2c). Disparity in cold ( = 0.186 ± 0.086) and polar areas ( = 0.090 ± 0.050) did not significantly differ from the other categories. The decrease of floral disparity from tropical to temperate climate categories held within categories tree (from factor growth form) and Africa (from factor region), and was only a tendency for category forest (factor habitat, SI section 2.3).

Within category South America (factor region), floral disparity was higher for tropical species than for arid species. Although not significantly, the tendency for disparity to decrease from tropical, to temperate, to cold and polar climate categories was retreaved within all factor categories but one (SI section 2.3).

Region. Overall, disparity was highest for African species ( = 0.245 ± SD 0.107). South American ( = 0.222 ± 0.101), Indo-Pacific ( 0.217 ± 0.081), and Eurasian ( = 0.215 ± 0.083) species displayed similar lower levels of disparity. North American ( = 0.176 ± 0.0.86) and Australian ( = 0.134 ± 0.087) species displayed the lowest levels of disparity (Fig. 2d). This trend was only recovered for the category forest of factor habitat (SI section 2.3).

Variation of floral disparity when combining factor categories

We found significant associations among categories for each pair of factors (Table 1). Post hoc test details are illustrated in Fig. 3a.

Our data show two clusters of associated categories that describe two large groups of species sharing particular ecological/biogeographic trends in Ericales (Fig. 3a). Cluster 1 corresponds to species belonging to the categories forest (factor habitat), tropical (factor climate), tree (factor growth form), and Africa or South America (factor region). Cluster 2 corresponds to species belonging to the categories open habitat, or wet habitat (factor habitat), temperate, arid, or cold and polar (factor climate), herbs and aquatic herbs, or shrubs (factor growth form), and North America or Eurasia (factor region). Species strictly representing Cluster 1 (n = 76) showed significantly higher (26 %) floral disparity ( = 0.247 ± SD 0.108) than those (n = 65) representing

Cluster 2 ( = 0.169 ± 0.082; permutation test on central tendency: T = 0.0782, p = 0; Fig. 3b).

Note that there was no significant association in our dataset for categories liana and Indo-Pacific to any other category.

Latitudinal distribution of species richness and disparity.

The estimated species richness and floral disparity both significantly decreased towards the poles (Figs. 1b, 4a, and4b). Species richness peaked in the subtropical area of the northern hemisphere and near the equator, between latitudes 40° and 20° (113 species), and between latitudes 0° and 10° (124 species; Fig. 1b), and steeply decreased with latitude (r = -0.78, p < 10 -5 ; linear regression: intercept = 103.7, slope coefficient = -1.336, Fig. 4a). On the other hand, disparity peaked in the southern hemisphere, between latitudes -10° and -20° ( = 0.266 ± SD 0.105; Fig. 1b). It decreased with latitude (r = -0.77, p = 0.001; linear regression: intercept = 0.26, slope coefficient = -0.002), with a weak decrease towards the North Pole, and a steeper decrease towards the South Pole (Figs. 1b and4b). This correlation held when removing the three latitudinal intervals containing five species or less (r = -0.90, p < 10 -3 ).

There was no clear correlation between disparity and species richness. A weak positive correlation is due to three latitudinal intervals each containing only 5 species or less (r = 0.63, p = 0.015) and this correlation disappears when these intervals are not included (r = 0.33, p = 0.329; Fig. 4c). The permutation test we performed also showed that the increase of disparity near the equator was not due to the higher number of species present at these latitudes (SI section 2.4).

Discussion

Our results indicate that, in the order Ericales, floral disparity is significantly higher in the tropics than in other climate zones. Both floral disparity (morphological diversity) and species richness increase with lower latitudes. However, floral disparity is highest in southern tropical seasonal forests, while species richness is higher in northern tropical and subtropical latitudes (Fig. 1). In a previous study, we used the same morphological dataset to investigate changes in disparity across floral modules and among ericalean lineages [START_REF] Chartier | How (much) do flowers vary? Unbalanced disparity among flower functional modules and a mosaic pattern of morphospace occupation in the order Ericales[END_REF]. We showed that flower morphology differed among Ericalean clades, that these clades filled the morphospace in a mosaic pattern, and that clade floral disparity increased with clade size, albeit with notable exceptions, e.g.

Balsaminaceae (touch-me-not family) and Sapotaceae (shea tree family). Disparity was not correlated to clade crown age and there was no phylogenetic pattern of distribution of disparity among families, suggesting that there are other factors that drive variations in floral disparity in the Ericales [START_REF] Chartier | How (much) do flowers vary? Unbalanced disparity among flower functional modules and a mosaic pattern of morphospace occupation in the order Ericales[END_REF]. The present analyses show that different categories of growth form, region, climate type and habitat show slightly different levels of disparity (Fig. 2). These factor categories are inter-correlated, which renders their respective effects on disparity variations difficult to separate at this taxonomic scale and given the structure of the order Ericales (see discussion below). Nevertheless, there is a strong signal that, in Ericales, tropical trees growing in forests of Africa and South America (among them the speciose and very diverse family Lecythidaceae) show higher floral disparity than other Ericalean representatives (Fig. 3).

Contrary to species richness, disparity is a complex and subjective measure of biodiversity, as it can be estimated from many different combinations of traits. As a consequence, trends in disparity variation will not always reflect the same evolutionary or biogeographic processes and will strongly depend on the ecological or physiological function of the measured traits. For example, no latitudinal gradient was found for the disparity of moth wing ornamentation in the New World, because this trait is under strong selective pressure to match resting backgrounds and avoid predators at all latitudes [START_REF] Ricklefs | Aspect diversity in moths revisited[END_REF]. For plants, there is also no latitudinal gradient in pollen ornamentation disparity [START_REF] Mander | The latitudinal distribution of morphological diversity among Holocene angiosperm pollen grains from eastern North America and the Neotropics[END_REF]: currently, it is still unclear which of the measured morphological pollen traits are adaptive and thus whether variation in these traits is driven by chance, taxonomy, or reflects evolutionary processes [START_REF] Lupia | Discordant morphological disparity and taxonomic diversity during the Cretaceous angiosperm radiation: North American pollen record[END_REF][START_REF] Mander | A combinatorial approach to angiosperm pollen morphology[END_REF][START_REF] Mander | The latitudinal distribution of morphological diversity among Holocene angiosperm pollen grains from eastern North America and the Neotropics[END_REF]. In contrast, it has been found that tree functional diversity is higher at low latitude and in tropical seasonal forests across North and South America [START_REF] Swenson | Ecological and evolutionary determinants of a key plant functional trait: wood density and its community-wide variation across latitude and elevation[END_REF][START_REF] Swenson | The biogeography and filtering of woody plant functional diversity in North and South America[END_REF], but see Lamanna et al., 2014). The measured traits predict plant growth and survival rates and thus reflect the demographic dynamics of plant communities. These results indicate that an increase in functional diversity may be promoted in regions where abiotic selective constraints are weaker, and where biotic interaction rates and niche partitioning are more important, triggering morphological differentiation [START_REF] Swenson | Ecological and evolutionary determinants of a key plant functional trait: wood density and its community-wide variation across latitude and elevation[END_REF][START_REF] Swenson | The biogeography and filtering of woody plant functional diversity in North and South America[END_REF].

Our analysis of floral trait points towards a role of climate as well as latitude in floral disparity patterns, probably linked to biotic interactions. For example, the most variable traits in Ericales flowers are petal union and stamen types, both linked to functional aspects of pollination biology [START_REF] Chartier | How (much) do flowers vary? Unbalanced disparity among flower functional modules and a mosaic pattern of morphospace occupation in the order Ericales[END_REF]. Biotic interactions directly impacting floral evolution are mainly due to pollinators. About 88 % of angiosperms are pollinated by animals, and this proportion has been estimated to be as high as 99 % at tropical latitudes [START_REF] Regal | Pollination by wind and animals: ecology of geographic patterns[END_REF][START_REF] Bawa | Plant-Pollinator Interactions in Tropical Rain Forests[END_REF][START_REF] Ollerton | How many flowering plants are pollinated by animals?[END_REF]. Several studies investigating plant clades and pollination networks have also brought forward evidence for an increase in plant-pollinator interaction dynamics in the tropics. For example, it has been shown that the number of different pollination systems increases towards the tropics, probably because tropical areas contain a broader diversity of functional groups of pollinators including taxa such as bats, birds or primates [START_REF] Ollerton | Geographical Variation in Diversity and Specificity of Pollination Systems[END_REF], but see Schleuning et al., 2012). In addition, it has been shown that interactions with pollinators are more specialized in the tropics (Trojelsgaard & Oleson, 2013). These combined factors explain possible selection for a higher number of floral traits adapted to specific pollinators in the tropics. Among the many different pollination systems that have been described in Ericales, some are found across all latitudes (e.g. pollen/nectar collecting bees, flies), but many are indeed unique to the tropics (bats, Euglossini bees, squirrels/flying squirrels) or at least more diverse in the tropics (moths, birds, hummingbirds, mammals; [START_REF] Sazima | The Bizarre Inflorescence of Norantea brasiliensis (Marcgraviaceae): Visits of Hovering and Perching Birds[END_REF][START_REF] Endress | Diversity and evolutionary biology of tropical flowers[END_REF][START_REF] Yumoto | A new pollination syndrome-Squirrel pollination in a tropical rainforest in Lambir Hills National Park, Sarawak, Malaysia[END_REF][START_REF] Kubitzki | The families and genera of vascular plants[END_REF]. Exceptions to this pattern might occur in biodiversity hotspots (South Africa, the Mediterranean area), although we do not observe a particular peak in floral disparity for the corresponding latitudes in our dataset (Fig 1). Note that wind pollination is of lesser importance in Ericales (it is found e.g. in Ericaceae -heath family-in the genus Erica and the tribe Empetreae, and in Actinidiaceae -kiwifruit tree family-in the genus Actinicia; [START_REF] Kubitzki | The families and genera of vascular plants[END_REF].

The general increase in disparity towards tropical latitudes that we observe in our data may be partly due to the diverse pollination systems in the largely tropical families Lecythidaceae (bees, bats, beetles; [START_REF] Kubitzki | The families and genera of vascular plants[END_REF], Sapotaceae (insects, bats, squirrels/flying squirrels; see below), Primulaceae p.p. (oil bees; [START_REF] Buchmann | The ecology of oil flowers and their bees[END_REF]. In contrast to this, it has also been shown elsewhere that species-rich tropical lineages (or assemblages) can show very little floral variation if all or most of their species are pollinated by animals from the same functional pollinator group. This is for instance the case in the tropical trees from the large genus Myrcia (Myrtaceae, Myrtales; Vasconcelos et al., 2018) bearing morphologically homogeneous, inconspicuous and unspecialized flowers pollinated by bees. Delmas et al. ( 2020) also showed that tropical and temperate/subtropical assemblages of woody species in Australia mostly produce small whitish generalist flowers probably pollinated by insects including thrips, flies and small beetles. In our dataset, Sapotaceae also mostly bear small white flowers [START_REF] Kubitzki | The families and genera of vascular plants[END_REF], but is one of the most variable families in the order when looking at other floral traits than color [START_REF] Chartier | How (much) do flowers vary? Unbalanced disparity among flower functional modules and a mosaic pattern of morphospace occupation in the order Ericales[END_REF].

As far as known, this family is pollinated by bats [START_REF] Cleghorn | Observations on the bat-flowers of the Mohwa (Bassia latifolia)[END_REF][START_REF] Van Der Pijl | Fledermauseund Blumen[END_REF][START_REF] Nathan | Bat foraging strategies and pollination of Madhuca latifolia (Sapotaceae) in Southern India[END_REF], squirrels and flying squirrels [START_REF] Yumoto | A new pollination syndrome-Squirrel pollination in a tropical rainforest in Lambir Hills National Park, Sarawak, Malaysia[END_REF], and insects [START_REF] Basga | Foraging and pollination activity of Xylocopa olivacea (Hymenoptera: Apidae) on Vitellaria paradoxa (Sapotaceae) flowers at Ouro-Gadji (Garoua, Cameroon)[END_REF] and shows high variation in e.g. petal and petal whorl numbers, stamen and stamen whorl numbers, and types of staminodes.

The presence of generalist systems in the tropics, leading to the evolution of lineages bearing homogeneous (e.g. small and white) flowers is not incompatible with an overall pollination-driven increase of floral disparity in the tropics. In our dataset, the morphospace area occupied by cold/temperate species and the area occupied by tropical species largely overlap, the area occupied by tropical species being larger (SI section 2.2). The morphological diversity of tropical ericalean flowers encompasses the diversity of the order as whole and exceeds that of non-tropical species.

This is in agreement with the general observation that floral diversity is broadest in the tropics (e.g. [START_REF] Endress | Diversity and evolutionary biology of tropical flowers[END_REF]. It also implies that there are no specific floral morphologies related to cold/temperate zones, pointing towards the absence of large-scale patterns of morphological convergence. Our data rather indicate a release of constraints in the tropics, expressed in the occupation of large areas of the floral morphospace by certain phylogenetic lineages. In particular, two tropical families increase the total area of the ericalean floral morphospace: (i) Lecythidaceae, a medium-sized family presenting the highest floral disparity in Ericales, and (ii) Sapotaceae, a very speciose homogeneous group, but whose unique combinations of floral features place the family in the periphery of the morphospace [START_REF] Chartier | How (much) do flowers vary? Unbalanced disparity among flower functional modules and a mosaic pattern of morphospace occupation in the order Ericales[END_REF].

The patterns of disparity variation that we observed at the order level were not significant or could not be properly tested within families or within factor categories with our sampling effort as some factor categories are distributed un-evenly across the order. For example, for some factors only one category is represented in a given family (e.g. all Sapotaceae and Lecythidaceae are tropical trees, all Marcgraviaceae are distributed in South America). In addition, some families are too small to observe any pattern even if sampled completely (seven families contain fewer than 12 species -e.g.

Tetrameristaceae, Roridulaceae, and Fouquieriaceae). Nevertheless, even if in many cases Ericalean families are limited to a narrow range of strategies (with regard to the factors we investigated here), we observe broad trends in biodiversity variation that emerge from these patterns at a larger phylogenetic scale. This has also been shown for the latitudinal gradient in vascular plant species number (Wieser et al., 2018). Even though we cannot test for the effect of phylogenetic relationships on disparity based on the present data because several deeper nodes of Ericales are presently unresolved or unsupported [START_REF] Schönenberger | Molecular phylogenetics and patterns of floral evolution in the Ericales[END_REF][START_REF] Rose | Phylogeny, historical biogeography, and diversification of angiosperm order Ericales suggest ancient Neotropical and East Asian connections[END_REF], exploring such effects could be approached in the future by focusing on well-supported subclades (e.g. the ericoids or the primuloids, [START_REF] Rose | Phylogeny, historical biogeography, and diversification of angiosperm order Ericales suggest ancient Neotropical and East Asian connections[END_REF] or at individual families.

The drawback of working at large taxonomic scales is, unfortunately, the present lack of ecological information (particularly about pollination) that could help us to understand the mechanisms leading to these broad-scale patterns. Our data on Ericales, however, suggest that a well-suited clade for studying these mechanisms at a finer scale would be Primulaceae (primrose family), because of its large size (2,788 species) and high morphological variability. Primulaceae represent 22.1% of Ericales species, and contribute 14% to the order's floral disparity [START_REF] Chartier | How (much) do flowers vary? Unbalanced disparity among flower functional modules and a mosaic pattern of morphospace occupation in the order Ericales[END_REF].

In addition, the family presents sufficient variation in climate types, growth form, habitat, and is widely distributed (SI "Dataset.xlsx"). However, even at this scale, the lack of ecological data for most species would remain a limiting factor for these analyses.

In our data, the species displaying the highest degree of floral disparity are those with an arborescent form distributed in the African and South American tropical forests (Fig. 3). There is, however, no apparent link between growth form and floral disparity, and the slightly higher floral disparity of trees may be an artefact due to the strong association between the states tree and tropics (Fig. 3). Indeed, nearly sixty percent of the tree species included in our dataset grow in tropical forests, and within the tropics, over sixty percent of Ericales species are trees. This makes it difficult to disentangle the effects of growth type and climate type on the variation of floral disparity. In addition, we did not correct for a phylogenetic effect when studying the relationships between factors and disparity, which is a limitation of this study. There is no distinct pattern of disparity variation in Ericales, for example early diverging clades do not seem to show more or less disparity than later diverging clades; however, disparity varies greatly among Ericalean families [START_REF] Chartier | How (much) do flowers vary? Unbalanced disparity among flower functional modules and a mosaic pattern of morphospace occupation in the order Ericales[END_REF]. The high disparity found for trees could for example be due to the contribution of the family Lecythidaceae. When Lecythidaceae are pruned from the dataset, our main results do not change but lose statistical significance as the category tropical climate then only tends to show the highest disparity. In these adapted analyses, there is also no more trend for any growth form to show different levels of morphological disparity. The effect of climate on floral disparity thus appears to be more robust than the effect of growth form. Further evidence for the importance of the effect of climate lies in the decrease in disparity from tropical to temperate climate categories. Categories cold and polar do not display significantly different disparity from any other climate category in our dataset (although they clearly tend to show lower disparity), most likely because these categories are very often associated to category temperate in the data (polymorphism).

In angiosperms, the flower is the structure dedicated to sexual reproduction, and a shift in floral features can provoke reproductive isolation by different mechanisms (Waser & Ollerton, 2006). We might thus expect floral disparity to be correlated with species number in a clade or a region. Our data shows that this is not always the case (Fig. 4c, SI section 2.4, [START_REF] Chartier | How (much) do flowers vary? Unbalanced disparity among flower functional modules and a mosaic pattern of morphospace occupation in the order Ericales[END_REF]. For example, we find that African species tend to display the highest level of floral disparity although, in our dataset, species number is significantly higher for the South American and Indo-Pacific regions. The decoupling of disparity and species number in a clade, a region, or through time is quite common [START_REF] Lupia | Discordant morphological disparity and taxonomic diversity during the Cretaceous angiosperm radiation: North American pollen record[END_REF][START_REF] Roy | Spatial patterns of morphological diversity across the Indo-Pacific: analyses using strombid gastropods[END_REF][START_REF] Neige | Spatial patterns of disparity and diversity of the Recent cuttlefishes (Cephalopoda) across the Old World[END_REF][START_REF] Roy | Morphological approaches to measuring biodiversity[END_REF][START_REF] Eble | Contrasting evolutionary flexibility in sister groups: disparity and diversity in Mesozoic atelostomate echinoids[END_REF][START_REF] Oyston | Why should we investigate the morphological disparity of plant clades?[END_REF].

Clearly, disparity is an important component of biodiversity and is worth being considered in any attempt to measure biodiversity. When calculated on floral traits, disparity may also provide useful approximations for the diversity of ecological relationships (e.g., plant-pollinator interactions) and might help understand evolutionary patterns (e.g., pollination-mediated selection in a biogeographic context). Floral disparity in a given geographical area might also be a particularly useful parameter for assessing the conservation value of the area, as disparity not only reflects an important part of the local plant community, but as it is, via plant-pollinator interactions, also a possible proxy for a community's ecological dynamics.

Figure and table legends

[ 1 ]

 1 trees, [2] shrubs, [3] lianas and climbers, [4] herbs (including aquatic herbs), and [5] root parasites.

Figure 1 .

 1 Figure 1. Climate categories and latitudinal gradient. a, Köppen-Geiger climate classification simplified to five categories (figure adapted from Peel et al. (2007)). b, Estimated latitudinal distribution (number of species) of Ericalean species (grey bars) and the corresponding floral disparity ( yellow dots, SD shown in light blue) per ten-degree longitudinal categories.

Figure 2 .

 2 Figure 2. Overall variation of floral disparity among categories of growth form (a), climate (b), habitat (c), and geographic region (d). D = mean pairwise differences. For each boxplot, sample size is given below each box and disparity ( ± SD) is indicated by orange dots and black error bars. Post hoc test results are depicted by red letters; categories that are significantly different are labelled with a different letter. The coloured barplots indicate the number of species sampled per family (according to APG IV; Stevens, 2001 onwards) in each factor category. For growth form (a), the category "root parasitic" was not included in the statistical analyses as it contains only two species.

Figure 3 .

 3 Figure 3. Association network (a) and disparity for two clusters of associated categories (b).The graph in a is used to visualize the results of chi-square tests assessing the multiple associations among factor categories in our dataset. Factor categories that are significantly associated are linked by a line whose colour represents the strength and direction of the association (interpreted from the values of Pearson residuals). This representation is equivalent to a classical correlation table (SI section 1.3). Our results show that some categories are associated to eachother, and form two distinct groups that we call Cluster 1 and Cluster 2. The disparity of these clusters is given in b: D = mean character differences between two taxa, sample size is given below each box, and disparity ( ± SD) is indicated by orange dots and black error bars.

Figure 4 .

 4 Figure 4. Relationships among species richness, floral disparity, and latitude for 347 species of Ericales. Black lines: significant correlation, red dashed line: correlation only significant when the three latitudinal intervals containing 5 species or less (red dots) are included. Absolute values were used for latitude, to pool data from the northern (gray/light red dots) and the southern (black/red dots) hemispheres.

Figure 1 Figure 2 Figure 3

 123 Figure 1

Figure 4

 4 Figure 4

Table 1 .

 1 Chi-squared tests for the association among the categories of factors growth form, habitat, climate, and region.

	Comparison	χ 2	df	p-value
	Growth form-climate	80,99 9	1,03.10 -13
	Growth form-region	100,12 15	1,24.10 -14
	Growth form-habitat	49,34 6	6,39.10 -09
	Climate-region	263,29 15	<2,20.10 -16
	Climate-habitat	64,13 6	6,49.10 -12
	Region-habitat	47,52 10	7,59.10 -07

Acknowledgements

We thank M.C. Peel for permission to reproduce figure 1a, A. Dellinger, S. Gerber and P. Mitteröcker for discussion, U. Schachner for spell-checking and formatting. We also thank the editor and three anonymous reviewers for their very helpful comments on a previous version of the article. This work was supported by the Austrian Science Fund (FWF P 250077-B16).

Author's contribution M.C., M.v.B. and J.S. designed the work, S.S., M.v.B., M.C., S.L., F.J. and J.S. generated the data, H.S. designed the online database (PROTEUS) used to record and store the data, M.C. analysed the data with help from T.P.; M.C., M.v.B. and J.S. wrote the paper with significant contributions from the other authors. All authors gave final approval for publication.

Material & correspondence

The dataset supporting this article is given in Supplementary Information ("Dataset.xlsx"). The data are also stored in the online database PROTEUS (http://eflower.myspecies.info/; [START_REF] Sauquet | PROTEUS: A database for recording morphological data and fossil calibrations[END_REF]. Correspondence and material requests should be addressed to M.C. and J.S.

Competing interests

The authors declare no competing interests.