relationships between plant traits and climate in the...

- Relationships between plant traits and climate in the Mediterranean region - 635

Journal of Vegetation Science 15: 635-646, 2004© IAVS; Opulus Press Uppsala.

AbstractQuestion: What are the correlations between the degree ofdrought stress and temperature, and the adoption of specificadaptive strategies by plants in the Mediterranean region?Location: 602 sites across the Mediterranean region.Method: We considered 12 plant morphological and pheno-logical traits, and measured their abundance at the sites as traitscores obtained from pollen percentages. We conductedstepwise regression analyses of trait scores as a function ofplant available moisture (α) and winter temperature (MTCO).Results: Patterns in the abundance for the plant traits weconsidered are clearly determined by α, MTCO or a combina-tion of both. In addition, trends in leaf size, texture, thickness,pubescence and aromatic leaves and other plant level traitssuch as thorniness and aphylly, vary according to the life form(tree, shrub, forb), the leaf type (broad, needle) and phenology(evergreen, summer-green).Conclusions: Despite conducting this study based on pollendata we have identified ecologically plausible trends in theabundance of traits along climatic gradients. Plant traits otherthan the usual life form, leaf type and leaf phenology carrystrong climatic signals. Generally, combinations of plant traitsare more climatically diagnostic than individual traits. Thequalitative and quantitative relationships between plant traitsand climate parameters established here will help to providean improved basis for modelling the impact of climate changeson vegetation and form a starting point for a global analysis ofpollen-climate relationships.

Keywords: CCA; Drought; Leaf phenology; Leaf size; Mor-phological trait; Plant functional type; Response function.

Abbreviations: α = ratio of actual to equilibrium evapo-transpiration; EPD = European pollen database; MTCO =Mean temperature of the coldest month; SLA = Specific leafarea.

Introduction

The Mediterranean region is characterized by a sea-sonal moisture regime, with summer drought and rain inautumn, winter and spring. The vegetation of the regionhas several physiological and morphological features tominimize the impact of this seasonal drought. Althoughthese plant characteristics form the basis for most classi-fications of Mediterranean vegetation types (Specht1969; Quézel & Barbero 1982), the relationship be-tween the degree of drought stress and the adoption ofspecific adaptive strategies is not well understood orquantified.

Traits are readily observable or measurable charac-teristics of plants, which are assumed to be plant physi-ological responses to external conditions (McIntyre etal. 1999). Variation in the occurrence of traits alongenvironmental gradients should reflect variation in therelative importance of adaptive mechanisms. Analysisof trait-based gradients provides a way of quantifyingthe relationship between environment and plant response.

Recent work on plant traits focused on relationshipswith environmental aspects that are important at a localscale, such as gradients in land use and disturbance(Lavorel & Cramer 1999; Rusch et al. 2003). Less atten-tion has been paid to the relationships between traits andclimate, in part because these relationships need to beexamined at larger spatial scales (Woodward & Cramer1996; Díaz & Cabido 1997; Díaz et al. 1998, 1999).

We use a large data set of modern pollen surfacesamples covering the full range of climate across theMediterranean region to investigate quantitative, re-gional scale relationships between 12 plant traits andclimatic variables. Statistical analyses of these data al-low the identification of climatic thresholds for traitoccurrence and climatically determined gradients intrait abundance.

Relationships between plant traits and climatein the Mediterranean region: A pollen data analysis

Barboni, D.1,2*; Harrison, S.P.1; Bartlein, P.J.3; Jalut, G.4; New, M.5; Prentice, I.C.1;Sanchez-Goñi, M.-F.6; Spessa, A.1; Davis, B.7; Stevenson, A.C.7

1Max Planck Institute for Biogeochemistry, MPI-BGC, Postfach 100164, D-07701 Jena, Germany; 2Present address: CEREGE,UMR-CNRS 6635, BP80, F-13545 Aix-en-Provence, France; 3Department of Geography, University of Oregon, Eugene,

OR 97403-1251, USA; 4Laboratoire d’Ecologie Terrestre, Université Paul Sabatier, F-31062 Toulouse cedex 04, France;5School of Geography and the Environment, University of Oxford, Mansfield Road, Oxford, OX13TB, UK; 6EPHE, Depart-ment of Geology-Oceanography, UMR-CNRS 5805 EPOC, University of Bordeaux 1, F-33405 Talence, France; 7University of

Newcastle, Newcastle upon Tyne, NE1 7RU, UK; *Corresponding author; Fax +33 0442971540; E-mail [email protected]

636 Barboni, D. et al.

Methods

Pollen data

Our trait analysis is based on a data set of modernpollen assemblages at 602 individual sites from South-ern Europe, the Middle East and Northern Africa (Fig. 1).These data were assembled as part of the CiMBIO project(http://www.bgc-jena.mpg.de/bgc_prentice/projects/projects.html) and were derived from the European Pol-len Database (EPD, http://www. ngdc. noaa. gov/paleo/epd.html) (App. 1).

Modern pollen data offer several advantages foranalysing the relationships between traits and climate.The existence of continental scale pollen data archivessuch as the EPD makes it possible to sample largegradients, thereby maximising the opportunities for re-lationships between specific climate parameters andtrait abundance to become apparent. The data set usedhere samples the full range of Mediterranean climates,the transition to temperate and/or montane climates andthe transition to semi-arid and desert climates. The AtlasFlora Europaeae (Jalas & Suominen 1972-1996), whichcovers a similarly large range of climate within theMediterranean region, provides information on the geo-graphical distribution of plant species but, in contrast tothe pollen data, does not provide any measure of abun-dance. Generally, pollen samples are selected to providea signal of the regional vegetation (e.g. Sugita 1994),which is more likely to be determined by climatic gradi-ents than local factors such as disturbance. A disadvan-tage of using modern pollen data to analyse the relation-ships between traits and climate is that the taxonomicresolution to which pollen can be identified is limited(Berglund 1986). Of the 455 taxa represented in our dataset, only eight are routinely identified to species level.Most pollen can be identified to genus level. Some types(e.g. Poaceae, Fabaceae) are only diagnostic to fami-lies. However, pollen data offer unparalleled opportuni-ties to examine large scale patterns that outweigh this

taxonomic limitation. Furthermore, if relationships canbe demonstrated with pollen data, they should be evenmore apparent with species level data.

Trait assignments

We identified 12 traits that appear to be associatedwith drought tolerant plants on the basis of a review ofthe literature. The traits (Table 1) fall into three catego-ries: descriptive of life form (e.g. habit), descriptive ofthe characteristics of the whole plant (e.g. leaf phenol-ogy, photosynthetic pathway) and those associated withleaf character (e.g. size, texture). We have not assigneda value for every trait to every life form because somelife forms are characteristic of local rather than regionalconditions (e.g. aquatic, bog moss, pteridophyte), whilein others the life form itself is the response to climate(e.g. geophyte, cactoid). We assigned trait classes to the455 pollen taxa represented in the modern pollen dataset on the basis of our personal knowledge, informationfrom floras (Tutin 1964-1993; Goldstein et al. 1983;Schönfelder & Schönfelder 1988; Coombes 1992; Sutton1998; Bremness 2000; Burnie 2000) and from web-based taxonomic or ecological resources (e.g. Watson &Dallwitz 1992-; Anon. 2000).

In those cases in which a pollen taxon representsmore than one species, and those species display differ-ent traits or trait classes, we assigned to the taxon all thetraits displayed by the component species. For example,the pollen of shrub (e.g. Bupleurum fruticosum) andforb (e.g. B. flavum) species of Bupleurum are indistin-guishable, so Bupleurum is assigned to both life formsand to pico, lepto, nano and micro leaf-size classes.

We also created composite traits for trees, shrubs,forbs and lianas/vines by combining life form with leaftype (broad, scale, needle) and leaf phenology (ever-green, summer-green, rain-green) traits. Other leaf andplant traits such as leaf size and texture, were thenallocated to the habit × leaf type × leaf phenologycomposite traits (App. 2).

Fig. 1. Geographical distribution andfrequency distribution according toplant water availability (α) and meantemperature of the coldest month(MTCO) for the 602 pollen sites avail-able in the Mediterranean and circum-Mediterranean region.


Climate data

We derived mean monthly temperature, precipita-tion and number of rain days at the exact location andelevation of every modern pollen site, using thin-platespline interpolation from station data. The station datawere derived from the Climate Research Unit, Univer-sity of East Anglia data set (New et al. 2002) and coverthe interval from 1961 to 1990. The spline interpolation(Hutchinson 1999), which is an elevationally sensitiveinterpolation, was based on 967, 1122 and 651 meteoro-logical stations in the Mediterranean region for tem-perature, precipitation and rain days respectively. Thesedata were used to calculate mean annual precipitation,number of rain days per year and number of rain days insummer and winter.

The temperature and precipitation data were alsoused to calculate bioclimatic variables thought to bemore closely related to the effective controls on plantgrowth and distribution (Prentice et al. 1992a,b; Kohfeld& Harrison 2000). These bioclimatic variables are meantemperature of the coldest month (MTCO), cumulatedtemperature sum over 5 °C during the growing seasonand the ratio of actual to equilibrium evapotranspiration(α) during the winter and summer seasons and over theyear. The α index measures drought stress experiencedby the plants. It is calculated using the water holdingcapacity of the soil and monthly means for sunshine,temperature and precipitation. The functions for dailywater supply (proportional to soil moisture and precipi-tation) and daily water demand (proportional to sun-shine and temperature) used for the computation of αwere calculated using the algorithm of Prentice et al.(1993) as in the BIOME1 model (Prentice et al. 1992a,b).The α index varies between 0 and 1, so that a value ofe.g. 0.5 represents a state in which rainfall meets morethan 50% of the evaporative demand. At the samplingsites in the Mediterranean region, the calculated α indexvaries widely. Rainfall meets up to 100% of theevaporative demand at sites in France, Italy and in thehighlands in Spain and Bulgaria. Rainfall meets lessthan 50% of the evaporative demand at several sites inSpain and Morocco and at many sites in Turkey, Syriaand Lebanon. Values for MTCO range from –10 °C to14 °C. Despite the geographical clustering of the sam-ples, this pollen data set has good coverage with regardsto winter temperatures and mean annual water availabil-ity (Fig. 1). These two bioclimatic variables are the onlyones we considered for further analyses, since theyexplain most of the climate variability in the study area,as evidenced by a factor analysis (not shown).

Analytical approach

The relative abundance of pollen taxa at each sitewas expressed as a percentage of the total pollen sum atthat site, to yield a matrix of pollen abundances by sites.The taxa-site matrix is used in combination with thematrix of trait allocations to pollen taxa to calculate ameasure of the relative importance of each trait at eachsite (trait score), using the formula:

(1)

where S is the score of trait a, n is the number of pollentaxa to which trait a is assigned and P is the relativeabundance of the pollen taxon. δia = 1 if taxon i exhibittrait a and dia = 0 if not.

All 455 taxa represented in our data set of 602samples are used to calculate the scores for traits andcomposite traits. However, pollen taxa constituting lessthan 0.5% of a given sample are not taken into accountin the calculation of the trait (or composite trait) scorefor that sample. The trait score is influenced by both thenumber of taxa displaying a given trait and the percent-age relative abundance of those taxa at the site. Thecalculation of trait scores thus goes some way to com-pensating for the fact that pollen taxa may be assigned tomore than one trait or trait class, because not all taxa ata site will be similarly affected.

Table 1. Life-form, leaf-level and plant-level traits used in thisstudy.

Category/Trait Classes

Life formHabit Tree, shrub, tuft tree/treelet, liana/ vine, wood parasite,

epiphyte, cactoid, forb, climber, aquatic, mosses,pteridophyte, graminoid, geophyte, root parasite

Leaf traitsType Broad-leaved, scale-leaved, needle-leaved, aphyllousSize Pico (< 5 mm2), lepto (5-25 mm2), nano (-250 mm2),

micro (-2000 mm2), noto (-4500 mm2), meso (-20000mm2), macro (-150000 mm2), mega (>150000 mm2)

Texture Membranous, coriaceous/leathery, rigidly coriaceous,succulent

Thickness Thick (when mentioned in the literature or when leafthickness > 0.2 mm)

Pubescence Hairs present on abaxial or adaxial or both sides of leafWaxiness Waxy cuticle or notAroma Aromatic leaves or not

Plant traitsLeaf phenology Evergreen, rain-green, summer-greenPhotosynthetic Leaf photosynthetic, Stem photosyntheticsystem (some plants are classified as having both)Pathway C3, C4, CAMThorniness Spines or thorns present

S Pa ia i

i

n

==

∑δ1


The pollen taxa diversity issue

Since trait scores are calculated on the basis ofpollen percentages and that pollen percentages are influ-enced by pollen taxa richness at sites, we analysed, foreach of the 43 most common pollen taxa in the 602 sites,the relationships between percentage relative abundanceof pollen taxa (% RA) and pollen taxa richness (TR)across sites. We found that %RA can be affected notonly by TR, but also by the raw counts of all the othertaxa represented in a pollen spectrum (RCO) and theraw count of the taxon in question (RCQ). TR can beaffected by climate, while RCO and RCQ are influencedby the counting method. Our analyses show, however,that RCQ has the predominate influence on %RA ratherthan TR or RCO. Because variation in RCQ and RCO isindependent of climate, we are confident that usingpercentage relative abundance of pollen taxa does notbias the analyses of trait score-climate relationships.

We calculated scores for each individual trait class(Table 1) and composite trait (App. 2). To calculate themain effects of the bioclimatic variables on the traitscores we conducted a stepwise regression analysis ofthe scores as a function of MTCO and α. We used asaturated quadratic model with interactions as our initialmodel. The regression was fitted through the square rootof scores. The predicted scores were then back-trans-formed (i.e. squared) in order to be compared withobserved score values. The F-probability distributionand associated probability level for each plant trait andcomposite trait were calculated to test the significanceof the obtained R2. Several individual and compositetraits showed significant correlations with MTCO and αat p ≤ 0.05 and ≤ 0.01 levels (Table 2 and App. 3). Usingthe fitted regression models we predicted trait scores forthe whole climate space defined by MTCO and α tovisualize the trends in the trait abundance according toclimate.

We used Canonical Correspondence Analysis (CCA;ter Braak 1987) to identify the successions of compositeplant traits along the climatic gradients. CCA is appro-priate (and preferred to Principal Component Analysis)when the aim is to analyse species or trait data alongenvironmental gradients, where some or all species ortraits are likely to show unimodal rather than monotonicrelationships to the underlying gradients (ter Braak &Prentice 1988). The CCA was carried out on the com-bined-trait × site matrix with the climate × site matrix.Only composite plant traits whose abundance was sig-nificantly correlated to α and MTCO were consideredfor this analysis.

Results

Climate space diagrams

Trees, shrubs and forbs are present in the wholeclimate range represented in the Mediterranean region(Fig. 2). However, their relative abundance varies alongclimatic gradients in α and MTCO. Trees become in-creasingly abundant as α increases. Their scores are > 5at α values > 0.3, and > 10 at α values > 0.5. Shrubs areabundant throughout the climate range (scores always > 5),and become even more abundant when α is < 0.5. Forbsincrease in abundance when aridity increases but theirabundance is also influenced by MTCO, i.e. the abun-dance of forbs at the two sites with same α, will behigher at the site where winter temperature is the lowest.Gradients in the abundance of geophytes and graminoidswith climate are apparent though weakly expressed (notshown). None of the other life forms considered showstatistically significant trends in abundance related toclimate range in the Mediterranean region.

Within the life forms there are secondary gradientsin trait abundance related to leaf type. Needle- andbroad-leaved trees are potentially abundant throughoutthe climate range. However, needle-leaved trees reachmaximum abundances (arbitrarily defined as score > 5)

Fig. 2. Distribution of scores for tree, shrub and forb life formsin the climatic range of the Mediterranean region as defined byplant water availability (α) and mean temperature of thecoldest month (MTCO).


at MTCO < –3 °C, whereas broad-leaved trees are mostabundant where α > 0.5. Scale-leaved trees tend to bemost abundant at MTCO values intermediate betweenthose favouring needle- and broad-leaved trees (notshown). Gradients in the relative abundance of pheno-logical characteristics cannot be considered independ-ently of life form and leaf type (Fig. 3). The relativeabundance of evergreen plants, whether these are broad-leaved trees or broad-leaved shrubs, increases as wintertemperature and aridity increase. The relative impor-tance of summer-green trees increases as both wintertemperature and aridity decrease, and the relative im-portance of summer-green shrubs in the Mediterraneanregion is mainly a function of increasing aridity.

At the trait level (Fig. 4a), i.e. irrespective of anyother plant traits, all leaf sizes except macrophyll andmegaphyll are well represented in the whole range ofclimate in the Mediterranean region. Mesophyll leaves(the largest in the Mediterranean region) are most abun-dant when water availability is high (α > 0.4) and wintertemperature is low (MTCO < 1 °C). Notophyll leaves

also decrease in abundance with increasing temperatureand aridity. Leaves of intermediate size (nanophyll andmicrophyll) are abundant throughout the climate range,whereas small picophyll and leptophyll leaves becomeincreasingly abundant with increasing aridity. The leaftexture also has a trend along the aridity and wintertemperature gradients. Although membranous leaves arevery abundant across the whole range of climate, rigidlycoriaceous and coriaceous leaves increase in abundancewith increasing temperature (Fig. 4a) and are most abun-dant when MTCO is > 0 °C. Thick leaves, (although theirscores remain < 5), have the greatest occurrence at low α(< 0.5) and high MTCO (> 12 °C). Succulent leavesincrease in abundance with increasing aridity. However,at a given level for α, leaf texture tends to be succulent incold environments and rigidly coriaceous in warm envi-ronments. Other traits such as the ability of shifting thephotosynthetic activity from the leaves to the stems, orthe presence of wax on the cuticles, reach maximumabundance when water availability and/or temperatureincrease (Fig. 4a).

Table 2.Traits and composite plant traits whose abundance is significantly correlated (p < 0.05; * = p < 0.01) to mean temperaturefor the coldest month (MTCO) and plant water availability (α). R2 values are obtained from regression models based on trait scoresat all sites (N = 602) available in the Mediterranean region.

Traits R2 Composite traits R2 Composite traits R2

Tree 0.37 * Forb Shrub broad-leaved summer-greenShrub 0.15 * - aphyllous 0.34 * - pico 0.37*Forb 0.23 - pico 0.37 * - lepto 0.34*Geophyte 0.07 - lepto 0.35 * - nano 0.34*Graminoid 0.06 - nano 0.31 * - micro 0.16*Scale 0.19 * - micro 0.22 - noto 0.16*Aphyllous 0.36 * - membranous 0.23 - membranous 0.16*Evergreen 0.08 * - coriaceous 0.11 - rigidly coriaceous 0.39*Summer-green 0.18 * - rigidly coriaceous 0.32 * - succulent 0.38*Pico 0.12 * - succulent 0.43 * - hair 0.12*Lepto 0.26 * - hair 0.16 * - wax 0.24*Nano 0.15 * - wax 0.33 * - photo.stem 0.34*Micro 0.14 * - aromatic 0.24 * - C3 0.16*Noto 0.16 * - photo.stem 0.31 * - C4 0.34*Meso 0.12 - C3 0.23Membranous 0.07 - C4 0.36 * Tree broad-leaved evergreenCoriaceous 0.08 - CAM 0.19 * - pico 0.18*Rigidly coriaceous 0.36 * - spine 0.14 * - lepto 0.17*Succulent 0.43 * - nano 0.23*Thick 0.13 * Tree or shrub scale-leaved 0.19 * - micro 0.34*Hair 0.05 - noto 0.06Wax 0.23 * Tree needle-leaved 0.04 * - membranous 0.22*Aromatic 0.14 * - coriaceous 0.21*Photosynthetic stem 0.32 * Shrub broad-leaved evergreen - rigidly coriaceous 0.25*C3 0.07 - pico 0.21 * - thick 0.21*C4 0.34 * - lepto 0.11 * - hair 0.24*CAM 0.21 * - nano 0.21 * - wax 0.30*spine 0.09 - micro 0.30 * - spine 0.27*

- membranous 0.21 * Tree broad-leaved summer-green- coriaceous 0.18 * - lepto 0.09- rigidly coriaceous 0.23 * - nano 0.14*- thick 0.19 * - micro 0.20*- hair 0.09 - noto 0.37*- wax 0.26 * - meso 0.24*- aromatic 0.23 * - membranous 0.37*- C3 0.12 * - hair 0.32*- spine 0.25 * - wax 0.14*


Life form, leaf type and phenology are important indetermining the gradients of other traits, such as leafsize and texture. Different gradients in leaf size accord-ing to life form and leaf phenology appear to reflectdifferent climate responses. At the trait level, smallleaves tend to be most abundant in cold and dry environ-ments (Fig. 4a). However, at the life form level, trees onone hand and shrubs and forbs on the other have differ-ent gradients in leaf size according to temperature. Withintrees, leaf size decreases as MTCO increases (Fig. 4b),irrespective of whether the trees are evergreen or sum-mer-green (Fig. 5). Within shrubs and forbs, it is thecontrary: leaf size increases as MTCO increases (Fig.4b). For forbs, e.g. at the α value 0.5, most abundantleaves are picophyll when MTCO is < 2 °C and leptophyllto nanophyll when MTCO is > 2 °C. For evergreenshrubs, leaf size increases and then decreases again aswinter temperature increases, leading to a succession ofmost abundant leaf sizes: lepto > micro > nano along theMTCO gradient (Fig. 5). The response of leaf size toaridity appears to be similar in all life forms: leaf sizedecreases as aridity increases (Figs. 4b and 5). There isalso a relatively homogeneous response of leaf textureto aridity for all life forms: leaf texture becomes morecoriaceous and thick, i.e. more sclerophyllous as aridityincreases (Figs. 4 and 5). However, because evergreenand summer-green trees respond differently to aridity

the abundance scores for rigidly coriaceous leaves fortrees remain < 5 (Fig. 4b). The leaf texture remainsmembranous for summer-green trees, while it can berigidly coriaceous as well as membranous when aridityis high for evergreen trees (Fig. 5). The gradients of leaftexture also indicate that as MTCO increases, leafsclerophylly increases. However, for forbs, sclerophyllyincreases when MTCO decreases (Fig. 4b).

CCA analysis

CCA was carried out only on composite plant traitssince most of the plant- or leaf-level traits we examinedexhibit different gradients in abundance across life formsand phenologies. We used 66 tree, shrub and forb com-posite traits plus the two life forms graminoid andgeophyte. These composite traits show variations inabundance significantly correlated with gradients ofMTCO and α (Table 2). Variations in α are the mostimportant determinant of trait distribution (Table 3),with a correlation of –0.71 with the first CCA axis.Variations in MTCO are also important, showing acorrelation of 0.27 with the first axis and –0.49 with thesecond axis. The dispersion of the composite plant traitsin the ordination diagram indicates four groups (Fig. 6).The succession of composite traits along the gradientsof either α or MTCO is plausible. Thus, summer-green

Fig. 3. Distribution of scores for ever-green and summer-green phenologiesof broad- and needle-leaved trees andshrubs in the climatic range of the Medi-terranean region, as defined by plantwater availability (α) and mean tem-perature of the coldest month (MTCO).


trees only occur when plant available moisture (α) isrelatively high. With increasing drought stress (decreas-ing α), the abundance of evergreen broad-leaved treesand shrubs in the vegetation increases. As drought stressincreases further, forbs and summer-green shrubs be-come dominant. Within each group there is a similarsuccession in the relative abundance of drought charac-teristic leaf traits with increasing aridity. Thus, the rela-tive importance of drought related plant traits changeswith first large (noto, micro), membranous and hairyleaves and subsequently waxy, rigidly coriaceous andfinally thick leaves reaching their maximum abundance.Similar mechanistically plausible relationships are ap-parent with MTCO. For example, the maximum expres-sion of summer-green trees and/or shrubs occurs atcooler temperatures than evergreen trees and/orshrubs.We can characterize the climatic extremes withinthe Mediterranean region in terms of traits. Specifically,colder and wetter climates are characterized by broad-leaved summer-green trees, with large membranousleaves and geophytes. Colder and drier climates aremainly characterized by forbs with spines, CAM photo-synthesis, coriaceous and aromatic leaves. Warmer anddrier climates are characterized by summer-green shrubsor forbs with rigidly coriaceous leaves, succulent andaphyllous plants, with C4 photosynthesis. When thetemperature is even higher, it is the domain for ever-

green shrubs with rigidly coriaceous and thick leavesand spines. Finally, warmer and wetter climates arecharacterized by broad-leaved evergreen trees, and treesor shrubs with coriaceous and rigidly coriaceous leaves.

Climate domains

We may use the regression of the trait scores by αand MTCO to define climatic domains for the non-occurrence and for the maximum expression of certainplant traits. This implies an arbitrary definition for somethresholds. For example, if we set the threshold for traitmaximum abundance at 5 (as illustrated in Figs. 4 and5), we can describe the domains of maximum abun-dance for most of the traits. Trees, for example, reachmaximum abundance when α is > 0.3, while broad-leaved summer-green trees reach maximum abundancewhen MTCO is < ca. 2 °C. If MTCO is > ca. 2 °C, thenα must be > 0.8 for broad-leaved summer-green trees tobe most abundant. Broad-leaved evergreen trees aremaximally abundant when MTCO is > 1 °C and α is <0.95, or when MTCO is > 1 °C and (α + 0.048 MTCO)> 0.82. Some traits appear to be present at low levels(scores < 2) everywhere (e.g. notophyll broad-leavedshrub, liana/vine). This implies either that the maximumabundance of these traits lies outside of the Mediterra-nean domain, or that the abundance of these traits is not

Fig. 4. Zones of maximum abundance(scores >5) for a. traits and b. for broad-leaved tree, shrub and forb composite traitsat the life-form level, in the climate range ofthe Mediterranean region defined by plantwater availability (α) and mean tempera-ture of the coldest month (MTCO). Thegrey zone indicates scores < 5. Dashed lineis for scores > 4, except when indicated.


Discussion

Mediterranean vegetation displays a large numberof traits that express plant tolerance to drought (Specht1969). Our analyses show that variations in α are themost important control on trait abundance, in agreementwith previous work. However, we are now able toquantify the relationships between specific traits andaridity. We also demonstrate that winter temperature isalso an important control on trait distribution in theMediterranean region. Indeed, winter temperature con-trols species distribution within the Mediterranean re-gion (Retuerto & Carballeira 1991; Gavilán & Fernández-González 1997) and is a climatic parameter commonlyused in the classification of Mediterranean vegetationtypes (Quézel & Barbero 1982). High summer tempera-tures and excess drought trigger high fire frequency inthe Mediterranean region (Mooney & Dunn 1970a).Under such climatic conditions, there is an abundanceof pyrophyte plants, such as shrubs and forbs withrigidly coriaceous, aromatic and waxy leaves. However,to identify the real impact of fire on the distribution ofthese plant types, it would have been necessary to con-sider regenerative traits such as resprouting ability, coneserotiny and seed dormancy.

We have identified several successions of plant mor-phological and phenological traits along the gradients ofaridity and winter temperatures that are supported by

Fig. 5. Zones of maximum abundance(score > 5) for the tree, shrub and forbcomposite traits at the life form andleaf phenology level, in the climaterange of the Mediterranean regiondefined by plant water availability(α) and mean temperature of thecoldest month (MTCO). The greyzone indicates scores < 5. Dashedline is for scores > 4, except whenindicated.

Table 3. Eigenvalues, correlation coefficients (R) betweentraits and climate and correlation coefficients between theCCA axes and water availability (α) and winter temperature(MTCO).

Axis 1 Axis 2

Eigenvalues 0.09 0.03R (traits,climate) 0.72 0.52Canonical coeff. α –1.08 –0.44

MTCO –0.19 –1.15Correlation coeff. α –0.71 0.08

MTCO 0.27 –0.49

strongly determined by climate. Similarly, if we definedomains for trait non-occurrence at scores < 0.5, we findthat trees occur throughout the Mediterranean climatedomain, but that broad-leaved trees do not occur when αis < 0.25 (not shown). Broad-leaved summer-green treesdo not occur when MTCO is > 6.5 °C, unless α is abovea certain threshold that increases as MTCO increases.For example, this α threshold is ca. 0.5 when MTCO isca. 7 °C). and ca. 0.6 when MTCO is ca. 10 °C (notshown). In contrast, broad-leaved evergreen trees areexcluded from arid climates although the α thresholdfor exclusion varies from 0.7 in regions with cold win-ters to 0.3 in regions where MTCO is > 6 °C Summer-green and evergreen shrubs and forbs occur throughoutthe climate domain of the Mediterranean (scores always>0.5). Aphyllous plants do not occur where α is > 0.9,unless MTCO is 3 °C (not shown).


ecological and physiological studies. Along the increas-ing aridity gradient, we found that the abundance oftrees decreases, while it increases for shrubs and forbs.This agrees with one of the oldest ecological observa-tions; plant height decreases as aridity increases (Mooney& Dunn 1970a; Williams et al. 1996; Fonseca et al.2000). Our data also show that as aridity increases, leafsize decreases for trees, shrubs and forbs. However,along the temperature gradient, it varies differently forbroad-leaved trees on one hand, and for shrubs and forbson the other hand. Leaf size for broad-leaved trees tendsto decrease with increasing winter temperatures. Forshrubs and forbs, the smallest leaves are most abundantwhen winter temperatures are extreme, that is, whenMTCO is very low or very high; the largest leavesoccurring when winter temperatures are moderate (2 °C< MTCO < 5 °C for shrubs at α level of 0.5). Becausesmall leaves avoid excessive evapotranspiration andleaf overheating under high solar radiation, high tem-perature and low water availability (Parkhurst & Loucks1972; Werger & Ellenbroek 1978) they tend to be moreabundant in the highlands and other cold regions(Morecroft & Woodward 1996; Tang & Ohsawa 1999),as well as in very hot or dry areas (Skarpe 1986; Fonsecaet al. 2000). The fact that leaf size varies differentlyamong life forms could be explained by the depth oftheir root systems, which is generally greater for treesthan for shrubs and forbs (Canadell et al. 1996). Hence,

trees that can take water from the deep soil layers canalso bear relatively large leaves even when water avail-ability is low. Leaf size and phenology, as well as depthof the root system play a major role in water use trade-offs for arid ecosystems (Schwinning & Ehleringer 2001).

Our results also prove that leaf texture becomesrigidly coriaceous and thick, i.e. more sclerophyllous,with increasing aridity and winter temperatures. Leaveswith thick cell walls and/or dense structure protect theplant against water loss. They have a low specific leafarea (SLA) and tend to be more abundant in the vegeta-tion when summer temperatures are high and whenwater availability is low (Mooney & Dunn 1970a; Specht& Rundel 1990; Cabido et al. 1993; Niinemets 2001).However, other strategies, such as effective stomatalclosure and cuticular restriction of water loss by thepresence of wax on the cuticle, can delay severe waterdeficits (Jefferson et al. 1989). Our results show thatbroad-leaved evergreen trees and shrubs with waxycuticles increase in abundance with increasing aridity.

Recent studies have shown that if leaf width andSLA both decline with increasing aridity and insolation,this is only valid at the plant community level wheremean traits values are calculated for the species found inthe plot. At the species level, however, leaf size varieswidely at any given level of leaf sclerophylly, and viceversa (Ackerly & Reich 1999; Fonseca et al. 2000;Ackerly et al. 2002). In agreement, we find that with

Fig. 6. CCA ordination diagram of 66 tree,shrub and forb composite plant traits (at thelife form and phenology level) plus grami-noid and geophyte life forms. The arrowsrepresent the gradients of water availability(α) and mean temperature of the coldestmonth (MTCO).


increasing aridity, at the trait level, leaf size decreaseswhile sclerophyll presence increases, but also that sizeand texture may not always go together at the life formand life form plus leaf phenology levels. For summer-green shrubs and forbs, leaves clearly become small andrigidly coriaceous when aridity increases, while forevergreen trees and shrubs, leaves can become sclero-phyllous as temperature and/or aridity increase, withoutbecoming smaller (Fig. 5).

Our results show that under a cool climate, trees aremainly needle-leaved while under wet and cold climate,they are essentially broad-leaved but summer-green.Trees and shrubs tend to be broad-leaved and evergreenwhen winter temperatures increase. However, shrubsare winter deciduous when aridity is very strong. Thedistribution of broad- and needle-leaved is physiologi-cally plausible according to temperature (Woodward1987). However, our response function, (which has avery low, although significant R2, Table 2) fails toreflect the abundance of needle-leaved (such as Pinushalepensis and Juniperus dupracea) under warm andxeric conditions, probably because other factors, such assoil nutrient richness, are responsible for the occurrenceof conifers. The distribution of evergreen and deciduousplants in the climate space is also physiologically plau-sible. The photosynthetic capacity of leaves decreaseswith age, such that trees subject to short growing sea-sons tend to be deciduous and have highly productiveleaves every year and hence, optimize energy uptakeduring the favourable season. On the contrary, ever-green leaves can conduct photosynthesis throughout theyear and show an appropriate strategy when environ-mental conditions are relatively favourable throughoutthe year (Box 1981; Kikuzawa 1991). The marked abun-dance of summer-green shrubs in the driest climatecould be interpreted as a response to drought. However,most deciduous elements are winter-deciduous in theMediterranean basin, even in the driest regions such asthe Near East (ca. 38° E) (Shmida 1981). The ordinationdiagram indicates that the climate range occupied bysummer-green shrubs is not only very arid, but is alsocharacterized by winter temperatures that are coolerthan that experienced by evergreens (Fig. 6). Hence, inagreement with previous studies, we find that plants dobetter by shedding their leaves every year when wintertemperatures are low (Woodward 1993). However,because they can make metabolic adjustments to re-strict carbon losses during the unfavourable seasonand because they can conduct photosynthesis through-out the year, evergreen plants are able to grow throughcompeting deciduous vegetation, putting them at adisadvantage once the evergreen dominate (Waring1991). While obligate summer-deciduous species arerare in the Mediterranean (only Euphorbia dendroides,

E. hierosolymntana and Anagyris foetida in the NearEast), some shrubs, however, are facultative summerdeciduous and have a green photosynthetic stem, e.g.Calcycotome, Genista, Retama, Spartium, Ulex (Shmida& Whittaker 1981). This system offers a very highcarbon fixation capacity and low water loss and iscommonly adopted by plants in arid areas (Mooney &Dunn 1970b). Our results show that summer-green shrubsand forbs with photosynthetic stems become increasinglyabundant with increasing aridity (Fig. 6). Spinescence,which is often associated with this syndrome (Shmida1981), also increases when aridity increases, as is shownfor other Mediterranean climatic areas (Mooney et al.1970).

Conclusions

Although we conducted this study based on pollendata, we have been able to identify gradients in theabundance of traits along climatic gradients. We alsofound a good agreement between our categories of planttraits and certain measured plant parameters, such asSLA and the subjective assessments of the degrees ofsclerophylly as given in the floras.

It is possible to consider individual leaf or plant leveltraits as diagnostic of climate (see, e.g., Wolfe 1990;Greenwood 1994; Niinemets 2001). However, most ofleaf or plant traits show different trends in the gradientof abundance with respect to climate, depending on lifeform, leaf type and leaf phenology. To derive meaning-ful relationships between plant level traits and climate,it is important to consider several traits together.

The recognition that the significance of individualleaf or plant level traits can differ amongst life formsunderpins the concept of a functional hierarchy of planttraits (Pillar 1999). Life form is the fundamental charac-teristic of a plant, leaf type and phenology are second-ary, and leaf and plant traits are tertiary characteristics.This hierarchy has emerged from various studies re-gardless of the approaches used (review by Lavorel etal. 1997), and is confirmed in our study.

The association of climatically diagnostic traits in ahierarchical way can provide an objective definition ofplant functional types (Steffen 1996; Smith et al. 1997) tomodel (e.g. Neilson et al. 1992) and to map (e.g. Prenticeet al. 2000, 2002a) vegetation patterns at a global scale.Our study suggests that it is possible to define PFTs in away that relates more closely to adaptive mechanisms,using specific, easily observable traits, and to relate thesePFTs to climatic thresholds in α and MTCO. However, amore objective way of defining zones of non-occurrenceand of maximum abundance for composite traits wouldbe to replace the arbitrary values for scores (at > 0.5 and


> 5) by probabilities of occurrence (Gachet et al. 2003).Finally, The climate-trait relationships established

for the circum-Mediterranean region need to be tested inother regions with Mediterranean type climates to deter-mine whether they are generally applicable. Also, toconduct similar analyses using species distribution data(e.g. Thuiller et al. in press) would provide a comple-mentary evaluation of our results. If, as we expect, therelationships established in this study are generally ap-plicable and can be extended to a wider range of cli-mates, they would provide a more solid basis for classi-fying PFTs at a global scale than has previously beenavailable.

Acknowledgements. This study is a contribution to theCiMBIO Project, supported by MPI-BGC. We thank membersof the project who have contributed original or unpublishedpollen data, and G. Boenisch for assistance in managing thedatabase. D. Barboni was funded through a Marie Curie Indi-vidual Fellowship from the EU (MCFI-2000-01599). We thankS. Lavorel for a helpful review of an earlier version of thispaper.

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Received 14 July 2002;Accepted 2 April 2004.

Co-ordinating Editor: J. Franklin.

For App. 1-3, see JVS/AVS Electronic Archives;www.opuluspress.se/pub/archives/index.htm

App. 1. Internet supplement to: Barboni, D. et al. 2004. Relationships between plant traits and climatein the Mediterranean region: A pollen data analysis. J. Veg. Sci. 15: 635-646.

Site name Longitude Latitude Elevation ReferencesA Cespedosa 1 and 2 –6.81 - –6.83 42.87 – 42.88 1425 Muñoz Sobrino et al. (1997)Akgol Adabag 33.73 37.50 1000 Bottema & Woldring (1984); Bottema (1987)

Albufera Alcudia 3.12 39.79 0 Burjachs et al. (1994)ALG1 - ALG5 –5.42 - –4.88 36.33 - 36.97 100 – 1051 Belmonte, J. unpubl.ALP1 - ALP9 –3.62 - –3.02 36.92 - 37.12 660 - 2350 Belmonte, J. unpubl.ALPA - ALPAC –3.12 - –2.92 37.15 - 37.18 1280 - 1660 Belmonte, J. unpubl.Alsa –4.02 43.12 820 Mariscal (1993)Amposta (Ebro Delta) 0.55 40.76 10 Peréz-Obiol, R. unpubl.Antas –1.82 37.21 0 Yll et al. (1995,1997)ARA1 - ARA4 –6.73 - –6.15 37.63 - 38.03 200 - – 810 Belmonte, J. unpubl.Arroyo de las Ciervas –6.23 41.97 790 Ramil–Rego, P. unpubl.Arsenala Varna Lake 27.83 43.20 0 Bozilova & Beug (1994)Atxuri –1.55 43.25 500 Peñalba (1989)Avlan Golu 29.95 36.58 1043 Bottema & Woldring (1984)Belia Kanton 24.30 41.83 1490 Panovska & Bozilova (1994)Besbog-2 23.67 41.75 2240 Stefanova & Bozilova (1995)Beysehir Golu 31.50 37.54 1120 Bottema & Woldring (1984)Black Sea S 28.49 42.07 0 Atanasova, J. unpubl.Black Sea SW 28.89 42.07 0 Atanasova, J. unpubl.Branas de Lamela –6.85 42.77 1280 Ramil-Rego, P. unpubl.BUR1 and BUR2 –3.87 - –3.32 42.38 - 42.63 990 - 1035 Belmonte, J. unpubl.Cairn 6.56 45.33 2315 David, F. unpubl.Chan do Lamoso –7.53 43.57 1039 Ramil-Rego, P. unpubl.Chao de Cheira-I –8.20 41.60 475 Ramil-Rego, P. unpubl.Chao do Chan da Cruz –7.53 43.52 800 Ramil-Rego, P. unpubl.Clota Yesera I and Clota Yesera II –0.12 41.40 354, 351 Davis, B.A.S. unpubl.Colfiori- 12.93 43.03 752 Brugiapaglia, E. unpubl.COV1 - COV9 –5.05 - –4.83 43.27 - 43.43 130 - 970 Belmonte, J. unpubl.COVA –5.03 43.38 220 Belmonte, J. unpubl.Cueto de la Avellanosa –4.36 43.12 1320 Mariscal (1983)DAI1 –3.65 39.10 650 Belmonte, J. unpubl.Dayet Iffir –4.91 33.61 1500 Lamb et al. (1991)Delta del rio Besos 2.25 41.38 0 Pantaleon-Cano J. unpubl.Edessa 21.95 40.82 350 Bottema (1974)El Portillo 1 and El Portillo 2 –6.30 41.92 870 Ramil-Rego, P. unpubl.Elmali 29.89 37.67 930 Bottema & Woldring (1984)EUR1 - EUR9 –4.85 - –4.68 43.07 - 43.17 460 - 1860 Belmonte, J. unpubl.EUR A - EUR E –4.87 - –4.58 43.10 - 43.23 130 - 1450 Belmonte, J. unpubl.EXT1 - EXT8 –5.85 - –5.33 39.18 - 39.60 410 - 1000 Belmonte, J. unpubl.FRA1 - FRA9 –6.48 - –6.12 40.43 - 40.57 630 - 1400 Belmonte, J. unpubl.FRAA –6.03 40.45 610 Belmonte, J. unpubl.G001 - G110 20.4 - 22.73 39.45 - 40.88 –200 - 1650 Bottema (1974)GAT1 - GAT9 –6.5 - –6.37 40.10 - 40.47 510 - 1100 Belmonte, J. unpubl.GATA –6.50 40.50 710 Belmonte, J. unpubl.Golbasi Lake 37.55 37.75 890 van Zeist et al. (1968)Golhisar Golu 29.60 37.13 930 Bottema & Woldring (1984)Grand Ratz le Pellet 5.61 45.34 650 Clerc (1988)GUD1 - GUD9 –7.8 - –6.2 40.20 - 40.4 1000 - 1900 Belmonte, J. unpubl.GUDA –7.20 40.05 980 Belmonte, J. unpubl.Hieres sur Amby 5.28 45.79 410 Clerc (1988)Hoya de los Aljeces –0.23 41.37 325 Davis, B.A.S. unpubl.Hoya de los Berzas –0.22 41.40 334 Davis, B.A.S. unpubl.Hoya de Rafelez –0.23 41.38 321 Davis, B.A.S. unpubl.Hoya de Valdcarreta –0.22 41.39 340 Davis, B.A.S. unpubl.Hoya del Castillo –0.51 41.26 250 Davis, B.A.S. unpubl.Hoya del Vinagrero I and II –0.23 - –0.22 41.40 337 - 339 Davis, B.A.S. unpubl.Hoyo de Bo-nes –0.14 41.46 340 Davis, B.A.S. unpubl.Hoyran Golu 30.88 38.28 920 Bottema, S. unpubl.Inurritza I and Inurritza II –2.15 - –2.13 43.30 200 Peñalba (1989)Kararmik Batagligi 30.80 38.43 1000 van Zeist et al. (1975)

App. 1. Modern pollen samples in the circum-Mediterranean region used for this study.

Site name Longitude Latitude Elevation References


Kardashinski Swamp 32.62 46.52 4 Kremenetskii, K.V. unpubl.Khimaditis Ia 21.57 40.59 560 Bottema (1974)Koiladha 23.02 37.92 –10 Bottema, S. unpubl.Koycegiz Golu 28.64 36.88 20 Bottema, S. unpubl.Kupena 24.33 41.98 1300 Huttunen et al. (1992)La Bobia-1 –6.93 43.38 900 Ramil-Rego, P. unpubl.La Estanca 1 and 2 –0.19 41.06 342 - 337 Davis, B.A.S. unpubl.La Laguna 1 –4.09 38.75 670 Stevenson, A.C. unpubl.La Laguna 2 –3.99 37.09 2260 Stevenson, A.C. unpubl.La Piedra –3.87 42.63 950 Muñoz Sobrino et al. (1997)Lac Saint Leger I and Iic 6.34 44.42 1308 Beaulieu (1977)Ladik Golu 36.02 40.92 950 Bottema (1991)Lago de Ajo –6.15 43.05 1570 McKeever (1984); Allen et al. (1996)Lago di Martignano 12.33 42.12 200 Kelly & Huntley (1991)Lago Grande di Monticchio (MONTLONG)15.60 40.93 1326 Watts (1985)Lagoa de Cospei –7.53 43.25 400 Ramil-Rego, P. unpubl.Lagoa de Lucenza –7.12 42.58 1440 Ramil-Rego, P. unpubl.Lagoa de Marinho –8.10 41.75 1150 Ramil-Rego, P. unpubl.Laguna Albardiosa –3.29 39.66 660 Stevenson, A.C. unpubl.Laguna Alcahozo –2.88 39.40 670 Stevenson, A.C. unpubl.Laguna Alcaparrosa –5.81 37.05 30 Stevenson, A.C. unpubl.Laguna Almodovar –4.17 38.70 670 Stevenson, A.C. unpubl.Laguna Altillo –3.30 39.69 700 Stevenson, A.C. unpubl.Laguna Amarga, Amarga-Mid and -Shore–4.69 37.48 370 Stevenson, A.C. unpubl.Laguna Arjona –5.82 37.04 30 Stevenson, A.C. unpubl.Laguna Barrillos –5.60 41.26 670 Stevenson, A.C. unpubl.Laguna Camino de Villafranca –3.26 39.42 620 Stevenson, A.C. unpubl.Laguna Campano –6.11 36.35 10 Stevenson, A.C. unpubl.Laguna Caracuel –4.07 38.83 670 Stevenson, A.C. unpubl.Laguna Carboneras –3.96 38.76 780 Stevenson, A.C. unpubl.Laguna Carralogroño –2.57 42.54 560 Stevenson, A.C. unpubl.Laguna Carravalseca –2.57 42.53 560 Stevenson, A.C. unpubl.Laguna Carrizosa –4.24 38.84 690 Stevenson, A.C. unpubl.Laguna Cerro Mesado –3.27 39.33 620 Stevenson, A.C. unpubl.Laguna Chica –4.31 37.10 790 Stevenson, A.C. unpubl.Laguna Chica de Villafranca –3.34 39.46 950 Stevenson, A.C. unpubl.Laguna Comisario –6.02 36.53 70 Stevenson, A.C. unpubl.Laguna Cucharas –4.15 38.75 640 Stevenson, A.C. unpubl.Laguna de la Estanca –0.14 41.23 130 Davis, B.A.S. unpubl.Laguna de la Playa –0.19 41.42 326 Davis, B.A.S. unpubl.Laguna de la Roya –6.77 42.22 1608 Allen et al. (1996)Laguna de la Salinas –0.89 38.50 480 Stevenson, A.C. unpubl.Laguna de las Sanguijuelas –6.70 42.13 1080 Ramil-Rego, P. unpubl.Laguna de Pito –0.04 41.42 323 Davis, B.A.S. unpubl.Laguna del Pez –0.27 41.38 330 Davis, B.A.S. unpubl.Laguna Dulce –4.83 37.05 460 Stevenson, A.C. unpubl.Laguna Eras –4.59 41.20 790 Stevenson, A.C. unpubl.Laguna Fuente de Piedra –4.75 37.11 410 Stevenson, A.C. unpubl.Laguna Fuentilejo –4.06 38.94 690 Stevenson, A.C. unpubl.Laguna Gallocanta –2.18 40.83 995 Davis, B.A.S. unpubl.Laguna Gosque –4.94 37.13 430 Stevenson, A.C. unpubl.Laguna Grande –4.30 37.11 790 Stevenson, A.C. unpubl.Laguna Grande 2 –2.72 39.43 690 Stevenson, A.C. unpubl.Laguna Grande 3 –3.25 40.89 950 Stevenson, A.C. unpubl.Laguna Grande-Mid and -Shore –4.30 37.11 790 Stevenson, A.C. unpubl.Laguna Guallar 1 and 2 –0.23 41.42 336 Davis, B.A.S. unpubl.Laguna Honda –4.13 37.60 450 Stevenson, A.C. unpubl.Laguna Iglesia –4.59 41.20 770 Stevenson, A.C. unpubl.Laguna Lomillos –3.94 38.74 760 Stevenson, A.C. unpubl.Laguna Malgarejo –2.83 39.40 670 Stevenson, A.C. unpubl.Laguna Manjavacas –2.86 39.42 670 Stevenson, A.C. unpubl.Laguna Marchalicho 1 (Upper) –1.88 37.13 700 Stevenson, A.C. unpubl.

App. 1, cont.



Laguna Mediana 0.73 41.50 340 Stevenson, A.C. unpubl.Laguna Medina –6.05 36.62 30 Reed et al. (2001)Laguna Medina –6.05 36.62 20 Stevenson, A.C. unpubl.Laguna Michos –4.36 38.96 680 Stevenson, A.C. unpubl.Laguna Nava Grande –3.94 39.18 620 Stevenson, A.C. unpubl.Laguna Navazuela –2.74 39.44 680 Stevenson, A.C. unpubl.Laguna Ontalafia –1.26 38.71 840 Stevenson, A.C. unpubl.Laguna Peña Hueca –3.34 39.51 650 Stevenson, A.C. unpubl.Laguna Pilon –5.90 36.91 70 Stevenson, A.C. unpubl.Laguna Prado (Laguna Pozuelo) –3.83 38.92 620 Stevenson, A.C. unpubl.Laguna Ratosa –4.70 37.18 450 Stevenson, A.C. unpubl.Laguna Rincon, Rincon-Mid and -Shore–4.63 37.46 310 Stevenson, A.C. unpubl.Laguna Rodrigo –4.46 40.98 900 Stevenson, A.C. unpubl.Laguna Rollico –0.30 41.39 323 Stevenson, A.C. unpubl.Laguna Salada Chiprana –0.26 41.16 150 Davis, B.A.S. unpubl.Laguna Salada de Chiprana –0.18 41.24 150 Davis, B.A.S. unpubl.Laguna Salicor –3.17 39.47 680 Stevenson, A.C. unpubl.Laguna Salina Grande (Laguna Villafafila)–5.61 41.83 671 Stevenson, A.C. unpubl.Laguna Salinas (Laguna de Villarin) –5.63 41.80 670 Stevenson, A.C. unpubl.Laguna Salobral (Laguna Conde) –4.20 37.59 410 Stevenson, A.C. unpubl.Laguna Sanchez Gomez –2.83 39.44 660 Stevenson, A.C. unpubl.Laguna Sarinena –3.17 41.80 380 Davis, B.A.S. unpubl.Laguna Tarage –6.06 36.55 70 Stevenson, A.C. unpubl.Laguna Taraje –5.91 36.92 50 Stevenson, A.C. unpubl.Laguna Taray las Pedroñeras –2.76 39.41 690 Stevenson, A.C. unpubl.Laguna Tirez –3.36 39.54 650 Stevenson, A.C. unpubl.Laguna Tiscar –4.82 37.43 170 Stevenson, A.C. unpubl.Laguna Tollos –6.02 36.85 60 Stevenson, A.C. unpubl.Laguna Villarin de Camp –5.64 41.80 680 Stevenson, A.C. unpubl.Laguna Yeguas –3.29 39.42 620 Stevenson, A.C. unpubl.Laguna Zarracatín –5.80 37.03 20 Stevenson, A.C. unpubl.Laguna Zonar, Zonar-Mid and -Shore –4.69 37.48 290 Stevenson, A.C. unpubl.Lake Balaton centre 17.40 46.74 104 Nagy-Bodor et al. (1995)Lake Balaton NE 18.10 47.00 104 Nagy-Bodor et al. (1995)Lake Balaton SW 17.74 46.82 104 Nagy-Bodor et al. (1995)Lake Duranunlak 1 28.55 43.67 4 Bozilova & Tonkov (1985; Bozilova et al. (1998)Lake Shabla Ezeretz 28.85 43.83 1 Filipova (1985)Lake Srebarna 27.12 44.82 20 Lazarova (1995)Lake Trikhonis 21.50 38.60 20 Bottema (1982)Lake Van 43.00 38.50 1648 van Zeist & Woldring (1978)Lake Vegoritis 21.75 40.75 570 Bottema (1982)Lake Viviis 22.78 39.58 50 Bottema (1979)Lake Xinias 22.27 39.05 500 Bottema (1979); Digerfeldt (1998)Las Alforjetas –0.13 41.40 352 Davis, B.A.S. unpubl.Las Palanques 3 2.44 42.16 440 Peréz-Obiol (1988)Le Grand Lemps (LEMPS83) 5.42 45.47 500 Clerc (1988)Lillo-2 –5.23 43.07 1450 Ramil-Rego, P. unpubl.Lleguna –6.72 42.12 1050 Ramil-Rego, P. unpubl.Maleshevska Mts 23.03 41.70 1720 Tonkov & Bozilova (1992)Marais de la Perge –1.01 45.40 2 Diot & Tastet (1995)Marais de la Perge S –1.12 45.38 2 Diot & Tastet (1995)MON1 - MON9 –2.78 - –1.82 41.70 - 41.85 975 - 1620 Belmonte, J. unpubl.MON A - MON E –1.83 - –1.77 41.80 - 41.87 720 - –1450 Belmonte J. unpubl.Monte Areo XII –5.77 43.52 265 Ramil-Rego, P. unpubl.MOR1 - MOR6 –4.38 - –4.32 38.38 - 38.65 550 - 902 Belmonte, J. unpubl.MUN1 - MUN3 –6.90 - –5.53 42.75 - 42.98 800 - 1200 Belmonte, J. unpubl.Mutorog- Southern Pirin Mts. 23.62 43.52 1700 Panovska et al. (1995)NEV1 - NEV9 –3.40 - –3.32 37.05 - 37.13 1350 - 3085 Belmonte, J. unpubl.NEVA and NEVB –3.37 - 3.35 37.13 1320 - 1360 Belmonte, J. unpubl.Orihuela de Tremedal –2.05 40.54 1650 Stevenson (2000)Pelleautier 6.18 44.52 975 Beaulieu (1977)Pena Vella –7.48 43.45 700 Ramil-Rego P. unpubl.

App. 1, cont.



Popovo Ezero 23.67 41.72 2185 Stefanova & Bozilova (1995)Porto Ancares –6.80 42.87 1580 Muñoz Sobrino et al. (1997)Pozo de Carballal –7.10 42.70 1330 Muñoz Sobrino et al. (1997)Puerto de Belate II –2.05 43.03 847 Peñalba (1989, 1994)Puerto de los Tornos –3.43 43.15 920 Peñalba (1989)Puerto de los Tornos-1 and -2 –3.43 43.15 920 Ramil-Rego, P. unpubl.Puerto del Escudo –3.87 43.08 940 Ramil-Rego, P. unpubl.Quintanar de la Sierra II –3.00 42.03 1470 Peñalba (1994, 1997)RON1 - RON8 –5.37 - –4.97 36.67 - 36.82 660 - 1400 Belmonte, J. unpubl.Sabbion 7.47 44.13 2216 Beaulieu (1977)Saint Julien de Ratz II 5.62 45.35 650 Clerc (1988)Saint Sixte 5.63 45.43 650 Clerc (1988)Salada Grande –0.20 41.04 370 Davis, B.A.S. unpubl.Salada Pequena 1 and 2 –0.22 41.04 357 - 370 Davis, B.A.S. unpubl.Saldropo –2.72 43.05 625 Peñalba (1989, 1994)Salina de la Muerte –0.26 41.40 335 Davis, B.A.S. unpubl.Salina de Pinol –0.25 41.43 338 Davis, B.A.S. unpubl.Salina del Cameron –0.28 41.41 328 Davis, B.A.S. unpubl.Salina del Rebellon –0.31 41.38 319 Davis, B.A.S. unpubl.San Ciprian –7.02 43.22 802 Ramil-Rego, P. unpubl.San Mames de Abar –3.97 42.62 920 Ramil-Rego, P. unpubl.San Rafael –2.60 36.77 0 Yll et al. (1995)SAN1 - SAN3 –3.98 - –3.62 43.4 - 43.43 20 - 150 Belmonte, J. unpubl.Sanabria Marsh –6.73 42.10 1050 Hannon (1985); Allen (1996)Selle di Carnino 7.69 44.15 1905 Beaulieu (1977)Serra do Agra -1 and Agra-2 –8.73 41.83 800 Ramil-Rego, P. unpubl.Sogut Golu 29.88 37.05 1400 van Zeist et al. (1975)Sredna Gora Mountains 24.83 42.83 1300 Filipovitch (1977); Petros & Filipovitch (1987)Suarbol –6.85 42.85 1080 Ramil-Rego, P. unpubl.SY01 - SY86 35.67 - 41.08 33.37 - 36.66 50 - 2100 Bottema & Barkoudah (1979)TB01 - TB60 27.25 - 31.94 36.56 - 39.0 0 - 1500 van Zeist et al. (1968)Tremoal de Ganidoira –7.62 43.55 700 Ramil-Rego, P. unpubl.Tremoal de Pena Veira –7.43 43.40 620 Ramil-Rego, P. unpubl.Tremoal de Schwejk –7.45 43.42 625 Ramil-Rego, P. unpubl.Tremoal de Sever –7.55 43.37 620 Ramil-Rego, P. unpubl.Tremoal do rio das Furnas–1 and –2 –7.55 43.53 750 - 800 Ramil-Rego, P. unpubl.Turbera de las Branuelas –6.20 42.67 1000 Ramil-Rego, P. unpubl.Veiga de Samarugo –7.57 43.42 800 Ramil-Rego, P. unpubl.Venta del Carrero E –0.11 41.40 360 Davis, B.A.S. unpubl.Venta del Carrero W –0.12 41.39 360 Davis, B.A.S. unpubl.Volvi 6 23.50 40.75 100 Bottema (1982)Zirbenwaldmoor 11.03 46.86 2150 Rybnicek & Rybnikova (1977)Zsombo–swamp 19.99 46.36 92 Nagy-Bodor et al. (1995)

App. 1, cont.


App. 2. Internet supplement to: Barboni, D. et al. 2004. Relationships between plant traits and climate in the Mediterranean region: an analysisbased on pollen data. J. Veg. Sci. 15: 635-646.

1

App. 2. Assignment of combined traits to pollen taxa

Lifeform

Leaftype

Phenology Classes Taxa list

Tree needle evergreen Abies, Cedrus, Picea, Pinaceae, Pinus, P. diploxylon, P. haploxylon, Taxussummer-green

Larix

Tree scale Casuarina, Cupressaceae, Tamarix

Tree broad evergreen pico Ericaceae, Fabaceae

lepto Erica arborea, Ericaceae, Fabaceae, Galium type

nano Buxus, Fabaceae, Galium type, Olea, O. europaea, Olea/Ligustrum, Rhamnus type

micro Cassia, Celtis, Ceratonia, Citrus, Eucalyptus, Fabaceae, Ficus, Olea, O. europaea, Olea/Ligustrum, Phillyrea, Pistacia, Quercus, Q.coccifera, Quercus Evergreen, Q. ilex/coccifera, Q. suber type, Rhamnus type, Rhus type, Viburnum, V. opulus type

noto Arbutus, Cassia, Celtis, Eucalyptus, Ficus, Ilex, Ligustrum, Olea, Olea/Ligustrum, Prunus type, Quercus, Quercus Evergreen, Q.ilex, Q. rotundifolia, Viburnum, V. opulus type

meso Celtis, Ficus, Laurus, Olea, Olea/Ligustrum, Prunus type, Quercus, Viburnum, V. opulus type

macro Ficus, Prunus type

mega Ricinus

membranous Capparidaceae, Caprifoliaceae, Cassia, Celtis, Eucalyptus, Euphorbiaceae, Fabaceae, Ficus, Galium type, Ligustrum, Moraceae,Myrtaceae, Olea, O. europaea, Olea/Ligustrum, Oleaceae, Oleaceae/Brassicaceae, Pistacia, Quercus, Rhamnaceae, Rhamnus type,Rhus type, Ricinus, Verbenaceae, Viburnum, V. opulus type

coriaceous Anacardiaceae, Arbutus, Buxus, Capparidaceae, Caprifoliaceae, Cassia, Celtis, Ceratonia, Citrus, Erica arborea, Ericaceae,Eucalyptus, Euphorbiaceae, Ficus, Ilex, Laurus, Moraceae, Myrtaceae, Olea, Olea/Ligustrum, Oleaceae, Oleaceae/Brassicaceae,Phillyrea, Pistacia, Prunus type, Quercus ilex/coccifera, Rhamnaceae, Verbenaceae, Viburnum opulus type

rigidly coriaceous Anacardiaceae, Cassia, Euphorbiaceae, Myrtaceae, Olea, Olea/Ligustrum, Oleaceae, Oleaceae/Brassicaceae, Quercus, Q. coccifera,Quercus Evergreen, Q. ilex, Q. ilex/coccifera, Q. rotundifolia, Q. suber type, Rhamnus type

thick Buxus, Euphorbiaceae, Ficus, Laurus, Olea, Olea/Ligustrum, Oleaceae, Oleaceae/Brassicaceae, Prunus type, Quercus ilex/coccifera,Rhamnaceae

hair Anacardiaceae, Capparidaceae, Caprifoliaceae, Cassia, Celtis, Erica arborea, Ericaceae, Euphorbiaceae, Fabaceae, Ficus, Galiumtype, Moraceae, Olea, O. europaea, Olea/Ligustrum, Oleaceae, Oleaceae/Brassicaceae, Phillyrea, Quercus, Quercus Evergreen, Q.ilex, Q. rotundifolia, Q. suber type, Rhamnaceae, Rhus type, Verbenaceae, Viburnum, V. opulus type

wax Arbutus, Buxus, Capparidaceae, Caprifoliaceae, Cassia, Ceratonia, Citrus, Eucalyptus, Euphorbiaceae, Fabaceae, Ficus, Ilex,Laurus, Ligustrum, Moraceae, Myrtaceae, Olea europaea, Oleaceae, Oleaceae/Brassicaceae, Phillyrea, Pistacia, Prunus type,Quercus, Q. coccifera, Quercus Evergreen, Q. ilex , Q. ilex/coccifera , Q. rotundifolia , Q. suber type, Rhamnaceae, Rhamnus type,Verbenaceae, Viburnum opulus type

aromatic Anacardiaceae, Eucalyptus, Laurus, Myrtaceae, Pistacia, Rhamnus type, Verbenaceae

spine Anacardiaceae, Capparidaceae, Citrus, Euphorbiaceae, Fabaceae, Ilex, Moraceae, Olea, O. europaea, Prunus type, Rhamnaceae,Rhamnus type, Verbenaceae

summer-green

pico Fabaceae

lepto Acacia type, Fabaceae, Galium type, Salix

nano Acacia type, Betula, Betulaceae, Fabaceae, Fraxinus, F. excelsior type, F. ornus type, Galium type, Rhamnus type, Salix, Sambucustype, Vitex agnus-castus


2

micro Acacia type, Acer, Alnus, Betula, Betulaceae, Cornaceae, Cornus suecica type, Crataegus type, Elaeagnus, Euonymus europeus,Fabaceae, Frangula alnus, Hippophaë rhamnoides, Juglans, Punica granatum, Quercus, Rhamnus type, Rhus type, Rosaceae, Salix,Sorbus type, Viburnum, V. opulus type, Vitex agnus-castus

noto Acer, Alnus, Betulaceae, Carpinus betulus type, Carpinus orientalis/Ostrya type, Carya, Castanea, Corylus, Elaeagnus, Fagus,Nyssa, Ostrya/Carpinus orientalis type, Ostrya/Corylus type, Parrotia, Populus, Prunus type, Pterocarya, Quercus, QuercusDeciduous, Quercus infectoria, Q. pubescens, Q. robur, Rosaceae, Tilia, Ulmus, Viburnum, V. opulus type, Vitex agnus-castus,Zelkova

meso Acer, Aesculus, Betulaceae, Cercis siliquastrum, Liquidambar, Morus, Platanus, Populus, Prunus type, Quercus, Q. canariensis, Q.cerris, Quercus Deciduous, Q. frainetto , Q. infectoria , Q. petraea , Q. robus/cerris , Rosaceae, Styrax, Tilia, Ulmus, Viburnum, V.opulus type, Vitex agnus-castus

macro Betula/Corylus/Myrica, Platanus, Prunus type

membranous Acacia type, Acer, Aesculus, Alnus, Betula, Betula/Corylus/Myrica, Betulaceae, Capparidaceae, Caprifoliaceae, Carpinus betulustype, Carpinus orientalis/Ostrya type, Carya, Castanea, Cercis siliquastrum, Cornaceae, Cornus suecica type, Corylus, Crataegustype, Elaeagnus, Euonymus europeus, Euphorbiaceae, Fabaceae, Fagus, Frangula alnus, Fraxinus, F. excelsior type, F. ornus type,Galium type, Hippophaë rhamnoides, Juglans, Liquidambar, Moraceae, Morus, Nyssa, Oleaceae, Oleaceae/Brassicaceae,Ostrya/Carpinus orientalis type, Ostrya/Corylus type, Parrotia, Platanus, Populus, Pterocarya, Punica granatum, Quercus, Q.canariensis, Q. cerris, Quercus Deciduous, Q. frainetto, Q. infectoria , Q. petraea, Q. pubescens, Q. robur, Q. robus/cerris,Rhamnaceae, Rhamnus type, Rhus type, Rosaceae, Salix, Sambucus type, Sorbus type, Styrax, Tilia, Ulmus, Viburnum, V. opulus

coriaceous Anacardiaceae, Betulaceae, Capparidaceae, Caprifoliaceae, Cornaceae, Elaeagnus, Euphorbiaceae, Moraceae, Oleaceae,Oleaceae/Brassicaceae, Prunus type, Rhamnaceae, Viburnum opulus type, Vitex agnus-castus

rigidly coriaceous Anacardiaceae, Euphorbiaceae, Oleaceae, Oleaceae/Brassicaceae, Quercus, Rhamnus type

thick Euphorbiaceae, Oleaceae, Oleaceae/Brassicaceae, Platanus, Prunus type, Rhamnaceae

hair Acacia type, Alnus, Anacardiaceae, Betula, Betulaceae, Capparidaceae, Caprifoliaceae, Cornaceae, Crataegus type, Euphorbiaceae,Fabaceae, Fagus, Galium type, Moraceae, Morus, Nyssa, Oleaceae, Oleaceae/Brassicaceae, Ostrya/Carpinus orientalis type,Ostrya/Corylus type, Populus, Quercus, Quercus Deciduous, Q. infectoria, Q. pubescens, Rhamnaceae, Rhus type, Rosaceae, Salix,Sorbus type, Styrax, Tilia, Ulmus, Viburnum, V. opulus type, Vitex agnus-castus

wax Betulaceae, Capparidaceae, Caprifoliaceae, Crataegus type, Euphorbiaceae, Fabaceae, Fraxinus, F. excelsior type, Juglans,Liquidambar, Moraceae, Oleaceae, Oleaceae/Brassicaceae, Platanus, Populus, Prunus type, Pterocarya, Punica granatum,Quercus, Rhamnaceae, Rhamnus type, Rosaceae, Salix, Viburnum opulus type, Vitex agnus-castus

aromatic Anacardiaceae, Rhamnus type, Salix, Styrax, Vitex agnus-castus

spine Acacia type, Anacardiaceae, Capparidaceae, Crataegus type, Elaeagnus, Euphorbiaceae, Fabaceae, Hippophaë rhamnoides,Moraceae, Prunus type, Punica granatum, Rhamnaceae, Rhamnus type, Rosaceae

rain-green pico Fabaceae

lepto Fabaceae

nano Fabaceae

micro Cassia, Celtis, Fabaceae

noto Cassia, Celtis

meso Celtis

membranous Cassia, Celtis, Euphorbiaceae, Fabaceae, Oleaceae/Brassicaceae, Rhamnaceae, Verbenaceae

coriaceous Anacardiaceae, Cassia, Celtis, Euphorbiaceae, Oleaceae/Brassicaceae, Rhamnaceae, Verbenaceae

rigidly coriaceous Anacardiaceae, Cassia, Euphorbiaceae, Oleaceae/Brassicaceae

thick Euphorbiaceae, Oleaceae/Brassicaceae, Rhamnaceae


3

hair Anacardiaceae, Cassia, Celtis, Euphorbiaceae, Fabaceae, Oleaceae/Brassicaceae, Rhamnaceae, Verbenaceae

wax Cassia, Euphorbiaceae, Fabaceae, Oleaceae/Brassicaceae, Rhamnaceae, Verbenaceae

aromatic Anacardiaceae, Verbenaceae

spine Anacardiaceae, Euphorbiaceae, Fabaceae, Rhamnaceae, Verbenaceae

Shrub scale Casuarina, Cupressaceae, Tamaricaceae, Tamarix

Shrub broad aphyllous Amaranthaceae-Chenopodiaceae, Euphorbia, Euphorbiaceae, Polygonaceae, Ulex type

Shrub broad evergreen pico Bupleurum, Calluna, Crassulaceae, Erica lusitanica type, Ericaceae, Fabaceae, Ulex type

lepto Artemisia, Bruckenthalia, Bupleurum, Calligonum type, Crassulaceae, Empetrum nigrum ssp. nigrum type, Erica arborea, E.lusitanica type, Ericaceae, Euphorbia, Fabaceae, Myricaria germanica, Spartium junceum, Ulex type, Vaccinium

nano Arctostaphylos uva-ursis, Artemisia, Atraphaxis type, Berberidaceae, Berberis vulgaris, Bupleurum, Buxus, Cistus type, Coremaalbum, Crassulaceae, Euphorbia, Fabaceae, Frankenia, F. hirsuta type, Helianthemum, Lonicera, Myricaria germanica, Myrtus,Olea, O. europaea, Olea/Ligustrum, Plumbaginaceae, Rhamnus type, Rhododendron, Ruta, Ulex type, Vaccinium, Zygophyllum

micro Arctostaphylos uva-ursis, Artemisia, Berberidaceae, Boraginaceae, Bupleurum, Cassia, Celtis, Cistus ladanifer, Cistus type,Crassulaceae, Daboecia, Daphne type, Erodium, Eucalyptus, Euphorbia, Fabaceae, Ficus, Fumana type, Helianthemum, Lonicera,Malvaceae, Myrica, Myrtus, Nitraria, Olea, O. europaea, Olea/Ligustrum, Pistacia, Plumbaginaceae, Quercus coccifera, Q.ilex/coccifera, Rhamnus type, Rhododendron, Solanum, S. nigrum type, Viburnum, V. opulus type, Zygophyllum

noto Acanthus, Berberidaceae, Boraginaceae, Cassia, Celtis, Crassulaceae, Daphne type, Erodium, Eucalyptus, Ficus, Ligustrum,Lonicera, Nerium oleander, Olea, Olea/Ligustrum, Prunus type, Rhododendron, Solanum, S. nigrum type, Viburnum, V. opulus type

meso Acanthus, Boraginaceae, Celtis, Ficus, Laurus, Olea, Olea/Ligustrum, Plumbaginaceae, Prunus type, Rhododendron, Solanum,Solanum nigrum type, Viburnum, V. opulus type

macro Ficus, Prunus type, Solanum, S. nigrum type

mega Ricinus

membranous Acanthus, Araceae, Artemisia, Atraphaxis type, Berberidaceae, Berberis vulgaris, Boraginaceae, Bupleurum, Calligonum type,Capparidaceae, Caprifoliaceae, Cassia, Celtis, Cistus ladanifer, Cistus type, Convolvulaceae, Daphne type, Erodium, Eucalyptus,Euphorbia, Euphorbiaceae, Fabaceae, Ficus, Fumana type, Geraniaceae, Helianthemum, Ligustrum, Lonicera, Loranthaceae,Malvaceae, Moraceae, Myrica, Myrtaceae, Myrtus, Nitraria, Olea, O. europaea, Olea/Ligustrum, Oleaceae, Oleaceae/Brassicaceae,Pistacia, Plumbaginaceae, Polygonaceae, Rhamnaceae, Rhamnus type, Ricinus, Ruta, Solanaceae, Solanum, S. nigrum type,Spartium junceum, Tamaricaceae, Ulex type, Vaccinium, Verbenaceae, Viburnum, V. opulus type

coriaceous Anacardiaceae, Araceae, Arctostaphylos uva-ursis, Berberidaceae, Berberis vulgaris, Bruckenthalia, Bupleurum, Buxus, Calluna,Capparidaceae, Caprifoliaceae, Cassia, Celtis, Convolvulaceae, Corema album, Daboecia, Empetrum nigrum ssp. nigrum type,Erica arborea, E. lusitanica type, Ericaceae, Eucalyptus, Euphorbiaceae, Ficus, Frankenia, F. hirsuta type, Laurus, Loranthaceae,Moraceae, Myricaria germanica, Myrtaceae, Nerium oleander, Olea, Olea/Ligustrum, Oleaceae, Oleaceae/Brassicaceae, Pistacia,Plumbaginaceae, Polygonaceae, Prunus type, Quercus ilex/coccifera, Rhamnaceae, Rhododendron, Solanaceae, Vaccinium,Verbenaceae, Viburnum opulus type, Zygophyllum

rigidly coriaceous Anacardiaceae, Berberidaceae, Cassia, Euphorbiaceae, Loranthaceae, Myrtaceae, Olea, Olea/Ligustrum, Oleaceae,Oleaceae/Brassicaceae, Quercus coccifera, Q. ilex/coccifera, Rhamnus type

succulent Capparidaceae, Caprifoliaceae, Convolvulaceae, Crassulaceae, Euphorbiaceae, Geraniaceae, Loranthaceae, Plumbaginaceae,Solanaceae, Tamaricaceae, Zygophyllum

thick Berberidaceae, Buxus, Crassulaceae, Empetrum nigrum ssp. nigrum type, Euphorbiaceae, Ficus, Geraniaceae, Laurus, Olea,Olea/Ligustrum, Oleaceae, Oleaceae/Brassicaceae, Polygonaceae, Prunus type, Quercus ilex/coccifera, Rhamnaceae, Solanaceae,Tamaricaceae, Zygophyllum

hair Acanthus, Anacardiaceae, Araceae, Arctostaphylos uva-ursis, Artemisia, Berberidaceae, Boraginaceae, Bupleurum, Capparidaceae,Caprifoliaceae, Cassia, Celtis, Cistus type, Convolvulaceae, Crassulaceae, Daphne type, Erica arborea, E. lusitanica type,


4

Ericaceae, Erodium, Euphorbia, Euphorbiaceae, Fabaceae, Ficus, Frankenia, F. hirsuta type, Fumana type, Geraniaceae,Helianthemum, Lonicera, Loranthaceae, Malvaceae, Moraceae, Myrica, Olea, O. europaea, Olea/Ligustrum, Oleaceae,Oleaceae/Brassicaceae, Plumbaginaceae, Polygonaceae, Rhamnaceae, Rhododendron, Solanaceae, Solanum, S. nigrum type,Spartium junceum, Ulex type, Vaccinium, Verbenaceae, Viburnum, V. opulus type, Zygophyllum

wax Araceae, Arctostaphylos uva-ursis , Berberidaceae, Bruckenthalia, Buxus, Capparidaceae, Caprifoliaceae, Cassia, Cistus ladanifer,Cistus type, Crassulaceae, Daboecia, Daphne type, Empetrum nigrum ssp. nigrum type, Eucalyptus, Euphorbiaceae, Fabaceae,Ficus, Geraniaceae, Laurus, Ligustrum, Lonicera, Moraceae, Myricaria germanica, Myrtaceae, Myrtus, O. europaea, Oleaceae,Oleaceae/Brassicaceae, Pistacia, Polygonaceae, Prunus type, Quercus coccifera, Q. ilex/coccifera, Rhamnaceae, Rhamnus type,Rhododendron, Tamaricaceae, Vaccinium, Verbenaceae, Viburnum opulus type, Zygophyllum

aromatic Anacardiaceae, Artemisia, Bupleurum, Cistus ladanifer, Cistus type, Eucalyptus, Geraniaceae, Laurus, Myrica, Myrtaceae, Myrtus,Pistacia, Rhamnus type, Ruta, Solanaceae, Verbenaceae

stemphotosynthetic

Crassulaceae, Euphorbiaceae, Fabaceae, Geraniaceae, Loranthaceae, Polygonaceae, Rhamnaceae, Spartium junceum, Tamaricaceae,Ulex type, Vaccinium, Verbenaceae

C3 Acanthus, Anacardiaceae, Araceae, Arctostaphylos uva-ursis, Artemisia, Atraphaxis type, Berberidaceae, Berberis vulgaris,Boraginaceae, Bruckenthalia, Bupleurum, Buxus, Calligonum type, Calluna, Capparidaceae, Caprifoliaceae, Cassia, Celtis, Cistusladanifer, Cistus type, Convolvulaceae, Corema album, Daboecia, Daphne type, Empetrum nigrum ssp. nigrum type, Erica arborea,E. lusitanica type, Ericaceae, Erodium, Eucalyptus, Euphorbia, Euphorbiaceae, Fabaceae, Ficus, Frankenia, F. hirsuta type,Fumana type, Geraniaceae, Helianthemum, Laurus, Ligustrum, Lonicera, Loranthaceae, Malvaceae, Moraceae, Myrica, Myricariagermanica, Myrtaceae, Myrtus, Nerium oleander, Nitraria, Olea, O. europaea, Olea/Ligustrum, Oleaceae, Oleaceae/Brassicaceae,Pistacia, Plumbaginaceae, Polygonaceae, Prunus type, Quercus coccifera, Q. ilex/coccifera, Rhamnaceae, Rhamnus type,Rhododendron, Ricinus, Ruta, Solanaceae, Solanum, S. nigrum type, Spartium junceum, Tamaricaceae, Ulex type, Vaccinium,Viburnum, V. opulus type

C4 Boraginaceae, Calligonum type, Euphorbia, Euphorbiaceae, Polygonaceae, Zygophyllum

CAM Crassulaceae, Euphorbia, Euphorbiaceae, Geraniaceae

spine Anacardiaceae, Atraphaxis type, Berberidaceae, Berberis vulgaris, Bupleurum, Capparidaceae, Convolvulaceae, Euphorbia,Euphorbiaceae, Fabaceae, Moraceae, Nitraria, Olea, O. europaea, Prunus type, Rhamnaceae, Rhamnus type, Solanaceae, Solanum,S. nigrum type, Spartium junceum, Ulex type, Verbenaceae

summer-green

pico Amaranthaceae-Chenopodiaceae, Fabaceae

lepto Amaranthaceae-Chenopodiaceae, Fabaceae, Salix, Vaccinium

nano Amaranthaceae-Chenopodiaceae, Berberidaceae, Betulaceae, Fabaceae, Lonicera, Plumbaginaceae, Rhamnus type, Ribes, Salix,Vaccinium, Vitex agnus-castus

micro Alnus, Amaranthaceae-Chenopodiaceae, Arctostaphylos alpinus, Berberidaceae, Betulaceae, Coriaria, Coriaria myrtifolia,Cornaceae, Cornus sanguinea type, Cornus suecica type, Elaeagnus, Euonymus europeus, Fabaceae, Fontanesia, Hippophaërhamnoides, Lonicera, Malvaceae, Myrica, Plumbaginaceae, Rhamnus type, Ribes, Rosaceae, Salix, Solanum, Solanum nigrum type,Viburnum, V. opulus type, Vitex agnus-castus

noto Alnus, Berberidaceae, Betulaceae, Elaeagnus, Lonicera, Ostrya/Corylus type, Prunus type, Rosaceae, Solanum, Solanum nigrumtype, Syringa, Viburnum, V. opulus type, Vitex agnus-castus, Zelkova

meso Betulaceae, Cercis siliquastrum, Gossypium, Plumbaginaceae, Prunus type, Rosaceae, Solanum, Solanum nigrum type, Styrax,Syringa, Viburnum, V. opulus type, Vitex agnus-castus

macro Betula/Corylus/Myrica, Prunus type, Solanum, Solanum nigrum type

membranous Alnus, Amaranthaceae-Chenopodiaceae, Berberidaceae, Betula/Corylus/Myrica, Betulaceae, Capparidaceae, Caprifoliaceae, Cercissiliquastrum, Coriaria, Coriaria myrtifolia, Cornaceae, Cornus sanguinea type, Cornus suecica type, Elaeagnus, Euonymuseuropeus, Euphorbiaceae, Fabaceae, Fontanesia, Geraniaceae, Gossypium, Hippophaë rhamnoides, Lonicera, Malvaceae,Moraceae, Myrica, Oleaceae, Oleaceae/Brassicaceae, Ostrya/Corylus type, Plumbaginaceae, Polygonaceae, Rhamnaceae, Rhamnus


5

type, Ribes, Rosaceae, Salix, Solanaceae, Solanum, Solanum nigrum type, Styrax, Syringa, Vaccinium, Viburnum, V. opulus type,Vitex agnus-castus, Zelkova

coriaceous Anacardiaceae, Arctostaphylos alpinus, Berberidaceae, Betulaceae, Capparidaceae, Caprifoliaceae, Coriaria myrtifolia, Cornaceae,Elaeagnus, Euphorbiaceae, Moraceae, Oleaceae, Oleaceae/Brassicaceae, Plumbaginaceae, Polygonaceae, Prunus type, Rhamnaceae,Solanaceae, Vaccinium, Viburnum opulus type, Vitex agnus-castus

rigidly coriaceous Amaranthaceae-Chenopodiaceae, Anacardiaceae, Berberidaceae, Euphorbiaceae, Oleaceae, Oleaceae/Brassicaceae, Rhamnus type

succulent Amaranthaceae-Chenopodiaceae, Capparidaceae, Caprifoliaceae, Euphorbiaceae, Geraniaceae, Plumbaginaceae, Solanaceae

thick Berberidaceae, Euphorbiaceae, Geraniaceae, Oleaceae, Oleaceae/Brassicaceae, Polygonaceae, Prunus type, Rhamnaceae,Solanaceae

hair Alnus, Anacardiaceae, Arctostaphylos alpinus, Berberidaceae, Betulaceae, Capparidaceae, Caprifoliaceae, Coriaria myrtifolia,Cornaceae, Euphorbiaceae, Fabaceae, Geraniaceae, Lonicera, Malvaceae, Moraceae, Myrica, Oleaceae, Oleaceae/Brassicaceae,Ostrya/Corylus type, Plumbaginaceae, Polygonaceae, Rhamnaceae, Ribes, Rosaceae, Salix, Solanaceae, Solanum, S. nigrum type,Styrax, Vaccinium, Viburnum, V. opulus type, Vitex agnus-castus

wax Amaranthaceae-Chenopodiaceae, Arctostaphylos alpinus, Berberidaceae, Betulaceae, Capparidaceae, Caprifoliaceae,Euphorbiaceae, Fabaceae, Geraniaceae, Lonicera, Moraceae, Oleaceae, Oleaceae/Brassicaceae, Polygonaceae, Prunus type,Rhamnaceae, Rhamnus type, Rosaceae, Salix, Vaccinium, Viburnum opulus type, Vitex agnus-castus

aromatic Anacardiaceae, Geraniaceae, Myrica, Rhamnus type, Salix, Solanaceae, Styrax, Vitex agnus-castus

stemphotosynthetic

Amaranthaceae-Chenopodiaceae, Euphorbiaceae, Fabaceae, Geraniaceae, Polygonaceae, Rhamnaceae, Vaccinium

C3 Alnus, Amaranthaceae-Chenopodiaceae, Anacardiaceae, Arctostaphylos alpinus, Berberidaceae, Betula/Corylus/Myrica, Betulaceae,Capparidaceae, Caprifoliaceae, Cercis siliquastrum, Coriaria, Coriaria myrtifolia, Cornaceae, Cornus sanguinea type, C. suecicatype, Elaeagnus, Euonymus europeus, Euphorbiaceae, Fabaceae, Fontanesia, Geraniaceae, Gossypium, Hippophaë rhamnoides,Lonicera, Malvaceae, Moraceae, Myrica, Oleaceae, Oleaceae/Brassicaceae, Ostrya/Corylus type, Plumbaginaceae, Polygonaceae,Prunus type, Rhamnaceae, Rhamnus type, Ribes, Rosaceae, Salix, Solanaceae, Solanum, S. nigrum type, Styrax, Syringa,Vaccinium, Viburnum, V. opulus type, Vitex agnus-castus, Zelkova

C4 Amaranthaceae-Chenopodiaceae, Euphorbiaceae, Polygonaceae

CAM Euphorbiaceae, Geraniaceae

spine Anacardiaceae, Berberidaceae, Capparidaceae, Elaeagnus, Euphorbiaceae, Fabaceae, Hippophaë rhamnoides, Moraceae, Prunustype, Rhamnaceae, Rhamnus type, Ribes, Rosaceae, Solanaceae, Solanum, S. nigrum type

rain-green pico Fabaceae

lepto Euphorbia, Fabaceae

nano Euphorbia, Fabaceae, Zygophyllum

micro Boraginaceae, Cassia, Celtis, Euphorbia, Fabaceae, Solanum, S. nigrum type, Zygophyllum

noto Acanthus, Boraginaceae, Cassia, Celtis, Solanum, S. nigrum type

meso Acanthus, Boraginaceae, Celtis, Solanum, S. nigrum type

macro Solanum, Solanum nigrum type

membranous Acanthus, Boraginaceae, Cassia, Celtis, Convolvulaceae, Euphorbia, Euphorbiaceae, Fabaceae, Oleaceae/Brassicaceae,Rhamnaceae, Solanaceae, Solanum, S. nigrum type, Verbenaceae

coriaceous Anacardiaceae, Cassia, Celtis, Convolvulaceae, Euphorbiaceae, Oleaceae/Brassicaceae, Rhamnaceae, Solanaceae, Verbenaceae,Zygophyllum

rigidly coriaceous Anacardiaceae, Cassia, Euphorbiaceae, Oleaceae/Brassicaceae

succulent Convolvulaceae, Euphorbiaceae, Solanaceae, Zygophyllum


6

thick Euphorbiaceae, Oleaceae/Brassicaceae, Rhamnaceae, Solanaceae, Zygophyllum

hair Acanthus, Anacardiaceae, Boraginaceae, Cassia, Celtis, Convolvulaceae, Euphorbia, Euphorbiaceae, Fabaceae,Oleaceae/Brassicaceae, Rhamnaceae, Solanaceae, Solanum, S. nigrum type, Verbenaceae, Zygophyllum

wax Cassia, Euphorbiaceae, Fabaceae, Oleaceae/Brassicaceae, Rhamnaceae, Verbenaceae, Zygophyllum

aromatic Anacardiaceae, Solanaceae, Verbenaceae

sphoto Euphorbiaceae, Fabaceae, Rhamnaceae, Verbenaceae

C3 Acanthus, Anacardiaceae, Boraginaceae, Cassia, Celtis, Convolvulaceae, Euphorbia, Euphorbiaceae, Fabaceae,Oleaceae/Brassicaceae, Rhamnaceae, Solanaceae, Solanum, S. nigrum type, Verbenaceae

C4 Boraginaceae, Euphorbia, Euphorbiaceae, Zygophyllum

CAM Euphorbia, Euphorbiaceae

spine Anacardiaceae, Convolvulaceae, Euphorbia, Euphorbiaceae, Fabaceae, Rhamnaceae, Solanaceae, Solanum, S. nigrum type,Verbenaceae

Liana/vine

broad evergreen lepto Jasminum

nano Berberidaceae, Jasminum, Lonicera, Periploca

micro Berberidaceae, Ficus, Hedera helix, Lonicera, Viburnum opulus type, Vitis

noto Berberidaceae, Ficus, Lonicera, Tamus communis, Viburnum opulus type, Vitis

meso Ficus, Viburnum opulus type, Vitis

macro Ficus, Vitis

membranous Araceae, Berberidaceae, Capparidaceae, Ficus, Jasminum, Lonicera, Moraceae, Oleaceae, Oleaceae/Brassicaceae, Periploca,Rhamnaceae, Solanaceae, Tamus communis, Verbenaceae, Viburnum opulus type, Vitis

coriaceous Anacardiaceae, Araceae, Berberidaceae, Capparidaceae, Ficus, Hedera helix, Moraceae, Oleaceae, Oleaceae/Brassicaceae,Periploca, Rhamnaceae, Solanaceae, Verbenaceae, Viburnum opulus type, Vitis

rigidly coriaceous Anacardiaceae, Berberidaceae, Oleaceae, Oleaceae/Brassicaceae

succulent Capparidaceae, Solanaceae

thick Berberidaceae, Ficus, Oleaceae, Oleaceae/Brassicaceae, Rhamnaceae, Solanaceae

hair Anacardiaceae, Araceae, Berberidaceae, Capparidaceae, Ficus, Lonicera, Moraceae, Oleaceae, Oleaceae/Brassicaceae, Rhamnaceae,Solanaceae, Verbenaceae, Viburnum opulus type

wax Araceae, Berberidaceae, Capparidaceae, Ficus, Hedera helix, Jasminum, Lonicera, Moraceae, Oleaceae, Oleaceae/Brassicaceae,Rhamnaceae, Verbenaceae, Viburnum opulus type, Vitis

C3 Anacardiaceae, Araceae, Berberidaceae, Capparidaceae, Ficus, Hedera helix, Jasminum, Lonicera, Moraceae, Oleaceae,Oleaceae/Brassicaceae, Periploca, Rhamnaceae, Solanaceae, Tamus communis, Verbenaceae, Viburnum opulus type, Vitis

spine Anacardiaceae, Berberidaceae, Capparidaceae, Moraceae, Rhamnaceae, Solanaceae, Verbenaceae

summer-green

nano Berberidaceae, Lonicera

micro Berberidaceae, Elaeagnus, Lonicera, Viburnum opulus type, Vitis

noto Berberidaceae, Elaeagnus, Lonicera, Parthenocissus, Viburnum opulus type, Vitis

meso Viburnum opulus type, Vitis

macro Vitis

membranous Berberidaceae, Capparidaceae, Elaeagnus, Lonicera, Moraceae, Oleaceae, Oleaceae/Brassicaceae, Parthenocissus, Rhamnaceae,Solanaceae, Viburnum opulus type, Vitis


7

coriaceous Anacardiaceae, Berberidaceae, Capparidaceae, Elaeagnus, Moraceae, Oleaceae, Oleaceae/Brassicaceae, Rhamnaceae, Solanaceae,Viburnum opulus type, Vitis

rigidly coriaceous Anacardiaceae, Berberidaceae, Oleaceae, Oleaceae/Brassicaceae

succulent Capparidaceae, Solanaceae

thick Berberidaceae, Oleaceae, Oleaceae/Brassicaceae, Rhamnaceae, Solanaceae

hair Anacardiaceae, Berberidaceae, Capparidaceae, Lonicera, Moraceae, Oleaceae, Oleaceae/Brassicaceae, Rhamnaceae, Solanaceae,Viburnum opulus type

wax Berberidaceae, Capparidaceae, Lonicera, Moraceae, Oleaceae, Oleaceae/Brassicaceae, Rhamnaceae, Viburnum opulus type, Vitis

C3 Anacardiaceae, Berberidaceae, Capparidaceae, Elaeagnus, Lonicera , Moraceae, Oleaceae, Oleaceae/Brassicaceae, Parthenocissus,Rhamnaceae, Solanaceae, Viburnum opulus type, Vitis

spine Anacardiaceae, Berberidaceae, Capparidaceae, Elaeagnus, Moraceae, Rhamnaceae, Solanaceae

rain-green nano Periploca

membranous Oleaceae/Brassicaceae, Periploca, Rhamnaceae, Solanaceae, Verbenaceae

coriaceous Anacardiaceae, Oleaceae/Brassicaceae, Periploca, Rhamnaceae, Solanaceae, Verbenaceae

rigidly coriaceous Anacardiaceae, Oleaceae/Brassicaceae

succulent Solanaceae

thick Oleaceae/Brassicaceae, Rhamnaceae, Solanaceae

hair Anacardiaceae, Oleaceae/Brassicaceae, Rhamnaceae, Solanaceae, Verbenaceae

wax Oleaceae/Brassicaceae, Rhamnaceae, Verbenaceae

C3 Anacardiaceae, Oleaceae/Brassicaceae, Periploca, Rhamnaceae, Solanaceae, Verbenaceae

spine Anacardiaceae, Rhamnaceae, Solanaceae, Verbenaceae

Forb aphyllous Amaranthaceae-Chenopodiaceae, Eriogonum type, Euphorbia, Euphorbiaceae, Polygonaceae

Forb broad pico Amaranthaceae-Chenopodiaceae, Brassicaceae, Bupleurum, Crassulaceae, Eriogonum type, Fabaceae, Polemonium

lepto Amaranthaceae-Chenopodiaceae, Artemisia, Brassicaceae, Bupleurum, Caryophyllaceae, Centaurea, C. cyanus type, C. nigra type,C. scabiosa type, Centaurea/Serratula type, Corydalis, Crassulaceae, Eriogonum type, Euphorbia, Fabaceae, Galium type,Illecebrum verticillatum, Parnassia palustris, Polygala, Polygonum, P. aviculare type, Primulaceae, Rumex type, Sanguisorbaminor ssp. minor, Sanguisorba type, Saxifraga, S. granulata type, S. hirsuta type, S. oppositifolia type, S. stellaris type, Spegulariatype, Spergula type, Taraxacum type, Thesium, Tribulus, Veronica type, Vicia type

nano Amaranthaceae-Chenopodiaceae, Anthemis type, Arnebia type, Artemisia, Brassicaceae, Bupleurum, Cannabaceae,Caryophyllaceae, Centaurea, C. cyanus type, C. nigra type, C. scabiosa type, Centaurea/Serratula type, Chrysosplenium,Corrigiola litoralis, Corydalis, Crassulaceae, Dryas, Emex, Euphorbia, Fabaceae, Galium type, Gentiana, G. pneumonanthe type,G. verna type, Gentianaceae, Geranium, Helianthemum, Helleborus, Herniaria type, Hypericum, H. perforatum type, Liliaceaetype, Linnaea borealis, Linum, Medicago, Papaveraceae, Parnassia palustris, Plumbaginaceae, Polygonum, P. alpinum, Potentilla,Primula veris type, Primulaceae, Radiola, Rhinanthus type, Rumex type, Sanguisorba officinalis, Sanguisorba type, Saxifraga, S.granulata type, S. hirsuta type, S. oppositifolia type, S. stellaris type, Scrophulariaceae, Sedum type, Spergula type, Taraxacumtype, Tribulus, Trifolium, Umbilicus rupestris type, Veronica type, Zygophyllum

micro Amaranthaceae-Chenopodiaceae, Ambrosia type, Anemone coronaria type, A. nemorosa, Anthemis type, Apiaceae, Arnebia type,Artemisia, Aster type, Atropa type, Boraginaceae, Brassicaceae, Bupleurum, Campanula type, Cannabaceae, Carthamnus,Caryophyllaceae, Centaurea, C. cyanus type, C. nigra type, C. scabiosa type, Centaurea/Serratula type, Circaea, Cirsium,Cornaceae, Cousinia, Crassulaceae, Datisca, Dryas, Epilobium type, Erodium, Euphorbia, Fabaceae, Filipendula, Fumana type,


8

Gentiana, G. pneumonanthe type, G. verna type, Gentianaceae, Gentianella, G. amarella type, G. campestris type, Geranium,Geum, Haplophyllum, Helianthemum, Heliotropium europaeum, Herniaria type, Hyoscyamus, Impatiens, Jasione type, Knautiatype, Lathyrus, Liliaceae type, Lobelia, Lythrum, L. portula, L. salicaria type, Malvaceae, Marrubium vulgare, Matthiola,Medicago, Mentha type, Mercurialis, Mesembryanthemum, Papaveraceae, Plantago, P. coronopus type, P. lanceolata type, P.major type, P. maritima type, P. media type, P. tenuiflora, Plumbaginaceae, Polemonium, Polygonum, P. aviculare type, P.persicaria type, Potentilla, Primula, P. veris type, Primulaceae, Prunella type, Ranunculaceae, Ranunculus type, Resedaceae,Rumex type, Saxifraga, S. granulata type, S. hirsuta type, S. oppositifolia type, S. stellaris type, Scabiosa type, Scrophularia type,Scrophulariaceae, Serratula type, Solanum, S. dulcamara, S. nigrum type, Stachys sylvatica type, Taraxacum type, Thalictrum,Theligonum, Urtica, U. dioica, Valerianaceae, Verbena officinalis, Viola arvensis type, V. palustris type, Zygophyllum

noto Acanthus, Anthemis type, Apiaceae, Arnebia type, Aster type, Atropa type, Boraginaceae, Brassicaceae, Cannabaceae, Carthamnus,Centaurea, Centaurea/Serratula type, Ceratocephalus, Chrozophora, Cousinia, Crassulaceae, Datisca, Digitalis purpurea type,Epilobium type, Erodium, Fagopyrum, F. esculentum, F. tataricum, Fumaria, Geranium, Hypecoum, Impatiens, Leontice type,Liliaceae type, Montia fontana type, Plantago media/major type, Primula, P. veris type, Primulaceae, Ranunculaceae, Ranunculustype, Rumex type, Saxifraga granulata type, S. hirsuta type, S. oppositifolia type, Scrophularia type, Serratula type, Solanum, S.nigrum type, Taraxacum type, Theligonum, Urtica dubia, U. pilulifera, Viola arvensis type, V. palustris type

meso Acanthus, Apiaceae, Arnebia type, Bongardia, Boraginaceae, Brassicaceae, Cannabis type, Carduus type, Digitalis purpurea type,Echinops, Fagopyrum, F. esculentum, F. tataricum, Impatiens, Liliaceae type, Myosotis arvensis type, Plantago media/major type,Plumbaginaceae, Primula veris type, Primulaceae, Ranunculaceae, Rumex type, Saxifraga granulata type, S. hirsuta type, S.oppositifolia type, Scabiosa type, Scrophularia type, Serratula type, Solanum, S. nigrum type, Symphytum, Tofieldia, Viola arvensistype, V. palustris type

macro Apiaceae, Arnebia type, Aster type, Listera type, Rheum, Serratula type, Solanum, S. nigrum type

mega Arnebia type

membranous Acanthus, Amaranthaceae-Chenopodiaceae, Ambrosia type, Anemone coronaria type, A. nemorosa, Anthemis type, Apiaceae,Araceae, Arnebia type, Artemisia, Aster type, Asteraceae, Asteraceae echinulate type, Atropa type, Bongardia, Boraginaceae,Brassicaceae, Bupleurum, Caltha type, Campanula type, Campanulaceae, Cannabaceae, Cannabis type, Capparidaceae,Caprifoliaceae, Carduus type, Carthamnus, Caryophyllaceae, Centaurea, C. cyanus type, C. nigra type, C. scabiosa type,Centaurea/Serratula type, Ceratocephalus, Chrozophora, Chrysosplenium, Circaea, Cirsium, Cistaceae, Convolvulaceae,Cornaceae, Corrigiola litoralis, Corydalis, Cousinia, Datisca, Digitalis purpurea type, Dipsacaceae, Emex, Epilobium type,Eriogonum type, Erodium, Euphorbia, Euphorbiaceae, Fabaceae, Fagopyrum, F. esculentum, F. tataricum, Filipendula, Fumanatype, Fumaria, Galium type, Gentiana, G. pneumonanthe type, G. verna type, Gentianaceae, Gentianella, G. amarella type, G.campestris type, Geraniaceae, Geranium, Geum, Halorrhagaceae, Haplophyllum, Helianthemum, Heliotropium europaeum,Helleborus, Herniaria type, Hyoscyamus, Hypecoum, Hypericum, H. perforatum type, Illecebrum verticillatum, Impatiens, Jasionetype, Knautia type, Lamiaceae, Lathyrus, Leontice type, Liliaceae type, Linnaea borealis, Linum, Listera type, Lobelia, Lythrum, L.portula, L. salicaria type, Malvaceae, Marrubium vulgare, Matthiola, Medicago, Mentha type, Mercurialis, Montia fontana type,Moraceae, Myosotis arvensis type, Oenotheraceae, Papaveraceae, Parnassia palustris, Plantago, P. coronopus type, P. lanceolatatype, P. major type, P. maritima type, P. media type, P. media/major type, P. tenuiflora, Plumbaginaceae, Polemonium, Polygala,Polygonaceae, Polygonum, P. alpinum, P. aviculare type, P. persicaria type, Potentilla, Primula, P. veris type, Primulaceae,Prunella type, Radiola, Ranunculaceae, Ranunculus type, Resedaceae, Rheum , Rhinanthus type, Rumex type, Sanguisorba minorssp. minor, Sanguisorba officinalis, Sanguisorba type, Saxifraga, S. granulata type, S. hirsuta type, S. oppositifolia type, S. stellaristype, Saxifragaceae, Scabiosa type, Scrophularia type, Scrophulariaceae, Sedum type, Serratula type, Solanaceae, Solanum, S.dulcamara, S. nigrum type, Spegularia type, Spergula type, Stachys sylvatica type, Symphytum, Tamaricaceae, Taraxacum type,Thalictrum, Theligonum, Thesium, Tofieldia, Tribulus, Trifolium, Umbilicus rupestris type, Urtica, U. dioica, U. dubia, U.pilulifera, Valerianaceae, Verbena officinalis, Verbenaceae, Veronica type, Vicia type, Viola arvensis type, V. palustris type,Violaceae

coriaceous Apiaceae, Araceae, Asteraceae, Asteraceae echinulate type, Bupleurum, Capparidaceae, Caprifoliaceae, Cistaceae, Convolvulaceae,Cornaceae, Dipsacaceae, Dryas, Echinops, Euphorbiaceae, Gentianaceae, Liliaceae type, Mesembryanthemum, Moraceae,


9

Cornaceae, Dipsacaceae, Dryas, Echinops, Euphorbiaceae, Gentianaceae, Liliaceae type, Mesembryanthemum, Moraceae,Plumbaginaceae, Polygonaceae, Primula veris type, Solanaceae, Verbenaceae, Zygophyllum

rigidly coriaceous Amaranthaceae-Chenopodiaceae, Apiaceae, Euphorbiaceae

succulent Amaranthaceae-Chenopodiaceae, Asteraceae, Asteraceae echinulate type, Capparidaceae, Caprifoliaceae, Convolvulaceae,Crassulaceae, Euphorbiaceae, Fagopyrum, Gentianaceae, Geraniaceae, Medicago, Mesembryanthemum, Plumbaginaceae, Primulaveris type, Saxifraga granulata type, S. hirsuta type, S. oppositifolia type, Saxifragaceae, Sedum type, Solanaceae, Spergula type,Tamaricaceae, Umbilicus rupestris type, Zygophyllum

thick Crassulaceae, Euphorbiaceae, Geraniaceae, Mesembryanthemum, Polygonaceae, Saxifragaceae, Solanaceae, Tamaricaceae,Zygophyllum

hair Acanthus, Ambrosia type, Anemone coronaria type, A. nemorosa, Anthemis type, Apiaceae, Araceae, Artemisia, Aster type,Asteraceae, Asteraceae echinulate type, Boraginaceae, Brassicaceae, Bupleurum, Campanulaceae, Cannabaceae, Capparidaceae,Caprifoliaceae, Carduus type, Carthamnus, Caryophyllaceae, Centaurea, C. cyanus type, C. nigra type, C. scabiosa type,Centaurea/Serratula type, Ceratocephalus, Chrozophora, Cirsium, Cistaceae, Convolvulaceae, Cornaceae, Crassulaceae, Digitalispurpurea type, Dipsacaceae, Echinops, Emex, Epilobium type, Eriogonum type, Erodium, Euphorbia, Euphorbiaceae, Fabaceae,Fagopyrum, F. esculentum, Fumana type, Galium type, Geraniaceae, Geranium, Helianthemum, Heliotropium europaeum,Herniaria type, Hyoscyamus, Impatiens, Jasione type, Lamiaceae, Malvaceae, Marrubium vulgare , Matthiola, Medicago, Menthatype, Mercurialis, Moraceae, Myosotis arvensis type, Oenotheraceae, Papaveraceae, Plantago coronopus type, P. lanceolata type,P. maritima type, P. media type, P. media/major type, Plumbaginaceae, Polemonium, Polygonaceae, Potentilla, Primula, P. veristype, Ranunculaceae, Ranunculus type, Rhinanthus type, Saxifraga, S. hirsuta type, S. stellaris type, Saxifragaceae, Scabiosa type,Scrophularia type, Scrophulariaceae, Serratula type, Solanaceae, Solanum, S. nigrum type, Spegularia type, Spergula type, Stachyssylvatica type, Symphytum, Taraxacum type, Tribulus, Trifolium, Urtica, U. dioica, U. dubia, U. pilulifera, Verbena officinalis,Verbenaceae, Veronica type, Viola arvensis type, V. palustris type, Violaceae, Zygophyllum

wax Amaranthaceae-Chenopodiaceae, Araceae, Caltha type, Capparidaceae, Caprifoliaceae, Cirsium, Crassulaceae, Echinops,Euphorbiaceae, Fabaceae, Gentiana verna type, Gentianaceae, Geraniaceae, Liliaceae type, Mesembryanthemum, Moraceae,Polygonaceae, Saxifraga granulata type, S. hirsuta type, S. oppositifolia type, Saxifragaceae, Tamaricaceae, Umbilicus rupestristype, Verbenaceae, Zygophyllum

aromatic Anthemis type, Apiaceae, Artemisia, Aster type, Asteraceae, Asteraceae echinulate type, Brassicaceae, Bupleurum, Cannabaceae,Cistaceae, Geraniaceae, Hypericum, H. perforatum type, Lamiaceae, Liliaceae type, Marrubium vulgare, Mentha type,Saxifragaceae, Solanaceae, Theligonum, Verbenaceae

stemphotosynthetic

Amaranthaceae-Chenopodiaceae, Apiaceae, Asteraceae, Asteraceae echinulate type, Cistaceae, Crassulaceae, Eriogonum type,Euphorbiaceae, Fabaceae, Geraniaceae, Liliaceae type, Polygonaceae, Tamaricaceae, Thesium, Verbenaceae

spine Apiaceae, Aster type, Asteraceae, Asteraceae echinulate type, Brassicaceae, Bupleurum, Capparidaceae, Carthamnus,Caryophyllaceae, Centaurea nigra type, Cirsium, Convolvulaceae, Dipsacaceae, Echinops, Euphorbia, Euphorbiaceae, Fabaceae,Liliaceae type, Moraceae, Saxifragaceae, Scabiosa type, Solanaceae, Solanum, S. nigrum type, Verbenaceae

C3 Acanthus, Amaranthaceae-Chenopodiaceae, Ambrosia type, Anemone coronaria type, A. nemorosa, Anthemis type, Apiaceae,Araceae, Arnebia type, Artemisia, Aster type, Asteraceae, Asteraceae echinulate type, Atropa type, Bongardia, Boraginaceae,Brassicaceae, Bupleurum, Caltha type, Campanula type, Campanulaceae, Cannabaceae, Cannabis type, Capparidaceae,Caprifoliaceae, Carduus type, Carthamnus, Caryophyllaceae, Centaurea, C. cyanus type, C. nigra type, C. scabiosa type,Centaurea/Serratula type, Ceratocephalus, Chrozophora, Chrysosplenium, Circaea, Cirsium, Cistaceae, Convolvulaceae,Cornaceae, Corrigiola litoralis, Corydalis, Cousinia, Datisca, Digitalis purpurea type, Dipsacaceae, Dryas, Echinops, Emex,Epilobium type, Eriogonum type, Erodium, Euphorbia, Euphorbiaceae, Fabaceae, Fagopyrum, F. esculentum, F. tataricum,Filipendula, Fumana type, Fumaria, Galium type, Gentiana, G. pneumonanthe type, G. verna type, Gentianaceae, Gentianella, G.amarella type, G. campestris type, Geraniaceae, Geum, Halorrhagaceae, Haplophyllum, Helianthemum, Heliotropium europaeum,Helleborus, Herniaria type, Hyoscyamus, Hypecoum, Hypericum, H. perforatum type, Illecebrum verticillatum, Impatiens, Jasionetype, Knautia type, Lamiaceae, Lathyrus, Leontice type, Liliaceae type, Linnaea borealis, Linum, Listera type, Lobelia, Lythrum, L.


10

portula, L. salicaria type, Malvaceae, Marrubium vulgare, Matthiola, Medicago, Mentha type, Mercurialis, Mesembryanthemum,Montia fontana type, Moraceae, Myosotis arvensis type, Oenotheraceae, Papaveraceae, Parnassia palustris, Plantago, P. coronopustype, P. lanceolata type, P. major type, P. maritima type, P. media type, P. media/major type, P. tenuiflora, Plumbaginaceae,Polemonium, Polygala, Polygonaceae, Polygonum, P. alpinum, P. aviculare type, P. persicaria type, Potentilla, Primula, P. veristype, Primulaceae, Prunella type, Radiola, Ranunculaceae, Ranunculus type, Resedaceae, Rheum , Rhinanthus type, Rumex type,Sanguisorba minor ssp. minor, Sanguisorba officinalis, Sanguisorba type, Saxifraga, S. granulata type, S. hirsuta type, S.oppositifolia type, S. stellaris type, Saxifragaceae, Scabiosa type, Scrophularia type, Scrophulariaceae, Serratula type, Solanaceae,Solanum, S. dulcamara, S. nigrum type, Spegularia type, Spergula type, Stachys sylvatica type, Symphytum, Tamaricaceae,Taraxacum type, Thalictrum, Theligonum, Thesium, Tofieldia, Trifolium, Urtica, U. dioica, U. dubia, U. pilulifera, Valerianaceae,Verbena officinalis, Verbenaceae, Veronica type, Vicia type, Viola arvensis type, V. palustris type, Violaceae

C4 Amaranthaceae-Chenopodiaceae, Asteraceae, Asteraceae echinulate type, Boraginaceae, Caryophyllaceae, Euphorbia,Euphorbiaceae, Heliotropium europaeum, Polygonaceae, Tribulus, Zygophyllum

CAM Aster type, Asteraceae, Asteraceae echinulate type, Crassulaceae, Euphorbia, Euphorbiaceae, Geraniaceae, Geranium, Sedum type,Umbilicus rupestris type

Life form Taxa list

Tuft treelet ChamaeropsWoodparasite

Arceuthobium oxycedri, Cuscuta europea type, Gentianaceae, Loranthaceae, Loranthus, L. europaeus, Viscum

Epiphyte Araceae, Impatiens, Moraceae, Orchidaceae

Cactoid Euphorbia, Euphorbiaceae

Climber Bryonia dioica, Calystegia, Cannabaceae, Convolvulaceae, Convolvulus, Euphorbiaceae, Humulus, Humulus/Cannabis, Lathyrus, Liliaceae type, Orchidaceae,Verbenaceae

Aquatic Alisma type, Apiaceae, Azolla, Azolla/Salvinia, Butomus umbellatus, Callitriche, Caltha type, Centaurium type, Convolvulaceae, Cyperaceae, Drosera, Elatine,Eriocaulon, Halorrhagaceae, Hippuris vulgaris, Hydrocharis morsus-ranae, Hydrocharitaceae, Isoetes, I. echinospora, I. hystrix, I. lacustris, Juncaceae, Lemna,Liliaceae type, Littorella uniflora, Menyanthaceae, Menyanthes trifoliata, Myriophyllum, Myriophyllum alterniflorum, Myriophyllum spicatum, Myriophyllumspicatum/M. verticillatum, Myriophyllum verticillatum, Najas marina, Nuphar, Nymphaea alba type, Nymphaeaceae, Nymphoides peltata, Oenotheraceae,Pinguicula, Polygonum amphibium, Potamogeton, Potamogeton subgenus Coleogeton, Potamogeton subgenus Potamogeton, Potamogeton type, Ranunculaceae,Ranunculus flammula type, Rumex type, Ruppia, Sagittaria, Salvinia, Sparganium/Typha, Sphagnum, Stratiotes aloides, Trapa natans, Typha, Utricularia

Moss Huperzia selago, Riccia type

Pteridophyte Adiantum capillus-veneris, Asplenium type, Blechnum spicant, Botrychium lunaria type/Ophioglossum vulgatum type A, Cheilantes type, Cryptogramma,Cystopteris, C. fragilis, Diphasiastrum type, Dryopteris, D. filix-mas type, Equisetum, Ferns, Filicales, Filicopsida, Hymenophyllum, Lycopodiaceae, Lycopodium,L. annotinum type, L. clavatum, Marsilea, Ophioglossum vulgatum, Osmunda regalis, Polypodiaceae, Polypodium vulgare type, Polystichum type, Pteridiumaquilinum, Pteris, Selaginella, Spore monolete, Spore monolete sculptured, Spore trilete, Spores, Thelypteris, Woodsia

Graminoid Avena-Triticum group, Cerealia type, Cyperaceae, Hordeum type, Lygeum type, Poaceae, Secale cereale, Zea mays

Geophyte Apiaceae, Aristolochia type, Asphodelus type, Liliaceae type, Orchidaceae, Oxalis, Ranunculaceae, Rumex type, Sisyrinchium

Root parasite Melampyrum, Orobanche, Pedicularis


TRAITStree 0.37 * -0.581 0.34 0.030 0.01 -0.002 0.00 10.240 0.94 -5.312 0.66 - -shrub 0.15 * 3.382 0.33 0.155 0.07 -0.004 0.00 -0.910 0.39 - - -0.143 0.07forb 0.23 6.145 0.25 -0.103 0.01 - - -3.882 0.29 - - - -geophyte 0.07 0.851 0.27 -0.122 0.04 - - 0.119 0.31 - - 0.120 0.05graminoid 0.06 2.585 0.33 -0.031 0.01 - - -1.831 0.90 1.495 0.63 - -scale 0.19 * -3.641 0.82 0.282 0.09 -0.008 0.00 12.777 1.82 -8.516 1.04 -0.407 0.10aphyllous 0.36 * 4.442 0.38 -0.055 0.02 0.002 0.00 -5.750 1.05 1.622 0.74 - -evergreen 0.08 * -0.377 0.75 0.252 0.08 -0.004 0.00 9.148 1.67 -5.398 0.96 -0.248 0.09summergreen 0.18 * 5.909 0.80 -0.410 0.06 - - -5.915 1.92 3.138 1.18 0.412 0.08pico 0.12 * 4.145 0.39 - - -0.006 0.00 -4.018 1.07 1.657 0.74 - -lepto 0.26 * 6.019 0.29 -0.230 0.04 - - -3.800 0.34 - - 0.150 0.05nano 0.15 * 5.031 0.16 -0.078 0.01 0.006 0.00 -1.778 0.19 - - - -micro 0.14 * 4.363 0.33 -0.038 0.01 0.004 0.00 1.734 0.93 -2.233 0.65 - -noto 0.16 * 3.094 0.34 -0.280 0.05 - - 0.411 0.40 - - 0.333 0.06meso 0.12 2.664 0.36 -0.316 0.05 - - -0.591 0.41 - - 0.345 0.07membranous 0.07 7.883 1.09 -0.419 0.12 0.005 0.00 -6.573 2.42 2.515 1.38 0.401 0.13coriaceous 0.08 3.931 0.73 -0.148 0.06 - - -5.735 1.74 3.402 1.07 0.277 0.07rigidly coriac. 0.36 * -0.816 0.77 0.347 0.09 -0.005 0.00 8.849 1.71 -6.709 0.98 0.357 0.09succulent 0.43 * 5.076 0.34 -0.191 0.07 0.005 0.00 -4.758 0.39 - - 0.101 0.07thick 0.13 * -3.139 0.88 0.423 0.10 -0.007 0.00 9.453 1.95 -5.796 1.12 -0.426 0.10hair 0.05 4.661 0.314 -0.249 0.048 - - -1.050 0.364 - - 0.307 0.059wax 0.23 * -0.709 0.50 0.295 0.04 - - 10.169 1.20 -6.533 0.74 -0.336 0.05aromatic 0.14 * 5.240 0.276 -0.228 0.056 0.003 0.002 -2.034 0.319 - - 0.174 0.056photo. stem 0.32 * 6.429 0.90 -0.281 0.10 0.004 0.00 -7.584 2.01 1.972 1.15 0.227 0.11C3 0.07 6.177 0.23 -0.213 0.04 - - -1.178 0.27 - - 0.225 0.04C4 0.34 * 6.173 0.88 -0.250 0.10 0.004 0.00 -7.542 1.96 2.051 1.12 0.175 0.10CAM 0.21 * 5.423 0.72 -0.477 0.08 0.008 0.00 -7.973 1.59 2.785 0.91 0.443 0.08spine 0.09 1.802 0.42 - - - - 1.999 1.18 -2.390 0.82 - -

COMPOSITE TRAITSForb

- aphyllous 0.34 * 3.672 0.18 -0.065 0.02 0.003 0.00 -3.441 0.20 - - - -- pico 0.37 * 4.310 0.18 -0.055 0.01 - - -3.820 0.21 - - - -- lepto 0.35 * 6.778 0.42 -0.310 0.09 0.006 0.00 -5.453 0.48 - - 0.200 0.09- nano 0.31 * 6.204 0.41 -0.239 0.08 0.005 0.00 -4.751 0.48 - - 0.140 0.08- micro 0.22 5.612 0.24 -0.086 0.01 - - -3.538 0.27 - - - -- membranous 0.23 6.147 0.25 -0.104 0.01 - - -3.887 0.29 - - - -- coriaceous 0.11 6.460 0.88 -0.521 0.10 0.006 0.00 -11.045 1.96 5.226 1.12 0.536 0.10- rigidly coriac. 0.32 * 3.761 0.18 -0.055 0.02 0.002 0.00 -3.316 0.21 - - - -- succulent 0.43 * 5.076 0.34 -0.191 0.07 0.005 0.00 -4.758 0.39 - - 0.101 0.07- hair 0.16 * 7.512 1.16 -0.496 0.13 0.008 0.00 -7.984 2.57 2.090 1.47 0.439 0.14- wax 0.33 * 3.912 0.18 -0.073 0.02 0.003 0.00 -3.449 0.21 - - - -- aromatic 0.24 * 6.766 0.92 -0.433 0.10 0.007 0.00 -8.339 2.04 2.479 1.17 0.384 0.11- photo.stem 0.31 * 4.547 0.20 -0.071 0.01 - - -3.687 0.23 - - - -- C3 0.23 6.147 0.25 -0.104 0.01 - - -3.887 0.29 - - - -- C4 0.36 * 4.640 0.19 -0.088 0.01 - - -4.002 0.22 - - - -- CAM 0.19 * 4.864 0.72 -0.397 0.08 0.006 0.00 -7.022 1.60 2.405 0.92 0.366 0.08- spine 0.14 * 7.252 1.06 -0.636 0.12 0.011 0.00 -10.068 2.36 3.675 1.35 0.594 0.12

Shrub broadleaved evergreen- pico 0.21 * 1.949 0.87 -0.093 0.10 -0.005 0.00 -5.516 1.92 4.873 1.10 0.240 0.10- lepto 0.11 * 6.513 0.64 -0.355 0.05 - - -12.062 1.53 6.923 0.94 0.427 0.06- nano 0.21 * -1.274 0.87 0.356 0.10 -0.005 0.00 8.393 1.93 -6.064 1.11 -0.411 0.10- micro 0.30 * -2.346 0.90 0.503 0.10 -0.007 0.00 11.211 2.00 -7.805 1.14 -0.555 0.11- membranous 0.21 * -0.994 0.87 0.346 0.10 -0.005 0.00 7.654 1.93 -5.542 1.10 -0.390 0.10- coriaceous 0.18 * -1.358 0.39 0.378 0.80 -0.009 0.00 2.630 0.45 - - -0.236 0.08- rigidly coriac. 0.23 * -2.252 0.63 0.304 0.05 - - 7.269 1.50 -4.820 0.92 -0.317 0.06- thick 0.19 * -2.968 0.82 0.433 0.09 -0.006 0.00 8.596 1.82 -5.299 1.04 -0.437 0.10- hair 0.09 0.953 0.36 0.279 0.07 -0.009 0.00 0.790 0.42 - - -0.207 0.07- wax 0.26 * -7.650 0.96 0.888 0.11 -0.012 0.00 20.010 2.13 -11.515 1.22 -0.930 0.11- aromatic 0.23 * 3.258 0.25 -0.099 0.04 - - -2.847 0.29 - - 0.069 0.05- C3 0.12 * 1.003 0.39 0.312 0.08 -0.008 0.00 0.865 0.45 - - -0.229 0.08- spine 0.25 * -6.425 0.80 0.689 0.09 -0.010 0.00 17.808 1.78 -10.625 1.02 -0.731 0.09

App. 3. Coefficients for the regression models obtained for plant traits and composite plant traits whose abundance is significantlycorrelated (p ≥ 0.05; * p ≥ 0.01) to mean temperature for the coldest month (MTCO) and plant water availability (a). Each model isbased on trait scores at all pollen sites (N= 602) available in the Mediterranean region and is calculated such as score = (β0 + β1 .MTCO + β2 . MTCO2+ β3 .α + β4 .α

2 + β5 . MTCO .α)2.

R2 Intercept SE MTCO SE MTCO2 SE α SE α2 SE MTCO . α SEβ0 † β1 † β2 † β3 † β4 † β5 †


Shrub broadleaved summergreen- pico 0.37 * 4.036 0.18 -0.077 0.02 0.003 0.00 -3.660 0.20 - - - -- lepto 0.34 * 3.991 0.18 -0.074 0.02 0.003 0.00 -3.518 0.20 - - - -- nano 0.34 * 3.952 0.18 -0.074 0.02 0.003 0.00 -3.472 0.21 - - - -- micro 0.16 * 5.670 0.83 -0.300 0.09 0.007 0.00 -7.696 1.84 3.061 1.05 0.280 0.10- noto 0.16 * 2.804 0.71 -0.340 0.08 0.006 0.00 -5.974 1.57 3.973 0.90 0.387 0.08- membranous 0.16 * 5.779 0.83 -0.270 0.09 0.006 0.00 -8.261 1.84 3.594 1.05 0.250 0.10- rigidly coriac. 0.39 * 3.797 0.17 -0.082 0.02 0.006 0.00 -3.640 0.20 - - - -- succulent 0.38 * 3.776 0.17 -0.073 0.02 0.004 0.00 -3.635 0.20 - - - -- hair 0.12 * 3.883 0.85 -0.439 0.09 0.007 0.00 -6.845 1.90 4.019 1.09 0.469 0.10- wax 0.24 * 5.035 0.83 -0.184 0.09 0.005 0.00 -6.263 1.85 2.012 1.06 0.140 0.10- photo.stem 0.34 * 3.917 0.18 -0.070 0.02 0.003 0.00 -3.486 0.20 - - - -- C3 0.16 * 5.779 0.83 -0.270 0.09 0.006 0.00 -8.261 1.84 3.594 1.05 0.250 0.10- C4 0.34 * 4.102 0.38 -0.059 0.02 0.003 0.00 -4.931 1.05 1.104 0.74

Tree/shrub scale-leaved 0.19 * -3.641 0.819 0.282 0.091 -0.008 0.003 12.777 1.821 -8.516 1.042 -0.407 0.096

Tree broadleaved evergreen- pico 0.18 * 1.418 0.81 -0.052 0.09 -0.005 0.00 -3.887 1.81 3.662 1.03 0.175 0.10- lepto 0.17 * 2.786 0.66 -0.274 0.05 - - -5.823 1.57 4.235 0.97 0.386 0.07- nano 0.23 * -5.999 0.81 0.604 0.09 -0.008 0.00 17.531 1.80 -10.715 1.03 -0.659 0.10- micro 0.34 * -8.534 0.94 0.822 0.10 -0.011 0.00 25.233 2.08 -15.329 1.19 -0.844 0.11- noto 0.06 -1.807 0.54 0.048 0.02 -0.004 0.00 7.880 1.51 -4.917 1.06 - -- membranous 0.22 * -5.349 0.81 0.544 0.09 -0.004 0.00 16.219 1.81 -9.905 1.03 -0.620 0.10- coriaceous 0.21 * -2.847 0.92 0.457 0.10 -0.010 0.00 6.758 2.04 -2.726 1.17 -0.325 0.11- rigidly coriac. 0.25 * -5.705 0.85 0.553 0.09 -0.009 0.00 17.373 1.88 -10.532 1.08 -0.540 0.10- thick 0.21 * -2.863 0.80 0.401 0.09 -0.004 0.00 8.581 1.79 -5.471 1.02 -0.414 0.09- hair 0.24 * -5.417 0.86 0.568 0.10 -0.012 0.00 16.043 1.92 -8.616 1.10 -0.487 0.10- wax 0.30 * -8.386 0.94 0.822 0.10 -0.012 0.00 24.241 2.08 -14.437 1.19 -0.843 0.11- spine 0.27 * -6.685 0.79 0.720 0.09 -0.010 0.00 18.236 1.75 -10.788 1.00 -0.764 0.09

Tree broadleaved summergreen- lepto 0.09 2.238 0.31 -0.322 0.06 0.004 0.00 -1.841 0.36 - - 0.299 0.06- nano 0.14 * 4.092 0.84 -0.485 0.09 0.007 0.00 -7.254 1.87 4.112 1.07 0.516 0.99- micro 0.20 * 5.601 0.95 -0.674 0.11 0.012 0.00 -10.176 2.11 5.931 1.21 0.705 0.11- noto 0.37 * 3.407 0.88 -0.497 0.07 - - -4.859 2.11 4.064 1.29 0.569 0.09- meso 0.24 * 1.594 0.30 -0.350 0.46 - - -0.003 0.35 - - 0.395 0.06- membranous 0.37 * 6.122 1.24 -0.843 0.14 0.006 0.00 -9.252 2.75 6.100 1.58 0.873 0.15- hair 0.32 * 3.157 0.85 -0.445 0.07 - - -3.322 2.04 2.616 1.25 0.476 0.08- wax 0.14 * 3.700 0.91 -0.489 0.10 0.007 0.00 -4.922 2.02 2.280 1.16 0.482 0.11

App. 3. Cont.

R2 Intercept SE MTCO SE MTCO2 SE α SE α2 SE MTCO . α SEβ0 † β1 † β2 † β3 † β4 † β5 †

relationships between plant traits and climate in the...

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