Kristin Metzner

Sophie Gachet

Pauline Rocarpin

Arne Saatkamp

Seed bank, seed size and dispersal in moisture gradients of

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

tor for co-existence in plant communities [START_REF] Silvertown | Plant coexistence and the niche[END_REF][START_REF] Silvertown | Hydrological niches in terrestrial plant communities: A review[END_REF]. A trade-off between water use efficiency and relative growth rate seems to drive niche partitioning along the hydrological gradient [START_REF] Angert | Functional tradeoffs determine species coexistence via the storage effect[END_REF][START_REF] Silvertown | Hydrological niches in terrestrial plant communities: A review[END_REF]. Niche partitioning and risk-reduction are both important mechanisms for persistence, but we still do not know how niche partitioning relates to risk-reduction [START_REF] Simons | Modes of response to environmental change and the elusive empirical evidence for bet hedging[END_REF]. This is important because most plants grow separately in local gradients (e.g. García-Baquero, [START_REF] García-Baquero | Dissecting the hydrological niche: Soil moisture, space and lifespan[END_REF] and perceive varying risk levels according to their niche boundaries.

Soil seed banks reduce risks when rainfall is unpredictable [START_REF] Cohen | Optimizing reproduction in a randomly varying environment[END_REF]) and this strategy can result in high abundance of seeds in the soil [START_REF] Volis | Joint evolution of seed traits along an aridity gradient: Seed size and dormancy are not two substitutable evolutionary traits in temporally heterogeneous environment[END_REF]. For deserts, one single global variance in rainfall is sufficient to model evolution of soil seed banks [START_REF] Clauss | Seed germination in desert annuals: An empirical test of adaptive bet hedging[END_REF][START_REF] Venable | Bet hedging in a guild of desert annuals[END_REF]). However, in small-scale gradients of moisture, the response of plants to rainfall variability is less synchronous [START_REF] García-Baquero | Dissecting the hydrological niche: Soil moisture, space and lifespan[END_REF][START_REF] Tielbörger | Germination behaviour of annual plants under changing climatic conditions: Separating local and regional environmental effects[END_REF]. In this case of uncorrelated local variances, when adjacent patches are different, seed dispersal is the optimal risk-reduction trait [START_REF] Nathan | Spatial patterns of seed dispersal, their determinants and consequences for recruitment[END_REF][START_REF] Siewert | Dispersal-dormancy relationships in annual plants: Putting model predictions to the test[END_REF][START_REF] Snyder | Multiple risk reduction mechanisms: Can dormancy substitute for dispersal?[END_REF][START_REF] Venable | The selective interaction of dispersal, dormancy and seed size as adaptations for reducing risks in variable environments[END_REF]. This suggests a shift of seed dispersal distances and seed bank abundances in moisture gradients, which has never been detected yet. Large seeds increase survival of seedlings under drought [START_REF] Baker | Seed weight in relation to environmental conditions in California[END_REF][START_REF] Daws | Germination responses to water potential in neotropical pioneers suggest large-seeded species take more risks[END_REF][START_REF] Leishman | The role of seed size in seedling establishment in dry soil conditions -Experimental evidence from semi-arid species[END_REF] and hence decrease the risk of extinction of a plant species. Soil seed banks may thus be negatively correlated with seed size and positively correlated with moisture. Since seed size is in a well-known trade-off with seed number [START_REF] Moles | Seed size and plant strategy across the whole life cycle[END_REF], large seeds have lower abundance in the soil and limited dispersal [START_REF] Bruun | Why are small seeds dispersed through animal guts: Large numbers or seed size per se?[END_REF][START_REF] Saatkamp | The seed bank longevity index revisited: Limited reliability evident from a burial experiment and database analyses[END_REF]. Moreover, large seeds have been suggested a risk-reduction trait because they store resources to survive adverse times [START_REF] Cohen | Optimizing reproduction in a randomly varying environment[END_REF][START_REF] Leishman | The role of seed size in seedling establishment in dry soil conditions -Experimental evidence from semi-arid species[END_REF][START_REF] Philippi | Hedging one's evolutionary bets, revisited[END_REF][START_REF] Siewert | Dispersal-dormancy relationships in annual plants: Putting model predictions to the test[END_REF]. Models revealed a negative correlation between seed size, seed banks and seed dispersal for locally homogenous habitats [START_REF] Cohen | The interaction between dispersal and dormancy strategies in varying and heterogeneous environments[END_REF][START_REF] Venable | The selective interaction of dispersal, dormancy and seed size as adaptations for reducing risks in variable environments[END_REF]. Altogether, large seed size should be associated with dry habitats and trade-off with soil seed bank abundance and seed dispersal in the moister habitats.

Beyond seed size, plants differ in adaptations to hydrology leading to varying water use efficiency, e.g. by C3, C4 and CAM phytosynthesis [START_REF] Keeley | CAM photosynthesis in submerged aquatic plants[END_REF] and in this way enable temporarily coexisting guilds [START_REF] Angert | Functional tradeoffs determine species coexistence via the storage effect[END_REF] or coexistance in spatially partitioned hydrological niches [START_REF] Ellenberg | Physiologisches und ökologisches Verhalten derselben Pflanzenarten[END_REF][START_REF] García-Baquero | Dissecting the hydrological niche: Soil moisture, space and lifespan[END_REF][START_REF] Silvertown | Hydrological niches in terrestrial plant communities: A review[END_REF]. It has been shown that niche partitioning in local moisture gradients contributes importantly to plant diversity [START_REF] Bauder | Inundation effects on small-scale plant distributions in San Diego, California vernal pools[END_REF][START_REF] Violle | Plant functional traits capture species richness variations along a flooding gradient[END_REF]. We therefore expect that effects of moisture niches on risk-reduction traits are strongest for moisture gradients on short spatial scales and when moisture gradients interfere with the extent of seed dispersal such as in Mediterranean temporary pools [START_REF] Deil | A review on habitats, plant traits and vegetation of ephemeral wetlands -A global perspective[END_REF]. Temporary pools are also subjected to strong year-to-year fluctuations in rainfall, increasing the importance of risk-reduction and they are notoriously rich in annual plants [START_REF] Deil | A review on habitats, plant traits and vegetation of ephemeral wetlands -A global perspective[END_REF]. Interestingly, year-to-year changes in surface are unequal for wet and dry habitats in the hydrological gradient. In wet years, high and steep areas remain dry while many lower parts are flooded, whereas in dry years even the lowest points remain dry. This implies that the importance of global versus local temporal variance experienced by plants differs according to their moisture niche in our gradient, i.e. aquatic plants have no escape and build up highly abundant soil seed banks [START_REF] Bauder | The effects of an unpredictable precipitation regime on vernal pool hydrology[END_REF], whereas plants with intermediate moisture niches should show higher seed dispersal.

Building on this context, we tested the following hypotheses on risk-reduction traits and moisture niches. (1) Abundance of seeds in soil banks increases towards the wet end of the moisture gradient, which is particularly pronounced in aquatic plants. (2) Dispersal of seeds in local gradients is highest for species with intermediate moisture niches, resulting in a higher spread in the soil seed bank for intermediate species.

(3) Seed size increases for species from dry habitats, reducing the effects of drought. (4) Seed dispersal, seed bank abundance and seed size may be negatively related, since they are alternative strategies of risk reduction.

We quantified abundance and dispersal of seeds in the soil bank as well as seed size for all vascular plant species in 15 Mediterranean temporary pools. We also quantified changes of water level over short distances, which are known to vary inter-annually with rainfall and to drive small-scale turnover in these plant communities [START_REF] Brock | Persistence of seed banks in Australian temporary wetlands[END_REF][START_REF] Deil | A review on habitats, plant traits and vegetation of ephemeral wetlands -A global perspective[END_REF][START_REF] Rhazi | The seed bank and the between years dynamics of the vegetation of a Mediterranean temporary pool (NW Morocco)[END_REF].

Materials and methods

Study sites

We studied three temporary wetland areas in Southern France, Feuillane (43 (2004( -2013, Istres), Istres). This site has alluvial soils with temporary pools in winter.

Evenos has a mean annual temperature of 16.4 ± 0.47 • C and a mean annual rainfall of 585 ± 168 mm (2004585 ± 168 mm ( -2013, Toulon), Toulon). A layer of tertiary basalt is the substrate for temporary pools.

Plaine des Maures has a mean annual temperature of 15.4 ± 0.56 • C and a mean annual rainfall of 747 ± 299 mm (2004-2013, Le Luc). Permian sandstones form shallow soils and temporary streamlets and pools. This site is of prime interest for the conservation of temporary pools in Europe and harbors 27 rare or endagered plant [START_REF] Grillas | Mediterranean temporary pools; Vol. 1-Issues relating to conservation, functioning and management[END_REF].

Sampling of established vegetation

In each of the three study sites we selected five temporary pools and at each pool a transect was laid out from the deepest point at the pool bottom to a dry point in the surrounding area. Along each transect, we established five sampling plots (1-5 m apart). Each plot consisted of 20 small quadrates (10 × 10 cm), which were arranged at right angles with the transect. Presence/absence of all vascular plants was recorded in each of the small quadrates, resulting in a total census area of 0.2 m 2 per plot. For analysis, we only used a plant's frequency in the small quadrates at plot level. We gathered data from April to June 2012 for Feuillane and Evenos and in June 2013 for Plaine des Maures. Nomenclature of plant names follows [START_REF] Tison | Flore de la France méditerranéenne continentale[END_REF].

Soil seed bank sampling

Around each plot we took 13 randomly placed soil cores. Cores had a diameter of 6 cm and a depth of 10 cm. Before sampling, we removed vegetation and litter. We mixed soil samples for each plot. The mixed soil samples were transported and stored at 3-5 • C until the emergence experiment. We sampled soil in April and June 2012 for Feuillane and Evenos and in June 2013 for Plaine des Maures. Sampling in spring avoided recently dispersed seeds and, hence, represents the persistent soil seed bank [START_REF] Walck | Defining transient and persistent seed banks in species with pronounced seasonal dormancy and germination patterns[END_REF]. However, some seeds of Cardamine hirsuta, Polypogon maritimus and Erophila verna dispersed before sampling.

We quantified seeds in the soil using the seedling emergence method (ter Heerdt 1996). We concentrated soil samples using sieves of 4 mm and 0.1 mm. The fine sieve retained even the smallest expected seeds (Juncus). These reduced samples were spread as a 0.5-cm layer in trays filled with vermiculite and cultivated in an unheated greenhouse at Aix Marseille University. We inclined the trays in water-filled panels with one side water-saturated and the other side 5 cm above the water line. We pooled all data, since we did not detect strong differences in emergence between both sides, and since both aquatic and xerophytic plants germinated well in this setting. We cultivated soil samples from Feuillane and Evenos from July to September 2012 and for Plaine des Maures, from November 2013 to June 2014. We counted emerged seedlings every week and removed identified plants. Unidentified seedlings were cultivated until identification.

Seed size

2 We measured seed size as dry weight of three replicates of 10 or 50 seeds of five individuals per species in 2012 and 2013.

Measurement and simulation of water levels in temporary pools

We measured water levels (L) at five dates in spring 2013 and spring 2014 for each of the 15 studied temporary pools. We then compiled data on daily precipitation (P) and daily potential evapo-transpiration (E) for the period 2011-2014 for each site. We used the simple water budget from [START_REF] Brooks | Weather-related effects on woodland vernal pool hydrology and hydroperiod[END_REF] to simulate water levels (in cm) for each pool on a daily basis. This model uses three parameters (a, b and c), which we fitted by maximizing the R 2 of the relation

L[t + 1] = (L[t] + a × P[t + 1] -b × E[t + 1]) × c
in a repeated linear regression. We then used the maximum water level obtained for each pool. We measured relative topographical heights of the different plots of all temporary pools with a water balance. The model for water level was run for the deepest point of each pool and we then substracted the topographical height to reach the water level value for each plot. This yielded negative water levels for dry habitats. We used these water levels as a surrogate for the moisture gradient in temporary pools and we calculated the mean and the median water level for each species.

Statistical analyses

We also used the position on an axis of Canonical Correspondence Analysis (CCA) as an alternative measure of a species' moisture niche [START_REF] Ter Braak | Canonical correspondence analysis: A new eigenvector technique for multivariate direct gradient analysis[END_REF]. We performed a CCA on a plot by species matrix, and transect position and site as environment data using the default settings of the cca module in vegan/R [START_REF] Oksanen | Vegan: Community ecology package[END_REF]). This forced the first axis parallel to the moisture gradient. We then compared a species' mean or median position on this axis from the established vegetation with its occurrence in the soil seed bank.

For comparisons between seed bank and standing vegetation we used box-plots of water levels or first CCA axis positions (Fig. 2) and t-or U-tests for comparison of means and Bartlett's test for variances.

In order to test the effect of moisture niche and seed size on the abundance of seeds in the soil, we used a zero-inflated negative binomial model to account for over-dispersion in our data [START_REF] Zuur | Mixed effects, models and extensions in ecology with R[END_REF]. We did a model selection based on likelihood-ratio tests and AICvalues as described in [START_REF] Zuur | Mixed effects, models and extensions in ecology with R[END_REF]. The optimal model for the count part was the full model with seed size, gradient position and their interaction. For the presence-absence part, only seed size was retained as predictor.

We measured spread of seeds in the soil along the gradient in terms of water levels or CCA-axis using the interquartile range (IQR) of gradient positions of all seeds of a species, IQR has been proven to be independent of sample size and can be used to compare species in our setting since number of occurrences vary; since IQR can be sensible to outliers we also calculated [START_REF] Rousseeuw | Alternatives to the median absolute deviation[END_REF] robust measure of scale as an alternative.

(B) (A) • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • -20 0 10
We tested the relation between moisture niche and spread by using a linear model of IQR on median seed positions in the gradient. Additionally, we wanted to know whether a non-linear model was more appropriate. We therefore also used generalized additive models (GAM) with two degrees of freedom to compare with the linear model. We also repeated all analyses using CCA axis in place of simulated water levels.

To study the relationship between seed size and moisture niche, we fitted a linear regression of log-transformed seed size against the median and mean of water levels for each species and of positions on the first CCA axis and alternatively compared it to a generalized additive model (GAM).

All analyses were performed in R (R-Core-Team 2014) using the packages vegan for CCA; pscl and lmtest for zeroinflated models and mcgv for GAM.

Results

The abundance of seeds in the soil seed bank was positively related to increasing moisture in the habitats of a plant (linear model of log-transformed abundances only, t = 2.2, p = 0.0285). This relation was even clearer when absences were included in a zero-inflated model with seed size as a covariate (Fig. 1). This indicates that species occurring in moist areas have higher abundances of seeds in the soil, independently of seed size (Fig. 1A). In this model, there was a weak interaction between seed size and gradient position, indicating that the effect of moisture niche was stronger for large than for small seeds. The correlation between plant position along the gradient and abundance in soil seed bank remained significant when median (z = 2.6, p = 0.0092) instead of mean positions were used or when its maximum abundance (z = 2.040, p = 0.0413) instead of total counts was used.

Moreover, the probability of an adult plant to be detected in the soil seed bank decreases with increasing seed size as illus-trated by the increase of false absences in the zero-inflated model (Fig. 1B). This relation between absence from seed bank and seed size was also found in a logistic regression on presence-absence data only (z = 3.174, p = 0.0015).

For 46 species, we had at least three occurrences in both data sets, so we compared their positions along the moisture gradient between standing vegetation and soil seed bank visually using box plots (Fig. 2). This revealed that most species were restricted to a particular range of water levels as adult plants. When sorted by the median position of adult plants (Fig. 2), the soil seed bank of a plant tended to be on drier parts at the moist gradient end and on moister parts at the dry gradient end compared to adults.

Using data on mean niche position and spread (interquartile range) in the soil seed bank of 78 species, we found a non-linear relationship (GAM analysis with seed size and abundance in the soil seed bank as (non-significant) covariates), with spread being larger at intermediate gradient positions (n = 78, F = 3.374, p = 0.0398, Fig. 3). This was confirmed when we used the Rosseuw-Croux index instead of the inter-quartile range (GAM, n = 78, F = 4.024, p = 0.0221) or when we used median positions instead of mean positions (GAM, n = 78, F = 3.509, p = 0.0352) and neither abundances of seeds in the soil (F = 0.661, p = 0.5195) nor seed size (F = 0.022, p = 0.9782) had an effect on spread. A linear model on the same data did not show any trend (df = 74, t = -0.465, p = 0.644).

We also analyzed niche spread for each species in the standing vegetation with at least three occurrences, measured by the inter-quartile range in water levels (Fig. 3). We found that it did not change with mean position in a linear model (df = 96, t = 0.1, p = 0.92), nor in a GAM (n = 98, F = 0.01, p = 0.92).

When we compared inter-quartile ranges between standing vegetation and soil seed bank, we found no overall significant difference (t-test, t = 1.6, p = 0.1022, N = 80). This result did not change when a robust measure of spread (Rosseuw-Croux index) was used or when only species occurring in both data sets were used in a paired t-test (t = -0.4, df = 40, p-value = 0.6727). The non-linear effect of a higher spread at intermediate gradient positions was even stronger when the moisture related CCA-axis 1 was used instead of water levels (analysis not shown).

When we compared water levels for seeds from the soil compared to adult plants within species, only two species, Ranunculus paludosus (t = -2.3, df = 8, p = 0.0572) and Lythrum hyssopifolia (t = -2.0, df = 15, p = 0.0524) tended to have adults in significantly moister conditions than seeds in the soil seed bank.

Additionally, comparing presence in the soil seed bank to the standing vegetation in the distribution along the gradient for each species separately, a Bartlett test of homogeneity of variances revealed that Lythrum borysthenicum (K 2 = 4.441, 100 200 300 400 500 600

-3 -2 -1 0 1 2 • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • Fig. 3.
Seed spread in soil along the gradient (inter-quartile range) on mean water level of a species and fitted line from a generalized additive model (n = 78, F = 3.374, p = 0.0398) with seed size and seed abundance as covariates. Inter-quartile range is square-root transformed and water level transformed to (x + 50) 1.5 to lessen leftskew. p = 0.0351), Juncus tenageia (K 2 = 8.5911, p = 0.0034) and Moenchia erecta (K 2 = 4.5512, p = 0.0329) had significantly greater variance in the soil seed bank and only Mentha pulegium (K 2 = 3.8831, p = 0.0488) had greater spread in the standing vegetation.

Using CCA axis coordinates instead of water levels to study positions of seeds from the soil compared to adults revealed that R. paludosus seeds (t = -4.3, df = 8, p = 0.0023) were found in drier conditions than the adult plants in the vegetation. A similar difference was found for Tuberaria guttata (t = 2.4, df = 12, p = 0.0354).

Using the CCA-axis, nine species (Callitriche brutia, Isolepis setacea, Juncus articulatus, Juncus bufonius, Juncus tenageia, Lythrum borysthenicum, Poa annua, Polypogon maritimus, Ranunculus peltatus, Sagina subulata) showed a larger spread in the soil seed bank compared to the standing vegetation (Bartlett's test of homogeneity of variances, K 2 = 4.2-23.4, p < 0.05). Only Juncus pygmaeus (K 2 = 4.2, p = 0.0348) and Plantago coronopus (K 2 = 3.1, p = 0.0796) had higher spread in the standing vegetation.

Seed size of a species decreased significantly (Fig. 4) with increasingly moist niches of adults as measured by their median position in the gradient. Analyzing the data set with non-linear regression methods (GAM R 2 = 0.14, F = 8.699, p = 0.0003) only slightly increased R 2 compared to the linear model and revealed again a generally decreasing seed size with increasing moisture. The species position on the moisture-related CCA-axis was also linearily related to seed size (p < 0.0001, t = 4.3, R 2 = 0.17). Analyzing this data as community-weighted means of seed size yielded a much weaker relationship (p = 0.049, marginal R 2 = 0.02).

•

• • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • -20
-10 0 10 20 30 0.01 0.1 1 10 Fig. 4. Seed size (weight on log-scale) and mean simulated water levels for 95 species of temporary pools. The regression line was calculated from a linear model on log-transformed data (p = 0.00172, t = -3.2, R2 = 0.10). Only species with at least 3 records are included. See Materials and methods section for details of water level simulation.

There was a significant negative relation between logtransformed seed size and log-transformed abundance in the soil seed bank with a slope of -0.3 ± 0.1 (t = -2.480, p = 0.0154). With gradient position as a covariate, there was no relation between seed size or seed abundance and measures of seed spread in the soil.

Discussion

Seed bank abundance and probability of detection of plant species in the seed bank by the seedling emergence method increased continuously with increasingly moist habitats, extending previous studies that reported generally high levels of seed bank for ephemeral wetlands [START_REF] Brock | Persistence of seed banks in Australian temporary wetlands[END_REF][START_REF] Cross | Seed dormancy and persistent sediment seed banks of ephemeral freshwater rock pools in the Australian monsoon tropics[END_REF][START_REF] Faist | Seed bank composition varies along invasion and inundation gradients in vernal pool wetlands[END_REF][START_REF] Leck | Ecological and evolutionary trends in wetlands: Evidence from seeds and seed banks in New South Wales, Australia and New Jersey, USA[END_REF][START_REF] Rhazi | The seed bank and the between years dynamics of the vegetation of a Mediterranean temporary pool (NW Morocco)[END_REF]. The effect of moisture niche on seed bank is statistically independent from seed size in our data and is thus not triggered by increasing seed size due to drought adaptation [START_REF] Leishman | The role of seed size in seedling establishment in dry soil conditions -Experimental evidence from semi-arid species[END_REF]. The high level of risk of aquatic species suggested by their abundant soil seed banks underlines previous studies showing that these species rely heavily on soil seed banks [START_REF] Bonis | Seed bank dynamics and coexistence of annual macrophytes in a temporary and variable habitat[END_REF][START_REF] Brock | Persistence of seed banks in Australian temporary wetlands[END_REF]. Increasing soil seed banks with higher moisture might be interpreted as a consequence of gravitational movement of seeds in vernal pools. However, moisture is the main factor that changes consistently in our transects even in flat or very rugged areas. Moreover, abundance of soil seed bank has been analyzed for position of adult plants, not for seed positions, and species show spe-cific lower limits of seed distributions (Figs. 1 A and2). We therefore think that moisture niches of adult plants trigger this change in the soil seed bank more than gravitational movement. Higher seed densities for the bottom compared to the margins of Californian vernal pools confirm this tendency for other regions [START_REF] Faist | Seed bank composition varies along invasion and inundation gradients in vernal pool wetlands[END_REF] and point to a relation between moisture niche and seed banking. Plants can achieve high abundance of seeds in the soil by producing high numbers of small seeds, increased levels of dormancy, light and fluctuating temperature requirements [START_REF] Saatkamp | The seed bank longevity index revisited: Limited reliability evident from a burial experiment and database analyses[END_REF][START_REF] Saatkamp | The functional role of soil seed banks in natural communities[END_REF]. For plants of Mediterranean temporary pools detailed laboratory studies [START_REF] Carta | Seed regeneration in Mediterranean temporary ponds: Germination ecophysiology and vegetation processes[END_REF][START_REF] Carta | Comparative seed dormancy and germination of eight annual species of ephemeral wetland vegetation in a Mediterranean climate[END_REF] indicate light and diurnally fluctuating temperature requirements as mechanisms for the build up of soil seed banks and that anoxia prevents germination. Experimental studies trying to exhaust seed banks of Australian temporary pools showed that many effective watering cycles or more than twelve years of successive exposure to germination seasons are needed to deplete soil seed banks to a low level, indicating that dormancy and specific germination conditions maintain an ungerminated but viable seed reservoir in the soil of temporary pools [START_REF] Brock | Persistence of seed banks in Australian temporary wetlands[END_REF][START_REF] Cross | Seed dormancy and persistent sediment seed banks of ephemeral freshwater rock pools in the Australian monsoon tropics[END_REF]. Together with data presented here this suggests that a gradient of increasing seed banking built upon adaptive traits such as germination requirements and reduced seed size exists from the surroundings to the interior of temporary pools.

Seeds recorded in the soil seed bank showed higher spread along the gradient for species with intermediate moisture requirements. This was independent of soil seed abundance or seed size, which confirms that spread measures were independent of sample size. We acknowledge that small-scale dispersal for individual plants can only be quantified by using seed traps around isolated individuals during the dispersal season [START_REF] Bonis | Seed bank dynamics and coexistence of annual macrophytes in a temporary and variable habitat[END_REF], but we think that spread of seeds trapped by soil is an indicator of small-scale dispersal. Higher spread of the seeds in the soil seed bank for intermediate species can also result from year-to-year shifting of above ground plant populations. However, it is difficult to quantify how much this shifting contributes to seed spread in our data compared to different dispersal distances. Nevertheless, when populations move according to moving environmental conditions, all species should have similar spreads of seeds in the soil including aquatic or xerophytic species, but this is not the case in our data, where we detected a higher spread of intermediate species, while controlling for seed production. We suggest that a modelling approach and in situ dispersal data are needed to quantify dispersal in moisture gradients.

Evidently, species on the moist or dry gradient end cannot move to better patches on a local scale, since in extreme years there are no moister or drier sites and adult plants would die from drought or flooding. Plants must thus have other adaptations for local persistence without movement such as a seed bank or a large seed size. These might be combined with adaptations for long distance dispersal instead of local scale dispersal such as hooks [START_REF] Fischer | Experimental studies on the dispersal of plants and animals on sheep in calcareous grasslands[END_REF][START_REF] Römermann | How to predict attachment potential of seeds to sheep and cattle coat from simple morphological seed traits[END_REF] or adaptations for long distance dispersal by wind [START_REF] Cheptou | Rapid evolution of seed dispersal in an urban environment in the weed Crepis sancta[END_REF]. The effective long distance dispersal for aquatic species by water and birds is a long known fact [START_REF] Darwin | On the origin of species by means of natural selection, or preservation of favored races in the struggle for life[END_REF][START_REF] Figuerola | Dispersal of aquatic organisms by waterbirds: A review of past research and priorities for future studies[END_REF]. But, short distance dispersal of these species is very difficult to assess.

Species shifted their mean gradient positions between soil seed bank and standing vegetation. The two species with a significant shift, R. paludosus and L. hyssopifolia, have high moisture requirements and occupied a moister niche as plants in the vegetation than as seeds in the soil seed bank. Evidence for a larger spread in the soil seed bank for individual species is stronger, three of four species for which there was a significant difference in spread above and below ground had larger spread in the soil seed bank and all of these had intermediate positions. These results suggest that maintaining a high spread of the seed bank in local gradients for annual plants is a mechanism to enhance local population persistence at intermediate gradient positions.

Plant species growing in dry parts showed consistently higher seed size than species from intermediate or moist plots. This finding supports the adaptive value of large seeds in dry environments [START_REF] Baker | Seed weight in relation to environmental conditions in California[END_REF][START_REF] Daws | Germination responses to water potential in neotropical pioneers suggest large-seeded species take more risks[END_REF][START_REF] Leishman | The role of seed size in seedling establishment in dry soil conditions -Experimental evidence from semi-arid species[END_REF]. Interestingly, plants with large seeds have smaller interannual variability in survival [START_REF] Metz | Plant survival in relation to seed size along environmental gradients: A long-term study from semi-arid and Mediterranean annual plant communities[END_REF][START_REF] Pake | Seed banks in desert annuals: Implications for persistence and coexistence in variable environments[END_REF]). Here we suggest that risk reduction traits are related to the niche position of a species in smallscale moisture gradients. Plants in dry parts, seem to rely more on conservative bet hedging via larger seed size. In our data, species with seeds lighter than 1 mg only occurred on plots waterlogged during the observation year (Fig. 4). Probably, many large seeds without impermeable teguments would also die in prolonged periods of flooding, and thus contribute to the size-hydrology relation.

We found no evidence for a trade-off between dispersal and seed bank with the indices and at the scale we studied. Including seed size and gradient position, both potential confounding factors with significant effect on dispersal and seed bank abundance, did not change this picture. However, our data support the idea that abundance of seeds in the soil is linked to seed size via the seed size-number trade-off, including a higher detectability of light and more numerous seeds [START_REF] Saatkamp | The functional role of soil seed banks in natural communities[END_REF][START_REF] Thompson | Seed size and shape predict persistence in soil[END_REF].

Rather than being in a trade-off, seed size and seed bank were both positively correlated to moisture. This suggests that seed banks or heavy seeds are not alternative bet hedging strategies at a given moisture condition [START_REF] Pake | Seed banks in desert annuals: Implications for persistence and coexistence in variable environments[END_REF][START_REF] Venable | The selective interaction of dispersal, dormancy and seed size as adaptations for reducing risks in variable environments[END_REF] but that the main differences in these traits are triggered by differences in a plant's moisture niche. Moreover, our findings do not sustain the idea of a trade-off between dispersal and seed bank that has been suggested by theoretical works (e.g. [START_REF] Venable | Delayed germination and dispersal in desert annuals: Escape in space and time[END_REF]. Since both dispersal [START_REF] Bruun | Why are small seeds dispersed through animal guts: Large numbers or seed size per se?[END_REF] and seed banks [START_REF] Saatkamp | The seed bank longevity index revisited: Limited reliability evident from a burial experiment and database analyses[END_REF]) depend on high seed production, seed production increases the probability of a seed to reach dis-tant places or times. Dispersal and seed banks are therefore positively related instead of being in a trade-off. Moreover, a higher productivity is known for light-seeded plants due to the seed number-mass trade-off [START_REF] Jakobsson | A comparative study of seed number, seed size: seedling size and recruitment in grassland plants[END_REF][START_REF] Moles | Small-seeded species produce more seeds per square metre of canopy per year, but not per individual per lifetime[END_REF], so one way to increase seed number adaptively is via decreasing seed size [START_REF] Shipley | The Allometry of Seed Production in Herbaceous Angiosperms[END_REF]. Possibly, stronger spatial and temporal variability in moisture both select for increased seed number, lowering seed size at the moist gradient end.

Probably, our results on risk-reduction may also be found in other rainfall-related local moisture gradients since even outside the context of temporary pools, small-scale moisture gradients move from one year to another. The different niche positions and adaptations of plants to drought and water-logged soils are, therefore, just one explanation for differences in the temporal variance between species within communities [START_REF] Angert | Functional tradeoffs determine species coexistence via the storage effect[END_REF][START_REF] Venable | Bet hedging in a guild of desert annuals[END_REF].

Our data sustain the view of [START_REF] Childs | Evolutionary bet-hedging in the real world: Empirical evidence and challenges revealed by plants[END_REF] that diversifying bet hedging should be favored in situations when escape in space or time is possible, which is the case for persistent soil seed banks of aquatic species in our data.

Fig 1 .

 1 Fig 1.Abundance of a species seeds in the soil on its mean simulated water level. (A) Observed (dots, stars for zeros) and fitted counts according to a zero-inflated negative binomial model using seed size as covariate (abundance, straight line, p = 0.0060, z = 2.74; seed size p < 0.0001, z = -4.124). (B) Probability of false zero according to zero-inflated model (seed size, p = 0.0487, z = 1.972). See text for details.

Fig. 2 .

 2 Fig. 2. Distributions of seeds in the seed bank (grey) and adult plants (white) growing along transects ranging from the bottom of temporary pools to permanently dry places in the vicinity. Species are sorted by growing conditions of adult plants, with wet conditions at the top. Negative values of simulated maximum water levels indicate dry conditions.

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Acknowledgments

We are grateful to Dominique Guicheteau (Réserve Naturelle Plaine des Maures) and SOMECA for access to study site and DREAL PACA and CNPN for permits. We thank Patrick Grillas and Alexandre Millon for helpful discussions and Daniel Pavon and Manon Batista for fieldwork and Frauke Behrendt (University of Brighton) for English language revision. SG benefits from IKEA grant to IMBE 13/8/2009 and AS from Région Provence Alpes Côte d'Azur grant "Gévoclé".


Michela Marignani

Daniele Bruschi

Davide Astiaso

Raffaella Frondoni

Emanuela Carli

Maria Silvia Pinna

Fabrizio Cumo

Franco Gugliermetti

Arne Saatkamp

Aggeliki Doxa

Identification and prioritization of areas with high environmental risk in Mediterranean coastal areas: A flexible approach

Keywords:

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

Introduction

The Mediterranean Basin constitutes one of 200 ecological regions with the highest level of biodiversity in the world [START_REF] Olson | The Global 200: a representation approach to conserving the Earth's most biologically valuable ecoregions[END_REF]. Although covering only 0.8% of the world's sea sur face and 0.3% of its seawater volume, the Mediterranean Sea is home to 10,000 to 17,000 marine species, 20% of which are endemic [START_REF] Bazairi | The Mediterranean Sea Biodiversity: State of the Ecosystems, Pressures, Impacts and Future Priorities[END_REF][START_REF] Coll | The biodiversity of the Mediterranean Sea: estimates, patterns, and threats[END_REF]. The terrestrial plant diversity of the Basin is similarly rich, with about 25,000 species native to the region (60% of them are Mediterranean endemics, half of which corresponds to narrow endemics; [START_REF] Thompson | Plant Evolution in the Mediterranean[END_REF], and around 10% of the world's higher plants concentrated in an area covering b 2% of the land mass [START_REF] Medail | Biodiversity hotspots in the Mediterranean Basin: setting global conservation priorities[END_REF]. Therefore, the Mediterranean Basin is also recognized as one of 34 Global Biodiversity Hotspots [START_REF] Mittermeier | Hotspots Revisited. 392[END_REF][START_REF] Myers | Biodiversity hotspots for conservation priorities[END_REF].

According to the IUCN (IUCN, 2016), the major causes of threat to Mediterranean species include, by order of importance, habitat loss and degradation, pollution and over exploitation of natural resources [START_REF] Cuttelod | The Mediterranean: A Biodiversity Hotspot Under Threat. In the 2008 Review of The IUCN Red List of Threatened Species[END_REF]. Moreover, urbanization, tourism and industrial development are the main drivers of land cover change [START_REF] Benoit | A Sustainable Future for the Mediterranean: The Blue Plan's Environment and Development Outlook[END_REF]European Environment Agency, 2013). It is estimated that the number of people living permanently in the Mediterranean coastal regions will increase by 1.4% per annum along the Southern and Eastern shorelines, reaching 108 million by 2025; while the North ern shorelines are expected to stabilize at about 68 million [START_REF] Coudert | IMAGINE: un ensemble de méthodes et d'outils pour contribuer à la gestion intégrée des zones côtières en Méditerranée[END_REF]. These increases are predicted to cause the loss of 200 km per year of coastline to urban areas between the present and 2025. The Mediterranean Basin is also one of the world's busiest areas for mar itime traffic with 200,000 commercial ships crossing annually the sea and approximately 30% of international sea borne volume originating from its ports or directed towards them (Abdulla and Linden, 2008). Tourism and freight transport, offshore platforms and waste discharges from boats or affluent rivers are an additional important pollution source for the semi enclosed sea [START_REF] Lejeusne | Climate change effects on a miniature ocean: the highly diverse, highly impacted Mediterranean Sea[END_REF][START_REF] Cózar | Plastic accumulation in the Mediterranean Sea[END_REF]. The request for an easy and efficient application of ICZM to the Mediterranean Basin remains very relevant [START_REF] Buono | The difficult road to Integrated Coastal Zone Management implementation in Italy: evidences from the Italian North Adriatic regions[END_REF][START_REF] Prem | Implementation obstacles of the ICZM protocol and mitigation efforts[END_REF]. This is especially true when considering also that the overall re sponse capability of many Mediterranean countries (Italy, Greece, Malta, Spain) to deal with Hazardous and Noxious Substances (HNS) in cidents was still rather limited few years ago (EMSA, 2013).

Historically, engineers were the main party in charge of the manage ment of coasts, because management was essentially focused on coastal projects that consisted of infrastructure design and construction to en hance the exploitation, or the physical protection of the coastal area [START_REF] Kamphuis | Coastal project management[END_REF]. As such, several instruments for the assessment of vulnerability and hazard have been developed, especially in the engi neering literature [START_REF] Appelquist | Application of a new methodology for coastal multihazard-assessment & management on the state of Karnataka, India[END_REF][START_REF] Komendantova | Multi-hazard and multi-risk decision-support tools as a part of participatory risk governance: feedback from civil protection stakeholders[END_REF] with limited studies focusing on the assessment of the concept of risk and hazard considering the ecological implications (see for a re view De [START_REF] De Lange | Ecological vulnerability in risk assessmenta review and perspectives[END_REF]. More recently, the definitions of coastal management and engineering have been extended with interdisciplin arity and transdisciplinarity evolving to become the cornerstone for the future management of coastal ecosystems [START_REF] Kamphuis | Coastal project management[END_REF][START_REF] Stock | Defining terms for integrated (multi-inter-trans-disciplinary) sustainability research[END_REF]. In fact, decision makers have started to feel that "simple solutions to complex problems" is not the key towards the suc cessful management of a territory [START_REF] Jackson | Creative holism: a critical systems approach to complex problem situations[END_REF][START_REF] Reyers | Conservation planning as a transdisciplinary process[END_REF]. As a consequence, both the scientific communities and funding agencies are refocusing their efforts towards integrating the research outcomes from multidisciplinary research, trying to break down barriers that often prevent our shared understandings of complex issues [START_REF] Jackson | Creative holism: a critical systems approach to complex problem situations[END_REF][START_REF] Stock | Defining terms for integrated (multi-inter-trans-disciplinary) sustainability research[END_REF]. Similarly, the concept of prioritization of sites has been widely examined for biodiversity conservation (e.g. [START_REF] Pressey | Beyond opportunism: key principles for systematic reserve selection[END_REF][START_REF] Wilson | Prioritizing global conservation efforts[END_REF], for public health implications in case of pollution [START_REF] Harold | Development of a riskbased prioritisation methodology to inform public health emergency planning and preparedness in case of accidental spill at sea of hazardous and noxious substances (HNS)[END_REF] but only recently as an instru ment for the routine management of the territory (e.g. for harbors in [START_REF] Valdor | Prioritization maps: the integration of environmental risks to manage water quality in harbor areas[END_REF].

Within this context, the GREAT Med project (Generating a Risk and Ecological Analysis Toolkit for the Mediterranean), funded by the ENPI CBC Med program of the European Union, aims to contribute to the de velopment of an interdisciplinary strategy for assessing plant diversity and the main human pressures in critical areas of the Mediterranean coasts, with a view towards conservation and monitoring of natural her itage. The specific objectives of the project include the development of an accessible and understandable procedure for assessing coastal plant diversity and its vulnerability to potential stressors (such as oil spills, fragmentation of natural habitats), and the definition of an easy to use approach to locate and prioritize the more susceptible areas. This would provide a practical instrument for risk management in the ordi nary and extra ordinary management of the coastline. The project in volves several pilot areas in four Mediterranean countries from different sides of the Mediterranean Basin (Italy, France, Lebanon and Tunisia), an engagement deemed crucial for setting up effective and standardized descriptors, criteria and indicators that take into account different ecological and socio economic contexts. The objective of our planning was to create a methodological framework that can be used and adapted to diverse situations, i.e. different knowledge of the biodi versity of the local area, different types of threats/pressure, different socio economic situation, different objectives of prioritization (for in stance for biodiversity conservation, tourism development, oil spill emergencies).

We present a flexible and adaptable methodological approach to i) assess environmental risk in coastal areas and, accordingly, ii) prioritize the areas more prone to suffer from one (or more) selected risks.

Material and methods

Pilot areas

The project implemented its activities in four pilot areas in the Med iterranean basin, which are characterized by high levels of biodiversity and economic development. Each pilot area comprises at least 60 km of coastline that is meant to cover the broad scale extension of the as sessment in which 11 sites were selected to address the local scale (small extension, Fig. 1). The selection process encompassed the main types of land use/cover, environmental characteristics, and main types of human pressures present in the whole Mediterranean basin. In par ticular, we focused on the presence of oil refineries, commercial port, Hazardous and Noxious Substances (HNS), and urban pressure.

Pilot Area 1 The Provence Alpes Côte d'Azur (PACA) region is at the southeastern coast of France. This region includes two National Parks, Calanques and Port Cros with terrestrial and marine protected areas and is limited to the west by the Camargue Regional Park. Tourism activities play a central role in the regional economy, with the PACA Re gion being the second most important touristic region in France. The area is home to four oil refineries and the port of Marseille, which is the largest in France and the fifth in Europe. In this pilot area, four study sites were selected along the coastal of the PACA region, which include several Habitat Directive sites (92/43/EEC).

Pilot Area 2 The Gulf of Cagliari in southern Sardinia includes hab itats of priority and community interest under the Habitats Directive (92/43/EEC) and two sites under the Ramsar Convention (UN Treaty Se ries No. 14583). The outstanding environmental and touristic value of the Gulf exists a short distance away from the city of Cagliari (N 150,000 people) and its major port, as well as with one of the largest re fineries in Europe (Sarroch). Along the Gulf of Cagliari two study sites were selected: Capo Sant'Elia Poetto Molentargius and the coastline stretching between the towns of Chia and Pula.

Pilot Area 3 The Gulf of Gabés in southern Tunisia is one of the coastal areas where tourism, increased urbanization and chemical in dustry (phosphate) carry the heaviest impact. The Gulf holds two major ports and is characterized by important salt marshes. Three study sites with different levels of human impact and development were selected: the island of Djerba and the surroundings of both Sfax and Gabés cities.

Pilot Area 4 In Lebanon, the high demand for coastal lands coupled with poor enforcement of legislation led to uncontrolled urban develop ment along the coastline. The coast is also littered with illegal occupa tion (recreational projects, breakwaters and marinas) that prevents public access to the seafront. These changes are major causes of coastal hydrodynamic modifications, degradation, soil erosion and biodiversity loss. Byblos and Beirut coastal regions were selected as the two study sites in Lebanon. The first zone is eligible to be part of the upcoming net work of Marine Reserves in Lebanon, and the second one is character ized by being highly urbanized.

Vulnerability, hazard, risk and prioritization: four linked concepts

Vulnerability is defined as "the degree to which a system is suscep tible to, and unable to cope with, injury, damage or harm" [START_REF] De Lange | Ecological vulnerability in risk assessmenta review and perspectives[END_REF]. It is a function of exposure, effect (potential impact, sensi tivity) and recovery (resilience or adaptive capacity). Several elements are normally considered in its assessment including: ecological or eco system, socio ecological and the use of expert judgment [START_REF] De Lange | Ecological vulnerability in risk assessmenta review and perspectives[END_REF]. [START_REF] Wamsley | Guidance for developing coastal vulnerability metrics[END_REF] adopts the definition proposed by [START_REF] Füssel | Vulnerability: a generally applicable conceptual framework for climate change research[END_REF], where vulnerability is defined according to the system being assessed, the attribute of concern, and the hazard (or the "threat", "stressors" or anything recognized as "a threatening event, or the prob ability of occurrence of a potentially damaging phenomenon within a given time period and area").

In the environmental studies, to assess the risk, defined as the prob ability of a harmful effect due to a given hazard and resulting conse quences [START_REF] De Lange | Ecological vulnerability in risk assessmenta review and perspectives[END_REF], considerations are given to ecological characteristics of the biological system potentially exposed. The results of an environmental risk assessment can be used to prioritize the coastal area according to the chances that one of multiple risks can happen. In fact, hazard and vulnerability are closely linked to the topic of schedul ing of management as well as conservation action and the consecutive selection and prioritization of sites. When prioritizing, a temporal di mension is added to the ordinary management of the territory: it means to fix a time for and plan in advance where the interventions will go first in case of an emergency and where to direct our attention later. In the same way, we can prioritize to schedule the possible actions on a territory in order to propose where conservation action will pro duce the best long term protection and conservation outcomes, consid ering that species, habitats and ecosystems can be compromised at rates that vary depending on the habitat type, location and management [START_REF] Kukkala | Core concepts of spatial prioritisation in systematic conservation planning[END_REF].

In this study, we used plant diversity (including plant species and plant assemblages, hereafter referred to as habitats) as an indicator for ecosystem vulnerability: we assumed that the greater the plant diversi ty, the greater the vulnerability of the location [START_REF] De Lange | Ecological vulnerability in risk assessmenta review and perspectives[END_REF]. This is because coastal areas that are naturally heterogeneous are likely to be relatively rare along the highly urbanized Mediterranean coasts and representative of environmental conditions that are under threat [START_REF] Bazairi | The Mediterranean Sea Biodiversity: State of the Ecosystems, Pressures, Impacts and Future Priorities[END_REF]European Environment Agency, 2013). Moreover, in this context, the potential loss of plant species or habitats of concern is of high significance since largely irreplaceable (very low recovery and/or resilience, De [START_REF] De Lange | Ecological vulnerability in risk assessmenta review and perspectives[END_REF].

The variety and availability of biological data is a common limit for many studies that conduct biodiversity assessments [START_REF] Marignani | Is time on our side? Strengthening the link between field efforts and conservation needs[END_REF]; during the vulnerability assessment, the greatest impediment for a consistent evaluation is the lack of biological data [START_REF] De Lange | Ecological vulnerability in risk assessmenta review and perspectives[END_REF]. Diverse situations are encountered in the four countries encompassing the pilot areas. While in Italy, Lebanon and Tunisia pri mary data collected during the project implementation were used, in France existing databases were relied upon. To face the problem of the availability and the use of heterogeneous biological data we tested a two scale approach in terms of spatial extension and data types.

At the pilot area level (broad extension: PACA region, France; Gulf of Cagliari, Italy; coastal areas between Byblos and Beirut, Lebanon; Gulf of Gabès, Tunisia, see Fig. 1) we considered habitat data, which are gener ally more easily available; at the site level (small extension, see Fig. 1) we used both species and habitat data (for more details on the plant di versity assessment see the Supplementary material).

We adopted a multi scale approach for two main reasons: data con straints and theoretical issues. Undeniably finer resolution data and richer set of variables permit the conduction of more precise risk as sessments and more accurate management planning [START_REF] Norton | The importance of scale in the development of ecosystem service indicators?[END_REF][START_REF] De Lange | Ecological vulnerability in risk assessmenta review and perspectives[END_REF]. Nevertheless, as stated by [START_REF] Levin | The problem of pattern and scale in ecology: the Robert H. MacArthur Award Lecture[END_REF], modeling at finer scales demands more detailed data in order to predict outcomes effectively, while at larger scales statistical patterns become more regular and the use of coarser proxies more rational. Bio diversity knowledge is scale dependent and when moving from coarser to finer spatial resolution, our knowledge shortfalls expand [START_REF] Hortal | Seven shortfalls that beset large-scale knowledge of biodiversity[END_REF].

For the hazard assessment we selected three main threat/pressure indicators: i) habitat loss and fragmentation due to urbanization ii) ex posure to Hazardous and Noxious Substances (HNS) and iii) exposure to oil spills (see Fig. 2). For the assessment of oil spills risk, we also used the morphology of shoreline to evaluate the sensitivity to pollution (for more details see Al Shami et al., 2017 and Supplementary material).

All spatial analyses were performed at pilot area (habitat only, broad extension) and at site level (habitat and species, small extension), using the GIS software Qgis and ArcGIS® 10.X ESRI.

Assessing vulnerability: plant diversity and coastal morphology

To quantify vulnerability, we used two synthetic spatial indices. The biological one refers to plant species and habitat types and is based on a common set of simple indicators: species richness, presence of species of conservation concern, diversity of natural habitats and cover of hab itat of conservation value. Species of conservation concern refer to spe cies of national or regional interest according to global, national and regional Red Lists (IUCN), international Conventions and Directives (Habitats Directive, Bern Convention, CITES), or judgment of local plant experts (for instance, for narrow endemics or species with re duced population size). For habitats we referred to international and na tional policies when available (e.g. Habitats Directive for Europe, 92/43/ EEC), or to local expert judgment (for more information on the concept of concern for species and habitats, see [START_REF] Blasi | Important plant areas in Italy: from data to mapping[END_REF][START_REF] Rossi | Are Red Lists really useful for plant conservation? The new Red List of the Italian Flora in the perspective of National Conservation policies[END_REF]. Note that all plant and habitat indicators refer to a standard spa tial grid of 1 × 1 km (100 ha). We adopted this size considering data availability in the pilot areas, time and money constraints; compared to other widely adopted spatial grids, e.g. 4 km 2 for the IUCN red listing assessment (IUCN, 2016), a 1 km 2 grain for biological data appeared as a good compromise, suggested also by the standard adopted in Europe for e.g. Habitats Directive (INSPIRE, Infrastructure for Spatial Information in Europe).

Besides existing data sources, for Italy, Lebanon and Tunisia data on plant species were collected through field surveys, with a sampling strategy designed to ensure at least one sample plot per habitat type within each grid cell. In France, plant species data were derived from the SILENE (System of Information and Localisation of native and inva sive species) georeferenced database compiled by the National Mediter ranean Botanical Conservatory (CBNMed). It contains ~4.5 million records on plant species occurrences in the French Mediterranean re gion (approx. 300 km coastline), which derived from different sources (herbaria specimen, field data, etc.…).

Habitat data were derived from land cover maps at the regional or local scale available for each country, except for Tunisia, where original data were produced. For habitats of conservation value, France and Italy used also the habitat maps, available from the Natura 2000 network (Habitats Directive, Council Directive 92/43/EEC).

The complete use of indicators (habitat plus floristic data) covered the study sites because existing georeferenced data on plant occur rences are discontinuous over the whole pilot areas with resource con straints preventing the extension of field surveys over long coastal stretches. This restriction does not affect the flexibility of the approach and allows future data addition and refinements.

For each cell, the scores of each descriptor are ranked in three clas ses, from one (lowest value) to three (highest value). The classified values of all indicators are then summed up to obtain an overall score, which we called Biodiversity Vulnerability Index (BVI), with values ranging from four (when all individual values are one), to a maximum value of 12 (when all indicator values are three, see Supplementary ma terial). We used a classification that permits us to distinguish among low, medium and high risk and vulnerability levels, which is a common approach in risk assessments (see for instance [START_REF] Halpern | A global map of human impact on marine ecosystems[END_REF][START_REF] Arkema | Coastal habitats shield people and property from sealevel rise and storms[END_REF]. Also [START_REF] Gauthier | Regional priority setting for rare species based on a method combining three criteria[END_REF] recommended to use an impair number (3 or 5 classes) for the classification of species accord ing to the conservation priority. We chose an additive score method be cause it is relatively easy to create and teach, despite its cons [START_REF] Hubbard | Problems with scoring methods and ordinal scales in risk assessment[END_REF].

The morphological index, or the Environmental Sensitivity Index (ESI), quantifies the sensitivity of the coastline to oil pollution. Shore lines are first classified in typologies according to a modified version of the NOAA coastline classification system (NOAA, 2002); classes are then ranked on the basis of their susceptibility to damage by oil spills, with lower rankings indicating lower vulnerability (0 lowest vulnerabil ity, 10 highest vulnerability). Shoreline classification criteria refer to a set of factors including relative exposure to wave and tidal energy, shoreline slope and substrate type (Al [START_REF] Shami | Risk assessment of oil spills along the Mediterranean coast: a sensitivity analysis of the choice of hazard quantification[END_REF] and Supple mentary material).

Hazard analysis: urbanization and pollution

The aim of the hazard analysis is to quantify potential and actual im pacts that can threaten the terrestrial plant diversity and the shoreline. In this context, fragmentation and habitat loss due to urbanization as well as oil and HNS pollution are recognized as main threats to coastal biodiversity in the Mediterranean [START_REF] Cuttelod | The Mediterranean: A Biodiversity Hotspot Under Threat. In the 2008 Review of The IUCN Red List of Threatened Species[END_REF][START_REF] Frondoni | A landscape analysis of land cover change in the municipality of Rome (Italy): spatio-temporal characteristics and ecological implications of land cover transitions from 1954 to 2001[END_REF]Astiaso et al., 2013a;[START_REF] Lhotte | Are there contrasted impacts of urbanization and land uses on population persistence? The case of Teucrium pseudochamaepitys, an endangered species in Southern France[END_REF][START_REF] Malavasi | The impact of human pressure on landscape patterns and plant species richness in Mediterranean coastal dunes[END_REF] and as such were used to quantify the hazard through the devel opment of synthetic spatial hazard indices. To ensure harmonization of indicators across the four pilot areas, fragmentation was calculated based on the Global Land Cover for the year 2010 (National Geomatics Center of China, 2014). It was measured by a set of five landscape met rics that provide information on different aspects: the relative urban cover, the roads length, the mean and maximum patch size of natural and semi natural habitats and their total length of borders [START_REF] Mcgarigal | FRAGSTATS: Spatial Pattern Analysis Program for Categorical Maps[END_REF]. All landscape metrics refer to a standard spatial grid of 1 × 1 km, calculated using a 3 × 3 km moving window, to better reflect the isolation effect (e.g. in the case of a cell where land cover is mainly natural, but it is surrounded by cells where urban areas dominate). In the context of the quantification of urban pressure, we also used a floris tic indicator "richness in exotic species", since they represent a major threat to biodiversity worldwide and their occurrence is considered a good indicator for human pressures [START_REF] Mack | Biotic invasions: causes, epidemiology, global consequences, and control[END_REF][START_REF] Hejda | Impact of invasive plants on the species richness, diversity and composition of invaded communities[END_REF]. Due to differences in ecological requirements, habitat prefer ences and invasion dynamics between ancient and recent introductions, we opted to consider only neophytes [START_REF] Pyšek | Alien plants in checklist and floras: towards better communication between taxonomists and ecologists[END_REF][START_REF] Pyšek | Alien plants in temperate weed communities: prehistoric and recent invaders occupy different habitats[END_REF][START_REF] Celesti-Grapow | Inventory of the non-native flora of Italy[END_REF][START_REF] Seebens | No saturation in the accumulation of alien species worldwide[END_REF]. In fact, the response of archaeophytes to environmental factors is often similar to that of na tive species [START_REF] Celesti-Grapow | Nonnative flora of Italy: distribution and threats[END_REF]. Data on the occurrence of ex otic plant species in each cell derived from field surveys and the literature.

The individual values of each indicator were ranked into three clas ses scored from one to three, with three representing the highest haz ard. All individual values were reclassified and then summed up to calculate an overall score, which represents the Habitat Fragmentation Index (HFI) ranging from 6 (low impact) to 18 (high impact)1 (see Sup plementary material for details).

As for the impacts of pollution on terrestrial plant diversity, we con sidered the effects of anthropogenic pollution sources, hazardous and noxious substances (HNS) and hydrocarbons [START_REF] Shami | Risk assessment of oil spills along the Mediterranean coast: a sensitivity analysis of the choice of hazard quantification[END_REF]. In dices were calculated only for grid cells that are located along the coast line (Astiaso Garcia et al., 2013c). All other cells were assigned a value of zero. Shoreline hazards associated with non oil pollution threats were assessed for all four study areas (Al [START_REF] Shami | Risk assessment of oil spills along the Mediterranean coast: a sensitivity analysis of the choice of hazard quantification[END_REF]; these hazards in cluded both land and marine based pollution sources (e.g. industries, agricultural activities, ports and marinas). We also collected data on oil volumes and types stored at airports, ports, industries, storage sites, oil rigs, maritime traffic, as well as potential exposure of shorelines to a hypothetical worst case oil spill. The latter was assessed through a set of oil spill simulations along the pilot areas' coastlines using the MedSLIK II model (see Al [START_REF] Shami | Risk assessment of oil spills along the Mediterranean coast: a sensitivity analysis of the choice of hazard quantification[END_REF]. The simulated oil spill accounted for variations in sea temperature, current velocity and direc tion, wind speed and direction along the Mediterranean coastline [START_REF] El-Fadel | A modeling approach toward oil spill management along the Eastern Mediterranean[END_REF]Astiaso et al., 2013b). Oil spill simulation results were used to generate a Shoreline Exposure Index (SEI) that defined both the areas that might be hit most frequently as well as the areas that are exposed to the highest concentrations. HNSI and Shoreline Ex posure Index (SEI) range from 0 to 10. 2For more information on vulnerability and hazard assessment please refer to the Supplementary material.

Prioritization of the coastline for specific risks

The vulnerability assessment outcomes were combined with the hazard analyses for the creation of three integrated evaluations that allow to prioritize the coastline for specific risks. To combine vulnerabil ity and hazard indexes without downweighting or upweighting any index, all original indices (BVI, HFI, HNS, SEI and ESI) were rescaled to a common 1 to 5 scale. This procedure can be changed in case the oper ator wishes to give more importance to one of the variables: for exam ple, to assign more importance to the stressor "urban fragmentation" HFI can be used with its original ranges (6 18) without rescaling, this giving to this factor more weight on the final prioritization score. Prior itizations were performed according to the two different BVI evaluation and spatial extension: using habitats only (area level, broad extension) and habitat and species (site level, small extension).

Prioritization for the risk of fragmentation of natural ecosystems.

The HFRI was developed combining the Biodiversity Vulnerability Index (BVI) and the Hazard Fragmentation Index (HFI). Both indices are cell based, hence we simply calculated the final prioritization rank ing for the fragmentation of natural ecosystems combining the indices according to the risk matrix (see Table 1.a and Fig. 2).

HFRI BVI Â HFI

where HFRI is the Habitat Fragmentation Risk Index, BVI is the Biodiver sity Vulnerability Index and HFI is the Habitat Fragmentation Index at cell level. Note that the Spearman rank correlation was used to quantify the coherence of the results obtained at site vs pilot area level.

2.2.3.2. Prioritization for the risk of anthropogenic, hazardous and noxious substances (HNS). The HNS/Anthropogenic Risk Index (HNSRI) was de veloped combining the Biodiversity Vulnerability Index (BVI) and the HNS/Anthropogenic Hazard Index (HNSI). Using a geo processing in strument, we extracted the overlapping areas of BVI cells and HNSI polygons. HNSRI was calculated by combining the indices according to the risk matrix (see Fig. 2). HNSRI BVI Â HNSI 2.2.3.3. Prioritization for the risk of an oil spill event. The Shoreline Expo sure Index to Oil (SEI) was integrated with the Biodiversity Vulnerabil ity Index (BVI) and with the Environmental Sensitivity Index (ESI) to develop an overall Oil Spill Risk Index (OSRI), according to the following formula: OSRI = (BVI × ESI) × SEI.

Overlaying the three data layers, we extracted the overlapping areas and calculated the final OSRI prioritization value (see Table 1.b).

Results

We produced the prioritization of the coastline for the three hazards analyzed, at site and area level, for the four countries (Fig. 3). 3 At the pilot area level we analyzed in Italy about 90 km of coastline, in France N150 km, about 80 km in Lebanon and N254 km in Tunisia; at the site level, we sampled and analyzed a total of approximately 82 km of coast line (26 in Italy, 23 in Lebanon, 23 in France and 10 in Tunisia).

Ranking the territory according the risk assessed for each hazard, we obtained different prioritization areas: for example in France the area to be monitored for oil spill hazard does not coincide with the one identi fied as more prone to suffer from future urbanization of the coastline. For the risk prioritization of fragmentation of natural ecosystems, a good correlation was observed among the results obtained at site vs pilot area level (205 cells; Spearman rank correlation, rho 0,74; p b 0.001). The results were perfectly coherent for 72% of the cells: Leb anon cells were all coherent (100% of consensus), we observed some discrepancies in France (63% of consensus) and Italy (62% of consensus) while in Tunisia we observed a strong disagreement among the two ranking (consensus only for 21% of the cells). At the site level, the cells were assessed as more at risk/priority than at the area level for 21% of the cells and at a lower risk at the site level than at the area level for 7%.

The countries exhibited a different distribution of the pilot areas at the different levels of prioritization (see Table 2). For example, with regards to the percentage of cells to be prioritized for plant diversity conservation vs the fragmentation hazard, all countries show values ranging from medium to low, except Lebanon, which was characterized by N 50% of the cells as "high medium" level (in comparison to other countries accounting for b 30%). For HNS, Lebanon and Tunisia showed the highest alert with a significant portion of areas ranked as very high high priority (Tunisia 42%, Lebanon 25%) and b50% included in the low/very low priority ranking. The prioritization for oil spill consid ered only a strict portion of the coastline but it gave, nevertheless, indi cation for the management of the coastline. In France the priority was lower, but we identified a portion of high priority in the area of Martigues (see Fig. 3a). In Tunisia the results described the pilot area as more in need of attention for oil spill risk (41% for high to medium risk, which was considerably higher than the one estimated for the other countries, i.e. 16% for Italy, 3% or less for France and Lebanon).

Discussion

We presented a methodological framework to identify the locations where plant diversity is more likely to be damaged by the most common human activities along Mediterranean coastal areas [START_REF] Cuttelod | The Mediterranean: A Biodiversity Hotspot Under Threat. In the 2008 Review of The IUCN Red List of Threatened Species[END_REF]. For this purpose, several topics were considered. To start with, defining the most appropriate scale is critical because ecological bound aries often do not coincide with the administrative ones, rendering the management of the coastline more difficult. Moreover, sampling biolog ical features is expensive and time consuming [START_REF] Hortal | Seven shortfalls that beset large-scale knowledge of biodiversity[END_REF][START_REF] Marignani | Is time on our side? Strengthening the link between field efforts and conservation needs[END_REF]; hence the extent of the study area can also be delimited by the sampling effort that can be covered. In this study, we adopted a double spatial scale (extent) and different levels of ecological information (habitats only, and habitats and plant species).

The two scale approach (area vs site scale) permitted us to show that the detailed information on species richness indicators was impor tant especially for areas of specific conservation interest that other land scape indicators may not efficiently reflect. However, we acknowledge that the use of such indicators can be considerably time and money consuming for data collection [START_REF] Hortal | Seven shortfalls that beset large-scale knowledge of biodiversity[END_REF]. Our approach shows that in the absence of such detailed indicators the biodiversity vulnerability indicator can still identify reasonably good the vulnerable areas even though the local variability may be disregarded.

For the fragmentation hazard, the results showed a good agreement among site vs pilot area level in most cases, suggesting that in this kind of assessment the greatest part of diversity can be summarized using A) Combining BVI with HFI we obtained the prioritization of the coastline for the fragmentation hazard. For example, cells with the combination "Very High" identify the areas more prone to suffer from future urbanization of the coastline. Combining BVI with HNSI we identify the level of susceptibility of the areas to a future hazard caused by hazardous and noxious substances (HNS). For oil spill prioritization we adopted a slightly different approach. B) Taking into account the morphological factors of the coastline (ESI).

data on habitats. When congruence was not respected, in most cases the prioritization based on more data (habitat and species, site level) com pared to the area based (habitats only) identified a greater number of high medium priority cells. Nevertheless, the Tunisian case suggests that when dealing with a reduced dataset, the correlation among habitats vs habitats and plants is weak and, consequently, the results of the prior itization can lead to a poor instrument for decision making. It is preferable to present prioritization results in the right context, whereby a first survey is suggested first on a larger area (e.g. pilot area level) to determine the most important sites at broad scale and then perform a more detailed in vestigation on biological elements in identified critical areas.

Selecting the location where to intervene first represents one of sever al actions that must be taken to preserve the ecological integrity of the Mediterranean coastline. But to prioritize areas according to their environmental risk, we must first assess and then combine ecological and hazard indicators into a repeatable risk assessment procedure. Our approach highlighted the chance to follow a methodology that can be flexible and weigh the different elements composing the procedure ac cording to local needs. The matrices adopted to prioritize the coastline for specific risks can be modified and different weight can be assigned to a specific hazard or to a specific element of the vulnerability (e.g. the presence of endemic species). Investigating three of the most common hazard threatening Mediterranean coastal areas, we could identify dis tinct areas and act properly for the singular examined hazard. For exam ple in the Gulf of Cagliari (Italy) the areas most jeopardized by an Anthropogenic/HNS hazard are scattered along the whole coastline, with a significant part in the Molentargius Park. Oil spill risk is higher in the Western (Chia) and Eastern part of the Gulf (Villasimius) whereas, for urbanization the higher risk is located in the city of Cagliari, surround ing Capo Sant'Elia and the Poetto beach, an area under pressure for tour ism exploitation all year round. When summarizing the three hazards, the Poetto area seems to be the most at risk for multiple hazards, but in a proper planning of risk management the one action fits all approach is not appropriate. Therefore, to be more effective we should focus on the area surrounding Capo Sant'Elia for a strict limitation of urbanization growth, monitor the area of Molentargius for Anthropogenic/HNS hazard and invest in specific emergency planning for the occasional (but danger ous) chance of oil spill in Villasimius and Chia. In our approach, we decid ed to assess risks singularly, to reinforce the message that prioritization is about resource allocation decisions, hence priority setting requires ex plicit and defensible objectives [START_REF] Brown | Effective conservation requires clear objectives and prioritizing actions, not places or species[END_REF]. In fact, decision sci ence is founded on the concept that to set priorities we must at least define a clear objective and a set of actions, from which a subset will be chosen as priorities [START_REF] Game | Six common mistakes in conservation priority setting[END_REF]. Nevertheless, we acknowledge that a multiple hazard analyses, able to consider the cascading effects in a full multi risk approach (e.g. [START_REF] Gill | Anthropogenic processes, natural hazards, and interactions in a multi-hazard framework[END_REF], could integrate the approach and improve its efficiency.

In the administration of the territory, managers frequently have to deal with multiple priorities and the request for a scientifically sound solution is becoming increasingly pressing [START_REF] Appelquist | Application of a new methodology for coastal multihazard-assessment & management on the state of Karnataka, India[END_REF][START_REF] Valdor | Prioritization maps: the integration of environmental risks to manage water quality in harbor areas[END_REF]: our flexible method can cope with different stressors (hazards) and can be weighted according to local necessities and specific urgencies. The prioritization, based on the risk assessment, will help in the ordinary and extraordinary management of those areas and assist in defining where and how to intervene in case of emergency. For example, in case of an environmental disaster (i.e. oil spill event), managers and local stakeholders will be better informed on the status of the coastline so to minimize the effect of the disaster and maximize the use of available resources. Ultimately, the adoption of this approach in different countries along with the elaboration of an integrated GIS da tabase will provide comprehensive sensitivity, risk, and hazard layers that can be easily updated and integrated in future monitoring manage ment programs in the Mediterranean Basin.

As for any other methodology, the real efficiency (and relative limi tations) of the method will be tested if it will be applied in other sites, keeping the general approach and modifying, e.g. the weights of the sin gular indexes or the stressors assessed, to adapt it to the specific local needs and verify its potentiality of flexibility and adaptability. For exam ple, we could have investigated more deeply the influence of agricultur al activities (fertilizers and/or agrochemicals), but in the involved countries agricultural activities have different forms and different influ ence on biodiversity. In Tunisia for example, the presence of agricultural areas have a great impact on the coastal aquifer and salt habitats consid ered in the study [START_REF] El Ayni | A new approach for the assessment of groundwater quality and its suitability for irrigation: a case study of the Korba coastal aquifer (Tunisia, Africa)[END_REF], in France the majority of agricul tural areas in the gulf of Marseille consists in traditional agricultural landscapes, which have an important role for the conservation of the plant species; in Italy the situation is in between [START_REF] Tieskens | Characterizing European cultural landscapes: accounting for structure, management intensity and value of agricultural and forest landscapes[END_REF]. Moreover, except for Lebanon, we could not gather any informa tion on the quantity and quality of the fertilizers and agrochemicals used in the agricultural areas. Nevertheless, we chose to include agricul tural pollution in the Anthropogenic hazard to maintain the possibility to include this type of stressor in the proposed approach.

We believe that the analyzed case studies represent a good range of the different situation we can find in the Mediterranean basin but, at the same time, we acknowledge that the application of the method in other Mediterranean countries could highlight the limitations and the possi ble future improvements of the method. These improvements could come not only from the application in other geographically distinct sit uations, but more interestingly in the implementation of the method in prioritizing the landscape for other stressors such as invasive alien spe cies or increasing sea level rise.

Conclusions

Coastal management in the Mediterranean is an important issue for the conservation of biodiversity and cultural heritage, and represents a chance for the sustainable use of resources. We proposed an integrated transdisciplinary method that incorporates technical and scientific disci plines combining an engineering approach to the problem of risk indices development (based on maritime traffic, morphological and hydrody namic factors) with an ecological approach that considers the value of plant diversity at species and habitat level in a highly biodiverse, but in creasingly stressed, system such as the Mediterranean basin. Neverthe less, transdisciplinarity does not directly ensure management success, which depends also on the complexity of the problem and the difficulties to find compromises between protection and conservation goals on one hand, and socio economic development on the other.

The proposed approach can help in providing solutions to face com mon threats and pressures across the Mediterranean Basin in a more comprehensive way. Its generality and transferability, provides a com mon sampling strategy for biodiversity assessment, a set of criteria for prioritizing sites based on biodiversity, and protocols and equations to generate maps of environmental vulnerability and evaluate hazards and priorities. As such, the approach has the potential to become a stan dard framework for monitoring and assessment of projects in coastal re gions for the entire Mediterranean Basin.

It can provide public administrations and local communities an easy to use instrument towards ICZM and preventing and managing unfore seen spills of hydrocarbons or other stressor menacing biodiversity, cul tural heritage or other valuable elements to be protected. We believe that building a cross border network where all partners meet to share needs, objectives, expertise and results is crucial to converge towards a single strategy that has the potential to be extended to other coastal Mediterranean areas.

Funding

The GREAT Med project was financed by the European Union (ENPI CBC Mediterranean Sea Basin Programme) through the European

Fig. 1 .

 1 Fig. 1. Location of the pilot areas in the four partner countries. Each pilot area is delimited by the white squared grid and it includes the study sites (white circles, purple grid).

Fig. 2 .

 2 Fig.2. Flowchart of the methodological approach.

Fig. 3 .

 3 Fig. 3. Investigated coastline was ranked according to three hazards, producing maps showing the area more prone to suffer from the selected hazards. a) France b) Italy c) Lebanon d) Tunisia.

Fig. 3

 3 Fig. 3 (continued).

Fig. 3

 3 Fig. 3 (continued).

Fig. 3

 3 Fig. 3 (continued).

Table 1

 1 Matrices adopted to prioritize the coastline for specific risks.

	HFRI or HNSRI

Table 2

 2 Relative ranking of the coastline according to the three different analyzed hazards: habitat fragmentation, HNS/anthropogenic substances and oil spill (data in percentage, pilot area level).

		Very high	High	Medium	Low	Very low
	Habitat fragmentation
	France	0,0	2,1	22,8	47,1	28,0
	Italy	0,0	1,2	17,4	62,5	18,9
	Lebanon	0,7	10,5	43,1	37,3	8,5
	Tunisia	0,1	1,7	25,8	37,7	34,7
	Mean value	0,2	3,8	27,3	46,1	22,5
	HNS/Anthropogenic substances
	France	0,1	6,8	27,4	65,4	0,3
	Italy	1,5	17,1	18,2	40,9	22,2
	Lebanon	5,0	23,5	29,5	30,0	12,1
	Tunisia	1,2	41,5	13,5	37,9	5,8
	Mean value	1,9	22,2	22,2	43,6	10,1
	Oil spill
	France	0,8	2,0	0,9	21,7	74,5
	Italy	0,1	6,7	9,6	33,1	50,4
	Lebanon	0,0	0,0	1,4	41,4	57,3
	Tunisia	0,0	23,1	18,3	36,2	22,4
	Mean value	0,2	8,0	7,5	33,1	51,2

http://www.enpicbcmed.eu/projects/library-of-deliverables and reports

http://www.greatmed.eu/joomla/component/content/article/reports-96

A complete list and downloadable files of the produced maps are available at: http:// www.greatmed.eu/joomla/component/content/article/maps-123

Acknowledgments

We wish to thank Chiara D'Angeli for GIS and technical support; Mauro Fois and Selena Puddu for data and field work assistance; Claudia Cogoni for administrative and logistic assistance; Gianluigi Bacchetta for valuable suggestions during the project; Regione Sardegna Assessorato della difesa dell'Ambiente (Servizio sostenibilità ambientale e Sistemi informativi; Servizio Tutela della natura e politiche forestali) for kindly providing the habitat maps of Natura 2000 sites for the Italian study area; the Conservatoire Botanique National Méditerranéen (Hyères, France) and Virgile Noble for extracting data from the SILENE database and Pierre Jean Dumas for providing coastline data.

Appendix A. Supplementary data

Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.scitotenv.2017.02.221.