The role of hydrodynamic forcing, sediment transport processes and bottom substratum in the shoreward development of Posidonia oceanica meadow

Accepted Manuscript The role of hydrodynamic forcing, sediment transport processes and bottom substratum in the shoreward development of Posidonia oceanica meadow Andrea Ruju, Angelo Ibba, Marco Porta, Carla Buosi, Marinella Passarella, Sandro De Muro PII:

S0272-7714(18)30101-X

DOI:

10.1016/j.ecss.2018.06.025

Reference:

YECSS 5901

To appear in:

Estuarine, Coastal and Shelf Science

Received Date: 7 February 2018 Revised Date:

9 May 2018

Accepted Date: 27 June 2018

Please cite this article as: Ruju, A., Ibba, A., Porta, M., Buosi, C., Passarella, M., De Muro, S., The role of hydrodynamic forcing, sediment transport processes and bottom substratum in the shoreward development of Posidonia oceanica meadow, Estuarine, Coastal and Shelf Science (2018), doi: 10.1016/j.ecss.2018.06.025. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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The role of hydrodynamic forcing, sediment transport processes and bottom substratum in the shoreward development of Posidonia oceanica meadow

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Andrea Ruju, Angelo Ibba, Marco Porta, Carla Buosi, Marinella Passarella, Sandro De Muro

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Department of Chemical and Geological Sciences, Coastal and Marine Geomorphology Group (CMGG), University of Cagliari, Cagliari, Italy

Abstract

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This paper investigates the combined role of hydrodynamic forcing, sediment transport processes and sea bottom features in determining the location of the meadow upper limit of the endemic Mediterranean seagrass Posidonia oceanica. For this purpose, an approach including extreme wave analysis and numerical modelling is applied to two sandy beach systems located in southern Sardinia (Italy). Information about bathymetry, P. oceanica meadow extension and bottom features has been made available by previous published studies. Based on the 30-year long NOAA hindcast dataset, a wave climate analysis is carried out to identify the incoming storm wave conditions (1 year return period) to be simulated with the Delft3D model package. The simulation results extend the current knowledge highlighting the importance of wave-induced hydrodynamic parameters as limiting factors for the survival of P. oceanica meadows. In particular, the results suggest that on sandy substrata the meadow upper limit lies well offshore of the surf zone, in areas with little morphological activity, where the wave orbital velocities associated to storms are on the order of 0.8 m/s and the mean current magnitude does not exceed 0.5 m/s. On rocky bottoms, the P. oceanica meadow can extend up to the outer surf zone of storms and is thus able to colonize shallow areas subject to stronger hydrodynamic forcings than those observed on sand. This difference in the plant tolerance to wave forcing depending on the substratum type shows how both hydrodynamic and geological factors play a key role in defining the environmental conditions for the development of seagrass meadows.

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Preprint submitted to Estuarine, Coastal and Shelf Science

June 28, 2018

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In the Mediterranean Sea, the endemic species Posidonia oceanica can colonize a large portion of the nearshore area forming an important system component able to affect both ecological and geomorphological processes in shallow waters. Light availability represents the limiting factor for the set-up of the meadow lower limit (Duarte, 1991) that has been observed at depths varying between 15-23 m in waters with high turbidity levels and 45-48 m where water transparency is high (Boudouresque et al., 2012). On the other hand, the meadow upper limit usually occurs within the most dynamic zone of the beach system (Boudouresque et al., 2012) at water depths ranging between 0 and 15 m, depending on environmental conditions. The role played by P. oceanica and other types of submerged vegetation in the mitigation of flood and erosion risks in coastal areas is well recognized (Ondiviela et al., 2014; Vacchi et al., 2016). Wave energy is attenuated by friction within the seagrass meadow which can reduce water flows and therefore lead to an increase of sediment deposition and accumulation as well as beach stability (Terrados and Duarte, 2000; Mendez and Losada, 2004; Koch et al., 2006; Chen et al., 2007; Widdows et al., 2008; Christianen et al., 2013). Moreover, seagrasses enhance water transparency and carbon sequestration (Duarte et al., 2005; Short et al., 2007). However these eco- and geomorphological services are under threat due to the global decline of seagrass meadows reported by several publications over the last decades (Orth et al., 2006; Duarte et al., 2008). This loss has been mainly ascribed to stresses related to climate change and to an increase of human pressure on coastal areas (Marba and Duarte, 2010; Philippart et al., 2011; De Muro et al., 2018). For this reason, EU legislation (including the Habitat Directive and the Water Framework Directive) implements protecting measures to promote the thriving of seagrass against natural and anthropogenic threats. Due to the recognized importance of seagrasses, the coastal scientific community has recently devoted a significant effort by publishing a considerable amount of research on the interactions between vegetation meadows and coastal hydrodynamics. These publications are usually based on a multidisciplinary approach and can be divided into two main groups: those that

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1. Introduction

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Keywords: Posidonia oceanica, Wave hydrodynamics, Wave modelling, Rocky subtratum, Sandy bottom, Seagrass meadow

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focus on the effects that the vegetation produces on the flow (Infantes et al., 2012; Manca et al., 2012; Luhar et al., 2010, 2013; Pujol et al., 2013; Maza et al., 2015) and those that deal with the role played by hydrodynamics in the determination of the meadow survival conditions and ultimately its extension (Infantes et al., 2009; Vacchi et al., 2010; Stevens and Lacy, 2012; Vacchi et al., 2014; Montefalcone et al., 2016). This work can be included in the second group as it aims at extending the current knowledge on the forcing conditions that limit the long-term persistence of P. oceanica in the nearshore. The influence of wave energy on the development of the upper limit of P. oceanica meadows in the Mediterranean area has been a relevant focus of recent research. Infantes et al. (2009) used a wave model based on mildslope equations to address the influence that orbital velocities induced by mean wave conditions have on the distribution of P. oceanica at Cala Millor (Balearic Island). Vacchi et al. (2010, 2014) quantitatively assessed the relationship between the breakpoint location expected under storms with return period of 1 year and the meadow upper limit at different sites along the Ligurian coasts (linear wave theory with an empirical breaking criterion was used for the nearshore propagation of offshore waves). Moreover, Montefalcone et al. (2016) reported that, on Ligurian coasts, P. oceanica on rocky substrata tolerates stronger hydrodynamic stresses than those usually tolerated on sandy bottoms. Although these studies provided valuable insights on the importance of hydrodynamics and bottom substratum characteristics to the spatial distribution of P. oceanica, a complete understanding of the interaction between the seagrass meadow and environmental parameters is far from being achieved. With the main aim of extending the current knowledge on this topic, this study implements the coupling of a wave and a circulation model to provide a large dataset of hydrodynamic and morphodynamic parameters expected to occur at the P. oceanica meadow upper limit during storm wave conditions (return period of 1 year). In this work, the wave climate on two beach systems located in southern Sardinia (Italy) is reconstructed by combining deep water hindcast data with nearshore numerical modelling. For these beaches, published field campaigns (De Muro et al., 2016; Buosi et al., 2017) made available information about bathymetry, P. oceanica meadow extension and bottom features. We implement the coupling between the wave and the circulation model of the Delft3D model package to propagate the wave motion from deep to shallow waters and simulate nearshore processes induced by the selected storm wave conditions

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This study focuses on the Solanas and Porto Pino beaches located in southern Sardinia, Italy, western Mediterranean (see figure 1). These beach systems can be classified as microtidal wave-dominated systems (De Muro et al., 2017a). Their main features are briefly outlined in this section, whereas an exhaustive description of sedimentological, geomorphological and hydrodynamic processes can be found in De Muro et al. (2016) and Buosi et al. (2017). Solanas is a South-West oriented embayed beach that extends for 950 m in the eastern sector of the Gulf of Cagliari. It receives a sedimentary input from the Solanas river that seasonally flows into the southern part of the beach. Coarse sediments prevail in the dry beach and dune system whereas the shoreface is mainly characterized by medium-fine sands (De Muro et al., 2016). Close to the shoreline, shoreface sediments are dominated by a siliciclastic component (mainly quartz and feldspars) that leaves space for a transition to mixed components increasingly rich in a bioclastic constituent towards the upper limit of the P. oceanica meadow. Porto Pino (the second beach studied in this paper) is a 5 km long, WestSouth-West facing embayment located in southern Sardinia. The northern sector of the beach is backed by a relatively narrow primary dune system (foredunes and embryo dunes) bordered by a wide system of marshes and lagoons. A complex system of primary and secondary dunes covers the southern part of the area. Analogously to Solanas, the composition of the mediumfine sediments of the shoreface in Porto Pino turns from mainly siliciclastic close to the shoreline to a mixed composition with a significant portion of bioclastic component towards the P. oceanica meadow (Buosi et al., 2017). Figures 1C and 1E show that in both areas, the distribution of P. oceanica meadow is roughly shore-parallel and occupies a sandy substratum between water depths of about 12 and 35 m. However, the meadow extends up to

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with return period of 1 year. Taking advantage of the refined information provided by the numerical simulations, we assess the spatial distribution of wave- and current-induced velocities, bed shear stresses and sediment transport processes with respect to the meadow upper limit location. In addition to the effect of the mentioned simulated hydro- and morphodynamic parameters, this work assesses the influence of the substratum type in determining the environmental conditions for the development of seagrass meadows.

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3. Methods

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3.1. Field data collection De Muro et al. (2016) and Buosi et al. (2017) reported the results of integrated geomorphological, sedimentological and coastal dynamic studies carried out at Solanas and Porto Pino beach systems. This section briefly describes the methods used by these studies to determine backshore/foreshore topography, shoreline location, shoreface bathymetry and benthic habitat distribution. For further details on the data collection procedure, including sample point and transect locations, the reader is referred to De Muro et al. (2016) and Buosi et al. (2017). DGPS (Differential Global Positioning System) surveys were carried out along equally spaced beach transects (line spacing was 60 m in Solanas and 150 m in Porto Pino) to determine the backshore/foreshore topography. The data were collected using a DGPS NavCom in a GNSS (Global navigation satellite system) and/or StarFire (Navcom SF3040) system. The shoreface bathymetry was recorded along a regular grid using a single-beam echosounder coupled with a DGPS receiver. The topographic and bathymetric data were linked to a geodetic network of points specifically created on the two beaches. The benthic habitat distribution was assessed distinguishing between: sandy bottoms, rocky outcrops and underwater vegetation meadows. A combination of aerial photograph interpretation and side scan sonar analysis was adopted to map the extension of the P. oceanica meadow, see the work of Pasqualini et al. (1998) and Tecchiato et al. (2016) who proposed an analogous procedure. Moreover, scuba diving explorations and sediment sampling

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shallow waters close to the headlands enclosing the beach systems where the bottom is mainly characterized by rocky outcrops. Wave conditions along the two beach systems result from a combination of Mediterranean swells and local wind waves with directions mainly ranging from the South-East to the West quadrant. In addition, Porto Pino is also exposed to wave motions generated by North-West wind (which is the dominant wind in this area) since the islands of San Pietro and Sant’Antioco only provide partial shelter. The mean significant wave heights calculated from the NOAA dataset (see section 3.2) for Solanas and Porto Pino are respectively 0.73 and 0.82 m as shown in figures 1D and 1F.

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Figure 1: Area of Study. Panel A: central Mediterranean area, the box indicates southern Sardinia. Panel B: southern Sardinia. Red triangles indicate the NOAA nodes, boxes indicate Solanas and Porto Pino beach systems. Panels C and D: beach systems. Rocky outcrops are in dark grey and P. oceanica meadow is in green. Panels E and F: wave roses of significant wave height Hs .

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3.2. Data analysis Wave climate offshore of the two beaches considered in this work was reconstructed using the hindcast dataset elaborated by NOAA. The NOAA dataset covers 30 years of wave data including simulated wave conditions from January 1979 to December 2009 with a time resolution of 3 hours and spatial resolution of 0.167◦ in the Mediterranean area (Chawla et al., 2012). For our purpose, we identified the mesh nodes that are located at 39◦ N, 9.33◦ E and 38.83◦ N, 8.5◦ E, in close proximity to the Solanas and Porto Pino beach systems (see figure 1), and we considered the extracted wave parameters as the representative offshore incoming conditions. In fact, the selected nodes lie at distances ranging from 15 to 20 km offshore of the coastline in water depths exceeding 100 m, where bottom features do not significantly affect wave propagation. The wave climate analysis includes significant wave height Hs , mean wave direction θ and peak period Tp as relevant wave parameters. At each NOOA node, we identified the 2-day independent storms by using the peak-over-threshold (POT) method (Goda, 2011), retaining only the storms that showed a significant wave height larger than 1.5 m for more than 12 hours. The wave height associated to each storm of the sample was selected as the maximum wave height observed during the storm (Goda, 2011). Moreover, the other relevant wave parameters such as the peak wave period and mean wave direction of each storm were picked as those observed at the time of occurrence of the maximum wave height. Finally, the wave energy flux Ef of each storm was calculated from linear theory, assuming a Rayleigh distribution of wave heights (Longuet-Higgins, 1952), as the product between the wave energy density E and the group celerity cg as:

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integrated the above mentioned methodology. All the results were stored in the UTM WGS84 Datum coordinate system.

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in which

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With the main purpose of classifying wave storms according to the types of forcing, we identified homogeneous wave direction classes at each NOAA node. As a first step towards the identification of these homogeneous wave direction classes, we divided the totality of storms into 32 sectors (each one 360◦ /32 = 11.25◦ wide) and we computed the associated wave energy flux as the linear sum of the energy flux contributions from individual storms. Then, the homogeneous direction classes were defined as those included between the directions associated with the sectors that show a local minimum in the wave energy flux. Following this procedure, we identified 3 homogeneous direction classes both at Solanas and Porto Pino (see figure 2). In order to obtain storm events associated to a particular return period Tr , extreme wave analysis was separately applied to each homogeneous direction class and its sample of wave storms. In this work we chose to consider annual wave conditions and thus we adopted a Tr equal to 1 year; this choice is consistent with previous studies (Boudouresque et al., 2012; Vacchi et al., 2014; Montefalcone et al., 2016) suggesting that P. oceanica meadows are likely to be controlled by storm events instead of mean wave climate. The significant wave height with return period of 1 year was obtained assuming that the selected storms follow a Weibull distribution (Goda, 2011). The estimation of the distribution parameters was carried out by means of the maximum likelihood method. Once the Hs with Tr =1 has been identified, we computed the associated Tp by fitting the combined observations of Hs and Tp by a function with the following form (CERC, 1984): p Tp = c · Hs , (4) in which the coefficient c has been obtained by means of the minimum square error method and the fit line is forced to pass through the origin. Finally, as a representative propagation direction for the storm event with Tr of 1 year, we took the mean energy flux direction θm computed as: ! PN E · sin θ i i=1 f i θm = arctan PN . (5) E · cos θ f i i i=1

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Table 1 includes the offshore incoming wave conditions that force the nearshore hydrodynamics simulated at the 2 beaches. 3.3. Numerical modelling The WAVE and FLOW modules of the Delft3D modelling package were used to simulate nearshore hydro- and morpho-dynamic processes induced 8

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Figure 2: Extreme wave analysis at Solanas (A) and Porto Pino (B) beaches. Gray dots indicate the significant wave height Hs and mean wave direction of the totality of storm events. Black circles are the 1-year return period events for the identified direction classes whose boundaries are highlighted by vertical dashed lines.

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by the wave scenarios identified from the wave climate analysis described in section 3.2. Wave propagation from the selected NOAA nodes to the shoreline and wave-induced currents were simulated using a multi-grid approach including a large-scale and a small-scale fine grid. The WAVE module (Deltares, 2014b) ran on both the large and small scale grids whereas the FLOW module (Deltares, 2014a) ran only on the small-scale grid. In the small-scale grid the FLOW and WAVE modules were online coupled allowing the simulation of wave-current interaction processes. The significant wave height, peak wave period and mean wave direction represented the boundary conditions imposed on the offshore boundary of the large-scale grid. In addition, we considered a directional spread of 20◦ to be representative of swells in the Mediterranean Sea. The large-scale grids with a constant spatial resolution of 60 m and 100 m for, respectively, Solanas and Porto Pino have been rotated with respect to the North direction with the main purpose of minimize the water depth variation along the entire offshore boundary. We chose the location of this coarse grid so that the offshore boundary is located in close proximity to the considered NOAA node. Waves, currents and sediment transport in shallow waters were simulated on a small-scale fine grid nested in this larger grid. The offshore boundary of this grid was located at water depths ranging between 25 and 35 m. The fine grid had a constant spatial resolution of 20 m in the long-shore direction and a varying spatial resolution in the cross-shore direction ranging from 20 m at the offshore boundary to 10 m close to the shoreline.

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Table 1: Offshore wave conditions. Hs : significant wave height; Tp : peak period; θ: mean wave direction.

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3.4. Processing of computed data From the numerical simulations we extracted as outputs those variables that are supposed to play a role in the development of the P. oceanica meadow. These variables are divided into 2 main groups: hydrodynamic and morphodynamic (related to sediment transport processes) variables. The hydrodynamic variables considered in this work are: wave-induced orbital velocity at the bottom ub , mean wave-induced current Uc , bed shear stress τb and fraction of wave breaking Qb . In addition, we considered the effect of morphodynamic variables such as: bed load transport BT , total transport T T , bed reference concentration RC and erosion/sedimentation rate ES. See the manuals Deltares (2014a,b) for the definition of these variables. Since the most severe wave conditions along an entire beach system are not necessarily forced by a unique prevailing offshore storm direction, a treatment of the output data proceeding from different simulations was needed. In fact, nearshore processes can yield to beach sectors that are exposed to different storm direction classes mainly depending on orientation and shelter. This is especially important on sites where headlands play an important role in controlling the inshore wave conditions and on stretches of coastline that do not face into the most energetic wave direction (Garcia-Valiente et al., 2017). It is crucial, then, to avoid overlooking those direction classes that are associated with relatively low wave energy offshore but that can still drive

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The sediment transport processes were simulated by including a layer of non-cohesive sediment with a uniform D50 equal to the mean value measured over the shoreface area of the two beaches (D50 =0.3 mm at Solanas and D50 =0.25 mm at Porto Pino). The sediment layer thickness over the sandy areas was set to a large value to ensure an unrestricted sediment availability throughout the simulation. On the contrary, no sediment was available over areas of rocky outcrops and P. oceanica meadows where the layer thickness was set to zero. The morphologic updates and sediment transport processes were turned off at the beginning of the simulations and according to the model set-up they were allowed to occur only once the hydrodynamic processes had evolved to a stationary state. An heuristic approach was used to estimate the time required by waves and currents to develop and reach stationarity. It was found that waves and mean currents showed minimal temporal variations after 2.5 hours from the start of the simulation at Solanas and Porto Pino. Figure 3 plots the northern part of the fine grid adopted for Solanas beach highlighting the substrata features at the grid nodes.

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Figure 4 shows the spatial evolution of hydrodynamic variables induced by storm wave conditions at the upper limit of the P. oceanica meadows of Solanas and Porto Pino beaches. The horizontal axis represents the distance D calculated over the meadow upper limit and, due to the complex geometries of the meadow limit, it reaches larger values than the linear beach length. On sand, the upper limit sets up in water depths of about 12 m with a slightly difference between the two beaches: the mean water depth is 11.7 ± 1.1 m at Solanas and 12.5 ± 1.6 m at Porto Pino (figures 4a and 4b). On the other hand, the presence of rocky outcrops allows the development of the meadow as far as 4 m depth at Solanas and less than 1 m depth at Porto Pino. It is worth mentioning that where the meadow reaches minimum water depths at Porto Pino (0.5
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severe hydrodynamics on determined beach sectors. To accomplish with this task, we combined all the simulated cases by selecting, for a specific variable at each mesh node of the fine grid, the maximum value from the entire set of direction classes. As a result, for each variable we obtained a single map representing the maximum values of that variable taking into account all the incident direction classes. The maximum values of each variable at the location of the upper limit of the P. oceanica meadow were obtained by linearly interpolating the model output from the model grid to the nodes of the polyline that constitute the shoreward boundary of the P. oceanica polygon. These values were then divided into values on rock and values on sand accordingly to the presence of sandy or rocky substrata at the upper meadow limit.

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limit on sand, see the grey dots in figure 4: mean wave orbital velocity ub is 1.42 ± 0.29 m/s and 1.46 ± 0.28 m/s at Solanas and Porto Pino, respectively. For instance, ub exceeds 1.8 m/s in proximity to the headlands that enclose the Solanas beach systems (where D<0.2 and D>4 km). This fact is in agreement with the observed fraction of wave breaking Qb values larger than 0 suggesting that the presence of rocky outcrops allows the survival of the P. oceanica meadow as shoreward as the outer surf zone of storm wave conditions. The morphodynamic variables at the upper limit of the meadow at Solanas and Porto Pino beaches are plotted in figure 5. Sediment transport processes are weak at the meadow upper limit of both beaches; see also figure 6 that displays the morphodynamic variables within the small-grid domain at Porto Pino. A total sediment transport T T peak of 0.23 dm3 /m/s is found at the rip current location at Solanas beach (see figure 4e). Reference concentration RC follows an analogous pattern to that observed for ub with values on the rocky limit significantly larger than those on the sandy limit (RC is on the order on 0.5 kg/m3 at both beaches). Morphological changes are small at the sandy upper limit where the erosion/sedimentation rates ES can take both positive and negative values but generally smaller than 20 mm/h in absolute terms. The erosion/sedimentation rates ES is almost negligible at the rocky limit due to the local absence of sediment available for transport. Table 2 provides statistics of the hydro- and morpho-dynamic variables of the two beaches, combined together, at the meadow upper limits on sand. The same variable statistics at the meadow upper limits developed on rocky substrata are provided in table 3. In these tables, we considered the absolute value of the erosion/sedimentation rate ES, that is the only variable that can take both positive and negative values. Among these statistics, QCD values can be interpreted as an indicator for the relevance of a particular variable. In other words, the lower QCD along the upper limit, the more relevant a variable is in determining the conditions for the meadow survival. The orbital velocity ub is the variable showing the lowest dispersion both along sandy (quartile coefficient of dispersion QCD equal to 0.08) and rocky (QCD equal to 0.14) upper limits. It is worth notifying that also τb is characterized by relatively low values of QCD (QCD equal to 0.1 on sand) only slightly larger that those of ub . On the other hand, large dispersions characterize the sediment transport parameters; only reference concentration RC shows moderate QCD values that are equal to 0.24 on sandy bottoms.

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Figure 4: Hydrodynamic variables at the upper limit of the P. oceanica meadow. Black dots are the variables at the sand/meadow boundary. Grey dots are the variables at the rock/meadow boundary. Water depth (A and B), wave orbital velocity ub (C and D), mean wave-induced current Uc (E and F), bed shear stress τb (G and H), fraction of wave breaking Qb (I and L) at Solanas (left panels) and Porto Pino (right panels).

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Figure 5: Morphodynamic variables at the upper limit of the P. oceanica meadow. Black dots are the variables at the sand/meadow boundary. Grey dots are the variables at the rock/meadow boundary. Water depth (A and B), bed load transport BT (C and D), total transport T T (E and F), bed reference concentration RC (G and H), erosion/sedimentation rate ES (I and L) at Solanas (left panels) and Porto Pino (right panels).

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Figure 6: Morphodynamic variables within the small-grid domain at Porto Pino beach. The thick green and black lines represent, respectively, the meadow and the rocky substratum limits. BT : bed load transport (A); T T : total transport (B); RC: bed reference concentration (C); ES: erosion/sedimentation rate (D).

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Table 2: Statistics at the meadow upper limit on sand. STD: standard deviation; CV: coefficient of variation; Q1: first quartile; Q3: third quartile; QCD: quartile coefficient of dispersion. ub : wave orbital velocity; Uc : mean wave-induced current; τb : bed shear stress; Qb : fraction of wave breaking; BT : bed load transport; T T : total transport; RC: bed reference concentration; ES: erosion/sedimentation rate.

ub [m/s] Uc [m/s] τb [N/m2 ] Qb [-] BT [dm3 /m/s] TT [dm3 /m/s] RC [kg/m3 ] ES [mm/h]

0.83 0.11 5.94 0 0.01 0.02 0.48 1.71

0.52 0.01 2.46 0 0 0 0.10 0

max On 1.31 0.52 10.07 0.01 0.10 0.23 3.68 46.8

STD sand 0.11 0.08 1.06 0 0.01 0.03 0.23 2.70

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Q3

QCD

0.13 [-] 0.73 [-] 0.18 [-] 18.18 [-] 1.38 [-] 1.45 [-] 0.47 [-] 1.58 [-]

0.77 0.06 5.36 0 0 0.01 0.35 0.32

0.90 0.15 6.58 0 0.01 0.02 0.57 2.06

0.08 [-] 0.40 [-] 0.10 [-] nan [-] 0.73 [-] 0.56 [-] 0.24 [-] 0.73 [-]

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Table 3: Statistics at the meadow upper limit on rock. STD: standard deviation; CV: coefficient of variation; Q1: first quartile; Q3: third quartile; QCD: quartile coefficient of dispersion. ub : wave orbital velocity; Uc : mean wave-induced current; τb : bed shear stress; Qb : fraction of wave breaking; BT : bed load transport; T T : total transport; RC: bed reference concentration; ES: erosion/sedimentation rate.

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mean 1.45 0.58 7.39 0.11 0.01 0.02 7.05 0.85

min

max On 0.48 2.00 0 1.57 0 11.45 0 0.65 0 0.21 0 0.48 0 28.21 0 36.6

STD rock 0.28 0.40 3.19 0.13 0.03 0.06 5.01 3.95

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[-] [-] [-] [-] [-] [-] [-] [-]

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The identification of the main forcing affecting the extension of the seagrass meadow in the nearshore is a challenging task due to the complexity and high non-linearity of the hydrodynamic processes involved (Koch et al., 2006). Moreover, the context is further complicated by the control realized by environmental factors such as geological substrata and sediment characteristics (Gacia and Duarte, 2001; De Falco et al., 2003, 2011; Tecchiato et al., 2016; De Muro et al., 2017c). In this work we used numerical model results to provide a new dataset of hydrodynamic and morphodynamic parameters induced by storm wave conditions at the meadow upper limit of two Mediterranean sandy beaches. In particular, we quantitatively assessed the combined influence of waves, current velocities as well as sediment transport parameters driven by storm wave forcing. This study extends previous work dealing with interaction between P. oceanica meadow and environmental parameters. In this section, we discuss our results in the light of previous work and highlight the main outcomes and limitations of this study. The numerical results presented in section 4 show that, on sandy bottoms, the meadow upper limit sets up where the near-bed wave orbital velocities induced by storms are on the order of 0.8 m/s. This velocity value is significantly larger than the threshold of 0.4 m/s that the numerical experiments of Infantes et al. (2009) reported in Cala Millor, Spain. Infantes et al. (2009) estimated the wave-induced hydrodynamic conditions that set the upper limit of the meadow by numerically propagating the offshore mean wave climate obtained from long-term hindcast data. Based on the observation that in Cala Millor, the decrease of P. oceanica cover is found in those areas with high wave energy, they suggested that the meadow hardly persists above a threshold of the near-bottom orbital velocity equal to ∼ 0.4 m/s. Here, we would like to point out and discuss two main reasons beyond the discrepancy between the Infantes et al. (2009) and our velocity threshold. In the first place, we propagated wave conditions with return period of one year that are more energetic than the mean wave conditions used by Infantes et al. (2009). Our choice was motivated by the hypothesis that the meadow distribution of the long-lived species P. oceanica is likely to respond more to storms rather than to mean wave climate (Boudouresque et al., 2012; Vacchi et al., 2014; Montefalcone et al., 2016). In the second place, we propagated wave states with different directions to take into account that the most energetic wavedriven hydrodynamic conditions occurring within the entire nearshore, in

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Figure 7: Mesh grid nodes in the northern sector of Solanas beach. In panel A, red circles and black crosses indicate the mesh nodes where the largest values of ub are induced, respectively, by run S2 and S3. In panel B, red circles and black crosses indicate the mesh nodes where the largest values of Uc are induced, respectively, by run S2 and S3. The thick green and black lines represent, respectively, the meadow and the rocky substratum limits.

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front of a particular beach, are not necessarily generated by incoming waves from a unique sector (Garcia-Valiente et al., 2017). See figure 7 showing that, whereas the largest wave orbital velocities ub are induced almost exclusively by run S3 (panel A), wave conditions of run S2 drive stronger currents than those induced by run S3 in the northern area of Solanas (panel B). Also this second methodological discrepancy with Infantes et al. (2009) tends to increase the wave energy and the related hydrodynamic forcing considered in our study. Other discrepancies, such as the different offshore wave hindcast datasets used or the adoption of two distinct wave models, are likely to play only a secondary and minor role. In the studied beach systems, P. oceanica meadows are able to colonize rocky outcrops in shallow depths under moderate to intense hydrodynamic forcing. In fact, whereas at Solanas and Porto Pino the meadow upper limit is found at depths on the order of 12 m on sandy bottoms, on rocky substrata P. oceanica is able to occupy shallow areas less than 5 m depth. This outcome is in agreement with Montefalcone et al. (2016) who reported similar observations along the Ligurian coast. The presence of the meadow under stronger hydrodynamic stresses than those usually tolerated on sandy bottoms seems to be related to the increased anchor strength offered by the rocky substrata. Moreover, the colonization of hard substrata is likely to be promoted by the stability of the bottom that prevents, or at least limits, the burial and the uprooting of P. oceanica plants. These results suggest that rocky substrata represent a favorable settling environment that is crucial for the survival of P. oceanica in nearshore areas characterized by intense hydrodynamics. Even tough our results show that wave-induced current values at the meadow upper limit have a large dispersion than other variables such as orbital velocities and bed shear stresses, the role played by mean flows as a limiting factor for the meadow development should not be overlooked. This is both because the bed shear stress calculation includes the effect of mean currents (together with that of orbital velocities) and because the mean current field in coastal waters is usually characterized by an uneven pattern due to the presence of rip and longshore currents. The disturbance that intense rip current flows can cause on the P. oceanica, leading to a possible meadow upper limit regression, has been suggested by several studies (Lasagna et al., 2011; Brambilla et al., 2016; De Muro et al., 2017b; Buosi et al., 2017). Figure 8 shows the results of the simulation P2, representing the most energetic wave condition in our numerical experiments. In figure 8 the spatial regres-

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sion of the meadow upper limit is found in those areas of the sandy shoreface where intense current velocities (on the order of 0.4-0.5 m/s) expand from shallow waters to water depths larger than 10 m. Thus, in this case the head of the rip currents can potentially affect the P. oceanica meadow. However, the same spatial relationship is not found at Solanas where an intense rip current develops induced by south-west swells during the run S3 (not shown in this paper) but the meadow upper limit does not have signs of spatial regression. It seems that our data do not bring enough evidence confirming the possibility that rip currents lead to local spatial regressions of the meadow upper limit. We suggest that this possible mechanism of interaction between currents and P. oceanica can be better clarified by means of a more extensive dataset proceeding from further investigations. Besides hydrodynamics, this study deals with the effects of sediment transport and morphodynamic parameters on the distribution of P. oceanica meadows. It is clear from the results that sediment transport processes and morphological changes are generally weak at the meadow upper limit location and they are significant only shoreward of the meadow. Thus, the large dispersion values associated with these processes are likely to be strictly connected to the weakness of sediment transport dynamics suggesting that, consistent with previous studies (Montefalcone et al., 2016), P. oceanica can tolerate only minimal sediment transport and morphological activities. In general terms, this work presents a new numerical dataset including hydrodynamic and sediment transport variables expected at the upper limit of the P. oceanica meadow under storm wave conditions. The numerical approach allows a quantitative study of nearshore processes that would otherwise be hardly possible through field measurements or remote sensing. These results integrate previous work contributing to the database relating seagrass meadow extension to hydrodynamic and sediment transport processes. As a final recommendation we would suggest that since the methodology is applied to two sandy beaches in southern Sardinia, caution should be taken before generalizing these results to beach systems with different characteristics or geographical settings.

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6. Conclusions In this paper we investigate the combined role of the hydrodynamic and sediment transport forcing on the shoreward development of the P. oceanica meadow. With this aim, we apply an approach including extreme wave anal22

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Run: P2; Hs = 3.9 m; Tp = 9.3 s; θ = 258.2° 4313

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1. On sandy substrata, the meadow upper limit sets up well outside the surf zone where the orbital velocities associated to storm wave conditions (1 year return period) are on the order of 0.8 m/s, the mean current magnitude does not exceed 0.5 m/s and the bed shear stresses are on the order of 6 N/m2 . 2. Hydrodynamic parameter values along the meadow upper limit location show less dispersion than those associated with sediment transport parameters. Among hydrodynamic parameters, wave-induced orbital velocities have the lowest quartile coefficient of dispersion QCD equal to 0.08. 3. Sediment transport processes and morphological changes under storm wave conditions are significant only shoreward of the meadow. The low values and high variability of the sediment transport parameters along the meadow upper limit (for instance, the mean total sediment transport is 0.02 dm3 /m/s with an associated coefficient of dispersion QCD equal to 0.56) suggest that P. oceanica can tolerate only weak morphological changes. 4. On the rocky outcrops in the close proximity of the headlands enclosing the two beach systems, the P. oceanica upper limit sets up on shallower depths (less than 5 m) with respect to those observed on the sandy shoreface (on the order of 12 m). The meadow upper limit on hard substrata is subject to more intense storm-induced hydrodynamics (mean wave-induced orbital velocity is 1.45 ±0.28 m/s) than those usually tolerated on sandy bottoms. This result is consistent with previous work and highlights the role played by the substratum in determining the environmental conditions for the long-term persistence of P. oceanica meadows.

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ysis and numerical modelling to two sandy beaches located in southern Sardinia (western Mediterranean). The results show that both hydrodynamics and sediment transport processes have a significant influence on the location of the P. oceanica meadow upper limit. Moreover, also bottom features play a role since the meadow upper limit over rocky substrata is usually observed in shallower depths with respect to those associated with the limit over sandy bottoms. On the whole, this paper provides a new numerical dataset that extends previous work representing an advancement towards a more complete understanding of the main factors that determine the P. oceanica upper limit location. The main findings are summarized here.

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Andrea Ruju and Sandro De Muro would like to acknowledge the funding by the Consorzio di Bonifica Sardegna Meridionale (CBSM) under project number COMCONV 2016DEMURO CBSM ARU.A.00.21. Marinella Passarella gratefully acknowledges Sardinia Regional Government for the financial support of her PhD scholarship (P.O.R. Sardegna F.S.E. Operational Programme of the Autonomous Region of Sardinia, European Social Fund 2007-2013 - Axis IV Human Resources, Objective l.3, Line of Activity l.3.1.). The authors would like to thank all those who helped with the field work: Daniele Trogu, Nicola Pusceddu, Paolo Frongia. Giovanni Coco is thanked for insightful discussions. References

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