Phenology of the Mediterranean seagrass Posidonia oceanica (L.) Delile: Medium and long-term cycles and climate inferences

Aquatic Botany 94 (2011) 77–92

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Phenology of the Mediterranean seagrass Posidonia oceanica (L.) Delile: Medium and long-term cycles and climate inferences Andrea Peirano a,∗ , Silvia Cocito a , Valeria Banfi a , Roberta Cupido a , Valentina Damasso a , Gianfranco Farina a , Chiara Lombardi a , Roberta Mauro a , Carla Morri b , Ingrid Roncarolo a , ˜ a , Dario Savini c , Sergio Sgorbini a , Cecilia Silvestri d , Nicola Stoppelli a , Sarahi Saldana Leonardo Torricelli a , Carlo Nike Bianchi b a

ENEA - Marine Environment Research Centre, C.P. 224, 19100 La Spezia, Italy DipTeRis - Dipartimento per lo studio del Territorio e delle sue Risorse, Università di Genova, Corso Europa 26, 16132 Genova, Italy c Dipartimento Ecologia del Territorio, Sez. Ecologia, Università di Pavia, Via S. Epifanio 14, 27100 Pavia, Italy d ISPRA - Institute for Environmental Protection and Research, Via Vitaliano Brancati, 48, 00144 Roma, Italy b

a r t i c l e

i n f o

Article history: Received 16 December 2009 Received in revised form 19 November 2010 Accepted 22 November 2010 Available online 27 November 2010 This paper is dedicated to the memory of one of the authors, Leonardo Torricelli, our great friend and colleague who left us in December 2006. Keywords: Seagrasses P. oceanica Phenology Climate

a b s t r a c t The results of 15 years of monitoring of Posidonia oceanica in the “Cinque Terre” Marine Protected Area (NW Mediterranean) are presented. Seasonal data on meadow characteristics (cover and shoot density), plant phenology (leaf number, leaf length and width, leaf brown portion, undamaged leaves), lepidochronology, leaf epiphyte cover and herbivore pressure collected from three stations at 5, 10 and 17 m depth were compared. Time-series analyses showed both medium-term (5 < years) and long-term cycles (from 5 to more than 20 years). The comparison of annual cycles with sea surface temperatures (SST) and rainfall showed correlations that differed in relation to depth and, in the case of epiphytes, with each side (internal and external) of the leaf blade. Meadow parameters (visual cover, shoot percent cover) and plant parameters (leaf number, number of undamaged leaves, number of scales shoot−1 ) showed a positive trend in accordance with the rise of air and sea surface temperature recorded over these last decades. Shoot density and leaf width showed exceptions. Leaf length, leaf brown portion length and the number of undamaged leaves shoot−1 showed positive or negative long-term trends, whose variability could not be related to climate data alone. The two major groups of epiphytes (encrusting algae and the bryozoan Electra posidoniae) showed negative trends. Grazing variability could be explained only partially by climate parameters. Epiphyte cover was found to be related to the NAO index. In conclusion, data showed that the effects of the climate change in terms of both sea surface temperature rising and rainfall decreasing may affect the growth cycles of P. oceanica on two levels: on a decadal level, with positive or negative trends in meadow and plant characteristics and in epiphyte cover; on yearly and seasonal levels, influencing endogenous plant growth rhythms, as in the case of leaf production cycle. © 2010 Elsevier B.V. All rights reserved.

1. Introduction The assessment of climate change effects on coastal marine communities is of paramount importance, and efforts are concentrated on both defining species and community responses to rising temperature, changing rainfall, and terrestrial runoff patterns as well as pH decrease (Nicholls et al., 2007) with the overall aim of predicting future trends in marine biodiversity (IPCC, 2002). These are crucial issues also for Europe (Alcamo et al., 2007), and especially in semi-enclosed basins like the Mediterranean Sea, where

∗ Corresponding author. Tel.: +39 0187978296: fax: +39 0187978273. E-mail address: [email protected] (A. Peirano). 0304-3770/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.aquabot.2010.11.007

an estimated 10% of the world’s marine biodiversity is present (Bianchi and Morri, 2000). Hydrographic and atmospheric-climate properties of the Mediterranean are correlated with the two major climate indicators: the North Atlantic Oscillation (NAO) index and the Northern Hemisphere Temperature index (Bouwer et al., 2008; Conversi et al., 2010). Since the end of the 1980s anomalies in seawater temperatures and circulation were recorded across the Mediterranean. At basin level, Conversi et al. (2009, 2010) found a ‘regime shift’, i.e. extensive and relatively abrupt changes in circulation, hydrological and zooplankton occurrence in the late 1980s. Surface seawater temperature (SST) maxima showed a positive trend from 1980 to 2005 at a rate of 0.04 ± 0.01 ◦ C year−1 (Diaz-Almela et al., 2007) and these increasingly frequent, positive thermal anomalies caused death of sensitive organisms and facili-

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tated colonization by tropical warm-water species (Cerrano et al., 2000; Bianchi, 2007; Galil, 2008). Primary effects of increased global temperature on seagrasses are expected to be the alteration of growth rates, physiological functions and sexual reproduction, depending on individual species’ thermal tolerance. Some indirect effects are changes in salinity, water depth, CO2 and pH, which could induce changes at community and productivity levels (Short and Neckles, 1999). Posidonia oceanica (L.) Delile is an endemic Mediterranean seagrass forming dense meadows up to 45 m depth (Procaccini et al., 2003). Its associated community is one of the most important of the Mediterranean both from an ecological (high diversity and biomass) and economic (fishery) point of view (Pérès and Picard, 1964; Ott, 1980). The plant is long-lived and it has covered all the littoral of the Mediterranean for millennia like a continuous ribbon (Pérès, 1984); its remnants are stratigraphic endogenous formations known as ‘mattes’, up to some meters thick, which are formed by rhizomes and roots that have entrapped sediment (Molinier and Picard, 1952; Lo Iacono et al., 2008). Among seagrasses P. oceanica has one of the greatest values in terms of biomass and primary production (Ott, 1980; Duarte and Chiscano, 1999). Carbon and nutrient stored in rhizomes and ‘mattes’ (Mateo et al., 1997) are transferred to epiphytes (Libes et al., 1987) or exported outside the seagrass bed through herbivory and litter transport (Pergent et al., 1997). Temperature and light availability are factors influencing seasonal P. oceanica growth and production (Ott, 1980; Zupo et al., 1997; Molenaar et al., 2000; Marbà and Duarte, 2010), the presence of leaf epiphytes (Cébrian et al., 1999a; Lepoint et al., 1999; Tsirika et al., 2007) and plant reproduction (Diaz-Almela et al., 2007). Morri and Bianchi (2001) and Díaz-Almela et al. (2009) suggested that the general decline of P. oceanica meadows could be enhanced by the decadal Mediterranean warming trend. Since the beginning of the 20th century, P. oceanica suffered a heavy regression as the inputs from urbanization and other anthropogenic activities (fishery, fish farming, tourism, desalination plants) reduced its presence on the Mediterranean coasts (Peirano and Bianchi, 1997). Futhermore, the spread of the alien green algae Caulerpa taxifolia and Caulerpa racemosa has probably stressed P. oceanica beds (Meinesz et al., 1993; Peirano et al., 2005a; Leriche et al., 2006; Molenaar et al., 2009). Potential covariance among these forcing factors may complicate conclusions on phenology of P. oceanica (Alcoverro et al., 1995), thus a multiannual to decadal approach could have sufficient power to differentiate long-term climate effects on the plant. On a decadal scale the lepidochronology and plastochrone interval (PI) methods, both based on the measurement of yearly growth of the rhizome, allow the reconstruction of leaf and rhizome production back to two-three decades earlier (Pergent et al., 1989; Duarte et al., 1994). Using the PI method, Marbà and Duarte (1997) showed that variability in P. oceanica growth along Spanish coasts could be partially explained (24–37%) by long-term climatic variance. However, the reconstruction methods cannot be used for measuring changes in meadow and plant characteristics such as cover, shoot density and leaf length, nor changes in epyphyte and grazing. Here, we show the results of 15 years of observations conducted on the P. oceanica meadow of the “Cinque Terre” Marine Protected Area (Ligurian Sea, NW Mediterranean), a site free from external disturbances since 1970. Leaf epiphytes, herbivory and plant parameters from three stations 5, 10, 17 m deep are analysed considering multiannual trends and climate characteristics and the long-term relations of these ‘ecosystem factors’ are discussed. Our specific objectives were: (a) to verify the periodicity in internal cycles of P. oceanica growth, in epiphytes cover and grazing activity; (b) to estimate possible correspondence among interannual variability in seagrass dynamics and climate.

Fig. 1. The P. oceanica meadow of Monterosso al mare and position of the three sampling stations. S = shallow station; I = intermediate station; D = deep station.

2. Material and methods Data collection in the P. oceanica meadow in Monterosso al Mare bay started in 1991, eighth years before the establishement of the area as MPA in the Italian National Park of ‘Cinque Terre’. The MPA has an extension of 16 km along the coastline and is characterized by a limited urbanization (five villages for a total of 5000 people). The meadow stretches for nearly 30 ha (Sgorbini et al., 2002) and covers the western side of the bay. Adjacent land-use and urbanization have not changed since 1970 (Cavazza et al., 2000). From the MPA’s institution new conservation measures, such as the ban of anchoring on the meadow, became effective only 5 years later. Three stations in the largest part of the meadow were sampled by means of SCUBA diving (Fig. 1): at the shallow (5 m) and the deep limit (17 m) and at intermediate depth (10 m). Sampling stations have a different habitat structure: patches of P. oceanica and bare blocks of eroded matte characterize the shallow area, a ‘hilltype’ meadow colonises the intermediate station, and dead and living matte covers the bottom of the deepest site, from 12 m to the lower, regressed limit (Cavazza et al., 2000). Sampling was performed seasonally in March, June, September and December from 1991 to 2001 and in June and December from 2001 to 2006. Sampling and laboratory analyses followed the conventional methods adopted for P. oceanica (Buia et al., 2004; Pergent-Martini et al., 2005; Boudouresque et al., 2006; Montefalcone, 2009). Recorded parameters considered two spatial scales: (a) meadow (cover and shoot density) and (b) shoot characteristics (leaf number, leaf length, leaf width, brown portion length, number of undamaged leaves and scales number). Two processes were analysed at shoot scale: (a) grazing activity and (b) epiphyte cover. At each station, three sampling sites were chosen randomly along a 50 m transect parallel along the shore. At each sampling site P. oceanica canopy cover (VC) was visually estimated by two experienced divers on a circle with a 5 m radius (Buia et al., 2004; Montefalcone et al., 2008). Shoot density (D) was estimated by counting the number of shoots in six sub-quadrats (20 × 20 cm), randomly selected on a gridded quadrat of 1 m2 located in the centre of the circle. Shoot percent cover (SPC) was calculated as the

A. Peirano et al. / Aquatic Botany 94 (2011) 77–92

percentage of sub-quadrats containing P. oceanica shoots in a total number of 25 quadrats. Shoot analyses were performed on 20 orthotropic shoots collected randomly at each sampling station. In the laboratory leaf length (LL), leaf width (LW), number of leaves (LN), the discolored proportion of the leaf, generally brownish (LBP), and the number of undamaged leaves (UL) were measured following Giraud (1977). The number of scales per year (SC) was counted on each shoot following the lepidochronological method. The method is based on the cyclic annual variation of the sheath thickness identifying the start of a ‘lepidochronological’ year as the annual minimum in scale thickness (Pergent, 1990; Peirano, 2002). Epiphyte percent cover on both leaf sides (internal and external) was measured from 1992 to 2000 on five shoots per station. The following epiphytic categories were taken into account: algae (encrusting = EA, erect = AE, algal mat = AM) hydroids = Hy (Sertularia perpusilla, Plumularia obliqua, others), bryozoan (Electra posidoniae = Ep, others) and other animal taxa (Peirano et al., 2001; Buia et al., 2004). Herbivore consumption was estimated per shoot counting the number of leaves with grazed tips. Leaf marks were attributed to the urchin (UG) Paracentrotus lividus (Lamarck) the fish (FG) Sarpa salpa (L.), or the isopods (IG) Idotea spp. Fabricius following Boudouresque and Meisnez (1982). Differences among stations and years were evaluated using twoway ANOVA (depth × year). Three-way ANOVA was used in the case of epiphytes (depth × year × leaf side). Levene’s test was used for testing the homogeneity of group variances and post-hoc comparisons of means were performed through Tukey’s test. Air temperature (AirT), surface sea temperature (SST), rainfall and North Atlantic Oscillation (NAO) index were included as climate indicators. AirT and SST are the main responsible in influencing the seasonal growth of P. oceanica, whereas rainfall is the main factor related to seasonal nutrient enrichment and seawater turbidity (Alcoverro et al., 1995; Marbà and Duarte, 1997). In the Mediterranean, winter is often the most important period for feeding and accumulating reserves for a great variety of organisms, from gorgonians to seagrasses (Pirc, 1985; Ribes et al., 1999). Close to the area of investigation nitrite and nitrate amounts may reach their maximum in January (respectively NO2 = 0.69 ␮mol l−1 and NO3 = 6.02 ␮mol l−1 ) when nutrient availability is enhanced by rain-off and resuspension of bottom sediments (Peirano et al., 2005b). Data on monthly air temperatures (AirT) were obtained from the Italian Environment Protection and Technical Services Agency (APAT) through the SINAnet-SCIA network (http://www.scia.sinanet.apat.it/). Data on monthly rainfall were computed by analysing the data available on the website http://www.ilmeteo.it. Both data series refer to the Genoa metereological station, the only station in Liguria where weather data were recorded since 1866. The station is located 70 km far away from Monterosso al Mare. Monthly sea surface temperatures (SST) data from 1985 to 2006 were computed from AVHRR Pathfinder 5 datasets, with a grid of 4 km, distributed by NASA Physical Oceanography Distributed Active Archive Center (PO.DAAC) through the Ocean ESIP Tool (POET) (http://poet.jpl.nasa.gov//). Data on the North Atlantic Oscillation (NAO) index were downloaded from www.cpc.ncep.noaa.gov/. Correlations of climate and P. oceanica parameters were evaluated through time-series analysis. Seasonal SST, rainfall and P. oceanica series were smoothed through four-point (seasonal) moving averages and correlations between climate and plant parameters were tested through stepwise regression analysis. Decadal linear trend differences among stations of each considered parameter were analysed through ANCOVA – homogeneity of slopes model, with time (year) as covariate. The ANCOVA test

79

Table 1 P. oceanica: two-way ANOVA results of differences among stations (5, 10, 17 m) at meadow level. Depth

Mean ± SE

n

Source of variation

Df

MS

p

Visual cover (%) 5m 51.8 ± 3.2 10 m 56.2 ± 3.1 17 m 46.1 ± 3

47 48 51

Depth Year Depth × year Error

2 15 30 98

Shoot percent cover (%) 5m 94 ± 5.3a 10 m 95 ± 4.7b 17 m 87 ± 8.4c

51 50 51

Depth Year Depth × year Error

2 15 30 104

948 128 42 27

<0.001 <0.001 0.059

53 51 53

Depth Year Depth × year Error

2 15 30 109

367 367186 5279 3962

<0.001 0.298 0.144

1064.2 0.071 914.1 0.007 243.1 0.931 391.6

a=b>c Density (n shoots × m−2 ) 5m 349.4 ± 9·4a 10 m 273.9 ± 9.6b 17 m 168.6 ± 9·4c a>b>c

of parallelism analysed the differences among the slopes of the regression lines (trends). Medium and long-term cycles of plant parameters and herbivore grazing and their periodicity were evaluated smoothing the four-point series through single series (Fourier) spectral analysis. The resulting periodograms allowed identification of spectral densities and periods that significantly contribute to cyclic behaviour of the series. 3. Results 3.1. Meadow parameters Meadow cover estimated by visual method (VC) varied from 46 to 56% (Table 1, Fig. 2a). Maxima occurred in June and December at the shallow station, in June at the intermediate station and in September at the deep station. Minima were observed in March at the intermediate and deep stations and in March and September at the shallow station. Two-way ANOVA showed differences among years mainly due to the greater mean annual value of 79% in 1996. The positive linear trends of the three stations did not show differences (ANCOVA, p = 0.89). Decadal analyses showed two cycles: one with a mean period of 3.6 ± 0.9 years and another one with a long-term oscillation of 14 years. Shoot percent cover per m2 (SPC) showed differences among stations and years (two-way ANOVA, p < 0.001) (Table 1, Fig. 2b). Shallow and intermediate stations had significantly higher cover (94–95%) than the deep station (87%). Maxima were recorded in December at shallow and deep stations. Minima occurred in September at the shallow station and in March at the deep station. Intermediate station did not show seasonality. The difference between years was due to increasing values from 1993 to 2004. The linear trend was positive with a steeper slope in the deep station which differed significantly from intermediate and shallow stations (ANCOVA, p = 0.03, Fig. 2b). All stations showed medium-term oscillations of 4.6 ± 2.4 years. A longer, decadal cycle with a period of nearly 20 years may be present (Fig. 2b). Shoot density per m2 (D) showed differences (two-way ANOVA, p < 0.001) between stations with shoot density progressively decreasing from the shallow (349.4 shoot m−2 ) to the intermediate (273.9 shoot m−2 ) and the deep station (168.6 shoot m−2 ) (Table 1, Fig. 2c). Maxima were observed in June and December at the shallow station, in September at the intermediate station and in March and September at the deep station. Minima occurred in March and September at the shallow station, in March and December at the intermediate station and in June and December at the deep

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A. Peirano et al. / Aquatic Botany 94 (2011) 77–92

a

Visual cover (%)

b

Shoot percent cover (%)

c

Density (shoot x m2 )

5m 10 m 17 m

100

80

60

40

20

0

110

100

90

80

70

60

500

450 400 350 300 250

200 150

12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12

100

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

Fig. 2. P. oceanica: four-point running averages of seasonal variations of meadow parameters at Monterosso al Mare from December 1991 to December 2006: a) visual cover; b) shoot percent cover; c) shoot density.

station. The decadal trends differed significantly among stations (ANCOVA, p < 0.001), they were positive at the shallow station and negative at the intermediate and deep stations. The three stations showed medium-term oscillations of 3.5 ± 1.2 years. Two multiannual cycles, one of 14 years (shallow station) and 7 years (intermediate station) were found.

3.2. Plant parameters Mean leaf number (varying from 6.8 to 6.9) per shoot (LN), did not show differences among stations (Table 2, Fig. 3a). The minima were observed in June and maxima in December. Differences were highly significant among years (two-way ANOVA, p < 0.001) due

A. Peirano et al. / Aquatic Botany 94 (2011) 77–92

81

a Leaf number (nx shoot 1 ) 10

5m 10 m 17 m

9 8 7 6 5 4 3

b Leaf length per shoot (mm) 600 550 500 450 400 350 300 250 200

c Leaf width per shoot (mm) 11 10.5 10 9.5 9 8.5 8 7.5

12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12

7

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

Fig. 3. P. oceanica: four-point running averages of seasonal variations of meadow parameters at Monterosso al Mare from December 1991 to December 2006: a) mean leaf number per shoot; b) mean leaf length per shoot; c) mean leaf width per soot.

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Table 2 P. oceanica. Two-way ANOVA results of differences among stations (5, 10 m, 17 m) at plant level.

−1

Leaf number (n × shoot

Depth

Mean ± SE

n

Source of variation

5m 10 m 17 m

6.8 ± 0.2 6.9 ± 0.2 6.8 ± 0.2

49 52 51

Depth Year Depth × year Error

2 15 30 104

0.1 7.8 0.6 1.3

5m 10 m 17 m

381.3 ± 23.8 395.0 ± 22.4 329.4 ± 22.8

49 52 51

Depth Year Depth × year Error

2 15 30 104

51141.0 24034.0 10153.0 22113.0

5m 10 m 17 m

9.3 ± 0.1a 9.4 ± 0.1b 9.1 ± 0.1c

49 52 51

Depth Year Depth × year Error

2 15 30 104

1.2 3.3 0.2 0.3

5m 10 m 17 m

34.5 ± 6.5a 41.2 ± 6.1b 68.6 ± 6.7c

49 52 48

Depth Year Depth × year Error

2 15 30 101

12179.6 1223.0 605.1 1632.5

0.001 0.729 0.999

5m 10 m 17 m

4.2 ± 0.3a 4.9 ± 0.2b 5.1 ± 0.2c

49 52 51

Depth Year Depth × year Error

2 15 30 104

8.5 6.9 1.0 2.5

0.035 0.001 0.996

5m 10 m 17 m

6.1 ± 0.3 6.4 ± 0.3 6.0 ± 0.3

42 43 42

Depth Year Depth × year Error

2 13 26 85

1.2 16.6 0.6 3.7

Df

MS

p

) 0.894 <0.001 0.988

Leaf length (mm) 0.104 0.378 0.992

Leaf width (mm) 0.028 <0.001 0.905

a=b>c Leaf brown portion (mm)

a=b
a=b
to the highest values recorded in 2000. Decadal analyses showed a net positive trend that did not differ among the three stations (ANCOVA, p = 0.08); medium-term cycles with a period of 3.5 years and multiannual oscillations with a period of 14 years were shown. Average leaf length per shoot (LL) varied from 329 to 395 mm and did not display differences among stations or years (Table 2, Fig. 3b). Minima were recorded in December and maxima in June. Shallow and intermediate stations showed a positive trend that differed (ANCOVA, p < 0.001) from the negative one of the deep station. Medium and long-term cycles corresponded to 3.2 ± 1.6 and 9.3 ± 4 years. Mean leaf width per shoot (LW) showed only moderate differences among stations (p = 0.03) decreasing from shallow and intermediate (9.3–9.4 mm) stations to deep (9.1 mm) station (Table 2, Fig. 3c). Maxima occurred in December at the shallow station, in December–March at the intermediate station and in March and September at the deep station. Minima were recorded in June at the shallow and the deep stations and in June and September at the intermediate station. Differences among years were significant (two-way ANOVA, p < 0.001) due to the leaf width increase in the deep stations between 1999 and 2001. A negative linear trend was present in all the three stations (ANCOVA, p = 0.11) and two cycles were recognizable: one of 2.3 years and one of 7 years. Mean length of the leaf brown portion per shoot (LBP) showed a difference among stations (two-way ANOVA, p = 0.001) due to the greater amount of mean brown portion in leaves of the deep station (68.6 mm) (Table 2). The maxima in brown cover were observed in September and minima in March at the shallow and intermediate stations, in March–June at the intermediate station. Differences were found among multiannual linear trends (ANCOVA, p < 0.001): positive in the shallow and intermediate stations, negative in the deep one. Medium and long-term analysis showed cycles with a periodicity respectively of 3.4 ± 1.2 and 10.5 ± 4.9 years.

0.717 <0.001 1.000

The mean number of leaves per shoot with undamaged tips (UL) increased from the shallow station (4.2 leaves shoot−1 ) to the deep station (5.1 leaves shoot−1 ). Differences were found both among stations (two-way ANOVA, p = 0.03) and among years (p = 0.001) with the mean highest number of UL recorded in 2000 (6.5 ± 1 leaves shoot−1 ) (Table 2, Fig. 4b). Maxima were recorded in December and minima in June at the intermediate and deep stations and in March–June at the shallow station. The comparison of the positive linear trends of the three stations showed differences due to the more steep slope of the shallow station (ANCOVA, p = 0.01). Time-series analysis showed a periodicity of 3.5 years in medium-term cycles and of 9.3 ± 4 years in long-term cycles. The average mean number of scales per shoot (SC) obtained through lepidochronology varied from 6 to 6.4 scales and showed differences among years (p < 0.001) (Table 2, Fig. 4c). An irregular shifting of the minimum in scale thickness was observed from March to June and September from 1994 to 2001. Maxima shifted from March to December from 1995 to 1999. The multiannual trend was positive and did not differ in the three stations (ANCOVA, p = 90.65). The decadal analyses showed two cycles: one with a period of 2.7 ± 0.7 years and one long-term cycle of 9.5 years. 3.3. Epiphytes Few epiphyte categories showed high abundance; only encrusting algae (EA) and the bryozoan E. posidoniae (Ep) showed continuous seasonal cover that allowed identifying multiannual cycles in the period 1992–2000. Three-ways ANOVA conducted on EA showed differences (three-way ANOVA, p < 0.001) due both to a decrease in cover of the inner side of the leaf, related to depth (from 3.7 to 2.3%) and to the difference between the internal and the external side of the leaves (Table 3, Fig. 5a, b, c). Maxima of cover were recorded in Septem-

A. Peirano et al. / Aquatic Botany 94 (2011) 77–92

83

a Leaf length of brown portion per shoot (mm) 150

5m 10 m 17 m

125

100

75

50

25

0

b Undamaged leaves (n x shoot

-1

)

8

7

6

5

4

3

2

-1 c Scales (n x shoot )

11 10 9 8 7 6 5 4 3

12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12 3 6 9 12

2

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

Fig. 4. P. oceanica: four-point running averages of seasonal variations of meadow parameters at Monterosso al Mare from December 1991 to December 2006: a) mean leaf length of brown portion per shoot; b) mean number of undamaged leaves per shoot; c) mean number of leaf scales per shoot.

ber at the shallow and deep stations and in June at the intermediate station. Minima were observed in December–March. The trend was negative at all depths and did not show differences between leaf sides. Fluctuations of 4 years were common to the shallow and the intermediate stations.

E. posidoniae cover differed between the internal and more colonised side (from 4.2 to 5.8%) and the external side of the leaves in all three stations (three-way ANOVA, p < 0.001) with the highest percentage cover found in the intermediate station (Table 3, Fig. 6a, b, c). Minima were recorded in September and maxima in

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Table 3 P. oceanica. Three-way ANOVA results of differences among stations (5, 10, 17 m) and leaf side (ext, int) of the two main groups of epiphytes: encrusting algae and E. posidoniae. Depth Encrusting algae (cover%) 5 ma 10 mb 17 mc

Leaf side

Mean ± SE

n

Source of variation

Df

ext int ext int ext int

2.3 ± 0.3 3.7 ± 0.3 2.1 ± 0.3 2.8 ± 0.3 2.5 ± 0.3 2.3 ± 0.3

182 182 184 184 174 174

Depth Year Leaf side Depth × year Depth × leaf side Leaf side × year Error

2 9 1 18 2 9 1020

95.98 338.59 49.83 59.22 27.93 5.07 7.98

<0.001 <0.001 0.013 0.000 0.031 0.767

0.8 ± 0.4 4.9 ± 0.4 0.9 ± 0.4 5.8 ± 0.4 1.8 ± 0.4 4.2 ± 0.4

182 182 184 184 174 174

Depth Year Leaf side Depth × year Depth × leaf side Leaf side × year Error

2 9 1 18 2 9 1020

18.86 210.64 2729.49 36.96 108.54 112.46 21.75

0.420 <0.001 <0.001 0.034 0.007 <0.001

MS

p

a > b = c; int (a) > ext (a); int (b) > ext (b) E. posidoniae (cover %) 5m 10 m 17 m

ext int ext int ext int

int > ext

March–June. Multiannual trends were negative in all the three stations and differed significantly (ANCOVA, p < 0.001); the external part of the leaves of the shallow station showed a more steeply slope. A cycle with a periodicity of 4 years was common to all stations. 3.4. Herbivory Urchin grazing activity (UG) had the largest impact on leaves in March–June whereas minima were recorded in September–December. The mean number of leaves grazed per shoot did not vary with depth (0.4 leaves shoot−1 ). Differences were significant among years (two-way ANOVA, p < 0.001) due to the maximum grazing recorded in 1999 – 2000 (Table 4, Fig. 7a). The linear trends differed significantly (ANCOVA, p = 0.01) with negative values in the shallow station and positive in the intermediate and deep stations. The multi- annual analyses showed two cycles: one with a periodicity of 2.8 ± 1.1 years and another one with a period of 7 years. The number of leaves grazed by fishes (FG) showed a significant difference among stations (two-way ANOVA, p = 0.006) due to the increasing grazing pressure moving from the deep (0.3 leaves shoot−1 ) to the shallow station (0.7 leaves shoot−1 ) (Table 4, Fig. 7b). The maxima were recorded in June at the shallow

Table 4 P. oceanica. Two-way ANOVA results of differences among stations (5, 10, 17 m) of grazing pressure. Depth

Mean ± SE

n

Source of variation

Urchin grazing (leaves grazed × shoot−1 ) 5m 0.4 ± 0.1 49 Depth 10 m 0.4 ± 0.1 52 Year 17 m 0.4 ± 0.1 51 Depth × year Error Fish grazing (leaves grazed × shoot−1 ) 49 Depth 5m 0.7 ± 0.1a 52 Year 10 m 0.5 ± 0.1b c 17 m 0.3 ± 0.1 51 Depth × year Error a=b
Df

MS

p

2 15 30 104

0.03 1.11 0.11 0.17

0.859 < 0.001 0.900

2 15 30 104

1.95 0.36 0.22 0.37

0.006 0.479 0.936

2 15 30 104

0.04 0.06 0.03 0.03

0.253 0.027 0.486

station and in September at the intermediate and deep stations; minima were recorded in December–March. The linear trends resulted different (ANCOVA, p < 0.001), changing from positive in the shallow station to negative in the deep one. Two cycles, with a period of 2.9 ± 0.8 years and 7 years were found. The number of leaves grazed by isopods (IG) was very low (0.1–0.2 leaves shoot−1 ) (Table 4, Fig. 7c). Differences among years (two-way ANOVA, p = 0.03) were associated to the high variability among three stations. Maxima were recorded in March at the shallow station and in September at the intermediate station. Minima occurred in September–December at the shallow station and in December at the intermediate station. The deep station did not show seasonality in grazing. Although the shallow and the intermediate stations showed a negative trend and the deep station a positive one, differences among stations were not relevant (ANCOVA, p = 0.06). A 3.2 ± 2 year cycle and one of 7 years were found. 3.5. Climate and phenological analyses Time-series analysis of air temperature data from 1866 showed a decadal, positive trend, a major cycle with a periodicity of 70 years and other minor cycles of 12.7 and 7.8 years (Fig. 8a). Sea surface temperature from Monterosso al Mare were highly correlated with Genoa air temperature (Astraldi et al., 1995; Peirano et al., 2009) and showed a general positive trend and oscillations of 11.9 years; further oscillations of 9.3 and 6 years were consistent with those found by Marbà and Duarte (1997) for the Spanish coast. At a seasonal level (Fig. 8b), the period 1985–2006 showed cycles of 6 and 3.5 years defined by regular minima in 1987–1993–1995–1999–2005 with a positive trend and a greater variability due to the highest frequency of high summer temperatures (1999 and 2003). Annual rainfall showed one cycle of 15.5 years and a negative trend due to a progressive decline of precipitations since the 1980s (Fig. 8c). The analysis on a multiannual scale showed 7 and 3.5 years’ cycles, with minima in 1989–1995–2001 and a great variability in rainfall that declined between 1991 and 1993. Comparisons of climate and meadow parameters performed on four-season running averages (Table 5) showed that visual cover (VC) was only weakly, negatively correlated to rainfall (p = 0.027) at the deep station. Shoot percent cover (SPC) was positively correlated with SST at the intermediate (p = 0.027) station. At the deep station SPC was negatively correlated with rainfall (p < 0.001) and positively correlated to SST. Shoot density (D) showed correlations with SST changing with depth, from

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85

Fig. 5. P. oceanica: four-point running averages of seasonal variations of encrusting algae on the internal (int) and external (ext) side of the leaves in the three stations (5, 10 and 17 m) from March 1991 to December 1999.

the shallow (positive; p = 0.015) to the intermediate and deep stations (negative; p ≤ 0.001). At the intermediate and deep station shoot density was also positively correlated with NAO (p < 0.05). Plant parameters (Table 6) showed a positive correlation of leaf number (LN) with SST (p < 0.0001) at the shallow station and a

positive correlation with SST (p < 0.001) and rainfall (p = 0.01) at the deep station. Leaf length (LL) was negatively correlated to SST (p = 0.04) at the deep station, it was negatively correlated (p = 0.02) with precipitation at the intermediate station, and negatively correlated with precipitation (p = 0.001) and NAO (p < 0.001)

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Fig. 6. P. oceanica: four-point running averages of seasonal variations of E. posidoniae on the internal (int) and external (ext) side of the leaves in the three stations (5, 10 and 17 m) from March 1991 to December 1999.

at the shallow station. Leaf width (LW) showed negative correlations with SST at all stations (p < 0.05). The length of the brown leaf portion (LBP) was correlated with rainfall (p < 0.001), SST (p < 0.001) and NAO (p = 0.035) only at the intermediate station. The number of undamaged leaves per shoot (UL) was positively

correlated to SST only at the shallow and deep stations (p < 0.001). The number of scales per season was highly correlated (p < 0.001) to SST in the intermediate stations and correlated with SST (p < 0.001) and precipitation (p < 0.05) at the shallow and deep station.

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87

Fig. 7. P. oceanica: four-point running averages of seasonal variations of grazing from December 1991 to December 2006. Mean number of leaf tips grazed per shoot by: a) Urchin; b) Fishes; c) Isopods.

Principal Component Analysis (PCA) conducted on plant, epiphytes (EA and Ep) and climate data (SST, rainfall amount and NAO index) was used to explore Northern Hemisphere climate effects on the studied meadow for the period 1992–2000. PCA showed that, as expected, epiphyte cover was mainly influenced by leaf length and leaf width and it covaried with these two parameters (Fig. 9a). The second vs. the third factor analysis showed that encrusting algae (EA) covaried with NAO at the shallow and intermediate station

whereas E. posidoniae (Ep) covaried with NAO only at the deep station (Fig. 9b). 4. Discussion and conclusions Time-series analyses showed that both medium and long-term oscillations are recognizable in the P. oceanica bed of Monterosso al Mare. Medium-term oscillations were found for all parame-

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Fig. 8. Climate characteristics of the Ligurian Sea: a) Mean annual air temperature, mean annual sea surface temperature (SST) and total annual rain amount (the window shows the period of P. oceanica monitoring at Monterosso al Mare). b) Seasonal variation of SST from 1985 to 2006 at Monterosso al Mare (the four-season running average is indicated with the broken line); c) seasonal variation of rain amount and the NAO index from 1985 to 2006.

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Table 5 P. oceanica. Linear stepwise regression of climate (SST; R = Rainfall; NAO) vs. meadow parameters after four-season running averages transformation. VC = visual cover (%); SPC = shoot percent cover (%); D = shoot density (number shoots m−2 ). Stepwise regression equations appear as follows: meadow parameter (y) = constant + climate parameter (x1 ) × coefficient (b1 ) + climate parameter (x2 ) × coefficient (b2 ). Depth

Meadow parameter (y)

Climate parameter (x)

r

p

n

Constant ± SE

Coefficients (b) ± SE

5m

D SPC

SST R

0.33 −0.42

0.015 0.001

55 55

−208.73 ± 217.23 98.37 ± 1.02

29 ± 11.54 −0.04 ± 0.01

10 m

D

SST (x1 ) NAO (x2 ) SST

−0.46 0.24 0.29

<0.001 0.047 0.027

55 55 55

788.93 ± 132.50

−27.34 ± 7.24 (b1 ) 15.61 ± 7.68 (b2 ) 1.42 ± 0.62

17 m

D

SST (x1 ) NAO (x2 ) R SST (x1 ) R (x2 )

−0.44 0.27 −0.29 0.27 −0.50

<0.001 0.023 0.031 <0.015 <0.001

55 55 55 55 55

473.74 ± 83.71

SPC

VC SPC

68.99 ± 11.73

−16.63 ± 4.44 (b1 ) 11.30 ± 4.85 (b2 ) −0.09 ± 0.04 2.94 ± 1.17 (b1 ) −0.07 ± 0.02 (b2 )

57.01 ± 3.92 39.22 ± 22.69

Table 6 P. oceanica. Linear stepwise regression parameters of climate (SST; R = Rainfall; NAO index) vs. plant parameters after four-seasons running averages transformation. LN = leaf number (n shoot−1 ); LL = leaf length (mm); LW = leaf width (mm); LBP = leaf brown portion (mm shoot−1 ); UL = undamaged leaf (n shoot−1 ); SC = Scales (n shoot−1 ). Stepwise regression equations appear as follows: plant parameter (y) = constant + climate parameter (x1 ) × coefficient (b1 ) + climate parameter (x2 ) × coefficient (b2 ) + climate parameter (x3 ) × coefficient (b3 ). Depth

Plant parameter (x)

Climate parameter (y)

r

p

n

Constant ± SE

Coefficient (b) ± SE

5m

LN LW UL SC

SST SST SST SST (x1 ) R (x2 ) R (x1 ) NAO (x2 )

0.54 −0.41 0.58 0.47 −0.32 −0.35 −0.52

<0.001 0.002 <0.001 <0.001 0.01 0.001 <0.001

56 56 55 49

−9.22 ± 3.5 17.97 ± 2.56 −16.35 ± 3.98 −19.61 ± 6.98

55

426.44 ± 14.86

0.86 ± 0.18 −0.45 ± 0.12 1.10 ± 0.21 1.44 ± 0.36 −0.02 ± 0.01 −0.54 ± 0.16 (b1 ) −62.67 ± 12.29 (b2 )

LL 10 m

LW SC LL LBP

SST SST R R (x1 ) SST (x2 ) NAO (x3 )

−0.30 0.58 −0.31 0.58 0.43 −0.25

0.024 <0.001 0.020 <0.001 <0.001 0.035

55 49 55 56

16.46 ± 2.97 −23.99 ± 6.21 44.19 ± 15.46 −187.53 ± 60.14

−0.37 ± 0.16 1.60 ± 0.32 −0.39 ± 0.16 0.20 ± 0.04 (b1 ) 11.04 ± 3.11 (b2 ) −7.0 ± 3.26 (b3 )

17 m

LN

SST (x1 ) R (x2 ) SST SST SST SST (x1 ) R (x2 )

0.63 0.31 −0.37 −0.43 0.60 0.56 −0.24

<0.001 0.010 0.004 <0.001 <0.001 <0.001 0.040

55

−13.34 ± 3.74

55 55 55 49

957.93 ± 207.77 19.55 ± 2.99 −14.37 ± 3.61 −19.58 ± 5.63

1.04 ± 0.19 (b1 ) 0.007 ± 0.002 (b2 ) −32.87 ± 11.04 −0.55 ± 0.16 1.036 ± 0.19 1.41 ± 0.29 (b1 ) −0.012 ± 0.006 (b2 )

LL LW UL SC

1.0

1.0 CV(d)

Ep int(s) Ep ext(s)

LW(d)

LN(d) SPC(d)

CV(s)

LL(d)

SST

Rain amount

EA ext(d) EA int(d) EA int(i) Ep ext(d) LBP(d) D(d)

LL(i)

0.5 LBP(i)

LL(s)

UL(d) Ul(s) LN(s) LN(i) UL(i)

SPC(i)

LW(s) LW(i) LL(s)

0.0

-0.5

D(s)

LBP(d) EA ext(I) Ep int(d)

D(s)

-0.5

-0.5

0.0

Factor 1 : 48 %

SPC(i) D(d)

UL(i)

EA int(s) EAext(s)

NAO NAO

D(i)

-1.0 -1.0

LN(s) LN(i)

Ep ext(d)

Ep int(d) NAO

Ep int(i)

LW(d) SPC(d) LBP(i) UL(d) LN(d) SST CV(s) Rain amount EA ext(d) EA int(d) EA int(i) Ul(s)

SPC(s)

SC(i)

Ep int(s) Ep ext(s)

LBP(s)

LL(d)

SPC(s)

EA ext(I) EA int(s) EAext(s)

CV(d)

SC(d)

LBP(s)

LW(s)

CV(i)

SC(d)

Factor 2 : 17 %

LW(i)

Factor 2 : 17 %

SC(s) Ep ext(i)

SC(i)

CV(i)

LL(i) Ep (int(i)

0.5

0.0

Ep (ext(i)

SC(s)

D(i)

0.5

1.0

-1.0 -1.0

-0.5

0.0

0.5

1.0

Factor 3 : 13 %

Fig. 9. Correlations of time-series from 1992 to 2000 in PCA: a) first vs. second factor, b) second vs. third factor. VC = visual cover (%), SPC = shoot percent cover (%), D = shoot density per m2 , LL = leaf length (mm), LN = leaf number per shoot, LW = leaf width per shoot, UL = undamaged leaf per shoot, SC = number of scales per shoot. Cover of epiphyets per shoot on the internal (int) and external (ext) leaf side, encrusting algae = EA, E. posidoniae = Ep, (s) = shallow station (5 m), (i) intermediate station (10 m), (d) deep station (17 m).

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ters considered, from plant to epiphytes and grazers’ activity. The variability in medium-term oscillations was mainly due to the differences among cycles in the three stations considered. The length of the long-term cycles, from 5 to 14 years, roughly corresponded to the duration of the observed sea surface temperature cycles. The plots of visual cover, undamaged leaves, leaf number, leaf length, leaf width, epiphytes and urchin grazing showed clear oscillations with minima or maxima in the years 1992–1993, 1995, 1999–2000, 2003, 2005. These findings are in agreement with the last four sea surface temperature oscillations, defined by the lowest SST annual values in 1993, 1995, 1999, 2005. Even if the main forcing factor on P. oceanica cycles appeared to be the lowest annual temperature, we cannot esclude the co-occurring influence of the two highest SST values recorded in 2000 and 2003. Although the meadow studied was formed by three zones that differed both for depth (5, 10 and 17 m) and morphological characteristics (shallow = eroded matte; intermediate = ‘hill type’ meadow; deep = regressed limit), visual cover (VC), shoot percent cover (SPC), leaf number (LN), number of undamaged leaves (UL) and number of scales (SC) shoot−1 showed positive trends, increasing with time, at all depths. Shoot density (D) showed correlations with both SST and rainfall with trend inversion from the shallow to the intermediate and deep stations. The significant negative correlation of shoot density with SST and the positive correlation with rainfall (i.e. nutrients load) at the intermediate and deep stations, suggest a greater sensitivity of the meadow to these two parameters below 10 m. In these last 15 years, the intermediate and deep stations have maintained healthy shoots, which are typical in terms of leaf number and leaf length. Adaptation was achieved through a shoot “rearrangement” on a larger area, as showed by the positive trend of shoot percentage cover and by the inverse negative trend in shoot density. This shoot density rearrangement can be seen as an adaptive response adopted by this clonal plant at micro-scale to self-shading effects (Molenaar et al., 2000; Olesen et al., 2002; Ralph et al., 2007). Kun-Seop et al. (2007) observed that seagrasses growing in low light condition reduce shoot densities and above-ground biomass as an effective acclimation response to reduce self-shading within the canopy. These shoot adaptations have probably led to increased plant productivity through physiological adaptations as increased chorophyll concentration and photosynthetic efficiency (Dalla Via et al., 1998; Kun-Seop et al., 2007). This adaptive response, in agreement with findings of Molenaar et al. (2000) on colonisation and branching pattern of P. oceanica, allowed the deep portion of the meadow to maintain a fragile equilibrium, a condition frequently observed in other P. oceanica beds of the Liguria region (Peirano et al., 2005a; Montefalcone et al., 2008, 2009). Marbà and Duarte (2010) demonstrated that higher summer temperature due to recurring events of abnormal heat waves, have a remarkably incidence on shoot mortality and in the future could have negative effects on this equilibrium and cause meadow regression. Leaf width (LW) showed a weak negative trend in the shallow and intermediate station and a more accentuated negative trend in the deep station. Abbate et al. (2000), analysing chlorophyll content and leaf characteristics from eighth shallow meadows in Liguria, showed that the increase in leaf width was directly related to light limitation. Hence, the reduced width, observed in P. oceanica leaves of the investigated meadow, allows hypothesizing an increase in irradiance during last 15 years, to which the decrease in epiphytic cover contributed. Such hypothesis is supported by the opposite, negative correlation of LW vs. SST. Lepidochronological analysis of the mean annual number of scales showed high correlations with SST and a positive decadal trend at all depths. These findings are in agreement with both the positive trend of SST recorded for the Mediterranean (Diaz-Almela et al., 2007) and with the positive trend in P. oceanica growth shown

by nearly all meadows from the Spanish (Marbà and Duarte, 1997) and Ligurian coasts (Peirano et al., 2005a). Rhizome growth analysis (lepidochronology and internodal length methods) are based on scale counts and on the timing of leaf renewal (Pergent, 1990; Duarte et al., 1994). In lepidochronology the ‘lepidochronogical year’ is assumed to be 12 months, although the start of the year may change from one place to another (Pergent, 1990). Using internodal length method, the average ‘plastochrone interval index’ or PI, is the mean time of appearance of two consecutive leaves; the PI may vary from 28 to 69 days and interannual variability is much smaller than seasonal variability (Cébrian et al., 1999b; Duarte et al., 1994). Our study reveals synchronous anomalies in leaf renewal cycles across all stations in the same area. Lepidochronological years were prolonged to 15 months or reduced to 6 months. Because leaf number appears closely related to SST, one may hypothesise that these changes are related to climate variability. In accordance with Prado et al. (2007) few epiphyte categories were abundant. The two major groups (encrusting algae and the bryozoan E. posidoniae) exhibited medium-term oscillations of 4 years and encrusting algae (EA) showed a cover decreasing with depth in agreement with findings of Dalla Via et al. (1998). Principal Component Analysis showed that the negative trends observed in encrusting algae, were probably related to a decrease in rainfall and seawater turbidity, which caused the cover reduction of these sciaphylic species. The negative trends in epiphytes have two main effects at the ecosystem level: a reduction in available food and carbon sources, from grazers to decompositors, and a decrease in particulate carbonates derived from animal skeletons (bryozoa) and encrusting algae. The amount of grazing by S. salpa, P. lividus and isopods showed long-term, 7 years, oscillations, but trends were not homogeneous among stations. The three grazers were not related to food (epiphytes) availability (Peirano et al., 2001) and climate parameters could explain the observed variability only partially; some other variables such as grazer seasonality and leaf palatability probably contribute to these oscillations (Peirano et al., 2001; Tomas et al., 2005). Medium and long-term analyses of climate effects on P. oceanica meadows suggest that some parameters considered in this study (LL, LBP, UL) are not suitable for long-term monitoring. These parameters varied in response to local effects; for example the frequency of rough sea, depth and the different morphology of the meadow, would influence the three parameters confounding long time patterns. Hence, the use of some indices, such as the leaf area index (LAI), which combines different parameters (leaf length, leaf width, number of leaf shoot−1 and shoot density) having different cycles and trends, would probably complicate long-term analyses. Variability in epiphyte and grazers communities induced by seasonal and decadal climate changes could result in cascading effects throughout the complex trophic web of P. oceanica with impacts on the coastal Mediterranean ecosystems similar to those recorded in other northern marine environments. Sydeman and Bograd (2009) showed how differences in phenology, in term of timing of biomass, may shorten the period of prey-food availability for consumers with consequences at reproductive level and other demographic traits. Peirano et al. (2001) found that herbivores preferred adult leaves with more epiphytes and higher N contents throughout the year. Prado et al. (2007) found that the largest part (25%) of the variability in P. oceanica epiphytic species composition may be explained by grazing pressure. Hence, a decrease of epiphytes could have two linked effects: a decrease of herbivores, which in turn may decrease the biodiversity of epiphytic community. Although present data are too limited for forecasting analysis, the general, positive trends in nearly all meadow and plant parameters, confirms findings by Peirano et al. (2005a) which described through lepidochronology a positive increase of P. oceanica growth in shallow waters, comparable to the increase in terrestrial plant

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growth observed in the Mediterranean region and in the Northern hemisphere (Myneni et al., 1997; Gordo and Sanz, 2009). Principal Component Analysis and stepwise regressions showed the possible links of P. oceanica growth with Northern Hemisphere weather. Encrusting algae (EA), E. posidoniae (EP) and shoot density (D) could be influenced by winter anomalies related to strong, positive NAO that often cause below-average temperatures and below-average precipitation over southern and central Europe. Two questions arise from the results of this study: (a) is the positive trend in growth of P. oceanica also influenced by the CO2 rise in seawater?; (b) could the decrease of epiphytic carbonate organisms, mainly bryozoa and calcareous algae, be related to a changing equilibrium in seawater carbonates? There are no available longterm data on CO2 seawater concentrations in the Mediterranean Sea to allow answering these questions. However, observed significant reduction of encrusting algae on P. oceanica leaves are in agreement with laboratory experiments by Martin et al. (2008) who showed significant reductions in encrusting algal cover related to the acidification of seawater, as an effect of increased CO2 concentrations. Medium and long-term cycles discourage the interpretation of trends based on data collected over only few years and stress the importance of implementing long-term series on P. oceanica meadows for the entire Mediterranean system. Findings on the state of health of Mediterranean P. oceanica meadows are different for meadows subjected to anthropogenic stress compared to those in MPAs. Diaz-Almela et al. (2007) showed that meadows along the Western Spanish coasts are regressing due both to anthropogenic pressure and climate change. On the contrary, González-Correa et al. (2007) found that P. oceanica rhizomes in six Marine Protected Areas in the Mediterranean (Spain included) below 10 m depth, did not show any differences in growth or any sign of sufferance. As our data demonstrated long time-series of selected parameters as SPC, D, LW, would be useful to monitor the impacts of climate change on P. oceanica meadows if monitored at least in two seasons per year, in our case in December and June. However, a more complete monitoring of plant, epiphytes (EA and Ep) and climate parameters should include at least four seasons. In the case of lepidochronology four seasons are the minimum period required to provide relevant results (Pergent and Pergent-Martini, 1991). Acknowledgements We thank J. Vermaat and two anonymous reviewers whose suggestions greatly improved the manuscript. A special thanks to M. Morgigni (ENEA) and the crew of Submariner S.N.C. of La Spezia for their help with field work. M. Biso, P. Di Nitto, M. Burgassi, S. La Rocca, A. Maggiani, G. Sorrentino helped in the laboratory. The Direction of AMP “Cinque Terre” is also thanked for the permission to work in the area. For C.N. Bianchi and C. Morri, research on biodiversity and climate change falls within the scope of the project ‘The impacts of biological invasions and climate change on the biodiversity of the Mediterranean Sea’ (Italy-Israel Cooperation, funded by the Italian Ministry for the Environment). References Abbate, M., Peirano, A., Ugolini, U., 2000. Structural changes in Posidonia oceanica leaves along the coast of Liguria (Italy): response to environmental stress? Biol. Mar. Mediterr. 7, 320–323. Alcamo, J., Moreno, J.M., Nováky, B., Bindi, M., Corobov, R., Devoy, R.J.N., Giannakopoulos, C., Martin, E., Olesen, J.E., Shvidenko, A., 2007. Europe. In: Parry, M.L., Canziani, O.F., Palutikof, J.P., van der Linden, P.J., Hanson, C.E. (Eds.), Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK, pp. 541–580. Alcoverro, T., Duarte, C.M., Romero, J., 1995. Annual growth dynamics of Posidonia oceanica: contribution of large-scale versus local factors to seasonality. Mar. Ecol. Progr. Ser. 120, 203–210.

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