Changes of Zooplankton Communities in the Gulf of Tigullio (Ligurian Sea, Western Mediterranean) from 1985 to 1995

Journal of Plankton Research Vol.22 no.12 pp.2225–2253, 2000 Changes of zooplankton communities in the Gulf of Tigullio (Ligurian Sea, Western Mediterranean) from 1985 to 1995. Influence of hydroclimatic factors Priscilla Licandro and Frédéric Ibanez1 Dipartimento per lo studio del Territorio e delle sue Risorse, Università di Genova, Corso Europa, 26, 16132 Genova, Italy and 1Laboratoire d’Océanographie Biologique et Ecologie du Plancton Marin, ESA 7076, BP 28, 06230 Villefranche-sur-mer, France Abstract. Year-to-year variations in abundance and composition of zooplankton were studied in the Ligurian Sea at a station sampled two times a month between 1985 and 1995. As a break of 2 years (April 1989–December 1990) occurred in the time series, the STATIS method was chosen instead of time series analysis. Each of the nine sampled years was a single table of monthly or seasonal average densities of 26 plankton taxa. STATIS allowed (i) estimation of similarity between each yearly table, (ii) visualization of the trajectories of both species and observations (seasons) from one year to another, and (iii) associations of particular species, which showed similar temporal variations, to be determined. A strong seasonal variation was evident for most species, and years 1987, 1992 and 1994 were different from the others. Trajectories indicated which species were stable and which were characterized by small or large fluctuations during the nine years. Five different taxa associations were detected. For each association, the most representative period was identified, where each period was a group of months obtained by clustering on species abundances. Taking into account hydro-climatic factors in the representative periods, a contingency discriminant analysis allowed us to identify and characterize the most discriminant environmental parameters associated with each group of species. Environmental factors that best discriminated the different representative periods were atmospheric pressure, current speed and direction, and water temperature. Introduction Numerous long-term studies carried out in the Atlantic and the Pacific have clearly shown the influence of hydroclimatic factors on plankton year-to-year variability [(McGowan, 1990) for a review; (Fromentin and Ibanez, 1994; Mullin, 1994; Le Fèvre-Lehoërff et al., 1995; Fromentin and Planque, 1996)]. However, similar studies in the Mediterranean Sea are somewhat rare because of the lack of zooplankton long-term datasets (Pucher-Petković et al., 1971; Goy et al., 1989; Ménard et al., 1994, 1997; Cataletto et al., 1995; Šolić et al., 1997). Relationships between climate and water circulation in the Western Mediter- ranean Sea have been detected over the last decade. This has led to identification of climatic parameters that influence hydrography in this region. Meteorological factors have been shown to involve oscillations of sea-water level (Vilibić and Leder, 1996) or variations in sea surface-water properties (Grbec, 1997). Seasonal and year-to-year variability of dominant forcing factors (e.g. atmospheric pressure, winds) may also have induced variations in flow and circulation dynamics (La Violette, 1995). Year-to-year variability of mesozooplankton was analysed at a pilot station over the eastern Ligurian Continental Shelf between 1985 and 1995. The goal was to examine relationships between hydroclimatic factors and zooplankton at the © Oxford University Press 2000 2225 P.Licandro and F.Ibanez interannual scale. A break of about two years (April 1989–December 1990) in the sampling collection prevented the use of time series analyses which require regular sampling intervals. Instead, the multivariate method STATIS (Robert and Escoufier, 1976) was used to compare changes between the nine sampled years. The basic questions were: what are the main patterns of variation of species during the nine years; are changes in mesozooplankton communities more sensi- tive to year-to-year or to seasonal environmental variations; what is the latent hierarchy between climatic forcing and hydrography on abundance and composition of zooplankton? Method Study site The Gulf of Tigullio is located along the Italian coast of the Ligurian Sea, 40 km east of Genoa (Figure 1). The Ligurian Current principally drives the water mass circulation within the gulf westwards. However, inversion in the direction of this current seasonally occurs in the upper layers (Bossolasco and Dagnino, 1957; Hela, 1963). The wind mainly blows southwards while SSE winds stronger than 10 km h–1 are considered responsible for storms (Papa, 1984). Previous studies on the productivity of coastal waters in the Ligurian Sea (Albertelli et al., 1982) showed that the pilot zone (including the sampling station ‘C’) in the Gulf of Tigullio may be considered as representative of the whole Ligurian coast with respect to hydrology and nutrients (Fabiano, 1984; Albertelli et al., 1994), particulate matter and planktonic biomasses (Fabiano et al., 1984; Zunini Sertorio et al., 1985; Fabiano and Zunini Sertorio, 1993). Fig. 1. Study area in the Gulf of Tigullio, on the Ligurian coast 40 km east of Genoa (Ligurian Sea). At the sampling station C (09°16ЈE, 44°17ЈN), zooplankton was collected twice a month from March 1985 to March 1989 and from January 1991 to December 1995. Bathymetry of the coast is also indicated. 2226 Zooplankton in the Gulf of Tigullio Sampling Zooplankton samples were collected between March 1985 and March 1989, and between January 1991 and December 1995, at station C (Figure 1). This is a coastal station (maximum depth of 80 m) not far from the harbour of Chiavari and the estuary of the river Entella. Twice a month, a Bongo sampler with two nets of 335 µm mesh size (90 cm long, with a 20 cm mouth diameter) was hauled obliquely at approximately 1 knot speed from west to east throughout a 60 m water column. A ‘General Oceanic’ flowmeter model 2030 inside the mouth measured the volume of water filtered. Two simultaneous samples were obtained between 10:00 and 15:00 h. Zooplankton samples were preserved in 4% buffered formalin seawater. Data records Hydrological and meteorological parameters. Temperature was measured in the water column by a bathythermograph (Model Belfort OC1) until July 1993, and thereafter by an electronic probe (Sea Bird Electronics Seacat 19–03). Only surface sampling for salinity measurements was carried out from March 1985 to March 1986. Salinity sampling was carried out throughout the water column from September 1987 onwards. Salinity measurements were made on water samples in the laboratory according to Strickland and Parsons (Strickland and Parsons, 1968), by a Salinometer Aanderaa-Model 3012-Sensor 2975 and by an electronic probe after July 1993. Water transparency was evaluated with a Secchi disk. Currents were measured from March 1987 between 09:00 and 15:00 h, at 8 min intervals for 4 h 50 min, at 5 m, 45 m and 75 m, using three current meters (Model SD 2000 Sensordata, Bergen) fixed near the bottom. The ‘East-West component’ of the currents at the three depths was estimated by the variable [␣ sin(␤)], where ␤ is the most frequent current direction of the day (degrees) and ␣ its daily average speed (cm s–1). Positive values of this function indicate current eastwards while negative values correspond to westward current. Several meteorological parameters were considered during the whole sampling period (Meteoclimatic Observatory of Chiavari): atmospheric pressure, air temperature, precipitation (monthly sum), sky cover and number of monthly days with N and SE winds stronger than 10 km h–1. Biological descriptors. Only the most abundant mesozooplanktonic taxa of the Gulf of Tigullio were considered, according to previous studies in this area (Bogli- olo et al., 1979). Thirty-one species and nine genera of medusae, siphonophores, ctenophores, cladocerans, copepods, chaetognaths, appendicularians and thali- acea were counted in a total of 213 collected samples. The copepod genus Clauso- calanus was classified in three size classes, A, B and C, according to decreasing size (Boucher et al., 1987). Zooplankton was counted in a fraction of the total sample where at least 40 individuals for each category could be identified. The total number in each sample was normalized per cubic meter. Two different tables of zooplankton densities were built, one with the monthly 2227 P.Licandro and F.Ibanez average and one with the seasonal average. Seasonal abundances were arbitrarily estimated averaging the following months: January, February and March for winter; April, May and June for spring; July, August and September for summer; October, November and December for autumn. Numerical methods Figure 2 shows the successive steps of the numerical procedure. 1. Biological variables Step 1 – Selection of representative species. The first step was to select among the 40 zooplankton categories considered (31 species and nine genera) the most Fig. 2. Summary of the numerical procedures computed in the present study. 2228 Zooplankton in the Gulf of Tigullio representative for the following numerical analysis. Percentages of null values (from 0 to 99%) were plotted against number of species (from 1 to 40). A change in the slope of the curve separated most abundant species (with a percentage of zeros below the curvature point) from the rarest ones (Ibanez et al., 1993). Following this procedure, 26 dominant species or genera, below the slope, were selected. Step 2 – Tables of data. Tables with the seasonal and monthly abundance of the 26 selected species were built for each year. The abundance was then log- transformed. Step 3 – STATIS. The nine annual tables were compared using the STATIS method (L’Hermier des Plantes, 1976; Robert and Escoufier, 1976; Lavit, 1988; Lavit et al., 1994; Dazy et al., 1996). STATIS had already been used in ecology to study diversity of benthic macrofauna in different stations in a French Lagoon (Amanieu et al., 1981) and spatial structures of demersal fish species (Gaertner et al., 1998). STATIS enables tables having at least one common dimension (e.g. a constant number of observations or a constant number of descriptors) to be analysed.

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