Phytoplankton response to climatic and anthropogenic influences in the north-eastern Adriatic during the last four decades

Estuarine, Coastal and Shelf Science 115 (2012) 98e112

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Phytoplankton response to climatic and anthropogenic influences in the north-eastern Adriatic during the last four decades Daniela Mari
c*, Romina Kraus, Jelena Godrijan, Nastjenjka Supi
c, Tamara Djakovac, Robert Precali Center for Marine Research, Rudjer Boskovi
c Institute, G. Paliaga 5, 52210 Rovinj, Croatia

a r t i c l e i n f o

a b s t r a c t

Article history: Received 5 July 2011 Accepted 7 February 2012 Available online 13 February 2012

A significantly lower Po River outflow in the 2000e2009 period, and altered circulation, was accompanied by a change in salinity and nutrient budget of the entire northern Adriatic. A four-decadal data set was analysed to gain a better perspective of phytoplankton driving pressures in the northern Adriatic. An observed regime shift in the system had altered the phytoplankton abundance, community composition and seasonal cycle. Appearance and frequency alterations of some prominent taxa (e.g. Pseudo-nitzschia delicatissima group and Pseudo-nitzschia seriata group) were detected. The identified changes highlight the importance of long-term observations for the understanding of the natural temporal variability in phytoplankton communities. We presume that such shifts in the community composition and abundance reflect on the entire Adriatic. Ó 2012 Elsevier Ltd. All rights reserved.

Keywords: phytoplankton abundance fluctuations phytoplankton seasonality phytoplankton diversity circulation pattern nutrients northern Adriatic Sea

1. Introduction Phytoplankton plays a central role in the health and productivity of marine ecosystems, in addition to being considered a sensitive indicator of speed and severity of global climate change (Widdicombe et al., 2010). Cloern and Jassby (2010) proposed the hypothesis that year-to-year variability of phytoplankton is a response to anthropogenic activities or shifts in the climate system. Phytoplankton in the eastern northern Adriatic (NA) was related to the Po River outflow and atmospheric forcing (Revelante and Gilmartin, 1976; Vili ci
c et al., 2009). Recently, the circulation regime was identified as a major driver of long-term phytoplankton variations (Kraus and Supi
c, 2011). Even though species succession and phytoplankton dynamics along the NA eastern coast have already been described (Vilici
c et al., 2009; Godrijan et al., 2010; Mari
c et al., 2010), there are still many open questions about long-term phytoplankton dynamics in the eastern NA. In particular, the main driving pressures and processes that play a key role in phytoplankton fluctuations have to be elucidated. Long-term observations, spanning several decades, help us to distinguish between regular, recurrent patterns and occasional and exceptional events (Ribera d’Alcalà et al., 2004).

* Corresponding author. E-mail address: [email protected] (D. Mari
c). 0272-7714/$ e see front matter Ó 2012 Elsevier Ltd. All rights reserved. doi:10.1016/j.ecss.2012.02.003

The aim of this study was to determine whether the observed regime shift in the NA reflected on qualitative and/or quantitative changes of the phytoplankton community. In addition, we have also focused on detecting and explaining the triggering factors of the changes which have occurred to the NA phytoplankton. 2. Study area The Adriatic is a land locked sea, located in the northernmost part of the Mediterranean basin. Regarding bathymetry and latitude it can be divided in three distinct sections: the northern, central and southern part. The NA is characterized by shallow water (up to 50 m) under the influence of oligotrophic central Adriatic waters or fresh waters from the Po River. Our research was concentrated on two stations in the north-eastern part of the Adriatic, close to the Istrian coast (Fig. 1). An important feature of the Adriatic circulation is the cyclonic surface flow, with the East Adriatic Current (EAC) bringing warmer and highly saline waters from the Ionian Sea with compensation of the volume flux by the less saline Western Adriatic Current (WAC) waters along the western shelf. The latter transports nutrient rich waters towards the central and southern Adriatic (Zore, 1956; Vilibi
c et al., 2009). The northernmost part (north of the Kamenjak Cape-Rimini line) is included in this Adriatic-wide circulation system during the winter period while an anticyclonic gyre becomes established in the region during spring and summer and extending between the Po River delta and Istria (Fig. 1). A strong current, the Istrian Coastal Counter Current (ICCC), of southward

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Fig. 1. Map of the studied area and sampling stations.

direction in the Istrian coastal zone, indicates that the gyre is well developed (Supi
c et al., 2000; Krajcar, 2003). The anticyclonic circulation system usually brings waters from the Po River mouth towards the eastern coast. However, significant year-to-year changes in the NA circulation with variations of these typical seasonal patterns were observed (e.g. Supi
c et al., 2012). The circulation changes are driven by meteorological conditions (Kuzmi
c et al., 2007; Supi
c et al., 2012). Depending on prevailing circulation patterns, and not only on the intensity of the Po river discharge rate, the impact of oligotrophic waters from the central Adriatic (indicated by EAC) or freshened waters of Po River origin (indicated by ICCC) on the NA drastically changes from year to year and from season to season. 3. Materials and methods 3.1. Water sampling Sampling was performed mostly monthly at two stations in the NA, 1 and 13 nautical miles off the western Istria coast (RV001 and SJ107 respectively), from 1972 until 2009 (Fig. 1). In the years

1974e1976, 1979 and 1985e1987 at both stations sampling was irregular and data were collected seasonally (details about sampling frequency are listed in the supplementary Table 1A, B). Water samples were collected with 5 L Van Dorn/Niskin bottles at the surface, 5, 10, 20 m and at the bottom. A total of 2422 phytoplankton samples were analysed during the study period (931 on RV001 and 1491 on SJ107). In this paper mostly surface data were used since phytoplankton from the upper layer has a more pronounced impact on the seasonal changes than those one in deeper ones (Kraus and Supi
c, 2011). 3.2. Analysis of environmental parameters Temperature was measured by protected reversing thermometers (Richter and Wiese, Berlin, Germany, precision
0.1  C) and salinity with high precision laboratory salinometers (
0.01). Determination of salinity was performed with a YEO-KAL 601Mk1V until May 2008, and afterwards with RBR Precision Instruments Microsalinometer-310. Nutrient concentrations (dissolved inorganic nitrogen e DIN as the sum of nitrate e NO3, nitrite e NO2 and ammonium e NH4,

100

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orthophosphate e PO4 and orthosilicate e SiO4) were analysed aboard immediately after sample collection by spectrophotometric methods widely used in oceanography (Ivan ci
c and Degobbis, 1984; Parsons et al., 1984) on Cecil CE 2040 spectrophotometer until the end of 2004 and with a Shimadzu UV-1800 model afterwards. The method accuracies for NO3, NO2, NH4, PO4, and SiO4 were
3%,
3%,
5%,
3%, and
6%, respectively, and detection limits were 0.05 mmol L1, 0.01 mmol L1, 0.1 mmol L1, 0.02 mmol L1, and 0.05 mmol L1, respectively. The calibrations were carried out following Strickland and Parsons (1972). The intensity of the northern component of the surface geostrophic current between SJ107 and RV001 was calculated from temperature and salinity values collected during oceanographic cruises in February, March, May and October (1972e2009) by means of a standard dynamical method described in Supi
c et al. (2000). 3.3. Phytoplankton analysis Water samples for phytoplankton analysis were filtrated through a 300 mm mesh plankton net immediately after collection. Subsamples of 200 ml were preserved with Lugol’s solution buffered with sodium acetate (2% final concentration) and stored in cool, dark conditions until analysis (Throndsen, 1978). Samples were gently homogenized before settling and variable volumes of samples, depending on the cell abundance (5e100 ml, predominantly 50 ml), were sedimented for 24e72 h. Samples were analysed under an inverted microscope (Invertoskop D, Zeiss, Oberkochen, Germany) following the Utermöhl’s (1958) technique. Cells were counted in random fields under a magnification of 400 and 200. Cells longer than 20 mm were designated to the microphytoplankton fraction and cells ranging from 2 to 20 mm to the nanoplankton fraction (Sieburth et al., 1978). Phytoplankton determination was performed to the species level whenever possible, following the literature species descriptions. Over the investigated period, numerous changes in taxonomy had occurred, hence before starting any biodiversity analyses, we updated the species list. For example, in this paper Skeletonema marinoi is shown to be present in the NA since 1972, as proved with molecular and electron microscopic analyses, although had been formerly identified as Skeletonema costatum (unpublished results). In addition, we emphasise that all microscopic analyses were performed by the same person thus enabling us to have a unique data set of constant quality. 3.4. Data and statistical analysis A cumulative sum chart for salinity was made with the aim of detecting major changes in the system. Average monthly mean on an annual base was used as the mean tendency estimator to build the cumulative sum chart. Continuous downward or upward direction of the cumulative line denotes persistently higher or lower values from the average, calculated upon the entire data set. For visualizing long-term changes of phytoplankton functional groups (total phytoplankton, diatoms, dinoflagellates, micro- and nanoplankton) basic statistical analysis was performed using Systat 12 software (Systat Software, Inc.). Values of each parameter were estimated for each month in the period 1972e2009, or by averaging data sampled within the month, or by using the average 1972e2009 monthly value when no sampling was performed. Seasonal cycles of each functional group in the two selected periods (1972e1999 and 2000e2009) were then computed and compared on the basis of a monthly mean, standard deviation and median values.

3.5. Regime shift To test the regime shift hypothesis we have used a parametric method based on sequential t-test analysis of regime shifts (STARS), developed by Rodionov (2004) and modified by Rodionov and Overland (2005). The software detects statistically significant shifts in the mean level and magnitude of fluctuations of the time series. A shift occurs when a significant difference exists between the variable mean value before and after a certain point. For this analysis we used the calculated interpolated means. In the STARS the time scale to be detected is controlled primarily by the cut-off length, which is similar to the cut-off point in low-pass filtering, and determines the minimum length of the regimes for which the magnitude of the shifts remains intact. A longer cut-off length hence identifies the strongest signal, as opposed to many smaller events. Here we used a medium cut-off length (10 years), to identify noteworthy changes in the data set for all analysed groups with a probability level equal to 0.02. 3.6. Principal component analysis Principal component analysis (PCA) was applied to determine the influence of main environmental factors on phytoplankton. The factors involved in the analysis were: surface abundance of diatoms (Diato), dinoflagellates (Dino) and nanoplankton (Nano), salinity (Sal), temperature (T), and concentrations of dissolved inorganic nitrogen (DIN), orthophosphate (PO4) and orthosilicate (SiO4) at stations RV001 and SJ107, as well as the intensity of the northern component of the geostrophic current between SJ107 and RV001 (Curr). PCA was performed with logarithmic values of biological parameters and nutrients in order to diminish the impact of extremely high or low values on correlations between parameters. The analysis was performed only for some months (February, March, May and October) as these were the months in which the largest discrepancies in phytoplankton abundances between the two investigated periods, i.e. the 1972e1999 and 2000e2009, were observed. Cruises for which the data set was incomplete (one or more parameters missing) were omitted from the analysis. PCA was performed with the statistical package Primer 6 (PRIMER-E, Plymouth, UK). 3.7. Community composition In analysis of species composition, the most prominent species were distinguished on the basis of frequency of appearance (>15%). To detect changes in species composition between the first and second period frequencies of appearance of each species were compared. 3.8. Diversity indices Both Margalef species richness (Margalef, 1951) and ShannoneWiener (H0 ) diversity index (Shannon, 1948) were considered in order to reveal changes in community structure. Indices were calculated in the software Primer 6 (PRIMER-E, Plymouth, UK) on transformed data (log Xþ1). 4. Results 4.1. Determination of periods A cumulative sum chart for salinity (Fig. 2) shows that from the early seventies, salinity values were continuously lower than the forty-year-average, followed by steady higher values after the year 2000 and coinciding with a lower Po River outflow (Fig. 3). With

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year 2000. Mean abundances of total phytoplankton (Fig. 4A) show an upward shift in 1988 and a downward one in 1995 with abundances decreasing until 2000. Diatoms (Fig. 4B) show an upward shift in 1990 and a downward one in 1996, while dinoflagellates (Fig. 4C) show no shift, though the data does indicate a slight reduction after 1992. Microplankton (Fig. 4D) follows the diatom shift, while nanoplankton (Fig. 4E) shows an upward one in 1987 and a strong downward shift in 1994. Total phytoplankton abundances at station SJ107 (Fig. 4F) show several upward shifts between 1980 and 1990, and a downward one in 2000. Diatoms (Fig. 4G) show an upward shift in 1990 and a downward one in 2000. Dinoflagellates (Fig. 4H) again show no shift. Microplankton (Fig. 4I) show the same shift as diatoms. Nanoplankton (Fig. 4J) shows a strong upward shift in 1982 and a strong downward one in 1994 (proceeding the upward shift of diatoms) and in 2000. 4.3. Phytoplankton coupled with environmental parameters

Fig. 2. Distribution of cumulative salinity data over the investigated period. Cumulative distribution was calculated as differences between each data entry and a monthly mean derived from the entire investigated period. Real salinity values over the study period with the trend lines on the second axes.

respect to salinity changes noted in the region, two main periods were established: 1972e1999 and 2000e2009. Consequently, most of the analyses and graphical representations of the data are based on these two periods. A more elaborate analysis of oceanographic parameters of this data set is presented in Djakovac et al. (2012). An overview and basic statistics for the considered data set for the two stations RV001 and SJ107 and for the two periods are given in Table 1. 4.2. Phytoplankton shifts Regime shift analysis on phytoplankton abundance indicated changes in accordance with the regime shift in salinity around the

The results of PCA are presented in Table 2 and Supplementary Table 2. PC1 at SJ107 was in all cases driven by salinity variations, which were usually combined with current and/or nutrient variations. The situation was more complex at RV001 where PC1 was driven by temperature, salinity or nutrients or by the combination of all three. PC2 was mostly, and at both stations, related to variations in concentration of SiO4. Large phytoplankton abundances at both stations generally occurred at low salinity values. In March and October high phytoplankton abundances at SJ107 were related to high DIN concentrations, while those at RV001 were correlated to PO4 concentrations. The southwards surface geostrophic current (indicating an anticyclonic gyre and ICCC) between SJ107 and RV001 was more often related to high phytoplankton blooms at SJ107 than at RV001. While temperature was occasionally correlated, SiO4 was mainly unrelated to phytoplankton abundances in the studied months. Associations of high total phytoplankton abundances and PO4 were present in some months: diatoms at SJ107 (February) and at RV001 (March and October), dinoflagellates at SJ107 (October) and at RV001 (March and October), and nanoplankton at SJ107 (October) and RV001 (May and October). Associations of total phytoplankton abundances and DIN were present in other months: diatoms at SJ107 (March, May and October), dinoflagellates at SJ107 (March) and at RV001 (October), nanoplankton at SJ107 (March and October) and at RV001 (October). Correlations in several cases with low DIN (diatoms at RV001 in May, dinoflagellates at SJ107 in February and nanoplankton at SJ107 in February and March) and in three cases with both high DIN and PO4 dinoflagellates at RV001 (October), and nanoplankton at both stations (October) were observed. 4.4. Shifts in the seasonality of phytoplankton groups

Fig. 3. Yearly average of the Po River flow (Qave) during the investigated period (1972e2009).

4.4.1. Total phytoplankton Compared to the second period, significantly higher total phytoplankton abundances at both stations were noted in the first one (Fig. 6). A shift in the seasonality of blooms has been recorded as well. In the first period, the highest abundances at RV001 (Fig. 6A) occurred from April to July and were followed by a second maximum in October. The maximum in the first period occurred in May 1991 (33.3  106 cells L1; z ¼ 27 m; S ¼ 37.99; t ¼ 13.41  C). In the second period, the highest abundances were recorded from March to April, and in October. The maximum occurred in August 2008 (1.66  106 cells L1; z ¼ 0 m; S ¼ 36.47; t ¼ 25.21  C). In the first period at SJ107 (Fig. 6B), high abundances were documented in May, August and October. A maximum

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Table 1 Mean statistics for hydro-chemical variables and phytoplankton abundances (total phytoplankton, diatoms, dinoflagellates, microplankton and nanoplankton abundances) over the two sampling periods (1972e1999 and 2000e2009). A) Station RV001; B) station SJ107.

A) RV001 Period 1972e1999

Period 2000e2009

B) SJ107 Period 1972e1999

Period 2000e2009

Temperature Salinity Density PO4 NO3 NO2 NH4 DIN SiO4 Tot Phytoplankton Diatoms Dinoflagellates Microplankton Nanoplankton Temperature Salinity Density PO4 NO3 NO2 NH4 DIN SiO4 Tot Phytoplankton Diatoms Dinoflagellates Microplankton Nanoplankton

Temperature Salinity Density PO4 NO3 NO2 NH4 DIN SiO4 Tot Phytoplankton Diatoms Dinoflagellates Microplankton Nanoplankton Temperature Salinity Density PO4 NO3 NO2 NH4 DIN SiO4 Tot Phytoplankton Diatoms Dinoflagellates Microplankton Nanoplankton



C

kg m3

mmol L1 mmol L1 mmol L1 mmol L1 mmol L1 mmol L1

cells L1 cells L1 cells L1 cells L1 cells L1 

C

kg m3

mmol L1 mmol L1 mmol L1 mmol L1 mmol L1 mmol L1

cells L1 cells L1 cells L1 cells L1 cells L1



C

kg m3

mmol L1 mmol L1 mmol L1 mmol L1 mmol L1 mmol L1

cells L1 cells L1 cells L1 cells L1 cells L1 

C

kg m3

mmol L1 mmol L1 mmol L1 mmol L1 mmol L1 mmol L1

cells L1 cells L1 cells L1 cells L1 cells L1

N

Min

Max

Range

Avg

SD

561 562 561 546 550 550 534 534 544 562 559 473 562 557

7.93 31.15 21.69
26.98 38.86 29.96 0.30 5.65 1.22 10.34 11.10 19.49 33.3  106 7.8  106 62.9  103 7.8  106 33.1  106

19.05 7.71 8.27 0.30 5.65 1.22 10.34 11.07 19.49 33.3  106 7.8  106 62.8  103 7.81  106 33.1  106

16.29 37.43 27.46 0.03 0.59 0.19 0.48 1.27 3.47 1.6  106 0.16  106 2.8  103 0.16  106 1.4  106

4.59 0.98 1.59 0.04 0.65 0.24 0.69 1.09 2.91 2.31  106 0.49  106 5.68  103 0.49  106 2.18  106

368 365 365 368 368 368 368 368 368 368 368 290 368 367

8.17 34.42 23.12
26.73 38.46 29.81 0.25 8.20 3.04 3.50 8.93 13.49 1.66  106 1.4  106 28  103 1.4  106 1.5  106

18.56 4.04 6.69 0.25 8.13 3.03 3.50 8.75 13.41 1.65  106 1.4  106 27.9  103 1.39  106 1.49  106

16.92 37.80 27.58 0.02 0.94 0.23 0.32 1.49 2.68 0.33  106 0.07  106 2  103 0.07  106 0.26  106

5.08 0.53 1.47 0.03 0.89 0.31 0.34 1.14 1.86 0.27  106 0.14  106 2.97  103 0.14  106 0.23  106

895 895 893 891 880 886 885 875 890 897 888 711 897 892

7.03 28.98 19.74
27.8 38.77 30.02 0.59 7.54 3.74 3.28 8.99 31.59 22.3  106 19.8  106 128  103 19.8  106 8.96  106

20.77 9.79 10.28 0.59 7.54 3.74 3.28 8.97 31.59 22.2  106 19.8  106 128  103 19.8  106 8.95  106

15.95 37.40 27.51 0.03 0.72 0.26 0.45 1.43 4.52 1.24  106 0.17  106 3.56  103 0.17  106 1.07  106

5.07 1.23 1.88 0.05 0.89 0.40 0.53 1.22 4.58 1.60  106 0.89  106 8.52  103 0.88  106 1.24  106

592 587 587 592 592 592 590 590 592 592 591 440 592 590

6.97 32.69 21.41
27.84 38.66 29.73 0.29 12.67 4.20 3.19 13.67 26.75 7.12  106 6.97  106 586  103 6.98  106 5.63  106

20.87 5.97 8.32 0.29 12.63 4.19 3.19 13.50 26.75 7.11  106 6.97  106 586  103 6.98  106 5.62  106

16.75 37.62 27.48 0.03 1.05 0.25 0.35 1.65 2.89 0.035  106 0.12  106 3.70  103 0.012  106 0.023  106

5.25 0.96 1.78 0.04 1.21 0.33 0.45 1.49 3.08 0.51  106 0.36  106 28.1  103 0.37  106 0.34  106

Abbreviations: Number of samples (N), minimum abundance (Min), maximum abundance (Max), range from min to max (Range), average abundance (Avg) and standard deviation (SD),
was reached during October 1993 in the surface layer (22.3  106 cells L1; S ¼ 28.98; t ¼ 19.35  C). There was a shift in seasonality of the total phytoplankton abundances in the second investigated period (2000e2009) at station SJ107 (Fig. 6B). The highest abundances were recorded in February, May and SeptembereOctober. The spring maximum was recorded in February 2004 (7.12  106 cells L1; S ¼ 33.55; t ¼ 6.97  C), and the

autumn one in October 2009 (5.72  106 cells L1; S ¼ 34.10; t ¼ 23.11  C). 4.4.2. Diatoms RV001 was characterized by significantly higher abundances in the first period than in the second one (Figs. 5 and 6) and a shift in seasonality of the blooms was observed. In the first period, blooms

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Fig. 4. Shifts in the mean total phytoplankton abundance at stations RV001 (AeE) and SJ107 (FeI). (A, F), diatoms (B, G), dinoflagellates (C, H), microplankton (D, I) and nanoplankton (E, J), 1972e2009. The stepwise function (solid blue line) characterises regime shifts in the level of fluctuation of the means, the cut-off length is 10 years, probability p ¼ 0.2, Huber weight function of 1. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

occurred in March, May and October, while in the second one there was no evidence of an early spring bloom, only increased abundances occurred in July and October (Fig. 6A). The maximum of the first period was documented in October 1993 (7.80  106 cells L1; z ¼ 0 m; S ¼ 31.22; t ¼ 18.88  C), and of the second one in July 2004 (z ¼ 0e10 m; 1.40  106 cells L1; S ¼ 36.66; t ¼ 24.60  C).

During the first period, SJ107 was characterized by blooms in March, June and October (Fig. 6B) and a maximum during the autumn bloom of 1993 (z ¼ 0e10 m; 19.8  106 cells L1; S ¼ 28.98; t ¼ 19.35  C). Lower overall abundances were recorded in the second period. A prominent February bloom was recorded in 2004 (6.96  106 cells L1 in the surface layer; S ¼ 33.55;

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Table 2 Part of the total variance explained by PC1 or PC2 (%V) and several most important parameters driving PC1 and PC2 with their coefficient ranges at stations RV001 and SJ107. Values are given for analysed months (February, March, May and October) for Diatoms (Diato), Dinoflagellates (Dino) and Nanoplankton (Nano). Parameters concerned are salinity (Sal), temperature (T), dissolved inorganic nitrogen (DIN), orthophosphate (PO4), orthosilicate (SiO4) and geostrophic current intensity (Curr). Negative coefficients are marked with prefix ().

Feb

Mar

PC1-RV001

PC2-RV001

%V

%V

Coefficients

PC1-SJ107

Coefficients

%V

Coefficients

%V

Coefficients

55.8 Sal, T, Curr, PO4, Diato (0.4)

18.9 SiO4, DIN (0.6e0.8)

Dino 26.2 Sal, Curr, Dino (0.3e0.7) Nano 29.3 Sal, Nano, Curr (0.5e0.6)

24.7 Sal, PO4, Curr, SiO4, DIN (0.4e0.5) 23.1 T, PO4, DIN, SiO4 (0.4e0.6) 22.5 T, PO4, DIN (0.4e0.7)

51.0 Curr, Sal, T, PO4 (0.4) 47.2 Sal, Curr, T, PO4 (0.4e0.5)

21.8 SiO4, DIN, Dino (0.4e0.7) 20.0 SiO4, Nano, DIN (0.4e0.8)

Diato 29.9 Diato, PO4 (0.5e0.6) Dino 28.4 Dino, Sal, PO4 (0.4e0.6) Nano 25.7 DIN, Curr, Nano (0.4e0.6)

23.1 SiO4, DIN, Curr, Sal (0.3e0.6) 23.8 DIN, Curr, SiO4 (0.5e0.6) 21.8 SiO4, PO4, Sal (0.4e0.6)

41.7 Sal, DIN, Diato (0.5) 39.8 DIN, Sal, T, Dino (0.4e0.5) 38.6 DIN, Sal, T, Nano (0.4e0.5)

28.4 SiO4, PO4, T (0.4e0.6) 25.1 PO4, SiO4, Curr (0.5e0.6) 25.0 PO4, SiO4, Curr (0.5)

Diato 31.2 Diato (0.6)

May Diato 32.4 T, DIN, Diato (0.5e0.6) 25.0 SiO4, Curr, PO4 (0.5e0.6) 32.6 Sal, Curr, PO4 (0.5e0.6) 26.0 SiO4, Curr, Sal, Dino (0.4e0.6) 42.3 Sal, Dino, Curr (0.4e0.5) Dino 29.5 T, PO4, DIN (0.5e0.6) 34.4 Sal, Curr, PO4 (0.4e0.5) Nano 29.0 T, PO4, Sal, Nano (0.2e0.6) 23.4 SiO4, Curr, DIN (0.5e0.6) Oct

PC2-SJ107

Diato 38.5 Sal, Diato, PO4, Curr, T (0.3e0.6) Dino 35.6 Sal, DIN, PO4, Dino, T (0.3e0.5) Nano 41.7 Nano, Sal, PO4, T, DIN (0.3e0.5)

26.6 T, Diato, SiO4, DIN (0.4e0.5) 24.3 PO4, DIN, SiO4 (0.5) 24.5 SiO4, DIN, T (0.4e0.6)

19.4 SiO4, DIN (0.5e0.8)

38.5 Sal, DIN, Curr, Diato (0.4e0.5) 19.7 SiO4, T (0.5e0.7)

18.2 SiO4, Curr (0.5e0.8)

41.0 Sal, Dino, Curr, PO4 (0.4e0.5)

20.9 SiO4, T, DIN (0.5e0.6)

18.1 SiO4, Curr (0.6e0.8)

42.3 Sal, Nano, DIN, PO4, Curr (0.4e0.5)

19.7 SiO4, T (0.4e0.7)

t ¼ 6.97  C). Two summer peaks were documented in May and July. The autumn bloom was lower in the second period with a maximum in 2008 (z ¼ 0e5 m; 2.6  106 cells L1; S ¼ 37.17; t ¼ 19.33  C). 4.4.3. Dinoflagellates The dinoflagellates exhibited a usual annual cycle in the study period at both stations (Fig. 6). During the first investigated period at RV001 high abundances of dinoflagellates were noted from April until August. A maximum occurred in May 1991 (62.9  103 cells L1; z ¼ 0 m; S ¼ 33.83; t ¼ 18.42  C). In the second period, abundances were lower and a peak was reached in June 2000 (28.1 103 cells L1; S ¼ 36.69; t ¼ 22.48  C). The dinoflagellate annual cycle at SJ107 showed a similar pattern. In the first investigated period the annual maximum was reached from May to July with maximal abundances in June 1989 (75.5  103 cells L1; z ¼ 0 m; S ¼ 32.21; t ¼ 17.73  C). In the second period, in May 2002 a peculiarly high maximum of 586  103 cells L1 was recorded (z ¼ 0 m; S ¼ 33.29; t ¼ 21.19  C; Fig. 6B). 4.4.4. Microplankton The annual cycles of microplankton and diatoms were very similar and maximum in microplankton abundances followed diatom maximum. RV001 was characterized by significantly higher abundances in the first period. A shift in seasonality of the blooms was detected as well. In the first period, blooms occurred in March, May and October, without any evidence of an early spring bloom in the second period and higher abundances were recorded in July and October. At SJ107 in the first period blooms in March, June and October were noted. The second period was characterized by lower overall abundances with pronounced autumn bloom. 4.4.5. Nanoplankton The nanoplankton fraction exhibited a changing annual cycle between the two periods at both stations (Figs. 5 and 6). During the first investigated period at RV001 the highest abundances were noted from April until July. The maximum abundance was 33.1 106 cells L1 recorded in May 1991 in the bottom layer (S ¼ 37.99; t ¼ 13.41  C). In the second period, abundances were

lower and although they were elevated during the AprileJune period, the annual peak was reached in September 2006 (1.5  106 cells L1; S ¼ 37.48; t ¼ 22.51  C). At SJ107, the situation was similar. In the first period the annual maximum was in May 1988 (8.56  106 cells L1; z ¼ 0 m; S ¼ 35.11; t ¼ 18.63  C). In the second period abundances were lower. The maximum was observed in September 2009 in the surface layer (5.63  106 cells L1; S ¼ 34.10; t ¼ 23.11  C). 4.5. Community composition At RV001, 222 taxa were identified in the first period and 174 in the second. A total of 217 phytoplankton taxa were identified at SJ107 in the first and 172 in the second period. The identified phytoplankton community was composed of diatoms, dinoflagellates, coccolithophorids and silicoflagellates. A list of the most frequent taxa is compiled in Table 3A and B. The most frequent and abundant group at both stations and in both periods was the Pseudo-nitzschia delicatissima group, followed by Dactyliosolen fragilissimus, while the most frequent dinoflagellate was Prorocentrum micans. The species composition within the phytoplankton community showed marked differences between the two periods. Table 3 shows the most prominent species with accompanying frequency (F%) of observation as well as their maximum (Max), average (Avg) and standard deviation (SD) of abundance during the periods. The most prominent differences between the two periods were caused by species listed in the lower part of Table 3A e RV001 and Table 3B e SJ107. At RV001 the most frequent diatoms (Pseudo-nitzschia spp., Cylindrotheca closterium/ Nitzschia longissima complex, Leptocylindrus danicus and Cerataulina pelagica) showed a frequency increase in the second period, while the most frequent dinoflagellates (Gyrodinium sp., Ceratium fusus) showed a decrease. Next to the very frequent and abundant species or groups like e.g. Pseudo-nitzschia spp. and Rhizosolenia spp. there are also a number of species with very low frequencies of observation and low abundances, showing marked differences between the two periods (e.g. Chaetoceros spp., see lower part of Table 3A, B). Overall, the dominance of diatoms in the microplankton community was clear. Some diatoms increased in average abundance or maximum abundance in

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Fig. 5. Annual mean of surface values of total phytoplankton, diatoms, dinoflagellates, microplankton and nanoplankton (cells L1) for the whole study period at station RV001 (A) and station SJ107 (B). Dashed lines indicate mean yearly abundances, bold lines stand for interpolated yearly means and circles show real abundances.

the second period e.g. Asterionellopsis glacialis, Chaetoceros compressus and Cerataulina. pelagica at both stations. Results from SJ107 are very similar to the ones from RV001. Slight differences show, for example, the dinoflagellates Prorocentrum micans and Ceratium spp. being more prominent at SJ107 than at RV001 in the first period, and strongly decreasing in the second one. A

higher number of dinoflagellates are present in the list of the most frequent species of station SJ107. Some species showed different patterns at the two examined stations, e.g. Skeletonema marinoi increased in F% at RV001 in the second period with lower average abundances. Skeletonema marinoi appearance and frequency at SJ107 was lower in the second

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Fig. 6. Annual cycle of total phytoplankton, diatoms, dinoflagellates, microplankton and nanoplankton abundances (cells L1) for station RV001 (A) and station SJ107 (B) for both periods. Bold lines represent average abundances while dashed-shaded area represents standard deviation. Dots represent medians.

period, with average and maximal abundances much higher (more than double) due to a very abundant February bloom in 2004.

5. Discussion 5.1. Determination of periods

4.6. Species diversity and richness Yearly mean of the species diversity (Fig. 7) exhibited a periodicity of about 6 years, but did not point to any significant tendencies throughout the studied period or to any special differences between the periods. The observed high variability in 1973 (Fig. 7, arrow) is probably a result of the change in sampling frequency (biweekly). Monthly means of species richness (Fig. 8A) and species diversity (Fig. 8B) were calculated for the months in which major phytoplankton blooms occurred (February, March, May and October) and the highest values were observed for the autumn bloom.

The northern Adriatic as a small and shallow basin and is known to show fast and strong changes in response to variations of anthropogenic influences and climatic conditions. Over the last decade the main environmental parameters showed important changes. Salinity values after 2000 were constantly higher than the average of the entire investigated period, at both stations (Fig. 2). These increased values are associated with decreased Po River outflow coupled with changes in the circulation pattern of the NA (Fig. 3). The usually predominant anticyclonic circulation pattern which spreads nutrient-enriched waters towards the Croatian coast was often replaced by an input

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Fig. 6. (continued).

of high salinity-low nutrient waters from the central Adriatic indicated by the EAC. This induced a significant increase of ambient salinity at both stations. Consequently, a lower nutrient input to the region in this period reduced the phytoplankton production. Irregular and occasional samplings which took place during the first decade of the study period resulted in obviously underestimated abundances for that period. Nevertheless, this part of the data set was included in all analyses and was especially valuable for observing the phytoplankton species diversity in the early seventies and for comparison with the subsequent periods. Interpolated means (Fig. 5) enabled neutralisation of the missing data effect, allowing a more probable insight in the actual phytoplankton abundance changes over the decades.

5.2. Regime shift analyses in phytoplankton abundances Regime shifts are abrupt changes around a multitude of physical properties and ecosystem variables which lead to new regime conditions (Conversi et al., 2010). Most recent investigations focused on the changes in ecosystem diversity and function coupled to such shifts (Kamburska and Fonda-Umani, 2009; Conversi et al., 2010). Regime shift analysis on phytoplankton abundance data (Fig. 4) showed several major changes. The first period is characterized by an upward shift in the eighties in abundance of total phytoplankton, diatoms, dinoflagellates, microplankton and nanoplankton at both stations. Those shifts were more pronounced at SJ107 than at RV001 (1984), where they preceded the shifts at the costal station (1988). Conversi et al. (2010) showed that the

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Table 3 Dominant phytoplankton species during 1972e1999 and 2000e2009 periods at: A) station RV001 and B) station SJ107. Listed are species with a frequency of appearance higher than 15%. Abundances are expressed as 103 cells L1. Species names in bold evidence the species with more pronounced differences between the two periods. 1972e1999

A) RV001 Species name Pseudo-nitzschia delicatissima group Cylindrotheca closterium/Nitzschia longissima complex Dactyliosolen fragilissimus (Bergon) Hasle Prorocentrum micans Ehrenberg Rhizosolenia alata f. gracillima (Cleve) Gran Guinardia striata (Stolterfoth) Hasle Leptocylindrus danicus Cleve Gyrodinium sp. Ceratium fusus (Ehrenberg) Dujardin Guinardia flaccida (Castracane) Peragallo Cerataulina pelagica (Cleve) Hendey Chaetoceros affinis Lauder Ceratium furca (Ehrenberg) Claparéde et Lachmann Hemiaulus hauckii Grunow Syracosphaera pulchra Lohmann Pseudo-nitzschia seriata group Gymnodinium sp. Skeletonema marinoi Sarno et Zingone Chaetoceros curvisetus Cleve Species with the most marked differences Prorocentrum triestinum Schiller Chaetoceros atlanticus Cleve Rhizosolenia imbricata Brightwell Glenodinium mucronatum Conrad Chaetoceros decipiens Cleve Thalassionema nitzschioides (Grunow) Mereschkowsky Chaetoceros socialis Lauder

2000e2009

F%

Max

Avg

SD

F%

Max

Avg

SD

B B

62.5 65.8

1076.7 218.3

52.2 7.5

143.6 20.2

82.1 78.3

427.7 59.9

26.6 4.1

57.7 8.3

B D B B B D D B B B D

51.0 40.4 40.4 30.3 29.3 28.8 28.4 26.0 25.5 23.6 22.6

599.4 33.3 224.4 22.2 66.6 3.0 2.2 9.6 134.7 63.6 40.3

13.9 2.1 7.9 3.3 7.1 0.6 0.6 1.2 8.1 12.4 1.6

59.5 5.2 29.1 4.8 11.9 0.7 0.5 1.5 22.0 16.4 5.9

53.6 42.0 50.9 33.0 55.4 26.8 19.6 22.3 54.5 31.3 16.1

142.1 7.4 15.5 11.1 79.9 2.2 1.5 2.2 371.5 222.7 3.0

7.0 1.1 1.9 1.8 5.5 0.8 0.6 0.9 20.1 16.9 0.7

19.8 1.3 2.4 2.4 12.8 0.6 0.3 0.6 61.2 38.5 0.7

B C B D B B

22.1 19.7 19.2 15.9 14.9 14.4

11.1 8.1 1139.6 8.1 3676.3 41.3

1.1 1.5 34.8 1.2 148.1 10.4

1.7 1.7 179.6 1.6 657.0 11.1

22.3 14.3 12.5 22.3 18.8 10.7

3.0 3.7 23.3 3.0 170.9 29.6

0.9 1.4 3.6 1.0 14.0 5.4

0.8 1.0 6.0 0.8 36.6 7.8

D B B D B B

7.2 3.8 1.9 7.2 6.7 13.5

2.2 23.7 0.7 7.4 77.0 5.2

0.5 7.8 0.3 0.8 11.0 1.0

0.5 7.4 0.3 1.8 19.7 1.0

14.3 13.4 11.6 17.0 17.0 40.2

3.7 10.7 1.5 1.5 22.2 6.7

0.8 2.9 0.5 0.7 5.0 1.6

0.8 3.0 0.4 0.4 5.6 1.7

B

13.0

5402.0

314.4

1045.6

7.1

47.4

8.7

15.8

B B B

56.6 53.4 49.6

2122.3 283.4 201.3

65.2 26.0 10.4

207.9 56.4 26.0

68.7 61.6 57.2

378.1 135.4 79.2

410.9 10.2 6.2

76.1 20.2 12.9

B) SJ107 Species name Pseudo-nitzschia delicatissima group Dactyliosolen fragilissimus (Bergon) Hasle Cylindrotheca closterium/Nitzschia longissima complex Prorocentrum micans Ehrenberg Rhizosolenia alata f. gracillima (Cleve) Gran Ceratium fusus (Ehrenberg) Dujardin Ceratium furca (Ehrenberg) Claparéde et Lachmann Guinardia striata (Stolterfoth) Hasle Gyrodinium sp. Leptocylindrus danicus Cleve Guinardia flaccida (Castracane) Peragallo Cerataulina pelagica (Cleve) Hendey Syracosphaera pulchra Lohmann Chaetoceros affinis Lauder Pseudo-nitzschia seriata group Hemiaulus hauckii Grunow Gymnodinium sp. Prorocentrum compressum (Bailey) Abé ex Dodge Chaetoceros curvisetus Cleve Glenodinium mucronatum Conrad Protoperidinium steinii (Jörgensen) Balech Skeletonema marinoi Sarno et Zingone Thalassionema nitzschioides (Grunow) Mereschk.

D B D D

46.1 42.9 39.0 35.5

18.5 159.7 7.4 11.1

2.6 7.4 0.9 1.2

4.0 23.6 1.0 2.1

29.5 50.0 20.5 20.5

8.9 47.4 3.0 3.0

1.2 2.5 1.0 0.8

1.5 6.3 0.6 0.7

B D B B B B B B B D D B D D B B

33.7 30.7 28.9 27.6 25.4 25.0 23.7 22.8 22.4 19.7 18.4 16.7 16.7 15.8 14.5 14.5

93.2 9.6 300.4 20.4 1019.7 81.4 330.0 1804.1 8.5 41.4 6.7 284.2 5.2 2.3 3346.3 219.0

5.9 1.2 21.4 1.8 29.1 4.6 22.6 46.4 1.2 3.0 1.0 28.3 1.1 0.6 290.5 9.9

13.6 1.7 49.9 3.0 136.3 12.0 47.1 249.7 1.4 6.9 1.3 51.9 1.1 0.5 697.5 38.0

36.6 25.9 40.2 25.0 58.9 20.5 36.6 12.5 26.8 16.9 2.7 15.2 17.9 8.0 11.6 41.1

19.2 5.2 53.3 3.0 985.7 4.4 192.4 611.2 110.3 3.7 0.7 41.4 3.7 1.5 6874.6 12.6

3.0 1.0 8.3 0.9 36.8 1.2 13.8 80.9 4.6 1.7 0.5 5.7 0.9 0.8 604.1 2.3

4.0 1.1 12.7 0.7 131.8 1.2 30.5 175.6 20.0 1.2 0.2 9.6 0.8 0.4 1891.5 3.0

Species with the most marked differences Protoperidinium pyriforme (Paulsen) Balech Proboscia alata (Brightwell) Sundström Protoperidinium diabolus (Cleve) Balech Chaetoceros compressus Lauder Rhizosolenia imbricata Brightwell Asterionellopsis glacialis (Castracane) Round Prorocentrum triestinum Schiller Chaetoceros decipiens Cleve

D B D B B B D B

12.3 10.5 13.6 8.3 0.9 10.9 4.4 13.6

2.9 24.4 4.1 205.0 0.4 210.9 2.2 22.9

0.6 1.9 0.9 46.8 0.3 18.3 1.0 5.9

0.6 4.9 1.0 62.3 0.1 42.8 0.6 6.1

2.7 1.8 5.4 17.0 9.8 22.3 16.1 29.5

0.7 0.7 1.5 529.1 1.3 384.8 5.2 24.4

0.6 0.6 0.8 56.6 0.6 22.9 1.5 5.3

0.3 0.3 0.4 131.6 0.4 78.7 1.2 6.5

Abbreviations: F: frequency, Max: maximum, AVG: average, SD: standard deviation, B: diatoms, D: dinoflagellates, C: coccolithophorids.

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Fig. 7. Box and whisker plots of species diversity index calculated for each station over the studied period.

Mediterranean Sea underwent a regime shift at the end of the 1980s that encompassed atmospheric, hydrological and ecological systems. Even though in our study a slightly different methodology (cut-off length) was used, similar results were noted, especially for RV001. Changes were most pronounced in the very abundant nanoplankton (which contributes considerably to the total phytoplankton). Civitarese et al. (2010) reported an alteration of circulation patterns (from anticyclonic to cyclonic) in the Ionian Sea, which reflected on the productivity of the Adriatic Sea. The shift in 2000 resulted in an overall reduced total phytoplankton abundance in the second period which is mainly driven by the reduction of nanoplankton abundances. Less abundant dinoflagellates show only a small decrease during the second period, while the microplankton dominating diatoms profited from the changes and increased from 1988 up to the highest abundances in 1992. From then on, diatoms showed a slight decrease towards the second period. This is in accordance with the results presented by Mozeti c et al. (2012) who observed the disappearance of large diatom blooms in the period from 1999 to 2003 and much lower diatom abundances in the period after 2003 in Trieste Bay.

5.3. Phytoplankton coupled with environmental parameters e PCA To better understand the mechanisms of environmental pressures which influence phytoplankton in the investigated region, a PCA was carried out (Table 2). As expected, the results indicated a strong relationship between salinity and phytoplankton abundance, as similarly showed by Bernardi Aubry et al. (2004). In their study the first component (PC1) was related to river discharge with the explanation that the spatial distribution of nutrients was closely related to river discharges and salinity in coastal systems. In our case, a significant correlation with low salinity could be explained by high amounts of nutrients in low salinity waters originating from the Po River and confirms that an increase in salinity coincided with a phytoplankton reduction after 2000. Low salinity waters at SJ107 are predominantly the result of an anticyclonic circulation system, indicated by the intense ICCC, while low salinity at RV001 could be a result of its specific coastal circulation. Strong correlations between phytoplankton abundance with either nutrients, or their combination, might be indicative of their role in limitation of phytoplankton growth, while uncorrelated nutrients

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Fig. 8. Box and whisker plots of diversity indices calculated for each station for the two studied periods (monthly). ShannoneWiener diversity index (A) and Margalef species richness index (B).

are presumably not limiting the phytoplankton abundance. A decrease in availability of orthophosphate could be noted from SJ107 towards RV001, which is concurrent with the diminishing influence of the Po River and exhaustion of nutrients towards the Croatian coast. This phosphate limitation of phytoplankton growth in the NA (Degobbis et al., 2000), is counteracted by phytoplankton alkaline phosphatase, which enables the cells to use organic phosphate as a source of P in situations of orthophosphate deficit (Ivanci
c et al., 2009). Negative correlations with nitrate indicate a high nitrogen-low phytoplankton situation, just as it was observed almost for the entire 2000e2009 period. This might be an indication that larger amounts of nitrogen remained unused in the water due to a general limitation of phosphorus availability. During the entire investigated period exceptionally high abundances of diatoms and dinoflagellates were recorded on several occasions (i.e. diatom blooms in October 1993 and February 2004, which reflected on micro- and total phytoplankton abundances; Figs. 5 and 6B). These events can easily be seen in Fig. 6B as the discrepancies between the average and median values, combined with a high standard deviation. Although in the months in question phytoplankton blooms were typical events in the seasonal cycle, such outstandingly high phytoplankton blooms are quite rare. A presumption that these exceptional blooms result from an infrequent, but particularly favourable combination of environmental conditions is reasonable. 5.4. Shifts in phytoplankton seasonality Total phytoplankton abundance is calculated as the sum of the microphytoplankton and nanoplankton fractions, with a major contribution of the latter. Diatoms are the main contributors to the microphytoplankton fraction (Revelante and Gilmartin, 1976). Similar observations were made by Bernardi Aubry et al. (2006) for

the western coastal area of NA (nutrient-enriched system), where the community structure was dominated by diatoms (both microand nanoplankton fractions), over most of the year. Dinoflagellates have an important role in phytoplankton diversity during the stratification period. According to Bernardi Aubry et al. (2004, 2006), the importance of dinoflagellates in the communities was generally low, with significant abundances present only in JuneeJuly, once the spring bloom of diatoms had left ‘nutrientpoor’ conditions in the water. Changes in phytoplankton abundance over the seasonal cycle could also be observed. Vili ci
c et al. (2009) noted a shift in timing of phytoplankton maximal abundances from spring to autumn in the NA (years 2005e2007). As mentioned in Mozeti c et al. (2010), over the last decade the Chl a maximum in the late wintereearly spring period has shifted from JanuaryeFebruary to AprileMay, especially at stations most affected by reduced Po River discharges. However, some of the previously regular bloom events seem to have virtually disappeared, e.g. the wintereearly spring bloom of diatoms and microplankton in the second investigated period at RV001 or the spring bloom of nanoplankton at station SJ107. In the first period, the majority of high abundances were associated with JanuaryeFebruary blooms that were dominated by small diatoms like Skeletonema marinoi (Harding et al., 1999; Bernardi Aubry et al., 2006). Other reports from the NA over the last decade describe the first seasonal bloom being dominated by autotrophic nanoflagellates or Cerataulina pelagica (Socal et al., 2008) and small dinoflagellates e.g. Prorocentrum minimum (Bernardi Aubry et al., 2006). Since the early spring bloom is sustained by regenerated nutrients from the late autumn, brought by mixing to the surface (Harding et al., 1999), Mozeti c et al. (2010) suggested that the decrease in magnitude of this early spring bloom could be a signal of recent oligotrophication of the NA ecosystem. Relating long-term changes in bloom dynamics to environmental change had some success because blooms are identifiable events, often with well

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understood triggers that can be altered by the changing climate (Smayda and Reynolds, 2001). 5.5. Community composition and diversity indices While comparing the number of identified species detected in the first and the second period at both stations, differences were noted (e.g. at SJ107, 222 in the first period compared to 170 in the second one). As the periods differed in length the best way to test if there were changes in biodiversity was with diversity indices. Those indices might be useful tools in the determination of the trophic state of the system, and in many cases they are more important and indicative than chemical characteristics of the water column per se (Revelante and Gilmartin, 1980). Here, the two studied stations, RV001 and SJ107, were compared in species diversity on a yearly (Fig. 7) and in species diversity/richness on a monthly (Fig. 8) basis. Both species diversity and richness were high and stable for both stations. High diversity indices on the eastern side of the NA were reported by Revelante and Gilmartin (1980), with the highest diversity in the months from September to December (Fig. 8) which is consistent with our results. In Fig. 7 it is evident (arrow) that the highest index was calculated for the year 1973 when the frequency of sampling was highest in the whole data set (weekly or biweekly). Thus this might be a reason for the highest biodiversity recorded in this particular year. The detected regime shift in phytoplankton abundances and environmental parameters did not affect the species biodiversity even though a sub significant periodicity in the species diversity index was found (with a 6e7 years period). This periodicity in biodiversity could be related to the circulation regime described by Civitarese et al. (2010) and changes in the Ionian Sea circulation and the source of EAC. It might be explained by the fact that EAC brings along its pathway highly diverse phytoplankton communities. Our observation of high index values indicated that this region is an important area regarding phytoplankton biodiversity as highly performing and competitively dominant species are more likely to be found within species-rich communities, where they contribute to the community diversity as described by Gravel et al. (2011). We nevertheless have to bear in mind that each species is also unique, and parameters important to growth and sustainability of one organism do not apply to another (Martin et al., 2009). Pseudo-nitzschia species were dominating the phytoplankton community in frequency of appearance over the whole 37 year study period. This genus profited strongly from the shift in 2000 showing an even higher frequency afterwards. Nevertheless, some changes in species composition of the Pseudo-nitzschia group have been observed. A decrease of frequency and abundance of the Pseudo-nitzschia seriata group was observed, whereas an increase in the frequency (up to 82.1%) of the Pseudo-nitzschia delicatissima group occurred at both stations in the second period. This group of species is particularly interesting because some of them were demonstrated to be potentially toxic and capable of domoic acid production. Lately, Pseudo-nitzschia calliantha was confirmed to produce toxins and dominate the phytoplankton community in Croatian coastal waters (Mari
c et al., 2011). Apparently the change in environmental parameters, e.g. nutrients, suited their environmental preferences or provided them with a competitive advantage. This was consistent with the analysis by Mari
c et al. (2011), where it was reported that nutrient conditions in the northern Adriatic in 2007 favoured the growth of Pseudo-nitzschia species over other diatoms, due to their lower nutrient requirements. Skeletonema marinoi was one of the rare diatoms that increased in the average abundance in the second investigated period at

111

SJ107, while at RV001 average numbers were lower in the second one. Skeletonema marinoi was reported as the early spring diatom of the Adriatic Sea on the western side of the NA, while in Croatian coastal waters such high abundances appeared only sporadically. The diatom Skeletonema was a convincing indicator of nutrient influx, most probably from anthropogenic sources, and it was characterized by higher rates of nitrate uptake and growth rate (DeManche et al., 1979). This made Skeletonema a much better competitor under similar conditions than many other diatoms which could profit from generally lower abundances of other competitors. This could be in line with the more frequent appearance of various diatom species of the genus Chaetoceros during the last decade. Similar observations were reported by Mozeti c et al. (2010) for the late wintereearly spring bloom in the Gulf of Trieste in recent years where the genus Chaetoceros was much more frequent, compared to the early 1990s period. Small-sized and chain-forming Chaetoceros spp., with a favourable surface to volume ratio, were able to grow at low nutrient concentrations and high N/P ratios (Lagus et al., 2004). This was the case in the coastal NA waters in the second investigated period. Mozeti c et al. (1998) stated that the phytoplankton annual biomass maximum mainly depended on opportunistic, fastgrowing diatoms like Skeletonema costatum (Skeletonema marinoi), P. pseudodelicatissima, Chaetoceros sp., Cyclotella sp. and Cylindrotheca closterium. These taxa seemed to respond quickly to nutrients introduced by rivers or precipitation (Mozeti c et al., 1998). Dinoflagellates increased in abundance after nutrient exhaustion in May and August, generally after the diatom bloom. Prorocentrum spp., Ceratium spp., Gyrodinium spp., Gymnodinium spp. and Protoperidinium spp. were the most frequent and most abundant genera of dinoflagellates during the investigated period, which is in accordance with previous observations by Bernardi Aubry et al. (2004) and Vili ci
c et al. (2009). The occurrence of species from genera such as Protoperidinium spp. and Gyrodinium spp. in spring and summer months was expected to be a response to an increase in diatoms, since they are a good food source for some dinoflagellates (Stelfox-Widdicombe et al., 2004). 6. Conclusions The change towards higher salinity values during the second period indicates a change in the freshwater distribution across the NA after 2000. Our analyses showed that long-term changes in phytoplankton abundances are closely related to changes in salinity, indicating strong climatic and anthropogenic influences on these primary producers. This and resulting changes concur with phytoplankton shifts in abundances in the middle and eastern NA part, as well as in phytoplankton composition and seasonality changes. These observed basin wide changes in the phytoplankton community represent the major change within the NA ecosystem. Our findings present the NA as a region fast in response to environmental perturbations, with phytoplankton as a good indicator of changes. They also show that the NA, like other similar marine systems, is changing fast, presenting an ever-alternating status quo for anthropogenic pressures or e.g. invasive species. These observations underline the necessity of close observations and continuous investigation of the phytoplankton biodiversity in the NA and similar fast reacting systems. Acknowledgements This work was supported by the Ministry of Science, Education and Sports of the Republic of Croatia (projects 098-0982705-2731, 098-0982705-2707 and “Project Jadran”). The authors thank all

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