controlling factors of phytoplankton seasonal succession in oligotrophic mali ston bay...

Controlling factors of phytoplankton seasonal successionin oligotrophic Mali Ston Bay (south-eastern Adriatic)

Marijeta Čalić & Marina Carić & Frano Kršinić &

Nenad Jasprica & Marijana Pećarević

Received: 16 July 2012 /Accepted: 29 January 2013# Springer Science+Business Media Dordrecht 2013

Abstract Fine spatial and temporal phytoplanktonvariability in Mali Ston Bay has been observed forthe first time based on physicochemical properties andsmall herbivorous zooplankton. Extensive year-through research was conducted during 2002 at Uskostation which is traditionally an area of intensive shell-fish farming. The Neretva River inflow, submarinesprings (“vruljas”) and precipitation are additionalsources of nutrients in the bay. Temperature and salin-ity, combined with total inorganic nitrogen (TIN) wereobserved to be the most important environmental fac-tors driving the succession of phytoplankton commu-nities. Orthophosphate was a potential limiting factorfor phytoplankton development. The nanophytoplank-ton abundances, as well as the microphytoplanktondiatoms are controlled by herbivorous zooplanktongrazing (‘top-down’ control) more than other groups

of microphytoplankton. Nanophytoplankton dominat-ed phytoplankton abundance and its most intensivedevelopment was recorded in winter and spring, whileincrease in microphytoplankton abundance occurredin spring and autumn. Diatoms dominated microphy-toplankton abundance mostly in winter and autumn,while dinoflagellates dominated in spring and sum-mer. Considering the number of taxa and abundance,dinoflagellates were the dominant microphytoplank-ton group during the year and were the main compo-nent of the spring blooms. At that time, in conditionsof elevated temperature (>16 °C), decreased salinity(34–36) and increased concentrations of TIN, bloomsof harmful dinoflagellate Prorocentrum minimumwere recorded for the first time in the bay. The resultsshowed a significant difference in environmental con-ditions, as well as in the annual phytoplankton succes-sion and community structure, as compared withstudies carried out more than 20 years ago in this area.

Keywords Adriatic Sea .Mali Ston Bay .

Physicochemical parameters . Phytoplankton .

Succession . Zooplankton

Introduction

The biomass and community structure of the marinephytoplankton is constantly adapting to changes in theenvironment.Margalef (1978) suggested that spatial andtemporal distribution of phytoplankton is determined by

Environ Monit AssessDOI 10.1007/s10661-013-3118-2

M. Čalić (*) :M. Carić :N. JaspricaInstitute for Marine and Coastal Research,University of Dubrovnik,Kneza Damjana Jude 12, PO Box 83,20000 Dubrovnik, Croatiae-mail: [email protected]

F. KršinićInstitute of Oceanography and Fisheries,Šetalište I. Meštrovića 63,21000 Split, Croatia

M. PećarevićDepartment of Aquaculture, University of Dubrovnik,Ćira Carića 4,20000 Dubrovnik, Croatia

specific microphysical and microchemical environmen-tal conditions. Intense or frequent disturbances in themarine ecosystems (e.g., sudden changes in the thermo-haline properties and nutrient quantities or strong turbu-lence) could eliminate many species and reducebiodiversity, while low-intensity or low-frequency dis-turbances allow for competitive exclusion. Coastalareas, such as Mali Ston Bay (south-eastern Adriatic),are particularly exposed to changes of environmentalproperties which makes them highly variable ecosys-tems (Mann 1982; Kjerfve 1994). Changes in watercirculation, and various land and human impacts induceconsiderable temporal variations in environmental con-ditions that may be reflected in the dynamics of thecoastal phytoplankton population (Richardson andLeDrew 2006).

Mechanisms which determine patterns of phyto-plankton succession in marine ecosystems have beenwell studied (e.g., Gilabert 2001; Bernardi Aubry etal. 2004; Domingues et al. 2005; Pilkaityté andRizinkovas 2007; Rigual-Hernández et al. 2010).Knowledge of ecological factors that regulate phyto-plankton seasonal succession is essential for under-standing the potential consequences of escalatingthreats to marine ecosystems, such as eutrophication,sea acidification, and climate change. Increasing eu-trophication in coastal marine areas in recent decadeshas resulted in a change in prevailing phytoplanktongroups (Rocha et al. 2002; Lillebø et al. 2005; Lopeset al. 2007). Béthoux et al. (2002) suggest that in-creasing concentrations of phosphate and nitrate inrelation to the silicates in coastal areas of theMediterranean are causing a change in the phyto-plankton community structure. Diatoms that werepreviously dominant are being replaced by non-siliceous groups of phytoplankton. Changes in seatemperature, cloud cover, as well as wind directionand strength can additionally affect phytoplanktonphenology (Nixon et al. 2009; Guinder et al. 2010;Paerl et al. 2011). In addition to the widely acceptedclassical spring biomass increases in temperatewaters, winter blooms and peaks in both the inshoreand offshore Mediterranean are regularly reported(Zingone et al. 2010). Meteorological variations ef-fect the occurrence and duration of phytoplanktonblooms that directly influence oxygen productionand biogeochemical cycles in the ecosystem, as wellas zooplankton and the food web in general(O’Connor et al. 2009; Edwards et al. 2010).

Mali Ston Bay is a coastal region in the southernAdriatic with a long mariculture tradition where oystersand mussels have been cultivated for centuries. Due toits ecological and economical importance, in 2002 thisarea was proclaimed a special maritime reserve.However, the most recent studies of phytoplanktonecology and taxonomy in Mali Ston Bay were carriedout in the period from 1979 to 1989 (e.g., Jasprica 1989;Jasprica et al. 1994, 1997; Viličić et al. 1994, 1998).Those studies have found that the intensity and frequen-cy of land water runoff has a strong influence on thephysical and chemical characteristics, the intensity ofeutrophication, and phytoplankton development in thisbay. An increase in phytoplankton biomass occurs dur-ing the summer months (May to August), althoughoccasionally the high productivity period extends intothe autumn months (September to October). In bothcases, diatoms dominate the phytoplankton community.Based on the frequency distribution of phytoplanktonabundances, nutrient concentrations and transparencythe bay has been classified as a moderately naturallyeutrophicated ecosystem (Viličić 1989).

The objective of this study was to clearly define thephytoplankton community succession and primary en-vironmental factors responsible for it. For this pur-pose, an extensive year-through sampling in MaliSton Bay was conducted during 2002. Weekly orbiweekly results of phytoplankton analyses in fine-scale spatial resolution, followed by physical andchemical parameters (‘bottom-up’ control) and smallherbivorous zooplankton (‘top-down’ control) are pre-sented for the first time for this area. In addition, theresults are compared with studies carried out morethan 20 years ago in order to determine how (and if)the phytoplankton community structure has changed.Knowledge of phytoplankton population dynamics inrelation to environmental factors in Mali Ston Bayprovides an important baseline for further monitoringand the detection of possible natural and anthropogen-ic ecosystem disruptions relevant to mariculturemanagement.

Materials and methods

Study site

Mali Ston Bay is a deeply indented neritic area be-tween the Pelješac Peninsula and the mainland

Environ Monit Assess

(Fig. 1). The bay expands to the northwest and con-nects with the Neretva River channel which is linkedwith the open sea. The specific winter cyclonic flowthat amplifies the inflow of eastern Mediterraneanwater into the Adriatic Sea (Gačić et al. 2001) hassome impact on the environmental properties of thebay (Viličić et al. 1998). But the most important fac-tors that affect the ecological conditions in Mali StonBay, primarily salinity and nutrient enrichment, are theinflow of fresh water from the Neretva River in theouter part of the bay and from underground springs(“vruljas”) in the inner part (Balenović 1981; Viličić etal. 1998; Milanović 2006). During the period of highersubsurface activity, brackish water rises to the surfaceand exits the bay. This outward flow facilitates thesub-halocline inflow of higher salinity water fromthe open sea. In this way, an estuarine circulation inMali Ston Bay is formed. During the dry seasons, theinflow of groundwater is significantly reduced whichaffects the circulation patterns in the bay, allowingboth inflow and outflow to occur, depending only onthe wind direction. The mean rate of current in the bayis 4 cms−1 at the surface, decreasing to 2.3 cms−1 atthe bottom (Vučak et al. 1981). The direction changebetween surface and bottom current velocity is 180°.According to the vertical distribution of current veloc-ities, the surface layer thickness was estimated as

being at 5–6 m at Usko station (Viličić et al. 1998).There are two periods of stratification: in summerinfluenced by solar heating and the impact of theNeretva River, and in winter influenced by freshwaterinput. The halocline is most frequently in the layerbetween 2 and 5 m depth.

Sampling was conducted at a station located in thecentral part of the Usko strait that connects the innerand outer part of Mali Ston Bay. This 13-m-deep and270-m-wide passage is a point where water massexchange between the inner and outer part of the bayoccurs. For this reason, our sampling was focused on asingle station in the strait since by monitoring thesituation at Usko the environmental conditions in thewhole bay could be predicted.

Field sampling and experimental design

Samples for physicochemical (temperature, salinity,dissolved oxygen, nutrients and chlorophyll a), phy-toplankton and zooplankton analysis were obtained inthe period from 2 January to 20 December 2002 atUsko station (42°52′22.13″N and 17°40′31.06″E).From January to May sampling were conducted oncea week and from June to December mostly twice amonth. Water samples for all parameters were takenwith 5-l Niskin bottles from the surface to the bottom

Fig. 1 Location of Uskosampling station in MaliSton Bay


(13 m) at 1-m depth intervals. A total of 33 fieldworkswere carried out and 462 samples of each parameterwere processed. According to previously obtained da-ta on phytoplankton distribution and quantity of non-living suspended particles (Viličić et al. 1998), andcurrent measurements (Vučak et al. 1981), as well asthe most frequent positions of halocline and pycno-cline in this study, the water column has been dividedinto the two layers: surface layer (0–6 m) and bottomlayer (7–13 m). All parameters were analyzed accord-ing to this criterion.

Data on the Neretva River flow (Žitomislići station,at ca. 40 river km) for 2002 were consigned by TheAdriatic Sea River Basin District Agency (Mostar,Bosnia and Herzegovina). Water temperature wasmeasured with an inverted thermometer. Salinity wasdetermined by the standard Mohr–Knudsen titrationmethod with silver nitrate (Grasshoff et al. 1983).Potential density (sigma-t=ρ−1,000 kgm−3) was cal-culated from temperature and salinity at given depths,based on the standard equation and referenced to 0dbar (UNESCO 1986). The depths of halocline, ther-mocline and pycnocline are defined as the depth wherethe maximum gradient is found (>0.3 m−1 for salinity,>0.5 °Cm−1 for temperature and >0.2 kgm−3m−1 forpotential density). Mixed layer depth is determinedby sigma-t profile, and it is a depth at which achange from the surface sigma-t is 0.125 kgm−3

(Levitus 1982). Dissolved oxygen was determinedby Winkler titration and oxygen saturation (O2/O2′)was calculated from solubility of oxygen in sea-water as a function of the corresponding tempera-ture and salinity (Weiss 1970; UNESCO 1986).Transparency is measured as a visibility of Secchi discmultiplied by 3 to determine euphotic depth (Berman etal. 1986). Chemical parameters included phosphate(PO4

3−), total inorganic nitrogen (TIN)=nitrate(NO3

−)+nitrite (NO2−)+ammonium (NH4

+), and sili-cate (SiO4

4−) were analyzed according to Stricklandand Parsons (1972) and Ivančić and Degobbis (1984).The TIN/PO4

3−, SiO44−/TIN and SiO4

4−/PO43− ra-

tios were calculated to determine the potentially limit-ing nutrients for phytoplankton population growth(Redfield et al. 1963).

Trophic status was characterized by the TRIX index,commonly used to classify the coastal marine areas inthe Mediterranean (Giovanardi and Vollenweider 2004;Karydis 2009): TRIX=[log10(Chl a×D%O×DIN×TP)+k]/m. Each of the factors represents a variable

reflected in the trophic state: Chl a=chlorophyll a con-centration (μgl−1), D%O=dissolved oxygen (absolutedeviation from 100 % oxygen saturation), dissolvedinorganic nitrogen DIN and TP=total phosphorus (μgl−1). The parameters k=1.5 and m=1.2 set the range ofthe TRIX scale from 0 to 10 (0–4 oligotrophic, 4–5mesotrophic, 5–6 eutrophic, 6–10 extremely eutrophic).

Chl a was determined from 500-ml sub-samplesfiltered through Whatman GF/F glass-fibre filters storedat −20 °C. These were homogenized and extracted in90 % acetone for 24 h at room temperature (Holm-Hansen et al. 1965). Samples were analyzed fluoromet-rically with a Turner TD-700 Laboratory Fluorometer(Sunnyvale, CA) calibrated with pure Chl a (Sigma).

Phytoplankton samples were preserved in neutral-ized formalin (2.5 % final concentration) and observedwith an Olympus IX-71 inverted microscope accordingto the Utermöhl method (Utermöhl 1958). Sub-samples (50 ml) were settled for 24–48 h in countingchambers (Hydro-Bios) before analysis. The phyto-plankton abundances are expressed as number of cellsper liter (cells l−1). The values of all abundances werecalculated as mean for 0–6 and 7–13 m layers, respec-tively, except for the most abundant phytoplanktonspecies where their maximum was noted. Counts ofmicrophytoplankton (cells >20 μm, MICRO) weremade at a magnifications of 400× in one central tran-sect, 200× in two to three central transects and at 100×over the entire area of the counting chamber base plateto obtain the most accurate evaluation. MICRO wasdivided into eight groups: diatoms (Bacillariophyceae-BACI), dinoflagellates (Dinophyceae-DINO), coccoli-thophorids (Prymnesiophyceae-COCC), silicoflagel-lates (Dictyochophyceae-DICT), green planktonicalgae (Chlorophyta+Prasinophyceae-CHLO), eugle-nophytes (Euglenophyceae-EUGL), filamentous cya-nobacteria (Cyanophyceae-CYAN) and desmids(Zygnematophyceae-ZYGN). Whenever possible,identification was taken to the species or genus levelusing standard taxonomic guides (e.g., Hustedt 1930;Schiller 1930, 1933, 1937; Steidinger and Tangen1996; Hasle and Syvertsen 1996; Bérard-Therriault etal. 1999; Viličić 2002). The nomenclature of the highertaxonomic categories and associated phytoplanktontaxa is in accord with database AlgaeBase (http://www.algaebase.org/) and publications cited therein.Nanophytoplankton (cells 2–20 μm, NANO) wascounted in 30 randomly selected fields-of-view at mag-nification 400×. NANO cells were not taxonomically


http://www.algaebase.org/

http://www.algaebase.org/

identified but were divided into five functional groupsaccording to size: small nanoflagellates <10 μm (SNFL),large nanoflagellates 10–20 μm (LNFL), small nanococ-colithophorids <10 μm (SNC), large nanococcolitho-phorids (LNC) and chroococoid cyanobacteria 2–20 μm (NCC).

Samples for protozoans and micrometazoans analysiswere taken with 5-l Niskin bottles and conserved 2.5 %neutralized formaldehyde solution. The initial volume of5 l was settled for 72 h three times and decanted in orderto reduce the volume to approximately 20 ml (Kršinić1980). Microzooplankton was determined and countedusing Olympus IMT-2 inverted microscope at magnifi-cation of 100× and 400×. Zooplankton includes: proto-zoans (nonloricate ciliates and tintinnids), and onlyherbivorous copepods (calanoids and cyclopoids) andtheir development stages (nauplii) as micrometazoans.Abundances are expressed as number of individuals perliter (ind. l−1), and calculated asmean for 0–6 and 7–13mlayers, respectively.

Data analyses

The annual range, average (avg.) and standard deviation(SD) are given for all variables in Results. ParametricStudent’s t-test was performed to determine the signifi-cance of the differences between layers. Spatiotemporalvariability of Chl a, physicochemical and hydrologicalparameters were explored using principal componentanalysis (PCA) by PcOrd 5 (McCune and Mefford2006). In order to determine the relationship betweenphytoplankton abundance with physicochemical param-eters and microzooplankton, Spearman rank andPearson’s product–moment correlations were performedby Statistica 7.0 (StatSoft Inc. 2004). The Kolmogorov–Smirnov test was used for testing normality of the datadistribution. Analyses were carried out on a total of tenphytoplankton groups in relation to the 12 environmen-tal parameters and five zooplankton groups. To improvethe correlation between variables data were first loga-rithmically transformed [log(x+1)] (Cassie 1962).

Results

Physicochemical characteristics

Based on the annual variation of halocline, pycnoclineand mixed layer depth water column was divided in

two layers. There was a statistically significant differ-ence in salinity and potential density between thelayers (p<0.001). The surface layer was characterizedby a wide range of salinity (29.08–38.33; avg. 36.32;SD 1.72) and potential density (20.91–29.23; avg.26.56; SD 1.6 kgm−3), and increased nutrients.Halocline, pycnocline and mixed layer depth wererecorded in 90 % samples in this layer, varied between1 and 6 m. The bottom layer was more stable withincreased salinity (35.5–38.62, exceptional minimumin April 34.38; avg. 37.77; SD 0.74) and potentialdensity (25.13–29.51; 27.7; SD 1.2 kgm−3). Lowersalinity values in the surface layer were observedduring periods of increased freshwater inflow.During 2002 the Neretva River showed an increasein flow in the winter–spring period but with an excep-tional peak in October (Fig. 2). Thus, in January,April, May and October, salinity was less than 34 inthe surface layer (Fig. 3). Below the halocline, salinity>38 was observed throughout most of the year. Waterdensity varied with salinity. Mixed layer depth coin-cided with the pycnocline. It was located in the surfacelayer throughout the year except in late May (9 m) andthe beginning of June (8 m). Secchi disc transparencyranged from 4.5 m in May to 12 m in January. As theeuphotic zone reached the bottom throughout thestudy, light availability was not a limiting factor forthe phytoplankton development.

There was no statistically significant variation (p>0.05) in water temperature between the layers (surfacelayer: 6.9–24.8; avg. 15.98; SD 4.68 °C and bottomlayer: 9.3–23.5; avg. 16.03; SD 4.01 °C), implying anisothermal water column for most of the year (Fig. 3). Athermocline was recorded in January (gradient 0.6–2 °Cm−1 in the surface layer), in May (gradient 0.9–1 °Cm−1

in the surface layer) and in the period from June toAugust (gradient 0.5–0.9 °Cm−1 in the bottom layer).

Fig. 2 Temporal variation of the Neretva River flow (m3/s)


The surface layer (O2/O2′: 0.82–10.9; avg. 1.63; SD1.12) was more saturated with oxygen (p<0.001) thanthe bottom layer (O2/O2′: 0.64–10.9; avg. 1.1; SD 0.93).NO3

−was the dominant form of nitrogen for most of theyear (contribution to TIN >50 % to 93.6 %).Concentrations of NO3

− in the surface layer (0.01–9.88; avg. 1.03; SD 0.92 μmoll−1) were higher (p<0.001) than in the bottom layer (0.01–2.9; avg.0.59;SD 0.33 μmoll−1). Concentrations of NO2

− during theyear were relatively low. NO2

− dominated the TIN(contribution >50 % to 62.9 %) in January and earlyFebruary in the bottom layer. Higher NO2

− concentra-tions (p<0.001) in the bottom layer (0.01–0.85; avg.0.19; SD 0.22 μmoll−1) than in the surface layer (0.01–0.75; avg. 0.15; SD 0.16 μmoll−1) were recorded formost of the year. NH4

+ (surface layer: 0.15–1.03; avg.0.44; SD 0.18 μmoll−1 and bottom layer: 0.03–0.99;avg. 0.43; SD 0.17 μmoll−1) dominated TIN in midJuly (contribution >59 % to 89.6 %). Concentrations ofPO4

3− were relatively low. Higher concentrations wererecorded in the surface layer (0.01–0.49; avg. 0.04; SD0.04 μmoll−1) than in the bottom layer (0.01–0.18; avg.0.04; SD 0.02 μmoll−1), but this difference was notstatistically significant (p>0.05). However, there wasa significant difference (p<0.001) in SiO4

4− concen-trations between surface (0.67–15.81; avg. 4.1; SD2.29 μmoll−1) and bottom layers (0.85–8.33; avg.3.74; SD 1.53 μmoll−1). Concentrations of SiO4

4−

>12 μmoll−1 were recorded in January and October.Chl a concentrations >1 μgl−1 were observed inMarch and April and in August (Fig. 3). Chl aconcentrations were higher (p<0.001) in the bottomlayer (0–1.83; avg. 0.6; SD 0.36 μgl−1) than insurface layer (0–1.54; avg. 0.48; SD 0.33 μgl−1).

Distribution of flow, physicochemical parametersand Chl a in different seasons and layers is shownby PCA plots (Fig. 4, Table 1). There was a significantcorrelation with the first three axes, and most of thevariance was explained by the first two (49.13 %).Axis 1 separates the winter–spring bottom sampleswith increased salinity and density from the surfacesamples with low salinity and increased NO3

−, SiO44−

and TIN. Axis 2 clearly separates winter samplesenriched with nutrients and with lower sea temper-atures from the summer nutrient-poor samples withhigher sea temperatures. Vectors of environmentalvariables showed that TIN and NO3

−, followed bysalinity and potential density are the most importantparameters that determine the distribution of samples.

The increase of nutrient concentrations was positivelycorrelated with increased of flow rate, and negativelywith the increase of temperature and salinity. Chl awas negatively correlated with flow and nutrient in-crease but positively with salinity.

Molar ratios of potentially limiting nutrientshave shown that the PO4

3− was a potential limitingnutrient for phytoplankton development throughmost of the period studied (Fig. 5). The relativelylow values of PO4

3− during the year (<0.1 μMl−1)contributed to the potential phosphate limitation in85 % of samples. Nitrogen limitation was recordedin periods of the lowest concentrations of NO3

−

and NO2− (mid-April, late May, mid-July and mid-

September). Redfield ratio of TIN/PO43− rangedfrom 2 in mid-September to 527 in late January.Redfield ratio ≥16 was recorded in 88 % of the samples.TRIX units were in the range of 1.25 in January,February and July to 3.78 in May. Values >3 wereobserved mostly in spring. TRIX index <4 indicates anoligotrophic water column throughout the year (Fig. 6).

Phytoplankton

Nanophytoplankton was the dominant phytoplanktongroup (Fig. 7) and their relative contribution to totalphytoplankton abundance was above 95 % for most ofthe year except in April (51 %). A greater proportion(p<0.001) of these abundances were in the bottomlayer (1.4×105–2.8×106; avg. 9.3×105; SD 4.6×105

cells l−1) than in the surface layer (1.1×105–1.7×106;avg. 6.2×105; SD 2.5×105 cells l−1). During the periodstudied, the nanophytoplankton is dominated by nano-flagellates <10 μm, and their relative contribution was≥80 % in the surface NANO and ≥90 % in the bottomNANO (Fig. 8). At the beginning of the year and inApril, an intensive development of nanocyanobacteria(Chroococcales) was recorded, with maximal abun-dance of 6.6×104 cells l−1 in January. In mid-Aprilthe highest abundance of microphytoplankton in2002 was recorded (Fig. 7) Microphytoplanktonabundances between the layers were not significant-ly different (p>0.05). In the surface layer (1.7×103–3.2×105; avg.1.1×104; SD 2.6×104 cells l−1) ahigher abundance of microphytoplankton wasrecorded in the period from April to the beginningof August, while in the remaining part of the yearit was in the bottom layer (2.2×103–3×104; avg.8.7×103; SD 4.6×103 cells l−1). Almost all nutrients


and flow negatively correlated with microphyto-plankton in the surface layer (Table 2).

Dinoflagellates dominate microphytoplanktonabundance most of the year (Fig. 9). There was anegative correlation of dinoflagellates with all thenutrients and the flow in both layers. The greatestincrease in dinoflagellate abundance was recorded in

mid-April (Fig. 10), due to intensive development ofProrocentrum minimum (Pavillard) J. Schiller (max.3×105 cells l−1) in surface layer. This taxon in thatperiod made the greatest contribution to microphyto-plankton abundance (95.1 %) but was also abundant inearly May in the same layer (max. 2.1×105 cells l−1)when it contributed 96.3 %. In the period of these two

Fig. 3 Spatio-temporal distribution of physicochemical parameters and chlorophyll a concentrations in the water column


blooms, significant positive correlations of P. mini-mum with NO3

−, TIN and SiO44− were observed (p<

0.05). Prorocentrum micans Ehrenberg in the surfacelayer and Scrippsiella spp. in the bottom layer, as wellas various unidentified armored dinoflagellates spp. inboth layers were the most frequent dinoflagellatesduring the year. The dominance of diatoms in bothlayers (Fig. 9) was observed in winter (January andDecember) and autumn (September and November).

Maximal abundance was found in mid-July in thesurface layer (3.7×104 cells l−1). Diatoms positivelycorrelated with NO3

−, NO2− and PO4

3− in the bottomlayer and negatively with NH4

+ in the surface layer(Table 2). The most abundant taxa were Chaetocerosaffinis Lauder (max. 1.5×104 cells l−1) in late March,Chaetoceros socialis H.S.Lauder (max. 1×104 cells l−1)in late April andChaetoceros spp. (max. 3×104 cells l−1)in mid May. Thalassionema nitzschioides (Grunow)

Fig. 4 Principal component analysis (PCA) of seasonal (a) and spatial distribution (b) of the environmental variables and Chl a for axis 1and 2 (N=401, cut-off r2 >0.2)


Mereschkowsky and various undetermined pennate dia-toms spp. were the most frequent diatoms during theyear in both layers. The highest relative contribution ofcoccolithophorids in microphytoplankton abundance

was recorded in mid-March in both layers (Fig. 9), dueto more intensive development of Calyptrosphaeraoblonga (max. 1.8×104 cells l−1). Syracosphaera pul-chra Lohmann in surface layer, and Calciosolenia

Table 1 Relative explainedvariance and correlation coeffi-cients of PCA analyses for thefirst three significant axes

Variable Axis 1 Axis 2 Axis 3

Eigenvalue 3.665 2.722 1.553

% of variance 28.189 20.938 11.943

Cumulative % of variance 28.189 49.128 61.070

p for 999 randomizations 0.001 0.001 0.001

Correlation coefficient:

Teperature (T) −0.4115 0.6272 −0.3768Salinity (S) −0.3773 −0.7646 −0.1641Density (sigma-t) −0.0374 −0.9537 0.1115

Oxygen saturation (O2/O2′) −0.4025 0.5416 0.3532

Nitrate (NO3) 0.8747 0.3177 0.0396

Nitrite (NO2) 0.3455 −0.5799 −0.2934Amonium (NH4) 0.3957 −0.1153 0.1851

Total inorganic nitrogen (TIN) 0.9482 0.1192 0.0053

Phosphate (PO4) −0.1601 0.1930 −0.5987Silicate (SiO4) 0.6947 0.1229 −0.3256Redfield ratio (TIN/PO4) 0.6920 0.0140 0.4555

Chlorophyll a (CHL a) −0.2267 −0.0458 0.6120

Flow 0.4591 −0.1475 −0.2794

Fig. 5 Si/N/P [SiO44−/

(NO3−+NO2

−+NH4+)/

PO43−] molar ratios in the

Usko station. Molar quotientsbetween in situ concentra-tions of potentially limitingnutrients are delimited bySi/N=1, N/P=16 and Si/P=16 lines. Lines define sixdifferent areas within the plot,each characterized by a po-tentially limiting nutrient inorder of priority (Rochaet al. 2002). Only the dateswhen N limitation occurredare marked


brasiliensis (Lohmann) J.R. Young in the bottom layer,as well as various unidentified coccolithophorids spp. inboth layers were the most common coccolithophoridsduring the year. The highest relative contribution offilamentous cyanobacteria in microphytoplankton wasin mid-February in the surface layer (20 %) and lateAugust in the bottom layer (22 %). Filamentous cyano-bacteria were negatively correlated with salinity andwere most abundant in the period of increased freshwa-ter inflows (max. 1.2×104 cells l−1 in February). Amongother groups, silicoflagellates and desmids were signif-icantly present in the winter, euglenophytes in springand summer, and the green planktonic algae in springand autumn. Silicoflagellates were present only in thewinter period in the surface layer, as shown by a negativecorrelation with temperature and salinity. The contribu-tion of other groups together in the microphytoplanktonabundance did not exceed 5 % in either layer. Significantabundance occurred of planktonic freshwater greenalgae Scenedesmus quadricauda (Turpin) Brébisson,which intensively developed in mid-May (max. 1×104

cells l−1). A total of 271 taxa were recorded in 462analyzed samples.

Zooplankton

Protozoans showed a greater (p<0.05) number of indi-viduals in the bottom layer (1–3,050; avg. 277; SD 468ind. l−1) than in the surface layer (1–731; avg. 178; SD164 ind. l−1). Nonloricate ciliates were dominant organ-isms in winter–spring (Fig. 11) with maximum inMarch(surface layer: 569 ind. l−1, bottom layer: 581 ind. l−1).FromMay to December, their abundances were uniformand low. Abundances of tintinnids showed two peaks.

The first occurred in mid-February (surface layer: 602ind. l−1, bottom layer: 503 ind. l−1), when the dominantspecies Tintinnopsis nana Lohmann reached a maximalabundance of 1,096 ind. l−1. The summer populationbegan to increase in July, with a maximum in lateAugust. In winter they were evenly distributed in thewater column, while during summer their abundanceswere mostly greater in the bottom layer.

Micrometazoans also showed a greater (p<0.05)number of individuals in the bottom layer (9–520;

Fig. 6 The distribution of TRIX index at Usko station

Fig. 7 Annual distribution of nanophytoplankton (NANO) andmicrophytoplankton (MICRO) abundances (cells l−1) in the wa-ter column


avg.75; SD 86 ind. l−1) than in the surface layer (4–430;avg. 49; SD 68 ind. l−1). All herbivorous copepods andtheir nauplii were abundant during warmer period with amaximum in the end of August. Maximum of nauplii(surface layer: 245 ind. l−1, bottom layer: 339 ind. l−1),calanoids (surface layer: 15 ind. l−1, bottom layer: 20ind. l−1) and cyclopoids (surface layer: 143 ind. l−1,bottom layer: 159 ind. l−1) were in the bottom layer,with a predominance of Paracalanus parvus Claus andOithona nana Giesbrecht.

Zooplankton distribution followed the distributionof phytoplankton. There was a statistically significantnegative correlation with the nanophytoplankton, dia-toms and other exclusively marine microphytoplank-ton groups (Table 3).

Discussion

The results presented in this study indicate that Mali StonBay is a highly complex coastal Adriatic basin wherefrequent fluctuations of physicochemical parameters are

reflected in the structure and dynamics of the phytoplank-ton community. A temperature gradient in the watercolumn was not present most of the year, but fluctuationsin salinity and density were significant. In the winter,spring and autumn the impact of freshwater inflow in-creased, creating a surface layer of lower salinity anddensity. The winter increase in salinity and density inthe bottom layer is most likely to be due to water inputfrom the open sea. Characteristics of the southernAdriatic surface water mass (0–200 m) in winter (T~14°C, S>38.2, sigma-t~29.2 kgm−3) coincide with theproperties of water in the lower part of water column atUsko station (Manca et al. 2002; Viličić et al. 2010;Batistić et al. 2011). The summer increase in salinitythroughout the water column is caused by the interactionof several factors, such as high air temperature and evap-oration, low precipitation and lack of submarine activity.Nutrient concentrations were relatively low, compared toother coastal ecosystems in the South Adriatic (Carić etal. 2012; Jasprica et al. 2012) and temporally related tothe inflow of fresh water. Important sources of nutrientswere the “vruljas” and precipitation in winter–spring and

Fig. 8 The relative contri-bution (%) of observed sizefractions in nanophyto-plankton abundance in theboth layers. Small nanofla-gellates <10 μm (SNFL),large nanoflagellates 10–20 μm (LNFL), small nano-coccolithophorids <10 μm(SNC), large nanococcoli-thophorids (LNC) andchroococoid cyanobacteria2–20 μm (NCC)


the Neretva River in the autumn. This is indicated by thehigher nutrient concentrations in the surface layer andtheir negative correlation with salinity. The ratio betweenthe molar concentrations of TIN and PO4

3− (Redfieldratio) was significantly higher than 16 for most of theyear, indicating that phosphate was a potential limitingfactor for phytoplankton development. Phosphate limita-tion of the development of primary producers is a char-acteristic phenomenon in different ecosystems in theAdriatic (e.g., Bernardi Aubry et al. 2004; Viličić et al.2008; Ivančić et al. 2010; Carić et al. 2011) and in theMediterranean (e.g., Tanaka et al. 2009; Krom et al.2010).

On the basis of the ecosystem classification accord-ing to the frequency distribution of phytoplankton

abundance (Viličić 1989), in 2002 the bay can beincluded in the first category of ecosystems with alow trophic level. This is contrary to the findings ofViličić et al. (1998), who have defined Mali Ston Bayas a moderate naturally eutrophicated ecosystem. Wehypothesize that environmental changes in the lastdecades have had an impact on the trophic state ofthe bay. TRIX analysis confirmed the oligotrophicstatus, where indexes lower than 4 indicate low pro-ductive coastal areas in the Adriatic (Giovanardi andVollenweider 2004; Pettine et al. 2007; Rinaldi andGiovanardi 2011). According to the slight signs ofdisturbance of phytoplanktonic composition and abun-dance as well as the slight increase in the frequencyand intensity of the type-specific planktonic blooms,

Table 2 Correlation matrix of the environmental variables and the major phytoplankton groups in the both layers (N=198 for thesurface layer and N=222 for the bottom layer)

MICRO NANO BACI DINO COCC CYAN EUGL CHLO DYCT ZYGN

0–6 m

T − −0.37 − − − − − − − −S −0.14 – − − − − − − − −φ −0.15 0.27 − − − − − − − −O2/O2′ − 0.15 − − − − − − − 0.14

NO3 −0.24 − − −0.23 − − − − − 0.18

NO2 −0.30 − − −0.27 − − − − 0.22 0.19

NH4 −0.21 0.18 −0.14 −0.18 − − − − − −PO4 − −0.37 − −0.15 − − − − − −SIO4 −0.31 − − −0.31 − − −0.18 − − −TIN/PO4 −0.14 0.28 − − − − − − − −CHL a 0.41 0.35 − 0.45 − − − − − −FLOW −0.18 − − −0.19 0.19 − −0.15 − − −7−13 m

T −0.19 −0.43 −0.18 − − − 0.14 − −0.18 −S − −0.27 − − − −0.14 − − −0.29 −φ − −0.26 − − − −0.14 − − −0.29 −O2/O2′ − −0.25 − − − − − − −0.23 −NO3 − −0.16 0.19 −0.16 0.21 − − − − −NO2 − − 0.21 −0.13 −0.17 − − − − −NH4 − 0.23 − −0.15 − − − − − −PO4 − − 0.14 −0.14 − − 0.24 − − −SIO4 −0.19 0.14 − −0.36 − − −0.17 0.15 − −0.18TIN/PO4 − 0.17 − − − − −0.14 − − −CHL a 0.29 0.29 − 0.31 − − − − − −FLOW − − − −0.23 − − − − − −

Only the statistically significant correlations (p<0.05) are shown


the bay had good ecological status (EU WFD 2000).Low nutrient concentrations were not significantlydifferent from other oligotrophic areas of the SouthAdriatic (Šilović et al. 2011; Batistić et al. 2011) andEastern Mediterranean (Karydis 2009; Denis et al.2010). Furthermore, oligotrophic status at Usko isindicated by high water transparency and biodiversi-ty of phytoplankton, as also recorded at other shell-fish sites in the Northern Adriatic (Tomec 2004), aswell as by low nutrient and chlorophyll a concen-trations, as recorded at mussel sites in the oligotro-phic Mediterranean area (Sara et al. 2009).

Our data reveals a significant difference in theannual phytoplankton succession and communitystructure as compared with earlier data. In previousstudies in Mali Ston Bay a maximum of 195 phyto-plankton taxa was recorded, and diatoms were identi-fied as the dominant group in terms of both number oftaxa and abundance (Viličić et al. 1998). In this studythe number of taxa has almost doubled, which couldbe due to the frequent sampling and the fine spatialscale. Also, dinoflagellates were found to dominate inabundance and taxonomic composition. Taxa of

cyanobacteria, green algae and desmids were recordedfor the first time in the bay. The seasonality of phyto-plankton during the study period was bimodal andassociated with seasonal temperature changes that arecharacteristic for the Mediterranean climate zone(Cushman-Rosin et al. 2001). It does not differ fromthe usual phytoplankton distribution in the Adriatic(Totti et al. 2000; Ninčević-Gladan et al. 2009) andtemperate zones (Winder and Cloern 2010) where astronger spring increase in abundance is expected. Inaccordance with the strategy described by Margalef etal. (1979) phytoplankton succession at Usko stationbegins with the development of small cells (R-taxa):nanophytoplankton, cyanobacteria, small diatoms anddinoflagellates, followed by intensive blooms of onetaxon (P. minimum) in spring, and ends with the de-velopment of the large (K-taxa) dinoflagellates cells insummer that were then replaced by diatoms in autumn.

Nanophytoplankton dominated phytoplanktonabundance and mostly consisted of flagellates smallerthan 10 μm which are the dominant group of primaryproducers in oligotrophic systems in the Adriatic (Tottiet al. 2000; Boldrin et al. 2002; Viličić et al. 2009;

Fig. 9 The relative contri-bution (%) of the majorphytoplankton groups inmicrophytoplankton abun-dance in the both layers.Diatoms (BACI), dinoflagel-lates (DINO), coccolitho-phorids (COCC),filamentous cyanobacteria(CYAN) and together silico-flagellates, green planktonicalgae, euglenophytes anddesmids (OTHERS)


Cerino et al. 2011). More intensive development ofnanophytoplankton was recorded in winter–spring pe-riod and has been confirmed with a negative correla-tion with temperatures in each layer. This differs fromearlier findings which described intensive nanophyto-plankton development in spring, summer and autumn.During our study greater nanophytoplankton abundanceswere observed in the lower, more stable part of the watercolumn, under high salinity and density conditions. This

indicates that the nanophytoplankton population is most-ly composed of open sea taxa.

The increase in microphytoplankton abundanceduring our study was in spring and autumn, whichdiffers from the results for the period 1979–1989(Viličić et al. 1998). These authors report two annualincreases in microphytoplankton abundance: in boththe spring–summer and summer–autumn periods. Thesummer increase in microphytoplankton abundance

Fig. 10 Annual distributionof abundances (cells l−1) ofmajor microphytoplanktongroups expressed as thewater column mean for eachlayer. Diatoms (BACI),dinoflagellates (DINO),coccolithophorids (COCC),filamentous cyanobacteria(CYAN) and together silico-flagellates, green planktonicalgae, euglenophytes anddesmids (OTHERS)


was not observed in this study and that is most likelydue to the very low nutrient concentrations at the time.

An intense spring increase in microphytoplanktonabundance mostly occurred in the surface layer and

Fig. 11 Annual distribution of abundances (individuals l−1) ofmajor zooplankton groups expressed as the water columnmean for each layer

Table 3 Correlation matrix of the major zooplankton groups (protozoans and micrometazoans) and the major phytoplankton groups inthe both layers (N=33)

MICRO NANO BACI DINO COCC CYAN DYCT EUGL CHLO ZYGN

0−6 m

Nonloricate ciliates − − − 0.41 − − −0.48 − − −Tintinnids −0.45 − −0.52 − − − − − − −Copepod nauplii − − − − − − − − − −Calanoids − −0.55 − − − − − − − −Cyclopoids − −0.56 − − − − − − − −7−13 m

Nonloricate ciliates − − − 0.44 − − − − − −Tintinnids −0.35 − −0.55 − − − − −0.37 − −Copepod nauplii −0.47 − −0.37 − − − − − − −Calanoids −0.53 −0.35 −0.48 − − − − − − −Cyclopoids −0.44 − − − −0.36 − − − − −

Only the statistically significant correlations (p<0.05) are shown


this indicates an optimum availability of nutrients dueto the freshwater influx, as well as a sufficient amountof light and favourable temperature conditions.Autumn microphytoplankton increase in abundanceis most likely a result of intensive regeneration pro-cesses in the bottom layer of the water column.Phytoplankton cells immediately take advantage ofre-suspended nutrients which result in their depletionin September. Microphytoplankton was mainly com-posed of dinoflagellates, diatoms and coccolithophor-ids, while the proportion of filamentous cyanobacteriaand other groups was insignificant.

In terms of the number of taxa and abundance,dinoflagellates were the dominant microphytoplank-ton during the year and were the main component ofthe increased abundance in spring. Intensive develop-ment of dinoflagellates began in late March, mostly inthe surface layer of the water column, at temperaturesof 13–19 °C. Such a distribution differs from theresults of Jasprica (1989), where the maximum devel-opment of dinoflagellates at Usko station was in earlysummer when sea temperatures exceeded 20 °C. Anegative correlation of dinoflagellates with flow inboth layers indicates that their distribution does notdepend on the influx of nutrients. Thus, dinoflagellateabundance was negatively correlated with all nutrientsthroughout the water column, which indirectly indi-cates an intensive consumption of these, and a domi-nance of heterotrophic and mixotrophic taxa. Manydinoflagellate taxa can develop under nutrient-limitedconditions due to a variety of physiological adapta-tions and specific mechanisms for their more efficientutilization (Baek et al. 2009; Van Mooy et al. 2009;Ivančić et al. 2010). There is more research showingthat phosphate limitation increases toxin productionby HAB dinoflagellate species (Maestrini et al. 2000;Lim et al. 2010). This is significant for Mali Ston Baybecause during the spring period (April and May)blooms of the harmful dinoflagellate P. minimum wererecorded. This cosmopolitan dinoflagellate oftencauses toxic blooms in areas under a stronger influ-ence of freshwater inflows (Grzebyk and Berland1996; Heil et al. 2005). The two blooms at Uskooccurred under conditions of increased temperature(>16°C) and lower salinity (34–36) in the surfacelayer. However, red tides and shellfish poisoning inhumans have not been recorded. The abundances of P.minimum in spring 2002 were the highest noted sinceecological research in Mali Ston Bay began. During

previous studies the maximum abundance of P. mini-mum in the bay did not exceed 80 cells l−1 (Viličić etal. 1998).

Diatoms dominated the microphytoplankton atthe beginning of the year (January–February), inSeptember, and again at the end of the year(November–December). A negative correlation withtemperature and a positive correlation with inorganicnitrogen explain their distribution in the colder part ofthe year. In winter the supply of nutrients increased,primarily NO3

− and SiO44−, which allowed a more

intensive development of diatoms (Bode and Dorch1996; Hoffmann et al. 2008). Such a trend is observedin other coastal areas of the Southern Adriatic (Caroppoet al. 2003; Carić et al. 2012). More intensive diatomdevelopment in September was enabled by the increasedtemperature (>15 °C), which facilitated the process ofremineralization of organic nitrogen, phosphorus andbiogenic silica, thus enriching the water column withnutrients (Yamada and D’Elia 1984; Jahnke et al. 2005).The increase in diatom abundance in September causeda decrease in the SiO4

4− concentration in almost theentire water column. However, SiO4

4− concentrationsduring the studied period were above the half-saturationconstant typical for coastal diatoms, and their develop-ment could not have been silicate-limited (Carlsson andGranéli 1999; Granéli et al. 1999). On the other hand,recent studies showed that diatoms can be nutrient lim-ited under concentrations much higher than the half-saturation constants and it is mainly related to the N-limitation (Domingues et al. 2011).

Coccolithophorids were most abundant in midMarch when they dominated the microphytoplankton(>50 %), and over the year have been observed pre-dominantly in the bottom layer as they favour morestable hydrological conditions with higher salinity(Viličić et al. 2008). Coccolithophorids are importantgroups of phytoplankton in the Ionian Sea (Boldrin etal. 2002; Malinverno et al. 2003), and their distributionin the bay may be an indicator of increased entry ofwater masses from the Mediterranean. Filamentous cya-nobacteria, silicoflagellates and desmids were abundantin the period of increased freshwater inflows. It isknown that the distribution of silicoflagellates is mostlyrelated to the winter–spring period, the cold water mass,and the impact of river inflow (Rigual-Hernández et al.2010). Desmids are exclusively freshwater forms(Baytut et al. 2005), and a greater abundance inSeptember and December suggests their inflow origin.


Euglenophyte abundance was observed to increase withthe temperature, as is found in estuaries and coastalwaters of the Eastern Adriatic in summer and autumn(Viličić et al. 1995; Šolić et al. 2010). Although the areais strongly influenced by the “vruljas” and NeretvaRiver inflow, freshwater phytoplankton are poorly rep-resented. The cause of this is most likely the mortality offreshwater species, mostly diatoms, due to osmoticshock (Burić et al. 2007).

Phytoplankton abundance is an indicator of environ-mental carrying capacity (food availability) for higherlevels of the trophic chain. In 2002, phytoplankton abun-dance at Usko was effectively controlled by herbivorouszooplankton predation, especially nanophytoplanktonand diatoms. There is a much greater predation pressureon diatoms, which may explain the dominance of dino-flagellates at Usko during the study period (Thompson etal. 2008). Larger copepods, such as calanoids and cyclo-poids mainly use diatoms as a food source (Head andHarris 1994; Mauchline 1998; Sakka Hlaili et al. 2007),and naupliar stages also feed mostly on autotrophs(Finlay and Roff 2004). Therefore we can assume thatthe abundance of nanophytoplankton and diatoms aremore controlled by herbivorous zooplankton predation(‘top–down’) than other groups of microphytoplanktonthat are more controlled by physicochemical conditionsin the bay (‘bottom–up’). Low TRIX indices during theyear indirectly indicate an intensive grazing activity inthe bay. It is most significant in January and Februaryinthe period of the greatestabundances of protozoans, andin July when micrometazoans were abundant. The high-est TRIX index in May was followed by the very lowabundances of all studied zooplankton groups.

On the other hand, Mali Ston Bay is a very impor-tant area for shellfish cultivation, which exerts a strongpredation pressure on phytoplankton populations.Changes in phytoplankton composition and reductionof abundance, as well as altered trophic status of thebay could be a consequence of an aquaculture overca-pacity in the ecosystem. It is assumed that the expan-sion of bivalve mollusc aquaculture in recent yearscould affect the phytoplankton community structureand abundance since phytoplankton is a main compo-nent in molluscs’ diet (Baker et al. 1998; Davenport etal. 2011). It is estimated that, since 20 years ago whenthe last phytoplankton survey was carried out, shell-fish production has doubled (Bratoš et al. 2004). Thepossibility of over-intense aquaculture is also indicat-ed by the dominance of dinoflagellates over diatoms,

which are the main food source for shellfish (Pernet etal. 2012). A once ecologically stable ecosystem withoutexcessive phytoplankton blooms (Viličić et al. 1994)now becomes a potentially impoverished area for shell-fish aquaculture with attendant risks of harmful algalblooms. Unfortunately, there has been no proper moni-toring of phytoplankton composition and abundance inthe last decades, so it is not possible to make a precisescientific assessment of the effect of aquaculture on thephytoplankton community in the bay.

Conclusion

Seasonal succession of phytoplankton in Mali Ston Baywas primarily controlled by thermohaline conditionscombined with TIN. Furthermore, grazing had an impor-tant role in controlling mostly nanophytoplankton anddiatom distribution, while other microphytoplanktongroups were more driven by physicochemical conditions.Differences from previous studies of phytoplankton com-munity structure were observed, indicating the impact ofshellfish farming. Further studies are required to establishthe linkages between phytoplankton succession patternsand aquaculture, especially the potential threat from toxicphytoplankton taxa and the long-term impact of anyfurther increase in breeding capacity. These results con-tribute to further comparative analyses in the bay: iden-tification of the dominant processes that are the causechanges in environmental condition and in phytoplank-ton community structure, and how all of those arereflected to the changes of trophic status in thisecosystem.

Acknowledgments This research was supported by the CroatianMinistry of Science, Education and Sports through projects0001001 and 275-0000000-3186. The authors are grateful to Dr.Zrinka Ljubešić and Dr. Ivona Cetinić for statistical instructions anduseful comments that greatly improved the manuscript. We wouldlike to thank Professor Steve Latham for improving the English.Principal author is grateful to colleague Ana Car who assisted inediting the manuscript. Thanks to technicians of Institute forMarineand Coastal research for sampling assistance.

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