Hostname: page-component-848d4c4894-v5vhk Total loading time: 0 Render date: 2024-07-01T07:56:38.419Z Has data issue: false hasContentIssue false

Determination of seasonal changes in phytoplankton community of the coastal waters of Burgaz Island (the Sea of Marmara)

Published online by Cambridge University Press:  06 July 2022

Yorgo Kayadelen
Affiliation:
Institute of Science, Istanbul University, 34134 Vezneciler, Istanbul, Türkiye
Neslihan Balkis-Ozdelice*
Affiliation:
Faculty of Science, Department of Biology, Section of Hydrobiology, Istanbul University, 34134 Vezneciler, Istanbul, Türkiye
Turgay Durmus
Affiliation:
Faculty of Science, Department of Biology, Section of Hydrobiology, Istanbul University, 34134 Vezneciler, Istanbul, Türkiye
*
Author for correspondence: Neslihan Balkis-Ozdelice, E-mail: neslbalk@istanbul.edu.tr
Rights & Permissions [Opens in a new window]

Abstract

The aim of this study is to determine the phytoplankton species found on the shores of Burgaz Island and the basic ecological variables that affect their seasonal distribution between May 2013 and February 2014. Water samples were collected from four stations at six different depths and plankton samples were gathered horizontally and vertically. The analysis of phytoplankton community composition revealed 101 phytoplankton taxa belonging to five classes. As a result of the study, two taxa belonging to the Dinophyceae (Corythodinium frenguellii and Gonyaulax scrippsae) were new records for Turkish coastal waters. Additionally, a taxon belonging to Dinophyceae (Pronoctiluca pelagica) and a taxon belonging to Bacillariophyceae (Nitzschia reversa) were new records for the Sea of Marmara. Prorocentrum micans, was the dominant species throughout all sampling periods. During the study, the highest phytoplankton abundance was observed at 0.5 m depth in May 2013 (138,500 cells l−1) and February 2014 (52,620 cells l−1). Primary ecological variables, such as temperature (9.0–21.5 °C), salinity (15.23–37.22‰) and dissolved oxygen (4.89–15.84 mg l−1), were recorded on each sampling occasion. In addition, nitrite + nitrate–N (NO2 + NO3–N) (0.01–7.37 μg-at N l−1), phosphate (PO4–P) (0.05–51.95 μg-at P l−1) and silicate (SiO4–Si) (0.01–0.20 μg-at Si l−1) concentrations were measured. Chlorophyll a and suspended material values ranged between 0.01–3.17 μg l−1 and 10.0–61.5 mg l−1, respectively. Spearman's rank correlation was used to determine the relationship between phytoplankton species and ecological variables, and Bray–Curtis analysis and Euclidean distance were applied to bring out the similarity between stations.

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press on behalf of Marine Biological Association of the United Kingdom

Introduction

In order to learn about the ecological status of a region, it is necessary to know the ecological variables that affect the species composition and distribution of phytoplankton, which have the ability to reflect changes in the ecosystem very quickly (Balkis, Reference Balkis2003). For this purpose, although the first research on plankton was related to the determination and systematics of the species, today the number of ecological studies that reveal their relationship with productivity in the sea has increased. In addition, studies on the reproduction of species and cyst distribution in the sediment were carried out in Türkiye (Aydın et al., Reference Aydın, Balcı, Uzar and Balkis2015; Balkis et al., Reference Balkis, Balcı, Giannakourou, Venetsanopoulou and Mudie2016).

The Sea of Marmara, which is divided into three sub-basins, each deeper than 1000 m in the east-west direction from the topographical direction, is a semi-closed inland sea between the Mediterranean and the Black Sea, with a surface area of 11,500 km2 and a maximum depth of 1390 m. Connected to the Black Sea by the Bosphorus and to the Aegean Sea by the Dardanelles, the Sea of Marmara is a transition zone from the Mediterranean to the Black Sea. This feature causes both sea traffic to be intense and for it to have two water layers with different salinities. These waters with different salinities reaching the Sea of Marmara form an intermediate salinity layer at a depth of ~25 m due to their different densities, and dissolved oxygen-rich surface waters are largely prevented from mixing with the lower layer. The upper layer water with low salinity that comes from the Black Sea increases both the amount of organic matter and the pollution in the Sea of Marmara. Bottom layer water with high salinity contains low oxygen as a result of the decomposition of biogenic particles coming from the upper layer. The oceanographic conditions in this sea are controlled by the two straits (Yüce, Reference Yüce1988; Yüce & Türker, Reference Yüce and Türker1991; Beşiktepe et al., Reference Beşiktepe, Sur, Özsoy, Abdul Latif, Oğuz and Ünlüata1994, Reference Beşiktepe, Özsoy, Latif, Oğuz, Öztürk, Kadıoğlu and Öztürk2000). In this environment where oxygen intake from the surface is prevented and oxygen consumption increases in the lower layer, the oxygen level is regulated by the Mediterranean water content which has high salinity and rich oxygen level (Beşiktepe et al., Reference Beşiktepe, Özsoy, Latif, Oğuz, Öztürk, Kadıoğlu and Öztürk2000). In the Sea of Marmara, which has a two-layered water system, vertical mixing is limited. As a result, the dissolved oxygen content of the lower layer water decreases from the Dardanelles to the Bosphorus. Although the surface water in the upper layer is saturated with oxygen, it varies according to the water temperature and season.

As a result of industrial development and the population increase that follows, the discharge of domestic and industrial wastes to the Sea of Marmara, the rapid increase in agricultural activities, industrial activities, tourism, fishing and sea transportation are the elements that threaten marine life. In developing countries such as Türkiye 90% of household waste and 70% of industrial wastes are discharged into coastal areas without applying any treatment (Creel, Reference Creel2003; United Nations World Water Assessment Programme, 2018). The pollution load into the Sea of Marmara from Istanbul is also high (Öztürk et al., Reference Öztürk, Dülekgürgen, Erşahin, Öztürk and Şeker2021). Marine ecosystems can tolerate wastes with a certain load and eliminate these wastes after a while. In semi-closed seas such as the Sea of Marmara, these wastewater discharges increase the pollutant load and this may cause eutrophication. Suitable environmental conditions with increased nutrients can lead to phytoplankton blooms. Among the species in the phytoplankton community, those that adapt best to the environment can become dominant and multiply enough to change the colour of the seawater and create the phenomenon called red-tide. Continuity of the excessive increase in organic load in the water column may cause the accumulation of organic matter in the sediment, and the decomposition of this organic matter can create an anoxic environment in the bottom waters and negatively affect benthic life.

Despite being a small inland sea, the Sea of Marmara has many islands of all sizes. The island community consisting of nine islands and two cliffs, called the Prince Islands, is located in the north-east of the Sea of Marmara, very close to Istanbul. From the upper layer current entering the Sea of Marmara through the Bosphorus, the eastern current extending to the south and the Gulf of Izmit is formed and this flow affects the region that includes the Prince Islands. Due to the large volume of the Sea of Marmara and the long hydraulic residence time of the water in this sea, pollutants can stay in this environment for a long time and pose serious dangers in terms of the ecosystem, especially when considering pollutants with a bioaccumulation character (Taşdemir, Reference Taşdemir2002).

Burgaz Island, where the study was carried out, is the third largest island of the Prince Islands with a surface area of 1.5 km2 and a coastline of 5.7 km. Since there is no comprehensive study on current phytoplankton communities and their relationships with ecological variables at Burgaz Island, the main purpose of this study is to define phytoplankton species and their abundance and determine the ecological variables that affect the distribution of these species around the island.

Materials and methods

Samples were collected seasonally at four stations selected around the island's periphery (Figure 1) from six different depths (0.5, 5, 10, 15, 20 and 30 m) between May 2013 and February 2014 by a fishing boat. During the sampling periods, all samples were collected on the same day. A 3-litre Ruttner water sampler with a thermometer was used for water analyses. The salinity of the seawater was determined by the Mohr–Knudsen method (Ivanoff, Reference Ivanoff1972) and the amount of the dissolved oxygen in the seawater by the Winkler method (Winkler, Reference Winkler1888). For the nutrient samples, samples were collected in polyethylene bottles with a volume of 100 ml and frozen in a deep freezer at −20 °C. Nitrite + nitrate–N (NO2 + NO3–N) samples were analysed by a Bran + Luebbe AA3 auto analyser (APHA, 1999), phosphate-P (PO4–P) and silicate-Si (SiO4–Si) analyses were detected by the methods described by Parsons et al. (Reference Parsons, Majita and Lalli1984). To determine the chlorophyll a concentration in the seawater, samples were taken with polyethylene bottles with a volume of 1-litre and filtered onto membrane filters (pore size: 0.45 μm), then analyses were carried out using the acetone extraction method according to Parsons et al. (Reference Parsons, Majita and Lalli1984). Suspended solid materials (SSM) of water samples were calculated according to the gravimetric 2540-D standard method (APHA, 1999).

Fig. 1. Study area and sampling stations of Burgaz Island.

Samples for phytoplankton identification were collected horizontally (the speed of the boat was 1–2 miles per hour for 10 min in each station) and vertically (30 m depth to surface) from the water column by using plankton nets with a mesh size of 40 μm and immediately fixed by the addition of borax-buffered formaldehyde solution (2–4%). In order to determine phytoplankton abundance, seawater samples taken from 0.5, 15 and 30 m depths in 1-litre polyethylene dark bottles were preserved with acidified Lugol's iodine solution (Throndsen, Reference Throndsen and Sournia1978). After sample sedimentation, excess water in the upper part was removed and concentrated to 100 ml, then to 10 ml (Sukhanova, Reference Sukhanova and Sournia1978) and 1 ml of the concentrated samples were counted. Phytoplankton enumeration was carried out in a Sedgewick–Rafter counting chamber of 1000 squares of 1 ml, 20 × 50 mm in size (Semina, Reference Semina and Sournia1978) under an ‘Olympus CK2’ model phase-contrast inverted microscope.

MarBEF data system, World Register of Marine Species (WoRMS) and sources mentioned by Balkis (Reference Balkis2003) were used for the identification, systematics and current nomenclature of the detected species. The relation between the species and cell numbers of phytoplankton and the ecological variables were evaluated using Spearman's rank correlation coefficient in SPSS 17.0 software (Siegel, Reference Siegel1956). The similarity between sampling stations in terms of the species abundance was calculated using the Bray–Curtis similarity index in Primer v6 software, based on [log (x + 1)] transformation (Clarke & Warwick, Reference Clarke and Warwick2001). Euclidean distance was used for the similarity between the stations in terms of environmental variables (Clarke & Warwick, Reference Clarke and Warwick2001). In addition, species diversity was estimated using Shannon–Weaver diversity index (Zar, Reference Zar1984).

Results

Ecological variables

During sampling periods, water temperature ranged from 9.0 °C (February 2014) to 21.5 °C (August 2013) (Table 1, Figure 2). In the samples of May and August 2013, it was determined that the temperature values of the upper layer water of Black Sea origin were higher than the water temperature values at 20–30 m depths. In November and February sampling, higher temperature values were reached at 30 m depth where Mediterranean-origin waters were dominant. In the study, salinity values varied between 15.2‰ (August 2013) and 37.2‰ (November 2013) and the highest value was measured at 30 m depth where Mediterranean water was dominant (Table 1, Figure 2). Dissolved oxygen values in water began to decrease especially at a depth of 20 m and varied between 4.89 mg l−1 (May 2013) and 15.84 mg l−1 (August 2013) (Table 1, Figure 2).

Fig. 2. Seasonal variations of ecological variables along the water column. Data are reported as averages of the sampling stations.

Table 1. The minimum and maximum values of ecological variables in Burgaz Island during the sampling periods

Among the nutrients, NO2 + NO3–N values ranged between 0.01–7.37 μg at N l−1, the amount of PO4–P between 0.05–51.95 μg at P l−1, the amount of SiO4–Si between 0.01–0.20 μg at Si l−1. All through the study, the values in the bottom water were higher than the surface layer (Table 1, Figure 2). Especially in May 2013, very high phosphate-P values were obtained at 10 and 15 m depths of station 2. The suspended solid material (SSM) values of the water were between 10.0–61.5 mg l−1 in the study, the lowest value was obtained in August 2013 and the highest value was obtained in May 2013 (Table 1, Figure 2). While chlorophyll a values were measured between 0.01–3.17 μg l−1, they showed a decreasing trend from the surface to a depth of 30 m throughout the study.

Phytoplankton species diversity and abundance

From the analysis of phytoplankton community composition in the Burgaz Island, 101 taxa of five different algal groups were identified: 49 dinoflagellates (48.5%), 47 diatoms (46.5%), three dictyochophyceans (3%), 1 pyramimonadacean (1%) and 1 (1%) cyanophycean (Table 2). Two dinoflagellate species (Corythodinium frenguellii and Gonyaulax scrippsae) were new records for the Turkish seas and two species (Pronoctiluca pelagica from dinoflagellates and Nitzschia reversa from diatoms) for the Sea of Marmara. The highest number of species was obtained in May (64 taxa) and August 2013 (66 taxa) representing the warm period. While 33 of 101 taxa obtained were encountered in all seasons, 31 of them were found only in the single sampling period. Dinoflagellates were the most common group in all sampling periods in terms of number of species.

Table 2. List of phytoplanktonic taxa of the coastal waters of Burgaz Island

*Indicates new record species in the Turkish seas, **indicates new record for the Sea of Marmara.

The cell numbers of phytoplankton species detected in the water column of the stations were determined and are presented in Figure 3. In the May 2013 sampling period, the highest number of cells (138,500 cells l−1) was obtained at 0.5 m depth in station 3 and the lowest cell number (4460 cells l−1) was obtained at 30 m depth in station 4. Dinoflagellates were dominant at all stations and depths, and the most dominant species was Prorocentrum micans. During the sampling period of August 2013, the highest cell number (1930 cells l−1) was obtained at 15 m depth at station 1, while the lowest cell number (120 cells l−1) was obtained at 30 m depth at the same station. It is noteworthy that diatoms decreased in terms of species and cell number with the increase in temperature during this period.

Fig. 3. Seasonal variations in the abundance (cells l−1) of different phytoplankton taxonomic groups at the stations.

During the November 2013 sampling period, the highest cell number (7060 cells l−1) was determined at 15 m depth at station 3, and the lowest cell number (270 cells l−1) at station 4 at 30 m depth. While Prorocentrum micans was determined as the species with the highest number of cells at all stations and depths, an increase was observed in the cell numbers of Tripos furca and Tripos fusus. In February 2014, the last sampling period of the study, the highest cell number (52,620 cells l−1) was determined at 0.5 m depth in station 4, and the lowest cell number (450 cells l−1) was determined at 30 m depth in station 1. Prorocentrum micans was the dominant species with the highest cell number (47,870 cells l−1, Station 4, 0.5 m). It was also observed that T. fusus and T. furca increased in abundance. As can be seen, the highest abundance in the study was obtained in May 2013 and February 2014 sampling periods and P. micans was the most abundant species that played a role in this increase.

Statistical data

In order to reveal the relationship between phytoplankton species and cell numbers obtained from four stations and six different depth points in the coastal waters of Burgaz Island and the ecological variables, Spearman's rank correlation method was used (Table 3). It was observed that NO2 + NO3–N and SiO4–Si values of nutrients decreased with increasing temperature and increased with increasing salinity and depth (P < 0.01). In the examination it was determined that phytoplankton abundance increased with the increase of PO4–P in the seawater, while it was found to have a negative relation with SiO4–Si. It was determined as the depth increased, salinity and SSM amount increased, whereas chl a concentration decreased (P < 0.01). The concentration of chl a decreased with the amount of light and consequently, the total phytoplankton abundance decreased as the depth increased (P < 0.01). It is also notable that the concentration of dissolved oxygen increases (P < 0.01) with the increase of chl a concentration. In addition, the concentration of dissolved oxygen showed a decrease (P < 0.01) as the amount of salinity increased with the increase in depth. In the study, it was determined that there was a negative relationship between the amount of SSM, total phytoplankton abundance and chl a concentration.

Table 3. Spearman's rank correlation coefficient between the environmental factors and phytoplankton communities

Temp, temperature; Sal, salinity; DO, dissolved oxygen; Chl a, chlorophyll a; SSM, suspended solid material; TS, total number of species; TN, Total abundance; DinS, number of Dinophyceae species; DinN, abundance of Dinophyceae; BacS, number of Bacillariophyceae species; BacN, abundance of Bacillariophyceae. *P < 0.05, **P < 0.01, N = 48.

Taking into account ~80% similarity, the Bray–Curtis similarity index which was applied to determine similarities in terms of species number and abundance between stations, it was observed that species especially from dinoflagellates such as Prorocentrum micans and Tripos fusus, increased similarity at depths and stations with similar abundances in August, November and February, excluding May. In August, station 1/0.5 m and station 3/30 m (77%), station 3/0.5 m and station 3/15 m (81%) in November, station 4/15 m and station 4/30 m (79%) in February were the most similar stations. In May, it was determined that all stations and depths, except 30 m depth, were similar over 80%. Within 30 m depths, station 1/30 m was separated from 30 m depths of other stations due to the lower abundance belonging to the species in August and February (Figure 4). The Euclidean distance based on environmental variables and seasons stated that the same depths of the stations are located close to each other (Figure 5).

Fig. 4. Bray–Curtis similarity dendrogram of the sampling stations and periods.

Fig. 5. Dendrogram of the Euclidean distance dendrogram of the sampling stations and periods.

During the sampling periods, Shannon–Weaver diversity index (H′) was used to determine the species diversity and the highest species diversity (H′) was found in station 3 of August 2013 (H′ = 2.57) sampling period, the lowest (H′) was observed in station 2 of May 2013 (H′ = 0.18).

Discussion

In the Sea of Marmara, phytoplankton studies have increased especially after the 2000s; in addition to determining the species, their abundance conditions, ecology and their relationships with ecological variables have been widely studied. Most of the studies are regional studies including bays and gulfs, and generally consist of data for seasonal sampling periods. The first checklist study in the region was made in 2004 (Balkis, Reference Balkis2004) and 168 phytoplankton taxa were reported. In the second comprehensive checklist study (Balkis & Tas, Reference Balkis, Tas, Özsoy, Çağatay, Balkis, Balkis and Öztürk2016), increased phytoplankton studies in the Sea of Marmara including the straits were evaluated and 333 phytoplankton taxa, 40 of which were genus level, were reported until 2016. In a study conducted in the Golden Horn Estuary, 127 phytoplankton taxa were identified (Tas, Reference Tas2020). After 2016 new records of Chaetoceros aequatorialis, C. contortus, C. lorenzianus f. forceps (Tas & Hernández-Becerril, Reference Tas and Hernández-Becerril2017) from the Golden Horn Estuary, Amphisolenia laticincta, Cochlodinium sp., Gynogonadinium aequatoriale, Heterocapsa rotundata and Metaphalacroma sp. (Balcı & Balkis, Reference Balcı and Balkis2017) from the Gemlik Gulf, Gymnodinium dogielii, Heterodinium rigdeniae and Pseliodinium fusus (Balkis-Ozdelice et al., Reference Balkis-Ozdelice, Durmus, Toklu-Alicli and Balci2020) from the Gulf of Erdek have been reported. With the addition of four new records of this study (Corythodinium frenguellii, Gonyaulax scrippsae, Pronoctiluca pelagica and Nitzschia reversa) the species number has increased to 348 in the Turkish Straits System.

Comparing with the comprehensive checklist study in the region (Balkis & Tas, Reference Balkis, Tas, Özsoy, Çağatay, Balkis, Balkis and Öztürk2016), the highest number of species was found in Bacillariophyceae with 162 species (49%) followed by Dinophyceae with 124 species (37%). The finding, which revealed that diatoms were dominant in the region in terms of number of species, is in parallel with the studies conducted in north-west coasts (Velasquez & Cruzado, Reference Velasquez and Cruzado1995; 51% diatoms, 36% dinoflagellates) and north-east coasts (Polat & Piner, Reference Polat and Piner2002; 57.4% diatoms and 37.2% dinoflagellates) of the Mediterranean Sea. In addition, in the Aegean Sea, diatoms and dinoflagellate species were reported with the rates of 45.8% and 41.2%, respectively (Koray, Reference Koray1994). However, in this study carried out in Burgaz Island, Dinophyceae is the dominant group with 49 species (48.5%) and followed by Bacillariophyceae with 47 species (46.5%). Similarly, in a study conducted around Bozcaada in the Aegean Sea (Balkis, Reference Balkis2009), dinoflagellates (50%) were reported as a dominant group over diatoms (47%) in terms of species number. In Villefranche Bay on the north-west coast of the Mediterranean Sea (Gomez & Gorsky, Reference Gomez and Gorsky2003: 52% dinoflagellates, 43% diatoms), in Genoa Bay (Bernhard & Rampi, Reference Bernhard and Rampi1967: 48% dinoflagellates, 31% diatoms) and in the previous studies in the Sea of Marmara (Balkis, Reference Balkis2003: 52% dinoflagellates, 40% diatom; Balcı & Balkis, Reference Balcı and Balkis2017: 54% dinoflagellates, 42% diatoms; Dursun et al., Reference Dursun, Tas, Bayram-Partal and Ediger2020: 48% dinoflagellates, 42% diatoms; Tas et al., Reference Tas, Kus and Yilmaz2020: 48% dinoflagellates, 47% diatoms) it was noted that dinoflagellates showed a greater variety than diatoms. It is known that regional climate changes, increasing temperature, industrialization and anthropogenic pressures can cause regional differences in species diversity (Gomez & Claustre, Reference Gomez and Claustre2003).

It is known that low salinity Black Sea waters affect the surface waters of the Sea of Marmara. According to Türkoğlu (Reference Türkoğlu1998), Bacillariophyceae were dominant in the Black Sea in the 1960–1970 period with the populations they formed, however; recent studies have shown that dinoflagellates species have increased in the phytoplankton assemblages. It has been reported that where there is an excess of nutrients in an environment, a decline in the number of phytoplankton species and a proportional variation between the taxonomic groups might be seen as an indication of stress (Türkoğlu, Reference Türkoğlu1999). The increase of dinoflagellate species in terms of diversity compared with diatoms in an environment shows that the Sea of Marmara is particularly affected by the waters of the Black Sea, as it shows the increasing negative change.

Most of the phytoplankton species identified on the shores of Burgaz Island are neritic, temperate and subtropical climate species, but oceanic species were also found. Benthic species adapted to planktonic life such as Licmophora sp. and Pleurosigma normanii, typical marine species such as Proboscia alata, Thalassionema nitzschioides and Tripos fusus, brackish water species such as Cylindrotheca closterium and Prorocentrum micans were observed during the sampling periods. Species such as Skeletonema costatum and Lingulodinium polyedra, which are typical species of eutrophic areas, were not encountered in this study. However, these two species are known from previous studies conducted in the Sea of Marmara and it has been reported that especially S. costatum shows an excessive increase in certain periods (Balkis, Reference Balkis2003). The dominance of P. micans, one of the brackish water species, in terms of abundance compared with other species in this study is another indication that the low salinity Black Sea waters are affecting the surface waters of the Sea of Marmara. In addition, Pseudosolenia calcar-avis and Hemiaulus hauckii, which are characteristic species of oligotrophic waters (Kimor, Reference Kimor1985), were also observed, but H. hauckii was detected only in November 2013.

Phytoplanktonic organisms form two seasonal peaks, a characteristic feature seen in temperate regions (Barnes & Mann, Reference Barnes and Mann1980). According to Sorokin (Reference Sorokin and Ketchum1983), for algal growth in the Black Sea, the larger of these peaks occurs at the end of winter (February) and early spring (March and April), then a second and smaller peak at the end of summer (August) and early autumn (September). In this study, when the species were evaluated in terms of abundance, dinoflagellates were the group with an increase, two peaks were observed in the sampling periods; one peak in May representing spring and one in February representing the winter period. In terms of abundance, especially P. micans was the most abundant species in this increase. As is well known, P. micans is a red-tide species that can cause harmful effects (palytoxin, ovatoxin-a; Khokhar et al., Reference Khokhar, Naz, Un-Nisa Burhan, Abassi and Siddiqui2018) during its dense blooms (Tas et al., Reference Tas, Ergül, Balkis and Ozsoy2016).

However, in this study, the highest cell number of P. micans was observed in the sampling period of May 2013 (135,540 cells l−1) and this cell number was not enough to form a water discolouration. In a study in the Black Sea, Bodeanu et al. (Reference Bodeanu, Moncheva, Ruta and Popa1998) observed that phytoplanktonic organisms larger than 50 μm may cause harmful effects when they reach 105 cells l−1. It was reported that P. micans increased to their abundance in the Sea of Marmara in May (Balkis, Reference Balkis2003). It has been stated that red-tide is observed especially in the Gulf of Izmit (Öktem, Reference Öktem1997), which, compared with Burgaz Island, is a semi-closed, stable water environment with high nutrient values from the wastewater inputs and agricultural fertilizers.

Even though it has low cell densities (<103 cells l−1), Dinophysis, which is known to cause diarrhetic shellfish poisoning (DSP) with the okadaic acid and dinophysistoxins (DsT) it produces (Reguera et al., Reference Reguera, Riobó, Rodríguez, Díaz, Pizarro, Paz, Franco and Blanco2014), is represented by seven species in Burgaz Island (Table 2). Among the species obtained in the study, Dinophysis acuminata, D. acuta, D. caudata, D. fortii, D. ovum and D. sacculus are known to produce DsT (Reguera et al., Reference Reguera, Riobó, Rodríguez, Díaz, Pizarro, Paz, Franco and Blanco2014). Dinophysis species reached their highest abundance in May 2013 (station 4, 15 m depth: 250 cells l−1) in Burgaz Island, and D. acuta played an important role in this increase (190 cells l−1). Dinophysis acuminata, D. acuta and D. fortii were encountered in all sampling periods. DSP cases were generally reported from regions where aquaculture studies are conducted (Economou et al., Reference Economou, Papadopoulou, Brett, Kansouzidou, Charalabopoulos, Filioussis and Seferiadis2007; Farrell et al., Reference Farrell, Ajani, Murray, Baker, Webster, Brett and Zammit2018). There are no aquaculture studies around Burgaz Island, but it has been observed that people living in the region collect mussels from the sea and consume them. However, there has been no case of DSP reported from around the Sea of Marmara to date (Balkis, Reference Balkis2003; Tas & Yilmaz, Reference Tas and Yilmaz2015; Balcı & Balkis, Reference Balcı and Balkis2017). These species, which cause harmful effects even under 103 cells l−1, need to be monitored in the Sea of Marmara.

In the samples of May and August 2013, it was determined that the upper layer water temperature values were higher than the lower layer. This is because the surface water temperature is affected by the atmosphere. Delcroix (Reference Delcroix1993) reported that the most important event affecting changes in surface water temperature is weather conditions. After 20 m depth in the samples of November 2013 and February 2014, temperature values were measured higher than the upper layer. The reason for this is that the Mediterranean Sea is dominant in the bottom layer. Similarly, the high salinity values at 30 m depth show the effect of the Mediterranean Sea. The lowest salinity values were found in the surface in all sampling periods and it was observed that salinity increased in parallel with the increase in depth. Low salinity waters coming from the Black Sea via the Bosphorus are influential in the depths of the Sea of Marmara between 0–20 m (Yüce & Türker, Reference Yüce and Türker1991). In this study, it was noted that salinity values between 0–20 m were lower than those at 30 m depth in all sampling periods. In terms of dissolved oxygen, surface waters in contact with the atmosphere have higher dissolved oxygen values. Spearman's rank correlation has also shown that dissolved oxygen was negatively correlated with increasing depth and salinity (P < 0.01). Moreover, DO values were positively correlated with chl a (P < 0.01) and the total phytoplankton abundance (P < 0.05). Photosynthetic organisms enable surface waters to be enriched with oxygen as a result of photosynthesis (Geldiay & Kocataş, Reference Geldiay and Kocataş1998). Higher chl a values were determined in the surface layer where the light was effective, and the highest total phytoplankton abundance was obtained at 0.5 m depth at the stations. The total abundance and chl a values decreased as the depth increased (P < 0.01). Specifically, the total phytoplankton abundance reached its highest value with the increase of dinoflagellates in May, while chl a reached its highest value in February 2014, when the second peak was observed. However, Travers (Reference Travers1971) also stated that there is not always connection between chl a amounts and phytoplankton abundance. It has been reported that chl a values change depending on hydrochemical conditions such as nutrients, temperature, light and water mixtures (Lakkis et al., Reference Lakkis, Jonsson, Zodiatis, Soloviev and Yilmaz2003). In the study, it was determined that salinity, which is one of the basic ecological variables, is correlated with a decrease in chl a values with increasing salinity (P < 0.01). This is also associated with a decrease in phytoplankton biomass and chl a values as a result of decreasing light with depth.

In a classification made in the Aegean Sea according to chl a values, <0.5 μg l−1 was evaluated as oligotrophic, 0.5–1.0 μg l−1 as mesotrophic and > 1.0 μg l−1 as eutrophic (Ignatiades, Reference Ignatiades2005). In this study, considering the chl a values (0.01–3.17 μg l−1), it was determined that the environment, especially the intermediate layer waters, reflected mesotrophic/oligotrophic conditions, while eutrophic conditions prevailed especially in surface waters during the sampling periods of May 2013 and February 2014. According to Simboura et al. (Reference Simboura, Panayotidis and Papathanassiou2005), moderate water quality (chl a: 0.4–0.6 μg l−1), low water quality and high mesotrophic (chl a: 0.6–2.21 μg l−1) conditions prevail in the study. Considering that S. costatum, which is one of the dominant species of eutrophic areas, was not observed during the sampling periods, and taking into account the intermediate layer chl a values and nutrient ratios, it can be said that the island shores are generally oligotrophic. It has also been stated that there was a decrease in the abundance of species such as Leptocylindrus danicus, D. brightwellii and P. calcar-avis, and an increase in the abundance of dinoflagellates such as Prorocentrum balticum, P. cordatum and P. micans before eutrophication (Zaitsev & Mamaev, Reference Zaitsev and Mamaev1997). In this study carried out in Burgaz Island, it was determined that P. micans species increased in surface layer waters reflecting potentially eutrophic conditions.

In the study area, nutrient values also increased in parallel with the increase in depth. Higher values were obtained especially in the bottom layer where the Mediterranean Sea is effective. The reason for this is that Mediterranean Sea waters, poor in nutrients at the entrance of Dardanelles, become enriched in nitrate and ortho-phosphate due to particulate organic matter in the bottom water by the time they reach to the Bosphorus (Polat & Tuğrul, Reference Polat and Tuğrul1995). According to Spearman's rank correlation, it was observed that especially Nitrite + Nitrate–N and Silicate–Si values were positively correlated with the depth increase (P < 0.01), and it was revealed that the total phytoplankton abundance increases with the increase of Phosphate–P (P < 0.01) and decreases with the increase of Silicate-Si (P < 0.01). The reason that the total phytoplankton abundance is inversely related to Silicate-Si is that dinoflagellates are dominant in abundance during the entire study period, whereas diatoms, that require silica, have lower abundance. The fact that there are low nutrient amounts in surface and near-surface waters compared with the lower layer is due to the rapid consumption of rich nutrient surface waters, which originate from the Black Sea, in primary production.

The main purpose of determining the diversity indices in a region is to examine the changes in the community structure in the region and to find a relationship between the degree of pollution and the structural changes of living communities if there is any pollution (Koray, Reference Koray1987). The same researcher stated that if the selected organism group is phytoplankton, it might be erroneous to use the diversity index results as a degree of contamination process, but it would be more appropriate to use it in comparisons based on time or regions. The reason that the Shannon–Weaver diversity index is low during the May 2013 sampling period when the phytoplankton abundance increased is that Prorocentrum micans is dominant to other species in terms of the abundance. In addition, considering both the abundance of species and ecological variables throughout the study, it has been revealed that the depths of the stations show close similarity by grouping them within themselves.

In conclusion, this study carried out on the shores of Burgaz Island aimed to reveal the phytoplankton species and their abundance in the region. It was determined that dinoflagellates were dominant in terms of species number and number of cells and with the addition of newly recorded species, it has contributed to the checklist of the plankton species of the Sea of Marmara and the relationship between species and ecological variables has been investigated.

Data

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Author contributions

Kayadelen, Y., and Balkis-Ozdelice, N., collected and identified the phytoplankton samples and evaluated the psycho-chemical data. Also, Durmus, T. helped to collect the samples. Statistical evaluation of the data was made by all authors, and they read and approved the final manuscript.

Financial support

This study was supported by the Research Fund of Istanbul University, Project number 34159.

Conflict of interest

The authors declare no conflicts of interest.

References

American Public Health Association (APHA) (1999) Standard Methods for Examination of Water and Waste Water, 20th Edn. Washington, DC: American Public Health Association.Google Scholar
Aydın, H, Balcı, M, Uzar, S and Balkis, N (2015) Dinoflagellate cyst assemblages in surface sediments of Southwestern Black Sea and Çanakkale Strait (Dardanelles). Fresenius Environmental Bulletin 24, 47894798.Google Scholar
Balcı, M and Balkis, N (2017) Assessment of phytoplankton and environmental variables for water quality and trophic state classification in the Gemlik Gulf, Marmara Sea (Turkey). Marine Pollution Bulletin 115, 172189.CrossRefGoogle Scholar
Balkis, N (2003) Seasonal variations in the phytoplankton and nutrient dynamics in the neritic water of Büyükçekmece Bay, Sea of Marmara. Journal of Plankton Research 25, 703717.CrossRefGoogle Scholar
Balkis, N (2004) List of phytoplankton of the Sea of Marmara. Journal of the Black Sea/Mediterranean Environment 10, 123141.Google Scholar
Balkis, N (2009) Seasonal variations of microphytoplankton assemblages and environmental variables in the coastal zone of Bozcaada Island in the Aegean Sea (NE Mediterranean Sea). Aquatic Ecology 43, 249270.CrossRefGoogle Scholar
Balkis, N and Tas, S (2016) Phytoplankton of the Sea of Marmara: a review. In Özsoy, E, Çağatay, MN, Balkis, N, Balkis, N and Öztürk, B (eds), The Sea of Marmara: Marine Biodiversity, Fisheries, Conservation and Governance. Istanbul: Turkish Marine Research Foundation (TUDAV), pp. 326343.Google Scholar
Balkis, N, Balcı, M, Giannakourou, A, Venetsanopoulou, A and Mudie, P (2016) Dinoflagellate resting cysts in recent marine sediments from the Gulf of Gemlik (Marmara Sea, Turkey) and seasonal harmful algal blooms. Phycologia 55, 187209.CrossRefGoogle Scholar
Balkis-Ozdelice, N, Durmus, T, Toklu-Alicli, B and Balci, M (2020) Phytoplankton composition related to the environmental conditions in the coastal waters of the Gulf of Erdek. Indian Journal of Geo-Marine Science 49, 15451559.Google Scholar
Barnes, RK and Mann, KH (1980) Fundamentals of Aquatic Ecosystems. Oxford: Blackwell.Google Scholar
Bernhard, M and Rampi, L (1967) The annual cycle of the Utermohl-phytoplankton in the Ligurian Sea in 1959 and 1962. Publicazioni della Stazione Zoologica di Napoli 35, 137169.Google Scholar
Beşiktepe, ŞT, Sur, HI, Özsoy, E, Abdul Latif, MA, Oğuz, T and Ünlüata, Ü (1994) The circulation and hydrography of the Marmara Sea. Progress in Oceanography 34, 285334.CrossRefGoogle Scholar
Beşiktepe, ŞT, Özsoy, E, Latif, MA and Oğuz, T (2000) Hydrography and circulation of the Marmara Sea. In Öztürk, B, Kadıoğlu, M and Öztürk, H (eds), Marmara Sea 2000 Symposium, 11–12 November 2000. Istanbul: Turkish Marine Research Foundation, pp. 314–326.Google Scholar
Bodeanu, N, Moncheva, S, Ruta, G and Popa, L (1998) Long-term evolution of the algal blooms in Romanian and Bulgarian Black Sea waters. Cercetãri Marine – Recherches Marines Constanta 31, 3755.Google Scholar
Clarke, KR and Warwick, RM (2001) Change in Marine Communities: An Approach to Statistical Analysis and Interpretation, 2nd Edn. Plymouth: PRIMER-E.Google Scholar
Creel, L (2003) Ripple Effects: Population and Coastal Regions, Population Reference Bureau. Available at http://www.prb.org/pdf/RippleEffects_Eng.pdf (Accessed 10 March 2018).Google Scholar
Delcroix, T (1993) Seasonal and interannual variability of sea surface temperatures in the Tropical Pacific, 1969–1991. Deep-Sea Research 40, 22172228.CrossRefGoogle Scholar
Dursun, F, Tas, S, Bayram-Partal, F and Ediger, D (2020) Determination of phytoplankton composition by microscopy and HPLC-derived pigment analysis in the Sea of Marmara. Mediterranean Marine Science 21, 653663.CrossRefGoogle Scholar
Economou, V, Papadopoulou, C, Brett, M, Kansouzidou, A, Charalabopoulos, K, Filioussis, G and Seferiadis, K (2007) Diarrheic shellfish poisoning due to toxic mussel consumption: the first recorded outbreak in Greece. Food Additives and Contaminants 24, 297305.CrossRefGoogle Scholar
Farrell, H, Ajani, P, Murray, S, Baker, P, Webster, G, Brett, S and Zammit, A (2018) Diarrhetic shellfish toxin monitoring in commercial wild harvest bivalve shellfish in New South Wales, Australia. Toxins 10, 446.CrossRefGoogle ScholarPubMed
Geldiay, R and Kocataş, A (1998) Deniz Biyolojisine Giriş. Izmir: Ege University Faculty of Science.Google Scholar
Gomez, F and Claustre, H (2003) The genus Asterodinium (Dinophyceae) as a possible biological indicator of warming in the western Mediterranean. Journal of the Marine Biological Association of the United Kingdom 83, 173174.CrossRefGoogle Scholar
Gomez, F and Gorsky, G (2003) Annual microplankton cycles in Villefranche Bay, Ligurian Sea, NW Mediterranean. Journal of Plankton Research 25, 323339.CrossRefGoogle Scholar
Ignatiades, L (2005) Scaling the trophic status of the Aegean Sea, Eastern Mediterranean. Journal of Sea Research 54, 5157.CrossRefGoogle Scholar
Ivanoff, A (1972) Introduction a l'oceanographie. Paris: Librairie Vuibert.Google Scholar
Khokhar, FN, Naz, T, Un-Nisa Burhan, Z, Abassi, MJ and Siddiqui, PJA (2018) Occurrence of HAB/toxic dinoflagellates species from the coast of Karachi, Pakistan (Northern Arabian Sea). Indian Journal of Geo Marine Sciences 47, 7388.Google Scholar
Kimor, B (1985) Round table on indicator species in marine phytoplankton. II. Background presentation. Commission Internationele pour L'Exploration Scientifique de la Mer Méditerranée (Rapp. Comm. Int. Mer Médit.) 29, 6579.Google Scholar
Koray, T (1987) Fitoplankton topluluklarındaki değişimlerin saptanması için diversite indekslerinin karşılaştırılması. Doğa, TU Müh ve Çev D C 11, 242253.Google Scholar
Koray, T (1994) Phytoplankton species succession, diversity and nutrients in neritic waters of the Aegean Sea (Bay of Izmir). Turkish Journal of Botany 19, 531544.Google Scholar
Lakkis, S, Jonsson, L, Zodiatis, G and Soloviev, D (2003) Remote sensing data analysis in the Levantine basin: SST and chlorophyll-a distribution. In Yilmaz, A (ed.), Oceanography of Eastern Mediterranean and Black Sea: Similarities and Differences of two Interconnected Basins. Ankara: TÜBITAK Publishers, pp. 266273.Google Scholar
MarBEF Data System (2018) The European Register of Marine Species (ERMS). http://www.marbef.org/data/erms.php (Accessed 06 March 2018).Google Scholar
Öktem, YA (1997) İzmit Körfezi'nde mevsimlik fitoplankton değişimi (MSc Thesis). Istanbul University, Istanbul, Turkey.Google Scholar
Öztürk, İ, Dülekgürgen, E and Erşahin, ME (2021) The mucilage problem in Marmara: definition, causes, dimensions, evaluation and recommendations for solution. In Öztürk, I and Şeker, M (eds), Ecology of the Marmara Sea: Formation and Interactions of Marine Mucilage, and Recommendations for Solutions. Ankara: Turkish Academy of Sciences, pp. 1547.Google Scholar
Parsons, TR, Majita, Y and Lalli, CM (1984) A Manual of Chemical and Biological Methods for Seawater Analysis. Oxford: Pergamon Press.Google Scholar
Polat, S and Piner, MP (2002) Nutrients and phytoplankton in the Babadillimani Bight, northeastern Mediterranean coast of Turkey. Indian Journal of Marine Sciences 31, 188194.Google Scholar
Polat, SC and Tuğrul, S (1995) Nutrient and organic carbon exchanges between the Black and Marmara Seas through the Bosphorus Strait. Continental Shelf Research 15, 11151132.CrossRefGoogle Scholar
Reguera, B, Riobó, P, Rodríguez, F, Díaz, PA, Pizarro, G, Paz, B, Franco, JM and Blanco, J (2014) Dinophysis toxins: causative organisms, distribution and fate in shellfish. Marine Drugs 12, 394461.CrossRefGoogle ScholarPubMed
Semina, HJ (1978) Treatment of an aliquot sample. In Sournia, A (ed.), Phytoplankton Manual. Paris: UNESCO, p. 181.Google Scholar
Siegel, S (1956) Non-parametric Statistics for the Behavioral Sciences. New York, NY: McGraw-Hill.Google Scholar
Simboura, N, Panayotidis, P and Papathanassiou, E (2005) A synthesis of the biological quality elements for the implementation of the European Water Framework Directive in the Mediterranean Ecoregion: the case of Saronikos Gulf. Ecological Indicators 5, 253266.CrossRefGoogle Scholar
Sorokin, YI (1983) The Black Sea. In Ketchum, BH (ed.), Ecosystem of the World, Estuaries and Enclosed Seas, Book 26. Amsterdam: Elsevier Scientific Publishing Company, pp. 253292.Google Scholar
Sukhanova, IN (1978) Settling without the inverted microscope. In Sournia, A (ed.), Phytoplankton Manual. Paris: UNESCO, p. 97.Google Scholar
Tas, S (2020) Changes in phytoplankton composition of the Golden Horn Estuary (Sea of Marmara) following remediation. Journal of the Marine Biological Association of the United Kingdom 100, 10531062.CrossRefGoogle Scholar
Tas, S and Yilmaz, IN (2015) Potentially harmful microalgae and algal blooms in a eutrophic estuary in the Sea of Marmara (Turkey). Mediterranean Marine Science 16, 432443.CrossRefGoogle Scholar
Tas, S and Hernández-Becerril, DD (2017) Diversity and distribution of planktonic diatom genus Chaetoceros (Bacillariophyceae) in the Golden Horn Estuary (Sea of Marmara). Diatom Research 32, 309323.Google Scholar
Tas, S, Ergül, HA and Balkis, N (2016) Harmful algal blooms and mucilage formations in the Sea of Marmara. In Ozsoy, E, Çağatay MN, Balkis N, Balkis N and Öztürk B (eds), The Sea of Marmara: Marine Biodiversity, Fisheries, Conservation and Governance. Istanbul: TUDAV, pp. 768786.Google Scholar
Tas, S, Kus, D and Yilmaz, IN (2020) Temporal variations in phytoplankton composition in the north-eastern Sea of Marmara: potentially toxic species and mucilage event. Mediterranean Marine Science 21, 668683.Google Scholar
Taşdemir, Y (2002) The Marmara Sea: pollutants and environment related precautions. Uludağ University Journal of the Faculty of Engineering and Architecture 7, 3945.Google Scholar
Throndsen, J (1978) Preservation and storage. In Sournia, A (ed.), Phytoplankton Manual. Paris: UNESCO, pp. 6974.Google Scholar
Travers, M (1971) Le microplankton du Golfe de Marseille: etude quantitative, structural et synécologique: variation spatio-temporelles. PhD thesis, Université Aix-Marseille-II, Marseille, France.Google Scholar
Türkoğlu, M (1998) Orta Karadeniz bölgesinin (Sinop Yarımadası kıyıları) fitoplankton kompozisyonu ve değişimini etkileyen faktörler. PhD thesis, Ege University, Izmir, Turkey.Google Scholar
Türkoğlu, M (1999) Some fluctuations in phytoplankton community structures of the Black Sea. E.U. Journal of Fisheries & Aquatic Sciences 16, 201217.Google Scholar
Velasquez, ZR and Cruzado, A (1995) Inventory of the diatom flora of the NW Mediterranean Sea. Vie et Milieu 45, 249263.Google Scholar
Winkler, LW (1888) The determination of dissolved oxygen in water. Berichte der Deutschen chemischen Gesellschaft zu Berlin 21, 28432855.CrossRefGoogle Scholar
World Register of Marine Species (WoRMS) (2018) http://www.marinespecies.org/index.php (Accessed 14 March 2018).Google Scholar
United Nations World Water Assessment Programme (WWAP) (2018) The United Nations World Water Development Report 2018: Nature-Based Solutions for Water. Paris: UNESCO.Google Scholar
Yüce, H (1988) Investigation of the Mediterranean water in the Black Sea. Istanbul University Institute of Marine Sciences and Geography Bulletin 5, 121157.Google Scholar
Yüce, H and Türker, A (1991) Marmara Denizi'nin fiziksel oşinografik özellikleri ve Akdeniz suyunun Karadeniz'e girişi. Uluslararası çevre sorunları sempozyumu tebliğleri, Atatürk Kültür Merkezi, 22–24 May 1991. İstanbul Marmara Rotary Kulübü, pp. 284–303.Google Scholar
Zaitsev, YP and Mamaev, V (1997) Marine Biological Diversity in the Black Sea: A Study of Change and Decline. New York, NY: United Nations Publications.Google Scholar
Zar, JH (1984) Biostatistical Analysis, 2nd Edn. Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
Figure 0

Fig. 1. Study area and sampling stations of Burgaz Island.

Figure 1

Fig. 2. Seasonal variations of ecological variables along the water column. Data are reported as averages of the sampling stations.

Figure 2

Table 1. The minimum and maximum values of ecological variables in Burgaz Island during the sampling periods

Figure 3

Table 2. List of phytoplanktonic taxa of the coastal waters of Burgaz Island

Figure 4

Fig. 3. Seasonal variations in the abundance (cells l−1) of different phytoplankton taxonomic groups at the stations.

Figure 5

Table 3. Spearman's rank correlation coefficient between the environmental factors and phytoplankton communities

Figure 6

Fig. 4. Bray–Curtis similarity dendrogram of the sampling stations and periods.

Figure 7

Fig. 5. Dendrogram of the Euclidean distance dendrogram of the sampling stations and periods.