Spatial Variation of Summer Microphytoplankton Communities Related to Environmental Parameters in the Coastal Area of the El Bibane Lagoon (Tunisia, Eastern Mediterranean)

Abstract

The distribution of microphytoplankton in relation to environmental factors in the coastal waters of the El Bibane lagoon was studied during the summers of 2009 and 2010. Microphytoplankton abundance and species richness found in the El Bibane lagoon during the summer of 2009 do not markedly differ from those reported from the same environment in the summer of 2010. Microphytoplankton abundance was higher in the summer of 2010 (169.50 ± 60.77 × 102 cells l−1) than in the summer of 2009 (84.50 ± 74.24 × 102 cells l−1), but species richness was slightly higher in the summer of 2009 (28 taxa) than in the summer 2010 (27 taxa). Dinoflagellate was the most abundant microphytoplankton group present during the entire study period, comprising 77–83% of the total microphytlankton community during summer 2009 and 2010, respectively.

1. Introduction

Coastal lagoons, which are transitional water ecosystems, exhibit significant heterogeneity, characterized by pronounced gradients in abiotic factors stemming from their link to the sea [1]. The shallow lagoons are dynamic and naturally stressed ecosystems with many environmental fluctuations [2]. Consequently, the term “lagoon” encompasses a diverse array of environments, each exhibiting notable differences in morphology, salinity, size, and trophic status. These factors significantly influence the structure of their biological assemblages, species richness, and fishing yields [3]. Lagoons are highly productive, hosting an important degree of biodiversity and providing many services for human use [4]. These services have an important economic value for the coastal lagoons as food resources, recreation, and tourism [5]. In these important productive areas, phytoplankton represent the basis of food webs and biochemical cycles and are generally the first autotrophic community to respond to a fluctuation in nutrient accessibility [6]. The structure and distribution of phytoplankton are controlled by the complex relations between environmental factors and biotic communities [7]. In addition, the lagoons are exposed to phytoplankton blooms because they get enriched with nutrients and pollutant inputs from land-derived run-off, aquaculture, wastewater disposal, and agricultural discharge [8]. Due to shallowness and confinement, these inputs result in elevated nutrient values and pollutants in lagoons, intensifying their degradation [9]. High nutrient concentrations and increased phytoplankton biomass lead to dystrophic crises, hypoxia, and anoxia events, dramatically impacting all other organisms [10]. Approaches for evaluating water quality are increasingly relying on phytoplankton species richness and distribution as indicators to assess deterioration in water resources stemming from enduring nutrient loading and eutrophication [11]. The inter-annual trends in environmental variables and their complex interaction with phytoplankton communities are still not comprehensively understood in lagoon ecosystems. This study is focused on the El Bibane lagoon (Tunisia), a stressed Mediterranean shallow lagoon classified as Ramsar Wetland since 2007. The general goal was to explore the responses of its phytoplankton communities to nutrient availability. Hence, this research has been undertaken with the following aims: (1) to study the summer microphytoplankton communities’ structure and distribution; (2) to determine their potential relationship with environmental factors by using statistical analyses; and (3) to define biological parameters that may drive their horizontal and inter-annual distribution.

2. Material and methods

2.1 Study site

The El Bibane lagoon, situated near the Libyan border, spans approximately 33 km in length and 10 km in width. It is positioned 10 km north of Ben Gardane and 20 km west of Zarzis, Tunisia. This lagoon is the second largest in Tunisia after the lagoon of Boughrara. Numbers of wintering birds reaching 35.000 are regularly observed. The majority of annual observations are conducted by the national Tunisian NGO “Association les amis des Oiseaux.” In the case of certain bird species, the numbers of those wintering around El Bibane lagoon surpass 1% of their global population. The lagoon is a safe place for some species of fish that spend part of their life cycle there before returning to the sea as adults. It is the largest lagoon in Tunisia and also the most important fishery. The current exploitation system is essentially based on “bordigue”, which assures the most significant part of the fish capture.

2.2 Field sampling

Samples for nutrients and microphytoplankton were taken during one-day campaigns performed in summer (July 2009 and 2010) along the El Bibane lagoon. During each campaign, water samples were collected in four stations (Figure 1). Samples were acquired using a horizontally deployed Van Dorn-type closing bottle at depths ranging from 4 to 6 m. Nutrient samples (120 ml) were promptly stored at −20°C in the dark upon collection. Microphytoplankton samples were preserved with a 3% acid Lugol solution [12] and kept at 4°C in the dark for enumeration. Water samples for Chlorophyll-a analysis (1 L) underwent vacuum filtration onto Whatman GF/F filters, followed by immediate storage at −20°C.

Figure 1.

Location of sampling stations of the El Bibane lagoon.

2.3 Physicochemical variables

Physicochemical parameters, including temperature, salinity, and pH, were measured immediately after sampling using a multi-parameter kit (Multi 340 i/SET). Subsamples for nutrients (nitrite, nitrate, ammonium, orthophosphate, silicate, total nitrogen, and total phosphate) were collected in previously washed plastic containers of 4.5 ml. Analysis was conducted using a Bran and Luebbe type 3 autoanalyzer, with concentrations determined colorimetrically using a UV-visible (6400/6405) spectrophotometer [13]. Each analysis was conducted independently. The automated analysis system enables rapid and precise analysis of these nutrients; although the method for each nutrient varies slightly, the overall procedure remains similar.

2.4 Microphytoplankton enumeration

Subsamples (50 ml) for estimating microphytoplankton abundance through counting were examined under an inverted microscope following the Utermöhl method [14] after settling for 24 h. Microphytoplankton species were counted across the entire sedimentation chamber at 40× magnification and identified using various keys [15, 16]. The level of community structure was assessed with the Shannon diversity index H′ [17].

$${\mathrm{H}}^{\prime }=-\Sigma \mathrm{N}\mathrm{i}/\mathrm{N}{log}_2\mathrm{N}\mathrm{i}/\mathrm{N}$$E1

N—total abundance, Ni/N—relative abundance of species i, n—total number of species.

2.5 Chlorophyll-a

After extraction of the pigments in acetone (90%), Chlorophyll-a was estimated by spectrometry. The concentrations were then estimated using the equations of SCOR-UNESCO [18]. This technique involves filtering 1 l of seawater through vacuum filtration onto Whatman GF/F glass fiber filters, ensuring that the pressure does not exceed 400 mmHg to prevent cell breakdown. A small amount of magnesium carbonate is added to prevent pigment degradation in photopigments during filtration. The filters are wrapped in aluminum foil and dried under vacuum with silica gel for 24 h before being stored at −20°C until extraction. Pigment extraction is carried out in 90% acetone under dark and cold conditions for 5 h. Following a 10-minute centrifugation at 3500g, absorbance is measured using a Jenway spectrophotometer at 630 nm, 645 nm, and 663 nm.

2.6 Data analyses

Pearson's correlation coefficient was used to examine potential relationships between variables. Significant differences between years were identified using a one-way ANOVA, followed by post hoc comparisons using Tukey's test.

Physicochemical and biological parameters evaluated at four stations during the summer underwent a normalized principal component analysis (PCA) [19]. A simple log (x + 1) transformation was applied to the data to stabilize the variance [20]. effectively. The physicochemical and biological parameters assessed at four stations during the summer were submitted to a normalized principal component analysis (PCA) [19]. A simple log (x + 1) transformation was applied to the data to stabilize variance correctly [20]. The spatiotemporal patterns of phytoplankton species were assessed with non-metric multidimensional scaling (NMDS) after square-root transformation of data using PRIMER v7 software.

3. Results

3.1 Hydrological features

The plot of physicochemical variables showed that the average temperature ranged between 27.74 and 29.15°C (Figure 2), with an average value of (28.20 ± 0.39) °C and (28.68 ± 0.54) °C in the summer of 2009 and 2010, respectively (Table 1). The salinity ranged between 44.50 and 46.83 (Figure 2), with the lowest temperature detected at station 4 and the highest at station 2 in summer 2009. The pH values ranged from 8.13 (summer 2010, station 2) to 8.61 (summer 2009, station 4) (Figure 2). All physical parameter values showed a non-significant difference between the two seasons.

Figure 2.

Spatial variation in physical parameters: temperature, salinity, and pH at sampled stations.

Variables	Summer 2009	Summer 2010	T- values	p
	Mean ± SD	Mean ± SD
Physical variables
Temperature (°C)	28.20 ± 0.39	28.68 ± 0.54	−2.37	0.08
Salinity (psu)	45.77 ± 0.96	45.46 ± 0.77	0.18	0.87
pH	8.35 ± 0.19	8.29 ± 0.16	0.92	0.41
Chemical variables
NO2^− (μM)	0.24 ± 0.07	0.22 ± 0.13	−0.29	0.79
NO3^− (μM)	1.11 ± 0.12	1.45 ± 0.58	−1.31	0.26
NH4^+ (μM)	1.23 ± 0.17	1.41 ± 0.31	−3.39	0.02*
T-N (μM)	5.67 ± 0.81	6.51 ± 0.46	−1.68	0.17
PO4^3− (μM)	3.25 ± 1.67	2.52 ± 0.42	0.89	0.42
T-P (μM)	12.65 ± 2.76	12.22 ± 0.32	0.82	0.46
N/P ratio	0.92 ± 0.35	1.25 ± 0.42	−1.79	0.15
Si(OH)4 (μM)	3.51 ± 0.96	4.63 ± 1.09	−1.63	0.18
Biological variables
Chlorophyll-a (μg l^−1)	1.00 ± 0.16	1.33 ± 0.54	−0.51	0.64
T-Microphytoplankton (× 10^2 cells l^−1)	84.50 ± 74.24	169.50 ± 60.77	−1.06	0.35
Diatoms (× 10^2 cells l^−1)	19.50 ± 29.03	23.25 ± 27.45	0.63	0.56
Dinoflagellates (× 10^2 cells l^−1)	65.00 ± 48.14	140.00 ± 34.99	−1.81	0.14
Cyanobacteriae (× 10^2 cells l^−1)	-	6.00 ± 6.97	−1.09	0.34
Dictyochophyceae (× 10^2 cells l^−1)	-	0.25 ± 0.50	−0.89	0.42

Table 1.

Mean ± SD of physicochemical and biological variables measured off the coast of the El Bibane lagoon and results of the analysis of variance (ANOVA) to identify the significant differences between the sampled summer 2009 and summer 2010 seasons.

In the last column, the asterisks indicate different levels of significance in the ANOVA (*p < 0.05).

Nutrient concentrations showed neither clear spatial patterns nor significant differences between summer 2009 and 2010, except for ammonium (Table 1). Most of them were lower in the summer of 2009 and showed the highest values in the summer of 2010, except NO2⁻, PO₄³⁻, and T-P. NH₄⁺concentration varied between 1.00 and 1.65 μM, with the lowest and highest concentrations observed in summer 2010 at stations 1 and 4, respectively (Figure 2), and mean values were significantly lower in 2009 than in 2010 (1.23 ± 0.17and 1.41 ± 0.31 μM, respectively). The mean values of dissolved inorganic nitrogen and inorganic phosphate concentrations were higher and lower in the summer of 2010 than in the summer of 2009 but with no significant difference (Table 1). The N/P ratio [dissolved inorganic nitrogen (DIN; NO₂⁻ + NO₃⁻ + NH₄⁺) to dissolved inorganic phosphate (DIP; PO₃⁴⁻) ratio] ranged from 0.49 (Summer 2009) to 1.83 (summer 2010) at station 2. They were thus less than the Redfield ratio (16) in both years, suggesting a potential N limitation. The silicate concentration varied between 2.09 and 5.82 μM, with the lowest and highest values recorded at station 4 in 2009 and 2010, respectively (Figures 2 and 3).

Figure 3.

Spatial variation in chemical parameters: nitrite, nitrate, ammonium, total nitrogen, orthophosphate, total phosphate, dissolved inorganic nitrogen/dissolved inorganic phosphate ratio, and silicate at sampled stations.

3.2 Chlorophyll-a

Chla concentrations during the seasonal survey remained <2 μg l⁻¹ (Figure 4). There was no significant difference between the two years (Table 1). Still, the highest mean concentration (1.33 ± 0.54 μg l⁻¹) Chla was recorded in the summer of 2010, associated with an important proliferation of microphytoplankton (Hermesinium sp., Navicula sp., Striatella unipunctata, and Anabaena sp.).

Figure 4.

Spatial variation in biological parameters: chlorophyll-a, total microphytoplankton abundance, diatoms abundance, dinoflagellates abundance, other phytoplankton abundance, and species diversity (H′) at sampled stations.

3.3 Microphytoplankton spatial distribution and community structure

Table 2A and B present a summary of the microphytoplankton species observed throughout the study period. Mean microphytoplankton abundance was twice as high in the summer of 2010 as in the summer of 2009. Still, the difference was not significant due to the high variability between stations (Table 1, Figure 4). Dinoflagellates dominated the phytoplankton assemblage and were particularly abundant in the summer of 2010, with values >140 × 10² cells l⁻¹ at stations 1, 2, and 3. Microphytoplankton individuals were classified into 41 taxa from 8 samples, belonging to four taxonomic classes (Cyanobacteria, Diatoms, Dinoflagellates, and Dictyochophyceae). Dinoflagellates were the most diverse order (24 species), followed by diatoms (15 species). Other groups, including Cyanobacteriae and Dictyochophyceaewere, were represented by two or only one species present in 2010 (Table 2).

	July 2009				July 2010
	S1	S2	S3	S4	S1	S2	S3	S4
Dinoflagellates
Ceratium furca	***	**	*	***	-	**	-	-
Ebria sp.	-	-	*	-	-	-	-	-
Gonyaulax grindleyi	-	-	-	-	100	-	-	-
Gonyaulax spinifera	*	-	-	**	-	-	-	-
Gyrodinium sp.	**	-	-	*	-	*	-	*
Hermesinium sp.	**	-	**	***	****	****	****	***
Mesoporos sp.	-	-	-	-	*	-	-	-
Noctiluca scintillans	-	-	-	-	-	*	-	*
Ostreopsis sp.	-	-	-	*	-	-	-	-
Peridinium sp.	***	-	**	***	**	**	*	-
Podolampas palmipes	-	-	-	-	-	-	-	-
Polykrikos sp.	*	-	-	**	-	-	-	-
Prorocentrum gracile	**	**	**	*	-	-	-	-
Prorocentrum lima	-	*	-	-	*	-	-	-
Prorocentrum micans	***	*	***	***	**	**	-	**
Prorocentrum minimum	-	-	-	-	**	-	-	-
Prorocentrum triestinum	-	-	*	*	-	-	-	*
Protoperidinium depressum	-	-	*	-	-	-	-	-
Protoperidinium divergens	*	-	-	-	-	-	-	-
Protoperidinium leonis	-	-	-	*	-	-	-	-
Protoperidinium sp.	-	-	-	*	-	-	-	-
Pyrophacus sp.	**	-	**	**	-	*	-	-
Scrippsiella trochoidae	-	-	-	-	**	**	-	-
Diatoms
Amphiprora ornata	-	-	-	-	-	*	-	-
Amphora sp.	-	-	**	-	**	-	-	*
Biddulphia alternans	-	-	-	*	-	-	-	-
Chaetoceros sp.	-	**	-	**	-	-	-	-
Cocconeis sp.	*	-	-	**	***	-	*	-
Coscinodiscus sp.	-	-	-	-	-	*	-	-
Licmophora flabellata	-	-	-	-	**	-	-	-
Licmophora tincta	-	-	-	-	**	-	-	-
Licmophora sp.	-	-	-	*	-	-	-	-
Navicula sp.	**	-	**	**	***	**	-	**
Nitzschia longissima	-	-	-	-	*	-	-	-
Pinnularia sp.	*	-	-	**	***	**	-	-
Rhabdonema sp.	-	-	-	***	*	-	-	-
Striatella unipunctata	*	*	-	-	**	***	-	-
Tabellaria sp.	-	-	-	***	-	-	-	-
Cyanobacteria
Anabaena sp.	-	-	-	-	**	***	-	-
Oscilatoria sp.	-	-	-	-	*	-	-	*
Dictyophyceae
Dictyocha fibula	-	-	-	-	-	*	-	-

Table 2.

Shows the abundance indecies of phytoplankton species observed in the summer of 2009 and 2010.

^*

0–100 cells l⁻¹.

^**

100–1000 cells l⁻¹.

^***

1000–10,000 cells l⁻¹.

^****

>10,000 cells l⁻¹.

-, not detected.

Taxonomic richness, considered as a whole, was the highest in the summer of 2009 at station 4 (21 taxa) and the lowest at station 3 (3 taxa) in the summer of 2010 (Table 1). The diversity of the microphytoplankton community exhibited an increase from station 3 during the summer of 2010 (H′ = 0.12 bits cell⁻¹, 3 taxa) to station 4 in the summer of 2009 (H′ = 3.46 bits cell⁻¹, 21 taxa). The lowest H′ value was linked to a significant proliferation of Hermesinium sp. (14.2 × 10² cells l⁻¹, station 3, summer 2010).

3.4 Statistical analysis

The first factorial plane of the PCA analysis on environmental variables explained 60.5% of the total variance; the first axis (36.3%) opposed stations 2 and 3, correlated with all nutrients, and stations 1 and 4 correlated to pH and Chla (Figure 5A). The second axis (24.2%) opposed stations 2 and 3 in July 2009, correlated with PO4 and T-P to the same stations in July 2010, and correlated with nitrogenic nutrients (NO₂, NO₃, and NH₄).

Figure 5.

Results of (A) principal component analysis (axes I and II) performed on environmental variables and (B) Non-metric multidimensional scaling on percentage abundance of phytoplankton species. Overlapping taxa are not shown on the figure, but red asterisks indicate their position: (*) = Licmophora sp., Ostreopsis sp., Podolampaspalmipes, Protoperidinium leonis, and Protoperidinium sp. (**) = Gonyaulax grindleyi, Licmophora flabellate, Licmophora tincta, Mesoporos sp., Nitzschia longissimi, and Prorocentrum minimum.

The NMDS on the relative abundance of phytoplankton species clearly separated the July 2009 and July 2010 samples, showing two distinct communities for the two periods (Figure 5B).

4. Discussion

During this study, the recorded temperature and salinity values were typical of arid to semi-arid zones [21]. This study's high water temperature and salinity were typical of a semi-arid to arid Mediterranean climate [22]. Furthermore, in summer, high temperature and salinity, low precipitation, and varying circulation patterns on the coast may influence the environmental conditions of the site [23].

In the lagoon coast, chemical factors impact the abundance and distribution of microphytoplankton [24]. Orthophosphate showed a very high concentration compared to the ultraoligotrophic Eastern Mediterranean Sea, where phosphorus is a limiting factor for microphytoplankton growth [25]. Similar results were recorded in the Eastern [26] and in the Western [27] Mediterranean or in both ecosystems [28]. Relatively high phosphate values compared with DIN may result from rapid regeneration of orthophosphates and anthropogenic pollution [29]. The average value of the N/P ratio was lower than the Redfield (16) ratio in both summer 2009 and 2010. These results suggest that, contrary to the Mediterranean basin, the limiting factor was inorganic nitrogen in the lagoon coastal water. Inorganic phosphate concentrations were in excess due to anthropogenic inputs.

The environmental factors recorded in the El Bibane lagoon coastal waters are favorable to microphytoplankton growth with high temperature, solar energy, and non-limiting nutrients in summer. Dinoflagellates dominated microphytoplankton assemblages in summer. Similar results were found by Rekik et al. [22] on the southern coast of the Kerkennah Islands, by Ben Ltaief et al. [30] in the Gulf of Gabes, by Abdennadher et al. [31] in south Tunisia and by Anderson et al. [32] in other Mediterranean marine ecosystems. The percentage of dinoflagellate was high in several stations, principally in the summer of 2010, where it could represent the bulk of microphytoplankton. High temperature and salinity are favorable for dinoflagellate development [33], suggesting that this group is well adapted to the warm and salty waters of the present study area [22].

Diatoms were the second most important group of microphytoplankton. Diatoms, therefore, have an excellent ability to adapt to various areas, which may explain the relative stability of their species composition [34].

In our study, environmental variables displayed spatial patterns with stations close to the channel and the bordigue zone (Stations 2 and 3) more influenced by nutrients compared to the innermost stations (Stations 1 and 4). In contrast, the microphytoplankton community showed no clear spatial pattern. Still, it was very different between the two study periods, perhaps in relation to different nutrient inputs from oceanic origin, as suggested by the apparent differences observed between the two periods in stations 2 and 3. Overall, these results indicate that exchanges with the sea, as well as fishing activity, are essential processes for fertilizing the lagoon and ensuring its productivity, as already emphasized for the neighboring Boughrara lagoon [35], highlighting the potential role of these processes for phytoplankton dynamics in the El Biban lagoon.

Acknowledgments

This study was conducted within the scope of the international project Société d’étude de Réalisation d’Aménagement et d’Hydraulique (SERAH). The research took place at the Marine Biodiversity and Environment LR/18ES30 laboratory, University of Sfax, Tunisia.