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All issues Volume 57 (2021) Ann. Limnol. - Int. J. Lim., 57 (2021) 1 Full HTML
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Ann. Limnol. - Int. J. Lim.
Volume 57, 2021
Article Number 1
Number of page(s) 17
DOI https://doi.org/10.1051/limn/2020029
Published online 07 January 2021

© EDP Sciences, 2021

1 Introduction

The incidence of harmful cyanobacterial blooms (CyanoHABs) in aquatic ecosystems has increased globally in frequency, severity and duration worldwide (Chorus and Bartram, 1999; Nyenje et al., 2010; Steffen et al., 2014; Ndlela et al., 2016; Preece et al., 2017; Paerl, 2018). It has become one of the most critical concerns for drinking water supply, as well as for maintaining the ecological and economic sustainability of freshwater ecosystems (Miller et al., 2017; Huisman et al., 2018). The causes for this apparent expansion of CyanoHABs are unknown, but numerous studies suggest that eutrophication and climate change are two processes that may promote their proliferation and expansion (Moore et al., 2008; O'Neil et al., 2012; Gobler et al., 2016; Pearl, 2018; Benayache et al., 2019; Jankowiak et al., 2019). Therefore, in the African continent the cumulative effects of global change, including climate warming and increased human population, followed by an increase in nutrient loads from either agricultural run-off or sewage treatment plants, will trigger the trend towards continuous proliferation of potentially toxic cyanobacteria species and degradation of the water quality (Nyenje et al., 2010; Ndlela et al., 2016). In addition to continuous degradation of their coastal areas, some African arid countries are identified with serious future limitations for water quality and quantity. Consequently, to overcome these issues and to support their economic and social development, certain countries such as Mauritania with low freshwater resources that do not exceed an average of 2000 m3 per year and per inhabitant, supplied important efforts of mobilization of the superficial water resources by construction of dams. However, the discharge of sewage, industrial pollutants, eroding soil, and deposition of effluents rich in nitrogen (N) and phosphorus (P) in these reservoirs potentiate the development of some toxic cyanobacterial species (Nyenje et al., 2010; Ndlela et al., 2016). One of the consequences of the cyanobacterial occurrence is the production of cyanotoxins, which can contribute to degrade the water quality and hazards to human and animal health (Niamien-Ebrottie et al., 2015; Svircev et al., 2017). Among these cyanotoxins, it appears that liver-toxic microcystins (MCs) are found most commonly in cyanobacterial blooms worldwide and are one of the most hazardous important pollutants in freshwater ecosystems in terms of concentration and risk for the human health (Corbel et al., 2014; Rastogi et al., 2014; Bouaïcha et al., 2019). Consequently, to protect consumers from the adverse effects of MCs, the WHO proposed a provisional upper limit in drinking water of 1 µg L−1 for the most toxic congener MC-LR and a Tolerable Daily Intake (TDI) of 0.04 µg kg−1 body weight (WHO, 2003).

Recent studies reported that expansion of CyanoHABs in freshwater ecosystems were promoted by nutrient loading and elevated temperatures (Jankowiak et al., 2019; Wurtsbaugh et al., 2019; Griffith and Gobler, 2019). Therefore, the availability of nutrients such as macro-elements, P and to a lesser extent N is essential for growth of cyanobacteria (Wurtsbaugh et al., 2019). In developing countries, like those in sub-Saharian Africa, wastewaters from sewage and industries in urban areas, which are often discharged untreated in the environment, are increasingly becoming a major source of these nutrients (Wurtsbaugh et al., 2019). The reservoir Foum-Gleita (Mauritania) investigated in the present study is, however, far from large metropolitan cities and it is under only anthropogenic pressures through discharge of communal wastewater, intensive livestock farming, irrigation and run-off from agricultural practices and sedimentation of eroded matter. Besides, P derived from the phosphate rocks provided by the phosphate mines that are present in the watershed of this reservoir can be expected to contribute more to cyanobacterial proliferation throughout the year. In fact, several studies have indicated that eutrophication, especially by P, often leads to significant shifts in phytoplankton species composition towards bloom-forming cyanobacteria (Steinberg and Gruhl, 1992; Steinberg and Hartmann, 1998). In addition to the presence of natural phosphate rocks loading water with high P concentrations, elevated temperature detected in this reservoir's water throughout the year could be a supplementary factor in triggering the growth of cyanobacteria. Indeed, several monitoring and modelling studies have assigned to the synergistic effects of eutrophication and temperature elevation on cyanobacterial growth (Elliott et al., 2006; Kosten et al., 2012; Paerl and Paul, 2012; Rigosi et al., 2014; Benayache et al., 2019; Jankowiak et al., 2019). In fact, maximum growth rates are attained by most cyanobacteria at temperatures exceeding 25 °C, in contrast to eukaryotic algal groups, which exhibit growth optima typically below 25 °C (Paerl and Huisman, 2009; Elliott, 2010; Paerl et al., 2011; Chaffin et al., 2011; Paerl and Paul, 2012; Thomas and Litchman, 2016; Mantzouki et al., 2018). For example, within the North-African basin, in Egypt (Brittain et al., 2000; Mohamed et al., 2003), Morocco (Oudra et al., 2001), Algeria (Nasri et al., 2004; 2007) and Tunisia (El Herry et al., 2007; 2008) cyanobacterial blooms have been observed in several surface freshwaters during the warmest months particularly in summer and in early autumn.

The main objective of this study was to evaluate, for the first time, the impacts of the phosphorus leaching from the exploitation of phosphate mines present in the watershed of the Foum-Gleita reservoir (Mauritania) on the physicochemical quality of water and its major contribution to the proliferation of harmful cyanobacteria in this reservoir during the study period.

2 Material and methods

2.1 Study sites and field measurements

The Foum-Gleita reservoir (Latitude: 16° 09′ 26.918″ North, Longitude: 12° 39′ 57.450″ West) is part of black Gorgol Rivers's catchment area (Fig. 1). It is situated 95 km East of the city of Kaédi, in the mountainous region of Gorgol, with the average elevation of 32 m and it was constructed in 1984. The climate in the reservoir watershed is typically Sahelian, characterized by two distinct seasons: a long dry season of 9 to 10 months (October‑June) characterized by a cool period (October‑February) and a warm period (March‑June), and a short rainy season (July‑September). Yearly average rainfall in the basin is approximately 255 mm/year with an annual average temperature of 31 °C (19 minimum and 44 °C maximum). The reservoir has a surface area of approximately 160 km2 (humid season) and 50 km2 (dry season) and shows an effective storage capacity of 1 billion m3 and a maximum depth of 9 m. The main inflow to the reservoir is that from the black Gorgol River (94%) with an average annual flow 343 million m3 for 3 months (July‑September). About 36% of the water flow from this reservoir is used for irrigation (downstream) and 49% for drinking water for human and livestock farming. The main types of land use within the catchment area are agriculture (9000 hectares upstream and 11,200 hectares downstream the dam), intensive livestock farming (about 25,000 cattle, 15,000 sheep and goats, and 10,000 camels), about 3300 domestic animals (donkey and horses) and phosphate mines (94,500 hectares). However, urban living areas (5309 families with 26,544 residents) cover only a minor portion of the catchment area of this reservoir. Due to the reservoir being both an agricultural and a mining (phosphate) region, its water quality suffers considerably from the leaching of nutrients such as nitrogen specially from intensive livestock farming and agriculture and phosphorus specially from eroding soil and phosphate rocks and shows a history of cyanobacterial blooms.

During this study, the Foum-Gleita reservoir's water was regularly monitored on a monthly basis from September 2017 to August 2018. The sampling was carried out on three sites (S1, S2, and S3) as indicated in Figure 1. The first site (S1) is located at the mouth of the black Gorgol River, which brings many nutrients from the agricultural region upstream of the reservoir. The second site (S2) is in a sheltered area of the reservoir and far from any anthropogenic pollution. The third site (S3) is located next to the village of M'bout where all the inhabitants come to wash their clothes and the animals come to drink every day. In addition, this site is characterized by its proximity to the traditional exploitation of phosphate mine in this region. Therefore, the S3 site is considered to be the most polluted one, firstly by the influx of a large quantity of nitrogen from the excrements and animal urine and untreated wastewater of residents, and secondly by the leaching of phosphorus from the phosphate mine.

At each site, surface water (0.1–0.5 m) temperature (T), salinity and pH were measured in situ by means of a C4E multi-parameter field datalogger (Calypso). Dissolved oxygen (DO) was measured using Winkler's chemical method. Water transparency was estimated using a Secchi disk. In addition, two liters of subsurface water (depth 0.5 m) were collected in each site from which four samples were obtained for further analysis of chemical parameters (nitrate, nitrite, ammonium, orthophosphate, total phosphorus and iron), chlorophyll-a, phytoplankton identification and quantification, and dissolved and particulate MCs determination. Water samples for phytoplankton identification and enumeration were preserved with Lugol's iodine solution (5% v/v) and samples for chemical parameters and MCs analysis were stored immediately in a portable refrigerator (4 °C) and brought back to the laboratory and stored at 4°C for further analysis (see sample analysis section below for details).

thumbnail Fig. 1

Sampling sites (S1, S2, and S3) and catchment area of the Foum-Gleita Reservoir. Ellipse indicates the phosphate mine in the city of Kaedi, open dots indicate major cities, and thick lines indicate Gorgol, Blanc, and Senegal Rivers. The insert shows the location of catchment area of the Foum-Gleita Reservoir within the map of Mauritania (modified from Van-Asten et al. (2002)).

2.2 Sample analysis

Identification and enumeration of phytoplankton was performed using light microscopy, following the method of Utermöhl (1958). For each preserved phytoplankton sample, 10 mL aliquots were settled for 24 h on a gridded chamber before being visually scanned on an inverted microscope (Leitz, Fluovert) at 20× and 40×. The two dominant cyanobacteria taxa have been identified at the species level, while the other minor ones have been identified only at the genus level, using universally accepted taxonomic keys described by Geitler (1932), Komárek and Anagnostidis (1999, 2005) and Wacklin et al. (2009), and then all have been quantified with a minimum of 100 units counted per sample. The biovolume (mm3 L−1) of Microcytis sp., Dolichospermum sp., Oscillatoria sp. and Planktothrix sp. was then estimated. Briefly, the mean number and the dimension of cells from 50 Microcystis colonies and 50 Dolichospermum filaments per sample were estimated. For Oscillatoria and Planktothrix, the average length and width of 50 filaments per sample were also estimated. The biovolume of each taxa was calculated as described by Hillebrand et al. (1999) by assuming each cell as sphere for Microcystis and Dolichospermum and each filament as a cylinder for Oscillatoria and Planktothrix species. The number of cells per liter for Microcystis and Dolichospermum species and filaments per liter for Oscillatoria and Planktothrix species were then multiplied by the average cell and filament biovolume. Other phytoplankton groups were identified according to the morphological characteristics described by Bourrelly (1972, 1981, 1985), Reynaud and Laloë (1985), and Olenina et al. (2006), and then quantified as cell per liter with a minimum of 100 units counted per sample.

Nutrient samples were taken from a depth of 0.5 m to determine nitrate (N-NO3 –), nitrite (N-NO2 –), ammonium (N-NH4 +), P-PO4 −3 (dissolved phosphorus) (DIP), total phosphorus (TP) and iron (Fe) on a DR2800 spectrophotometer (Hach) using methods described by Rodier (1996). Concentrations (mg L−1) of N-NH4 +, N-NO3 – and N-NO2 – were determined with Nessler, sulfosalicylic acid and the Zambelli reaction methods, respectively (Rodier, 1996). Total dissolved inorganic nitrogen (DIN) was then calculated as the sum of N-NH4 +, N-NO3 – and N-NO2 –. Dissolved phosphorus (DIP) was measured by the ascorbic acid method and total phosphorus (TP) was analyzed by the persulfate digestion method (Rodier, 1996). Iron (Fe) was measured by the phenentroline 1-10-dimethyl-2.6 addition method (Bergounhou et al., 1996). For chlorophyll-a (Chl-a) analysis, raw water samples (250 mL) were filtered through 0.45 µm microfiber glass filters (Whatman GF/C, diameter: 25 mm). Filters were then extracted in 5 mL of methanol in cold and darkness. Chlorophyll-a was then determined by the fluorimetry method using a Jenway 6200 fluorimeter according to the method described by Neuveux (1974).

To determine evaluate the eutrophication state of Foum-Gleita reservoir, the Trophic State Index (TSI) method of Carlson (1977) was used. The TSI index value is calculated using only two quality parameters such as Chl-a (μg L−1) and TP (μg L−1) following the method described in Ghashghaie et al. (2018). However, the depth of the Secchi disk was not used in the calculation of this index because the waters of this reservoir are always cloudy by the presence of a very high rate of clay. Total amount of TSI is therefore, the average of TSI (Chl-a) and TSI (TP). Value of TSI varies between 1 and 100. Based on this index, the trophic state of this water reservoir was categorized following the classification table of eutrophication (Ebrahimpour et al., 2012).

2.3 Microcystins extraction, analysis, and identification

For MCs extraction, water samples (500 mL) were filtered through glass microfiber filters GF/C (Whatman, diameter: 47 mm) to separate dissolved and particulate MCs and then treated as described in Bouhadadda et al. (2016). Microcystin fractions were then analyzed and quantified by High Performance Liquid Chromatography-tandem mass spectrometry (HPLC-MS/MS) using a Spectraphysics 8000 HPLC system and a Bruker ESI mass spectrometer (electrospray ionization) as described by Bouhadadda et al. (2016) with little modifications. Briefly: ESI, cone voltage: 90 V, mass/load ratio: 50 to 1500 m/z, analyzer/detector: 1 Hz, software HyStar 3.2 and DataAnalysis 3.4. Chromatographic separation was performed on a Chrompack-Netherlands C18 Microsphere reverse phase column (150 × 4.6 mm, 5 µm) maintained at 30 °C. The mobile phase consists of a solvent A: MilliQ water +0.1% TFA (v/v) and a solvent B: Acetonitrile +0.1% TFA (v/v) with a flow rate of 1 mL/min. The injected volume is 20 µL and the detection wavelength is 238 nm. To identify the peak corresponding to a given MCs, a standard solution containing MC-LR, MC-RR and MC-YR (Biochemicals Alexis) was injected and retention times and mass/charge ratios of the different variants present in the water samples were compared with those of the three microcystin standards. Full-scan spectra were obtained over the mass range of 100–1200 Da. Analyses in MS-MS were performed by Collision Induced Dissociation (CID) using argon at 3.4 mbar in collision cell, with 50 and 70 eV collision energy, in parent mode acquiring parents of the m/z 135 ion and in daughter mode fragmenting the [M+H]+ ions. The [M+H]+ ion currents was used to evaluate the microcystin relative concentrations.

2.4 Statistical analysis

All statistical analysis were performed using IBM SPSS Statistics 20 software. One-way ANOVA followed by the Tukey post-hoc test was performed to compare environmental variables including limnological variables: water temperature (T), hydrogen potential (pH), salinity, Secchi distinction depth (Secchi), dissolved oxygen (DO), nitrate (N-NO3 –), nitrite (N-NO2 –), ammonium (N-NH4 +), total dissolved inorganic nitrogen (DIN), dissolved inorganic phosphorus (DIP), total phosphorus (TP), Iron (Fe), DIN:TP mass ratio (DIN/TP) and biological variables: Chlorophyll-a (Chl-a) and microcystin-LR (MC-LR) concentrations, M. aeruginosa and D. flos-aquae biovolumes in samples collected from the three sites. Pearson's correlation was then conducted to identify the relationship between these variables. The strength of the correlation was described using the guide that Evans (1996) suggested according to the absolute value of r.

To explore the relationship between dependent variables (M. aeruginosa and D. flos-aquae biovolumes, and MC-LR concentration) and independent variables (temperature, pH and nutrients: DIN, TP and Fe) a stepwise multiple linear regression with forward selection were performed to detect the contribution of each independent variable. The stepwise regression consists of incrementally adding and removing predictor variables, in the model, in order to find the subset of variables R2 resulting in the best performing model with the highest value of adj. R2. The variables values (DIN, TP, Fe, and MC-LR concentrations and biovolume of Microcystis and Dolichospermum) were transformed to logarithm (log10) except for the water temperature and pH. In total, fifteen models were constructed to predict changes in the biovolume of M. aeruginosa and D. flos-aquae and the concentration of MC-LR in the surface water of the Foum-Gleitareservoir.

3 Results

3.1 Physicochemical characteristics of studied sites

The spatial and temporal variations of the environmental parameters including limnological and biological variables in the surface water samples collected at the three different sites (S1 to S3) in the Foum-Gleita reservoirduring this study were presented in Table 1. Mean water temperature, pH, Secchi disk depth, salinity and dissolved oxygen concentration were not significantly different within sites. Surface water temperature shows similar variations ranging from 20 to 30 °C within sites, with a maximum value observed in May 2018, during the warm-dry season. The reservoir's water was slightly alkaline and poorly transparent at all sampling sites throughout the study period with pH values ranged from 7.1 to 8.06 and Secchi diskdepths ranged from 0.16 to 0.33 m, which was disturbed by the very high rate of clay in the surface water. However, the reservoir's surface water showed mean dissolved oxygen concentrations ranged from 7.83 to 10.06 mg L−1. Nutrient concentrations varied on a spatiotemporal basis within sites; however, significant differences were observed only for mean concentrations of nitrite between sites S1 and S3 (p = 0.012) and S2 and S3 (p = 0.009), and ammonium between sites S1 and S2 (p = 0.034), and S2 and S3 (p = 0.012). Mean iron concentration was similar within sites ranging from 0.12 (S1) to 0.15 mg L−1 (S2 and S3). Mean TP concentration was higher in site S3 (0.36 mg L−1) than in site S1 (0.32 mg L−1) and S2 (0.27 mg L−1) throughout the sampling period, however, there is no significant difference between sites. Meanwhile, dissolved phosphorus (DIP) concentration ranged from 0.15 to 0.42 in S1, from 0.16 to 0.32 in S2 and from 0.15 to 0.50 mg L−1 in S3 but with no significant difference was observed within sites. Mean N-NO3 – and DIN concentrations were higher in site S3 ranging from 1.89 to 6.17 and from 2.16 to 6.53 mg L−1, respectively without any significant difference between sites. Mean concentration of Chl-a in surface water samples was between 6.22 and 10.16 µg L−1, with a maximum value (19.31 µg L−1) detected in site S3 during the warm-dry season in May 2018 that was significantly different only with the S1 value (p = 0.036). Based on the calculated Carlson's Trophic Status Index (TSI), the Foum-Gleita reservoir with TSI ranging from 66 to 80 can be classified as hypereutrophic (Fig. 2).

Table 1

Mean and standard deviations of environmental parameters of the Foum-Gleita reservoir (Mauritania) during one-year study period (from September 2017 to August 2018). T: surface water temperature; pH: water hydrogen potential; Secchi: secchi disk depth; DO: dissolved oxygen; N-NO3 –: nitrate; N-NO2 –: nitrite; N-NH4 +: ammonium; DIN: dissolved inorganic nitrogen; P-PO4 −3: dissolved phosphorus (DIP); TP: total phosphorus; DIN/TP: DIN:TP mass ratio; Fe: iron; Chl-a: chlorophyll a. The significance of the regression coefficients (Pearson?s r) is indicated by *0.01 < p < 0.05, **0.001 < p < 0.01, and ***p < 0.001.Values followed by the different letters are significantly different (p < 0.05). N: number of samples; SD: standard deviation; *: p < 0.05.

thumbnail Fig. 2

Radar Graph of the trophic state index (TSI) values calculated at different surface water sampling sites in Foum-Gleita Reservoir during the study period from September 2017 to August 2018.

3.2 Phytoplankton phyla dynamics

The seasonal quantitative and qualitative variations of phytoplankton from September 2017 to August 2018 in the Foum-Gleita reservoir were shown in Figure 3. Six phytoplankton phyla were identified in this reservoir including Chlorophyta, Cyanobacteria, Bacillariophyta, Cryptophyta, Miozoa and Euglenozoa (Fig. 3). The Chlorophyta was the most diverse phylum, accounting for 40–60% of the total species number of phytoplankton, with the highest abundance occurring during dry season months in the sites S1 and S3 (December 2017 to June 2018) and in the S2 (April 2018 to June 2018). This phylum was mainly dominated by the order Desmidiales and especially by the genera Closterium, Staurodesmus and Staurastum. The Cyanobacteria was the second phylum in abundance, accounting for 17–34% of the total species number of phytoplankton, with the highest abundance occurring in the site S3 during wet season months (August‑October) when the temperature of the water was high. Cyanobacteria in this reservoir were presented by colony-forming genera Microcystis, Gloeocapsa and Chroococcus as well as the solitary filamentous genera Dolichospermum, Oscillatoria, Planktothrix, Lyngbya, and Spirulina with the dominance of the two species Dolichospermum flos-aquae (D. flos-aquae) and Microcystis aeruginosa (M. aeruginosa) Bacillariophyta phylum occupied the third position after Chlorophytaceae and Cyanobacteria where they represent 11–13% of the total species number . This phylum was mainly dominated by the orderPennatophycidae, especially by the genera Pinnularia, Fragilaria and Gomphonema, with higher densities in site S1 during wet season months (September‑November 2017) and in site S2 during wet and dry season months (September 2017‑March 2018). Cryptophyta represented by the genera Cryptomonas and Rhodomonas, Miozoa represented by the genera Prorocentrum and Symbiodinium, and Euglenozoa dominated by the genus Euglena were the less abundant phyla with a relative species number that ranged from 7 to 9%, 5 to 6% and 3 to 5%, respectively. In conclusion, the abundance of the two dominant cyanobacteria species D. flos-aquae and M. aeruginosa in the three sampling sites (S1 to S3) peaked during the wet season months (July to October) and was lower in the dry season months (November to March) (Fig. 4).

thumbnail Fig. 3

Seasonal variations of the relative abundance of phytoplankton phyla at different surface water sampling sites in Foum-Gleita Reservoir during the study period from September 2017 to August 2018.
thumbnail Fig. 4

Dynamic of Dolichospermum flos-aquae and Microcystis aeruginosa, and variability of total MC-LR concentration at different surface water sampling sites in Foum-Gleita Reservoir during the study period from September 2017 to August 2018.

3.3 Cyanobacteria community dynamics and variability of MC-LR concentrations

The two dominant species D. flos-aquae and M. aeruginosa, 47 and 39% of total cyanobacteria, respectively showed a constant presence throughout the study period in all sampling sites. However, theirs peaks wereobserved in site S3 during the warm-rainy season months and when the DIN/TP mass ratio was less than 10, with two well pronounced peaks noted in September 2017 (7.222 and 3.899 mm3 L−1, respectively) and August 2018 (7.095 and 4.221 mm3 L−1, respectively) (Figs. 4 and 5). Both Oscillatoria sp., Planktothrix sp. and Lyngbya sp. were less abundant (0.8, 0.4 and 0.1% of total cyanobacteria, respectively) and showed an irregular monthly presence in the three sites. The species Oscillatoria sp. appeared in the three sites only during the end of the rainy season months (September, October, and November) with a peak in October 2017 (0.045 mm3 L−1) in S3. However, Planktothrix sp. was observed only in sites S2 and S3 with low irregular densities during dry season months with a peak in March 2018 (0.003 mm3 L−1) in S2. As for the species Lyngbya sp., it appeared only once at site 3 during September 2017 with a very negligible biovolume (0.0001 mm3 L−1). For this reason, these last three species were not considered in the statistical analysis.

The four species, M. aeruginosa, Oscillatoria sp., D. flos-aquae, and Planktothrix sp., observed in this reservoir, were known in the literature as potentially toxic and can biosynthesize MCs. Only one variant of MCs was found in the three sampling sites throughout the study period and identified as microcystin-LR (MC-LR) (Fig. 6). Measurable MC-LR levels were detected in the three sites with total (dissolved + particulate) concentrations ranging from the acceptable detection limit of 0.001 to 3.548 µg L−1, where site S3 had higher MC-LR concentration than the other two sites (Fig. 4). Dissolved MC-LR concentrations were always lower than the particulate concentrations, with proportions in the surface water samples in all sites never exceeded 0.5% of the total MC-LR concentrations. Total MC-LR concentrations followed the same pattern as for M. aeruginosa and D. flos-aquae biovolume, reaching a maximum concentration of 3.548 μg L−1 at site S3, where the biovolume of these two cyanobacterial species peaked during warm-wet season months (July-September) (Fig. 4). However, the lowest levels of MC-LR were observed during cool-dry season months (November 2017 to March 2018) when the abundance of cyanobacteria was the lowest (Fig. 4).

thumbnail Fig. 5

Abundance of Dolichospermum flos-aquae and Microcystis aeruginosa as a function of Temperature (°C) and DIN/TP mass ratio at water surface sampling site 3 (S3) in Foum-Gleita Reservoir during the study period from September 2017 to August 2018.
thumbnail Fig. 6

LC-UV chromatograms of microcystin-LR standard (upper) and cyanobacterial bloom sample extract (middle) harvested in September 2017 at sampling site 3 (S3) and LC-MS/MS precursor ion spectrum (down) of the peak at 5.31 min exhibits parent ion [M+H]+ of MC-LR (m/z: 995.1).

3.4 Relationships between environmental factors and cyanobacterial abundance, or MC-LR concentrations

The Pearson's correlation between limnological variables and biological variables such as the biovolume of the two most abundant cyanobacteria species M. aeruginosa. and D. flos-aquae, and Chl-a and MC-LR concentrations were presented in Table 2. A significant correlation was observed between the biovolume of M. aeruginosaand the water temperature,the DIN, TP, Fe concentrations and the DIN:TP mass ratio Similarly, the biovolume of D. flos-aquae was significantly correlated to TP, DN, Fe concentrations, to water pH, and the DIN:TP mass ratio. Total MC-LR concentration was significantly correlated to DIN, TP and Fe concentrations, water temperatureand DIN:TP mass ratio. In addition, MC-LR concentration was strongly, positively correlated to the biovolume of M. aeruginosa. However, it was not significantly correlated to the biovolume of D. flos-aquae.

In order to define which independent variables explain most of the variation of the biovolume of the two abundant toxic species M. aeruginosaand D. flos-aquaeand the MC-LR concentration, we perform a stepwise multiple linear regression (MLR) analysis. The final set of the predictor independent variables includes DIN, TP, and Fe concentrations and the surface water temperature (T) and pH (Tab. 3). The maximal significant values obtained for adj. R 2 were high ranging from 0.485 for D. flos-aquae, to 0.902 for M. aeruginosa, and 0.909 for MC-LR. According the formula of the regression model (Tab. 3, model 5) including all independent variables, TP and DIN concentrations were the most negative (Beta = −0.066) and positive (Beta = +0.035) influence factors to predict the biovolume of D flos-aquae, whereas iron (Beta = +0.001) and pH (Beta = −0.014) showed the lowest effect. However, for the biovolume of M. aeruginosa (Tab. 3, model 10) the most influence independent variables were concentrations of TP (Beta = +0.240) followed by DIN (Beta = −0.036) and iron (Beta = −0.017), and water temperature (Beta = −0.016). However, the most influence factors to the concentration of MC-LR were concentrations of TP (Beta = −0.640) followed by DIN (Beta = +0.190) and iron (Beta = +0.008), and water temperature (Beta = +0.002).

Table 2

Correlations between cyanobacterial abundance (Dolichospermum flos-aquae and Microcystis aeruginosa), microcystin-LR (MC-LR) concentration, and environmental factors (surface water temperature- T; water hydrogen potential- pH; secchi disk depth- Secchi; dissolved oxygen- DO; nitrate- N-NO3 –; nitrite- N-NO2 –; ammonium- N-NH4 +; dissolved inorganic nitrogen- DIN; dissolved phosphorus- P-PO4 −3 (DIP); total phosphorus- TP; DIN:TP ratio- DIN/TP; iron- Fe; chlorophyll a- Chl-a in the Foum-Gleita reservoir (Mauritania). The significance of the correlation coefficients (Pearson's r) is indicated by *0.01 < p < 0.05, **0.001 < p < 0.01, and ***p < 0.001.

Table 3

Linear regression models explaining the abundance of the two dominant species Dolichospermum flos-aquae and Microcystis aeruginosa, and MC-LR concentration in the Foum-Gleita Reservoir (Mauritania). The models result from a forward stepwise selection procedure and explain M. aeruginosa and D. flos-aquae biovolume (log MycBiov and log DolBiov in mm3 L−1) and Microcystin-LR concentration (log [MC-LR] in μg L−1) by the independent variables: dissolved inorganic nitrogen (log DIN in mg L−1), total phosphorus (log TP in mg L−1), and iron (log Fe in mg L−1), and surface water temperature (T in °C) and pH. All regression models were significant (p < 0.0001). The significance of the regression coefficients is indicated by * (0.01 < p < 0.05), ** (0.001 < p < 0.01), and *** (p < 0.001). Number of observations = 36.

4 Discussion

4.1 Hydro-physicochemical parameters and dynamics of phytoplankton

The phytoplankton community of the Foum-Gleita reservoir was considerably evolved since its creation in 1984, which characterized by increasing appearance of cyanobacterial blooms over a long period of the year. This striking change was probably linked to different factors such as urbanization with the absence of a wastewater treatment network and agricultural and phosphate mines activities in the watershed, which could contribute both to a greater supply of N and P, and a long period of sunshine (around 350 days) accompanied by the increase of water temperatures. Therefore, continuous discharge of nutrients combined with a typical Sahelian climate, characterized by two distinct seasons: a long dry season (October-June) and a short rainy and warmer season (July-September) provide a considerable opportunity for cyanobacteria such as M. aeruginosaand D. flos-aquae to grow in this reservoir. Similarly, Fernández et al. (2012) reported that cyanobacteria blooms dominated principally by M. aeruginosa and Anabaena circinalis were recurrent during summer and early autumn months since 1982 in the hypereutrophic Paso de las Piedras Reservoir (Argentina). Moreover, Ndela et al. (2017) reported that water scarce regions in Africa, which characterized by low rainfall, have higher reports on cyanobacterial blooms than regions with high rainfall. Likewise, Marion et al. (2017) reported that the region with proportionately the most cyanobacterial blooms in the United States was a semi-arid landscape subject to severe droughts; and when the water shortage in this region was coupled with high nutrient inputs, the probability of cyanobacterial blooms increases.

Microscopic analysis of water samples showed that phytoplankton in this reservoir was composed essentially with Chlorophycta–Cyanobacteria assemblage, with some Bacillariophyta. Other phyla such as Cryptophyta, Miozoa and Euglenozoa were also present but with much lower importance, although some local short-term developments can sometimes be observed, as for the Cryptophyta phylum at the site S2 in July-August (Fig. 3). Overall, the dynamic of phytoplankton in the Foum-Gleita reservoir was quantitatively dominated by the Cyanobacteria phylum during the rainy period (July-September) specially in the site S3 at which anthropological pollutions were the most important with high concentrations of DIN (6.53 mg L−1) and TP (0.56 mg L−1) combined with a high water temperature (30.2 °C). However, when the water temperature starts to drop during the dry season months (November-April), the Chlorophyta become the dominant group in this site (S3) although the cyanobacteria were always present as the second group with relative abundances from 17 to 29% (Fig. 3). In the other two sites, S1 located at the mouth of the Gorgol Noir River and S2, which is far from any anthropogenic pollutions, the phytoplankton community, was characterized by a distinct abundance succession of Bacillariophyta/Chlorophyta. However, the Cyanobacteria were always present in third position except in the site S2 in July-August where they were present in the fourth position after the Cryptophyta (Fig. 3). Our results are consistent with other studies which found that phytoplankton succession in tropical aquatic systems was characterized by a distinct shift between dry and rainy seasons: Chlorophyceae/Cyanophyceae in Lake Tanganyika (Tanzania) (Descy et al., 2005), Diatomophyceae/Cyanophyceae in Lake Victoria (Kenya) (Kling et al., 2001) and in Lake Guiers (Senegal) (Bouvy et al., 2006; Tian et al., 2012). While in temperate regions such as in northern Africa, the phytoplankton communities were dominated by the Diatomophyceae group in winter and Chlorophyceae in spring-summer, succeeded by Cyanophyceae in autumn (El Herry et al., 2008; Gellati et al., 2017; Hammou et al., 2018). In other regions such as Europe and America, a global field data analysis of 143 lakes, has been shown that cyanobacteria biomass increases steeply with temperature in lakes with high rates of light absorption (Kosten et al., 2012). In addition, Jankowiak et al. (2019) reported that in both field surveys and experiments, cyanobacterial abundance in Lake Erie (situated at the international boundary between Canada and the USA) significantly increased in response to elevated N, with the greatest increases in combined high N and P concentrations, and water temperature. In contrast, Almanza et al. (2019) showed that some cyanobacterial genera such as Aphanizomenon, Aphanocapsa, Aphanothece, and Dolichospermum can form bloom in freshwater ecosystems in south-central Chile at low temperatures in autumn and winter (10.8–15.6 °C), suggesting that eutrophication is the main factor for bloom formation of these genera independent of the water temperature.

Phosphorus (P) is commonly considered to be the limiting nutrient in freshwater ecosystems, and high concentrations of this nutrient often correlate to the occurrence of cyanobacterial blooms worldwide (O'Neil et al., 2012; Xu et al., 2015; Huang et al., 2016; Gobler et al., 2016; Harke et al., 2016; Li et al., 2018). It is well established that changes in nutrient concentration and stoichiometry, for example decreasing N to P ratio, can shift phytoplankton assemblages toward cyanobacteria dominance (Trimbee and Prepas, 1987; Downing and McCauley, 1992; Watson et al., 1997; Paerl et al., 2011; Gobler et al., 2016). Although P was generally considered the main limiting nutrient for the growth of cyanobacteria in freshwater ecosystems, N can sometimes be co-limiting, since it was a quantitatively important bio-element (O'Neil et al., 2012). In addition to rates of these two nutrients, their ratio (TN/TP) has been also considered as one of the main parameters for determining the growth of cyanobacteria (Smith, 1983; Jeppesen et al., 2009). For example, Havens et al. (2003) reported that keeping absolute N and P concentrations low and combined with maintaining a high TN/TP ratio above 30 reduces the risk of cyanobacterial proliferation. However, a high concentration of P and a low N/P ratio tend to favor the growth of some cyanobacterial species, especially heterocystous species like Dolichospermum sp., in which N deficits can be compensated by nitrogen fixation from the atmosphere (Smith, 1983; Horne and Commins, 1987; Li et al., 2018). Similarly in this study, although N and P concentrations were always high in the Foum-Gleita reservoir throughout the period of study, the highest abundance of the two dominant cyanobacterial species D. flos-aquae and M. aeruginosa was observed when the DIN/TP mass ratio was less than 10 (Fig. 5). Recently, Bogard et al. (2020) tested using experimental mesocosms the evolution of phytoplankton when adding a nitrogen gradient (0 to 18 mg L−1) in the shallow hypereutrophic lake Wascana (Canada) containing strong concentrations of total dissolved phosphorus (400–500 µg L−1) and orthophosphate (280–400 µg L−1), similar to the average values recorded in the Foum-Gleita reservoir. The results of this study showed that low-to-moderate concentrations of N (1–3 mg L−1/week) promoted toxic cyanobacterial dominance and elevated concentrations of MCs. Conversely, high concentrations of N (up to 18 mg L−1/week) led to the dominance of chlorophytes over cyanobacteria and lower MCs content. Therefore, our study provides new insight into the effects of moderate N concentrations (up to 6 mg L−1) on phytoplankton community composition with dominance of the cyanobacteria group in P-rich freshwater ecosystems.

4.2 Dynamics of M. aeruginosa and D. flos-aquae and correlations with environmental factors

The cyanobacterial community in the Foum-Gleita reservoir was composed predominantly of M. aeruginosa and D. flos-aquae which were known amongst the most common MCs producer and bloom-forming species throughout the world (Cook et al., 2004; Sukenik et al., 2012; Harke et al., 2016; Li et al., 2016; Haakonsson et al., 2017; Pearl, 2018; Benayache et al., 2019). The growth pattern trend of these two dominant species was the same at the three sites (S1 to S3); showing low abundance during December to February when the surface water temperature was a little lower (approximately 20 °C). However, the biovolume of both species starts to increase since March in parallel with temperatures to reach a peak in September when the temperature of the water reaches 30 °C (Fig. 5). In non-limiting N and P ecosystems like this reservoir, high water temperatures can may favor cyanobacteria by maximizing their growth rates compared to the other phytoplankton groups (Paerl and Paul, 2012; Carey et al., 2012). Despite a similar trend of growth of M. aeruginosa and D. flos-aquae in this reservoir at the three sampling sites, their biovolume was approximately 30 times higher in the site S3 (Fig. 4). One possibility for the difference in spatial dynamics was that S3 was the most exposed site to anthropogenic pollutions. In fact, the high concentrations of DIN and TP have been detected in this site with peaks reaching 6.53 and 0.56 mg L−1, respectively (Tab. 1).

By using Pearson's correlation, we observed a moderate significant negative correlation between the DIN concentration and the biovolume of D. flos-aquae (r = −0.565, p < 0.05), indicating that the decreases of the DIN concentration did enhance the abundance of this species. Conversely, within the M. aeruginosaits abundance rise when the DIN concentration increases as there was a moderate significant positive correlation (r = 0.592, p < 0.01) between these two variables. Our results were similar to some findings that reported that Dolichospermum, an N-fixing genus, is generally a competitive taxa under low N concentrations, while Microcystis species which are unable to fix N require more nutrient rich waters (Willén and Mattsson, 1997; Li et al., 2012). However, several other studies demonstrated that DIN is not always the only factor that determines the formation of cyanobacterial blooms but P has also commonly considered as the limiting nutrient in freshwater ecosystems. High concentrations of P (Xu et al., 2010; O'Neil et al., 2012; Huang et al., 2016; Benayache et al., 2019) with a low N/P ratio (Schindler, 1977; Ekholm, 2008; Jeppesen et al., 2009; Li et al., 2018) were often promote the growth of cyanobacteria. In this study, we observed a moderate significant negative correlation between the TP concentration and the biovolume of M. aeruginosa (r = −0.421, p < 0.05), indicating that the decreases of the TP concentration did rise the abundance of this species. Conversely, a strong significant positive correlation (r = 0.694, p < 0.01) was observed between the abundance of D. flos-aquae and the concentration of TP, indicating that its abundance rise when the TP concentration increases. This result was consistent with other studies that reported that Microcystis was able to up-regulate several P-scavenging genes allowing it to persist in low P conditions; however, under high orthophosphate (DIP) conditions Dolichospermum was the dominant cyanobacterial genera (Harke et al., 2012, 2016). In addition to the absolute concentrations of N and P, their ratio (N/P) has also considered as one of the main parameters in determining cyanobacterial growth (Schindler, 1977; Ekholm, 2008; Jeppesen et al., 2009; Li et al., 2018). In this study, strong significant positive (r = 0.630, p < 0.01) and moderate significant negative (r = −0.504, p < 0.01) correlations were observed between the DIN/TP mass ratio and the biovolume of M. aeruginosa and D. flos-aquae, respectively. However, the relationship between N/P ratios with abundance of nitrogen-fixing species such as Dolichospermum spp. has been subject to considerable debate. For example, several studies reported that TN or TP concentrations are better predictors of cyanobacterial dominance than the TN/TP ratio (Jensen et al., 1994; Downing et al., 2001; Kosten et al., 2012).

Given that both N and P concentrations in the Foum-Gleita reservoir were extremely high throughout the year and were always above the required levels for phytoplankton growth (Reynolds, 1997), they may not be, therefore, the only factors of the co-dominance of D. flos-aquae and M. aeruginosa in this reservoir. Consequently, other limnological factors such as water temperature and pH and iron (Fe) concentration may interact with DIN and TP in determining the relative dominance of these two species. We observed in this study that only M. aeruginosa presented a moderate significant positive correlation (r = 0.474, p < 0.05) with surface water temperature (Tab. 2). Therefore, the absence of a significant correlation between D. flos-aquae abundance and surface water temperature can probably be due to the small temperature variation during the period of study, ranging from 20 to 30 °C. It has been suggested that global warming will not increase bloom frequencies only directly by promoting cyanobacterial growth (Affan et al., 2015; Paerl et al., 2016; Visser et al., 2016; Huisman et al., 2018) but also indirectly via enhanced the release of P from sediments (Jeppesen et al., 2009). Taken together, these factors such as high uniform temperature conditions and high levels of DIN and TP might not only enhance the growth of toxic cyanobacteria but also affect cyanobacterial dynamics in this reservoir. In addition to the water temperature, water pH can also contribute to the proliferation of cyanobacteria in freshwater ecosystems. Indeed, Wicks and Thief (1990) reported that cyanobacteria usually prefer slightly alkaline conditions with pH ranging from 7.7 to 9.4. Similarly, in the Foum-Gleita reservoir with water pH values ranging from 7.1 to 8.06 a moderate significant negative (r = −0.553, p < 0.05) and a weak significant positive (r = 0.493, p < 0.05) correlations were observed between the water pH and the biovolume of M. aeruginosa and D. flos-aquae, respectively. Recently, Yang et al. (2018) reported that high temperature and pH favor M. aeruginosa to outcompete the green algae Scenedesmus obliquus. Moreover, our results also showed a strong positive (r = 0.671, p < 0.001) and a moderate negative (r = −0.478, p < 0.05) correlations between iron concentration and the biovolume of M. aeruginosa and D. flos-aquae, respectively. Experimental studies involving the addition of Fe alone as well as in combination with P and/or N have been conducted in the water samples from Lake Erie (United States) and several oligotrophic lakes in Sweden. The results of these studies showed that enrichment of Fe alone did not result in a significant increase in phytoplankton biomass, but the combined addition of Fe, P, and N yielded greater biomass increases than the addition of P and N alone (Twiss et al., 2000; Vrede and Tranvik, 2006; North et al., 2007). In another experimental study, Wang et al. (2015) evaluated the competitive capacity of M. aeruginosa to Pseudanabaena sp. in co-cultures with low (0.08 μM) and high (1 μM) FeCl3 concentrations. Their results showed that the cell abundance of M. aeruginosa decreased by 18.4% under the high concentration of Fe but increased by 23.7% under the low concentration; suggesting that M. aeruginosa had a competitive advantage compared to Pseudanabaena sp. in the presence of this nutrient. Moreover, Morton and Lee (1974) reported that Fe concentrations ranging from 0.1 to 1.0 mg L−1 caused a shift in the dominant type of alga grown from the green alga to M. aeruginosa.

The forward stepwise multiple linear regression analysis showed that the DIN concentration explained 86.3% of the variability in the biovolume of M.aeruginosa (Tab. 3, model 6), however, only 18.2% of the variability of D. flos-aquae (Tab. 3, model 1). When adding the TP concentration to the model, a slight increase of the adj. R2 value from 0.182 to 0.193 was observed for D. flos-aquae, however, a significant decrease of the adj. R2 value from 0.863 to 0.650 was observed for M. aeruginosa (Tab. 3, models 2 and 7, respectively). This is in accordance with the recent study of Jankowiak et al. (2019) showing that in response to gradients of N and P doses during a cyanobacterial harmful algal bloom in Lake Erie, N significantly increased the relative abundance of nondiazotrophic genera such as Planktothrix, while diazotrophic genera such as Dolichospermum and Aphanizomenon were enhanced by high concentrations of P. Moreover, regression models for the biovolume of these two dominant species explained maximum variance if the Fe concentration was included as an independent variable (Tab. 3, models 5 and 10, respectively). Therefore, the best overall linear model structure that explains the most variation in the biovolume of D. flos-aquae is the one including DIN, TP, and Fe concentrations, and the pH water as predictors (adj. R2  = 0.489). However, for M. aeruginosa stepwise regression resulted in a four-variable linear model, including also DIN, TP, and Fe concentrations and the water temperature as best predictors (adj. R2  = 0.902). This consistent to the results reported by Wever et al. (2007) showing that the combined addition of Fe, P and N to water samples from Lake Tanganyika (East African Rift Valley) stimulates the growth of cyanobacteria but not diatoms or chlorophytes.

4.3 Microcystin-LR concentrations and correlation with environmental factors

This study showed for the first time the presence of MC-LR in freshwater ecosystems in Mauritania with a peak (3.548 μg L−1) reaching 3.5 times higher the guide value recommended by the World Organization for health for drinking water which is 1 μg L−1 (WHO, 1998). Pearson's correlation analysis (Tab. 2) showed a significantly strong positive correlation between the concentration of MC-LR and the biovolume of M. aeruginosa (r = 0.606, p < 0.001). This strong significant relationship suggests that the presence of this toxin in the Foum-Gleita reservoir's water depends on the abundance of this species. However, despite this strong evidence, we cannot confirmed that M. aeruginosa was the only producer species of MC-LR, since the LC-MS analysis was conducted on an environmental sample containing several other cyanobacterial species such as D. flos-aquae, Oscillatoria sp., and Planktothrix sp. which are also known in the literature as potentially toxic and can biosynthesize MCs (Benayache et al., 2019). Therefore, to link a cyanobacterial species present in this reservoir to the biosynthesis of MC-LR, it would be necessary to isolate at least these four majority species and then search for the cyanotoxin-related marker such as the microcystin synthetase A gene (mcyA) using real-time PCR in each cyanobacterial isolate as described by Furukawa et al. (2006).

Although to-date there are 279 microcystin congeners characterized (Bouaïcha et al., 2019), only the most frequent and toxic variant, MC-LR was detected in this reservoir. As reported in several studies worldwide, MC-LR was usually detected as the major variant in cyanobacterial blooms specially in Europe and Africa, however, it frequently co-occurred with one or up to more than 10 other minor variants (Bouhaddada et al., 2016; Ndela et al., 2016; Taranu et al., 2019). Numerous field and laboratory studies have demonstrated that the biosynthesis of MCs is strain dependent (Vézie et al., 1998; Dittmann et al., 2015). However, their structural diversity is even more complex, since certain environmental factors such as the availability of N and P nutrients, light intensity, iron limitation, water temperature and pH are involved in enhancing or suppressing the expression of microcystin synthetase genes (Jähmichen et al., 2011; Pimentel and Giani, 2014; Dittmann et al., 2015; Puddick et al., 2016; Taranu et al., 2019). However, the relationship between these environmental factors and MC biosynthesis is invariably complex and gaps remain in the understanding of how these environmental factors can modulate the relative abundance of MC variants and their concentrations in a cyanobacterial bloom. In this study, we observed that the concentration of MC-LR was positively correlated to concentrations of DIN (r = 0.471, p < 0.05) and Fe (r = 0.574, p < 0.001), and the water temperature (r = 0.466, p < 0.05), however, it was negatively correlated to the concentration of TP (r = −0.409, p < 0.05). By applying stepwise linear regression with incrementally adding these four predictor variables, we observed that the concentration of DIN alone explained 72.3% of the variability in the concentration of MC-LR (Tab. 3, model 11), suggesting that N-increase resulted in an increase in MC-LR content. This is in agreement with other studies showing that the content of the N-rich toxin MC increases with increasing N availability (Sivonen, 1990; Van de Waal et al., 2009; Horst et al., 2014). However, in a recent study based in a batch culture experiment testing the effect of N on biosynthesis of MCs by a non-heterocystous species such as M. aeruginosa PCC 7806, Pan et al. (2019) reported that high N concentration results in the decrease of the expression of microcystin synthetase genes (mcy). In contrast, in a previous study Sivonen (1990) reported that high N concentration in the culture medium increased both growth and intracellular MC concentrations of the non-N-fixing Oscillatoria agardhii strains 97 and CYA 128. Conversely, P concentrations appear to be linked with toxin production of both heterocystous and non-heterocystous species (Sivonen 1990; Rapala et al., 1997). Therefore, the results of these different laboratory and field studies on the effect of the concentration of N on the production of MCs by non-heterocystous species are controversial, suggesting that in addition to the N other factors such as P and Fe concentrations and water temperature may increase the toxicity of these species. In fact in this study, we have shown that, although the concentration of DIN alone shows a high proportional capacity to predict the variation of the concentration of MC-LR (adj. R2  = 0.723), when adding the concentrations of TP and Fe and water temperature, the linear prediction model presents a remarkable improvement as indicated by the increase in the adj. R 2 value from 0.723 to 0.909 (Tab. 3, models 11 to 15).

5 Conclusion

The current study contributed to understanding for the first time the seasonal variations of phytoplankton community and microcystin-LR production in the Foum-Gleita reservoir (Mauritania), which is characterized by high phosphorus concentrations throughout the year due to the exploitation of phosphate mines in its watershed. Our investigation indicated that the cyanobacterial species M. aeruginosa and D. flos-aquae were a common component of phytoplankton communities in this reservoir. Moreover, multiple linear regression analysis showed that abiotic factors such as phosphorus, nitrogen, and iron concentrations and water temperature and pH played an important role in the occurrence and variation of the abundance of these two species and MC-LR concentration. Furthermore, more research is needed to better understand the ecological relationships that allow a non-diazotrophic cyanobacterium like M. aeruginosa and a diazotrophic species like D. flos-aquae to dominate simultaneously within the same hypereutrophic P-rich waterbody. The presence of MC-LR at concentrations more higher than the guide value (1 μg L−1) for 4 months (July to October) of the year, clearly demonstrates the need for health services to become aware of the public health hazards of these cyanobacteria and for set up regular monitoring for cyanotoxins in the waters of this reservoir.

Acknowledgements

This study results from a collaboration between the Universities of Nouakchott Al-Aasriya (Mauritania), Paris-Saclay (France), the Spanish Bank of Algae at the University of Las Palmas de Gran Canaria (Spain), the Erasmus+ Program, and the Mauritanian Institute of Oceanographic and fisheries Research (IMROP). The authors would especially like to thank these institutions for their courtesy, kindness and help. We would also like to thank the Director and the staff of COMASUD office at Foum-Gleita as well as the staff of Aftout Echargui Project (SNDE) for their support.

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Cite this article as: Sadegh AS, Sidoumou Z, Dia M, Pinchetti JLG, Bouaïcha N. 2021. Impacts of phosphorus loads on the water quality and the proliferation of harmful cyanobacteria in Foum-Gleita Reservoir (Mauritania). Ann. Limnol. - Int. J. Lim. 57: 1

All Tables

Table 1

Mean and standard deviations of environmental parameters of the Foum-Gleita reservoir (Mauritania) during one-year study period (from September 2017 to August 2018). T: surface water temperature; pH: water hydrogen potential; Secchi: secchi disk depth; DO: dissolved oxygen; N-NO3 –: nitrate; N-NO2 –: nitrite; N-NH4 +: ammonium; DIN: dissolved inorganic nitrogen; P-PO4 −3: dissolved phosphorus (DIP); TP: total phosphorus; DIN/TP: DIN:TP mass ratio; Fe: iron; Chl-a: chlorophyll a. The significance of the regression coefficients (Pearson?s r) is indicated by *0.01 < p < 0.05, **0.001 < p < 0.01, and ***p < 0.001.Values followed by the different letters are significantly different (p < 0.05). N: number of samples; SD: standard deviation; *: p < 0.05.

In the text
Table 2

Correlations between cyanobacterial abundance (Dolichospermum flos-aquae and Microcystis aeruginosa), microcystin-LR (MC-LR) concentration, and environmental factors (surface water temperature- T; water hydrogen potential- pH; secchi disk depth- Secchi; dissolved oxygen- DO; nitrate- N-NO3 –; nitrite- N-NO2 –; ammonium- N-NH4 +; dissolved inorganic nitrogen- DIN; dissolved phosphorus- P-PO4 −3 (DIP); total phosphorus- TP; DIN:TP ratio- DIN/TP; iron- Fe; chlorophyll a- Chl-a in the Foum-Gleita reservoir (Mauritania). The significance of the correlation coefficients (Pearson's r) is indicated by *0.01 < p < 0.05, **0.001 < p < 0.01, and ***p < 0.001.

In the text
Table 3

Linear regression models explaining the abundance of the two dominant species Dolichospermum flos-aquae and Microcystis aeruginosa, and MC-LR concentration in the Foum-Gleita Reservoir (Mauritania). The models result from a forward stepwise selection procedure and explain M. aeruginosa and D. flos-aquae biovolume (log MycBiov and log DolBiov in mm3 L−1) and Microcystin-LR concentration (log [MC-LR] in μg L−1) by the independent variables: dissolved inorganic nitrogen (log DIN in mg L−1), total phosphorus (log TP in mg L−1), and iron (log Fe in mg L−1), and surface water temperature (T in °C) and pH. All regression models were significant (p < 0.0001). The significance of the regression coefficients is indicated by * (0.01 < p < 0.05), ** (0.001 < p < 0.01), and *** (p < 0.001). Number of observations = 36.

In the text

All Figures

thumbnail Fig. 1

Sampling sites (S1, S2, and S3) and catchment area of the Foum-Gleita Reservoir. Ellipse indicates the phosphate mine in the city of Kaedi, open dots indicate major cities, and thick lines indicate Gorgol, Blanc, and Senegal Rivers. The insert shows the location of catchment area of the Foum-Gleita Reservoir within the map of Mauritania (modified from Van-Asten et al. (2002)).
In the text
thumbnail Fig. 2

Radar Graph of the trophic state index (TSI) values calculated at different surface water sampling sites in Foum-Gleita Reservoir during the study period from September 2017 to August 2018.
In the text
thumbnail Fig. 3

Seasonal variations of the relative abundance of phytoplankton phyla at different surface water sampling sites in Foum-Gleita Reservoir during the study period from September 2017 to August 2018.
In the text
thumbnail Fig. 4

Dynamic of Dolichospermum flos-aquae and Microcystis aeruginosa, and variability of total MC-LR concentration at different surface water sampling sites in Foum-Gleita Reservoir during the study period from September 2017 to August 2018.
In the text
thumbnail Fig. 5

Abundance of Dolichospermum flos-aquae and Microcystis aeruginosa as a function of Temperature (°C) and DIN/TP mass ratio at water surface sampling site 3 (S3) in Foum-Gleita Reservoir during the study period from September 2017 to August 2018.
In the text
thumbnail Fig. 6

LC-UV chromatograms of microcystin-LR standard (upper) and cyanobacterial bloom sample extract (middle) harvested in September 2017 at sampling site 3 (S3) and LC-MS/MS precursor ion spectrum (down) of the peak at 5.31 min exhibits parent ion [M+H]+ of MC-LR (m/z: 995.1).
In the text

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