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Article

Macrophytes and Phytoplankton, Two Primary Antithetical Producers in Degraded Water Systems

by
Adriano Sfriso
1,*,
Alessandro Buosi
1,
Giulia Silan
1,
Michele Mistri
2,
Cristina Munari
2 and
Andrea Augusto Sfriso
3
1
Department of Environmental Sciences, Informatics and Statistics (DAIS), University Ca’ Foscari Venice, Via Torino 155, 30170 Mestre, Italy
2
Department of Chemical, Pharmaceutical and Agricultural Sciences, University of Ferrara, Via Luigi Borsari 46, 44121 Ferrara, Italy
3
Department of Life Science and Biotechnology, University of Ferrara, Via Luigi Borsari 46, 44121 Ferrara, Italy
*
Author to whom correspondence should be addressed.
Water 2025, 17(3), 338; https://doi.org/10.3390/w17030338
Submission received: 19 December 2024 / Revised: 14 January 2025 / Accepted: 22 January 2025 / Published: 25 January 2025
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Abstract

:
One year of monthly sampling in some lagoons of the Po Delta and a pond in the Comacchio Valleys helped fill a gap in the knowledge of the primary producers of these degraded environments, focusing on the competition between macrophytes and phytoplankton. Key water column and surface sediment parameters showed a strong association with the different primary producers, explaining the main factors influencing the dominance of one group over the other. Phytoplankton, recorded as Chlorophyll-a and Phaeophytin-a, and Chlorophyceae among the macrophytes, dominated in conditions of high water turbidity and elevated nutrient concentrations. In contrast, macrophytes, particularly Rhodophyceae, their abundance, total biomass, and number of taxa. prevailed in clear, oxygenated waters. Under optimal conditions, sensitive macroalgae and aquatic angiosperms were also present. Additionally, the current list of macroalgal taxa has been updated, highlighting the dominance of some nonindigenous species (NIS) that had not been recorded before the 2000s. Specifically, Gracilaria vermiculophylla and Ulva australis, native to the North West Pacific (Japan, Korea, China, and Vietnam) and to South Australia, as well as the Indo-West Pacific (India, South Africa, Japan, and Korea), respectively, are now the most frequent and abundant taxa in these lagoons.

1. Introduction

In aquatic systems, the assimilation of CO2 through photosynthesis occurs across different systematic categories, including bacteria, macroalgae, phytoplankton, and aquatic angiosperms. Generally, environments that are severely affected by anthropogenic activities, such as nutrient inputs and sediment resuspension, which severely reduce underwater light transmission, are colonized by unicellular producers that are not associated with the substrate and move freely in the water column. In shallow environments, blooms of cyanobacteria [1,2,3] or other phytoplanktonic producers, especially diatoms [4,5] or dinoflagellates [6,7,8], hamper the growth of macroalgae and aquatic angiosperms. Under these conditions, the environment is severely compromised, and the annual net primary production (ANPP) shows high values ranging between 500–900 g C m−2 yr−1 and 1890 g C m−2 yr−1 (Tamagawa Estuary, Japan) [9]. However, in the presence of high nutrient concentrations and clear waters, nuisance macroalgae outcompete phytoplankton, producing an abnormal biomass [10] with an ANPP ranging from 15 to 20 Kg FWT m−2, accounting for 500–650 g C m−2 yr−1 [11] that can collapse, triggering anoxic crises when temperatures rise over 25 °C or water renewal is strongly reduced during neap tides. A high ANPP is also achieved with algae of the genus Gracilaria, which have productions close to that of Ulvaceae [12]. In the presence of these Rhodophyceae, anoxic conditions are less likely to occur because these species, in particular G. vermiculophylla (Ohmi) Papenfuss, a nonindigenous species (NIS) that rapidly colonized these lagoons, also survive when water temperatures exceed 30 °C and water turbidity is prohibitive, even for Ulvaceae [13].
Macro–microalgal blooms, which may last for just 20–30 days, hamper aquatic angiosperms’ ability to root and grow even if the ecological conditions are favorable for the rest of the year. When the water is clear and nutrient concentrations decrease, phytoplankton and nuisance macroalgae are replaced by aquatic angiosperms and sensitive macroalgae. Under these conditions, aquatic angiosperms can form dense meadows and ANPP can overcome that of macroalgae. Indeed, ref. [11] reported ANPP for Z. marina and C. nodosa in the Venice Lagoon ranging between 1093 and 1289 C m−2 yr−1.
This study analyzes the primary producers (benthic macrophytes and phytoplankton) and the changes in water and sediment environmental parameters collected monthly during the reintroduction of aquatic angiosperms in various lagoons (Caleri, Barbamarco, and Goro in the Po Delta, as well as in the pond of Fattibello in the Comacchio Valleys, Italy). These areas have experienced the disappearance of aquatic angiosperms in the last decades of the 20th century due to eutrophication, the farming of the clam Ruditapes philippinarum Adams & Reeve, and the silting of new areas formed by sediments transported by rivers. The aim of this study is to demonstrate how these producers are interconnected and dependent on the environmental conditions that characterize the transplant areas and to update the checklists of macroalgae of these lagoons, which are now dominated by nonindigenous species (NIS), such as Gracilaria vermiculophylla and Ulva australis Areschoug.

2. Materials and Methods

2.1. Study Areas

The Po Delta (44°57′ N, 12°23′ E) spans a large area within the Veneto and Emilia Romagna Regions (northwestern Adriatic Sea, Italy), covering a water surface of approximately 200 km2, of which only approx. 100 km2 are influenced by tidal expansion. The remaining surface is part of embanked fishing valleys. Before flowing into the sea, the river called Po di Venezia forms a large delta, splitting into five branches: Po di Maestra, Po di Pila, Po di Tolle, Po di Gnocca or di Donzella, and Po di Goro. These branches delineate lagoons and ponds with distinct geomorphological and environmental characteristics, such as those considered in this study: Caleri, Barbamarco, and Goro (Figure 1). Another transitional area was considered in the northernmost part of the Comacchio Valleys, in a pond called Fattibello Valley (44°40′ N, 12°12′ E).
The primary differences between these areas relate to salinity, which is influenced by river inflows, seawater exchange, and water depth, which varies from 0.5–1.0 m to 1.5–2.5 m, depending on the basin. The lagoons are devoid of hard substrata, except for certain levees and natural oyster beds scattered along the bottoms.

2.2. Sampling

Sampling was conducted on natural soft substrata from 29 March 2022 to 7 February 2023 in two sites, one placed in Goro and the other in Fattibello; and from 26 January to 18 December 2023 in two sites, one in Caleri and the other in Barbamarco (Figure 1). The average depth of the stations was approximately 0.5 m above the mean tide level.
In each site, macrophytes and environmental parameters of the water column and surface sediments were sampled monthly, and sedimentation traps were used to calculate the sedimentation rates on monthly, daily, and yearly bases.

2.2.1. Macrophytes

Macrophyte cover in areas with clear waters was determined by visual census technique [14], whereas under turbid conditions, the presence/absence of macrophytes was assessed by touching the bottom 20 times with a rake in order to obtain a 5% resolution according to [15]. The macroalgal biomass was determined by averaging 6 subsamples of 0.5 m−2 according to the procedure of [16]. The dominance of Chlorophyta or Rhodophyta was obtained by collecting 3–6 subsamples of macroalgae and weighing the different drained taxa. Samples were stored in a 4% formaldehyde solution and identified by a stereoscope and light microscopy, taking into account [17] and the most recent literature. Cryptic species were determined using the DNA barcoding method [18].
The cover of aquatic angiosperms, when present, was reported within 4 ranges: 0–25%, 25–50%, 50–75%, and 75–100%.
According to the Water Framework Directive (2000/60/EC), the ecological status of each station was obtained by applying the macrophyte quality index (MaQI) [15] throughout two macrophyte samplings, one performed in late spring and the other in autumn, to collect both cold and warm taxa.

2.2.2. Environmental Parameters

At each station and sampling date, the following environmental parameters were measured: water temperature, pH (pHw), and redox potential (Ehw) using a portable Hanna pHmeter (mod. HI98190, Hanna Instruments, Villafranca Padovana, Italy srl); dissolved oxygen (DO) using a WTW portable dissolved oxygen meter, Oxi 3310 (Wissenschaftlich-Technische Werkstätten GmbH, Weilheim, Germany); and water transparency using a Secchi disk. Six subsamples of the entire water column were collected with a handmade bottle (diameter 4 cm, height 150 cm), and 0.25–1.0 L of the mixed subsamples were filtered with a Swinnex filter holder through Whatman GF/F glass microfiber filters (porosity 0.7 µm). Filters and 250 mL of filtered water samples were stored at −20 °C for Chlorophyll-a (Chl-a), Phaeophytin-a (Phaeo-a), and nutrient (silicate: SiO44−, reactive phosphorus: RP, DIN: sum of ammonium (NH4+), nitrite (NO2−), and nitrate (NO3−)) determination according to [19]. Two additional subsamples (250–500 mL) were filtered through Whatman GF/F glass microfiber filters (Merck Life Science S.r.l., Milan, Italy) after desiccation at 130 °C for one hour for the determination of total suspended solids (TSS). After washing with Milli-Q water to remove salts, the filters were frozen and stored, awaiting laboratory analysis. Finally, subsamples of 20 mL were retained for the determination of salinity by titration following [20].
Three sediment cores were collected with a Plexiglas corer (i.d. 10 cm), and three sections of the 5 cm sediment top layer were carefully mixed in a tank. Sediment pH (pHs) and redox potential (Ehs) were immediately measured with a second portable Hanna pHmeter used only for sediment measurements. Two 50–100 mL sediment subsamples were frozen, one for the determination of Fines (i.e., sediment grain-size fraction < 63 µm, namely Pelite), density, and moisture, and the other for the determination of the concentrations of total phosphorus (Ptot), inorganic phosphorus (Pinorg), organic phosphorus (Porg), total nitrogen (Ntot), total carbon (Ctot), inorganic carbon (Cinorg), and organic carbon (Corg).
The percentage of Fines was determined by wet-sieving approx. 50 g of dried sediment through Endecotts sieves (ENCO Scientific Equipment, Spinea, Italy). Dry sediment density was obtained in the laboratory after sediment desiccation at 110 °C in tared crucibles of approx. 30 mL. All analyses were performed in duplicate.
The concentration of total phosphorus (Ptot) was obtained after 2 h combustion at 550 °C of 0.3–0.4 g of pulverized dried sediment and sonication of the residue in 50 mL of 1 N HCl for 30 min. After sample decantation for at least 1 h, exactly 0.5 mL of the supernatant was taken with a graduated gas-chromatographic syringe and diluted to 10 mL in volumetric flasks to have a final dilution of 1 L, and the results were expressed directly in µM. Phosphorus concentration was determined spectrophotometrically at an absorbance of 885 nm according to [21]. Inorganic phosphorus (Pinorg) was obtained with the same procedure used for Ptot but without combustion at 550 °C, while the concentration of organic phosphorus (Porg) was determined by difference.
The concentrations of total nitrogen (Ntot), total carbon (Ctot), and inorganic carbon (Cinorg) were obtained using a CHNS Analyzer (Vario-MICRO, Elementar CHNS, Thermo Fisher Scientific Inc., Monza, Italy). Ntot and Ctot were determined by analyzing approx. 3 mg of the sample without any prior treatment. Inorganic carbon (Cinorg) was determined after sample combustion at 440 °C for 2 h [22] to eliminate most of the organic matter with negligible loss of carbonates [23]. Organic carbon (Corg) was determined by difference. All nutrient analyses were performed in duplicate and replicated on different days to achieve an accuracy >95%. Concentration values were considered reliable when the coefficient of variation (standard deviation/mean) was <5%.
Settled particulate matter (SPM) was collected using Plexiglas pyramidal traps (base 20 × 20 cm, height 15 cm, mouth 15 × 15 cm) placed on the station bottoms according to Sfriso et al. (2022) [24]. Traps were covered with a 1 cm mesh net to prevent fish and crabs from entering and resuspending the SPM. At each monthly sampling, the traps were emptied into measuring containers, the particulate matter was carefully homogenized, and volumetric subsamples were retained for the determination of dry weight after marking the ratio between the total sample and the subsample. The determination of the SPM dry weight was carried out after freeze-drying the subsamples. Results were expressed per square meter considering both the volumetric ratio between the total sample and the subsample and the surface area of the trap mouth (conversion factor: 10,000/225 cm2 = 44.44). The final values were increased by 10% to compensate for the loss of SPM during the various transfer operations of the samples and the use of a frame with a net to prevent the entry of fish and crabs into the trap. Finally, because the samples were collected on different dates, the sedimentation rates (SRs) were reported monthly, considering the number of days and SRs in the first and second months. Samples were integrated accordingly to obtain the SRs for each month, following the formula:
monthly SRs = g DWT d−1 × N° days of month 1 + g DWT d−1 × N° days of month 2
In this way, the data for each year can be compared on any time basis: second, hour, day, month, and year.

2.2.3. Ecological Status Determination

The determination of the taxonomic list of macroalgae and aquatic angiosperms, the cover and abundance of Chlorophyceae and Rhodophyceae, the cover of aquatic angiosperms, and the number of macroalgal taxa of high ecological value (sensitive taxa) enabled us to evaluate the ecological status of these lagoons by applying the macrophyte quality index (MaQI). This index was developed and validated for transitional environments of the Mediterranean Sea [25] and calibrated by the European Commission with Greece and France [26].
The MaQI index requires two samplings, one in spring and one in autumn, to collect both cold- and warmth-loving taxa. However, since the macrophytes in this study were sampled and identified monthly, it was also possible to determine the ecological status trend throughout the year.

2.2.4. Statistical Analyses

The timescale associations among 6 macrophyte variables (i.e., number of macroalgal taxa, macroalgal biomass and cover, Rhodophyta and Chlorophyta abundance, and angiosperm cover), 2 phytoplankton variables (i.e., Chl-a and Phaeo-a), 12 water column parameters (i.e., temperature, pHw, Ehw, salinity, DO, transparency, TSS, RP, NH4+, NO3−, NO2− and SiO44−), 11 surface sediment parameters (i.e., pHs, Ehs, density, moisture, porosity, Fines, Pinorg, Porg, Cinorg, Corg, Ntot), and SPM which were recorded monthly in the 4 lagoons were obtained by applying principal components analysis (PCA) using STATISTICA Software, release 10 (StatSoft Inc., Tulsa, OK, USA). Before analysis, the values of all parameters and variables were normalized by using the formula: (x − min (x))/(max (x) − min (x)) in order to range between 0 and 1. The first two components were plotted in a plane to discuss the contribution of each parameter/variable to the total variance of the dataset and to highlight the environmental parameters most closely associated with macrophyte or phytoplankton variables, although results cannot always prove cause and effect.

3. Results

3.1. Macrophytes

In total, 67 macroalgal taxa (i.e., 27 Chlorophyceae, 32 Rhodophyceae, and 8 Phaeophyceae) and 3 aquatic angiosperms (N. noltei (Hornemann) Tomlinson & Posluszny, Z. marina Linnaeus, and C. nodosa (Ucria) Ascherson) were found across the four lagoons during the 48 sampling days (Figure 2). Angiosperms were recorded only in Caleri, near the lagoon mouth, where, two years after transplants, they formed well-structured meadows, especially N. noltei and C. nodosa. At the moment, transplants have not been successful in the other lagoons.
In Goro, although only 16 macroalgal taxa were recorded, the mean biomass was the highest, with a mean value of 1453 g FW m−2 and a peak value of 4787 g FW m−2, found in March 2023. Macroalgae were represented mainly by Rhodophyceae (64%), such as Gracilariopsis longissima (S.G. Gmelin) Steentoft et al., Gracilaria gracilis (S.G. Gmelin) Steentoft et al., and G. vermiculophylla. In this station, no Phaeophyceae were recorded, and the mean cover was approx. 48%, with macroalgae grouped in patches. Conversely, 24 taxa were recorded in Fattibello, but the mean biomass was negligible (22 g FW m−2, only) with a mean cover of 8.4%, represented mainly by filamentous Chlorophyceae. In Barbamarco, 33 taxa accounted for a mean biomass of 445 FW m−2 and a mean cover of 53%, mainly represented by Chlorophyceae, such as Ulva rigida C. Agardh. In Caleri, the highest number of taxa was found (47), with a mean biomass of 649 g FW m−2 and a cover of 80%. At this station, Rhodophyceae (53%) prevailed over Chlorophyceae (34%), and Phaeophyceae were present with six taxa. Ulva australis, G. vermiculophylla, and Solieria filiformis (Kützing) P.W. Gabrielson, along with the native species G. longissima and G. gracilis, accounted for most of the algal biomass. In Caleri, three species of high ecological value were also found (Alsidium corallinum C. Agardh; Centroceras gasparrinii subsp. minusinor Wolf, Buosi, Juhmani & Sfriso; Dasya punicea (Zanardini) Meneghini) and 14 alien species.
The macroalgae most frequently recorded were the NIS G. vermiculophylla (35 out of 48 samplings) and U. australis (33 samplings), followed by the native taxa Blidingia dowsonii (Hollenberg & I.A. Abbott) S.C. Lindstrom et al. (28 samplings) and G. longissima (27 samplings) (Table 1).
Another 12 NIS were recorded; among them, four (i.e., Agardhiella subulata (C. Agardh) Kraft et M J. Wynne, Solieria filiformis, Uronema marinum Womersley, and Polysiphonia morrowii Harvey) showed a sampling frequency higher than 10, whereas the others were less common. Globally, 18 species were found 2–3 times and 21 species only once.

3.2. Environmental Parameters

Figure 3 shows the mean values of some relevant parameters of the water column. Total Chlorophyll-a (Chl-a) and total suspended solids (TSS) showed very high mean values, especially in Fattibello. At this station, the mean Chl-a concentration was 13.7 µg L−1, with a peak of 38.9 µg L−1 in May. Mean values ranging from 6.04 to 7.08 µg L−1 were also recorded in Goro and Barbamarco, with peak values of 8.29 and 27.5 µg L−1, respectively. In contrast, Chl-a in Caleri showed a mean value of 2.47 µg L−1, never exceeding 4.71 µg L−1 across the year. In Fattibello, the TSS mean value was 53.1 mg L−1, approximately three times higher than in Barbamarco (18.8 µg L−1) and Caleri (17.4 µg L−1). At this station, the highest mean temperature (20.9 °C) was also recorded, while the percentage of DO saturation (113%) and pH (8.35) showed the highest values in Caleri. Salinity mean value was the highest at Goro (26.7); at the other stations, it ranged between 20.6 (Fattibello) and 17.5 (Barbamarco).
Reactive phosphorus (RP) showed the highest mean value in Barbamarco (0.56 µM), whereas in the other stations it ranged from 0.36 µM in Goro to 0.43 µM in Caleri and 0.43 µM in Fattibello. In contrast, the dissolved inorganic nitrogen (DIN = sum of NH4+, NO3−, NO2−) showed very high mean values in Fattibello (35.8 µM), i.e., approx. 4 times higher than in Goro (9.45 µM), whereas it ranged from 12.5 µM in Caleri to 16.7 µM in Barbamarco.
The mean amount of settled particulate matter (SPM) collected by sedimentation traps was the highest in Goro with 382 g DW m−2 day−1 (accounting for 139.4 Kg DW m−2 year−1), decreasing to 257 g DW m−2 day−1 in Fattibello, 123 g DW m−2 day−1 in Barbamarco, and 94 g DW m−2 day−1 (accounting for 34.3 Kg DW m−2 year−1) in Fattibello, i.e., approximately 4 times lower than in Goro.
Figure 4 shows the mean values of some parameters in surface sediments. In Barbamarco, sediments were characterized by the lowest percentage of Fines (6.05%) and moisture (25.6%) as well as by the highest dry density (1.33 mg DW g−1). This station also showed the lowest total phosphorus (Ptot = 383 µg g−1), total nitrogen (Ntot = 0.66 mg g−1), and total carbon (Ctot = 19.8 mg g−1) concentrations, whereas nutrient concentrations were highest in Caleri.

3.3. Ecological Status Assessment

The ecological status at the four stations was assessed monthly, even though the indices require only two samplings per year. The results are reported in Table 2.
Goro and Barbamarco exhibited Poor ecological conditions due to the absence of sensitive taxa and aquatic angiosperms. The ecological quality ratio (EQR) ranged from 0.25 (higher abundance of Chlorophyceae) to 0.35 (higher abundance of Rhodophyceae).
Fattibello showed the worst ecological conditions (Bad conditions), as macrophytes were almost entirely absent (cover < 0.05%) and consisted solely of opportunistic species.
Caleri demonstrated a progressively improving ecological trend, with Poor conditions recorded from January to April, Moderate conditions from May to November, and Good conditions in December. However, the classification based on the spring (May) and autumn (November) samplings was Moderate.

3.4. Statistical Analyses

The principal component analysis (PCA) of 32 parameters/variables reveals the variance associated with each parameter/variable (significant loading: p > 0.7) and the associations between macroalgae, aquatic angiosperms, phytoplankton (reported as Chl-a and Phaeo-a concentrations), and water/sediment parameters. The PCA identified nine components explaining 79.2% of the total variance. The first two components (explaining 37% of the variance) are plotted in a plane (Figure 5). On the first axis, the parameters that explain most of the variance on the positive side of the plane were sediment density and, on the negative side, sediment moisture, Fines and Ntot (p > 0.7). On the second axis, the main variance was associated with SPM and TSS. Additionally, in the first axis, minor contributions were from RP, Ehw, Ehs, and, among algae, Chl-a, Phaeo-a, and Chlorophyta abundance on the positive side, with Porg, Pinorg, macroalgal biomass, and Rhodophyceae abundance on the negative side. Similarly, on the second axis, salinity, temperature Cinorg, and Porg contributed mainly to the variance on the positive side, whereas DO, pHs, and pHw, along with macroalgal cover and the number of taxa, contributed to the variance on the negative side.
Overall, the biplot shows that the variance of parameters/variables is distributed in two opposing groups. Most of the water column characteristics, especially nutrient concentrations in the water column (SiO44−, RP, NO2−, NH4+, NO3−), Ehw, temperature, phytoplankton variables, Chlorophyceae, and, to a lesser extent, SPM, TSS, and salinity, were grouped on the positive side. Water transparency, DO, pHw, Corg, and the other macrophyte variables (number of taxa, macralgal cover, angiosperm presence, macroalgal biomass, and Rhodophyceae abundance) were grouped on the negative side. In contrast, most of the sediment characteristics, such as density, Ehs, and pHs, were on the right, while nutrient concentrations (i.e., Porg, Pinorg, Ntot), Cinorg, moisture, and Fines were less associated with the primary producers.

4. Discussion

Macrophytes (i.e., macroalgae and aquatic angiosperms) and phytoplankton are the main primary producers in transitional water systems (TWSs), with one often prevailing over the other, depending on the ecological conditions. Phytoplankton dominate in degraded environments where water is turbid and insufficient light reaches the bottom, hindering macrophyte growth. In contrast, aquatic angiosperms and certain sensitive macroalgae become the dominant producers in clear waters with low nutrient concentrations.
The TWSs considered in this study are heavily degraded environments where aquatic angiosperms disappeared in the last decade of the 1900s due to the high trophic status and the harvesting of the clam Ruditapes philippinarum [25]. The historical presence of aquatic angiosperms and sensitive macroalgae is documented in the literature for the Comacchio Valleys [27,28,29], including Fattibello [30], and Goro [31]. However, no information is available for the other lagoons until 2008 [25].
For the Comacchio Valleys, refs. [27,28,29] reported a rich taxonomic list (Table S1 [32,33,34,35,36,37,38,39,40,41,42]), which included 28 taxa: 2 aquatic angiosperms (i.e., N. noltei and R. cirrhosa), 8 Rhodophyta, 17 Chlorophyta, and 1 Ochrophyta. Among them, according to [43], several macroalgal taxa of high ecological value were also recorded, including Hydrolithon farinosum (J.V. Lamouroux) D. Penrose et Y.M. Chamberlain, Pneophyllum fragile Kützing, Pneophyllum confervicola (Kützing) Y.M. Chamberlain, Vertebrata fucoides (Hudson) Kuntze, Valonia aegagropila C. Agardh, Chaetomorpha linum (O.F. Müller) Kützing, and Lamprothamnion papulosum (Wallroth) J. Groves [31]. Their disappearance was due to the profound alteration the basin underwent resulting from the introduction of large quantities of organic matter and nutrients, particularly from aquaculture facilities and eel farming. In fact, the basin is characterized by very poor water exchange, high trophic conditions, anoxic sediment layers, and the production of sulfides [44]. As a result, the original macrophyte vegetation was rapidly replaced by intense and continuous blooms of phytoplankton and cyanobacteria [1]. In 2009, the mean total Chl-a concentration was 53.3 µg L−1 and water transparency was approx. 20–30 cm throughout the year. No macrophytes were recorded in the entire basin, except for four Chlorophyceae (i.e., Ulva compressa Linnaeus, Ulva ralfsii (Harvey) Le Jolis, Ulva rigida, and Ulothrix implexa (Kützing) Kützing), which formed a 10 cm band in the upper part of the banks [45]. Information about the Fattibello pond, located in the northernmost area of this large basin, is scarce. A study by [30] reported that this pond was dominated by Ulva rigida, with a minor presence of Cladophora sp., both coexisting with high densities of phytoplankton. Fattibello pond has limited exchange with the main basin, slight Chl-a concentrations, and clearer waters. In 2009, Fattibello likely also had vegetation with macroalgae like those present today, although the dominant primary producers were still phytoplanktonic algae. Similarly, in 2022, Fattibello showed the presence of a certain number of macroalgal taxa (24), but the biomass was negligible (mean value: 22 g FW m−2, with a peak of 207 g FW m−2 in October and zero biomass from March to June and in August). In contrast, phytoplankton showed high concentrations (total Chl-a mean value: 13.7 µg L−1, with a peak in May of 38.9 µg L−1).
Considering the ecological conditions and the trophic status of these lagoons, phytoplankton (Chl-a and Phaeo-a) predominated in the presence of turbid waters (i.e., higher TSS and SPM rates) and higher water temperatures. Chlorophyceae abundance (especially the nitrophilic taxa Ulva rigida, Ulva polyclada, and Ulva australis) was favored by higher nutrient concentrations in the water column, especially DIN concentrations. In contrast, the presence of aquatic angiosperms, the number of taxa, Rhodophyceae abundance, and macroalgal biomass and cover predominated in the presence of higher water transparency, which increased the pH of the water column (pHw) and the organic carbon (Corg) content in the surface sediments. The concentrations of nutrients in surface sediments and the sediment texture played a minor role in the presence of phytoplankton or macrophytes.
The different presence and abundance of macrophytes, the presence/absence of sensitive species and aquatic angiosperms, as well as their cover, allowed us to assess the ecological status of these lagoons by applying the macrophyte quality index (MaQI). Fattibello showed the worst conditions (Bad) due to the absence of aquatic angiosperms and sensitive macroalgae and, generally, to the almost complete absence of macroalgal biomass. In contrast, Caleri showed an improving ecological status (from Poor to Moderate) due to the rooting and spread of angiosperms, the presence of some sensitive taxa, and the predominance of Rhodophyceae over Chlorophyceae. Goro and Barbamarco showed no changes, remaining consistently Poor with significant macroalgal biomass and the complete absence of aquatic angiosperms and sensitive macroalgae.
The blooms of phytoplankton or macroalgae, and the prevalence of one over the other, have been the subject of many studies carried out in the world’s TWSs, such as estuaries, bays, lagoons, and ponds. A study by [46] reported that phytoplankton in the brackish waters of San Francisco Bay grew much more slowly in the presence of natural densities of Ulva. The competition for dissolved inorganic nitrogen (DIN) was identified as the probable cause of the depression of phytoplankton by Ulva. At its rapid growth rates, this macroalga can reduce DIN to critically low levels, as was also observed in the Venice Lagoon, where DIN concentrations in spring can drop to values <1 µM [11]. Ulva outcompetes phytoplankton by reducing nitrogen to levels below those necessary to support phytoplankton growth. Similarly, in mesocosm experiments, ref. [47] found that high nutrient loading reduced phytoplankton growth by a factor of 10 in the presence of macroalgae or cyanobacterial mats. In addition, at low DIN concentrations, algal mats shifted phytoplankton communities from flagellates to blue-green algae but did not affect the total biomass of the phytoplankton. They concluded that the attached forms of macroalgae, as well as the cyanobacterial mats, were more efficient competitors for high nutrient levels than phytoplankton. The nutrient competition hierarchy was as follows: cyanobacterial mats > attached green macroalgae > floating green macroalgae > phytoplankton. As recorded in this study, this resource competition may explain the negative correlation found in field studies between phytoplankton and macroalgae in shallow nutrient-enriched estuaries. Another study by [48] analyzed the factors affecting the presence/absence of nuisance macroalgae and/or phytoplankton in some areas of the Venice Lagoon, one densely populated by macroalgae and the other colonized only by phytoplankton. Using Ulva growth into cubic net cages (side: 25 × 25 × 25 cm, mesh sizes: 0.1 and 1 cm to prevent or allow the entry of grazers) placed in the water column at the surface and on the bottom in an area with a mean depth of approximately 1 m, they identified the main causes of macroalgal and phytoplankton competition. In the first case, the fast-growing macroalgal biomass rapidly depleted DIN and reactive phosphorus (RP), preventing phytoplankton growth. In the second case, phytoplankton prevailed over macroalgae due to the high water turbidity caused by wave motion from ship traffic. In addition, macroalgae in the net cages with a net mesh of 1 cm were affected in late spring by the grazing pressure of large numbers of Gammaridae that escaped from areas where the macroalgae were collapsing, triggering extensive anoxia. These crustaceans completely grazed the macroalgae present in the net cages, thereby favoring the blooms of phytoplankton. In addition, ref. [49], using a simulation model, showed that while phytoplankton response to growth factors is more intense and of shorter duration, internal nutrient storage in macroalgae stabilizes the growth process, making macroalgal assemblages relatively more independent of variations in chemical conditions and external forcing functions. Indeed, macroalgae can grow for 15–20 days even in the presence of low water nutrient concentrations, thanks to their ability to accumulate nutrients inside their cells. Just one day of exposure to high nutrient concentrations in the water column is enough to increase internal nitrogen concentrations from 10% to 23% and phosphorus concentrations from 20% to 45% [50]. In this context, ref. [51] reported that nutrients, due to the tissue concentrations, almost never restricted the growth of U. rigida in Jamaica Bay, NY, USA. Indeed, the growth of these populations was light-limited by phytoplankton blooms, which in turn were regulated by the availability of silicates, as also found by [52] in Chesapeake Bay. Furthermore, ref. [53] conducted mesocosm experiments in the field in estuaries of NY, USA during blooms of the harmful microalga Aureococcus anophagefferens Hargraves & Sieburth (brown tide 105 cells mL−1) and found that U. lactuca Linnaeus consistently caused a significant (p < 0.05) and often large (>50%) reduction in cell densities within approximately 48 h. This suggests that the use of macroalgae may be a promising mitigation strategy for harmful algal blooms in coastal ecosystems.
On a larger scale, ref. [54] provided valuable information on the relationships between nutrient concentrations, phytoplankton, and macroalgae. Using long-term moderate resolution imaging spectroradiometer (MODIS) observations, they found that the world’s largest blooms of Ulva prolifera Müller, O.F. in the Yellow Sea caused a mean Chl-a increase of 98% (from 0.64 μg L−1 to 1.26 μg L−1). These blooms competed with phytoplankton for nutrient uptake, leading to no increase in phytoplankton biomass compared to periods without a macroalgal presence.
All of these authors have reported an inverse response of phytoplankton and macroalgae to environmental pressures, identifying water turbidity and nutrient concentrations in the water column as the main factors favoring one systematic category over the other. These pressures can act individually or synergistically. In shallow transitional water systems (TWSs), clear waters promote the presence of aquatic angiosperms and the growth of Rhodophyceae when nutrient concentrations are not excessively high. In contrast, an increase in nutrient concentrations in the water column favors the bloom of Chlorophyceae, which are then replaced by phytoplankton in turbid waters.
This dynamic was evident in the Po Delta lagoons and Comacchio Valleys, where different nutrient concentrations and water turbidity regulated the presence of these primary producers. In Fattibello pond, high dissolved inorganic nitrogen (DIN) concentrations and water turbidity (measured as total suspended solids (TSSs)) inhibited macroalgal growth, triggering phytoplankton blooms (measured as total Chl-a and Phaeo-a concentration) throughout the year. Conversely, in Barbamarco and Goro, where the waters were generally clearer, macroalgal blooms alternated with phytoplankton blooms. However, the water conditions in Goro were affected by significant Po river outflows and sediment resuspension (see the high concentrations of SPM) caused by clam (Ruditapes philippinarum) harvesting in the farms present all around. In contrast, lower river outflow impacts and the proximity of the lagoon mouth in Caleri provided clearer waters that favored macroalgae dominance, higher biodiversity, and even the growth of aquatic angiosperms.
Examining macroalgal biodiversity across the four lagoons revealed that the higher number of taxa recorded in Caleri (48 taxa) was strongly associated with better ecological conditions, the dominance of macroalgae (i.e., algal biomass and algal cover) over phytoplankton, the abundance of Rhodophyceae, and the possible presence of aquatic angiosperms. Conversely, the abundance of Chlorophyceae was recorded in Poor ecological conditions characterized by higher nutrient concentrations. Phytoplankton (i.e., Chl-a and Phaeo-a) blooms completely replaced macroalgae in turbid waters.
In this investigation, despite the greater number of species compared to previous macroalgal checklists, two significant differences were recorded: the disappearance of several sensitive species and the introduction of nonindigenous species (NIS) not recorded before surveys conducted in 2008 [25]. In 2023, no sensitive species were recorded in Fattibello, Goro, and Barbamarco, whereas three new taxa were occasionally observed in Caleri for the first time: Alsidium corallinum C. Agardh, Dasya punicea (Zanardini) Meneghini, and the NIS Centroceras gasparrinii subsp. minus Wolf, Buosi, Juhmani & Sfriso. In all lagoons, however, some NIS had almost completely replaced the native vegetation. Indeed, Gracilaria vermiculophylla and Ulva australis are now the most frequent and abundant taxa, along with Agardhiella subulata, Solieria filiformis, Uronema marinum, and Polysiphonia morrowii.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/w17030338/s1, Table S1: Check-list of the past macrophytes recorded in Goro and in Comacchio Valleys [31].

Author Contributions

Conceptualization, A.S. and A.A.S.; methodology, A.S.; validation, M.M. and C.M.; formal analysis, A.B. and G.S.; investigation, A.S. and A.A.S.; resources, A.S.; data curation, A.S.; writing—original draft preparation, A.S.; writing—review and editing, M.M., C.M. and A.A.S.; supervision, A.B., G.S., M.M., C.M. and A.A.S.; funding acquisition, A.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the European Union’s LIFE program financial instrument 2014–20 (grant LIFE19 NAT/IT/000264)—Life TRANSFER (seagrass TRANSplantation or ransitional Ecosystem Recovery), which contributes to the environmental recovery of the Natura 2000 sites: IT4060005 (Sacca di Goro), IT3270017 (Caleri and Barbamarco), IT4060002 (Comacchio Valleys).

Data Availability Statement

Part of the data presented and discussed in this paper are available on the website of the Life TRANSFER Project (Life19 NAT/IT/000264).

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Study areas and sampling sites.
Figure 1. Study areas and sampling sites.
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Figure 2. Macrophyte variables mean values in the four sampling stations. Bars are the sampling errors.
Figure 2. Macrophyte variables mean values in the four sampling stations. Bars are the sampling errors.
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Figure 3. Mean values of some parameters of the water column. Bars are the sampling errors.
Figure 3. Mean values of some parameters of the water column. Bars are the sampling errors.
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Figure 4. Mean values of some parameters of surface sediments. Bars are the sampling errors.
Figure 4. Mean values of some parameters of surface sediments. Bars are the sampling errors.
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Figure 5. Principal component analysis (PCA) between macrophytes, phytoplankton (recorded as Chl-a and Phaeo-a), and water, sediment, and SPM parameters. Significant parameters in red. Green arrows indicate the variance of macrophyte and phytoplankton (Chl-a, Phaeo-a) variables.
Figure 5. Principal component analysis (PCA) between macrophytes, phytoplankton (recorded as Chl-a and Phaeo-a), and water, sediment, and SPM parameters. Significant parameters in red. Green arrows indicate the variance of macrophyte and phytoplankton (Chl-a, Phaeo-a) variables.
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Table 1. Frequency of macroalgal taxa recorded in the 48 samples. Chlorophyceae are in green, Rhodophyceae in red, and Phaeophyceae in brown. Sensitive taxa are highlighted in blue.
Table 1. Frequency of macroalgal taxa recorded in the 48 samples. Chlorophyceae are in green, Rhodophyceae in red, and Phaeophyceae in brown. Sensitive taxa are highlighted in blue.
Macroalgal FrequencyMonths
CaleriBarbamarcoGoroFattibelloTotal
N°Taxa1212121248
1Gracilaria vermiculophylla (Ohmi) Papenfuss7811935
2Ulva australis Areschoug58101033
3Blidingia dowsonii (Hollenberg & I.A. Abbott) S.C. Lindstrom et al.888428
4Gracilariopsis longissima (S.G. Gmelin) Steentoft et al.1168227
5Agardhiella subulata (C. Agardh) Kraft et M.J. Wynne 7-7317
6Solieria filiformis (Kützing) P.W. Gabrielson 364417
7Uronema marinum Womersley384116
8Ulva polyclada Kraft442212
9Ulva rigida C. Agardh732-12
10Polysiphonia morrowii Harvey 521311
11Ulvella viridis (Reinke) R. Nielsen, C.J. O’Kelly, & B. Wysor35--8
12Cladophora glomerata (Linnaeus) Kützing 312-6
13Ulva prolifera O.F. Müller11-46
14Chondria capillaris (Hudson) M. J. Wynne24--6
15Erythrotrichia carnea (Dillwyn) J. Agardh33--6
16Hypnea cervicornis J. Agardh3-3-6
17Radicilingua mediterranea Wolf, Sciuto, & Sfriso6---6
18Cladophora albida (Nees) Kutzing-4-15
19Ulva compressa Linnaeus22-26
20Acanthosiphonia echinata (Harvey) Savoie & G.W. Saunders23--5
21Caulacanthus okamurae Yamada41--5
22Gracilaria bursa-pastoris (S.G.Gmelin) P.C. Silva23--5
23Gracilaria gracilis (S. G. Gmelin) Steentoft et al.14--5
24Melanothamnus japonicus (Harvey) Díaz-Tapia & Maggs 1-135
25Cladophora sericea (Hudson) Kützing1--34
26Alsidium corallinum C. Agardh4---4
27Carradoriella elongella (Harvey) Savoie & G.W. Saunders31--4
28Dasya punicea (Zanardini) Meneghini4---4
29Chaetomorpha ligustica (Kützing) Kützing -3--3
30Cladophora lehmanniana (Lindenberg) Kützing --123
31Ulva flexuosa Wulfen1--23
32Dasya pedicellata (C. Agardh) C. Agardh---33
33Dictyota linearis (C. Agardh) Greville3---3
34Ectocarpus siliculosus var. arctus (Kützing) Gallardo12--3
35Blidingia minima (Nägeli ex Kützing) Kylin-2--2
36Bryopsis hypnoides J.V. Lamouroux11--2
37Ulothrix implexa (Kützing) Kützing 2---2
38Ulva intestinalis Linnaeus-11-2
39Ulva pilifera (Kützing) Škaloud & Leliaert2---2
40Callithamnion corymbosum (Smith) Lyngbye2---2
41Ceramium polyceras (Kützing) Zanardini2---2
42Kapraunia schneideri (Stuercke & Freshwater) Savoie & G.W. Saunders 2---2
43Sahlingia subintegra (Rosenvinge) Kornmann1-1-2
44Ectocarpus siliculosus (Dillwyn) Lyngbye11--2
45Kuckuckia spinosa (Kützing) Kornmann ---22
46Myrionema orbiculare J. Agardh---22
47Blidingia ramifera (Bliding) Garbary & L.B. Barkhouse---11
48Bolbocoleon piliferum Pringsheim-1--1
49Chaetomorpha aerea (Dillwyn) Kützing-1--1
50Chaetomorpha gracilis Kützing---11
51Cladophora dalmatica Kützing1---1
52Derbesia tenuissima (Moris et De Notaris) P. et H. Crouan1---1
53Ulva linza Linnaeus---11
54Ulvella leptochaete (Huber) R. Nielsen et al.-1--1
55Antithamnion nipponicum Yamada & Inagaki 1---1
56Bangia fuscopurpurea (Dillwyn) Lyngbye1---1
57Bostrychia scorpioides (Hudson) Montagne---11
58Catenella caespitosa (Withering) L.M. Irvine ---11
59Ceramium cimbricum H.E. Petersen -1--1
60Centroceras gasparrinii subsp. minus Wolf, Buosi, Juhmani & Sfriso1---1
61Erythrocladia irregularis Rosenvinge1---1
62Neopyropia elongata (Kylin) L.-E. Yang & J. Brodie-1--1
63Spyridia filamentosa (Wulfen) Harvey1---1
64Stylonema alsidii (Zanardini) K.M. Drew-1--1
65Acinetospora crinita (Carmichael) Sauvageau1---1
66Gongolaria barbata f. aurantia (Kützing) Falace, Alongi & Kaleb1---1
67Scytosiphon dotyi M.J. Wynne1---1
Table 2. Ecological status assessment using the MaQI (macrophyte quality index). The colors used correspond to the official representation of the five ecological classes: Bad in red, Poor in ochre, Moderate in yellow and Good in green.
Table 2. Ecological status assessment using the MaQI (macrophyte quality index). The colors used correspond to the official representation of the five ecological classes: Bad in red, Poor in ochre, Moderate in yellow and Good in green.
MaQI
LagoonsJanFebMarAprMayJunJulAugSepOctNovDecEcological Status
Ecological Quality Ratio (EQR)
Goro0.250.250.250.350.250.250.250.350.350.350.350.35Poor
Barbamarco0.350.350.250.250.250.250.250.350.250.250.250.25Poor
Fattibello0.000.000.000.000.250.000.000.250.000.000.000.00Bad
Caleri0.350.350.250.250.550.550.550.550.550.550.550.65Moderate
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Sfriso, A.; Buosi, A.; Silan, G.; Mistri, M.; Munari, C.; Sfriso, A.A. Macrophytes and Phytoplankton, Two Primary Antithetical Producers in Degraded Water Systems. Water 2025, 17, 338. https://doi.org/10.3390/w17030338

AMA Style

Sfriso A, Buosi A, Silan G, Mistri M, Munari C, Sfriso AA. Macrophytes and Phytoplankton, Two Primary Antithetical Producers in Degraded Water Systems. Water. 2025; 17(3):338. https://doi.org/10.3390/w17030338

Chicago/Turabian Style

Sfriso, Adriano, Alessandro Buosi, Giulia Silan, Michele Mistri, Cristina Munari, and Andrea Augusto Sfriso. 2025. "Macrophytes and Phytoplankton, Two Primary Antithetical Producers in Degraded Water Systems" Water 17, no. 3: 338. https://doi.org/10.3390/w17030338

APA Style

Sfriso, A., Buosi, A., Silan, G., Mistri, M., Munari, C., & Sfriso, A. A. (2025). Macrophytes and Phytoplankton, Two Primary Antithetical Producers in Degraded Water Systems. Water, 17(3), 338. https://doi.org/10.3390/w17030338

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