Chaetomorpha Linum Classification Essay


Eutrophication affects seagrasses negatively by increasing light attenuation through stimulation of biomass of fast-growing, bloom-forming algae and because high concentrations of ammonium in the water can be toxic to higher plants. We hypothesized nevertheless, that moderate amounts of nitrophilic macroalgae that coexists with seagrasses under eutrophic conditions, can alleviate the harmful effects of eutrophication on seagrasses by reducing ammonium concentrations in the seawater to non-toxic levels because such algae have a very large capacity to take up inorganic nutrients. We studied therefore how combinations of different ammonium concentrations (0, 25 and 50 μM) and different standing stocks of macroalgae (i.e. 0, 1 and 6 layers of Ulva sp.) affected survival, growth and net production of the seagrass Zostera noltei. In the absence of Ulva sp., increasing ammonium concentrations had a negative influence on the performance of Z. noltei. The presence of Ulva sp. without ammonium supply had a similar, but slightly smaller, negative effect on seagrass fitness due to light attenuation. When ammonium enrichment was combined with presence of Ulva sp., Ulva sp. ameliorated some of negative effects caused by high ammonium availability although Ulva sp. lowered the availability of light. Benthic microalgae, which increased in biomass during the experiment, seemed to play a similar role as Ulva sp.–they contributed to remove ammonium from the water, and thus, aided to keep the ammonium concentrations experienced by Z. noltei at relatively non-toxic levels. Our findings show that moderate amounts of drift macroalgae, eventually combined with increasing stocks of benthic microalgae, may aid seagrasses to alleviate toxic effects of ammonium under eutrophic conditions, which highlights the importance of high functional diversity for ecosystem resistance to anthropogenic disturbance.

Citation: Moreno-Marín F, Vergara JJ, Pérez-Llorens JL, Pedersen MF, Brun FG (2016) Interaction between Ammonium Toxicity and Green Tide Development Over Seagrass Meadows: A Laboratory Study. PLoS ONE 11(4): e0152971.

Editor: Richard K.F. Unsworth, Seagrass Ecosystem Research Group, Swansea University, UNITED KINGDOM

Received: June 26, 2015; Accepted: March 22, 2016; Published: April 1, 2016

Copyright: © 2016 Moreno-Marín et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: This work was supported by the Spanish Project Sea-Live (CTM2011-24482) from the Spanish Ministry of Science and Innovation and by the Junta de Andalućıa Excellence Project PRODESCA (P12-RNM-03020). Francisco Moreno holds a contract financed by the Spanish Project Sea-Live (CTM2011-24482) from the Spanish Ministry of Science and Innovation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.


Seagrass based ecosystems are among the most productive coastal ecosystem types providing a broad range of ecosystem services such as carbon burial, amelioration of natural hazards and habitat and nursery functions [1,2,3]. These ecosystems are increasingly endangered by anthropogenic pressures; 78% of the human population lives within 50 km of coastline [4] and increasing population density in coastal zones promotes an increase in nutrient loads derived from catchment areas and sewage, which contributes to boost eutrophication processes [5,6]. Eutrophication has a strong negative effect on seagrass systems [2,7,8], which are affected by increased nutrient availability in two major ways. The first and most important is by triggering blooms of fast-growing micro- and macroalgae [9,10]. Such blooms cause increased light attenuation in the water column, which may lead to diminished depth limits [11]. Algal blooms may also result in enhanced inputs of organic matter to the seafloor, leading to sediment anoxia [12] and higher sulphide levels in the sediment pore water, increasing the risk of sulphide intrusion into the plants [13,14,15]. Secondly, eutrophication is typically followed by higher concentrations of dissolved inorganic nutrients in the recipient [16,17], and in the case of ammonium, high concentrations can be potentially harmful (i.e. toxic) to seagrasses [17,18,19].

The negative (toxic) effect of high ammonium concentration has been documented in several studies [19,20,21] where seagrasses exposed to high ammonium availability show slower growth and reduced survival. The toxic effect of ammonium is mainly related to an uncoupling of ATP production from photosynthetic electron transport [22,23], enhanced respiratory demand [24,25], alteration of intracellular pH [23] and decreased uptake of some cations [17,26], all of which may lead to reduced plant performance.

Accumulation of fast-growing micro- and macroalgae and the resulting light attenuation is typically considered more important for seagrass performance than ammonium toxicity under eutrophication, because the concentration needed for ammonium to be toxic is relatively high (typically > 25 μM) and not very common for extended periods of time in nature. Ammonium toxicity is therefore mainly considered relevant in places with extreme inputs of nutrient rich freshwaters and limited water exchange, for example close to point sources in semi-enclosed estuaries and bays.

High concentrations of ammonium may, however, occur in bottom waters due to decomposition of organic matter. Fast decomposition of sediment organic matter combined with anoxic conditions in summer may accelerate the efflux of ammonium from the sediment, resulting in elevated levels of ammonium in near bottom waters where concentrations can reach 50–100 μM [27]. Hence, ammonium concentrations in bottom waters surrounding seagrasses can reach levels at which plants performance is affected. In addition, seagrass meadows are often covered by fast-growing, drift macroalgae under eutrophic conditions [28,29,30,31]. These mats of drift macroalgae reduce light penetration, which may reinforce the toxic effect of ammonium on seagrasses [32,33,34]. A previous study [34] reported a negative synergetic effect of high ammonium concentration and artificially reduced light levels and hypothesized that seagrasses, which are temporarily covered by algal mats in summer, might suffer from two stressors simultaneously since the algal mat attenuates light, while the concentration of ammonium below the mat and around the plants may increase substantially. However, fast-growing, mat-forming macroalgae, such as members of the genera Ulva, take up nutrients much faster than seagrasses [35,36,37]. Ammonium uptake by the overgrowing mat-forming algae could thus potentially aid to reduce the average ammonium concentration in the canopy, thereby alleviating the toxic effect of high ammonium concentration on seagrasses. Mat-forming macroalgae may thus have an overall negative effect on the seagrasses they cover (through light attenuation), but may, at the same time, aid seagrasses to sustain prolonged coverage by lowering the exposure to high ammonium concentrations.

We conducted a laboratory experiment where we simulated eutrophic conditions in a shallow water coastal system to investigate both, single and combined effects of high ammonium concentration, and cover by free-floating macroalgae, on seagrass survival and growth. Our aim was to test the hypothesis that the single effect of each stressor on Zostera noltei Hornem was negative, but that moderate amounts of Ulva sp. could have an ameliorating effect on seagrass performance under high ammonium concentrations.

Materials and Methods

Plant, water and sediment collection

Specimens of Z. noltei were collected at Santibáñez intertidal mudflats (Cádiz Bay Natural Park (36° 28’ N, 6° 15’ W), Spain) with permission granted by "Junta de Andalucía" and "Cádiz Bay Natural Park”. The area is characterized by a mild climate with annual mean water and air temperatures of 19 ± 3 and 17 ± 5.3°C, respectively [38]. Ambient nutrient concentrations in the water column are relatively low, averaging 1.89 ± 1.22 μM ammonium, 0.18 ± 0.14 μM nitrite, 0.68 ± 1.88 μM nitrate and 0.38 ± 0.28 μM phosphate on an annual basis [S1 File]. Experimental plants (Z. noltei) and algae (Ulva sp.–likely Ulva rigida) were collected haphazardly from a large area (ca. 20,000 m2) and immediately transported to the laboratory. Sediment and water for the experiments was collected from Rio San Pedro, a sandy inlet in the vicinity of the laboratory. Seawater was collected using a pump with a 100 μm filter to remove suspended material.

Experimental set-up

The experiment was designed to investigate how the combined effect of high ammonium seawater concentrations and the presence of free-floating algae (here Ulva sp.) affected survival and growth of Z. noltei. We used a 2-factorial orthogonal design with 3 levels of ammonium loading and 3 levels of Ulva sp. biomass. Each treatment combination was replicated 3 times, rendering a total of 27 aquaria.

The experiment was conducted in a temperature controlled climate room set at 20°C. The aquaria were illuminated by lamps with cool fluorescent tubes (T5 High Output Blau Aquaristic aquarium color extreme fluorescents) in a 16:8 light:dark cycle, resulting in a light intensity of ca. 160 μmol photons · m2 · d-1. Each aquarium (volume = 20 L) was first filled with ca. 5 L of pre-sieved (through a 0.5 cm mesh) sediment and subsequently filled with ca. 15 L of seawater. Aeration pits were placed in all aquaria to ensure adequate mixing of water and air. Aquaria were left for 24 hours until re-suspended sediment had settled prior to transplantation of the plants.

All Z. noltei plants were first ‘standardized’ to consist of 1 apical shoot bearing a rhizome with 2–3 intact internodes and associated roots. Plants were individually labeled and then weighted (initial fresh weight; FW0) and the initial number of leaves and rhizome internodes per plant were recorded. The plants were subsequently distributed randomly among the 27 aquaria at a density of 15 plants per aquarium, corresponding to a density of ca. 200 shoots m-2 or a biomass of ca. 45 g FW m-2, which was approximately similar to the plant density and biomass at the sampling site.

Layers of Ulva sp. (0, 1 or 6 depending on treatment level) were placed between 2 pieces of nylon mesh (mesh size: 1 cm), which was fixed to the walls of each aquarium in the upper part of the water column, allowing the free circulation of seawater around the thalli (Fig 1). The biomass of Ulva sp. in treatments with 1 and 6 layers corresponded to a biomass of ca. 38 and 225 g FW aquarium-1, or 520 and 3086 g FW m-2, respectively, which resemble biomass values of drift algae in eutrophic systems [28,31,39]. The light intensity measured at the sediment surface differed substantially among Ulva treatments; the intensity was 28.9 ± 12.2 μmol photons · m-2 · s-1 (i.e. close to the compensation point of Z. noltei [40]) with 6 layers of Ulva sp., 74.5 ± 21.9 μmol photons ·m-2 · s-1 with 1 layer of Ulva sp. and 158.0 ± 40.3 μmol photons · m-2 · s-1 in the absence of Ulva sp. (saturating light levels). This set up was left for 48 hours to allow plants and algae to acclimate to experimental conditions before initiating the experiment.

Three levels of ammonium loading were assayed; aquaria in the first level (designated as level C) received no additional ammonium, while aquaria in the second treatment level (designated as +N) received 1125 μmol ammonium per week and aquaria in the third treatment level (+NN) received 2250 μmol ammonium per week. Ammonium was added from a stock solution to all aquaria in the +N and +NN treatments as 3 pulses per week. The target concentrations of ammonium in the 3 treatment levels were thus ca. 0, 25 and 50 μM per pulse, respectively. These concentrations were chosen since concentrations above 25 μM are known to cause adverse effects in Z. noltei [19,20]. Ammonium was added to the water column just beneath the algal layers and close to the aeration pit to ensure quick diffusion of nutrients in the aquaria. Water samples were taken from each aquarium before and 15 minutes after ammonium addition and immediately frozen at -20°C for later analysis of ammonium. Physico-chemical parameters (i.e. temperature, salinity, oxygen saturation and pH) were monitored when ammonium was supplied to the aquaria.

Addition of ammonium was repeated during days 0, 2 and 5 of each week, while water sampling for nutrient analyses and monitoring of physico-chemical parameters was repeated on days 0, 2, 5 and 7 of each week during the experiment (6 weeks in total). The seawater from all aquaria was renewed weekly (on day 7 each week). During water renewal the aquarium walls were cleaned with soft tissues to remove salt and epiphytes from the walls and detached seagrass leaves were removed. Sediment samples were also taken and frozen at -20°C for later analysis of benthic chlorophyll. Ulva sp. thalli in the meshes were replaced by new thalli every second week to maintain experimental conditions (i.e. approximately constant biomass and photosynthetic capacity).

All seagrass plants were harvested at the end of the experiment (plants without leaves were considered dead), cleaned and blotted with a soft paper towel, individually weighted (i.e. final fresh weight; FWF) and the number of internodes, shoots and leaves per shoot was counted. Survival rate (SR) was estimated for each aquarium from the number of surviving plants. Relative growth rate (RGR; % change in biomass · individual-1 · d-1) of all surviving Z. noltei plants was estimated as: where FWF and FW0 are the final and initial blotted fresh weight biomass, respectively, and t is the incubation time (in days). Net production (NP) of the seagrass assemblage in each aquarium (g FW · aquarium-1 · d-1) was estimated as the change in total biomass of the seagrass assemblage over time according to: where ΣFW0 is the total initial fresh weight biomass of all plants in an aquarium and ΣFWFS is the final total fresh weight biomass of all surviving individuals in the same aquarium and t is the incubation time (in days).

Laboratory analyses

The ammonium concentration in water samples was determined by the salicylate-hypochlorite method [41]. Net removal (uptake) of ammonium from the water in each aquarium was estimated by subtracting the amount of ammonium present in the aquaria at the end of each week from the amount of ammonium added to the water during the preceding week.

Chlorophyll in the sediment was extracted overnight with methanol and measured spectrophotometrically to obtain total chlorophyll concentrations [42].

Statistical analyses

Physico-chemical variables (water temperature, salinity, pH and oxygen saturation) and the biomass of benthic microalgae were compared across time and treatments (ammonium: 3 levels and Ulva sp. biomass; 3 levels, both considered fixed factors) using repeated measures ANOVA.

Changes in final ammonium concentrations from each week and estimated weekly removal of ammonium by the autotrophic assemblage (i.e. seagrass, Ulva sp. and benthic macroalgae) across treatments and time could not be tested by repeated measures ANOVA since several treatment combinations had identical replicate values (i.e. 0 μM ammonium or 100% removal, respectively), and therefore, no variation associated to their treatment means. Mean values for each treatment combination and sampling time was instead plotted with ±95% confidence limits for visual inspection.

Two factorial ANOVA was used to test the effects of ammonium loading and Ulva sp. biomass on seagrass survival, growth and net production. Tukeys test was used to compare levels of treatment factors when main factors (but not interactions) had a significant effect. In case of significant interactions, Tukeys test was used to compare the levels of each factor within each level of the other factor and vice versa using Bonferroni to correct the Type I error level as recommended Underwood (1997) [43] and Meyers et al. 2006 [44]. All data were checked for normality and homoscedasticity using Kolmogorov Smirnoffs test and Levenes test, respectively, and data were ln-transformed when necessary to obtain homogeneity of variances. The level of significance was set at 5% (α = 0.05) in all analyses except those that were Bonferroni corrected.

Pearsons correlation analysis was used to test the possible correlation between ammonium concentration in the water at the end of the week and the biomass of benthic microalgae at the same time. Only data obtained from aquaria without Ulva sp. were included in this analysis because presence of Ulva sp. would have confounded the outcome of the test.

All statistical analyses were conducted using SPSS v. 22 while graphs were made using SigmaPlot v. 11.


Physico-chemical variables

Water temperature averaged 20.9 ± 1.7°C, salinity 38.9 ± 2.9, oxygen saturation 94.7 ± 1.1% and pH 8.3 ± 0.1 across all aquaria and sampling dates. Repeated measures ANOVA did not reveal any significant differences in these variables among treatment combinations nor over time (p always >> 0.05).

Ammonium dynamics in the aquaria

The ammonium concentration in the water at the end of each week (i.e. just before changing the water) differed considerably depending on tretament (Fig 2). Final ammonium concentrations increased generally with increasing ammonium loading, averaging 0 ± 0 μM (mean ±95% CL) in treatments without ammonium addition (across all levels of Ulva sp. and sampling time), 12.7 ± 17.4 μM in the +N treatments and 30.9 ± 36.3 in the +NN treatments. Ammonium concentrations at the end of the week tended to decrease with increasing biomass of Ulva sp. (across all levels of ammonium and sampling time), averaging 34.4 ± 35.8 μM in treatments without Ulva sp., 8.0 ± 13.4 μM in treatments with one layer of Ulva sp. and 1.3 ± 4.2 μM with six layers of Ulva sp. The effect of ammonium loading tended to diminish with increasing Ulva sp. biomass even though the interaction between ammonium and Ulva treatments could not be tested formally.

Fig 2. Change in ammonium concentrations at the end of the week over time (μM).

A) No Ulva sp., B) 1 layer of Ulva sp., C) 6 layers of Ulva sp. Mean values ± 95% confidence limits (n = 3).

The final concentrations of ammonium in the various treatment combinations reflect the balance between ammonium added (through treatment) and ammonium removed by the autotrophic assemblage (seagrasses, Ulva sp. and benthic microalgae) in each aquarium. Estimated ammonium uptake by the autotrophs differed markedly among treatment combinations (Fig 3). Thus, it increased generally with increasing ammonium loading; averaging (across all levels of Ulva sp. biomass and sampling time) 0 ± 0 μmol aquarium-1 week-1 (mean ±95% CL) with no addition of ammonium, 934 ± 261 μmol aquarium-1 week-1 in the +N treatment and 1786 ± 544 μmol aquarium-1 week-1 in the +NN treatment. The uptake of ammonium tended to increase with increasing Ulva sp. biomass; averaging 609 ± 567 μmol aquarium-1 week-1 without Ulva sp., 1006 ± 858 μmol aquarium-1 week-1 with one layer of Ulva sp. and 1105 ± 922 μmol aquarium-1 week-1 with 6 layers of Ulva sp. From Fig 3 there is no visible indication of a strong interaction effect between ammonium loading and Ulva sp. biomass.

Fig 3. Removal (uptake) of ammonium from the water by autotrophs.

A) No Ulva sp., B) 1 layer of Ulva sp., C) 6 layers of Ulva sp. Horizontal lines represent 100% removal of ammonium by autotrophs for the +N treatment (grey) and the +NN treatment (black), respectively. Mean values ± 95% confidence limits (n = 3).

Benthic microalgae

The average (across all treatment levels) biomass of benthic microalgae (Fig 4) increased significantly from 0.08 ± 0.15 μg Chl g-1 sediment (mean ± 1 SE) in week 2 to 4.76 ± 2.36 μg Total Chl g-1 sediment in week 5 (RM ANOVA, effect of Time; F = 14.4, p < 0.001). The biomass of benthic microalgae was unaffected by ammonium treatment, by Ulva treatment and by any of the interactions between ammonium, Ulva treatment and time (RM ANOVA, p always > 0.066). However, correlation analysis revealed a moderate negative and significant correlation between benthic chlorophyll and ammonium concentration at the end of the week (R = -0.48, p = 0.005; Fig 5).

Fig 4. Biomass of benthic microalgae.

Each bar represents pooled data from all treatments since there were no significant differences in biomass among treatments. Letters above the bars represent significant differences among weeks. Mean values ± 1 SE (n = 27).

Fig 5. Relationship between ammonium concentration in the water and biomass of benthic microalgae at the end of each week.

Only data of treatments without Ulva sp. and with ammonium addition were used for this analysis (n = 30).

Plant responses

Z. noltei was negatively affected by ammonium addition as indicated by lower survival, slower growth and lower net production in treatments with ammonium enrichment, whereas the presence of Ulva sp. tended to alleviate the negative effects of ammonium (Fig 6, Table 1).

Fig 6. A) Survival rate, B) Relative growth rate and C) Net production of Z. noltei.

Letters over the bars represent significant differences between treatments with the same number of Ulva sp. layers; symbols (*, +) represent significant differences between Ulva sp. treatments with the same ammonium treatment. Data represent the mean ± SE (n = 3).

Table 1. ANOVA results testing the effects of ammonium and Ulva treatments on survival rate (SR), relative growth rate (RGR) and net production (NP) of Zostera noltei.

Bold letters indicate significant differences.

Survival rate (Fig 6A) ranged from 26.7 ± 30.6% to 60.0 ± 6.7% (mean ± 1 SE) depending on treatment, indicating that there was some mortality in all the aquaria. Survival tended to decrease with increasing ammonium loading across all levels of Ulva sp. biomass, albeit this effect was not significant (p = 0.107; Table 1). Survival was not affected by Ulva sp. biomass nor by the interaction between ammonium loading and Ulva treatment (Table 1).

The relative growth rate of Z. noltei ranged from -0.27% d-1 to 1.2% d-1 across all treatment combinations and was significantly affected by the interaction between ammonium loading and Ulva sp. biomass (Fig 6B, Table 1). Growth rate decreased substantially with increasing ammonium loading in the absence of Ulva sp. (C vs. +N and C vs. +NN; both p < 0.001). This negative effect of ammonium loading dissapeared, however, in treatments with 1 or 6 layers of Ulva sp., where growth rate did not differ among ammonium treatments (p always > 0.138). The effect of Ulva sp. biomass on growth was not straightforward; without any addition of ammonium, Z. noltei grew faster in treatments without Ulva sp. than in treatments with 1 layer of Ulva sp. (p = 0.002), while the opposite was true in treatments with addition of ammonium, i.e. the +N treatment (p < 0.001) and the +NN treatment (p = 0.006).

Net production was negative in all treatments, and only significantly affected by ammonium loading (Fig 6C, Table 1). Net production decreased with increasing ammonium loading across all levels of Ulva sp. biomass (p = 0.006). Net production remained unaffected by Ulva sp. biomass and it was neither affected by the interaction between ammonium loading and Ulva sp. biomass.

We found no significant effects of ammonium loading or Ulva sp. biomass, nor any significant effect of the interaction between these main factors on the remaining response variables, i.e. number of new internodes and leaves produced (p always >> 0.05, data not shown).


Eutrophication affects seagrasses in several ways. Enhanced light attenuation caused by increasing amounts of phytoplankton, epiphytes and drift macroalgae is considered the most important negative consequence of eutrophication for benthic macrophytes [9,45], but an increasing number of studies have also shown that high ammonium concentrations in the water column can be toxic to seagrasses [18,19,21]. It is however unclear how the combination of high ammonium concentrations and large amounts of drift algae will affect seagrass performance, although recent studies have shown that low light conditions might intensify the negative effect of high ammonium availability [34].

The effect of high ammonium availability

High ammonium concentrations in the water had a profound negative effect on seagrass performance in our experiment. Zostera noltei suffered higher mortality, slower growth and lower net production when cultivated alone (i.e. without Ulva sp.) under high ammonium concentrations (i.e. 25 and 50 μM treatments) than when grown without additional addition of ammonium. It agrees with results from other studies on Z. noltei [17,19,20] and other seagrass species [18,21,34] and confirms that high levels of ammonium in the water can be harmful to Z. noltei.

Ammonium toxicity appears when plants are exposed to high levels of ammonium in the water for extended periods. In seagrasses, foliar ammonium uptake is rather proportional to the concentration of ammonium in the surrounding water [35,46,47]. Exposure to high concentrations of ammonium will therefore lead to enhanced uptake, assimilation (i.e. production of amino acids) and protein synthesis. Intracellular levels of ammonium are typically held low by assimilation, which continuously removes ammonium from the intracellular space, but ammonium may accumulate within cells when assimilation and protein synthesis slows down as plants become N-replete [48,49] or if assimilation becomes limited by lack of C-skeletons due to reduced photosynthesis and/or depletion of internal carbon stores [17]. Accumulation of intracellular ammonium may alter pH and enzyme kinetics, and thus, adversely affect plant metabolism including photosynthesis [50].

Zostera noltei was able to remove most, but not all, of the added ammonium when cultured without Ulva sp. (Fig 3A) as indicated by the relatively high ammonium concentrations in the water at the end of each week (Fig 2A). The high ammonium concentrations observed in aquaria with ammonium addition indicate that plants became saturated with nitrogen over the course of the experiment, and that ammonium may have accumulated within the plants. We did not measure internal N-concentrations, nor did we measure internal sugar levels in the plants, but other studies have shown that accumulation of various N fractions (i.e. ammonium, amino acids etc.) in plants and algae appears at time scales of days to few weeks when exposed to high concentrations of ammonium [17, 48], and that decreasing rates of N-assimilation and increasing accumulation of ammonium occurs parallel with decreasing amounts of stored carbohydrates [17]. We feel therefore confident that the observed negative effects of high ammonium concentrations on Z. noltei were caused by toxic effects due to accumulation of ammonium within the plant cells.

Presence of Ulva and the effect of reduced light conditions

Photosynthesis and growth depends essentially on light and reduced light levels will therefore slow down net photosynthesis and growth. Shading is therefore considered one of the most harmful stressors for seagrasses and other benthic macrophytes. The presence of Ulva sp. in the aquaria caused a significant light attenuation and the reduction in light intensity was directly proportional to the number of Ulva sp. layers. With 1 layer of Ulva sp., light levels at the bottom of the aquaria were reduced to sub-saturating levels and the growth rate of Z. noltei was reduced by ca. 68% in comparison to the control treatment (i.e. no Ulva sp.). Survival and net production tended also to decrease although these rates did not differ significantly from rates in the control treatment without Ulva sp.

Light levels were substantially reduced below 6 layers of Ulva sp. and corresponded more or less to the compensation point of Z. noltei [40]. We expected therefore to detect a significant effect on seagrass performance, but the effect was much less evident than with 1 layer of Ulva sp. and neither survival, growth nor net production differed significantly from those in the control situation. Although this response seemed puzzling, it could be explained by the fact that Z. noltei can acquire DOC released from macroalgae and use it as a supplement to DIC obtained by photosynthesis. Previous studies [32,51,52] have shown that growth of Z. noltei are severely reduced when shaded by 2 layers of Ulva rigida, but also, that a larger biomass of macroalgae (i.e. 8 layers of U. rigida) had an ameliorating effect on seagrasses even though light limitation was stronger. The same authors showed that Z. noltei was able to acquire DOC released from U. rigida and that high DOC concentrations in the water stimulated the growth of Z. noltei significantly under low light conditions.

The combined effect of Ulva sp. and high ammonium levels

The negative effect of high ammonium availability can be boosted under experimentally reduced light intensity using shading screens resulting in a negative synergistic effect of high ammonium and low light [17, 53]. Combining the two main factors (i.e. high ammonium level and shading caused by overlying Ulva sp.) resulted however in a quite different response in this experiment. The growth rate of Z. noltei increased significantly at high ammonium availability when moderate amounts of Ulva sp. were present, and a similar trend was observed for survival and net production albeit these differences were not statistically significant. This positive effect of Ulva sp. can be explained by the interaction between main factors; addition of ammonium to cultures without Ulva sp. resulted in saturated uptake of ammonium in Z. noltei that experienced relatively high concentrations of ammonium over the course of the experiment. In contrast, when cultured together with Z. noltei, Ulva sp. contributed to remove ammonium from the water, and thus, prevented ammonium concentrations to increase to critical, toxic levels within Z. noltei.

Ulva sp. and other fast-growing ephemeral macroalgae take up ammonium much faster than seagrasses per unit time and biomass [35,36,47]. The potential removal of ammonium by Z. noltei and Ulva sp. in treatments with both species can be estimated from the observed biomass and published uptake kinetic values (i.e. Vmax and Km) for Ulva lactuca [36] and leaves of Zostera marina [47]. Assuming that plants and algae were exposed to either 25 or 50 μM ammonium, Z. noltei would be able to remove ca. 234 or 270 μmol ammonium aquarium-1 d-1 (assuming a biomass equivalent to the initial biomass per aquarium), which is less than added to each aquarium in the two treatments (375 and 750 μmol ammonium every second day, respectively), explaining why ammonium concentrations could remain high in treatments without Ulva sp. Seagrass biomass declined over the course of the experiment in all treatments except those with no ammonium addition, so these estimates are conservative and likely overestimating the actual removal of ammonium by Z. noltei during the last 3–4 weeks of the experiment. The potential removal of ammonium by Ulva sp. was 40–250 fold higher than that for Z. noltei, being 10.6 and 11.7 mmol d-1 (in the 25 and 50 μM treatments, respectively) with one layer of Ulva sp. and 62.7 and 69.4 mmol d-1 with six layers of Ulva sp. Ulva sp. had thus a great potential to remove ammonium from the water and it is evident that 1 and especially 6 layers of Ulva sp. must have been able to keep concentrations of ammonium low to the benefit of Z. noltei that performed better in the presence of Ulva sp. even though light conditions were deteriorated. A study on freshwater macrophytes in a Chinese hyper-eutrophic lake supports our findings. The authors of this study [54] found that the concentration of ammonium in the water column decreased substantially during an algal bloom, while at the same time, the performance of rooted macrophytes growing in the system was improved when compared to the performance of plants before the algal bloom.

The efficient removal of ammonium from the water in treatments with Ulva sp. can be explained by the large uptake capacity of this macroalgal species. Without Ulva sp. and partly 1 layer of Ulva sp., final ammonium concentrations at the end of each week were relatively high and especially so during the initial 1–3 weeks of the experiment, after which they decreased progressively over the course of the experiment. This would suggest that the capacity of Z. noltei to remove ammonium increased with time. The capacity to acquire ammonium from the water should, however, decrease as plants become more N-replete [49]. Also, the absolute removal of ammonium through uptake should partly depend on seagrass biomass, which decreased significantly in all treatments except those without ammonium addition. The increased capacity to remove ammonium from the water can therefore not be explained by an increased capacity to acquire ammonium by Z. noltei, nor by an increasing biomass of Ulva sp., since the biomass of Ulva sp. was kept constant by continuously replacing old thalli by new ones with approximately the same initial biomass. Instead, it seems that the increasing uptake capacity of the autotrophic assemblages can be explained by the increasing biomass of benthic microalgae. The amount of benthic microalgae increased over time and across all treatment combinations (Fig 4). A significant negative correlation between benthic chlorophyll and ammonium concentration in the water column at the end of the week was found, suggesting that part of the ammonium was being depleted by benthic microalgae. The biomass of these algae might have been substantially smaller than that of Z. noltei and Ulva sp., but microalgae grow much faster and, thus, have a much higher need for nitrogen per unit biomass and time [55]. The large potential of benthic microalgae to remove ammonium from the overlying water was shown in a previous study [56] where it was demonstrated that benthic microalgae could remove up to 80% of the ammonium in the water column across a range of concentrations similar to those used in our experiment. Our results therefore suggest that at least 2 (benthic microalgae and Z. noltei) or 3 (Ulva sp., benthic microalgae and Z. noltei) different types of organisms were involved in the removal of ammonium from the water column and also that further studies are required to investigate the larger capacity to remove ammonium from the water column by more diverse assemblages.

In summary, eutrophication affects seagrasses in various ways: by increasing light attenuation caused by proliferating fast-growing algae (i.e. phytoplankton, epiphytes and drift macroalgae), and through ammonium toxicity when concentrations become high enough. Seagrass meadows in eutrophic, sheltered coastal areas are often covered by fast-growing drift macroalgae in summer [28]. Such algal mats can be thick and they may persist and cover the seagrasses for weeks. Under such conditions, light attenuation through the mat may be complete, which is certainty harmful to the underlying seagrasses. Algae in the lower part of the mat may also suffer severe light limitation, which may stop growth and nutrient uptake, and, thus, create a barrier for the ammonium that diffuses from the sediment. Ammonium may thus accumulate to high concentrations in the water surrounding the canopy. Seagrasses covered by thick layers of drift macroalgae may therefore suffer from substantial light limitation and potential ammonium toxicity at the same time. In contrast, when algal mats are thinner and/or are more dynamic [31], algae in the lower part of the mat will still receive light (albeit at lower levels than those the upper part of the mat). All algae in the mat will be actively growing [57], and they will take up nutrients, which may aid to remove part of the ammonium diffusing from the sediment thereby contributing to keep the ammonium concentrations relatively low around the seagrass plants. We hypothesize that moderate layers of drift macroalgae may aid seagrasses to sustain shorter periods of algal cover through removal of excess ammonium although such seagrasses will be negatively affected by the algal cover through light limitation.


We thank Pedro López Pulido, Rosa Cantero Rodriguez and Alexandre Martínez Schönemann for the help in the field work necessary (plant harvesting) for conducting this experiment. This work was supported by the Spanish Project Sea-Live (CMT2011-24482) from the Spanish Ministry of Science and Innovation and by the Junta de Andalucia Excellence Project PRODESCA (P12-RNM-03020). This is CEIMAR journal publication no. 125.

Author Contributions

Conceived and designed the experiments: FMM JJV JLPL MFP FGB. Performed the experiments: FMM. Analyzed the data: FMM FGB JJV MFP. Contributed reagents/materials/analysis tools: FGB JJV JLPL. Wrote the paper: FMM JJV JLPL MFP FGB.


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1. Introduction

Marine organisms produce a variety of compounds with pharmacological activities, including anticancer, antimicrobial, antifungal, antiviral, antiinflammatory and others, and are potential sources of new therapeutic agents. Marine organisms survive and live within complex communities and in close association with others in a competitive and hostile environment. They produce complex secondary metabolites as a response to ecological pressure, such as competition for space, predation and tide variations. Some of these compounds are antimicrobials that inhibit or limit the development and growth of other competitive microorganisms.

Marine sessile organisms, such as algae, sponges and corals, have developed physiological adaptations, including the synthesis of bioactives which confer defense against grazers and/or the installation of epiphytes and fouling organisms [1,2,3]. Metabolites from green, brown and red marine algae may be useful for inhibiting bacteria, viruses, fungi and other epibionts (e.g., cytostatic, antiviral, antihelmintic, antibacterial, antifungal activity). Algae crude extracts and their fractionated or purified components also exhibit, for example, anticoagulant [4], antiviral [5], antioxidant [6], anticancer [7], and antiinflammatory [8] activities.

Microorganisms have developed new strategies to evade the action of antibiotics, leading to multiple drug-resistant bacterial strains. With increasing resistance of pathogens to antibiotics, there is a public health priority for exploring and developing cheaper and effective natural antimicrobial agents with better potential, less side effects than antibiotics, good bioavailability, and minimal toxicity [9]. It is also worthwhile to test the marine antimicrobials for possible synergism with existing drugs [10].

Updated information on this research area has been compiled recently, including the antiviral properties of marine organisms [11], the seaweed-associated bacterial and fungal communities [12], and the diversity and bioactives production of actinobacteria associated with the marine organisms [13]. Based on published studies, Vatsos and Rebours [14] reviewed the antimicrobial properties of seaweed extracts related with aquaculture. Eom et al. [15] reviewed the antimicrobial effects of phlorotannins from brown algae, in relation to the food and pharmaceutical industries. Abu-Ghannam and Rajauria [16] reviewed the algal antimicrobials with potential food applications. The studies showing biological activities of extracts from native and some non-native Brazilian seaweed [17] and the research progress concerning the isolation and structural elucidation of the secondary metabolites from the genus Cystoseira [18] were overviewed. The objective of this work is to gather the recently published information on the antimicrobial properties of compounds from seaweed, their extraction and the major applications.

2. Bioactive Compounds

In the food, pharmaceutical, cosmetic, cosmeceutical, nutraceutical and biomedicine industries, seaweed/macroalgae are used as a valuable source of bioactive compounds. Many compounds, being antiparasitic, antiviral or antibacterial, are effective [19]. The influence of some natural factors, such as the environmental conditions, including light, temperature or salinity, the life stage, reproductive state and age of the seaweed, and the geographical location and seasonality, allowed for the consideration that this antimicrobial activity was not attributed to a single compound, but it could be related to some of them and to a combination of metabolites.

Seaweed or macroalgae provide a great variety of metabolites and natural bioactive compounds with antimicrobial activity, such as polysaccharides, polyunsaturated fatty acids, phlorotannins and other phenolic compounds, and carotenoids.

2.1. Polysaccharides and Derived Oligosaccharides

The main components of green, brown and red seaweed are usually polysaccharides, which may have storage and structural functions. Cell walls of algae are composed of a variety of polysaccharides including alginic acid and alginates, carrageenans and agar, laminarans, fucoidans, ulvans and derivatives [20,21].

Their antimicrobial activity depends on some factors, such as their distribution, molecular weight, charge density, sulphate content (in sulphated polysaccharides), and structural and conformation aspects. In addition, oligosaccharides obtained by depolymerization of seaweed polysaccharides also induce protection against viral, fungal and bacterial infections in plants [22].

These polymeric carbohydrates structures are usually composed of various monosaccharides linked with different glucosidic bonds. Some algal polysaccharides, such as sulphated galactans of the red algae or ulvans of the green algae, have linear backbones containing dissacharide repeating units. Otherwise, alginic acids have linear molecules built up of different blocks of two monomerics units. Algal macromolecules include sulfated polysaccharides such as: carrageenan and agar from red algae; alginate, fucan and laminarinan from brown alga; and cellulose and ulvan from green algae.

2.1.1. Alginates

Algins/alginates are available in both acid and salt forms. Alginic acids are linear copolymers of two uronic acids, β-d-mannuronic acid (M) and α-l-guluronic acid (G) linked in position 1→4. The salt forms (alginates), with several cations (Na+, K+, Mg2+ and Ca2+), are the major components of brown seaweed cell walls and also of the intracellular matrix [21]. Alginates are anionic polysaccharides and are made up of β-d-mannuronic acid (M) and α-l-guluronic acid (G), and alternating blocks of d-guluronic and d-mannuronic (M-M, G-G or M-G blocks) [22,23] (Figure 1). The molecular weight of alginate ranges generally between 500 and 1000 kDa.

2.1.2. Carrageenans

Carrageenans are the major components of red seaweed cell walls, and this group of molecules is composed of linear polysaccharide chains with sulphate half-esters attached to the sugar unit. There are three general forms: kappa, lambda and iota, according to the degree of sulphation (Figure 1). Kappa carrageenan and iota carrageenan have one or two, respectively, sulphate groups per disaccharide unit and anhydrogalactose residue, and lambda carrageenan has three sulphate groups per disaccharide unit [22].

2.1.3. Agar

Agar is a mixture of at least two polysaccharides, i.e., agarose and agaropectin, extracted also from red seaweed with similar structural and functional properties as carrageenans. Agarose is the predominant fraction of agar, and it consists of high molecular weight polysaccharides composed of repeating units of (1→3)-β-d-galactopyranosyl-(1→4)-3,6-anhydro-α-l-galactopyranose (Figure 1). The structure of agaropectin, with a lower molecular weight than agarose, is essentially made up of alternating (1→3)-β-d-galactopyranose and of (1→4)-3,6-anhydro-α-l-galacto-pyranose residues.

2.1.4. Galactans

Sulphated galactans are the main extracellular polysaccharides of red algae (but are also found in brown and green algae). Typical structure is a linear chain of galactoses; a chain of alternating 3-β-d-galactopyranose (G units) and 4-α-d-galactopyranose residues, or 4-3,6-anhydrogalactopyranose residues complete their structural backbone with presence of d-series (d unit) in carrageenans and l-series (l unit) in agarans. Other exceptional galactans present the dl-hybrids that enclose G unit attached to both d and l units [24].

2.1.5. Laminarans

Laminaran is the principal storage polysaccharide of brown seaweed (e.g., Laminaria or Saccharina spp.) and their content can represent up to 32%–35% (d.w.). Laminarans are small glucans and are a linear polysaccharide composed of β-(1→3)-linked glucose, containing randomly β-(1→6) intra-chain branching, with a ratio around 3:1 [23]. The degree of polymerization varying between 20 to 50 units and the polymeric chains can be of two types according to their reducing end: M chains end with a d-mannitol residue, whereas G chains end with a glucose residue (Figure 1). The molecular weight is approximately 5000 Da depending on the degree of polymerization (usually 25) [25].

2.1.6. Fucoidans/Fucans

Fucoidans and laminarans are considered as the main water-soluble polysaccharides of brown algae. Fucoidans are a complex and heterogeneous group of polysaccharides, which contribute to intercellular mucilage and are sulfated polysaccharides composed of l-fucose and sulphate ester groups with minor amounts of different molecules, which can vary from monosaccharides (i.e., mannose, arabinose, glucose, galactose, xylose, etc.), acidic monosaccharides, acetyl groups to proteins [26].

Terms such as fucans, fucosans, fucose containing polymers or sulfated fucans have also been adopted for this group; however, finally, according to the IUPAC terminology, fucoidans is retained for polysaccharides of algal origin, and fucan sulphates (or fucans) to the similar polymers from marine invertebrates [21].

Various molecular weights, from 100 to 1600 kDa, have been reported in the literature for fucoidans [25] because they may differ considerably in their composition and chemical structure (degree of branching, substituents, sulphation and type of linkages).

Fucoidan composition varies with species and geographical origin, even within the same species. It appears that the prevalent core backbone structures are primarily the (1→3)-linked α-l-fucopyranosyl backbone structure, and secondarily the backbone structure composed of alternating α (1→3) and α (1→4)-linked l-fucopyranosyls [27]. The first group includes the fucoidans from Laminaria spp., Analipus japonicus, Cladosiphon okamuranus, and Chorda filum and the second group included fucoidans isolated from Ascophyllum nodosum and Fucus sp. However, sulphate- and acetyl-groups and some sugar residues may occur at C2 and/or at C4 positions.

2.1.7. Ulvans

Ulvan designates a water-soluble sulphated polysaccharides extracted from the intercellular space and in the fibrillar wall of green seaweed (mainly Ulva sp.) and accounts from 18% to 29% of the algal dry weight [28]. These polysaccharides are mainly composed of glucuronic acid and iduronic acid units together with rhamnose and xylose sulfates, connected by α- and β-1→4 bonds, with an average molecular weight of ulvans ranging from 189 to 8200 kDa.

The main repeating disaccharide units reported are ulvanobiouronic acid 3-sulphate types containing either glucuronic or iduronic acid (Figure 1). Additionally, minor repeating units have been reported that contain sulfated xylose replacing the uronic acid or glucuronic acid as a branch on O-2 of the rhamnose-3-sulphate [29].

2.2. Lipids, Fatty Acids Ans Sterols

Algal lipids content in seaweed ranges from 0.12% to 6.73% (dry weight), and are composed mainly of phospholipids, glycolipids and non-polar glycerolipids (neutral lipids) [30]:
  • Phospholipids are located in extra-chloroplast membranes and account for 10%–20% of total lipids in algae. They are characterized by higher contents of n-6 fatty acids, and the major fatty acids present are oleic, palmitic, stearic, arachidonic and eicosapentanoic acids. The most dominant phospholipid in algae is phosphatidylglycerol in green algae, phosphatidylcholine in red algae, and phosphatidylcholine and phosphatidylethanolamine in brown algae.

  • Glycolipids are located in photosynthetic membranes and constitute more than half of the lipids in the main algal groups. They are characterized by high n-3 polyunsaturated fatty acids. Three major types of glycolipids are monogalactosyldiacylglycerides, digalactosyldiacylglycerides, and sulfoquinovosyldiacylglycerides [31].

  • Triacylglicerol is the most prevalent neutral lipid, their content ranging from 1% to 97% with a function of storage and energy reservoir.

Fatty acids are carboxylic acids with aliphatic chains and prevalent even carbon numbers (C4-C28) that may be straight or branched, saturated or unsaturated. According to the double bond, fatty acids are classified as monounsaturated (MUFA) or polyunsaturated (PUFA) fatty acids, and the last one could be classified as n-3 or n-6 depending on the position of the first double bond from the methyl end. Green algae are rich in C18 PUFAs, mainly α-linolenic (C18:3 n-3), stearidonic (C18:4 n-3) and linoleic (C18:2 n-6) acids; red algae is rich in C20 PUFAs, mainly arachidonic (C20:4 n-6) and eicosapentaenoic (C20:5 n-3) acids, and brown algae exhibit both.

Oxylipins are the oxygenated products of fatty acids and are mainly derived from C16, C18, C20 and C22 PUFAs and confer innate immunity in response to biotic and abiotic stress, such as pathogenic bacteria and herbivores. [30].

Sterols are structural components of cell membrane and regulate membrane fluidity and permeability. They are composed of four rings (A–D) with a hydroxyl group in carbon-3, two methyl groups at C18 and C19 carbons and a side chain at C17 (see Figure 2). The main sterols in macroalgae are cholesterol, fucosterol, isofucosterol, clionasterol [30].

2.3. Phenolic Compounds

Phenolic compounds are secondary metabolites because they are not directly involved in primary processes such as photosynthesis, cell division or reproduction of algae. They are characterized by an aromatic ring with one or more hydroxyl groups and the antimicrobial action is due to the alteration of microbial cell permeability and the loss of internal macromolecules or by the interference with the membrane function and loss of cellular integrity and eventual cell death [16].

Chemically, structures ranging from simple phenolic molecules to complex polymers with a wide range of molecular sizes (126–650 kDa) have been described [26]. Polyphenols could be divided into phloroglucinols and phlorotannins. Phloroglucinol contains an aromatic phenyl ring with three hydroxyl groups (Figure 2). Phlorotannins are oligomers or polymers of phloroglucinol with additional halogen or hydroxyl groups; and, according to the inter-linkage, phlorotannins can be subdivided into six specific groups: (i) phlorethols (with aryl-ether linkage); (ii) fucols (with aryl-aryl bonds); (iii) fucophlorethols (with ether or phenyl linkage); (iv) eckols (with dibenzo[1,4]dioxin linkages); the less frequent (v) fuhalols (with ortho-/para-arranged ether bridges containing an additional hydroxyl on one unit); and (vi) carmalols (with dibenzodioxin moiety) [32]. The presence of simple phenols, such as hydroxycinnamic and benzoic acids and derivates, and flavonoids were reported in the green seaweed [33], but brown seaweed has higher contents of phenolic compounds than green and red macroalgae. The typical phlorotannin profile from brown algal with antimicrobial activity mainly consists of phloroglucinol, eckol and dieckol [19].

2.4. Pigments

Algae as photosynthetic organisms can synthezise the three basic classes of pigments found in marine algae:chlorophylls, carotenoids and phycobiliproteins, allowing classification of seaweed into Chlorophyceae (green algae), Phaeophyceae (brown algae) and Rhodophyceae (red algae). The green color is due to the presence of chlorophylls a and b, the greenish brown color is attributed to the fucoxanthin, chlorophylls a and c, and responsible for the red color are the phycobilins, such as phycoerythrin and phycocyanin [34].

The antimicrobial mechanism proposed for carotenoids could lead to the accumulation of lysozime, an immune enzyme that digests bacterial cell walls [16]. Carotenoids are present in all algae and are lipid-soluble, natural pigments composed of eight units of five carbons, namely tetraterpenoids, with up to 15 conjugated double bonds. Carotenoids are usually divided in two classes: carotenes (when the chain end with a cyclic group, containing only carbon and hydrogen atoms) and xantophylls or oxycarotenoids (which have at least one oxygen atom as a hydroxyl group, as an oxy-group or as a combination of both). β-Carotene is the most common carotene (Figure 2), whereas lutein, fucoxanthin (Figure 2) and violaxanthin belong to the xanthophylls class [35]. β-Carotene, lutein, violaxanthin, neoxanthin and zeaxanthin are found in green seaweed species; α- and β-carotene, lutein and zeaxanthin are present in red seaweed, and β-carotene, violaxanthin and fucoxanthin are found in brown algae [34].

2.5. Other Compounds

Seaweed is also able to produce other secondary metabolites with a broad range of antifungal, antiviral, antibacterial, antimacrofouling and antiprotozoan activities, such as terpenes, alkaloids, lectins or halogenated compounds.

2.5.1. Lectins

Lectins are natural bioactive ubiquitous proteins or glycoproteins of non-immune response that bind reversibly to glycans of glycoproteins, glycolipids and polysaccharides possessing at least one non-catalytic domain causing agglutination.

Algal lectins differ from terrestrial lectins because they are monomeric, low molecular weight proteins, exhibiting high content of acidic amino acids, with isoelectric point in the range of 4–6. They do not require metal ions for their biological activities, and most of them show higher specificity for oligosaccharides and/or glycoproteins than for monosaccharides. Based on the binding properties to glycoproteins, algal lectins are categorized into three major categories: complex type N-glycan specific lectins, high mannose (HM) type N-glycan specific lectins and lectins with specificity to both the above types of N-glycans [36]. Lectins from marine organisms are also classified into C-type lectins, F-type lectins, galectins, intelectins, and rhamnose-binding lectins [37].

2.5.2. Alkaloids

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