Journal of Applied Phycology https://doi.org/10.1007/s10811-019-1748-7 Is Ulva sp. able to be an efficient biofilter for mariculture effluents? M. Shpigel 1,2 & L. Guttman 3 & D. Ben-Ezra 3 & J. Yu 4 & S. Chen 4 Received: 29 August 2018 / Revised and accepted: 28 January 2019 # Springer Nature B.V. 2019 Abstract Nitrogenous compounds such as ammonia, nitrate, and dissolved organic nitrogen (DON) are the main waste components of marine fish pond effluents. These compounds are also regarded as the primary nitrogen sources for seaweed. Aiming at designing an efficient and cost-effective extractive biofilter for fishpond effluents, Ulva lactuca performance and the dynamics of dissolved inorganic (DIN) and DON uptake by this alga grown in the effluents of a land-based integrated multi-trophic aquaculture (IMTA) system were studied. Stocking densities of 1 and 3 kg m−2 were found to be optimal for yield along with specific growth rate (SGR) and protein content, respectively. The presence of ammonia inhibited nitrate uptake by U. lactuca and carbon limitation reduced SGR and yield. However, protein levels of U. lactuca tissue in a carbon-limited situation were higher than when unlimited carbon was made available. When compared with 3 kg m−2 stocking densities, the high C/N ratio in U. lactuca tissue cultured at 1 kg m−2 likely indicated carbon limitation. Ammonia assimilation rate was density dependent. At 1 kg m−2, ammonia uptake was relatively fast, at 4.31 μmole N h−1, and nitrate uptake started only 24 h after ammonia depletion, suggesting this period to be the time required for nitrate reductase (NR) synthesis in the algae tissue. At 2 kg m−2, ammonia uptake was 2.51 μmole N h−1 and nitrate uptake started 24 h after that observed in 1 kg m−2, suggesting that the lower ammonia threshold for uptake by the U. lactuca is around 1.4 μmole L−1. Contrary to 1 and 2 kg m−2 stocking densities, in the 3 kg m−2 stocking density, ammonia uptake was as low as 1.51 μmole N h−1 and no uptake of nitrate appeared to have taken place due to the presence of ammonia in the water. The additional ammonia in the water was found to be due to DON-ammonifying bacteria on the surface of U. lactuca thalli. In the 1ow stocking density, the additional ammonia was relatively low compared to that measured at the high algae density. In the light of the better understanding of the system dynamics achieved in our study, we hypothesize that a set of similar bioreactors using U. lactuca can intensify the system purification efficiency manifold. Keywords Ulva lactuca . Biofilter . Nutrient dynamics . Biochemical composition . IMTA . Aquaculture * M. Shpigel shpigelm@gmail.com L. Guttman lior.guttman@mail.huji.ac.il D. Ben-Ezra bedavid38@gmail.com J. Yu yuhaibinzmri@126.com S. Chen chenshaobo@hotmail.com 1 Morris Kahn Marine Research Station, The Leon H. Charney School of Marine Sciences, University of Haifa, Haifa, Israel 2 The Interuniversity Institute for Marine Sciences (IUI) in Eilat, Eilat, Israel 3 Israel Oceanographic and Limnological Research, National Center for Mariculture, Eilat, Israel 4 Zhejiang Mariculture Research Institute, Wenzhou, China Introduction Integrated multi-trophic aquaculture (IMTA) systems aim at maintaining an economically sustainable farming industry while reducing the adverse impact of intensive aquaculture (freshwater, brackish or marine) on the coastal environment (McVey et al. 2002; Neori et al. 2004; Shpigel 2015). Although varying in geographic location, climatic conditions, species cultured, and social environment throughout the world (Little and Muir 1987; Edwards 1998; Shpigel 2015), the IMTA systems constitute an essential element in coastal zone management wherever industrial aquaculture and ecological responsibility must coexist. Seaweeds selected as biofilter for IMTA systems should have a number of desirable features: high growth rate, simplicity of cultivation, easily controlled life cycle, and resistance to epiphytes and disease-causing organisms (Kang et al. 2007). J Appl Phycol In addition to using seaweeds as biofilter, their integration in a diet, either as feed for macroalgivores (abalone, sea urchins, shrimp, and fish) or as a supplement for human consumption, can increase the overall profitability of IMTA systems (Shpigel and Neori 1996; Neori et al. 2000; Shpigel et al. 2017, 2018; Laramore et al. 2018). Seaweed growth and protein content under mariculture effluents have proved to be superior to growth using fertilizer-enriched, clean seawater (Lewis et al. 1978; Vandermeulen and Gordin 1990; Neori et al. 1991; Shpigel 2015). Mass production of seaweeds has also been proposed as a source of functional food ingredients, pharmaceuticals, and cosmetics (Pimentel et al. 2018; Stiger-Pouvreau and Guerard 2018). Ulva spp. (sea lettuce) are macroalgae of importance for the marine ecology and have been identified as ideal candidates for biofiltering fishpond effluents. In particular, the worldwide distribution of U. lactuca in many ecological settings indicates that this is a suitable species for cultivation globally (del Rio et al. 1996; Neori et al. 2000; Msuya and Neori 2002; Mata et al. 2003). The rapid growth of U. lactuca is attributed to its high photosynthetic activity and uptake rate of nitrogenous nutrients (Neori et al. 1991; Magnusson et al. 1996; Naldi and Wheeler 2002). In Israel, optimal density for cultured U. lactuca was determined to be 1 kg m−2 (Neori et al. 1996). The TAN uptake, yield, and protein content of U. lactuca grown in fishpond effluents were also determined (Vandermeulen and Gordin 1990; Cohen and Neori 1991; Neori et al. 1991; Israel et al. 1995; Neori 1996). Ulva lactuca yield and protein content also depended on the load of ammonia. Ulva lactuca biomass produced in mariculture effluents contained 2–4 times more protein (up to 40% in dry weight) than U. lactuca from the wild (Shpigel et al. 2018). The rate and efficiency of sustained ammonia removal by U. lactuca were related to the rate of ammonia supplied (Cohen and Neori 1991). As the ammonia supply rate increased, at an ammonia load of 5 g m−2d−1, the removal efficiency dropped to 50% (Neori et al. 1991) The composition of nitrogenous compounds in aquaculture water may vary depending on fish stock, feed, feeding regime, culture system, and water-quality management (Mazón et al. 2007; Merino et al. 2007). Fish also excrete metabolic nitrogen as urea (Wright and Land 1998; Kajimura et al. 2002) and ammonia, the latter being their principal nitrogenous waste (Morii et al. 1978). While fish are excreting ammonia as their main catabolic product, fish pond effluents also carry NO 2 , NO 3 (NO x ), and dissolved organic nitrogen (DON) that accumulate via ammonification and/or nitrification in the fish ponds, pipes, and sedimentation ponds (Van Rijn 1996). In some cases, the ratio of ammonia to nitrate in effluent water reaches 1:1 (Shpigel et al. 2013; Ben-Ari et al. 2014). Most studies that dealt with U. lactuca uptake efficiency referred to TAN as the main parameter (Vandermeulen and Gordin 1990; Msuya and Neori 2008) and not nitrate or total dissolv ed nitroge n (TDN) and DON. T homa s a nd Harrison (1987) demonstrated that the presence of ammonia inhibits the nitrate uptake in different macrophytes. Since the uptake of the reduced-state ammonia demands less energy investment than the oxidized-state nitrate, there is a significant preferential balance toward ammonia (Ale et al. 2010). As a consequence, at a high nutrient load with a sufficient ammonia level, there will be no NOx (NO2 + NO3) uptake. Utilization of ammonia and nitrate by seaweed varies among species and the assimilation of these nutrients influences growth. The performance of seaweed as a biofilter drops greatly in all three parameters (N removal, yield, and protein content) if the nitrogen supplied to the seaweed is in the form of nitrate and DON rather than ammonia (Neori 1996). Like most other algae, U. lactuca can readily take up an excess of ammonia (Bluxury uptake,^ converted principally to protein). However, nitrate which must be reduced metabolically before it is assimilated is taken up only in moderation (Neori 1996; Guttman et al. 2018). The nitrate assimilation process occurs in a two-step reaction catalyzed by two sequential enzymes, nitrate and nitrite reductase. The reduction of nitrate to nitrite is the first step in the reduction to ammonia and is catalyzed by an NADH-dependent nitrate reductase (NR), and therefore may be rate-limiting in the nitrate assimilation process. Eppley et al. (1969) have used the presence of nitrate reductase (NR) in marine phytoplankton to determine which form of nitrogen the plankton is utilizing. NR activity typically increases after the exposure of a plant to elevated levels of nitrate (Roth and Pregnall 1988; Touchette and Burkholder 2001), particularly after a period of nitrate depletion (Lopes et al. 1997). Few experiments have been conducted on U. lactuca (Gao et al. 1992; Ale et al. 2010; Guttman et al. 2018) regarding the interaction of ammonia and nitrate uptake. However, these interactions were previously examined in small-scale experiments using artificial chemicals (Ale et al. 2010). Aiming at designing a more efficient and cost-effective extractive biofilter, the dynamics of ammonia and nitrate uptake in U. lactuca grown in the effluents of a land-based IMTA system were studied. In particular, the effects of the presence of dissolved nitrogen (ammonia-N, nitrate-N, and DON) in fish pond effluents on U. lactuca growth, biochemical composition, NR activity, and ammonia and nitrate dynamics were examined. J Appl Phycol Materials and methods Both biotic and abiotic parameters were measured during 24-h observations at 6-h intervals (at 09:00, 15:00, 21:00, and 03:00) throughout the experiments. Water temperature, dissolved oxygen (DO), and pH were determined using portable devices (OxyGuard and Checker-Hanna Instruments). Light intensity was measured once a day at 15:00 at three depths of the tanks using HOBO Pendant coupler light meter (bottom, 30 cm and 10 cm below surface). Growth rate, yield, biochemical composition, and C/N ratio of U. lactuca were measured at the beginning and at the end of the experiment. Growth rates and yields of U. lactuca were measured following the procedures outlined by Neori et al. (1991). Samples for dry weight determination were oven dried (60 °C, 48–72 h) to constant weight. The specific growth rate (SGR) was calculated as SGR = 100 × [ln (WT/W0)]/t, where W0 = initial biomass, WT = final biomass, and t expresses the days of culture in the experimental set. The yield was calculated as the difference between initial and final weights and expressed in units of g m−2 day−1. For the total ammonia nitrogen (TAN), nitrite and nitrate (NOx–N) measurements, samples were collected in 500 mL acid-rinsed plastic jars and filtered (for NOx–N only, GF/C Whatman). Nutrient concentration analyses were made in duplicate with a SAN++ Automated Wet Chemistry Analyzer - Continuous Flow Analyzer (CFA). Biochemical composition (protein, carbohydrate, and lipid levels) of U. lactuca was measured using the Kjeldahl method and multiplying the N by 5.65 (Shuuluka et al. 2013). The lipid content was measured according to Folch et al. (1957) extraction method. Carbohydrate was measured using the Bphenol-sulfuric acid method^ (Dubois et al. 1956). Ash was calculated from the weight loss after incineration for 24 h at 550 °C in a muffle furnace. Phosphorus was measured by ashing samples and applying the vanado– molybdate method (AOAC 1980). N and P incorporated into seaweed biomass were calculated according to these results. C/N ratio in U. lactuca tissue was measured by CHN analyzer. Samples for C/N analyses (Perkin-Elmer Model 240) were rinsed with deionized water, dried and ground to a fine powder with a mortar and pestle. To evaluate the correlation between nitrate depletion and NR dynamic, NR was measured from the Ulva thalli once a day for the first 48 h and then once every 12 h (at 10:00 and 22:00) to the end of the experiment. Algal thalli were collected from two tanks (one from each density, three replicates for each tank), placed in ambient water, and analyzed immediately upon collection. Samples of 0.25 g of fresh tissue were cut into pieces and introduced into aluminum foil–covered test tubes with 5 mL of the assay medium containing 0.1 M Table 1 Dissolved nitrogen and phosphate composition (μmole average ± SD) of the fishpond effluents entering twelve experimental tanks (600 L) in the first and the second phases. DON levels were calculated by subtracting NH 4 + NO3 + NO2 levels from the total dissolved nitrogen levels (TDN). Initial effluent levels in phases I (29 Oct 2012) and II (2 Nov 2012) The work was carried out for a total of 120 h from October 29 to November 2, 2012, at the National Center for Mariculture (NCM) in Eilat, Israel. Two consecutive experimental phases were implemented, the first lasting 96 h and the second one 24 h. Twelve rectangular tanks (800 L; 1 m2 surface area and 80 cm depth) were used. The algae were grown unattached and kept suspended in the water column by air diffusers situated at the bottom of each tank (Neori et al. 1991). At the beginning of the first experimental phase, fishpond effluents from an integrated multi-trophic aquaculture (IMTA) system (described in Shpigel et al. 2017, 2018) were pumped into the tanks and kept as a batch flow regime for 96 h, during which nutrient concentration in the tank decreased with time. The second phase was then initiated, consisting of a 24-h flow-through regime (92 ± 7.5 L h−1). Biochemical composition of the inlet dissolved nutrients is summarized in Table 1. Three tanks were stocked with 1 kg m−2 (optimal stocking density according to Cohen and Neori 1991), 2 and 3 kg m−2 wet weight (WW) U. lactuca, respectively. Three tanks without U. lactuca were used as control. The following parameters were recorded: 1. Abiotic parameters (temperatures, pH, dissolved oxygen, salinity, and light intensity) (light intensity was measured only for the 1 and 3 kg densities). 2. Growth rate, yield, biochemical composition, nutrient assimilation rates, C/N ratio, and NR activity of U. lactuca (NR ratio was measured only for the 2 kg m−2 density, and C/N ratio was measured only for 1 and 3 kg m −2 densities). 3. Ammonia, nitrate, and nitrite dynamics of the effluents. 29/10/12 2/11/12 Ammonia (NH4–N) Nitrate (NO3–N) Nitrite (NO2–N) Phosphate (PO4) DON 124.03 ± 4.46 65.67 ± 2.21 18.43 ± 0.43 5.55 ± 0.07 4.69 ± 0.32 19.43 ± 0.24 2.40 ± 0.09 0.82 ± 0.18 147 ± 3.4 74 ± 2.4 J Appl Phycol KNO3 and 3% isopropanol in 50 μM potassium phosphate buffer (pH 7.5). For the sake of reproducibility, the thalli were cut into smaller pieces so as to increase the homogeneity of the assay medium during incubation (Corzo and Niell 1991). A modified assay for in vivo NR assay was performed at 30 °C incubation using Lartigue and Sherman (2002) method. To quantify the amount of nitrate that was reduced to nitrite per biomass of alga over time, nitrite concentration of the incubation medium was measured calorimetrically before and after 60 min of incubation. Absorbance was measured by reading optical density at 540 nm on a Synergy HT-fluorescence plate reader (Bio Tek Power wave XS). Absorbance readings were calibrated against a nitrite standard curve. Final data are presented as μM NO2 g−1 dry Ulva h−1. Statistical analysis Data were analyzed using the JMP IN 8 statistical software (SAS Institute Inc., Cary, NC). One-way ANOVA was employed to compare the mean values (α = 0.05). Results Ulva lactuca growth Average yields (WW) at the end of the experiment were 259 ± 18, 138 ± 11, and 134 ± 4 g m−2 day−1 for 1, 2, and 3 kg m−2 stocking densities, respectively (Fig. 1a). SGRs were 18 ± 2.1, 6 ± 1.3, and 4 ± 1.3% day−1 for the 1, 2, and Protein levels were 24.90 ± 1.50, 33.86 ± 2.60, and 41.1 ± 1.91% dry weight (DW) for the 1, 2, and 3 kg m−2 stocking densities, respectively (Table 2). Significant differences (p < 0.01) in biochemical composition were found among the stocking densities. A significant difference (p < 0.05) was found in carbohydrate levels between the 1 kg m−2 and the 2 and 3 kg m−2 stocking densities. No significant differences (p > 0.05) were found among the stocking densities in lipids, phosphate, and ash levels. C/N ratios were 8.72 ± 2.10 and 14.5 ± 6.0 in the 1 and 3 kg m−2 density, respectively. 25 Growth rate [% d-1] Yield [g m-2 d -1] Biochemical composition a 300 250 200 150 100 50 b 20 15 10 5 0 0 1 kg 2 kg 1 kg 3 kg 1.0 c N uptake [mg N g-1 WW d-1] 1.2 N uptake (g N m2 d-1) Fig. 1 Yield (a), growth rate (b), nitrogen uptake m−2 day−1 (c), and nitrogen (d) uptake g−1 WW of U. lactuca in 1, 2, and 3 kg m−2 stocking densities (N = 3) 3 kg m2 stocking densities, respectively (Fig. 1b). Average yield and SGR were significantly (p < 0.01) higher in the 1 kg m−2 than in the 2 and 3 kg m−2 stocking densities. Final dry weight (DW) yields were 25.1 ± 1.23, 15.8 ± 46, and 13.4 ± 1.23 g for 1, 2, and 3 kg m−2 stocking densities, respectively. Total nitrogen assimilation per tank was 0.99 ± 0.11, 0.854 ± 0.09, and 0.818 ± 0.05 g N m−2 day−1 for the 1, 2, and 3 kg m2 stocking densities, respectively (Fig. 1c). No significant difference was found among the treatments. When normalizing nitrogen assimilation to Ulva yield (g WW), nitrogen assimilations were 0.19 ± 0.06, 0.24 ± 0.02, and 0.65 ± 0.19 mg N g−1 WW Ulva day−1 for 1, 2, and 3 kg m−2 stocking densities, respectively (Fig. 1d). Nitrogen assimilation per g WW was significantly (p < 0.01) higher in the 3 kg m−2 than in the 1 and 2 kg m−2 stocking densities. 1 0.8 0.6 0.4 0.2 0 1 kg 2 kg 3 kg 2 kg 3 kg d 0.8 0.6 0.4 0.2 0.0 1 kg 2 kg 3 kg J Appl Phycol Table 2 Biochemical composition: protein, lipids, carbohydrate (Bcarbo.^), phosphate, ash (% DW), and C/N ratio of Ulva lactuca exposed to three stocking densities at the end of the experiment (average ± DS; three replicates; n = 6). (Initial values: protein 40%, lipids 3.5%, carbo. 28.28%, phosphate 0.22%, and ash 28%) Treatment Protein Lipid Carbo. Phosphate Ash C/N ratio 1 kg m−2 24.90 ± 1.5 33.86 ± 2.6 41.1 ± 1.91 3.61 ± 0.3 3.68 ± 0.4 3.39 ± 0.5 43.99 ± 12.4 34.26 ± 18.3 35.35 ± 13.7 0.18 ± 0.01 0.19 ± 0.02 0.21 ± 0.01 27.32 ± 9.1 28.01 ± 2.4 23.55 ± 6.1 14.50 ± 6.0 ND 8.72 ± 2.10 the 3 kg m−2 density, ammonia-N level increased in the first peak from 40.76 at 16:30 to 79.08 μmole at 02:30, from 26.64 to 47.74 μmole in the second peak and 13.11 to 26.57 μmole in the third peak (Fig. 2a). Dissolved nitrogen dynamics Ammonia Most of the ammonia was promptly removed from the water in all the stocking densities after 12 h at the same uptake rate (10.1 μg N h−1 m−2) (Fig. 2a). In 1 kg m−2 density, ammoniaN levels decreased sharply from 124.03 ± 4.69 to 3.48 ± 2.1 μmole within 28 h, with an average decrease rate of 4.31 μmole N h−1. In the 2 kg m−2 density, ammonia-N levels decreased to 3.23 in 48 h, with an average decrease rate of 2.51 μmole N h−1. In the 3 m−2 density, ammonia-N levels decreased to 2.67 in 80 h, with an average decrease rate of 1.51 μmole N h−1 (Table 3, Fig. 2a). DON levels decreased to 24 ± 5.45, 21 ± 4.54, and 2.5 ± 1.24 μmole for the 1, 2, and 3 kg m−2 densities, respectively (Table 3). At night, ammonia-N levels increased to a peak at 2:30 in all the densities. There were one, two, and three times peaks for 1, 2, and 3 kg m−2, respectively. In the 1 kg m−2 density, ammonia-N level increased from 19.98 at 16:30 to 29.72 μmole at 02:30. In the 2 kg m−2 density, ammonia-N level increased from 24.65 at 16:30 to 48.35 μmole at 02:30 in the first peak and 8.52 to 15.84 μmole in the second peak. In In the 1 kg m−2 density, nitrate-N levels remained stable for 36 h and then decreased sharply from 24.35 to 0 μmole within 10 h, with a decrease rate of 2.43 μmole N h−1. In the 2 kg m−2 density, nitrate levels remained stable for 84 h and then decreased sharply from 24.5 to 0 μmole within 10 h, with a decrease rate of 2.45 μmole N h−1. In the 3 kg m −2 density, nitrate-N levels remained stable for 96 h (Fig. 2b). In the second phase, both ammonia and nitrate-N levels in the 1 and 2 kg m−2 densities decreased to almost zero within 12 h. Nitrate remained stable in the 3 kg m−2 density (Fig. 2a, b). In the 2 kg m−2 density, nitrate-N reductase activity started after 60 h (from 0 to 28 μmole L−1) following ammonia dropping to zero. NO3 levels dropped sharply after NR appeared (Fig. 3). 140 120 100 80 60 40 20 0 1 Kg 2 kg 28/10/12 30/10/12 12:30 8:30 2:30 22:30 16:30 12:30 8:30 2:30 22:30 12:30 16:30 8:30 2:30 22:30 12:30 29/10/12 31/10/12 1/11/12 30 25 20 15 10 5 28/10/12 29/10/12 30/10/12 31/10/12 1/11/12 inlet 22:30 2:30 8:30 12:30 0 8:30 8:30 12:30 16:30 22:30 2:30 8:30 12:30 16:30 22:30 2:30 8:30 12:30 16:30 22:30 2:30 8:30 12:30 16:30 b 8:30 3 kg 8:30 NH4-N (µmole L-1) a NO3-N (µmole L-1) Fig. 2 Ammonia-N (a) and nitrate-N (b) uptake of U. lactuca in 1, 2, and 3 kg m−2 stocking densities throughout 96 h (N = 3) Nitrate 16:30 2 kg m−2 3 kg m−2 2/11/12 J Appl Phycol Table 3 Biochemical composition (μmole average ± SD) of the final fishpond effluents (2/11/12) in phase 1. Final effluent levels in phase I (1/11/12) 1 kg−2 2 kg−2 3 kg−2 Ammonia (NH4–N) Nitrate (NO3–N) Nitrite (NO2–N) Phosphate (PO4) DON 2.48 ± 2.3 2.23 ± 1.2 2.67 ± 2.1 0 0 12.20 ± 6.54 0 0 14.89 ± 7.66 0 0 0 24 ± 5.45 21 ± 4.54 2.5 ± 1.24 Abiotic parameters Ulva lactuca growth performance No differences were observed in the abiotic parameters among the stocking densities (Table 4). Light level was depth dependent. In the control, light levels decreased from 1585.4 μmol photons m−2 s−1in 10 cm depth (surface) to 733.4 μmol photons m−2 s−1at 80 cm depth. In the 1 and 3 kg m−2 stocking densities, light levels decreased from 729 and 680 μmol photons m−2 s−1 to 44 and 13.5 μmol photons m−2 s−1 in the 1 and 3 kg m−2 densities, respectively (Fig. 4). Growth rate and yield of Ulva spp. depend on nutrient flux and composition, light regime (e.g., season), climate, and culture management such as standing stock and flow regime (Troell et al. 2003; Neori et al. 2004). Ulva sp. performance in various studies is summarized in Table 5. In these studies, which are based on flow-through regimes in which nutrients flow continuously to the algae, yields ranged between 11 and 55 g DW day−1. Our yields, 13–25 g DW day−1, were in the lower range of the published data mainly because our system was based on a batch flow regime and was carried out in the fall (October–November) with relatively short daylight (~ 10 h). The yield for 1 kg m−2 day−1 was ~ 25 g m−2 day−1 (DW). In the same facility during the summer (June–August, 13-h daylight), daily yield was ~ 35 g m−2 day−1 in a flowthrough regime (Shpigel et al. 2017). As in Cohen and Neori (1991), the optimal SGR for U. lactuca was measured at stocking density of 1 kg m−2 and decreased as stocking densities increased. The reduction in growth rate of U. lactuca at higher stocking densities has also been recorded by Lapointe and Tenore (1981), Vandermeulen and Gordin (1990), and Neori et al. (1991). Because U. lactuca thalli were vertically agitated by aeration in the tanks, it is assumed that light limitation did not reduce growth at higher densities. In addition, Henley and Ramus (1989) reported Ulva spp. to be capable of photoacclimation when exposed to lower light levels and of maintaining growth rates even if total daily irradiance is reduced slightly (by a factor such as self-shading at high densities). Control In the control tanks, only 2–4% of the TDN was lost during the experiment. Discussion Nitrogenous compounds such as ammonia, nitrate, and DON are the main waste components of marine fish pond effluents and are regarded as the main nitrogen sources for seaweed (Dortch 1990; Cochlan et al. 1991). To design an efficient biofilter, we considered it essential to maximize total dissolved nitrogen (TDN) removal rather than that of each component. A better understanding of the dynamics of each component would give the tools to maximize TDN removal, thus increasing biomass production. 2 kg m- 60 NO3 NR- NO2 50 NH4 40 30 20 28/10/12 29/10/12 30/10/12 31/10/12 1/11/12 2/11/12 16:30 8:30 12:30 2:30 inlet 22:30 16:30 8:30 12:30 2:30 22:30 16:30 8:30 12:30 2:30 22:30 16:30 8:30 12:30 2:30 22:30 16:30 0 8:30 10 12:30 Nutrients levels (µmole L-1) NR levels (µmole g-1) Fig. 3 Ammonia-N, nitrate-N, and nitrate reductase (NR) dynamics of 2 kg m−2 stocking density throughout 96 h (N = 3) J Appl Phycol Table 4 Temperature, oxygen, and pH profiles throughout phase I 1 kg m−2 2 kg m−2 3 kg m−2 AVG STD AVG STD AVG STD 08:30 12:30 16:30 22:30 02:30 08:30 12:30 16:30 22:30 02:30 08:30 12:30 16:30 22:30 02:30 08:30 12:30 16:30 22:30 02:30 08:30 12:30 16:30 21.0 23.0 23.2 22.0 21.0 20.7 23.4 23.8 22.6 21.6 21.4 23.9 23.0 22.5 21.9 21.5 24.2 24.3 23.5 22.1 21.6 24.5 26.0 0.12 0.05 0.08 0.09 0.12 0.12 0.00 0.00 0.05 0.08 0.37 0.00 0.05 0.05 0.05 0.31 0.05 0.54 0.00 0.08 0.00 0.00 0.25 20.9 23.0 23.2 21.9 21.0 20.7 23.4 23.8 22.6 21.7 21.1 23.8 23.1 22.6 21.9 21.5 24.2 24.4 23.5 22.0 21.6 24.5 26.1 0.16 0.05 0.14 0.05 0.12 0.08 0.08 0.05 0.08 0.12 0.29 0.09 0.09 0.05 0.00 0.17 0.08 0.33 0.05 0.05 0.09 0.00 0.43 20.9 23.0 23.2 21.9 20.9 20.6 23.4 23.8 22.6 21.7 21.0 23.8 23.1 22.6 21.9 21.3 24.2 24.7 23.6 22.1 21.5 24.3 26.2 0.16 0.05 0.12 0.05 0.12 0.09 0.05 0.05 0.05 0.12 0.21 0.09 0.09 0.05 0.05 0.16 0.09 0.45 0.08 0.08 0.08 0.22 0.63 08:30 12:30 16:30 22:30 02:30 08:30 12:30 16:30 22:30 02:30 08:30 12:30 16:30 22:30 02:30 08:30 12:30 16:30 22:30 02:30 08:30 12:30 16:30 107 106 101 99 98 104 104 97 98 100 108 106 102 100 102 108 106 100 101 101 106 111 103 1.2 0.8 2.1 0.5 0.5 0.8 1.2 0.0 0.8 0.5 2.4 1.2 0.9 0.5 0.5 2.6 0.8 1.9 0.5 0.5 2.1 0.5 0.9 106 106 100 99 99 103 103 97 97 100 110 106 102 100 100 109 105 99 101 101 107 113 102 2.1 0.8 0.8 0.5 0.5 2.4 1.2 0.0 0.9 0.5 1.2 0.5 1.4 0.0 0.9 0.8 0.9 0.8 0.5 0.5 1.4 2.1 0.0 105 106 100 99 99 103 103 98 98 100 111 106 101 100 101 109 106 99 102 101 107 111 102 2.1 0.5 0.0 0.8 0.5 1.4 0.8 0.8 0.5 0.5 1.2 0.5 0.0 0.0 0.0 0.5 0.5 1.4 0.5 0.5 1.4 0.8 0.5 08:30 12:30 16:30 22:30 02:30 08:30 12:30 16:30 22:30 02:30 08:30 12:30 16:30 22:30 8.38 8.96 9.06 8.44 8.37 8.41 9.03 9.13 8.57 8.38 8.27 8.86 8.96 8.54 0.01 0.02 0.07 0.09 0.07 0.02 0.02 0.06 0.10 3.95 0.05 0.07 0.10 0.10 8.37 9.05 9.20 8.43 8.43 8.43 9.08 9.20 8.61 8.41 8.38 9.04 9.18 8.65 0.01 0.01 0.01 0.05 0.05 0.01 0.01 0.04 0.06 3.96 0.03 0.01 0.05 0.08 8.36 9.05 9.16 8.39 8.39 8.41 9.07 9.15 8.56 8.36 8.35 9.02 9.09 8.54 0.00 0.00 0.02 0.04 0.04 0.02 0.01 0.03 0.05 3.94 0.02 0.01 0.04 0.07 Date Temp. (°C) 29/10/2012 30/10/2012 31/10/2012 1/11/2012 2/11/2012 Oxygen (%) 29/10/2012 30/10/2012 31/10/2012 1/11/2012 2/11/2012 pH 29/10/2012 30/10/2012 31/10/2012 Table 4 (continued) Date 1/11/2012 2/11/2012 02:30 08:30 12:30 16:30 22:30 02:30 08:30 12:30 16:30 1 kg m−2 2 kg m−2 3 kg m−2 AVG STD AVG STD AVG STD 8.40 8.39 9.00 9.12 8.19 8.25 8.36 8.91 9.06 0.08 0.04 0.03 0.08 0.03 0.02 0.01 0.02 0.06 8.44 8.37 9.07 9.26 8.19 8.22 8.36 9.06 9.54 0.07 0.05 0.04 0.09 0.01 0.03 0.03 0.02 0.32 8.34 8.35 9.04 9.16 8.18 8.24 8.38 9.04 9.26 0.04 0.03 0.02 0.06 0.02 0.02 0.00 0.03 0.09 Since Ulva spp. utilize bicarbonate as their primary carbon source (Beer and Eshel 1983), the reduction in yield and SGR may be the result of carbon limitation (Cohen and Neori 1991; Zou 2014). Indeed, the doubled C/N ratio in U. lactuca tissue when cultured at 1 kg m−2 compared with 3 kg m−2 and pH elevation in higher densities may indicate carbon limitation at high stocking densities in our system. Nitrogen assimilation Nitrogen assimilation rate and protein content in U. lactuca biomass appeared to be density dependent. Nitrogen uptake rate per g biomass was higher in 3 kg m−2 stocking densities. This may explain the significantly higher protein level of U. lactuca (~ 41.1% DW) in the 3 kg m−2 density compared with the relatively low protein level (~ 24.9% DW) in the 1 kg m−2 density. Similar results were obtained by Cohen and Neori (1991) and Gao et al. (1992) in which increased stocking density could lead to a carbon-limited system and increased N content of Ulva tissue up to 5.5% of DW. Apparently, nitrogen uptake rate by U. lactuca from the water is not influenced by either carbon availability or light limitation. At low levels of bicarbonate, nitrogen continued to be assimilated into U. lactuca tissue at a lower assimilation rate. Protein levels (24–41% DW) of U. lactuca in our system are higher than in the thalli collected from the wild, which range between 8.0 and 16.0% (Diler et al. 2007; Güroy et al. 2007, 2011). Our results were similar to those observed in U. lactuca cultured as biofilter in IMTA systems, which contained over 30–35% protein (DW) and was shown to be a highly suitable food for abalone, sea urchins, and fish (Shpigel et al. 1998, 2000, 2017, 2018). Nitrogen dynamics Ulva lactuca strongly Bpreferred^ ammonia-N over other oxidized-N forms. Nitrite and nitrate were taken up by the seaweed when ammonia-N concentrations were relatively low (Admiraal et al. 1987; Flynn and Fasham 1997; Flynn J Appl Phycol Fig. 4 Daylight penetration levels in 1 and 3 kg m−2 stocking densities in the experimental tank (800 L; 1 m2 surface area and 80 cm depth) on the surface, at 40 cm depth and on the bottom. The control tanks are without algae Light level (μmol photons m-2 s-1) 30 25 20 15 10 5 Surface Halfway 0 Control 1999). A similar DIN uptake pattern was found in our experiments. Ammonia uptake rate in our system was density dependent. At the lowest stocking density, 1 kg m−2, ammonia uptake was relatively rapid and nitrate uptake started 24 h after ammonia depletion, suggesting this period to be the time required for NR synthesis in the algae tissue. At 2 kg m−2, nitrate uptake started 24 h after that observed in 1 kg m−2. Contrary to 1 and 2 kg m−2 stocking densities, no uptake of nitrate appeared to have taken place in the 3 kg m−2 stocking density, probably due to the presence of ammonia in the water. It seems that the lower ammonia threshold for U. lactuca is Table 5 Bottom 3 kg 1 kg around 1.4 μmole L−1 (Table 1). Although both the first and second phase of the experiment had a similar effluent composition, a sharp decrease of both ammonia and nitrate was measured simultaneously in the 1 and 2 kg m−2 stocking densities. It is hypothesized this to be due to the fact that NR was still active in the seaweed tissue. However, when both N forms were present in the effluents, ammonia uptake was more rapid than that of nitrate. When we compare the amount of nitrogen introduced to the algae by biomass yield to the amount of available DIN in the water, we can see a significant deficit of nitrogen (Table 6). It seems that DON, which appeared in Cultivation conditions, biomass yields, biofiltering efficiency, and nitrogen removal of Ulva spp. cultivated in experimental systems Species Tank volume (L) Stocking density (kg WW m−2) Water exchange (vol. day−1) Growth rate (g DW m−2 day−1) U. lactuca U. rigida 800 110 1–3 1.9 0 2.4–96 U. rigida 1900 1.9 U. lactuca U. reticulata 600 40 U. rigida U. lactuca TAN removal (g m−2 day−1) TIN removal (g m−2 day−1) References 25–13 44–73 2.7–5.1 1.1–1.6 2.7–3.6 This study Mata et al. 2010 14.4 48 1.3 1.45 Mata et al. 2003 1 1 34 2040* 11–38 46 0.4–7.4 1.9–6.5 ND ND Msuya and Neori 2008 Msuya et al. 2006 750 600 2.5 2–6 2–12 4–16 40 55 1.2–5.6 1.7 ND del Rio et al. 1996 Neori et al. 1991 U. lactuca 600 1 4–8 55 – ND Vandermeulen and Gordin 1990 U. lactuca 1700 1 1–24 45–16 ND DeBusk et al. 1981 U. lactuca 600 1–8 12 12.32 – ND Bruhn et al. 2011 U. lactuca 600 1.5 2 21.3 – 1.72 Neori et al. 2000 U. lactuca 6900–1700 1 14–56 19 2.9 ND Neori et al. 2003 *High volume of water movement were used instead of bottom aeration J Appl Phycol Table 6 Nitrogen balance: nitrogen mass (g) assimilated as yield to U. lactuca tissue exposed to three stocking densities throughout the experiment vs. the DIN-N and DON-N supplied by the effluents Stocking density (kg m−2) Average yield (DW g) Protein levels (%) N content (g) TDN-N assimilated (g) DON-N assimilated (g) N budget (g) 1 100.4 24.9 4.42 1.62 1.39 − 1.41 2 63.2 33.8 3.78 1.62 1.41 − 0.75 3 53.6 41.1 3.89 1.61 1.61 − 0.67 high concentration in the effluent water, is the only source of nitrogen to fill this gap. Bacterial transformations of DON represent an important DON flux in marine systems (Berman and Bronk 2003). It is suggested that ammonifying bacteria (described by Burke et al. 2011) on the surface area of U. lactuca thallus are responsible for the conversion of the DON to ammonia. The latter assumption is also based on previous studies showing seaweed-associated bacteria to play a crucial role in morphogenesis and growth of seaweeds in direct and/or indirect ways (Singh and Reddy 2014). Dvir et al. (1999) revealed ammonification in a seaweed biofilter for mariculture effluent to enhance nitrification processes in organic particles attached to the biofilter walls rather than on the seaweed surface. By studying the holobiont of Ulva australis following the core functional genes of its associated bacterial community, Burke et al. (2011) revealed high similarity of 70% in the bacterial functional composition between different samples of the seaweed, while nitrate and nitrite ammonification-related genes within this functional core appeared to be 0.3% of the total assigned reads. A bacterial ammonification in the fish effluents which rapidly converted DON to ammonia-N was reported by Krom and Neori (1989) and Krom et al. (1995). Similar to these reports, our fishponds effluent contained approximately 40–50% DON. Details of these rapid transformations involving DON, which is often unusable by algae (Flynn and Butler 1986), are not well studied although they may be significant in the total nitrogen budget. Most of the ammonia was promptly removed from the water in all stocking densities after 12 h at the same uptake rate (10.1 μg N h−1 m−2). After 12 h, ammonia levels gradually decreased to almost zero after 12, 36, and 68 h at 1, 2, and 3 kg m−2 stocking densities, respectively. Ammonia removal period was influenced by the additional input of ammonia by DON into the water. The reduction of nitrogen uptake rates after the first 12 h is hypothesized to be due to carbon limitation. The enhancement of ammonia level in the water by DON-ammonifying bacteria is assumed to depend on the total surface area of U. lactuca thalli in the tanks; as in the 1 kg m−2 stocking densities, the addition of ammonia was relatively low compared with that in the 3 kg m−2 density. This would explain the differences in the final protein levels among the three densities. Two processes occurred simultaneously in our tanks: ammonia uptake by photosynthesis activity that occurred mainly during the day and ammonification processes by bacteria which increase ammonia levels throughout the day and night. These two processes can explain the ammonia increases that built up from the evening to the morning with a peak at 02:30 when no ammonia uptake took place (Fig. 3a). Suggestions for future biofilters Nitrate and DON constitute around 50% of the dissolved nitrogen in fishpond effluents. Therefore, not treating them increases the wasted resources that may further act as water pollutants since this component is not available for the seaweed in the presence of ammonia. Following our results, for an efficient fishpond biofilter, multiple U. lactuca bioreactors are recommended. The first seaweed bioreactor would be stocked with non-acclimated U. lactuca (1 kg m−2). The dimension, flow rate, and aeration regime of the tank (Ben Ari et al., 2014) should be calculated and designed to assimilate around 100% of the ammonia. Season and light conditions should be taken into consideration. The second bioreactor could be stocked with starved U. lactuca at higher stocking density (3 kg m−2) in order to remove excess nitrate and DON. The dimension, flow rate, and aeration regime of the tank should be calculated and designed to assimilate around 100% of the nitrate and the DON. In this scenario, the first tank is expected to produce high U. lactuca biomass with relatively fast growth rate, and the second tank is expected to produce high-protein U. lactuca. By manipulating factors such as stocking density or flow rate (Ben Ari et al., 2014), we were able to develop systems with variable nutrient removal efficiencies and produce crops of Ulva with variable nitrogen content. The addition of an algal component to intensive fishponds allows for a more integrated, flexible approach to the management of these complex mariculture systems. Acknowledgments We thank Dr. Angelo Colorni for his critical suggestions and Ms. Mikhal Ben-Shaprut for her editorial assistance. We are grateful to Ms. Ala Zalmanson for her invaluable technical assistance. 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