INFLUENCE OF DEPTH ON THE GROWTH OF THE SEAWEED GRACILARIA BIRDIAE ( RHODOPHYTA ) IN A SHRIMP

Oliveira, V. P.; Freire, F. A. M. & Soriano, E. M. 2012. Influence of depth on the growth of the seaweed Gracilaria birdiae (Rhodophyta) in a shrimp pond. Braz. J. Aquat. Sci. Technol. 16(X): 33-39. eISSN 1983-9057. This study evaluates the influence of depth and environmental parameters on the development of Gracilaria birdiae Plastino & Oliveira (Gracilariaceae) in an organic shrimp pond. The macroalgae was cultivated on modules placed at three depths (surface, 10 and 20 cm depth). Growth rates were measured weekly based on variation in fresh weight during 35 days. G. birdie showed the greatest productivity (35.7%) at 10 cm, followed by 20 cm (33.4%) and surface (25.3%). Average SGR values were 0.36±0.57% d-1(surface) 0.38±0.96% d-1 (10 cm) and 0.38 ±0.54% d-1(20 cm), over the study period. The biomass variation of G. birdiae showed significant difference among the three depths. The correlations generated by multiple regressions demonstrated that analyzed environmental parameters explain from 62 to 67 % of G. birdiae growth.


INTRODUCTION
In recent years intensive aquaculture has increased significantly worldwide (Naylor et al., 2000).In Brazil, the most advanced area of aquaculture is shrimp farming, which is considered one of the most economically important activities in the Northeast of Brazil (Nunes et al., 1997).Despite this promising picture, the expansion of aquaculture has been associated with the eutrophication of coastal ecosystems.This process can lead to enhanced sediment metabolism, anoxia, and others environmental variations that can also affect the benthic fauna and flora (Angel et al., 2000;Neori et al., 2007).These are direct consequence of the accumulation of organic material from the wastewater of aquatic organism cultivation system.
Recently, world shrimp farming has been searching for new methods to achieve sustainability and minimize the impact of eutrophication (Chopin et al., 2001).Aquaculture with seaweeds has been suggested as a viable solution for the problems caused by excessive waste in coastal areas.Seaweeds turn the available nutrients (N and P) into composites necessary for their development, improving water quality for cultivated animals and reducing nutrient concentration in the environment (Troell et al., 2003).
Seaweeds belonging to the genus Gracilaria Greville (Rhodophyta) are the most promising in integrated farming.This is because of their ability to achieve high biomass, significant commercial value of their derivatives and substantial potential as nutrient bioremediation agents (Msuya & Neori, 2002;Tyler & McGlathery, 2006;Marinho-Soriano et al., 2009).Despite the experience obtained in different studies, the cultivation of Gracilaria in integrated systems is still difficult in theory and practice (Marinho-Soriano et al., 2002;Buschmann et al., 2008).Limitations in acclimation, nutrient absorption, photosynthesis and various abiotic factors leave gaps in our understanding of this group (Friedlander & Levy, 1995).This limited information prevents an effective understanding of these algae in eutrophicated environments and "in situ" studies are necessary to clarify the physiological response of the algae to environmental parameters.
Successful seaweed cultivation in shrimp ponds is mainly related to the concentration of nutrients, type of cultivation and water flow (Buschmann et al., 2001).However, little is known on the effect of depth on the development and productivity of macroalgae in this environment.Previous studies indicate that seaweeds show different ecophysiological characteristics in response to depth changes during growth (Molloy & Bolton, 1996;Xu & Gao, 2008).Therefore, to explore this relationship and optimize cultivation conditions of G. birdiae, we investigated its growth at three depths.

MATERIAL AND METHODS
The study was carried out at an organic shrimp farm (PRIMAR) in the Northeast of Brazil (06° 18' S, 035° 09' W) in September and October 2006 (35 days).
The total surface area in the farm ponds is 7.1 ha and their mean depth is 60 cm.No animal feed, antibiotics, aerators or water circulation equipment were used.
The seaweeds were cultivated on modules comprising a square frame of PVC pipes of 1.0 m² and polypropylene ropes (5 mm diameter).Each module contained four ropes in which ten G. birdiae seedlings (15 g) were inserted every 10 cm, totaling 150 g of seaweed per rope.The modules were placed horizontally at three different depths (surface, 10 cm and 20 cm) into shrimp pond.These depths were selected based on turbidity values observed in the ponds water.Every week, the seaweeds were removed of the ropes in order to determine their biomass and growth rate.Daily growth rate was calculated using the following formula: SGR = (100 ln (Wt/ W0)) t-1, where SGR = specific growth rate (% d-1); W0 = initial wet weight; Wt = wet weight at time t (7 days) based on Lobban & Harrinson (1994).
Water salinity, temperature, pH and turbidity were measured weekly with Horiba U-10 water quality checker (CA, USA).Transparency was determined weekly with a Secchi disk and daily meteorological information on rainfall, evaporation, solar radiation and insolation were supplied by the Universidade Federal do Rio Grande do Norte meteorological station, and presented as week average.The nutrients (NH 4 , NO 3 , NO 2 and PO 4 ) were sampled weekly (around the noon) and measured (in triplicate) by colorimetric analysis (FEMTO® 600S) according to Strickland & Parsons (1972).All water samples were filtered (GF/F WHATMAN™), kept in a cool box (≈10°C) and analyzed after 4 hours.
Growth and abiotic data were first tested for normality (Kolmogorov-Smirnov test) and homocedasticity (Levene test), as suggested by Zar (1999).The Friedman test was used to determine significant differences between biomass values under different experimental depth.The Kruskal-Wallis analyses were performed to test significant differences (p<0.05)comparing the temporal variation of environmental data.
Multiple regression analysis (backward stepwise) were carried out to establish correlations between the SGR and environmental variables at each depth.Linear correlations between observed and predicted values were fitted from the not explained variance by the models to express the best prediction of the SGR variable.As the requirements, equations with p<0.05 and normal residuals distribution were accepted.All analyses were performed using the software Statistica 7.0 (StatSoft®).

Environmental Parameters
The results on water quality and meteorological data are shown in Table 1.During cultivation the pond showed little variation in temperature (26.7 ºC to 28.5 °C), a mean salinity of 31.2 ± 2.0 and slightly alkaline mean pH (8.1 ± 0.3).Transparency did not exceed 33 cm and maximum turbidity was registered at the end of the experiment (116 NTU).The dissolved nutrient content of the water was high throughout the study.Ammonium (NH 4 ) showed the highest concentrations, ranging from 1.68 to 15.15 µmol L -1 ; nitrite (NO 2 ) ranged from 0.39 to 0.68 µmol L -1 ; nitrate (NO 3 ) between 0.14 and 1.03 µmol L -1 and orthophosphate (PO 4 ) ranged from 0.13 to 3.22 µmol L -1 .In general, the physical and chemical parameters values increased with the development of shrimp at the pound.The mean daily scores of the climatological variables precipitation (0.97 ± 2.17 mm), evaporation (6.17 ± 0.93 mm), insolation (9.6 ± 0.7 hr d -1 ) and the accumulated solar radiation (2.84 ±1.02 MJ m -2 ) emphasize the tropical nature of the area, characterized by abundant and uniform sunlight (Table 1).

Biomass and Growth Rate
The biomass and growth of G. birdiae were significantly affected by the abiotic parameters inherent to the depth variation.The lowest biomass increase was obtained at the surface, increasing by 25.3% during the cultivation period.In this depth the lowest biomass recorded in each rope was 150 g (1 st week) and the highest 222 g (5 th week), with a mean value of 173.9 ± 14.6 g.
The seaweeds grown at 10 cm depth showed the highest biomass among those tested, increasing by 35.7% when compared to the initial inoculum.Its minimum biomass value in each rope was 171 g (1 st week) and maximum 227 g (5 th week) with a mean value of 193.6 ± 18.2 g during the study period.
Biomass increased by 33.4% at 20 cm.The lowest biomass value for seaweeds cultivated at this depth was 157 g (4 th week) and the highest was 208 g (1 st week), with a mean value of 186.5 ± 17.2 g.Comparisons between cultivation depths show significant differences in biomass variation (p<0.001).
Two distinct growth periods were observed for seaweed maintained at 10 cm and 20 cm (1 st and 3 rd week) and two periods of little or no growth (2 nd and 4 th week).The lowest SGR for the module at 10 cm was -2.97% d -1 (5 th week) and the highest was 1. 28% d -1 (1 st week).At a depth of 20 cm the SGR variation was -0.59% d -1 (4 th week) and 1.28% d -1 (3 rd week).
Multiple regression analysis showed that temperature, salinity, pH, orthophosphate and ammonium ion accounted for 67% of SGR variability in seaweeds kept at the surface (Table 2).
The SGR data obtained at this depth were positively correlated to the data from the simulated by the multiple regression (R²=0.67;r=0.82; p<0.05; Figure 2a).The SGR of seaweeds maintained at 10 cm was related to temperature, turbidity and pH (Table 2) and simulated SGR at this depth also correlated well with the values observed (R²=0.66;r=0.81; p<0.05) (Figure 2c).The results for algae at 20 cm confirm that turbidity, ammonium and orthophosphate can be used in the prediction equation (Table 2).The SGR at this depth correlated positively with that predicted by the regression (R²=0.62;r=0.78; p<0.05; Figure 2e).The relationship between the predicted and measured values showed that some of the growth rates were below the estimated values at the three depths tested (Figure 2a, 2c, 2e).The residue analyses showed normal distribution at all three cultivation depths (requirement of multiple regression; Figure 2b, 2d, 2f).

DISCUSSION
The significant differences in biomass variations of G. birdiae at the three depths tested establish this variable as a relevant factor in seaweed growth.Although the water column of the pond was homog- enous in physical and chemical composition, turbidity and light penetration significantly controlled seaweed growth.High turbidity in ponds is generally related to the amount of suspended material produced by shrimp culture, which decreases solar light penetration into the water column, restricting photosynthesis and seaweed growth (Marinho-Soriano et al., 2009).
The fact that G. birdiae was more productive at a depth of 10 cm suggests that it prefers environments with moderate irradiation.However, small variations in cultivation depth caused a decrease in algal growth.This is partly explained by the reduced light intensity owing to the high turbidity of the pond.Seaweeds grown at the surface gained less biomass.This low biomass may be due to dehydration and excess of light.The surface seaweeds were partly exposed to the air because of water evaporating from the ponds and wind effect.These caused water loss in the thallus and consequently a loss of biomass.Although there are no evaluations about the consequence of dehydration on Gracilaria growth, studies related to dehydration in Ulva reticulata stems, cultivated in fish pond waste, recorded losses of wet biomass (Msuya & Neori, 2002).In addition, Yang et al., (2006) also recorded variations in seaweed growth between cultivation depths when growing Gracilaria lemaneiformis in eutrophicated water.This emphasizes that different depths in eutrophicated environments are a relevant factor in the productivity of Gracilaria.
Seaweeds generally have high growth rates when exposed to environments rich in nitrogen and phosphorous.However, they cannot tolerate nutrient rich environments for long periods, causing reduced productivity (Yu & Yang 2008).G. birdiae showed positive SGR values at the surface, during the first 21 days of cultivation and at 10 and 20 cm depth on the 1st and 3rd weeks.Although the values recorded during these periods were positive, they were lower than those found by other authors for the Gracilaria species in integrated cultivation (Nelson et al., 2001;Marinho-Soriano et al., 2002;Msuya & Neori 2002;Chirapart & Lewmanomont 2004).The modest values obtained in this study may also be related to limited water movement in the pond since no aerators or water circulation mechanisms were used.The direct association between water movement and nutrient absorption should be pointed out.In fact, Ryder et al. (2004) demonstrated that the lack of water movement significantly decreases growth rates of Gracilaria parvispora in ponds and lagoons in Hawaii.
Equations involving seaweed growth may be useful in studies about productivity.The equations used in this study included different environmental variables (temperature, salinity, pH, orthophosphate, ammonium ion and turbidity) and the growth rate at each depth was significantly related to these factors.This fact emphasizes the influence of small depth variations on the growth rates of G. birdiae, as well as the interaction and specificity of environmental variables on the seaweeds development.
The regression equation showed higher prediction values (R² surface =0.67; R² 10cm =0.66; R² 20cm =0.62) than those found by De Casabianca et al. (1997), which demonstrated that a 59% SGR variation for G. bursapastoris was related to differences in light intensity and water temperature.They were also higher than those of  Marinho-Soriano et al. (2006), that proposed a growth model for G. birdiae relating 61% of the variation to salinity and the epiphyte biomass.Despite the high determination coefficient of the model, the relationship between predicted and observed values shows that some recorded growth values were lower than modelestimated amounts at the three depths tested.This may be due to biomass loss during the experiment.Furthermore, factors not measured such as herbivore, algal biomass losses, absorption kinetics and algal metabolism had some influence on algal development, affecting the accuracy of the growth equation.If these and other variables were included in future studies, they might improve the validity of the equation.
In summary, these results point out the significant effect of depth as an integrator of several parameters that can influence the growth of G. birdiae.It is an important factor to bear in mind when evaluating the cultivation conditions in shrimp pounds.

Figure 2 -
Figure 2 -Correlation between field and simulated data for G. birdiae cultivation and normal probability of residues for the estimated models: (a -b) surface; (c -d) 10 cm deep; (e -f) 20 cm deep.

Table 1 -
Environmental parameters recorded during the study period (Kruskal-Wallis among the weekly data; n=4).

Table 2 -
Regression, coefficient, standard error, and p-valorfor the variables in multiple regression related to SGR of G. birdiae as a dependent variable.