5. THE RESPONSE OF FRESHWATER MICRO-ALGAE TO INORGANIC SALTS
5.2 MATERIALS AND METHODS
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Processes such as photosynthesis, protein synthesis and metabolic activity may be affected by salt stress in plants. A relationship between water and salt uptake, enzymatic salt removal capacity and toxicity of salts has been found in some plants (Trapp et al. 2008). Salt stress in plants has three main effects: it reduces water potential, causes ionic imbalance and induces toxicity (Parida and Das 2005). However, plants and algal cells may be able to develop phenotypic adjustments such as changes in biochemical and molecular mechanisms that enable them to cope with salt stress. Biochemical strategies such as change in photosynthetic pathways, induction of anti-oxidative enzymes, as well as alteration of membrane structures may assist plants and algae to cope with salt stress (Berube et al. 1999, Trapp et al. 2008).
These biochemical processes may act additively or synergistically in plants to improve salt tolerance (Parida and Das 2005). Some micro-algae such as some blue-green algae have been found in some hypersaline environments indicating their tolerance to salts. This may be cause for concern in aquatic environments because some blue-greens may cause algal blooms when they are able to out-compete salt-sensitive algae from other taxonomic groups.
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general method used in these toxicity tests is described in Chapter 3 (Section 3.4). Sodium chloride and sodium sulphate were applied at a series of eight concentrations respectively, for each species (0.07, 0.156, 0.313, 0.625, 1.25, 2.5, 5 and 10 g/L). Each exposure of one species to a toxicant was replicated six times. Algal population growth was determined spectro-photometrically by measuring optical density at 450 nm for each plate on a micro- plate reader, at the beginning and the end of the toxicity test.
Test following criteria were used to determine test validity:
Coefficient of variation of control growth ≤10% for P. subcapitata and ≤20% for other species.
An average OD450nm reading of >0.10 for the controls at the end of the test
R2 of more than 0.8 in the linear regression for ECx calculations
Inhibition data between 10% and 90% growth inhibition used in the linear interpolation for ECx calculations
5.2.2 Analysis
5.2.2.1 Growth inhibition and effective concentration (ECx) determination
Data for all test replicates were assessed for validity using the above mentioned criteria, and those that did not meet all the criteria were not used. Percentage inhibition values were estimated for each experimental group (exposure of each species to each toxicant). EC50 values were determined by linear regression and graphic interpolation on the percentage inhibition data (between 10% and 90%). Data belonging to the upper-most and lower-most part of the curve (< 10% and > 90%) were excluded so as to minimize any negative influence they may have on the curve-fitting (Mayer et al. 1997, Slabbert et al. 2004). The EC50 values for all replicates of each toxicant on each species were pooled together and expressed as mean EC50 (+standard deviation). The differences in sensitivity of species to each of the two toxicants were determined by statistically comparing the EC50 values. Data were tested for normality and homogenous variance, and a one-way-ANOVA (Analysis of Variance), with Unequal N HSD post-hoc test was used for normally distributed data (due to unequal replicates after quality control of the data). A non-parametric Kruskal Wallis ANOVA by ranks was used for data that were not normally distributed.
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5.2.2.2 Specific growth rate, no observed effect concentration (NOEC) and lowest observed effect concentration (LOEC)
All the experimental data were used (even those with higher than acceptable variability in control growth after 96hrs) to determine specific growth rate for the control and each toxicant concentration treatment (see Chapter 3.4). This was done in order to include and present stimulation data, which was omitted in ECx calculations. The data were tested for normality and homogeneity, and a one-way ANOVA was used to determine which treatments differed significantly from the control, thus determining NOEC (no observed effect concentration) or LOEC (lowest observed effect concentration) values (using treatments with significantly reduced growth compared to the control). All statistical analyses were undertaken using STATISTICA (Version 8) software package with p≤0.05 as the level of significance.
5.2.2.3 Species sensitivity distributions
Species sensitivity distribution curves were generated in order to compare the sensitivity of macro-invertebrates and micro-algae to the selected inorganic salts (NaCl and Na2SO4).
Median concentration effect (EC50 and LC50) data of the two salts on algae and macro- invertebrates used for the SSDs were extracted from the US EPA ECOTOX database, the UCEWQ (Unilever Centre for Environmental Water Quality) database (Palmer et al. 2004), and data generated in this study. The data from the ECOTOX database were pre-screened and filtered by only using laboratory generated toxicity data and excluding the following data:
seawater as the medium of exposure,
exposure duration longer than 96 hours and shorter than 24 hours, and
no reports on fields such as endpoint, effects measurement, exposure duration and/or concentration units.
Data extracted from the UCEWQ database were pre-screened by excluding data with exposure duration longer than 96 hours and shorter than 24 hours, and those with concentration units other than mass/volume (mg/L or g/L). Species sensitivity distribution curves were drawn using SSD generator (US EPA 2005), and effect concentration data (LC50 or EC50) for different species. In cases where there was more than one effect concentration value of a species on the salt, the geometric mean of all the values was taken as a
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representative value for that species. In cases where there was only one value for the species, that value represented that species on the SSD. The SSD generator was used to construct SSD curves with single species toxicity data generated from this study, and pre-screened data extracted from the ECOTOX and UCEWQ databases.