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Journal of Environmental Quality 31:539-547 (2002)
© 2002 American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America

TECHNICAL REPORT
Ecological Risk Assessment

Combination Effect of Light and Toxicity in Algal Tests

Michael Cleuvers*,a, Rolf Altenburgerb and Hans Toni Rattec

a Department of General Biology, Aachen University of Technology, Kopernikusstraße 16, D-52056 Aachen, Germany
b Department of Chemical Ecotoxicology, UFZ Centre for Environmental Research, Permoserstraße 15, D-04318 Leipzig, Germany
c Aachen University of Technology, Worringerweg 1, D-52056 Aachen, Germany

* Corresponding author (cleuvers{at}bio2.rwth-aachen.de)

Received for publication April 2, 2001.

   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
The sensitivity of Scenedesmus subspicatus against potassium dichromate is positively correlated to the photon flux density during the algal growth inhibition test. Low photon flux densities led to significantly reduced maximum effects and higher EC50 levels. To improve the testing of colored substances, we distinguished between the toxic effect (chemical part, represented by potassium dichromate) and the shading effect (physical part, simulated by reduced light intensities during the test) of a hypothetical light absorbing substance. The contribution of these single effects to the total inhibition varied greatly. At high concentrations of potassium dichromate (1.6 and 3.2 mg L-1) the physical part never exceeded 25% of the total inhibition, not even at strongest light reduction, while at low concentrations (0.2 and 0.4 mg L-1) the physical effect became more prominent when halving the amount of available light. Further, the combination effect of the chemical and the physical effect could be calculated well only by using the concept of independent action. Thus, if chemical and physical effects are measured in combination, as is the case in tests with dyestuffs, the current test protocol for the algal growth inhibition test may lead to incorrect estimations of the toxic potential.

Abbreviations: EC, effect concentration • ETAD, Ecological and Toxicological Association of Dyes and Organic Pigments Manufactures • IPQ, index of prediction quality


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
IN THE BASE SET for the notification of new substances, the algal growth inhibition test with the green alga Scenedesmus subspicatus and Selenastrum capricornutum (European Commission, 1993, p. 179–186; Organisation for Economic Co-Operation and Development, 1984; International Standards Organisation, 1989) is the only test method to assess the effects of a substance on primary producers. Therefore, the results of this test are important for classification and labeling as well as for the risk assessment for the environment, which is mostly based on laboratory tests. The algal growth inhibition test is an established tool for the assessment of the phytotoxicity of xenobiotics. However, with light absorbing substances, such as dyes, some problems arise.

Any decrease in the quantal flux in the photosynthetically active spectral region will cause a reduction of algal growth, which is independent of a potential (chemical) toxicity of the test substance. Thus, beneath the primary factor of toxicity, a secondary factor, namely the light absorption of a colored substance, will confound the analysis of the results. Current standard test protocols are not able to distinguish between the real toxic effect and an inhibition due to the shading effect of a light absorbing substance. Hence, for the classification of such substances the test must fail. This of course leads to problems for the notification, where coloring agents are one of the most important groups of chemicals within the notifications of new substances (approximately 20%).

Moreover, as a consequence of light absorption in the test solution, the metabolism of algal cells can be inhibited (Oswald, 1988). Due to this metabolic inhibition, differing results can be expected with regard to the determination of the toxicity of test substances. Bearing this in mind it becomes a problem that in the international guidelines for test protocols the light intensity is not prescribed exactly, but a range of 60 to 120 µE s-1 m-2 is recommended. However, in the lower part of this range light saturation may not be achieved. Thus, in tests with dissimilar light intensities different growth rates in the control can be expected, which would surely influence the sensitivity and thus possibly the results of the test. Due to this, and particularly, if the toxicity of the test substance is even light dependent, the reproducibility of the results would be strongly diminished. This point is also important in connection with the use of reference substances. Potassium dichromate is often chosen in algal tests to assess the general test performance. It is also used in interlaboratory ring tests, for example, when the effect of variations in the test design shall be checked. Thus, it is extremely important to ensure the comparability of results from different laboratories. Hence, the conditions in tests performed anywhere must be as similar as possible and differences in light intensity should be avoided.

Up to now there has been no international agreement on how to handle light absorbing substances in the algal growth inhibition test. As described above, it is clear that the current test protocols may have flaws, because there is no possibility to differentiate between the primary chemical effect and the physical side-effect of a colored test substance. As a consequence, toxicity will be overestimated. The Ecological and Toxicological Association of Dyes and Organic Pigments Manufactures (ETAD) proposed a modified test method to solve this problem (Memmert et al., 1994). They measured in a first part (A) the total inhibition of a dye and in a second part (B) only the shading effect using solutions of the test substance as optical filters between the light source and the test flasks. By computing the inhibitions A minus B they assume to assess the algicidal effect C. However, problems occurred with the interpretation of the results. This calculation presupposes that the total inhibiting effect of a dye (the physical effect of shading and the chemical effect of toxicity) act like the sum of the single effects. Dealing with this question we get in touch with the topic of combination effects and mixture toxicity. Originally, this was a topic of pharmacological research, but it became increasingly important in ecotoxicology and is discussed in detail in several recent publications (Altenburger et al., 1993, 2000; Backhaus et al., 2000; Pöch, 1993; Greco et al., 1995; Drescher and Bödeker, 1995). In that context the calculation method done by the ETAD is called effect summation. Other concepts for the calculation of combination effects of toxic agents are the concepts of concentration additivity and independent action, which will be described below. In this study we examined whether it is possible to apply one of these three concepts on a combination of a chemical and physical effect, as it would be present in an algal test with a colored substance, where the phenomenon of shading occurs concomitantly with a potential toxicity of the test substance. Discovering the correct concept would enable us to recalculate the toxicity of substances, which has already been tested with the ETAD design.

The objective of this paper was to study the effects of different photon flux densities on the results in algal growth inhibition tests and their interaction with the chemical effect to get additional information on how to deal with light absorbing substances. Furthermore, we wanted to examine whether it is possible to differentiate between the chemical and physical inhibition exerted by colored substances and to determine the relationship between these two effects.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Unless stated otherwise, all tests were conducted following ISO 8692 (International Standards Organisation, 1989). The tests were carried out in 250-mL Erlenmeyer glass flasks with a 100-mL test volume with six replicates in the control and three replicates in the treatments. The test duration was 72 h.

Test Algae
In this study we used the planctonic chlorococcale green algae Scenedesmus subspicatus Chodat (SAG 86.81 = UTEX 2594) obtained from the SAG-Sammlung von Algenkulturen at the University of Göttingen, Germany (Schlösser, 1994), and maintained in culture for several years at our laboratory. Inocula were taken from exponentially growing precultures set up 3 d before the experiments and propagated under the conditions of the subsequent test. To ensure exponential growth over the whole test period the initial cell density in the preculture as well as in the test flasks was adjusted at 104 cells mL-1 using a calibration curve of optical density at 720 nm (OD720nm) versus cell number (linear regression; r2 = 0.99) and appropriate dilution of the preculture.

Medium and Test Substance
The test medium of the ISO Standard 8692 was prepared according to the protocol using deionized water and analytical grade chemicals. The pH of the medium was set to 8.3 ± 0.2. The maximum variation allowed during the test is 1.5 pH units, which is probably too high for substances with a pH-dependent toxicity like potassium dichromate. In our test we measured a pH increase of 0.2 to 0.9 with the highest increase in the controls at high light intensity. Potassium dichromate (K2Cr2O7; ErC50 0.84 mg L-1), well known from previous ring tests of the ISO standard (Hanstveit and Oldersma, 1981; Hanstveit, 1982), was used as the test substance and was applied in a geometric dilution series of five concentrations (0.2, 0.4, 0.8, 1.6, and 3.2 mg L-1). The light absorption of the potassium dichromate solutions, which was measured with a LI-COR (Lincoln, NE) Model LI-185B Quantameter, is negligible. Even in the highest concentration the reduction of photon flux density by absorption of the dichromate solution was less than 1%, so all measured inhibitions are only due to the toxicity of potassium dichromate.

Incubation
Conditions in the test and during the preculture were the same. The algae were incubated at 23 ± 2°C under continuous white light (Philips [Hamburg, Germany] TLD). In our tests we used 120 µE s-1 m-2 as a "standard light intensity" and varied the irradiance levels from 21 up to 120 µE s-1 m-2 as measured with a LI-COR Model LI-185B Quantameter using a cosine corrected LI-COR Quantum sensor to investigate the impact of different photon flux densities in the test. To minimize the effect of self shading and to improve gas exchange for the reduction of pH variation the algae were kept in suspension by using continuous shaking (approximately 70 rpm).

Measurements
As an estimate of cell number every 24 h the optical density at 720 nm (OD720nm) of the algal solution was measured in a 5-cm cuvette with a spectrophotometer (Hitachi [Tokyo, Japan] Model 100-40). This wavelength was chosen to avoid differences due to absorption of the pigments. As described above, we calculated the cell number using a calibration curve. The pH was measured using a glass electrode (InLab 412; Mettler-Toledo, Gießen, Germany) and a pH meter (CG 820; Schott-Geräte, Hofheim, Germany).

Endpoint and Effect Calculation
The results were quantified in terms of average growth rates (µav) calculated from measurements of total cell numbers. With a test time t, the average growth rate is:

[1]
where X = biomass (here cell number) and t = test duration.

Inhibitions (in the following called effects, E) were calculated from relative average growth rates:

[2]

Effect concentration (EC) figures obtained with this endpoint are referred to in the ISO standard as ErC values (r for growth rate), but in the following were called simply EC. For a discussion of the selection of the proper response variable or endpoint in algal toxicity tests, refer to Nyholm (1985)(1990, 1994) and Ratte et al. (1998). The EC values were determined with the program Sigma Plot 5.0 (SPSS, 2002a) using nonlinear curve fitting based on a sigmoid model (four parameter logistic function). Statistical comparisons of concentration response curves were performed using the program Allfit (De Lean et al., 1988).

Concepts for the Analysis of Combination Effects
A major topic of this study was the assessment of the combination effect of potassium dichromate and a reduced photon flux density. In this study we examined whether it is possible to apply one of three concepts: independent action, concentration additivity, and effect summation (Altenburger et al., 2000; Backhaus et al., 2000; Kortenkamp and Altenburger, 1998) on a combination of a chemical and physical effect.

The concept of independent action is based on the assumption that the combined effects have different places and modes of action. In this concept, the total effect E(c1,2) is given by Eq. [3]:

[3]
where E(c1) = effect of Substance 1 (as calculated by Eq. [2]) and E(c2) = effect of Substance 2 (as calculated by Eq. [2]).

Note that in contrast to the normal application of the concept, in our study only E(c1) is a chemical effect (Echem): that of potassium dichromate as measured at standard conditions (120 µE s-1 m-2). On the contrary, E(c2) is a physical effect (Ephys) of reduced light intensity, which was controlled by providing different amounts of light. E(c1,c2) is the total effect (Etotal), which can be calculated by using the equation for independent action (Eq. [4]):

[4]

The concept of concentration additivity assumes that the combined substances have a joint molecular place of action and therefore a similar mode of action. The concept can be described mathematically by Eq. [5]:

[5]
where c1,c2 = concentrations of Substances 1 or 2 in the mixture evoking a defined effect, and ECx1,ECx2 = concentrations of Substances 1 or 2 to cause the same effect as the mixture (i.e., EC50).

The third examined concept is called effect summation. It is based on the assumption that the single effects can simply be added up to calculate the combination effect:

[6]
where E(c1) = effect of Substance 1 (as calculated by Eq. [2]) and E(c2) = effect of Substance 2 (as calculated by Eq. [2]).

In contrast to the two other concepts there is no idea given about possible interactions regarding the place and mode of action of combined effects. Due to the immanent shortcomings (Kortenkamp and Altenburger, 1998) this concept is nowadays seldom used in the research, which specifically pursues the prognosis of combination effects based on information about the toxicity of the single substances.

The three concepts differ in the procedure for estimating the combination effect. If the toxicity of the substances applied singly is known, with the concepts independent action and effect summation the combination effect can be calculated directly, while the concept concentration additivity operates only with effect concentrations. Thus, these effect concentrations (e.g., EC50) must be known or their calculation must be possible. For all concepts, the predicted effect of a mixture of substances applied in biologically effective concentrations is always higher than the discrete effect of each of the substances singly.

Index of Prediction Quality
As a criterion for the exactness of the prediction of the combination effect we used the index of prediction quality (IPQ) (Grimme et al., 1996). The IPQ is a measure for the relative distance between observed and predicted toxicity.


[7]

The closer to zero the IPQ, the better the calculation of the combination effect corresponds to the effect measured empirically.

Prediction of EC50 Values According to the Different Concepts for the Analysis of Combination Effects
In Table 1b are given the inhibitions caused by potassium dichromate obtained with "standard light intensity" (120 µE s-1 m-2), while in the third column of Table 1c the physical effect of reduced light intensity is shown. With this data we have calculated the expected combination effects of the five dichromate concentrations at all light intensities (using Eq. [4] for independent action and Eq. [6] for effect summation) to obtain concentration response curves. Then, the predicted EC50 values were determined with a nonlinear curve fitting procedure (four parameter logistic function, Sigma Plot 5.0).


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  		Table 1. Mean average growth rates and measured inhibitions as obtained in the algal growth inhibition tests. nd = Not determinable.

 
To estimate the EC50 predicted by the concept of concentration additivity we used the transformed Eq. [5]:

[8]
where c1,2 = values for potassium dichromate and light reduction in the mixture evoking an effect of 50%, ECx1 = EC50 of potassium dichromate at standard light conditions (0.75 mg L-1, see Table 1b), and ECx2 = EC50 of light reduction (81% light reduction according to the standard light intensity of 120 µE s-1 m-2, determined with nonlinear curve fitting).

Of course, the EC50 of light reduction is not an effective concentration but an effective value. This introduces to the question whether the concept of concentration additivity is also applicable for a nonchemical stressor, such as light reduction or a decrease in temperature. Generally, there is no reason to limit the concept to chemical stressors alone, if it is possible to get a reliable dose response curve and thus dependable effect concentrations with nonchemical factors. Hence, we believe that the inclusion of reduced light intensity as a nonchemical stressor in the concept of concentration additivity is a feasible way to prove the significance of this concept for a combination of toxicity and light reduction. There is a restriction in that way, that the results regarding the effective values of light reduction depend on the starting point (in our case 120 µE s-1 m-2), but this objection pertains only to the exact values of the measured parameters and not the general principle of the concept.

Because the values for c2 are predetermined by the reduction of light intensity (see Table 1c, second column), we can calculate for each physical effect the concentration of potassium dichromate being necessary to evoke jointly 50% inhibition, for example, for 72 µE s-1 m-2 (= 40% light reduction in comparison with 120 µE s-1 m-2):

[9]


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
Figure 1 shows the concentration–time response curves for the mean of three independent experiments with three replicates each using K2Cr2O7 at 120 µE s-1 m-2, which gives the basic data for all subsequent tests and evaluations. The growth in the control and in the lowest tested concentration seemed to become nutrient limited before the end of the test, or, self-shading occurred and inhibited the growth of the algae. Thus, for the calculation of growth rate and inhibitions we used data only from the first two days for these treatments, whereby higher growth rates than after three days were measured.



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  		Fig. 1. Growth curves of Scenedesmus subspicatus as obtained for the test with five concentrations of potassium dichromate at a photon flux density of 120 µE s-1 m-2.

 
Impact of Light Intensity on Growth Rates and Inhibitions Measured in the Algal Growth Inhibition Test
The measured growth rates and inhibitions for all light intensities are given in Table 1. As shown in Table 1a, the average growth rate of the algae increased with higher photon flux densities in the control and in the three lowest dichromate concentrations, but not in the two highest concentrations. Table 1b shows an overview about the measured inhibitions due to the various dichromate concentrations at different light intensities corresponding to the growth rates reported in Table 1a. At a given dichromate concentration, the lower the light intensity, the lower are the inhibitions of the average growth rate. This effect was most pronounced at 3.2 mg L-1 potassium dichromate and significant at all concentrations except the lowest (determined with SPSS/PC+ 4.0 for Windows 6.1.2, linear regression analysis; SPSS, 2002b). These changes in sensitivity are reflected in the EC50 (last column of Table 1b) of potassium dichromate, which decreases slightly with increasing photon flux densities from 0.89 to 0.75 mg L-1. These EC50 values take into account only the toxic effect of potassium dichromate at different light intensities. But in a common algal test with light absorbing substances the conditions are different than ours, because the substance treatments are not only affected by the toxicity of the test substance, they also get a lower part of the photon flux density than the control cultures. To take this into consideration and to measure the combined effect (chemical and physical) we had to compare the growth rates of the five treatments from the tests with reduced light conditions (21–98 µE s-1 m-2) with the control growth rate from the test at 120 µE s-1 m-2. The resulting inhibitions of the average growth rate are given in Table 1c. The EC50 values (now also including the physical part) change clearly and show the opposite development as observed before: the lower the photon flux density the higher is the toxicity of the substance, and the greater is the difference between the measured EC50 values. Because at 21 µE s-1 m-2 the physical effect alone was already higher than 50% (50.9%), an EC50 of potassium dichromate could not be specified, but it is clear that for a slightly lower physical effect (e.g., 49%) a very low EC50 would be measured and if the physical effect approaches 50% the EC50 approximates zero.

Concentration Response Curves
To obtain a clearer impression about the impact of light intensity, the concentration–response curves of potassium dichromate at four selected light intensities are shown in Fig. 2 regarding the measured inhibition and in Fig. 3 for the average growth rate. For the sake of clarity the other curves were omitted. A concentration–response curve can be described by four parameters: the minimum, the slope, the inflection point (which is the half-maximum effective dose), and the maximum. While in Fig. 2 all curves share the first three parameters (F test, Allfit), the curves at lower light intensities clearly show maxima below the standard curve and this effect is especially pronounced at higher concentrations of the chemical. Hence, these curves show clearly reduced maximum effects—the lower the light intensity, the lower the maximum.



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  		Fig. 2. Concentration response curves of potassium dichromate at four selected light intensities (120, 72, 48, and 21 µE s-1 m-2). Shown are the inhibitions of the average growth rates, nonlinear regressions, four parameter logistic fit (for all fits: r2 = 0.999).

 


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  		Fig. 3. Concentration response curves of potassium dichromate at four selected light intenisties (120, 72, 48, and 21 µE s-1 m-2). Shown are the average growth rates, nonlinear regressions, four parameter logistic fit (for all fits: r2 = 0.999).

 
From Fig. 3 one can clearly see reduced growth rates at reduced light intensities on the left vertical axis. One can also see that for the two highest dichromate concentrations there is a higher growth rate at lower light intensities (e.g., 0.36 at 21 µE s-1 m-2 compared with 0 at 120 µE s-1 m-2). One would expect the dotted curves at reduced light intensities, if the chemical effect remains constant at all light intensities and is not affected in any way by the physical effect. However, at low light conditions the effect of potassium dichromate is somewhat reduced as the curves are slightly above the dotted independence curves and the asymptotic minimum of the curves is clearly shifted upward.

This result shows that the chemical effect of potassium dichromate is modified by the physical effect. Hence, a simple subtraction of the physical effect from the combination effect, as it was proposed by the ETAD using the concept effect summation, leads to incorrect (underestimated) results for the chemical effect.

Combination Effect and Prediction of EC50 Values
To differentiate between the chemical and physical part of the total inhibition, it is necessary to know how they act in combination. We found that the combination of the chemical and the physical effect can be calculated better by the concept of independent action than by using concentration additivity or effect summation. This can be shown clearly by a comparison of the predicted EC50 values and the obtained IPQ values (Table 2). For the concept of independent action we have calculated the lowest absolute IPQ values in the range from -0.05 to -0.25, indicating only a slight overestimation of the combination effect. For effect summation we get small IPQ values only when the physical effect is low (98 and 84 µE s-1 m-2), while at higher physical effects (lower light intensities) effect summation leads to clearly stronger deviations and thus a worse prediction with IPQ values in the range from -0.25 to -0.57. Using concentration additivity we got the worst results with IPQ values from -0.19 to -1.89. Regardless of the concept, all obtained IPQ values are negative, indicating that a lower light intensity reduces the toxic effect of potassium dichromate.


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  		Table 2. Comparison of the observed and predicted EC50 values of potassium dichromate in combination with a reduced photon flux density and the resulting index of prediction quality (IPQ) values for the concept of independent action (IA), concentration addition (CA), and effect summation (ES). nd = Not determinable.

 
Contribution of the Chemical Effect in Relation to the Total Effect
A further question that we wanted to answer was: What part (chemical or physical) can we expect to measure if we test a colored substance with a defined physical and chemical effect? By knowing the chemical effect of potassium dichromate at a given light intensity (Echemx, Table 1b) it is possible to compute its contribution to the measured total inhibition (Table 1c), calculating the ratio Echemx to Etotal, which is shown in Table 3.


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  		Table 3. The chemical part of the total inhibition as dependent on the physical effect and the concentration of potassium dichromate.

 
The values for 3.2 and 1.6 mg L-1 potassium dichromate were very similar, showing that the chemical part remains clearly dominant (>90% of the total inhibition) for physical effects up to 30% inhibition of the algal growth rate. Even for the strongest physical effect (50.9%) the chemical effect is clearly the dominant part (76%). The 0.8 mg L-1 values start at the same level like the higher concentrations and then exhibit a constant decrease of the chemical part, which remains nevertheless dominant for all values of the physical effect. The importance of the chemical part decreases much stronger for lower concentrations (0.4 and 0.2 mg L-1) and there the physical part became already dominant at 19.0 and 8.2% light reduction, respectively. These different values are based on the combination of a growing physical effect and the negatively correlated, light-dependent toxicity of potassium dichromate (Table 1b), which varies for a concentration of 3.2 mg L-1 between 62 and 95%. This is a highly significant and much stronger deviation in comparison with the minor changes that we have measured between the test replicates at this concentration: the effect at, for example, 120 µE s-1 m-2 amounted to 94.8 ± 6.6%.


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
Little is known about how light intensity may interact with toxicity. One possibility, assumed by Nyholm and Källqvist (1989), is that specific effects on photochemical reactions are expressed earlier at low light intensities. Gavis et al. (1976) found that in a study on toxicity of copper to marine phytoplankton the light regime had a measurable influence on the results. Both decreased and increased toxicity were observed, depending on the algal clone. Gaur and Singh (1991) reported an increase of petroleum toxicity to Anabaena doliolum with high light intensities, but this was probably merely due to photooxidation of petroleum and the occurrence of more toxic metabolites. Wängberg and Blanck (1988) generated EC100 values for three different algae and 19 chemicals at two light intensities (2 and 10 W m-1). However, no general influence of light intensity on toxicity was observed. Generally, algae growing with the maximum growth rate are seen as more sensitive than algae growing under conditions limited in any way. Therefore, we assumed that under limited light conditions in the test, Scenedesmus subspicatus exhibits reduced sensitivity against the reference substance potassium dichromate.

As shown in Table 1b and Fig. 2, the sensitivity of the test algae against the reference substance correlates with the photon flux density during the algal test. The higher the photon flux density, the more potassium dichromate acts toxically, whereas the clearest influence was found at high dichromate concentrations where, for example, at 3.2 mg L-1 the effect can vary between 62 and 95% inhibition. This is in line with findings of Mayer et al. (1998), who found that inhibition caused by potassium dichromate, 3,4-dichloraniline, and 3,5-dichlorphenole was significantly reduced under light limitation. The impact on the EC levels was given in Table 1b. Because the change in toxicity had not the same extent at all concentrations but was most pronounced at high dichromate concentrations, the EC50 decreased only slightly with increasing light intensity from 0.89 to 0.75 L-1 (mean value in an interlaboratory ring test: 0.84 ± 0.12 L-1; contrary to our study, the medium contained 150 mg NaHCO3 per liter). This variability of the toxicity of potassium dichromate demonstrates that the results of an algal growth inhibition test can differ considerably under different light conditions. This of course makes the comparability more difficult and should be avoided by providing stringent rationales for a light regime during the test.

Table 1c shows in the last column EC50 values for the total inhibition (chemical and physical effect). At low levels of light reduction the effect of reduced sensitivity against the reference substance is high enough to compensate for the reduction of available light. But at stronger reductions of light intensity the EC50 values decrease clearly, feigning higher toxicity at lower light intensities. But as mentioned before, the toxic action actually decreases with reduced photon flux densities, only the growing physical effect causes an increase of the total inhibition and therefore generates lower EC50 values. This clearly indicates that for the ecotoxicological assessment of light absorbing substances the current test protocol must fail, because it cannot distinguish between reduced growth of the algae due to a real (chemical) toxic effect and a physical effect, caused by light absorption in the turbid or colored test solution. Thus, the results of those tests are always a mixture of both effects, toxicity and reduction of available light. If the inhibition of algal growth is solely due to shading, this is probably not relevant for the estimation of the ecological risk. For example, in the criteria for environmental classification of substances put forward by the European Commission there is an exemption clause, which states that the inhibition of algal growth solely by light absorption is specifically excluded as a classification criterion. This means that EC50 values should not be used as a basis for classification if the inhibition is the result of a pure light effect. Such effect is expected to occur only at high visual coloration. Therefore, it is important to know how much of the total inhibition is due to the shading effect.

Differentiation between the chemical and physical part of a total measured inhibition seems to be possible if we know how the two effects act in combination. Therefore, we have examined whether one of the concepts (effect summation, concentration additivity, and independent action) can be used to calculate the combination effect of toxicity and light reduction. Effect summation presupposes that the single effects do not affect each other. But as shown in Fig. 3, the observed experimental chemical effect is lower than expected, presuming independence from the physical effect, particularly at high concentrations of potassium dichromate. The minimum of the growth curves is clearly shifted upward, implying that at low light intensities the effect of the chemical is reduced, most probably due to a reduced Cr uptake caused by reduced photosynthesis. The absolute values of the IPQ attained with the concept of independent action were clearly lower than those by the use of the other concepts (see Table 2). Such results should have been expected for a combination of effects, which have different modes and places of action (Backhaus et al., 2000; Pöch, 1993). This is obviously the case for light reduction on the one hand and the toxic action of potassium dichromate on the other hand.

The concentration–response curves of potassium dichromate at different light intensities (Fig. 2) show this effect more clearly. As described above, all curves can be seen to share the same half-maximum effect and slope but differ significantly in their maximum effect. Such a type of inhibition is described in pharmacology as a noncompetitive type of antagonism. It implies that only the effectiveness or intrinsic activity of a chemical is affected, not its affinity to its molecular site of action. This raises the question, What is known about the mechanism of action of potassium dichromate? Chromate crosses biological membranes and has a strong oxidative power that produces a high concentration of reactive species of O2 inside cells (Bassi et al., 1990; Taylor et al., 1979; Witmer et al., 1994), which can impair the photopigments. Baszynski (1981) reported that chromate strongly decreases the pigment content, inhibits photosystem II activity, and disorganizes the fine structure of chloroplasts of Lemna minor. Whether the observed effect of higher maximum chromium toxicity at high light conditions is the result of a specific interaction, for example, caused by an increase of the redox potential of potassium dichromate enhancing its oxidative power, is not clear and can only be speculated.

By knowing the total effect, the physical part, and the fact that the equation for independent action can be used to calculate the chemical effect, the contribution of the chemical and the physical part to the total inhibition (Table 3) can be determined. These results show that—depending on the toxicity of the tested substance—the same physical effect (e.g., 19.0%) can have a totally different impact from 8 to 98% on the total inhibition. Thus, knowing the shading effect of a substance alone does not allow a judgement of the toxic potential of this substance.

In the introduction we have described the method of the ETAD to calculate the chemical toxicity of a colored substance (Memmert et al., 1994). Beside the fact that light conditions for algae in the two parts (A and B) of such an experiment would not be identical, there is an important fault in the calculation: we have shown that the two parts of the total effect do not act additively as described in the concept effect summation, but follow the concept of independent action. Therefore, the chemical part of the total inhibition is much higher than expected from a simple subtraction. Because a lot of substances have already been tested with the ETAD design, the new knowledge about the combination effect of light intensity and toxicity can now be used to recalculate the chemical toxicity of these substances.

In the light of these new facts, a consequence for algal testing should be (i) to standardize the light intensity more exactly on a higher level to ensure light saturating conditions during the whole test duration. This would avoid changes in toxicity of a test substance due to different light conditions, and (ii) if the ETAD approach for the testing of colored substances is used, the chemical part has to be recalculated by using the equations for independent action.


   ACKNOWLEDGMENTS
 
The authors thank A. Weyers, M. Hammers-Wirtz, K. Appenroth, G. Pöch, and the anonymous reviewers for helping to improve the manuscript.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 





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