AN ABSTRACT OF THE THESIS OF
Elizabeth Ann Kiokemeister for the degree of Master of Science in
Fisheries and Wildlife presented on
Title:
j:
1
I
The Effects of Multiple Toxicants on Growth of the Guppy,
Poecilia reticulata
Redacted for privacy
Abstract approved:
Lern .3. Weber
An approach for studying the effects of multiple toxicants on
growth is proposed.
Based upon theoretical development of the model,
possible types of interaction are discussed.
The proposed model was
tested by studying effects of zinc, nickel and their mixture plus
zinc, copper and their mixture on the growth of juvenile guppies,
Poecilia reticulata.
Dose response curves expressing gross growth
efficiency and relative, growth rate as a function of the natural
logarithm of the zinc and nickel curves were not found to be statistically different from parallel, thus concentration addition was pre.icted
for the effects of their interaction.
Theoretical dose response curves
were developed based upon Finney's mathematical model for concentration
addition,
These theoretical equations were statistically compared to
the equations
e.rived from the observed data.
miytnre on gross growth efficiency and relative
Effects of the toxicanc
towth rate of ouppies
indicatea that zico and ni okel are inCra-auncentration additive.
The zinc and copper doze. response curves for both gross growth
efficicocy and relative growth rate were found statistically to be nonparallel.
Response addition was . redicted for the interaction.
Based
upon an appropriate mathematical model for response addition a predicted
curve was developed for a copper-zinc mixture.
When compared to the
predicted curve, the observed dose response curve for the interaction
(for both gross growth efficiency and relative growth rate) was supraadditive with respect to both concentration and response addition.
The Effects of Multiple Toxicants on Growth
of the Guppy, Poecilia reticulata
by
Elizabeth Ann Kiokemeister
A THESIS
Submitted to
Oregon State University
in partial fulfillment of
the requirements for the
degree of
Master of science
June 19Th
APPROVED:
Redacted for privacy
Profssor of,Lshries in charge of major
Redacted for privacy
Fisheries and Wildlife
Redacted for privacy
Dean of Gradu.te School
Date thesis is presented
Typed by Virginia Veach for
7 June 1978
Elizabeth Ann Kiokemeister
ACKNOWLEDGMENTS
To Dr. Lavern Weber, my major professor, I am indebted for his
support and guidance throughout my study.
I am most grateful to Dr. James Hedtke who has provided me with
valuable assistance.
My sincerest thanks are also given to Dr. Charles Warren and the
staff at the Oak Creek Laboratory for their inspiration and encouragemerit.
I wish to extend my appreciation to Dr. Roger Peterson for his
assistance in statistical matters.
Thanks are also given to Dan Reed,
Dana Thomas, and Neil Paulson for their statistical suggestions.
My appreciation is extended to Jim Meeks, Jim Esch, Bill Knapp,
Rick Snow, Dennis Morgan, and Bob Marchant for their invaluable
technical assistance.
Analytical services were provided by the
Environmental Health Science Center.
My thanks to this group, especial-
ly Brian Arborgast.
This research was supported by NIH Grant ES-02210.
TABLE OF CONTENTS
Page
INTRODUCTION
1
RATIONALE
3
EXPERIMENTAL PROCEDURES
Experimental Animal
8
Environmental Conditions
8
Dosing Apparatus
8
Toxicants
9
Food Conversion Studies
9
Toxicant Interaction Studies
10
RESULTS
Zn-Ni Interactions
12
Copper-Zinc Interactions
14
DIS GUS S ION
Zinc-Nickel Mixture
16
Copper- Zinc Mixture
16
BIBLIOGRAPHY
57
LIST OF ILLUSTRATIONS
Page
Figure
la,b,c
Theoretical dose response curves with its isobole
19
diagram.
2
Schematic diagram of the diluter system.
23
3
Dose response curves showing the effects of zinc,
nickel and the 1:4 mixture on gross growth
efficiency.
25
4
Dose response curves showing the effects of zinc,
nickel, and the 1:6 mixture on gross growth
efficiency.
27
Isobole diagrams developed for an 80%, 50%, and
30% reduction in gross growth efficiency for
the zinc-nickel interaction.
29
6
Dose response curves showing the effects of zinc,
nickel and the 1:4 mixture (predicted and
observed) on relative growth rate.
33
7
Dose response curves showing the effects on zinc,
nickel and the 1:6 mixture (predicted and
observed) on relative growth rate.
35
Isobole diagrams developed for an 80%, 50%, and
30% reduction in relative growth rate for
the zinc-nickel interaction.
37
Dose response curves showing the effects of
copper, zinc and the 1:250 mixture on gross
growth efficiency.
41
Isobole diagrams developed for an 80%, 50%, and
30% reduction in gross growth efficiency for
the copper-zinc interactions,
43
Dose response curves showing the effects of
copper, zinc and the 1:250 mixture (predicted
and observed) on relative growth rate.
47
Isobole diagrams developed for an 80%, 50%, and
30% reduction in relative growth rate for
the copper-zinc interaction.
49
5a,b,c
8a,b,c
9
lOa,b,c
11
12a,b,c
LIST OF TABLES
Table
Page
1
Average values of gross growth efficiency and
relative growth rate of control fish.
53
2
Regression equations for the zinc and nickel dose
response curves expressing gross growth
efficiency and relative growth rate.
54
3
Average values of gross growth efficiency and
relative growth rate of copper-zinc interaction control fish.
55
4
Regression equations for copper and zinc response
curves expressing gross growth efficiency and
relative growth rate.
56
The Effects of Multiple Toxicants on Growth of the Guppy,
Poecilia reticulata
INTRODUCTION
A vast amount of work has been done in evaluating the effects of
discrete toxicants on responses of several organisms.
In the environ-
ment where man-made pollution occurs, usually more than one toxicant
will be present.
Water pollution biologists have expressed much concern
about the problem of multiple toxicity.
Sprague (1970) provided a review of the joint toxicity studies that
analyzed the effects of aquatic pollutants on fish.
The two ways that
multiple toxicity has been approached are differmtiated by the level of
biological organization under consideration (Schild, 1961).
The first
approach has involved predicting concentration effect relationships
based upon assumed mechaaisms of action and then compared empirical
results to these curves.
Investigators using this approach are inter-
ested in the biochemical and physiological responses of organisms to
toxicants.
Clark (1937) and Ariens (1964) developed many of the basic
concepts underlying current theory of interaction at these levels.
The second approach, being more general in nature, deals with
mathematical models for toxicant interaction and provides a foundation
which is supported statistically.
Early investigators of this approach
were Trevan (1927) and Bliss (1939), and further development was done
by Gaddurn (1953) and Hewlett and Plackett (1959).
This other approach
has been used to study the quantal effects (death) of multiple toxicants
on organisms.
2
In earlier studies the quantal response was investigated quite
extensively; however, in order to insure the success of organisms in
nature it is very important to study the effects of toxic substances
on performances of the whole organism such as growth and reproduction.
Anderson and Weber (1977) were able to use Plackett and Hewlett's
(1948) mathematical model to predict, in most cases, the effects of
mixtures of selected environmental toxicants on the survival of guppies
(Poecilia reticulata).
Muska and Weber (1977) tested the applicability
of the model for the response of growth.
Growth was selected as the
quantitative response because it represents a performance of the integrated activities of the whole organism and as such is found to often
be a sensitive indicator of susceptibility to environmental toxicants
(Warren, 1971).
The results of this work raised some important ques-
tions which led us to further investigation of the model's applicability
to sublethal effects.
The objectives of the project are to:
1) develop an approach
theoretically and methodologically for studying the effects of multiple
toxicants on growth; 2) conduct experiments to test the applicability
of the proposed model to quantitative studies such as growth; 3) evaluate the theoretical aspects of toxicant interaction.
3
RATIONALE
A two-way classification scheme was developed by Hewlett and
Plackett (1959) that explains various types of toxicant interaction:
Similar
Dissimilar
Non-Interactive
Simple Similar
(Concentration Addition)
Independent
(Response Addition)
Interactive
Complex Similar
Dependent
They defined toxicant mixtures as similar or dissimilar depending upon
whether or not the toxicants act upon the same physiological systems and
interactive or non-interactive depending upon whether one toxicant does
or does not influence the amount of the second toxicant reaching its site
of action.
Due to the complexity of "interactive" toxicants, they were
excluded from this study.
Anderson and Weber (1977) introduced the terms concentration and
response addition which correspond to "simple similar" and Ttindependentlt
action.
Concentration addition is mathematically defined as the addi-
tive effect determined by the surnmatin of the concentrations of the
individual constituents in a mixture after adjusting for their respective potencies.
The proportions of the two toxicants total 1 unit.
For example, the proportion of toxicant 1 (111) and the proportion of
toxicant 2 (Tr2) for a 1:4 mixture would be .2 and .8, respectively.
In this type of interaction, it is assumed that the toxicants are
affecting the same physiological systems; thus the dose response curves
of the individual toxicants ar
usually parallel.
When the curves for
4
the two individual toxicants are parallel, a dose response curve of the
mixture is calculated based upon the assumption of concentration addiThe regression equations for the individual toxicants are in the
tion.
form of Y
a + bln(x) (where Y is the percent response to each toxicant
and x is the concentration).
The regression equation £ or a binary
mixture is represented by
Y
m
= a
1
+ bln(7r
1
(1)
+ pr ) + bln(x)
2
where,
Y
m
a1
b
= % response to the mixture
Y intercept of first toxicant
= common slope
= proportion of the first toxicant in the mixture
= proportion of the second toxicant in the mixture
p
= potency of the second toxicant relative to the first
p
= e'
x
intercepts of the two toxicants/common slope)
concentration of the mixture
Response addition is based upon the assumption that the toxic
constituents are affecting different physiological systems or affecting
differently the same systems within the organism.
This interaction is
predicted for a mixture if the dose response curves of the individual
toxicant are non-parallel or if it is known that the toxicants are
affecting different physiological systems or affecting differently the
same systems.
It is expressed in terms of the following equation
+ P2
where,
P1P7
P
= response to the mixture with respect to gross
growth efficiency or relative growth rate
P1 = response to toxicant 1
P2 = response to toxicant 2
The greatest reduction in growth without causing mortality is designated
as a 100% response and no reduction in growth is a 0% response.
The
responses to a binary mixture are response additive only if the concentrations of both toxicants are above their respective threshold levels.
Threshold here refers to the lowest concentration of a toxicant that
will cause a reduction in growth.
If in a mixture one toxicant is
above threshold and one is below, only the effect of the toxicant above
threshold will be seen if the toxicants are response additive.
The data developed for growth is expressed in terms of an average
response of a group of 15 fish.
unknown.
The susceptibility of each fish is
For a graded response such as this, maximum possible response
is not clearly defined.
Three equations were developed by Hewlett and
Plackett (1959) utilizing degrees of correlation (complete positive
correlation, no correlation and complete negative correlation) in order
to predict response additive dose response curves when dealing with an
all or none response such as death.
Assuming there is no correlation
in susceptibilities Hewlett and Plackett developed the formula
P1 + P2 - P1P2.
An organism's growth response can range from growth enhancement to
negative growth, depending upon the concentrations of the toxicant(s).
The to1erancs of the individuals in the group will vary for different
toxicants in a mixture; however, this factor will not alter the relative
6
toxicity of the mixture because the range of tolerances of the population is theoretically represented in the sample or organisms from this
population (Muska and Weber, 1977).
The type of addition can be described only in relation to the
response under consideration.
response.
Growth, in this case, is a very specific
Different types of interactions might be expected for dif-
ferent responses (survival, growth, reproduction) with the same toxicant
mixtures.
These studies are important, however, because they provide
us with a better understanding of the effects of toxicant mixtures and
also enable us to evaluate our approach.
The terms supra- and infra-addition are used to describe those
interactions that are greater or lesser than those interactions
predicted on the assumption or concentration or response addition.
tsobole Diagrams
Relationships between dose response curves can easily be visualized
by the use of isobole diagrams (Loee, 1928).
equivalent response (for example, a 5O
Isoboles are lines of
reduction in growth).
They can
be developed for any level of rasponse and the relationships between
the isoboles may vary depending upon the response level chosen.
A
diagram is developed by plotting one toxicant on the X-axis and a
second toxicant on the Y-axis (see Figure 1).
The boundary concentra-
tion for each individual toxicant in the diagram would be that concentrátion at which the designated response was achieved.
Mixing rays
can easily be developed for various mixing ratios of toxicants A and B.
If the designated response to various combinations of the two toxicants
falls within the square, then the two toxicants are additive.
If the
7
points fall outside this area, the toxicants are antagonistic which
means that the presence of one toxicant requires that a higher concentration of the second toxicant be present to obtain the defined level of
response.
Isoboles for concentration addition are determined from the
concentrations of the two toxicants which correspond to points of
intersection between the designated response line and the respective
hypothetical dose response curve.
These concentrations can then be
plotted on the appropriate mixing ray.
points define the course of the isobole.
The lines connecting these
The predicted concentration
addition line is represented by the diagonal isobole.
One of the
drawbacks of the isobole diagrams is that there is not a statistical
test yet developed to test significance of the data.
Another way to evaluate the data is to develop theoretical dose
response curves based upon Hewlett and Plackett's (1959) model for
each mixture and compare those to the dose response curves for the
observed mixtures.
This method, utilized by Anderson and Weber (1977)
for lethality studies, was adopted in the present study to evaluate
its applicability to quantitative responses.
F;]
EXPERIMENTAL PROCEDURES
Experimental Animal
Newborn guppies (Poecilia reticulata) were collected and transferred in lots of 30-35 fish to individual acclimation tanks.
The
acclimating fish were fed an excess ration of tubifex worms daily.
In
previous growth studies, (Weber and Muska, 1977) weight of the fish was
observed to be responsible for some of the variability observed in the
To reduce this potential source of variation, steps were taken
data.
to ensure the selection of fish of the same weight.
At the age of 12-
15 days, 15 fish of approximately the same size, weighing 0.45-0.50
grams were placed in each tank.
At the end of each experiment, wet
weights were taken for each group of fish which were then placed in an
oven for 5 days to determine a wet-dry weight relationship.
Environmental Conditions
Environmental conditions were monitored and controlled during the
acclimation and experimental period.
The pH was maintained at 7.0 ±
0.20 by bubbling CO7 in the incoming water for both the experimental
and acclimation vater systems.
Photoperiod was set at 13 hours of
light, 6 hours of dark, and the water temperature was maintained at
25.5 ± 1.0°C.
Levels of alkalinity (130 mg/l as CaCo3), hardness
(100 mg/i as CaCo3) and dissolved oxygen (3.3 mg/l) were checked.
Dos in2
patus
The dosing apparatus used in this study was the same used by
Muska and Weber (1977).
A schematic diagram of the system is shown in
It consisted of a series of plexiglas chambers designed to
Figure 2.
continuously dilute the stock solutions of toxicant to the desired
concentrations.
Four such diluters in the system deliver water (with
or without toxicant) to a total of 24, 10-liter tanks.
The total flow
rate to each tank was checked daily and maintained at 100 mi/mm.
Each diluter was constructed so that the three experimental tanks of
fish were subjected to the same concentrations.
This modification
provided more observations at each concentration and also reduced the
number of water samples for analysis.
Toxicants:
The toxicants studied were the chloride salts of nickel, zinc, and
copper.
Water samples were collected daily and analyzed by flame atomic
absorption spectrophotometry.
Very low concentrations of copper were
used for the experiment (.00l26-.0l02 mg/i).
Consequently, a special
procedure was developed to concentrate the copper prior to analysis by
atomic absorption.
This technique was a modification of a procedure
developed by Baetz and Kenner (.1975).
Food Conversion Studies:
Each group was fed a restricted ration of tubificid worms daily
during the 7-day experimental period to determine the effects of
toxicants an food conversion efficiency.
A restricted ration equivalent
to 20% of the initial wet weiht of each group was used.
This ration
size was entirely consumed and resulted in a high growth rate and
represented a ration close to the maximum gross growth efficiency
(Nuska and Weber, l977L
10
The efficiency with which an animal converts food energy into body
tissue is called gross growth efficiency (Er) and can be represented by
the following equation (Warren, 1971):
E=4_*l00
(2)
where C is growth measured as the change in body wet weight and I is
the total food consumption.
The measurement of growth was expressed in terms of relative
growth rate (RCR), a growth rate relative to body weight.
This was
calculated by the following equation (Warren, 1971):
lnW
- lnW.
RGR=
f
I
where W. is the initial wet weight of each group at the beginning (t.)
of an experiment and Wf is the final (tf) wet weight.
To account for variables (such as change in caloric content of
the tubificid worms) approximately half of the bioassays were identical
to the exposure tanks except no toxicant was introduced.
Control gross
growth efficiency and relative growth rates were consistant throughout
the experimental period.
Toxicant interaction Studies
Dose response curves, expressed as a function of the natural
logarithm of each discrete toxicant concentration, were calculated.
Regression lines of the individual toxicants were compared statistically
(t-test) for parallelism.
Based upon Finney's (1971) equation for con-
centration addition (1), theoretical dose response curves were developed
for a mixture of the two toxicants.
The prediction of concentration
11
addition was tested by performing a bioassay with the toxicant mixture.
The observed curve for the mixture was compared statistically (t-test)
to the predicted dose response curve.
If the two toxicants were found to be non-parallel, response
addition was predicted and tested emperically.
The bioassay results
of two toxicants that are response additive are difficult to evaluate
because the dose response of the interaction is usually curvilinear,
thus making it very difficult for statistical comparison.
12
RESULTS
Zn-Ni Interactions:
Studies were conducted to determine the results of zinc and nickel
chlorides and their mixture on gross growth efficiency and relative
growth rate of the juvenile guppy.
The resulting responses of all
experimental fish were calculated as % of the maximum response and
plotted versus the natural logarithm of the toxicant concentration.
Means and standard deviations of the internal control responses are
presented in Table 1.
Equations developed for the nickel-zinc data
including sample size and concentration range are shown in Table 2.
Slopes of the dose response curves (expressing gross growth efficiency)
for zinc and nickel (107.14 and 130.90) were not found to be statisti-
cally Ct-test) different from parallel at the = .05 level.
concentration addition was predicted for the mixture.
Consequently,
A common regres-
sion coefficient.(1l2..50) was calculated from the regression equations
of the individual toxicants by analysis of covariance (Finney, 1971).
A potency factor of .2136 along with the Droportionality factor
(Zn1
Ni2 = .2:.8 for the 1:4 mixture and .l42:.858 for the 1:6
mixture) were substituted into equation (1) to calculate the predicted
dose. response curve for the mixtures.
The dose response curves for
the individual toxicants and their mixture (predicted and observed)
are shown in Figures 3 and 4.
It is interesting to note that growth
enhancement (greater than 100% response) was observed in a zinc concentration of .96 mg/i.
Based upon these theoretical and observed dose
response curves, three isobole diagrams were developed (Figure 5a,b,c).
13
Points were plotted to show the concentrations which caused an 80%,
50% and 30% reduction in gross growth efficiency at a 1:4 and 1:6 zincStatistical t-tests demonstrated that the slopes of
nickel mixture.
both the 1:4 and 1:6 observed mixtures were not different from those of
the predicted equations.
Statistical (t-test) comparison of the dose
response curves for the two mixtures of zinc and nickel were infraconcentration additive.
The observed and predicted dose response curves for the relative
growth rate of the fish (Figs. 7+8a,b,c) were essentially the same as
the curves for gross growth efficiency.
This was not unexpected since
food consumption of the fish is constant relative to body weight (Muska
and Weber, 1977).
The resulting data for the control and experimental
studies are presented in Tables 1 and 2, respectively.
Effects of the
toxicants on the relative growth rate of the fish was due to the dosedependent relationship between gross growth efficiency and toxicant
concentration.
Slopes of the dose response curves of relative growth
rate for zinc and nickel (103.01 and 138.11) were not statistically
different from parallel.
A common regression coefficient of 113.01 was
calculated from the regression equations of the discrete toxicants by
analysis of variance (Finney, 1971).
A relative potency factor of .2086
along with the proportionality factors (Zn
mixing ratio and .142
:
: Ni
,
.2:.8 for the 1:4
.858 for a 1:6 mixing ratio) were then
substituted into equation (1) to determine the predicted equations.
Statistical tests indicated that, in both cases, the slopes were not
statistically different, yet the mixtures were infra-concentration
additive.
14
Copper-Zinc Interaction
Effects of copper and zinc on gross growth efficiency and relative
growth rate of the guppy were determined for the individual dose
response curves.
mg/i.
Copper concentrations ranged from .00239 - .01020
Concentrations of copper higher than .00102 mg/i resulted in
fish mortality and those lower than .00235 mg/i did not cause a reduc-
tionin growth.
Zinc dose response curves were the same ones used in
the previous study.
Zinc concentrations ranged from .96 - 2.50 mg/i.
Concentrations higher than 2.50 mg/i caused fish mortality and those
lower than .96 mg/i caused 0% reduction in growth.
The responses of
the toxicants were normalized and plotted as a function of the natural
logarithm of toxicant concentration.
The dose response curves for the
discrete toxicants and their mixture (predicted and observed) are shown
in Figures 9-12.
Means and standard deviations of the control data
corresponding to each bioassay are shown in Table 3.
Slopes of the
dose response curves (expressing gross growth efficiency) for copper
and zinc (57.84 and 112.50) were found to be statistically different
from parallel.
Slopes of the relative growth rate dose response curves
for copper and zinc (60.59 and 113.01) were also found to be statistically
nonparallel.
Response addition was predicted for the Cu-Zn mixture
expressing gross growth efficiency and relative growth rate.
A fixed proportion of copper and zinc (1:250) was used to study
the nature of the interaction.
Zinc concentrations for the interaction
ranged from .37 - .96 mg/i and copper concentrations from .00126
.00346 mg/i.
Regression equations for copper, zinc and the mixture
expressing gross growth efficiency and relative growth rate are presented
15
in Table 4.
Comparison of the prdicted versus observed data indicated
that the interaction was not response additive but it was supra-response
additive.
The observed mixtures (for gross growth efficiency and
relative growth rate) were also shown not to be concentration additive
by statistical t-test.
16
DISCUSS ION
Zinc-Nickel Mixture
The zinc and nickel dose response curves expressing gross growth
efficiency and relative growth rate were not found to be statistically
different from parallel suggesting that when administered simultaneously,
their effects on growth would be concentration additive.
The results of
the interaction studies on both gross growth efficiency and relative
growth rate at the 1:4 and 1:6 mixtures were found to be infraconcentration additive.
In other words, the observed dose response
curve is shifted to the right of the predicted curve which indicates
that the mixture is less toxic than it was predicted to be.
It is interesting to note that the highest concentration of nickel
used in this study that did not cause fish mortality was 10.89 mg/i.
Two years prior, Muska and Weber (1977) conducted a similar study, in
the same laboratory, under the same environmental conditions using fish
from the same brood stock.
The highest nickel concentration used in
their study without causing mortality was 18.00 mg/i.
The copper con-
centrations that I used (.00126-.01020 mg/i) were also lower than those
concentrations (.00200-.01200 mg/l) used by Muska and Weber (1977).
The water quality remained the same throughout both studies.
This may
he an indicaticu that the brood stock is undergoing a genetic change
which is a very important consideration when doing comparative studies.
Copper-Zinc Mixture
A copper-zinc interaction was chosen specifically because it was
thought that these toxicants might act in a response additive manner.
17
Dose response curves (expressing both gross growth efficiency and relative growth rate) developed for copper and zinc were found to be statistically different from parallel.
this study.
Response addition was predicted for
Resulting interaction curves for both gross growth effici-
ency and relative growth rate were found to be significantly different
from the predicted concentration additive dose response curve.
The
entire concentration range of zinc used in the interaction study (.37.95 mg/l) was below the threshold level of zinc when administered alone.
Copper concentrations for the mixture ranged from .00126-.00346 mg/l.
Four of the six copper concentrations used in the interaction were
below copper's threshold.
This indicates the possibility that copper
and zinc may be interacting in some other manner.
This project has provided additional information regarding the
assumption, limitation, and predictability of the proposed model.
Further development of the isobole diagrams has allowed us to choose
the best ratios of toxicant mixtures that will show the largest differentiation between response and concentration addition, however, when
are the points that are plotted for a specific response far enough away
from the specified line (for either response or concentration addition)
that they are no longer called response additive (or concentration
additive)?
For example, the observed dose response curves are supposedly
parallel with the predicted curve but shifted to the right indicating
infra-concentration addition.
In the isobole diagram which corresponds
to an 80% reduction in growth, the points for a 1:4 and 1:6 mixture
corresponding to this reduction are found such that the mixtures look
infra-response additive, yet according to the statistical tests and
18
original assumptions of the model, these interactions were really infraconcentration additive.
The same type of results occurred with relative
growth rates of nickel and zinc.
For another example, the original dose
response curves for copper and zinc were found too statistically different from parallel, thus response addition was predicted.
From the
looks of where the point falls on the isobole diagrams, the interactions
appear to be supra-concentration additive yet we know that the two
original lines were not parallel.
In order for the interaction to be
concentration additive, we should not have seen the statistical
difference between the predicted and observed concentrations additive
dose response curves.
The copper-zinc interaction results indicate the
interaction is neither concentration additive or response additive, yet
this is not shown clearly by the isobole diagrams.
19
Figure la,b,c.
Shown in Figure 1 are theoretical dose response curves
and an isobule diagram for both concentration and
response addition expressing the effects of zinc and
The point #1 cor-
nickel on gross growth efficiency.
responds to an 80% reduction in gross growth efficiency
when zinc was studied alone and #7 shows that concentration of nickel alone which caused an 80% reduction in
growth.
Points 2-6 are plotted at the concentrations
an 80% reduction in growth at a 1:3, 1:4, 1:5, 1:6, and
1:9 mixture, respectively.
la and 13.
These points are shown in
Predicted concentration additive dose
response curves (la) were developed from Finney's (1971)
equation (1).
Based upon Hewlett and Plackett's (1959) equation
for response addition (P
P
in
± P
1
2
- P P,), the
lh
theoretical response additive curves for a 1:3, 1:4,
1:5, 1:6, arid 1:9 mixture were developed (ib).
Points
(7-il) corresponding to an 80% reduction in growth are
shown in lb and Ic.
20
111
2.1862
8
9
1:6
I0
II
2
z
0
I-
1.0931
I-
z
0
z
0
0
z
1:9
4
5
Lii
0
C-)
4.9688
NICI<EL CONCENTRATION (mg/I)
7
9.9375
I'.)
2.4
2.2
2.0
1.8
1.6
i.q
'.0
CONCENTRATION LN
j.
.
0
I0
20
1ti
C,)
LL
x
w
C',
C,,
-30z
40
50
7C
C)
w
2
>-
C-)
m
.1.
r
C)
z
r)
0
I
Zr0
-4z
m
C,
ZcD
0
C,
r
0
5
0
0
0
0
0
0
0
0
0
RESPONSE) MAXIMUM OF (%
EFFICIENCY GROWTH GROSS IN REDUCTION
0
NiZn
23
Figure 2.
Schematic diagram of the diluter system.
refers to the concentrated toxicant.
Stock solution
MARIOTTE BOTTLE
25
Figure 3.
Dose response curves showing the effects of zinc, nickel
and the 1:4 mixture (predicted and observed) on reduction
of gross growth efficiency of juvenile guppies.
Each
point represents the mean value of 3 experiments which
has 15 fish in each.
* Data represents the mean value of only 2 experiments which
has 15 fish in each.
0
--CD
-zr
U)
U,
>-
1L
20
30
70
8O
0
.40
120
LN CONCENTRATION
.80
1.60
/
2.00
/
2.40
0"
I'.;
27
Figure 4.
Dose response curves showing the effects of zinc, nickel
and the 1:6 mixture (predicted and observed) on reduction
of gross growth efficiency of juvenile guppies.
Each point
represents the mean value of 3 experiments which has 15
fish in each experiment.
* Data represents the mean value of 2 experiments only which
A 100% response is
has 15 fish in each experiment.
designated as the greatest reduction in gross growth efficiency without causing mortality and a 0% response refers to
no reduction in growth.
(9
0
a:
Cl)
U)
a:
0
I-
LL
ULU
(-)
-J
w
a:
0
I
w U
I-
(-)
80
90
tOO
-.40
0
to
20
30
40
50
U 70
w
U 60
>-
o
0
IL
-
><
z
0
.40
L20
LN CONCENTRATION
.80
L60
2.00
240
NICKEL
RE
29
Figure 5a,b,c.
Isobole diagrams developed for an 80%, 50%, and 30%
reduction in gross growth efficiency for the zincnickel interaction.
1:2
1:3
2.1862
1:5
/ ///v
E
z
0
I
I
1.0931
1:6
I:?
1:8
1:9
z
Lii
C)
z
0
C-)
C-)
/
4.9688
Fig. 5a.
NICKEL CONCENTRATION (mg/I)
9.9375
I652
E
1:2
1:3
1:4
00'
z
0
I-
8262
z
SlO
Lu
C)
z
0
C)
C)
z
3.9507
Fig. 5b.
NICKEL CONCENTRATION (mg/I)
7.9013
1.3709
II
/
/
/q;\/
':7
z
0
1:8
I-
1:9
6855
,:io
I-.
z
0
2
0
0
0
2
LU
3.3907
Fig. 5c.
NICKEL CONCENTRATION (mg/I)
6.78 13
33
Figure 6.
Dose response curves showing the effects of zinc, nickel
and the 1:4 mixture (predicted and observed) on relative
growth rate of juvenile guppies.
Each point represents
the mean value of 3 experiments which has 15 fish in each
experiment.
* Data represents the mean value of only 2 experiments
which has 15 fish in each experiment. A 100% response
refers to the greatest reduction in relative growth
rate and 0% represents no response.
(J
-w
I
NJO
WL)
-J
F-
>
Iii
(D
0
I-
=
I-
w
'-,
0
Li..
-
-.40
0
I0
20
30
40
50
60
0
80
90
,00
0
40
120
LN CONCENTRATION
.80
160
2.00
2.40
4,.
35
Figure 7.
Dose response curves showing the effects of zinc, nickel
and the 1:6 mixture (predicted and observed) on reduction
of relative growth rate of juvenile guppies.
Each point
represents the mean value of 3 experiments which has 15
fish in each experiment.
* Data represents the mean value of only 2 experiments which
has 15 fish in each experiment. A 100% response refers to
the greatest reduction in relative growth rate and 0%
represents no response.
50
71)
80
20
30
Lu
N.J 0
.40
0
. to
-J
>
Lu
0
0 40
._
I-..
Lu
dP
0
IL.
z
90
ESIe]
0
.40
120
/
I
I
/
LN CONCENTRATION
.80
/
EDICTED,
ZINC
/
/
/
1.60
A
2.00
2.40
URE
-NICKEL
37
Figure 8a,b,c.
Isobole diagrams developed for an 80%, 50%, and 30%
reduction in relative growth rate for the zinc-nickel
interaction.
1:2
1:4
2.2758
':5
1:6
a'
E
z
0
I:?
I.
a:
I
z
w
0
z
0
0
0
z
/
1.1379
I
I
1:8
/
/
/O<
//
I:20
5.0 075
Fig. 8a.
NICKEL CONCENTRATION (mg/U
10.015
U.)
I3
1:2
1:4
1.7008
1:5
E
1:7
z
0
H
1:8
1:9
I
85040
l:io
Li
C)
z
0
0
0
z
ISY4*J
Fig. 8b.
NICKEL CONCENTRATION (mg/I)
8.0598
14007
1:2
1:3
1:4
1:6
(:7
z
0
':8
1:9
F2:
70035
((0
LU
C-)
z
0
0
z
C-)
0
Fig. 8c.
3.4866
NICKEL CONCENTRATION (mg/I)
6.9732
41
Figure 9.
Dose response curves showing the effects of copper, zinc
and the 1:250 mixture on reduction of gross growth efficiency of juvenile guppies.
Each point represents the mean
value of 3 experiments which has 15 fish in each experiment.
* Data represents the mean value of 2 experiments only which
has 15 fish in each experiment. The greatest reduction in
gross growth efficiency is represented by 100% response
and no reduction = 0%.
100
'INC
< 90
LL
0 80
>
70
U
Ui
-4
U
U-
IL 50
Lii
=
I-
0
30
U)
L(0
20
ULUU
0
0
Ui
-6.00
-5.00
-4.00
-3.00
-2.00
-(.00
00
1.00
LU CONCENTRATION
.4.
43
Figure lOa,b,c.
Isobole diagrams developed for a 20%, 50% and 70%
reduction in gross growth efficiency for the
copper-zinc interaction.
1:50
00934
i:ioo
1:150
1:175
l:2oo
1:250
I:300
E
z
0
I4
I-
z
Li
0
z
0
0
/
00457
/
1:400
////)/
1/11/ /
1/11/
O'
>
\4,
I:500
'04,
:600
Li
:700
aa-
:800
0
0
:ioao
:1200
:1700
0
Fig. iOa.
1.115
ZINC CONCENTRATION (mg/I)
2.230
00543
1:50
1:100
\
1:400
E
\.
0
1
.002715
1:500
:600
2
Lii
U
z
0
0
:700
w
:1000
0
0
0
0
U
Fig. lob.
.8262
ZINC CONCENTRATION (mg/I)
I.65a3
Ln
I200
.0038E
2SO
1:400
E
Cd
z
0
:600
I
a:
I
w
0
z
0
0
00193
4,
:800
I.IeI.
a:
Ui
0.
C-)
U
Fig. lOc.
£855
ZINC CONCENTRATION (mg/I)
1.3709
47
Figure II.
Dose response curves showing the effects of copper, zinc
and the 1:250 mixture (predicted and observed) on reduc-
tion of relative growth rate of juvenile guppies.
Each
point represents the mean value of 3 experiments which has
15 fish in each experiment.
* Data represents the mean value of only 2 experiments
which has 15 fish in each experiment. The greatest reduction in relative growth rate = 100% response and no
reduction in growth = 0%.
toe
ZINC
90
IL
°
LU
80
70
60
I-.
50
(D
LU 40
>
30
c',J
U.)
..c
20
2:
0-4
2:
- = 10
I
ow
0
-bOO
-.00
-4.00
-3.00
-2.00
LN CONCENTRATION
-L00
0.0
1.00
49
Figure 12a,b,c.
Isobole diagram developed for an 80%, 50% and 30%
reduction in relative growth rate for the copperzinc interaction.
(:200
008619
1:250
I:300
E
z
0
t:400
ix
z
w
0
2
0
0
0043(0
/
//X0,
1:600
ix
w
1:800
a.
a.
(:1000
0
(-)
/
/
0
Fig. 12a.
t1352
ZINC CONCENTRATION (mg/I)
2.2702
005266
1:100
i:oo
1:250
s:3oo
):400
\/
\t
E
z
0
(:500
I-
1
I:600
.002633
U
z
0
1:800
C-)
w
i:i000
0
0
C-)
0
Fig. 12b.
.8446
ZINC CONCENTRATION (mg/I)
1.6692
Ui
1200
1:100
0037
1250
1300
-p
,:400
\'/
C,
1:500
E
z
0
I
1:600
ci:
a:
I
z
w
0
z
0
0
.001895
i:soo
>
IKISISIII
a:
LLI
1
0
C)
700
Fig. 12c.
ZINC CONCENTRATION (mg/I)
1.400
53
Table 1.
Average values o:E gross growth efficiency and relative growth
rate of control fish.
Cross growth efficiency
A
27
24.62 ± .42
42.29 ± .28
B
28
23.99 ± .42
41.32 ± .63
C
22
23.81 ± .35
40.95 ± .52
D
18
23.49 ± .51
40.57 ± .78
groups4-
A
13
Relative growth rate
(mg/g!day ± S.E.)
Sample
size2
Control
(Z ± S.E.)
Control fish were tested simultaneously with zinc.
Control fish were tested simultaneously with nickel.
1C,D Control fish were tested simultaneously with the zincnickel
mixtures, 1:4 or 1:6,
2
This value represents the number of groups each of which contain
15 fish.
Table 2.
Toxicants
Sample
size1
Zinc
27
Y
Nickel
16
Y
-220.60 ± 130.90
Y
-119.03 + 112.50
Zn
Zn
-
Zn
Zn
1
2
3
Regression equations for the zinc and nickel dose response curves expressing gross growth
efficiency and relative growth rate as a function of tox[caut concentration. Y
% reduction
in growth expressed as mg/g/day.
X = toxicant concentration in mg/i.
-
Gross growth efficiency2
-3.8
+ 107.14
Ni pre.
1:4
Ni obs.
1:4
18
Y
-128.21 +
Ni pre. 1:6
-
Y
-133.80 + 112.50
Ni obs. 1:6
15
Y
-104.41
96.26
79.08
Relative growth rate3
mx
mx
mx
mx
Y =
mx
mx
-4.71 ± 103.01
Y = -238.22 + 188.11
Y
-123.86 + 113.01
Y
-148.78 + 105.06
Y
-138.97 + 113.01
Y
-108.12 +
79.27
This value represents the number of groups each of which contain 15 fish.
x 100 refer to equation (2).
Gross growth efficiency
mW
loW.
1
Relative growth rate
f
refer to equation (3).
mx
mx
mx
mx
mx
mx
Toxicant
concentration range
.96
6.36
Zn
.95
Ni 4.03
3:84
-
2.50 mg/i
10.89 mg/I
2.30 mg/i
9.36 mg/i
10:6? mg/i
55
Table 3.
Average values of gross growth efficiency and relative growth
rate of copper-zinc interaction control fish.
Control
groups1
Sample
size2
Gross growth efficiency
A
22
22.97 ± .70
39.71 ± 1.04
B
27
24.62 ± .42
42.29 ±
C
17
24.31 ± .72
41.91 ± 1.05
(% ± S.E.)
Relative growth rate
(mg/g/day ± S.E.)
.28
Control fish were tested simultaneously with copper.
Control fish were tested simultaneously with zinc.
Control fish were tested simultaneously with the copper-zinc
mixture.
2
This value represents the number of groups each of which contain
15 fish.
Table 4.
Regression equations for copper and zinc dose response curves expressing gross growth
efficiency and relative growth rate as a function of toxicant concentration. Y = % reduction
X = toxicant concentration in mg/i.
in growth expressed as mg/g/day.
Toxicant
Toxicarit
Sample
size1
Copper
17
Y = 352.68 +
Zinc
27
Y =
-3.8
18
Y =
99.79 +
Copper-Zinc
Mixture (1:250)
Relative growth rate3
Gross growth efficiency2
58.07 mx
Y
369.41 +
60.88 mx
107.14 mx
Y =
-4.71 + 103.01 mx
95.28 lnx
Y =
98.82 +
92.39 mx
This value represents the number of groups each of which contain 15 fish.
Gross growth efficiency =
3
Relative growth rate =
s 100 refer to equation (2).
mW - mW.1
f
0
refer to equation (3).
concentration range
.00239 - .0102 mg/i
.96
Cii .00126
Zn .37
-2.50 mg/i
.00346 mg/i
.96 mg/i
57
BIBLIOGRAPHY
The toxicity to aquatic populaAnderson, P. D. and L. J. Weber.
1977.
tions of mixtures containing certain heavy metals.
Proceedings of
the International Conference on Heavy Metals 2:933-953.
Ariens, E. J.
1964.
Molecular pharmacology. The mode of action of
biologically active compounds. Vol. 1. Academic Press, New York.
503 p.
Baetz, R. A. and C. T. Kenner. 1975. Determination of trace metals in
foods using chelating ion exchange concentration.
J. Agricultural
and Food Chemistry 23:41-45.
Bliss, C. I.
1939.
The toxicity of poisons applied jointly.
Appi. Biol. 26:585-615.
Ann.
Clark, A. J.
1937.
In W. Heubner and S. Schuller
General pharmacology.
Vol. 4.
[ed.] Heffler's handbuch der experimentellen pharmakologie.
Verlag von Julius Springer, Berlin.
228 p.
Finney, D. E.
1971.
Probit analysis.
Press, Cambridge, London.
33 p.
4th ed.
Gaddum, J. H.
1953.
Bioassays and mathematics.
Reviews 5:87-134.
Cambridge University
Pharmacological
Hewlett, P. S. and R. L. Piackett. 1959. A unified theory for quantal
Biometrics
responses to mixtures of drugs: non-interactive action.
15:591.
1928.
Loewe, S.
Die quantitativen Probleme der Pharmakologie.
Physiol. 27:47.
Ergebn.
Muska, C. F. and L. S. Weber.
An approach for studying the
1977.
effects of mixtures of environmental toxicants on whole organism
performances. Recent Advances in Fish Toxicology: A Symposium.
pp. 71-87.
Plackett, R. L. and P. S. Hewlett. 1948.
Statistical aspects of the
independent joint action of poisons, particularly insecticides.
I.
The toxicity of a mixture of poisons. Ann. Appi. Biol. 35:
347-358.
Schild, H. 0.
Introduction to symposium on the mixture of drugs,
1961.
p. 282-285.
In H. DeJonge [ed.] Quantitative methods in pharmacology.
North-Holland Publishing Co., Amsterdam.
391 p.
Sprague, J. B.
El.
1970. Neasurement of pollutant toxicity to fish.
Utilizing and applying bioassay results. Water Research 4:3-32.
58
The error of determination of toxicity.
Trevan, J. W.
1927.
101:483-514.
ings Roy. Soc. London Ser. B.
Biology and Water Pollution Control.
1971.
Warren, C. E.
Saunders Co., Philadelphia.
434 p.
Proceed-
W. B.