Analyzing Daphnia Data
This page contains information on how to analyze your Daphnia bioassay.
It will help you make comparisons to the
control, analyze trends, examine
variability, and draw conclusions
about the toxicity of your tested compound.
First, at the end of the test period, count and record how
many Daphnia in each dish have died. Make a data table that looks something
Average # Dead
Next, take a look at your control group. These individuals
were not exposed to any toxic chemicals, and you might have expected all of
them to survive. If a few died, that's OK. With any type of living organism
there is variability in health, life span, and sensitivity to environmental
conditions. But if more than 20% of the Daphnia in your control group
died, you should take a look at the test conditions. Perhaps the dissolved
oxygen level dropped too low, or the individuals you started out with were
not young and healthy. If fewer than 20% of your control group died, then you
can go on to analyze your data for the NaCl treatments.
Analysis of Trends
Graphs are useful in interpreting the dose-response relationship. Make a graph
that indicates how many organisms died at each concentration that you tested.
Looking at your graph, do you notice any trends? For example, does the toxicity
of your test chemical appear to increase as the concentration increases, or
does it stay the same from one concentration to the next? Are there any data
that dont seem to make sense? If so, make a note of these and try to
think of any possible explanations for why they are different from your expectations.
A Look at
The means for each treatment tell only part of the story.
It is also useful to take a look at the individual data points (the number
of Daphnia in each of the three beakers) to get an idea how much variability
exists within each treatment. Try graphing individual data points for each
treatment. The wider the spread between data points, the greater the variability
within that treatment. The more variability there is within each treatment,
the less confident you can be that one treatment is different from another,
even if the means appear different on your bar graph.
Because of individual differences among organisms, you shouldnt
expect each animal to respond in exactly the same way. However, it is reasonable
to expect that the groups of individuals in each treatment will follow predictable
trends. Did replicate beakers have similar numbers of Daphnia at the
end of the five-day period? If your data are more variable than you think is
reasonable, you could look into the potential sources of this variability.
For example, did the animals appear to be healthy at the beginning of your
experiment, or were they already stressed? Think about whether any of the Daphnia
may have died for reasons other than poisoning by the chemical. What other
factors do you think might have killed some of them? Did you carefully follow
the protocol for making the
different salt solutions? Based on your experience with this bioassay protocol,
what ideas do you have for reducing variability if you were to run this experiment
Estimating the LC50
are designed to estimate the concentration of a test material that affects
50% of the test organisms. The concentration that kills half of the test animals
over a specified period of time is called the LC50 (this stands for lethal
concentration for 50% of the test population). From your graph, make an estimate
of the LC50 for your experiment.
It may be necessary to report the LC50 as a range rather than
a single number. For example, you might need to say that the LC50 is greater
than or less than the concentrations you tested, or that it lies somewhere
between two of your tested concentrations.
Conclusions about Toxicity
After you have estimated the LC50 for your
experiment, you will be able to use this number to make a statement about the
toxicity of the substance you were testing. Usually this statement will be
The LC50 for chemical X and Daphnia is in the range of __ to __.
If you have LC50 values for Daphnia exposed to other
chemicals, you can use these numbers to rank which chemicals are most toxic
to Daphnia. For example:
The LC50 for chemical X is a smaller number than the LC50 for chemical Y. This
means that chemical X can kill Daphnia at lower concentrations than
chemical Y. Therefore, I conclude that chemical X is more toxic to Daphnia
growth than chemical Y.
It is important to remember that Daphnia bioassays
are not designed to help you reach conclusions about toxicity to humans because
Daphnia and humans are likely to respond very differently to chemical
exposures. In order to use bioassays to predict toxicity to humans, you would
need to use organisms such as laboratory rats that are known to provide a better
model of human response to toxic chemicals.