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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 like this:




 Average # Dead


Comparison to the Control
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 don’t 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 Variability
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 shouldn’t 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 again?

Estimating the LC50
Bioassays 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.

Drawing 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 something like:

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.


Copyright 2009 Environmental Inquiry, Cornell University and Penn State University
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