I made a case study activity to use get my Biology students to think about the scientific method. This is research from my dissertation. Any feedback for improving it would be great! Feel free to use in your classroom, or just for fun!!
Here is a link to the pdf for easier printing
link to pdf
The Bigger the Momma,
the Better: A Case Study Reviewing the Scientific Method
Bowhead whales (
Balaena
mysticetus) belong to a group of
whales called mysticetes or baleen whales. Bowhead whales live in the Arctic
waters of Alaska, Canada, Greenland, and Russia. They used their baleen like a
strainer to filter out and capture krill. They are a very large and rotund with
heads that are 1/3 the size of their body (See picture above). They are also the
only whale that lives in the Arctic year-round. All females of baleen whales
are larger than males, on average. The reason for why baleen whales are
sexually dimorphic is unclear.
What are some observations made from this background
information on bowhead whales?
Why do you think female bowhead whales are larger than male
bowhead whales?
One hypothesis as to
why females are larger than males is called the big mother hypothesis. The big mother hypothesis is that bigger
mothers are better mothers because they can allocate more resources to their
young. In the case of bowhead whales, calves are 4 meters at birth, weigh 2000
lbs, and grow approximately 1 cm of length per day. During this growth they eat
nothing but their mother’s milk until they are weaned after around 12 months.
That’s a lot of energy being transferred! Bowhead whale milk is 50% fat, can
you imagine taking a gulp of milk that is 50% fat?
Baleen is made of keratin and is similar to the structure of
fingernails. Baleen grows from the gums of bowhead whales continuously. One
piece of baleen can have up to 20 years of growth from end to end. Reproductive
hormones such as progesterone will increase in circulation when a female is
pregnant and can be measured in baleen. Thus baleen can be used to detect
pregnancies in bowhead whales over time. By counting pregnancies in a piece of
baleen a pregnancy rate (number of years between pregnancies on average) can be
calculated.
A large piece of baleen from a bowhead whale.
What would you expect the relationship between pregnancy
rate and length of a female to be if the big mother hypothesis is accurate? Circle
the line that would best fit the hypothesis.
Here is some actual data as calculated by the hormones in
baleen.
Female Whales
|
Length (meters)
|
Pregnancy Rate
(years)
|
Age (years)
|
00B5
|
17.5
|
3.225
|
64.1
|
05S5
|
16.5
|
3.86
|
47.4
|
86KK2
|
17.2
|
4.52
|
53
|
87B5
|
15.7
|
4.625
|
51
|
87B6
|
15.7
|
3.5952381
|
53
|
88B11
|
15.6
|
4.4
|
|
88G1
|
15.7
|
4.25
|
46
|
88KK1
|
14.9
|
5.3889
|
39
|
90G4
|
15.2
|
4.104
|
|
11B6
|
16.9
|
3.09
|
71.3
|
86WW2
|
17.7
|
5.17
|
34
|
89B7
|
14.6
|
3.86
|
|
87N1
|
15.2
|
3.595
|
|
05S6
|
17.1
|
3.49
|
|
05S7
|
18
|
3.275
|
81.5
|
Graph the relationship between length and pregnancy rate by
making a scatterplot in the figure below
How does the actual graph compare to your proposed graph? If
it is different why do you think that is?
Results: The statistical significance of this correlation is
measured by a p-value. A p-value of less than 0.05 would mean that this
relationship is statistically significant. The p-value of the relationship
between pregnancy rate and length is 0.170.
Conclusion and interpretation:
Does the data from your results support the big mother
hypothesis?
Now Graph the relationship between calving rate and age
Results: The statistical significance of this correlation is
measured by a p-value. A p-value of less than 0.05 would mean that this
relationship is statistically significant. The p-value of the relationship
between pregnancy rate and age is 0.001.
Does the data from your results support the big mother
hypothesis? If not, what is an alternative hypothesis?
What conclusions can be made from this study?
What type of study is this?
Does this mean the big mother hypothesis is wrong (Explain)?
What would you change or do to improve this study and/or
increase the confidence of our results?
What is the importance of this study (what are practical
uses for this information)?
