Using the Vernier data collection system, we measured the O2consumption and CO2 production of Dubia cockroaches (*Blaptica* *dubia*) at 18, 24, and 36°C.

Unfortunately, our brand new oxygen probes seem to be quite inaccurate. I’ve included the data on the spreadsheet, but the data are not consistent and, therefore, not useful. This means that we can’t calculate accurate respiratory exchange ratios (the original goal of this exercise) but we *can* look at the effect of body size and temperature on metabolic rate.

Your assignment:

1. The data presented are metabolic rates expressed as ppm per second. To be useful to compare to other studies, they need to be converted into microliters of CO2 per gram per minute (µl·g-1·h-1).

This involves three steps:

a. The ppm unit is parts per million: a ratio of how many molecules of gas were exchanged per million molecules of air in the chamber. The chamber has a 250ml volume so you can use a simple ratio to convert the ppm to volume of gas.

b. Next you simply divide this value by the mass of the cricket. (This value is on the raw data spreadsheet on the right-hand side.)

c. Finally, you need to convert the seconds (remember the original data in ppm/s) to hours. If a certain amount of gas is produced in one second, how much would be produced in one hour? Simply multiply the original value by 3600 (60 minutes in an hour, 60 seconds in each).

Modify the raw data spreadsheet to do this calculation so the data are in µl CO2·g-1·h-1 and label the calculation so your TA can find it!

2. Next let’s look at the effect of body size on metabolic rate. Graph the mass-specific metabolic rate at 24°C (calculated in #1 above) against mass (on the X-axis since it is the independent variable) for each of the six crickets. Save this graph in the“Raw data” Excel file. Calculate “b” in the formula M=a·Wb) as we discussed in the class. There are several ways to do this: you can log-transform the data and use a linear fit to the data (actually gives you b-1, right?) or try a non-linear fit to fit b.

Is the value of “b” what you expect? Compare to the values of “b” presented in your textbook.

3. Finally, let’s look at the effect of temperature on metabolic rate. Add another graph to the Excel file that compares mean mass-specific CO2 consumption (with error bars for standard error) at each temperature. Based on these means calculate the Q10.

Q10 is the __factor__ by which metabolic rises with an increase of temperature by 10°C. We didn’t measure metabolic rates at any two temperatures separated by 10°C, did we? Figure out how many times metabolic rate increased over an 18°C span (that is, from 18 to 36°C) and use a ratio to estimate how much metabolic rate increased over 10°C.

What was the Q10? Compare this value to a Q10 from the scientific literature or a book. Does it match what we expect? Why or why not?

Upload your update Excel file (with your name in the title) and answers to the questions on or before Wednesday, May 6th).

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