# 9.4: Process of Science - Predicting Drought Tolerance in Leaves

- Page ID
- 33470

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The object of this activity is to use characteristics of leaf anatomy that you have observed in the previous sections of this lab to predict how drought tolerant a leaf will be. To assess this, you will measure the amount of water lost by individual leaves when exposed to an arid (dry) environment.

## Materials needed

- An assortment of leaves of different shapes and sizes preferably collected from different environments.
*Note: These leaves should be collected at the same time to account for moisture loss, which will begin once removed from the plant.* - A ruler
- A digital scale
- A camera
- 1mm\(^2\) graph paper and pencils (optional - a computer with the program ImageJ)
- A calculator
- A contained, arid environment (e.g. an incubator at 30-37C)

**Observation:** Obtain a set of leaves of different shapes and sizes. Make observations about these leaves, including aspects that the leaves possess or lack, that you think might contribute to drought tolerance. Record your observations below.

**Question:** The question that has been posed for this experiment is “Which characteristics of leaves are associated with drought tolerance?”

**Hypothesis: **To narrow the realm of focus, you will be looking specifically at the surface area to volume ratio of these leaves. For your hypothesis, make a statement as to how you think the surface area to volume ratio will influence moisture retention. A null hypothesis (H0), which predicts no relationship between the variables of interest, has been included below.

**H0**: The ratio of surface area to volume will have no correlation to the moisture retention in leaves when exposed to an arid environment.

H1:

## Initial Data Collection

**Step 1**: Lay the leaves out as flat as possible on a solid background, such as a sheet of white paper, with a ruler aligned to one side of the paper. This will allow you to determine scale in your images. Make a label with your name (or group name), date, time, and "T0". T0 will denote "time zero", the state of the leaves before the start of the experiment.

**Step 2**: After you have arranged your leaves, ruler, and label, take a picture of them.

**Step 3**: Use the digital scale to obtain the mass of each leaf and record these values in Table \(\PageIndex{1}\).

Note

The density of water is 1 g/cm\(^3\). Notice that density is a measurement of mass divided by volume (D = m/v). Because leaves are 90% water, we can assume that they have approximately the same density, a 1:1 ratio of mass to volume. With this information, we can use the mass of the leaf as an approximation of the volume of the leaf.

**Step 4**: Calculate the surface area of each leaf using ONE of the following methods:

- Upload your picture to the computer and open it with ImageJ. Obtain the surface area and record these values in Table \(\PageIndex{1}\).

or

- Trace each leaf on 1mm\(^2\) graph paper. Count the number of squares fully contained within the tracing. Try to approximate the number of squares that are partially filled in by matching them to other squares that are also partially filled and counting these as one square. Take the number of completely filled in squares, add the number of approximated squares, then multiply this by 2 to get the total surface area (this accounts for both sides). Record these values in Table \(\PageIndex{1}\).

Note

Because the measurement of volume is using cm, it might be more useful to convert mm2 to cm2. Divide the number of mm\(^2\) by 100 to get cm\(^2\). To do this, place a decimal at the end of the number of mm\(^2\), then move it two places to the left.

**Step 5**: Use the values in \(\PageIndex{1}\) to calculate the surface area to volume ratio for unit volume of each leaf by dividing the surface area by the volume.

Leaf ID |
Volume (equal to mass, cm\(^3\)) |
Surface Area (cm\(^2\)) |
Surface Area : Volume Ratio for Unit Volume |
---|---|---|---|

Example: |
3.4 |
120. mm\(^2\) /100 = 1.2 cm\(^2\) |
1.2 / 3.4 = 0.35 |

**Experiment:** To test the drought tolerance, the leaves will be placed into a contained arid environment. After a set time, you will remove the leaves from the arid environment and determine the amount and rate of moisture loss from each leaf.

**Step 1**: Arrange the leaves on a tray and place in the contained arid environment. Set a timer or note the time. After 1 hour, remove the tray and take it back to your lab table.

**Step 2**: Use the digital scale to obtain the mass of each leaf in grams and record these values in Table \(\PageIndex{2}\).

**Step 3**: Calculate the percent of water lost in each leaf by using the formula below:\[((\text{Initial mass of leaf } - \text{ Mass of leaf after 1 hr in arid environment}) \div \text { Initial mass of leaf })\times 100 \nonumber \]

**Order of operations*: Do the subtraction in the innermost parentheses first, then divide the result by the initial mass, then multiply the result of that by 100.

**Step 4**: Calculate the rate of water loss from each leaf per minute by using the formula below:\[((\text{Initial mass of leaf } - \text{ Mass of leaf after 1 hr in arid environment}) \div 60 \text { minutes} \nonumber \]

Leaf ID |
Mass after 1 hour (g) |
% Water Loss |
Rate of Water Loss (g/min) |
---|---|---|---|

Example: |
0.9 g |
((3.4-0.9) / 3.4) x 100 = (2.5 / 3.4) x 100 = |
(3.4-0.9) / 60 = 2.5 / 60 = |

**Analysis:**

To interpret data, it helps to visualize it. In the space below, make a graph with __Surface Area : Volume Ratio for Unit Volume__ on the x-axis and __Percent Water Loss__ on the y-axis. Graph these values from tables 1 and 2 for each leaf. Do your data seem to follow any particular pattern?

Add at least 15 more data points from your classmates. Do your data seem to follow any particular pattern? Attempt to draw a line of best fit through your data points.

## Interpretation and Conclusions

Did water loss correlate to the surface area : volume ratio? Explain.

Are there any correlations between water loss and any of the other observed characteristics?

Consider any sources of error in this experiment and how you could improve upon the design.