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Introduction
One of the basic functions carried out by trees in ecological systems is photosynthesis. Trees combine water, carbon
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dioxide and the energy in sunlight to produce energy stored as glucose. Oxygen is produced as a by-product. Trees differ in
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height, therefore leaves at the top and the bottom of trees receive differing amounts of light. Leaves farther down the tree will
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receive less sunlight than leaves at the top of trees because at least some of the energy available has already been absorbed by
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the upper leaves. Since leaf surface area determines how much energy a leaf might obtain, leaves receiving a lower level of
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energy would need to have a larger surface area to produce the same amount of energy as leaves receiving higher levels of
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energy. Given the hypothesis that leaf surface area is related to photosynthetic production, it is predicted that leaves on the
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upper branches of trees will have a smaller surface area than leaves on the lower branches of trees. To test this prediction,
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leaves will be randomly obtained from the upper and lower limbs of trees, an estimate of the surface area of each leaf will be
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obtained, and the means values compared to determine if there are indeed differences.
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Methods
The independent variable in this experiment is the location from which leaves were obtained and there are two cases
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of the independent variable, leaves obtained from upper branches and leaves obtained from lower branches. The dependent
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variable is leaf surface area. To insure that there are no confounding factors, all leaves were obtained from the same type of
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tree (tulip poplar), in the same forest and at the same time of year. Different types of trees have differing leaf shapes and these
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differing shapes might affect estimates of the surface area of the leaf. Trees growing in different forests might be exposed to
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differing soil types and precipitation levels and since these factors affect nutrient availability, leaf growth rates may differ
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between forests, which could also influence surface area. Finally, leaves may continue growing in size throughout the growing
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season, therefore collecting leaves at differing times may also influence the surface area of the leaves sampled. By controlling
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these factors, differences due to differing leaf shapes, differing environmental conditions, and differing leaf ages should not
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affect the outcome of the investigation.
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Leaves for this study were obtained from tulip poplars in the Kennesaw State University Arboretum. Leaves from the
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uppermost branches (defined as branches that were in full sunlight at the top of the tree) were obtained by climbing with ropes
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to the top of the selected trees and clipping 10 random leaves from these branches with a pair of scissors. Leaves from the
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lowermost branches (defined as branches that were in the shade and could be reached without climbing the tree) were also
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obtained by randomly selecting 10 leaves from the lowermost branches and clipping them with a pair of scissors. A total of 10
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trees were sampled, giving a sample of 100 leaves from uppermost branches and 100 leaves from lowermost branches.
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Measurements for estimation of leaf surface area were obtained using a metric ruler. Leaf length was measured from
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the point where the stem is connected at the base of leaf to the uppermost edge of the leaf surface. Leaf width was measured
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along the widest point of the leaf perpendicular to the leaf length. All measurements were made to the nearest 0.1 centimeter.
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Leaf surface area in square centimeters was estimated by multiplying leaf width by leaf length. To determine if there were
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differences in leaf surface area between uppermost and lowermost branches, a two-sample t-test was used to compare the mean
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surface area values of the two samples.
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Results
The purpose of this study was to determine if leaf location influences leaf surface area. Surface areas were estimated
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from 100 upper branch leaves and 100 lower branch leaves. The mean surface area of upper branch leaves was 1.5 square
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centimeters greater than the mean surface area of lower branch leaves (Figure 1), however the standard deviation for upper
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branch leaves was also much higher than that of lower branch leaves (Figure 1), indicating the individual values from the two
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samples overlapped considerably. The t-test comparing the two sample means produces a p-value of 0.15, indicating that the
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difference in mean surface area between the two samples is not significant.
Figure 1. Surface area of tulip poplar leaves as a function of location.
Mean surface area (+/- one standard deviation) from 100 upper branch
leaves and 100 lower branch leaves are presented.
Mean Surface Area (sq. cm.)
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Lower Branches
Upper Branches
Leaf Location
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Discussion
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The purpose of this study was to determine if leaf location has an effect on leaf surface area. Since the independent
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variable was leaf location, ten leaves were obtained from the upper and lower branches of ten tulip poplar trees in the KSU
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Arboretum for a total sample size of 100 leaves from each of the two locations. The leaves were located at markedly differing
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points in each tree sampled, therefore the leaves from the two locations should have received differing amounts of solar energy,
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providing a reasonable test of the underlying hypothesis for this experiment. The dependent variable was leaf surface area in
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square centimeters and this was estimated by measuring the length and width of each leaf at a clearly defined point. While
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length and width are reasonable measures for obtaining the surface area of a rectangular object, it was noted that the leaves
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obtained were irregular in shape and therefore the estimate of surface area may have been inexact. An alternative measure of
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surface area that accounted for the irregular shape of the leaves might have been more appropriate. All leaves were obtained
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from the same location, the same species of tree and at the same time of year to control for confounding factors that might
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influence leaf size.
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The hypothesis for this experiment was that leaf surface area influences photosynthetic activity and that leaves lower
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on the tree should have larger surface areas to compensate for the lower level of solar radiation they receive. If the hypothesis
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was correct, leaf surface area of lower branch leaves should have been greater than leaf surface area of upper branch leaves.
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The data obtained in this experiment contradicted the expected result, as leaf surface area of upper branch leaves (mean = 16.7
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cm2, standard deviation = 3.7 cm2) was greater than lower branch leaf surface area (mean = 15.2 cm2, standard deviation = 1.1
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cm2). A t-test indicated no significant difference between means (p = 0.15) and therefore the null hypothesis of no significant
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difference cannot be rejected. Although there were no significant differences in mean leaf area between upper and lower
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leaves, the descriptive statistics suggest that leaf size is more variable on upper branches. Although the original hypothesis
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cannot be supported, the data obtained suggest there are factors influencing the energy used in creating new tissue between
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upper and lower branches.
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An underlying assumption in this experiment was that trees will compensate for reduced solar radiation by increasing
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the surface area of leaves on lower branches. Given the results obtained, this assumption may be incorrect. Further work on
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this question should address the mechanisms plants use to balance the energy obtained in photosynthesis with the energy used
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in creation of new tissue.
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Introduction:
The introduction should include:
1. A description of the topic/phenomenon you are examining
• Start out with the bigger picture; describe the natural occurrences you are investigating; clarify any concepts or
terms that are important.
• Describe specific observations or premises that are relevant to your study. These could include observations or
results made by others (be sure to cite the source) and/or yourself. The goal is to provide the basis for your particular
study. What has led you to believe that a relationship exists between the independent and dependent variable of your
study?
• Why is it of interest or importance to scientists?
2. A statement of your hypothesis or purpose and your prediction(s).
3. A very general description of how the prediction(s)s will be tested (e.g. a summarized version of the experimental design).
• For example, if you examine the effect of temperature on a molecule's ability to function note the specific molecule
selected for examination and why, the temperatures used, and how the molecules ability to function will be assessed.
Methods:
A good methods section should include:
1. Statements presenting the independent variable (and treatments/cases if this applies) and dependent/responding variable and
how they will be selected or applied and measured/monitored.
2. Statements presenting important controlled variables. An explanation as to why, specifically, it was important to control
each given variable and how it was controlled should also be included. Do NOT simply state that the factor, if not controlled,
would affect the outcome of the study – note why and/or it would affect the outcome.
3. A description of the experimental procedures and data collection. Do NOT number steps!
• Write only in enough detail that someone else could easily repeat the experiment.
• Details on how to use an instrument (e.g. a micropipettor or spectrophotometer) are NOT necessary.
• Do not make reference to I, we, Dan, etc. (e.g. write in the third-person style)
• Use past tense. This section describes what you did. If you followed a lab procedure written for you, you should
reference it in this section. DO NOT list all solutions and materials used.
• Indicate which, if any, inferential statistical tests you used.
Results
A good results section should include:
1. All data from experiments:
• Preface individual experiments (sometimes more that one experiment is performed) with a brief statement
(s)reminding reader what was being examined. This prepares the reader for the data you are about to describe. Then
follow with a data summary (as described next).
• Verbally describe the highlights of the data collected or summarize the data collected. Refer specifically to table
and/or graph of data. Essentially, you are telling the reader what they should see, or what is important, when they
look at a given table or graph. Examples: "The data from this study, shown in Table 1, show ......" or, "As shown in
Table 1, ....
• Present data in tabular OR graphical form whenever possible. Each table and graph should be numbered and titled.
Include a descriptive caption for each. Generate tables with the software being used to prepare the report. Generate
graphs with a graphing software program. If the data in a table are the same data used to generate a graph, DO NOT
include both in the lab report. Choose one format.
• Tables and graphs should immediately follow the paragraph that makes reference to them. In other words, they
should be included in the body of the report, rather than attached on a separate page(s) at the end.
2. The results from any statistical analysis (if used). Statistical tests should be used whenever possible because they make
interpreting data and drawing conclusions easier. The kind of analysis should be mentioned, as well as any important features
that will help the reader to evaluate the outcome of the analysis (e.g. a probability value, number of samples used). For
example: "A t-test comparing these two means suggests that they are significantly different (p< 0.05 or p = 0.001, n=5).” The
results section SHOULD NOT INCLUDE conclusions and inferences. It should only include observations.
Discussion
A good analysis/discussion should include the following. DO NOT treat these recommendations as a sequential list. Instead,
structure your discussion in a way that each of these points is included in the body of the discussion.
1. A critique of the experimental design. Establish that the experimental design(s) tests the hypothesis, or is appropriate for
testing the hypothesis.
•Identify and critique the independent variable for the study. For example, analyze the manner in which it was
selected or applied, note the number of cases/treatments that were used and comment on whether you feel they were
adequate, note the number of replicates that were used/performed for each case/treatment, note if application of the
independent variable trouble free, etc.
•Identify and critique the dependent variable. Comment on whether it was appropriate (e.g. could some other factor
have been measured and perhaps been more appropriate). Explain how it was measured and then comment on if this
was trouble free.
•Identify and explain important controlled variables you used. Why was it necessary to control each of these
variables. Do NOT simply state that a variable was controlled “because it could impact the outcome of the study.”
Comment on factors that you should have controlled but didn't.
2. Identification and explanation of any important assumptions you made (note if, after the fact, you feel any were incorrect).
3. Use of data to determine whether the hypothesis is supported or refuted:
• Begin by restating the hypothesis and noting whether the data obtained support/do not support this hypothesis. Do
NOT state that the hypothesis was “proven” to be correct or true.
• Describe how the hypothesis was tested (in general terms), the kind of results that you would need to support the
hypothesis, and those that would refute/not support it. This is essentially your prediction(s) (e.g. what action(s) were
taken and what you expected to see if the hypothesis were true).
• Cite specific relevant data that you collected to support your position.
• Mention any statistical analysis performed to further support your position.
• Relate data to a conclusion (e.g. make inferences based on the evidence collected). Describe/explain a significant
implication(s) that can be drawn from the study.
4. Comment on how your results compare with that of others. This is one place where you would bring in outside
information/sources. Mention a logical next step/experiment or given any problems or limitations you experienced with the
experimental design or associated methods, what would you do differently if you were to do the experiment again?