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Variation in Natural Systems

Biology 1108L Laboratory Exercises: Variation in Natural Systems

Kennesaw State University Department of Ecology, Evolution, and Organismal Biology

LABORATORY Ecology: Variation within Ecological Communities

due to Secondary Succession


Observations: Forests within the same region often vary dramatically in species composition. This is easily observed within Cobb County, where the variable abundance of pines and hardwoods (deciduous trees) is readily visible in forest patches on campus or along the highway. One explanation for these differences comes from changes in species composition that occur over decades. In many ecosystems, species composition changes over time in fairly predictable ways. This process is known as ecological succession.

For many forest patches in this region, the last major disturbance was agriculture. By the early 20th century, most of the land in the region was farmed with cotton as the major crop. Severe soil erosion and infestations of the cotton boll weevil made farming unprofitable, and much of the land has slowly returned to forest.

Loblolly Pine seedlings are able to colonize bare mineral soil, grow tall very quickly, and grow well in full sun. However, seedlings cannot survive for long in the shade of other trees and are absent from the forest interior. By contrast, oaks and most other hardwood seedlings will only colonize areas where organic material has had time to accumulate under existing trees, and oak seedlings gain height more gradually over time while surviving for extended periods in the shade.

These characteristics mean that Loblolly Pines should densely colonize abandoned agricultural land much faster than hardwoods, but the understory will soon become too shaded for future Loblolly Pine seedlings to establish. As soon as organic matter such as rotting pine needle littler begins to accumulate, shade tolerant hardwood seedlings can begin to move in and will gradually overgrow the Loblolly forest as shown in the diagram below.

1st year 2nd year year 3 to 18 year 19 to 30 year 31 to 70 year 71 to 100 100+ years


Through secondary growth, tree trunks increase in diameter every year. Grown under similar conditions (soil nutrient, light, and water availability) a 100 year-old tree should have a significantly larger circumference than a 50 year-old tree. However, since hardwood seedlings can survive in the shade, there will always be a range of smaller trees regenerating under a hardwood forest regardless of the time since the last disturbance (see diagram below). While there should never be tree trunks as large as the 100 year-old trunks in the 50 year-old forest, some 50 year-old trees are expected be found within a 100 year-old forest. Therefore, the largest hardwood trees are often the best indicators of the age of a forest since the last major disturbance.

Trunk cross-sections from a Trunk cross-sections from a 50 year-old hardwood forest 100 year-old hardwood forest

Remnants of an old fenceline run through the Kennesaw State Arboretum, separating the forest into roughly an upslope and a downslope portion. Your task will be to investigate whether there is evidence these forests differ significantly in time since the last disturbance by determining if they are at different stages of secondary succession. We have measured tree size and type within the two forest sections to allow you to test the following predictions that we expect to be true if the forests are of different ages:

The forests will differ in the size of the oldest hardwood trees.

The forests will differ in the proportion of mature hardwoods relative to pines.

SAMPLING IN FOREST AREAS A AND B Due to the Covid-19 pandemic, you will compare your own data to data collected from the KSU arboretum by previous lab sections. To gather the data, the class was divided into two groups, and each group sampled plots in one of two different forest areas (upslope or downslope in the arboretum). Students established 100 square meter plots by stretching a 40 m rope out on the ground in a square with 10 m marks on the rope indicating the corners. Students made sure quadrats did not overlap a path. This is the same basic protocol you used for your section.

Data was collected from ten 100 m2 quadrats upslope and an additional ten quadrats downslope. Students measured the circumference in centimeters of all pine trees and hardwood trees with a single trunk greater than 25 cm at chest height found in the quadrats.

DATA ANALYSIS You will be analyzing data collected independently in two different years (2019 and 2021). The data is provided as an excel spreadsheet in D2L.

In order to determine whether there is a significant difference in the size of the oldest hardwood trees, you will be conducting a test with which you should be familiar from the Fish Lab earlier in the semester- the t-test. T-tests determine whether there is a significant difference between the mean of two different distributions. In this case, you will be comparing the mean circumference of the top 10 largest trees upslope vs. downslope. Next, you will do the same comparison

with the top 25 largest trees upslope vs. downslope. Usually in statistics, a larger sample size is preferable. In this case, we are trying to capture the oldest trees in each forest patch. Why might a larger sample size be worse than a smaller sample size in this case? Making a column chart comparing the top 25 tree circumferences from each forest patch (see below) may help you visualize the reason why.

As a control experiment, you will be comparing data from 2019 and 2021 within the same forest type. The chances that students set up their quadrats in the same 10 x 10 m spots in 2019 and 2021 is pretty minimal. However, when you compare upslope data from 2019 to upslope data from 2021, hypothetically you are comparing datasets from forest patches that should be the same age. Any difference you see should be due to random chance. Do you expect a high or low p-value if you compare upslope data from 2019 with upslope data from 2021?

To determine whether the forests differ in the proportion of mature hardwoods relative to pines, you will be employing a different test, the Fisher’s Exact Test. In this test, a two by two contingency table is constructed with two categories: upslope vs. downslope, and pines vs. hardwoods. The p-value in this test tells you the percent probability that you’d see the given distribution across the four categories in the table (upslope pines, upslope hardwoods, downslope pines, downslope hardwoods) by random chance. If the number of pines vs. hardwoods is contingent on whether you are upslope or downslope, there should be a low probability that the distribution is due to chance alone. In this case, more data might be better, so you will also test whether combining the data from 2019 and 2021 strengthens or weakens the hypothesis that the proportion of pines and hardwoods differs between the upslope and downslope forest patches.

Ecology Research Manuscript: This assignment is to be done individually; the assignment will be checked against the database for plagiarism. If you are retaking this course, using your own manuscript from a previous semester is still plagiarism according to university rules. Do not read anyone else’s manuscript or let them read yours.

Abridged Summary:

Title: 2 pts

Abstract: 3 pts- Brief summary of the experiment and conclusions

Introduction: 8 pts- Should at least a couple paragraphs for this manuscript explaining the background for the experiment and the questions asked by the experiment.

Materials and Methods: 5 pts- Reference the lab protocol, but also describe the methods of the experiment enough that someone could precisely replicate the experiment only by reading your manuscript.

Results: 13 pts- Column chart showing the sizes of the 25 largest circumference hardwoods in the upslope and downslope plots; p-values of 4 t-tests and 3 Fisher’s exact test results with tables showing mean and standard deviation for the t-test data and contingency tables for the Fisher’s exact test data.

Discussion: 14 pts- Interpretation of the t-test and Fisher’s exact test results and discussion of what the results mean relative to the questions posed in the introduction. Also discuss how the hypotheses could be further tested and how the experiments could be improved. Should be at least a couple good paragraphs.

Literature Cited: 2 pts- Properly cite the lab protocol and the websites described below.

Composition: 3 pts- Ability to clearly communicate scientific results in writing.

Detailed instructions on how to write the research manuscript

Title: Your title should be twenty words or less and must be different than the Lab Exercise name. Your title should be an informative and straightforward reflection of the factual content of the manuscript. 2 points

Abstract: Abstracts are a brief, one paragraph summary of the hypothesis, results, and conclusions of the manuscript. The abstract will be redundant with information elsewhere in your manuscript, but that’s OK. After reading the abstract, scientists can decide if they want to read the rest of the manuscript for more details. 3 points

Introduction: The Introduction gives necessary background to the reader of the manuscript, states the general hypotheses to be addressed, makes a brief statement summarizing the experiment to indicate how the hypothesis will be tested, and formulates specific predictions of possible results. The Introduction should specifically state the question or questions to be addressed by your study or experiments. You may wish to introduce these questions with a beginning phrase such as “In this report” or “In this experiment.” Most of the background and introductory information is already laid out in the lab protocol, but include anything you think is relevant background information and cite the lab protocol and the Duke Forest website listed below under Literature Cited. Your introduction should be a couple paragraphs long (background paragraph and hypothesis/questions paragraph). 8 points

Materials and Methods: Cite the lab protocol, but be sure to include a description of how the lab was conducted so that anyone reading the manuscript could easily replicate the protocol. Also briefly describe how the analyses were performed (t-test p-values were calculated in Microsoft Excel 2008 for Mac, etc.). 5 points

Results: In this section, you should summarize the data from the experiments without discussing the implications of the results or attempting to explain why particular results occurred. The data should be organized into tables and graphs. These should be labeled (e.g. Table 1, Figure 1) with a descriptive title. A brief sentence or two (legend) describing each table or graph should accompany the data.

For this lab, include the following in your results: 1. Tables showing the mean and standard deviation of the circumference of the 25 largest hardwoods in the upslope plots and the downslope plots for the 2019 data. 2. Make a column chart showing the circumferences of the 25 largest hardwoods (not just the means) for 2021 upslope and downslope data. To do this, highlight the data for the 25 largest hardwoods in both the upslope and downslope, then create the simplest type of column chart (first choice). Excel will automatically color the upslope and downslope data differently. Your chart should look something like this (but with 25 trees instead of 10):

Ci rc um

fe re nc e (c m )

10 Largest Trees Upslope


3. Results from 4 t-tests: a. t-test comparison (p-values) of 2021 data for the 10 largest hardwoods from upslope vs. downslope. b. t-test comparison (p-values) of 2021 data for the 25 largest hardwoods from upslope vs. downslope. c. t-test comparison of the 10 largest upslope hardwoods from 2019 vs. 2021. d. t-test comparison of the 10 largest downslope hardwoods from 2019 vs. 2021.

Be sure to use a 2-tailed test, type 2 (equal variance) for all t-tests.

4. Results from 3 Fisher’s Exact Tests: Perform Fisher’s Exact Test in order to determine whether the proportion of pines and hardwoods differs between upslope and downslope. To perform the test, you’ll need to go to one of the following websites (any of the three should give you the same 2-tailed p- value):

For this test, we are only going to be looking at the mature trees that reach to the forest canopy, so only count pines and hardwoods over 80 cm in circumference (approximately 10 inches in diameter). Simply enter the number of pines and hardwoods for upslope and downslope into the 4 squares (Upslope and Downslope can be ‘groups,’ # of each tree type can go in the ‘outcomes’) and run a two-tailed Fisher’s exact test for the following:

A. # of Pines over 80 cm and #hardwoods over 80 cm upslope vs. downslope for 2019 B. # of Pines over 80 cm and #hardwoods over 80 cm upslope vs. downslope for 2021 C. # of Pines over 80 cm and #hardwoods over 80 cm for both years combined

13 points

Discussion: Interpret your results and draw conclusions from them. Avoid using the words “believe” and “belief” in science writing, as these words can have unclear and varied meanings to different readers. Instead of writing “I believe the results demonstrate,” write “The results demonstrate.” Nothing can be “proven” beyond all doubt in science. The very nature of science is that new data could potentially come along that would require us to adjust our understanding of something we thought we had “figured out.ʼ As such, you should never set out to ʻproveʼ or demonstrate the ʻtruthʼ about something. Instead, set out to ʻtest,ʼ ʻdocument,ʼ or ʻdescribe.ʼ Instead of saying “our data proves the hypothesis,” say “our data supports the hypothesis.”

This section should have a brief restatement of your hypotheses and a discussion of how your actual results compare to your expected results. Did the results support your hypothesis? (discuss in terms of accepting/rejecting the null hypothesis) If your results were unexpected, you may wish to consider and address some of the following: Were the assumptions of the original hypothesis correct? Was the experimental design valid? While these issues should be considered, do not fall into the common trap of “looking for blame”. All experiments have some weaknesses in their design. However, for the purposes of this lab you should assume that your results are reasonable. Negative or inconclusive results can and will occur during this lab course. In such circumstances, you should suggest how further experimentation might clarify the areas of doubt in your data.

Focus on the following points for your discussion: • Describe whether or not the data and statistical tests support your predictions. • For any results that don’t support your predictions, give possible explanations as to why the results didn’t support your hypothesis; note any flaws in the lab procedure that may have influenced the results, but more importantly you should also mention possible biological reasons as to why the results might differ from what you predict. • Specifically address the following questions: Why did we use only the largest hardwoods for the t-tests rather than all the hardwoods? What do the number of small hardwoods vs. young pines (<60 cm) indicate? Why would you use only trees over 80 cm rather than all the pines and hardwoods for the Fisher’s exact test? Was the data similar between 2021 and 2019? Does that give more confidence or less confidence in the results? The t-tests in part 3 c & d in the Results section above are specifically testing how well the data was replicated from one year to another. Should there be a significant difference in measurements taken in the same forest area? Do you expect a high p-value or low p-value from those t-tests? 14 points

Literature Cited: For this lab, you should cite the lab protocol (Kennesaw Biology 2020. Biology 1108 Laboratory Manual. “Ecology: Variation within Ecological Communities.” Kennesaw State University, GA.), the website you used to perform the Fisher’s Exact Test, and the following website: . The Duke Forest website will give you a good general overview of old-field succession in the piedmont (Duke is in the piedmont of North Carolina, with the same soil type and very similar plant composition as Atlanta/Kennesaw), and you should even be able to predict how old the trees were in your plots. Here is how to properly cite the Duke website: Duke Forest at Duke University: Environment>>Forest Succession. 2020. Duke University. 10/29/2020. <:>. Here is how to cite the website for Fisher’s Exact Test: QuickCalcs: Analyze a 2×2 contingency table. 2020. GraphPad Software. 10/29/2020. <> In both cases, 10/29/2020 refers to the date you accessed the website. In general, it’s best to cite research published in peer-reviewed journals and not to cite web pages, but we’re making an exception here since most literature on piedmont forest ecological succession is pretty old and harder to access. 2 points

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