Lab 9 pre-lab.

In today's lab, you will learn how we can best use the type of data we collected next week. Biodiversity can evaluated in many ways and each measure, metric, and index tells us something slightly different about the biodiversity in a given community. Statistics play an important role in biodiversity measurement and ecological work in general. This lab will also introduce you to another simple statistical test, called a t-test. It relies on some of the same principles as the chi-square test with which you are already familiar. You will use this new knowledge to finishing our exploration of watershed health and bioindicators and you will put it all together in a scientific manuscript. 

• Introduction
• Do you know enough?
• What we will do in lab?
• LABridge

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how is biodiversity measured?

Biodiversity can be measured at various levels (genetic, species, and ecosystem) and assessed in different ways (review the primary components below). 

• Species abundance describes the total number of individuals of a particular species type or across all species' types. 
• Species richness describes the number of different species present in an area (more species = greater richness). Determine the species richness “S” by counting the number of species of in the area of interest. Suppose there are 10 orchids, 20 roses and 100 marigolds in a garden. The species richness of flowers in this garden equals three (S = 3).
• Species evenness describes the relative abundance of the different species in an area (similar abundance = more evenness). Evenness can be calculated using other biodiversity indicators, but often it is just rated in reference to another area (e.g., as higher or lower in comparison).

Be sure you know all the bold-faced terms and could calculate the biodiversity metrics as in the example.

Do you understand why some species make good bioindicators? Be sure to read over the example graph.

Both these communities have the same abundance (16 trees). They both have the same richness (4 types of trees = 4 species). But they have different evenness. Community 1 has an "even distribution" of species (all four are in the same amount), whereas community 2 is dominated by one species. Click to enlarge.

Examples of anthropogenic disturbances (human-caused), from neonscience.org.

DO you know enough about Analyzing biodiversity?

Because biodiversity can be measured in multiple ways, an index is often use so that one number can provide a good metric for biodiversity across a community. These indices often include measures of both richness and abundance, and therefore take evenness into account. Simpson's Biodiversity Index (SDI) is a common such measure. It ranges from 0 to 1, where high scores (close to 1) indicate high diversity and low scores (close to 0) indicate low diversity. One of the more the useful aspects of the index is to compare two sets of data to see which is more diverse. For example, if one region has an SDI of 0.5 and another has an SDI of 0.35, then the region with the SDI of 0.5 is more diverse. Let's work through the example below.

Example data collected from a water sample.

Simpson's Diversity Index formula, where n = number of individuals of each species N = total number of individuals of all species

The example data were collected from a water sample and show the abundance of five species (A thru E). This community would have a richness = 5. With low evenness as it appears to be dominated by taxa A and B. We can use the SDI as a general calculation to solve for diversity (D). The formula is provided and some of the initial calculations are shown in the table. 
​According to the table:

• There were five species were found in this water sample.
  • 9 individuals of species A (n=9)
  • 7 individuals of species B (n=7)
  • 2 individuals of species C (n=2)
  • 1 individual of species D (n=1)
  • 1 individual of species E (n=1)
    
  • Total there were 20 individuals of all species combined (9 + 7 + 2 + 1 + 1), so N=20

Complete the calculation:

• Numerator = sum of n(n-1) = 72 + 42 + 2 + 0 + 0 = 116
• Denominator = 20 x (20-1) = 20 x 19 = 380
• D = 1 - (116/380) = 0.69

It is also possible compare the biodiversity of two locations with statistics. In this lab, you will be using a paired t-test to assess the biodiversity of two different water samples, based on the richness and abundance of protists. You will be provided with an excel sheet, a demonstration video on you tube, and a t-test calculator to use online. But, read on to see why we need statistics in the first place...
Different is different. Why do we need to run a t-test? 
We look for patterns to help us understand the natural world. As we do so, we are fighting our own human tendency to see patterns where none truly exist, and to take what we see in a specific context and try to apply it more broadly.
Let’s say you notice that within your friend circle, those who regularly eat breakfast did much better on their first BIOL 122 exam than those who skipped your morning meals together. You might then assume that somehow, eating breakfast is causing the better grades. But! Consider the following:

Review our songbird scenario for an example using a t-test for statistical analysis.

• How much of a difference in test averages should there be between breakfast-eaters and breakfast-skippers for that to be true? 90 vs. 60? 80 vs. 70? Reasonable people could disagree.
• How often do you need to see this relationship for that to be true? On exam 1 and 2? On all the BIOL 120 exams? Reasonable people could disagree.  

Statistics solve this problem. Using the principles of probability, they help us parse what we observe from randomness (chance alone) vs. meaning (a real difference, or a real relationship). Statistics tell us how likely we would be to make the same observations we have made, if chance and randomness were the only drivers. If the probability is very low (<5%), we refer to these patterns as significant.

Be sure you have worked through the SDI example and that it makes sense.

You need a basic understanding of Excel. Use the tutorials in our library (if needed) and be sure you have it on your device.

Review the songbird example for a general understanding of how a t-test works.

What will we do in lab & how will we do iT?

Lab 9 contains three exercises and an introduction to your next assignment.​​

1. You will calculate the species abundance and richness of your samples and the SDI.
2.  ​You will conduct a t-test.
3. You will review your hypothesis and determine which metrics to use.
4. You will begin work on your manuscript.

​Last week, you collected diversity data on water samples from two streams (stream A and stream B). This week we will use those data to draw conclusions about the health of each watershed. 

Read this article!

If you feel confident with this material, click the bridge icon below and navigate to Blackboard to take the LABridge for this week. Be ready to be tested on this material before you go to the quiz, and make sure you have your Lab Notebook Guide ready to submit as well.

Click here to get to WKU's blackboard to take your LABridge for this week.

Lab 9 Protocol

​Following this lab you should be able to...

• Use the scientific method including hypothesis creation, data collection, and analysis with a t-test
• Calculate common diversity indices including: richness, abundance, and Simpson's Diversity Index
• Create tables and graphs for inclusion in a manuscript
• Produce a scientific manuscript​

Overview. In today's lab you will analyze your data from Lab 8, draw some conclusions, and begin working on your manuscript.

1. Exercise I. You will calculate species richness and abundance in your samples, as well as the Simpson's Diversity Index (SDI).
2. Exercise II. You will explore your data further using a t-tests.
3. Exercise III. You will review your hypothesis and determine which metrics use and how they should be visually represented.
4. Exercise IV. Begin work on your manuscript.

• Exercise I
• Exercise II
• Exercise III
• Exercise IV. Manuscript

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Exercsie i. Calculate metrics of biodiversity

Procedure. Calculate biodiversity metrics (richness, abundance, and SDI)

1. You will be calculating metrics from your raw data.
2. Open your Biodiversity Data Collection Table from last lab. Tab 1 contains your raw data.
3. Go to tab 2, labeled "Calculations," in your spreadsheet. Transfer your data (in the correct form) to tab 2. The yellow cells will auto-generate.
4. Complete the indicators of diversity table using all the data. Refer to the pre-lab if you need a review on how to calculate these values.
5. Remember: Species abundance describes the total number of individuals of a particular species type or across all species' types. 
6. Remember: Species richness (S) describes the number of different species present in an area (more species = greater richness). Determine the species richness “S” by counting the number of species of in the area of interest. Suppose there are 10 orchids, 20 roses and 100 marigolds in a garden. The species richness of flowers in this garden equals three (S = 3). 
7. Remember: Species evenness describes the relative abundance of the different species in an area (similar abundance = more evenness). Evenness can be calculated using other biodiversity indicators, but often it is just rated in reference to another area (e.g., as higher or lower in comparison).
8. The Simpson's Diversity Index formula is provided in the sidebar.
9. Complete your Lab Notebook Guide for Exercise I.
   
10. Ask your TA to review your table before proceeding.

Simpson's Diversity Index formula, where n = number of individuals of each species N = total number of individuals of all species

Exercise II. Conduct a T-test

Procedure.​

1. Review and discuss the "Songbird Scenario" (in the sidebar) with your group. It is very similar to the types of questions we are asking about protist diversity and watershed health.
2. You will need to reorganize your data to perform a T-test. Open your data sheet from the last lab. Add two tabs: one labeled "Combined Data" and another labeled "T-test."
3. You have already made these calculations. Simply copy paste the "total" columns for each stream into a new table on your combined data tab. See the example table in the side bar. Your tables should be set up in a similar way. 
4. Paste your new tables into your Lab Notebook Guide.
5. Now you're ready to run your T-test.  Alternatively, each step is detailed below. 
6. Copy/paste JUST your species data into the t-test tab (the greyed-out cells in the example in the sidebar). These are the data we will be using to test if the diversity is significantly different between these two streams. PLEASE NOTE: When you paste data in excel, be sure to click the "text only" option. To do this, right after your click (ctrl+v), click the dropdown arrow next to the control box and select "values only" as shown here.
7. Open the t-test calculator by GraphPad. The video link in the sidebar will walk you through these steps. 
   1. Under number 1: Chose the "Enter or Paste..." option.
   2. Under number 2: Select the "Paired T-test." This means the test will compare the number of amoeba in stream A to the number of amoeba in Stream B -AND- the number of euglena in Stream A to the number of euglena in Stream B...and so on. They are "paired" because they are the same species. 
   3. Under number 3: Label "Group 1" as "Stream A" and "Group 2" as "Stream B." Go back to your spreadsheet combined data tab. Copy-paste the column of species counts for Stream A (from your combined data tab) into the corresponding calculator column. Repeat the same steps for Stream B. Now you have successfully entered your data into the calculator.
   4. Under number 4: Click "Calculate Now."
8. The results of your t-test will quickly appear. Copy/paste all of them into your t-test tab in Excel. You should also take a snip of table provided by the calculator and paste it into Excel.
9. Now. What do these results mean? When we complete a statistical test, we are actually testing our null hypothesis (that there is no difference). We seek to reject the null, which conversely supports the idea that there is a significant difference. We are looking for three things in order to do that:
   1. ​The p-value: If it is less than 0.05, we can reject our null hypothesis.
   2. The t-vale: This is our test statistic. The higher it is, the bigger the difference between Stream A and Stream B. 
   3. The means: Remember, this test is actually testing the mean abundance for each species in these two streams. Whichever stream has the highest "mean abundance," we can interpret as having "more diversity." 
10. What do your data show? Complete Exercise II. in your Lab Notebook Guide. 

• If your test shows a significant difference, report the results as follows: The protist diversity, as measured by a paired samples t-test, was significantly higher in Stream ? vs. Stream ? (t = 2.6496, p < 0.05, df = 8).
• If your test shows does not show a significant difference, report the results as follows: The protist diversity, as measured by a paired samples t-test, was not significantly different in the two streams.

Review our songbird scenario for an example using a t-test for statistical analysis.

What your combined data tables should look like, with example data.

Click for link to t-test calculator.

link to video instructions

Exercise III. Further Analysis

You now have several different measures of "biodiversity" in our two streams. You can use all your data and calculations, or strategically match them up to your predictions. ​

Procedure.

1. Discuss what other biodiversity indicators you will used, based on your hypothesis.
2. You will need to create individual predictions for each test to match your hypothesis. For example: "We predicted species richness and the SDI would be higher in stream X."
3. Be sure to doublecheck all your calculations, especially your SDI. Here's a good SDI calculator to check your work.
4. Think about what your data show and discuss any conclusions with your group.
5. Think about the ways you would display these data as tables.
6. Think about the best ways to display these data as graphs. Two examples as provided below.
7. Complete Exercise III in  your Lab Notebook Guide.

SDI Calculator

You can represent your data as needed to adress your hypotheses in whatever way you see fit. These are just some examples.

Exercise IV. Scientific Manuscript

You will be producing a scientific manuscript to communicate your results for this research project. Remember, communicating your results is a vital part of the scientific method; without this step, the field could not grow. 

• Review the step-by-step guide from the Pre-Lab, also posted in this sidebar.
• You already have much of what you will need, especially for your results section.
• I have included some starter references in our library also.
• Use the template provided. It includes a general description/outline for each section, specific to our current topic.
• Be sure to doublecheck all your calculations, especially your SDI. Here's a good SDI calculator to check your work.

​Submission Guidelines

• You can work together or individually on this project.
• You will have the option to submit a draft for review in one week. The final will be due in two weeks.
• Everyone must submit a final manuscript individually and one time for points.
• You must submit as a word document only through Blackboard.
• Late submissions or emailed submissions will not be accepted. 

​Formatting Guidelines

• ​Title at top of page in bold 14 pt. font.
• Authors names go directly under the title.
• Times New Roman 12 pt. font throughout manuscript.
• Single spaced throughout.
• 1 inch margins with 0pt above and below text.
• Paragraphs are not indented but start on a new line after a carriage return, or "enter" (see template).
• Headings in bold (Abstract, Introduction, Methods, Results, Discussion) and one a stand-alone line.
• Sub headings in bold italics with a period and in-line with text.
• Pages should be numbered.
• Titles go above tables and should stand alone.
• Figure captions go below figures, should stand alone, and include source if applicable.
• Write mostly in active voice.
• You should have a minimum of 8 references (in-text and in your reference section).Use the same formatting as for your poster. Directions are in our library as well. 

Read this article!

Manuscript template & outline

Manuscript Rubric

captions, titles, & citations

Faculty Spotlight: Dr. Scott Grubs

Scott Grubbs specializes in food web and nutrient dynamics of karst riverine watersheds and the taxonomy, systematics, and biogeography of stoneflies (order Plecoptera). Stoneflies are widely recognized as valuable bioindicators of stream health. The are used, along with Ephemeroptera (mayflies) and Trichoptera (caddisflies) to calculate the EPT index. Streams with higher numbers of these species, and higher EPT index values, are considered healthier and less-impaired. A few of Dr. Grubb's recent publications are available below.
Students who are interested in this work, please email @ [email protected].
Assorted Publications: 
A surprising rediscovery and description of a new species of Soyedina Ricker, 1952 (Plecoptera: Nemouridae) from Great Smoky Mountains National Park...
An update on the stonefly fauna (Insecta, Plecoptera) of Maryland, including new and emended state records and an updated state checklist...