BISC209:Assignment 209 Lab3

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Wellesley College-BISC 209 Microbiology -Spring 2012

Partial Results Section

Due at the beginning of Lab 4.
Your assignment will be to show how your enumeration data addresses one of your investigative topics: Abundance of Microorganisms in a Soil Community. This draft partial results section of a scientific paper will include a table with a title and legend and data analysis in the form of an independent narrative. Your goal is to show a reader who is unfamiliar with these experiments and who has read no other part of the paper how you assessed abundance, what you concluded, and what those conclusions mean in terms of your overall investigative goals. Be careful not to include too much methods detail when you explain the essentials of the experimental design. The reader does not need to know exactly how to perform these tests. Begin each section of results with this structure: "In order to find out_________, we did__________."

In this assignment, you should focus on the quantitative work we've completed that addresses enumerating microorganisms in your soil community. You used two different methods, a colony count and a direct count. The former is a culture based method and the later is culture independent. Did we expect to get the same number using these two methodologies? Did you? Do you have evidence to support the "Great Plate Count Anomaly"?

Before you begin to write, you should objectively analyze the data collected by your team to determine what your data says about the abundance of microbes in your soil community. What's the main conclusion? Is there an "abundance" of microbial life in soil? Are you astonished by the number of microbes in ONE GRAM of soil?!!!! How will you show and write about these data to stress that mind-boggling abundance? The table should visually allow the reader to get the main points at a glance. The enormous numbers are the main point but there are other findings that are important here, too. You did two measurements of the same thing using different methods. If our findings support the Great Plate Count Anomaly, you probably got a substantially higher number in the direct count than in the colony count. How can you help your reader to see that comparison? How do you want to write about it in the narrative to stress the important point that culture based methods of ennumeration miss huge numbers of microbial members of your community? Rather than just repeating what the reader can see in the table (the counts), you should explain what's important about these number comparisons, eg. that the culture independent count found ____% more microbes than the culture dependent count. That is a good synopsis of the findings but don't forget to make conclusions rather just describing the data or findings. Help you reader see that the importance of finding a substantially higher number of microbes in the culture independent method (the conclusion) is that these findings support the idea that there are a significant proportion of soil microorganisms that have never been studied because they can't be cultured. Are there any other points (conclusions) that are important to make about these findings? Do you think that your direct count is completely accurate and that this is the "true" number of microbes in that soil community/gram? What are the limitations of the direct count method that you have concluded is the more accurate? Is it important that your reader understand that even the direct count is only an estimation? Yes, it is, but be very careful NOT to trash your experimental design when you try make this point in your narrative.

Your data is unlikely to be a perfect fit with published estimates of numbers of culturable or total soil bacteria, but that does not mean that you didn't get the "right" answer for your soil community. In science it is rare to be able to know if your findings or quantitative estimates are "accurate". Unlike a lot of your lab experiments in other courses, your instructor doesn't have the right answer. No one does. There is no reason to think that your answer, however different from previously published estimates, isn't accurate, within the limitations of the enumeration methods used. """DO NOT trash your data or your experimental design in your narrative, but DO (BRIEFLY) make your reader aware of limitations in the methods used when you explain your conclusions. Do NOT have a "sources of error" section where you stress all the difficulties or the things you did wrong. This is not a lab report; rather, think of this as part of a research report that might, eventually, be sent to a journal for publication. No one wants to publish (or read) a report of a lousy set of experiments that couldn't conclude anything. Realize that all experiments have their problems and no data are perfect. Our goal in science is NOT to "prove" a hypothesis but to objectively see whether or not our experiments and our data from them allow us to form some answers to the questions that drove the investigation. If we don't have perfect confidence in our conclusions because our experimental design has limitations or is imperfect, that's pretty much the universal situation in science. We tell the truth as best we can figure it out from our data--- using "hedge words" in our conclusions that reflect our confidence in our findings, ie. "it appears likely that______; ________ seems to indicate that____; it is possible that_____,although______; it appears as though____, but_____; etc."

Insert your table at the end of the paragraph where the table is first introduced. The table should have a table number and a title that summarizes the table. The table number and title are found ABOVE the table. If the data collection methods or processing is not obvious (for these data it is NOT obvious), there should be an explanatory legend that is found BELOW the table, separated from the table with parallel lines below and above the information it includes. You should look at published journal article tables that model this structure. The legend explains the essentials of how the data were collected and processed into the form shown (you will need to explain what was counted and to give the formulas for converting counts to # of microbes/gram of dry soil, which means you will also have to explain how you determined the conversion factor from wet to dry).

Your data analysis/results section must be written completely in your own words (not the wiki's) and it should include only what is necessary for a new reader to follow your data analysis from question to conclusion. You may consult with your teammates or others to discuss your data and its meaning, but all writing must be your own.

There are many ways to write a good Results analysis. To get a feel for how a data analysis is written as a Results section in a scientific paper, take a look at the results section in a variety of published science research reports such as those provided in your Reference folder. The Wellesley library has electronic subscriptions to many other journals that model this concept well. Also refer to the “How to Write a Scientific Paper” section in the Resources section of this wiki. There you will find valuable information on how to format figures/ tables with proper legends and the basics of how to write about data.

Remember that the Resources section of the wiki has a lot of valuable information on every section of a research report. You should read carefully the information there on the Results section, including on effective figure and table design and how to construct a proper legend.

Good luck!
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