Introduction

This website is designed to teach ecological concepts and principles in an agricultural setting, to give you a much more in-depth and practical experience than you can glean from a textbook alone. You are challenged to view the fields or gardens where you work as ecological systems made up of complex interacting parts that respond to human manipulation and management. You are also encouraged to view agricultural systems as not just production systems, but rather as living, dynamic, evolving systems that must be adapted to the particular ecological and cultural conditions of each region of the world.

Investigations

This website describes 24 different agroecological investigations. The description of each is designed to provide all the information you and your instructor will need to plan and carry out an experimental or com-parative study, from background information to step-by-step procedures and suggestions for writing up the results. Most of the information in an investigation is directed to you, the investigator, but the section labeled Advance Preparation is meant to inform your instructor about what needs to be done before the investigation actually begins. You may or may not be called upon to take part in this preparation.

Keeping a Lab Notebook

Good science depends on careful record keeping. Because memory is always incomplete and very often faulty, everything you do in an investigation should be written down in a lab notebook. A well-kept lab note- book will help you work efficiently, stay organized, and have the necessary information at your fingertips when you need it.

Many kinds of information can be recorded in a lab notebook, including

  • Hypotheses
  • General notes and comments
  • Data and observations
  • Descriptions of how you set up experiments
  • Diagrams of field and experimental setups
  • Notes on variations or modifications in methodology
  • Field notes
  • Descriptions of progress in an investigation
  • Flashes of insight
  • Tentative explanations of results
  • Conjectures and speculations
  • Team agreements
  • Calculations

As you can see from this list, a lab notebook serves at least three different purposes: it is (1) an objec- tive record of scientific investigation, (2) a workspace, a nd (3) a record of your t hinking a nd learning. To fulfill the latter purpose, you should try to make ongoing predictions and explanations of your results and observations. Construct hypotheses when applicable, and do as much interpretation of the data as you can.

Before you begin your lab notebook, decide how you will organize it. A suggested strategy is to orga- nize it chronologically. Each day of the lab section, begin a new page with the date on top, and write a brief description of what you expect to do that day. Then record information related to that day’s activities, even if it involves more than one investigation. If your lab notebook is a three-ring binder, you can organize it by subject or by investigation.

Using the Datasheets

Most of the investigations include one or more blank datasheets, which are designed to make it easier to record and analyze your data. Each datasheet is also shown filled in with sample data as an aid in understanding not only what the data should look like, but how they relate to the setup of the investigation and how they should be analyzed.

For many of the investigations, you will need more than one copy of a datasheet or set of datasheets. This occurs, for example, when you are comparing two different agroecosystems and one datasheet can accommodate the data from only one system. If there is a need for extra copies of any datasheets, this need is indicated in the Materials, Equipment, and Facilities section of the investigation.

Working as a Team

The investigations are set up to be completed by teams. Each team is responsible for a certain portion of the investigation—a set of treatments, for example—and the investigation as a whole depends on every team doing its job well and not introducing errors or bias. The results obtained by each team are shared with the other teams to create a dataset larger and broader than one team alone can create. It is very important that all teams follow the same methodology, so that the data they obtain contain as little artificial variation as possible.

Good teamwork is essential for completing the team’s tasks in a timely manner, minimizing error, and getting meaningful results. Team members must coordinate their activities, so that each person’s responsi-bilities are clear cut and everyone is working toward a common goal. To achieve coordination, a team should discuss tasks and responsibilities at the beginning of each investigation and each class period, and reach an agreement on who will do what.

Using Statistical Analyses

None of the investigations require the use of complex statistical methods. The most advanced statistical tests are chi-square and t-tests, and most investigations involve only the calculation of means and some- times standard deviations. When an investigation calls for a statistic to be calculated, the procedure for doing so is presented, and no advanced training in statistics is required.

However, you are encouraged to perform whatever statistical analyses you are capable of and feel are useful in the context of each investigation. In many of the investigations, for example, analyses of variance would be very useful (even though they are not part of the formal procedure). For this reason, a background in statistics is helpful.

Generating Random Numbers

Several of the investigations call for random sampling (of plants, of leaves, etc.). The goal is to obtain an unbiased sample of objects (such as 50 corn plants) that represent a larger group of those objects (such as a field of 1000 corn plants).

Random sampling in the field is best accomplished by (1) numbering each member of the large group (e.g., by row and column in a field), (2) preparing a list of random numbers, and (3) taking as the sample each member of the group whose number corresponds to one of the random numbers.

To prepare an appropriate list of random numbers for random sampling, you need to know two things:

(1) the quantity of random numbers needed (this figure, which we will call Q, corresponds to the size of the sample) and (2) the approximate size of the large group being sampled (the universe). This latter piece of information is very important. If the universe has only 100 members, you do not want random numbers larger than 100 because they cannot yield any selections. Conversely, if the random numbers only range from 1 to 50, none of the members of the universe with a number higher than 50 can be selected, and the sample cannot be truly random. Ideally, then, the list of random numbers should range from 1 to a maximum magnitude (M) equal to the size of the universe. More precisely, each number between 1 and M should have an equal chance of being chosen in the process of generating the list of random numbers.

There are two basic methods for generating a list of random numbers of quantity Q and maximum magnitude M.

Method A—using a table of random numbers:

  1. If M is 9 or less, arbitrarily choose any location in a table of random numbers and read individual digits in sequence down or across, keeping those between 1 and M and throwing out those greater than M, until a quan- tity of random numbers equal to Q has been collected.
  2. If M is between 10 and 99, the procedure described in (a) is followed, except two digits at a time are read. If M is much less than 99, many numbers may have to be thrown away before Q is reached.
  3. If M is between 100 and 999, the procedure described in (a) is followed, except three digits at a time are read. If M is much less than 999, many numbers may have to be thrown away before Q is reached.

Method B—using an electronic random number generator (on a calculator or computer):

  1. Generate random numbers one at a time.
  2. Move the decimal point of each number the appropriate distance to obtain a number with the same number of places as M – 1.
  3. Ignore all numbers greater than M and record all numbers equal to or less than M until a quantity of random numbers equal to Q has been collected.

Writing Lab Reports

Besides serving as a basis for your instructor’s evaluation of your performance, a lab report helps you understand the results of your investigation and allows you to communicate the results to others. In these respects, a lab report is very much like a scientific paper and should be treated as one. A person unfa- miliar with the investigation should be able to understand from your report what you did, how and why you did it, what results you obtained, what you think the results mean, and what insights you have into applying the results.

The investigations in this manual are written to leave the interpretation, analysis, communication, and application of the results up to you (or you and your team, in the case of team reports). You may find that you can take the results in a variety of different directions, all equally valid. The investigations offer suggestions for what to include in your reports, but the results you get and your own unique approach to interpreting them will guide how you construct your reports.

Report Format

Scientific papers follow a basic format designed to present information clearly and in a logical order. The following chart lists the section headings usually included in a scientific paper and describes what each sec- tion typically contains.

  • Title
    Fifteen or fewer words describing fully but concisely what the investigation was about.
  • Abstract
    A one-paragraph summary of the report succinctly describing the objectives of the study, the methods used and measurements made, the results, and the conclusions.
  • Acknowledgments
    A good place for explaining who in your group did what, and for noting any help you received.
  • Introduction
    A short section describing the purpose of the investigation or what was being tested or explored—often includes some background information helping the reader understand the context and significance of the investigation.
  • Materials and Methods
    A short description of what you did and how, including variations from the written procedure, and the statistical tests you used. As long as you reference the lab manual procedure, you need not repeat it.
  • Results
    A presentation of the data (not an interpretation of them), accompanied by clearly labeled tables and/or graphs. Indicate the statistical significance of individual results, if appropriate; explain the meaning of the graphs and tables; and highlight trends, patterns, and significant results.
  • Discussion and Conclusions
    An interpretation of the results, focusing on what they mean. Indicate if the objectives were met and whether the hypothesis was refuted or supported; speculate about mechanisms of action and cause-and-effect relationships; critically analyze your methods and speculate on possible sources of error; acknowledge your assumptions and the limitations of the study; make general conclusions; offer ideas for further study or application of the results; and explain what the results indicate about the importance of using an ecological basis for designing and managing agroecosystems.
  • Literature Cited
    List any sources cited in the report.

Scientific Nomenclature

The Latin names of organisms should be given when appropriate. A rule of thumb: identify crops with their common names (including the variety or cultivar) and identify weeds, disease organisms, insects, other non- farm animals, and native plants with their Latin names. If giving both a Latin name and a common name, be consistent about which you list first, and put the second one in parentheses.

Latin names of organisms consist of two words: the genus name comes first and is capitalized, and the specific name is second and is not capitalized. Both words are either italicized or underlined (e.g., Avena fatua). If a particular Latin name is used more than once, each subsequent mention can use a one-letter abbreviation of the genus name (e.g., A. fatua).

Constructing and Labeling Graphs and Tables

Creating clear, easily understandable graphs and tables is crucial to communicating your results. Here are some guidelines to follow. You may want to study published scientific papers for examples.

  • Present data in the most appropriate form. A table is adequate for a summary of data; but when you want to compare results or show trends and patterns, a graph is usually better.
  • Use the appropriate type of graph. The type of data you want to present, as well as your purpose in presenting it, will determine which type of graph is best. Much of the data you will present is suited to simple bar graphs, but sometimes you will need to use stacked bar graphs or other complex bar graphs, line graphs, or even pie charts.
  • Choose titles that describe exactly what a table or graph contains.
  • Label graphs and tables clearly. Everything should be labeled: columns and rows in tables, and bars, lines, hori- zontal axes, vertical axes, and units of measure in graphs. Labels should be concise and precise, leaving no room for confusion or ambiguity. If you performed a test of statistical significance (e.g., a t-test or chi-square test) on the data you are presenting, indicate which results are significantly different from each other and at what level of significance or confidence (e.g., p ≥ .05).
  • Always explain the meaning or content of graphs and tables in your discussion; do not let them stand on their own.