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Richard Wahl began learning beekeeping the hard way starting in 2010 with no mentor or club association and a swarm catch. He is now a self-sustainable hobby beekeeper since 2018, writing articles, giving lectures and teaching beginning honey bee husbandry and hive management.
Off the Wahl Beekeeping
New(ish) Beekeeper Column
Understanding Research
By: Richard Wahl
Intro
Quite often when new beekeepers go looking for information, they come across research papers filled with unfamiliar terms like abstract, control, hypothesis, methods and materials. It can feel like trying to read a foreign language. Understandably, many folks close the tab and turn instead to a forum or a YouTube video for advice. But, learning to read and understand research, even just at a basic level, can be one of the most useful skills a beekeeper can develop. My aim in this article is to clarify what some of the terms mean and to explain the research process as I came to understand it while teaching high school students. During the last six years of my teaching career, I was fortunate to teach at a magnet school. The school invited gifted students from surrounding rural districts to our accelerated science, technology, engineering, and mathematics (STEM) program for a half day of their studies while completing their other half day humanities course work at their home schools. Because we were able to cover all the STEM material in four days each week, all Wednesdays were devoted entirely to research projects.
I watched 16-year-olds wrestle with terms like variables and literature review, and other words that can make a beekeeper set aside a research paper. What the students learned, and what I learned teaching them, was that research is really just organized curiosity. It’s the same instinct that makes us wonder why one hive swarms earlier than another, or whether that fancy new feeder is worth the money. The research process involves defining a topic and developing questions, reviewing existing literature, designing a study, collecting data, analyzing it for patterns, interpreting the results, and finally reporting and citing the findings. These steps are often iterative, meaning researchers may revisit earlier stages as their understanding evolves. What follows is a brief synopsis, the explanation and implementation, of the research process offered to help new and experienced beekeepers better understand the terms and steps they will encounter when reading a research document.
Advantaged Beekeepers Understand Research
You might say, “Look, I only have two hives in the backyard and I’m not a scientist.” Fair enough; but bees do not care if you have two colonies or two hundred. They are still responding to pests, weather, forage, and genetics in the same complex way that we are all trying to understand. Experienced beekeepers know they must keep adapting to new situations as advice changes constantly. Twenty years ago, powdered sugar dusting for Varroa mites was all the rage. Today, through experience and research, it has been found to be mostly ineffective. Understanding how research works helps you cut through the clutter of opinions and fads and to find advice grounded in real evidence to support that advice. For example, a common recommendation is to add essential oils to your syrup. Some beekeepers swear their bees thrive on it, while others dismiss it as an unnecessary expense. Without research, it is just one person’s word against another’s. With research, you can see whether there are any previous trials (literature reviews) to see if measurable benefits exist, or whether the results found in that research simply do not hold up. That is the power of research as it provides credible evidence.
The Abstract is the Road Map
One of the first intimidating words new readers encounter in a research paper is abstract. It sounds far more complicated than it really is. Think of it like the back-cover synopsis of a book, or a condensed preview that tells you what you’re about to read in greater detail. The abstract is a short summary of what question the researchers asked, sometimes also known as the hypothesis, what was done, what was found, and what those findings might mean. For example, suppose a researcher wants to know whether screened bottom boards reduce mites. The abstract will spell out the basics which would include, how many colonies were tested (say fifty total), how they were divided (half with standard and half with screened bottom boards), and what was used as a control. In this case, the solid bottom boards act as the baseline, or control, while the screened boards are the variable being tested.
The abstract also states how long the study ran and then presents the results. Perhaps the researcher observed about 15% fewer mites in colonies with screened bottom boards over an entire Summer season. That is the data collected over the period of the observation. From there, the researcher draws a conclusion, which is likewise summarized in the abstract. In this case the researcher would conclude that screened bottom boards can help, but that they will not solve mite problems in and of themselves. The beauty of an abstract is that you get the main point of the research without wading through pages of technical language and charts. You do not need to be fluent in all the academic jargon, merely able to understand a few basic terms, to gain useful value out of what the study found. In other words, did the study support or refute the hypothesis that screened bottom boards help reduce mites?
A Control Sets the Baseline
One of the most powerful but often overlooked ideas in science, and one many new beekeepers miss, is the control. A control is simply the facet in an experiment that does not get the new treatment or change. Think of it as your baseline, the steady yardstick against which everything else is measured. Without it, you cannot know whether the results you see are due to what you did or to something else entirely. Let’s say you feed your bees a fancy protein patty in the Fall and they survive Winter as a strong colony. Was it the patties that made the difference, or would they have survived just as well without it? To know for sure, you would need a control group, colonies that did not get the patty. Then you could compare survival rates between the two groups. Without controls, you are left with guesswork, because bees can be influenced by weather, forage, mite levels, or just plain good luck. Controls strip away some of the external chaos and provide a clearer picture of whether the change you made, the variable, really matters.
The Moving Parts are Called Variables
If controls are the baseline, then variables are the moving parts of the research. Beekeeping is messy because so many variables can influence a hive, like weather, forage, genetics, pests and the list goes on. In research, those factors get sorted into categories. The independent variable is the one thing you purposely change, like deciding to add pollen patties. The dependent variable is what you measure in response, for example, how strong the colony is come Spring. Then there are controlled variables, which are all the other details you try to keep the same, like starting colony size, hive equipment, or location, so those other factors do not muddy the waters. Think of it like cooking chili; if you swap three spices and change the beans all at once, you won’t know which change made it taste better. The fewer uncontrolled variables you have in the mix, the clearer a picture the research results will provide.
It Starts with a Hypothesis
A hypothesis is the question or supposition that research seeks to support or refute. It is a tentative, specific and testable prediction about the relationship between two or more variables, serving as a preliminary assumed answer to a research question that guides the entire study. Think of it as an educated guess such as, if I change element A, will result B happen? For instance, maybe you have noticed that one of your colonies builds up much faster every Spring than the others. You might wonder, “Is it because that hive gets more morning sun?” That thought, “I wonder if more sun makes a difference?” would form the basis of a hypothesis. However, to be useful in research, it has to be stated in a testable way. A proper form would be a statement or question such as, “Colonies that receive more morning sunlight will build up faster in Spring than colonies kept in shade.” A hypothesis is not just a random idea but a prediction that can be measured. In beekeeping, nearly every management debate can be framed as a hypothesis. Some examples include, “Does insulation help?” or “Should I re-queen every year?” Choosing to insulate a hive or deciding not to re-queen one year become the variable to be tested. The changed condition, or the variable, that allows results to be measured.
Methodology States the Methods and Materials Used
Once you have a hypothesis, you need a plan. That’s where methods and materials come into play. If the hypothesis is the big idea, then the methods and materials are the nuts and bolts of the study, in other words, the “how” and the “with what”. I like to think of them as the orchestration of the research. The materials are simply the stuff you used such as hives, bees, syrup, mite counters, or whatever tools were part of the works. Methods are the step-by-step directions; when you fed, how often you checked and how many colonies you worked with. Just like sharing notes from a hive inspection, the details matter. If you leave out whether you saw eggs or how many frames of brood were present, another beekeeper will not get the same picture or the same results that you did.
A solid methods section is detailed enough that another beekeeper could repeat the experiment and reasonably expect to see similar results. For example, let’s say a study is testing Fall feeding. The methods might spell it out in this fashion. Twenty colonies were split into two equal groups; Group A received 2:1 sugar syrup weekly from September through October, while Group B received no supplemental feeding. Colony weight and brood area were measured twice a month. The more precise the instructions, the more confidence we can place in the results because we know exactly how the study was carried out. Sometimes a broader term, methodology, is used. This refers not only to the steps and materials, but also to the reasoning behind their use. Methodology explains why the experiment was designed in that way, and how the parts fit together. It is the framework that explains both the “what” and the “why” of the research process.
Collecting Data is Gathering the Evidence
Once your inquiry is underway, you need data. Data is just a structured word for evidence. It can be numerical; like mite counts, hive weights, brood area in square inches or simply observational, like whether the bees seem calm or hot-tempered. The trick is consistency. If you measure brood on one hive using “square inches” and in another using “frames covered,” the data will not compare. Likewise, if your measurements were taken once in April and again in July you have missed the story in between. Honest, consistent, repeated measurements are what make the data useful. I once had students tracking seed germination. The ones who measured every two days could chart accurate growth patterns. The ones who forgot and then guessed produced graphs full of gaps. The same applies to us beekeepers. Guessing at mite levels is not the same as actually counting them. Reliable data comes only from steady, repeatable observation.
Facts That Happen Are the Results
The results section of a research paper simply lays out what happened. This is where all the planning, measuring and note-taking finally come together into a picture that others can see. Importantly, the results section should not tell you what to think. It simply reports the findings from the collected data. This information may appear as charts, graphs, percentages, or just tables of numbers. For beekeepers, results might show something like, “Colonies fed syrup weighed 20% more going into Winter than colonies that were not fed”, or “Screened bottom boards reduced mite levels by an average of 15%.” Notice that in the results, the researcher is not adding opinion. They are only reporting what was observed. It is like returning from a hive inspection and writing down exactly what you saw without speculating about why the bees behaved that way. Later, in the discussion and conclusion, the meaning of those results will be explored. But here, the focus is on putting the evidence on the table so everyone can see it clearly.
The Discussion and Conclusion Make Sense of It All
The discussion and conclusion are where the researcher finally steps back to make sense of all those numbers, charts, and observations. If the results section is like writing down what you saw during a hive inspection, the discussion is the part where you ask, “So what does that mean for the health of my bees?” In this section, the researcher interprets the findings, compares them with other studies (literature reviews), and points out any limitations. For example, if colonies given pollen patties built up faster in the Spring, the discussion might explain that patties can provide a boost, but may only be effective when natural forage is scarce. The conclusion then ties everything together; summarizing the big picture and sometimes suggesting what beekeepers or future researchers could try next. In practical terms, this is the section that helps you decide whether the research offers something useful for your own beekeeping or if more testing is needed before changing your management practices.
Replication is the Key to Reliable Research
Reliable research requires replication because one trial alone is never enough to be certain of the results. Bees and their environment are influenced by countless factors. Here come those variables again such as weather shifts, forage availability, or even queen temperament, all of which can skew a single test. By repeating the same evaluation multiple times, or by having different researchers replicate studies under comparable conditions, confidence grows that the outcome is real and not just a fluke. For example, if several studies in different regions all show that Fall feeding improves colony survival, you can be far more confident in the practice than if only one beekeeper happened to get lucky. Replication is what turns an interesting observation into dependable knowledge and reliable evidence.
Statistics or the Math Behind It All
Statistics may sound intimidating, but in research it is simply the math that helps separate real patterns from random chance. Bees are living creatures, and their behavior is naturally variable. One hive may thrive while another struggles for reasons we don’t fully understand or control. Statistics take all those numbers, like mite counts or colony weights; and help determine whether the differences between groups are meaningful or just coincidence. For example, if colonies fed syrup weighed more going into Winter, statistics can show whether that weight gain was likely caused by the feeding or if it could have happened by random variation. You do not need to do the math yourself, but knowing that a study used solid statistical methods should give you greater confidence that the results are reliable. As an aside, this was also where much of my high school students’ statistical mathematics education came into play. They learned to analyze their collected data using valid statistical methods.
Bringing It Back to Your Bee Yard
The steps of research aren’t so different from what you’re already doing. It begins with defining a topic and asking questions, reviewing what’s known, designing a plan, collecting data, analyzing patterns, interpreting results, and sharing findings. These steps are often iterative as you circle back looking at new insights as they emerge. It is much like returning to the hive for subsequent inspections as the season unfolds. Even if you never publish a research paper, you can apply these principles in your own apiary. Every time you try something new, you are running a small experiment or conducting research. For example, if you wonder whether pollen patties help in late Winter, treat half your hives, leave half untreated, keep everything else the same, and see what happens. Measure honestly, and you’ll have your own mini-study to guide colony management. It won’t be as airtight as a university trial with two hundred colonies, but it will be far better than relying on gut feeling alone.
As beekeepers, we are constantly balancing old traditions, club advice, internet debates, and new discoveries. Learning the language of research, those words like abstracts, hypotheses, methods, controls, and variables to name a few, gives you the tools to sort fact from opinion. You don’t need a PhD to read a paper with confidence or to apply the same principles in your own bee yard. At its core, research is simply organized curiosity. It is the same process you use when you crack open a hive. You look, wonder, and test ideas against what you see. So next time you come across a research paper, do not be intimidated by the new vernacular. Behind all that formal structure is the same thing you do every time you do a hive inspection. You observe, you ask questions, and continue to try to understand these remarkable honey bee creatures a little better.
Richard Wahl began learning beekeeping the hard way starting in 2010 with no mentor or club association and a swarm catch. He is now a self-sustainable hobby beekeeper since 2018, writing articles, giving lectures and teaching beginning honey bee husbandry and hive management.
