Honeybee nest-site selection activity demo

 

Here's what I want you to do:

For this demonstration, we'll test the effect of nest quality on colony nest choice. You could also use this model to test the effect of nest distance from the swarm or the interaction of both variables on colony nest choice. You'll be manipulating simulated environments, and testing which nest the colonies choose. Each student group will be testing both the control (all nests are of equal quality) and the experimental (nests vary in quality) treatments with six simulated bee colonies. The data from the entire class will be collected and analyzed. 

Here's why I want you to do it:

We're currently studying the decision-making and home/territory selection in animals. Honeybees are a great system for studying this behavior because we can observe the decision-making process of the colony by recording the behaviors of individual worker bees. In a honeybee colony, workers evaluate several possible nest sites until a quorum reaches a decision. Then, the entire colony moves into that nest. There has been a significant amount of research done in this area providing the basis for this activity. Although I can't provide observation bee colonies for our class to study this behavior with real animals, we can use this model to simulate the experimental setup we would use with live animals to test our own hypotheses about nest-site selection in honeybees. The model has been built using the research that has been done with honeybee colonies and models real honeybee colony behavior. Additionally, this model was built using NetLogo, which is an open-source agent-based modeling software used by biologists, engineers, computer scientists, etc. to conduct scientific research. Through this activity, you will gain insights into the topic we are covering in class while also gaining exposure to a common research tool and experimental design. 

Here's how to do it:

Key components of the model control panel:

  1. The Model speed slider at the top of the model determines how quickly the model will run and complete each simulation. You can adjust this to suit your preferences.

  2. Colony "Quorum Size" states the number of individuals that need to reach a consensus for a decision to be made.

  3. "Time (ticks) when quorum reached" is a measure of time. NetLogo uses "ticks" as a time measurement. This value will allow you to compare how long it takes for each colony to reach a decision. 

  4. The visualization pane on the left allows you to observe the experiment in progress. You will see the colony swarm located in the center of the pane with workers and a single queen represented by a crown. The three nests the colony will be choosing between are placed around the swarm. The location and quality of these nests can be set using the model controls.

  5. The graph allows you to visualize the number of bees evaluating each nest in real-time and over the course of the experiment. There are also three boxes that display the current number of individuals in each nest at a given time.

Setting up and running the simulation:

  • Experimental treatment (treatment 1):

    1. Set your population size to 200 using the slider bar on the upper left. This sets the size of your swarm. You can vary this number later on your own.

    2. Set your nest qualities using the three sliders on the left side of the screen. Higher numbers equal a better nest. This is determined by the size of the cavity in the tree and the size of the cavity opening. The cavity must be sufficiently large for the colony to inhabit and grow. The nest is better if the cavity opening is smaller.

      • nest 1 = quality 1​

      • nest 2 = quality 3

      • nest 3 = quality 5

    3. Set the distance of the nests to far by using the drop-down boxes in the second column from the left.  Because we are testing nest cavity quality, we will make the distance to each nest the same. Later, you can use this same model to test distance and the interaction between distance and nest quality.

    4. Enter the parameters you've chosen into your model by clicking the "setup" button located in the "Control Simulation" section. You'll see the "Colony Quorum Size" populated with the number of individuals that must agree on a nest in order for a decision to be made for this size of a colony. This number will change for smaller or larger colonies. You'll also see that the "Actual nest quality" values are populated. These values are calculated based on the nest quality and the distance of the potential nest from the colony swarm.

    5. Press "Go" to run the experiment. 

    6. Record the nest the bees chose.

    7. You'll need to do this two more times. After the bees make a decision, press "Setup" to reset the model. Then, press "Go" to run the next replicate. 

    8. Now you have completed three replicates of the experimental treatment.

  • Control treatment (treatment 2):

    1. Set your population size to 200 using the slider bar on the upper left. This sets the size of your swarm. You can vary this number later on your own.

    2. Set your nest qualities using the three sliders on the left side of the screen. All nests will be the same quality for this treatment.

      • nest 1 = quality 3

      • nest 2 = quality 3

      • nest 3 = quality 3

    3. Set the distance of the nests to far by using the drop-down boxes in the second column from the left.  Because we are testing nest cavity quality, we will make the distance to each nest the same.

    4. Enter the parameters you've chosen into your model by clicking the "setup" button located in the "Control Simulation" section. 

    5. Press "Go" to run the experiment. 

    6. Record the nest the bees chose.

    7. You'll need to do this two more times. After the bees make a decision, press "Setup" to reset the model. Then, press "Go" to run the next replicate. 

    8. Now you have completed three replicates of the control treatment.

 

Enter your data and view the class results:

  1. Navigate to this form to enter your data for all of your replicates. 

  2. Open this data sheet to see all of the data entered. View the results by clicking on the 

  3. We will discuss the results as a class. If you're interested in the model, feel free to take a look at the code by clicking on the NetLogo Code tab at the bottom. You can even change the code if you would like to see what happens.