🎃 Garden of the Giants Genetics - Giant Pumpkin Breeding
Estimated Time: 90-120 minutes Materials: Internet access, Garden of the Giants Genetics simulation, calculator (for statistics).
Teacher Notes & Alignment
- Performance Expectation: HS-LS3-3. Apply concepts of statistics and probability to explain the variation and distribution of expressed traits in a population.
- Science and Engineering Practice (SEP): Analyzing and Interpreting Data. Apply concepts of statistics and probability to scientific and engineering questions and problems.
- Disciplinary Core Idea (DCI): LS3.B: Variation of Traits. Environmental factors also affect expression of traits, and hence affect the probability of occurrences of traits in a population.
- Crosscutting Concept (CCC): Scale, Proportion, and Quantity. Algebraic thinking is used to examine scientific data and predict the effect of a change in one variable on another.
Evidence Statements Addressed:
- Organizing data: Students organize the given data by the frequency, distribution, and variation of expressed traits in the population. (Demonstrated in Part 2 and 3 as students record the average weight and observe the histogram distribution over generations.)
- Identifying relationships: Students perform and use appropriate statistical analyses of data to determine the relationship between a trait’s occurrence and environmental factors. (Demonstrated in Part 3 as students analyze how altering soil nutrients or introducing stressors shifts the population mean.)
- Interpreting data: Students analyze and interpret data to explain the distribution of expressed traits, including recognition and use of patterns to predict changes if variables change, and describing the expression as causative or correlational to environmental factors based on evidence. (Demonstrated in Part 4 where students construct an evidence-based argument linking selection and environment to the statistical distribution of pumpkin weights.)
Part 1: Engage - The Quest for the Giant Pumpkin
Every year, farmers compete to grow the largest pumpkin, with some weighing over 2,500 pounds! But these massive gourds don’t happen by accident. They are the result of careful genetic selection and precise environmental control.
Phenomenon: A farmer is trying to breed the largest pumpkin possible. They know they need to select the seeds from the biggest pumpkins to plant next year, but they also know that bad weather, pests, and poor soil can ruin the crop, regardless of genetics.
Questions:
- Why might planting seeds from the largest pumpkin not guarantee that all of next year’s pumpkins will be just as large?
- How do you think an environmental stressor (like a drought) would change the shape of a graph showing the weights of all pumpkins in a field?
Part 2: Explore - Baseline Genetics and Selection
In this simulation, you will manage a population of pumpkins. You can control which pumpkins are selected for breeding and adjust their environment. Let’s start by establishing a baseline.
Instructions:
- Open the Garden of the Giants Genetics simulation.
- Click Reset Simulation to ensure you are starting fresh.
- Keep all Environmental Factors (Nitrogen, Phosphorus, Potassium, Water) at their default optimal settings.
- Set the Breeding Selection to “Top 10%”.
- Run the simulation for 5 generations using the Next Generation button or Auto-Run 5 Generations.
- Record the average weight for each generation in the data table below. Observe the “Population Weight Distribution” chart.
Data Table: Baseline Top 10% Selection
| Generation | Avg Weight (lbs) | Describe the shape/peak of the distribution curve |
|---|---|---|
| 1 | ||
| 2 | ||
| 3 | ||
| 4 | ||
| 5 |
Analysis Question:
- As you selected the top 10% for breeding over 5 generations, what happened to the mean (average) of the population? Did the variation (the width of the bell curve) change?
Part 3: Explain - The Impact of Environment and Stressors
Now we will see how the environment influences the expression of these genetic traits.
Instructions:
- Reset the Simulation.
- Set the Breeding Selection to “Top 10%”.
- Under Environmental Factors, lower the Soil Nitrogen (N) and Water Input to “1” (Poor/Low).
- Run the simulation for 5 generations. Record the average weight at Generation 5: ____ lbs.
- Reset the Simulation.
- Keep Environmental Factors optimal, but under Stressors & Events, check “Enable Random Stressors”.
- Run the simulation for 5 generations, occasionally clicking “Trigger Drought” or “Trigger Pests”.
- Record the average weight at Generation 5: ____ lbs.
Sensemaking:
- Compare your Generation 5 average weight from the baseline (Part 2) to the poor environment trial (Part 3, Step 4). Use statistics (e.g., calculating the difference in means) to describe the impact of the environment.
- When stressors (drought/pests) were introduced, what did you observe about the frequency of lower-weight pumpkins on the distribution chart compared to a non-stressed generation?
- LS3.B: Explain why the variation and distribution of traits observed depends on both genetic factors (breeding selection) and environmental factors.
Part 4: Elaborate/Evaluate - Predicting Trait Distributions
Imagine a neighboring farm uses a different strategy. They select the “Top 50%” of pumpkins for breeding, but they maintain perfect environmental conditions. You select the “Top 5%” for breeding, but you experience frequent droughts.
- Predict: Which farm will have a higher probability of producing a pumpkin over 200 lbs in the next generation? Why? Use algebraic thinking (Scale, Proportion, and Quantity) to justify your prediction.
- Test your prediction: Use the simulation to model both scenarios. Run each scenario for 5 generations and record the final average weight and distribution shape.
- Farm A (Top 50%, Perfect Environment): Gen 5 Avg Weight = ____ lbs.
- Farm B (Top 5%, Frequent Drought): Gen 5 Avg Weight = ____ lbs.
- Construct an Argument: Write a short paragraph supporting or refuting your initial prediction using the statistical data (means and distribution shapes) collected from the simulation. Explain how the data serves as reliable evidence that environmental factors can limit the expression of genetic potential in a population.