Dandelion Leaf Shape Along Urban Gradients

ISEF Category: Plant Sciences

Subcategory: Ecology  ·  Difficulty: Intermediate  ·  Setup: Home Setup  ·  Time: 1 to 2 Months

The Hook

Dandelions look simple, but their leaves can change shape when the environment changes. That makes them a great model for asking how city life affects plants. You can turn sidewalk weeds into real data with a phone, a ruler, and ImageJ. This kind of project teaches you how to spot pattern from noise.

What Is It?

Phenotypic plasticity means one plant can grow different shapes in different places without changing its genes. Think of it like the same recipe making a flatter or thicker cookie, depending on the oven. Here, you are looking at leaf-lobe depth, which is how deeply the spaces between the leaf points cut toward the center of the leaf.

Dandelions are useful because they grow in many habitats, from parks to parking lots. If city conditions change light, heat, soil moisture, or foot traffic, leaf shape may shift too. You are not just counting weeds. You are measuring how plant form tracks the environment.

Why This Is a Good Topic

This is a strong science fair topic because you can collect your own field data, define one clear trait, and compare sites along a real urbanization gradient. You can connect your results to ecology, plant adaptation, and city habitat change. You do not need fancy gear, but you still get to do real measurement, image analysis, and statistics.

Research Questions

• How does leaf-lobe depth in dandelions change with distance from the urban core? ?
• What is the effect of pavement cover around a site on dandelion leaf-lobe depth? ?
• Does leaf-lobe depth differ between dandelions growing in lawn grass and those growing in cracks or disturbed soil? ?
• To what extent does roadside traffic level predict dandelion leaf-lobe depth? ?
• Which urban habitat type shows the largest variation in dandelion leaf-lobe depth? ?
• How does leaf-lobe depth vary between sun-exposed and shaded sites in the same neighborhood? ?

Basic Materials

• Smartphone camera with a good focus setting.
• White paper or clipboard to create a flat photo background.
• Ruler or coin for scale in each image.
• Masking tape or chalk to mark sampling spots.
• Field notebook or spreadsheet for site notes.
• GPS phone app or map app to record location.
• Free ImageJ software on a laptop or desktop.
• Measuring tape for estimating nearby land cover.

Advanced Materials

• Smartphone camera with manual exposure control.
• Flatbed scanner for consistent leaf images.
• Calipers for leaf size checks.
• Soil moisture meter.
• Portable light meter.
• GPS receiver or high-accuracy location app.
• Laptop with ImageJ and R installed.
• Geographic information system software such as QGIS for mapping the urban gradient.

Software & Tools

• ImageJ: Measures leaf-lobe depth, leaf area, and other shape traits from photos.
• Google Sheets: Organizes site data, photo IDs, and summary statistics.
• R: Tests whether urban variables predict leaf shape and helps graph the results.
• QGIS: Maps sampling locations and links plant traits to land-use patterns.
• Google Earth: Helps you estimate surrounding pavement, buildings, and green space.

Experiment Steps

1. Define one leaf trait you will measure, and write a clear rule for how you will measure it every time.
2. Choose sites that span a real urbanization gradient, such as park edges, residential lawns, and dense downtown areas.
3. Standardize your photo setup so each leaf is captured from the same angle with a scale included.
4. Build a data sheet that pairs each leaf image with site variables such as pavement cover, shade, and traffic nearby.
5. Calibrate ImageJ so you can convert each photo into the same measurement units and compare across sites.
6. Plan your statistics before collecting data, so you know whether you will compare site types, fit a trend line, or test correlations.

Common Pitfalls

• Measuring leaves at different growth stages, which mixes age effects with urban effects.
• Taking photos with warped or curled leaves, which inflates or hides lobe depth.
• Skipping a scale in some images, which makes ImageJ measurements useless for comparison.
• Sampling only one patch per habitat type, which makes site differences look stronger than they are.
• Ignoring repeated plants from the same area, which can make your dataset look larger than it really is.

What Makes This Competitive

A competitive project goes beyond a simple city-versus-suburb comparison. You can strengthen it by sampling many sites, quantifying the surrounding habitat, and testing more than one urban variable at once. Strong projects also separate leaf shape from leaf size, then use clear statistics to show whether the pattern holds after those controls. If you add mapping or a citizen-science sampling design, your work looks even closer to real ecological research.

Project Variations

• Compare dandelion leaf-lobe depth across mowed lawns, unmanaged lots, and sidewalk cracks.
• Test whether leaf-lobe depth tracks percent tree cover instead of distance from downtown.
• Use repeated seasonal sampling to see whether the same site shifts leaf shape across spring and summer.

Learn More

• PubMed: Search review articles on phenotypic plasticity in plants and urban ecology to find background concepts and methods.
• USGS Urban EcoLab resources: Search for articles and reports on urban environmental gradients and plant responses.
• NOAA Climate.gov: Find accessible background on urban heat islands and local climate effects.
• USDA PLANTS Database: Confirm species identification and learn the range of Taraxacum-related records.
• ImageJ Documentation: Learn how to calibrate images and measure distances and areas from plant photos.