Urban Soil Microbiome Across Heat Islands

ISEF Category: Microbiology

Subcategory: Environmental Microbiology  ·  Difficulty: Advanced  ·  Setup: University Lab  ·  Time: Full Year

The Hook

City pavement does more than get hot. It can change the tiny life living in soil right under your feet. That makes urban heat islands a real-world lab for studying microbiomes. You can ask whether warmer ground means less diverse soil bacteria.

What Is It?

This project studies how the soil microbiome changes across a city heat gradient. The soil microbiome is the community of microbes, mostly bacteria, that live in soil. You collect samples from different spots, sequence a marker gene called 16S, and compare which microbes show up and how varied each sample is.

Think of it like making a census of a neighborhood. Instead of counting people, you count bacterial types. Alpha-diversity measures how many different types live in one sample and how evenly they are spread. Then you compare those numbers with land-surface temperature from public satellite data, such as Landsat, to see whether hotter sites tend to have simpler or richer microbial communities.

Why This Is a Good Topic

This is a strong science fair topic because it asks a clear question, uses public environmental data, and produces real biological sequence data. You can test a pattern across many sites instead of just one sample, which makes the project more convincing. It also connects to urban ecology, climate, soil health, and how cities change living systems in ways people can measure.

Research Questions

• How does soil alpha-diversity change along an urban heat-island transect?
• What is the effect of land-surface temperature on Shannon diversity in urban soils?
• Does soil type or ground cover predict microbial diversity better than temperature alone?
• To what extent do shaded sites differ from exposed sites in bacterial community composition?
• Which land-use class, such as park, roadside, or vacant lot, shows the highest soil alpha-diversity?
• How does distance from the city center relate to soil microbiome diversity after controlling for temperature?

Basic Materials

• Sterile soil sample bags or tubes
• Disposable gloves
• Clean scoop or stainless-steel spoon
• Permanent marker and waterproof labels
• GPS-capable phone or handheld GPS unit
• Field notebook or data sheet
• Cooler with ice packs for transport
• Laptop with spreadsheet software
• Public Landsat temperature data access
• Mentor or school contact for sample shipping coordination.

Advanced Materials

• Soil corer or sterile auger
• DNA extraction kit validated for soil
• Centrifuge
• Nanodrop or similar DNA quantification instrument
• PCR thermocycler
• 16S amplicon sequencing service order form
• Bioinformatics workstation
• QIIME 2-compatible reference database
• Statistical software for mixed models
• ArcGIS or QGIS for spatial analysis.

Software & Tools

• QIIME 2: Processes 16S sequence data, builds diversity metrics, and compares communities across sites.
• R: Runs diversity statistics, regression models, and plots temperature against alpha-diversity.
• QGIS: Maps sampling locations and overlays land-surface temperature with land-use layers.
• ImageJ: Can help if you also quantify soil color, texture, or cover images from field photos.
• Excel: Organizes field metadata and sample tracking before sequence analysis.

Experiment Steps

1. Define your transect and choose sites that span a clear temperature range while keeping other conditions as similar as possible.
2. Decide which metadata you will record at every site, including soil cover, shade, distance, and land use.
3. Plan your sequencing and bioinformatics workflow before sampling so every sample gets the same processing pipeline.
4. Build a data table that links each soil sample to its GPS point, temperature value, and sequence file.
5. Choose the diversity metrics and statistical tests you will use before you look at the results.
6. Design a control plan that checks whether any pattern comes from sampling location, not from temperature alone.

Common Pitfalls

• Sampling different soil depths at different sites, which changes the microbial community more than temperature does.
• Mixing shaded and exposed spots without tracking canopy cover, which confuses heat effects with light and moisture effects.
• Letting samples sit warm before DNA extraction, which can shift the community profile.
• Comparing sequence runs without checking read depth, which makes low-quality samples look less diverse.
• Treating Landsat surface temperature as ground truth for every sample point, which can hide mismatch between satellite pixels and the exact soil spot.

What Makes This Competitive

A stronger project does more than show a simple correlation. You can improve it by controlling for moisture, land cover, and soil type, then testing whether temperature still predicts diversity. You can also compare multiple diversity metrics, not just one, and use spatial statistics instead of only a basic scatter plot. A project gets stronger when you explain why the pattern happens, not just whether it exists.

Project Variations

• Compare soil microbiomes across green roofs, street trees, and bare lots instead of only along a temperature gradient.
• Add soil moisture and pH as extra predictors to test whether they explain more variation than surface temperature alone.
• Use a small set of functional markers or shotgun metagenomics, if available, to ask whether hotter sites shift not just diversity, but microbial potential.

Learn More

• QIIME 2 Documentation: Free tutorials for processing 16S data and computing diversity metrics, found through the official QIIME 2 website.
• NIH PubMed: Search review articles on urban soil microbiomes, alpha-diversity, and heat islands.
• NASA Earthdata: Find Landsat land-surface temperature products and guidance for downloading satellite data.
• USGS Landsat Missions: Read background on Landsat thermal products and how surface temperature is derived.
• NCBI Taxonomy Browser: Check bacterial taxon names and taxonomy while interpreting 16S results.
• MIT OpenCourseWare, Environmental Microbiology: Use free lecture material for background on microbial ecology and environmental sampling.