PopG & K–12 Standards Alignment

PopG is a single-locus, two-allele population genetics simulator that models how allele frequencies change under drift, mutation, migration, and selection. It offers a data-rich, inquiry-driven framework for exploring core evolutionary principles that align with K–12 science standards—especially the Next Generation Science Standards (NGSS).

1. Middle School Life Sciences

MS-LS4: Biological Evolution – Unity and Diversity

• Using PopG: Students set a beneficial allele with a certain selection coefficient. They observe how it tends to rise in frequency over multiple generations. Random fluctuations (drift) show why the outcome can deviate from the “ideal.” This illustrates how some variations consistently confer advantages.
• Inquiry Activity: “What happens if you make the selection advantage small vs. large? In which populations is the beneficial allele more likely to fix, and why?”

• Mutation Rate Demo: Students experiment with a small mutation rate, letting them see how new alleles appear sporadically and can be lost or fixed depending on drift and selection.

MS-LS2: Ecosystems – Interactions, Energy, and Dynamics

• Connection: Although PopG focuses on allele frequencies, it can be conceptually tied to resources/fitness. For example, you can set different fitness values for the genotypes to simulate resource-based selection (e.g., “A” genotype uses a resource more efficiently).

2. High School Life Sciences

HS-LS4: Biological Evolution – Unity and Diversity

• Using PopG: Students see that heritable variation (allele A vs. allele a) interacts with a finite population size (sampling drift), plus a selection parameter (competition factor). Over multiple generations, fitter genotypes become more common.
• Inquiry Extension: Introduce multiple sub-populations with migration to demonstrate how gene flow can spread or dilute advantageous alleles across demes, integrating (2) and (3).

• Inquiry Activity: Although PopG does not directly model speciation, students can investigate how a beneficial allele spreads under one set of environmental conditions (high fitness for A) vs. another (high fitness for a). They see how environmental shifts can flip the advantage, leading to new equilibria or allele loss.

HS-LS2: Ecosystems – Interactions, Energy, and Dynamics

• Connection: PopG’s outputs (frequency vs. generation) provide quantitative data that students can interpret, graph, and compare to predicted outcomes. This fosters skill in analyzing mathematical models (Hardy-Weinberg, selection equations) and real or simulated data.
• Advanced Variation: Some versions allow complex migration matrices or selection scenarios that simulate small differences among subpopulations, showing how biodiversity can arise or be suppressed by gene flow.

3. Crosscutting Concepts & Science/Engineering Practices

• Cause & Effect: Students manipulate a single parameter (e.g., increasing mutation rate) and observe its direct effect on allele frequency patterns, reinforcing the concept of cause and effect in dynamic biological systems.
• Patterns & Variation: Multiple runs can reveal patterns in the data—how often an allele fixes or goes extinct—emphasizing that different parameters can produce distinctive population outcomes.
• Mathematical & Computational Thinking: Running PopG encourages the use of predictive models (selection equations, Hardy-Weinberg, migration formulas) to compare theoretical expectations vs. simulation outputs.

4. Classroom Implementation Tips

Below are some ideas for integrating PopG into a lesson or unit:

• Guided Inquiry: Students form hypotheses (e.g., “If allele A is beneficial at 5% advantage, it will reach 100% by generation X”), then run PopG to see real vs. expected results.
• Compare Population Sizes: Show how smaller populations experience more drift; link to real-world conservation biology (endangered species with small gene pools).
• Multi-Population / Gene Flow Scenarios: Relate to habitat fragmentation or patchy resources. Students see how migration can homogenize differences or allow beneficial alleles to spread across demes.
• Data Analysis: Export results, graph frequencies in spreadsheets, and calculate standard deviation or run multiple replicate simulations. This emphasizes statistical thinking in biology.

5. Integration with Climate or Environmental Factors

Though PopG does not natively simulate a changing climate, teachers can conceptually relate selection coefficients (or resource-based fitness) to a “warming” or “cooling” scenario. Variation in selection pressure from environment X to environment Y parallels real-world climate shifts that can favor new mutations or drive local extinctions.

6. Summary

PopG lends itself well to NGSS-aligned instruction on evolutionary mechanisms, data analysis, and cause/effect relationships. By allowing students to tinker with population size, mutation rates, selection strength, and migration between populations, it illuminates fundamental concepts across middle and high school life science standards.

Whether used for a brief demonstration of Hardy-Weinberg principles or a multi-lesson project on evolutionary genetics and ecology, PopG provides a hands-on, inquiry-based approach that resonates with both **NGSS performance expectations** and **crosscutting concepts** in science education.

9. Contact & Acknowledgments

PopG was originally developed by <Prof. Joe Felsenstein> and was ported to Javascript by <Wesley R. Elsberry>. For more information, bug reports, or feature requests, email <welseber at gmail> or visit evo-edu.org.

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