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
MS-LS4-4: “Construct an explanation based on evidence that describes
how genetic variations of traits in a population increase some individuals’
probability of surviving and reproducing in a specific environment.”
- 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?”
MS-LS4-6: (Varies by state, but often focuses on explaining
how new traits can appear and spread through populations.)
- 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
MS-LS2-1: “Analyze and interpret data to provide evidence
for the effects of resource availability on organisms and populations of
organisms in an ecosystem.”
- 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
HS-LS4-2: “Construct an explanation based on evidence that
the process of evolution primarily results from four factors: (1) potential
for a species to increase in number, (2) heritable genetic variation, (3)
competition for limited resources, and (4) the proliferation of individuals
better able to survive and reproduce in the environment.”
- 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).
HS-LS4-5: “Evaluate the evidence supporting claims that changes
in environmental conditions may result in: (1) increases in the number of
individuals of some species, (2) the emergence of new species over time, and
(3) the extinction of other species.”
- 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
HS-LS2-2: “Use mathematical representations to support and
revise explanations based on evidence about factors affecting biodiversity
and populations in ecosystems of different scales.”
- 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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