Grades 9–12 · Seasons & change
Signal Through the Seasons: does biodiversity shift with the calendar?
Track how a genetic signal at one site changes from season to season.
Students design a repeated-measures investigation, sampling the same site with a new kit each season (or term), and use the accumulating Field Journal record to test whether species detections track predictable seasonal patterns like migration, breeding, or dormancy.
Grade band
Grades 9–12
Time required
4 class periods per sampling round (multi-round unit across a school year)
Class size
20–35 students, one kit per round
Sample type
Water, one vial
Standards and outcomes
- HS-LS2-2 — Use mathematical representations to support explanations of factors that affect biodiversity and populations across seasons
- HS-LS2-6 — Evaluate claims about the factors that cause ecosystems to change over time
- HS-LS4-4 — Construct explanations for how seasonal and environmental factors influence species behavior and survival
- Science & Engineering Practices — planning and carrying out longitudinal investigations, using mathematics and computational thinking, constructing explanations, engaging in argument from evidence
How one kit serves a whole class
Each round of the Starter Kit holds one collection vial, targets the same up-to-five species across rounds, and returns results in 7–10 days for $200 per kit. The class keeps the sampling site, species list, and composite batching protocol identical across rounds so that season is the only variable that changes, turning the accumulating Field Journal entries into a genuine time series.
Choose one
Research tracks
Track A — Migration Watch
Seasonal presence and absence
Driving question. Does a migratory or seasonally active species appear in our site's genetic signal only during its expected season?
Species to pick. Species with well-documented seasonal patterns local to the region: a migratory fish or bird category, a hibernating or dormant amphibian, and two to three year-round residents as a comparison baseline.
What students take away. Students build a seasonal presence/absence chart and test it against known life-history timing.
Track B — Breeding Season Surge
Reproductive timing and signal strength
Driving question. Does relative signal strength for a breeding-season species spike during its known breeding window?
Species to pick. A species with a well-known breeding season (many amphibians and fish) tracked across rounds, paired with a species that breeds continuously or unpredictably as a contrast.
What students take away. Students connect relative signal changes to breeding activity, not just presence/absence.
Track C — Temperature and Community Shift
Thermal tolerance and community turnover
Driving question. Does the detected community shift as water or soil temperature changes across the year?
Species to pick. A cold-tolerant species paired with a warm-tolerant species from the same group, plus a habitat generalist as a baseline, tracked across at least two temperature-contrasting rounds.
What students take away. Students use temperature data alongside detections to argue whether thermal tolerance explains the pattern.
The lesson sequence
Step by step, with teacher notes
- 01
Designing a repeated-measures investigation
50 minutesStudents learn why keeping site, species list, and protocol constant across rounds is essential to a valid seasonal comparison, then research the expected seasonal timing (migration, breeding, dormancy) for their five chosen species and write predictions for each planned sampling round.
Teacher notes
- Say: "The only thing that's allowed to change between rounds is the season. If we change the site or the species list, we can't trust the comparison anymore."
- Introduce the term 'repeated measures' and contrast it with a one-time snapshot study like a single-kit biodiversity survey.
- Have students build a prediction table now for every planned round (e.g., fall, winter, spring) before any data exists, so predictions aren't biased by early results.
- Discuss logistics honestly: this unit requires the class (or department) to commit to multiple kits across the year — plan the calendar with students so they understand the investment.
Materials
- Regional species life-history reference sheet
- Multi-round prediction table template
- School year calendar for planning sampling dates
- Site map
Student prompts
- What season is each of our five species expected to be most detectable in, based on its life history?
- Why must we keep the site and species list identical across every round?
- What would a surprising result look like, and what would it tell us?
- 02
Round one: baseline composite sampling
50–60 minutesCrews run the standard composite batching protocol at the fixed site, establishing the baseline round. Extra care is taken to document exact conditions (temperature, day length, weather) since these will be the comparison point for every future round.
Teacher notes
- Say: "Everything we record today becomes the baseline every future round gets compared against — be as precise as you can."
- Photograph the exact sub-sample locations (with a marked map or flagged points) so future rounds can return to the same spots.
- Record day length and general seasonal markers (leaf-out, flowering, ice cover) in addition to temperature, since these often correlate with species activity better than the calendar date alone.
- Store the site map and protocol notes somewhere the class (or next term's class) can retrieve them for round two.
Materials
- 1 classroom eDNA collection vial and prepaid mailer per round
- Nitrile gloves
- 4 sterile sub-sample cups or bags
- Field data sheet
- Camera or phone for documenting site conditions
Student prompts
- Sampling crew — draws four sub-samples from the same fixed micro-habitat points established for this investigation.
- Field scribe — records temperature, day length, weather, and seasonal markers (ice, leaf-out, flowering) in detail.
- Documentation crew — photographs and maps exact sub-sample locations for repeatability in future rounds.
- Chain-of-custody crew — preserves, labels (including round number/season), seals, and prepares the sample for mailing.
- 03
Interpreting a time series, not a single data point
50 minutes, during each round's 7–10 day turnaroundStudents learn how scientists interpret change over time, including the danger of over-interpreting a single round's result. They build a running seasonal chart and discuss how many rounds are needed before a pattern can be trusted.
Teacher notes
- Say: "One data point is a snapshot. Two data points is a line — but a line with two points can be misleading. We need enough rounds to be confident."
- Introduce the idea of natural year-to-year variability: a single season's absence could be normal variation, not a trend, unless replicated across multiple years.
- Have students build or update a running chart (detections and relative signal by round) each time new results arrive — this becomes the core data artifact of the unit.
- Discuss how real long-term ecological monitoring programs (e.g., LTER sites) handle this same challenge with many years of data.
Materials
- Running seasonal detection chart (shared spreadsheet or poster)
- Vocabulary handout (time series, natural variability, replication)
- Sample redacted multi-round Field Journal report
Student prompts
- Why is it risky to draw a strong conclusion from just one or two rounds of data?
- How would you distinguish a real seasonal pattern from random year-to-year variation?
- What does a real long-term ecological monitoring program do differently from our single-year unit?
- 04
Cumulative reveal and seasonal CER
50 minutes (repeated at the end of each round, deepened at year's end)After each round's Field Journal results arrive, the class updates its running chart and revisits predictions. At the end of the multi-round unit, students write a full CER argument about whether the site's detected community changes predictably with the season.
Teacher notes
- After each round, hold a short 10-minute 'chart update' discussion even if the full CER essay only happens at year's end — this keeps the investigation alive across the term.
- At the final reveal, have students overlay their original Phase 1 predictions on the completed chart and mark each as supported, partially supported, or not supported.
- Push students to reason about mechanism, not just pattern: why would this species' detection change with season, biologically?
- Close the unit by asking what the class would do differently if this investigation continued for three more years.
Materials
- Completed running seasonal detection chart
- CER writing frame
- Original Phase 1 prediction table for comparison
Student prompts
- Claim — does the detected community at our site change predictably with the season?
- Evidence — cite the specific pattern of detections and relative signal across all sampling rounds.
- Reasoning — connect each species' known life history (migration, breeding, dormancy, thermal tolerance) to the pattern observed.
Student handout
For every student
Thinking prompts
- State your seasonal prediction for each of the five target species before any round begins.
- Explain why site, species list, and protocol must stay constant across rounds.
- Record exact site conditions (temperature, day length, seasonal markers) for each round.
- After each round, update your prediction table with actual results and note matches or surprises.
- Explain the difference between a real seasonal trend and natural year-to-year variability.
- Write your final CER argument using the full multi-round dataset.
Data sheet
- Round number, date, and season:
- Site name and fixed sub-sample locations (map reference):
- Water or soil temperature, day length, and weather:
- Seasonal markers observed (ice cover, leaf-out, flowering, breeding calls, etc.):
- Target species list with per-round pre-reveal predictions:
- Detection results and relative signal per round (updated after each Field Journal release):
- Notes on any protocol deviations between rounds:
Discussion questions
- Why is a repeated-measures design more powerful than a single snapshot for answering a seasonal question?
- How many rounds of data would you want before trusting a seasonal pattern, and why?
- What environmental variable (temperature, day length, precipitation) seemed to matter most in our results?
- How would this investigation need to change to run reliably as a multi-year program at our school?
Field checklist
- Same fixed site and sub-sample points used in every round.
- Same five target species used in every round.
- Nitrile gloves on before touching any sampling equipment.
- Temperature, day length, and seasonal markers recorded each round.
- Composite sample mixed gently, preserved and sealed without touching the vial interior.
- Round number and season clearly labeled on the sample and datasheet.
Analysis
CER: Does biodiversity at our site shift predictably with the season?
- 1.Claim — state whether the detected community shows a predictable seasonal pattern.
- 2.Evidence — cite specific detections and relative signal values across all sampling rounds, referencing the running chart.
- 3.Reasoning — connect each species' life history (migration, breeding, dormancy, thermal tolerance) to the observed pattern.
- 4.Counter-evidence — identify any round's result that doesn't fit the pattern and consider whether it reflects natural variability or a protocol issue.
- 5.Revise — propose how many additional rounds or years would be needed to strengthen confidence in the pattern.
Assessment
20-point rubric
Investigation design and predictions
5 ptsA sound repeated-measures design is set up with specific, life-history-grounded predictions for every round.
Field discipline and consistency across rounds
5 ptsSite, species list, and protocol are kept consistent, with precise seasonal condition documentation each round.
Time-series data interpretation
5 ptsThe running chart is accurately maintained and students correctly distinguish real pattern from natural variability.
Final CER conclusion
5 ptsA well-defended, mechanism-based explanation connects seasonal detections to species life history across the full dataset.
Go further
Extensions
- Continue the investigation into a second school year to test whether the pattern repeats, strengthening the case for a real trend.
- Share the running seasonal chart with a regional naturalist or extension office to compare against known regional phenology data.
- Have students graph relative signal (not just presence/absence) across rounds to look for breeding-season surges.
- Combine this investigation with a citizen-science phenology project (e.g., tracking bloom or migration dates) for cross-validation.
For the teacher
Answer key and misconceptions
- Expected: species with well-documented seasonal life histories (migratory fish, breeding amphibians) often show clear presence/absence or signal-strength patterns that match the calendar.
- Common misconception: two rounds of data are enough to prove a trend. Correct framing: multiple rounds, ideally across multiple years, are needed to distinguish a real pattern from natural variability.
- Common misconception: if a species isn't detected in its 'expected' season, the method failed. Correct framing: weather anomalies, shifted phenology, or sampling timing can all explain a mismatch — this is a legitimate finding to investigate, not an error.
- Expected: students should correctly identify that keeping site and protocol constant across rounds is what allows season to be treated as the tested variable.
- Common misconception: relative signal strength and presence/absence tell the same story. Correct framing: a species can be present in every round but show a signal spike specifically during breeding season — that's a different, deeper finding than simple presence/absence.