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College intro · Invasives & conservation

Biosecurity by the Numbers: testing for invasive species with a single composite sample

Students apply hypothesis testing and detection-probability reasoning to a real invasive-species biosecurity question.

Students formulate and test a hypothesis about whether a regionally relevant invasive species is present at a local waterway, using a single class-wide composite sample and up to five target species. The unit foregrounds detection probability, false positive/negative risk in a biosecurity context, and the statistical basis for early-detection monitoring programs, culminating in a formal lab report with a management recommendation.

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Grade band

College intro

Time required

5 lab sessions (150 min each)

Class size

16–24 students, one kit

Sample type

Water, one vial

Standards and outcomes

  • Vision & Change Core Competency — Ability to apply the process of science: design a hypothesis-driven investigation and interpret results probabilistically
  • Vision & Change Core Competency — Ability to communicate and collaborate with other disciplines, including applying science to inform policy or management decisions
  • Vision & Change Core Concept — Systems: species interactions and disturbance shape ecosystem structure and function
  • Course Learning Outcome — Evaluate the statistical basis and limitations of a real-world biological monitoring program

How one kit serves a whole class

The $200 Classroom Starter Kit provides one collection vial, targets up to five species, and returns detections plus relative signal in 7–10 days via the class Field Journal — no counts. Because agencies conduct real invasive-species surveillance under exactly this kind of resource constraint, the class treats its single composite sample as a simulation of an early-detection monitoring program: sub-samples are pooled from multiple points suspected of highest invasion risk (boat launches, inflows, high-traffic access points) into one representative sample, with every design decision documented for the shared lab report and management recommendation.

Choose one

Research tracks

Track A — Early Detection at High-Risk Access Points

Biosecurity monitoring design under resource constraints

Driving question. Is there genetic evidence of an invasive species at the access points where it is most likely to first arrive (boat launches, bait disposal sites, inflows)?

Species to pick. Up to five species: two or three invasives with documented regional introduction pathways (e.g., invasive crayfish, non-native fish, invasive mollusk) and two or three natives they would most directly threaten if established.

What students take away. Students design a risk-based (not random) sampling scheme and defend it as consistent with real early-detection monitoring practice.

Track B — False Positives and Regulatory Consequences

Error cost asymmetry in biosecurity decisions

Driving question. How confident must a detection be before it triggers a costly management response, and what happens if we are wrong?

Species to pick. Up to five species selected so at least one pair includes an invasive and a closely related native or previously-established species, forcing an explicit discussion of primer specificity and cost of a false alarm versus a missed detection.

What students take away. Students construct a decision framework weighing the cost of a false positive (unnecessary management action) against a false negative (undetected spread).

Track C — Detection Probability and Monitoring Frequency

Statistical basis for surveillance program design

Driving question. Given the detection probability observed in one sampling event, how often would a monitoring program need to sample to be confident of catching an early invasion?

Species to pick. Up to five species with published detection-probability or occupancy-modeling data available from state or federal invasive species monitoring programs.

What students take away. Students use published detection-probability estimates to reason about how many independent samples a real monitoring program would need per season.

The lesson sequence

Step by step, with teacher notes

  1. 01

    Framing the biosecurity hypothesis

    50 minutes

    Teams select a track and write formal, falsifiable hypotheses about invasive species presence, citing regional invasive species watch lists or agency reports. Discussion emphasizes the asymmetric cost of false positives versus false negatives in a management context.

    Teacher notes

    • Open with: "In pest control and biosecurity, a false negative can cost a watershed years of recovery — your hypothesis has to take that seriously."
    • Require each H0/H1 pair to cite a specific regional invasive species list or agency source, and to state a testable prediction about detection.
    • Introduce the concept of asymmetric error cost explicitly: ask teams to state, for their chosen species, which error type (false positive or false negative) would be more costly to a real management agency and why.
    • Facilitate the class-wide vote consolidating team proposals into one shared five-species list, since only one vial is available.
    • Flag any proposed species without a documented, testable regional distribution and redirect before the vote.

    Materials

    • Regional invasive species watch list or agency report
    • Hypothesis worksheet with H0/H1 and error-cost template
    • Whiteboard for class vote

    Student prompts

    • State H0 and H1 for each of the five candidate species, citing a specific regional source.
    • For your species, which error (false positive or false negative) would be more costly to a management agency, and why?
    • What introduction pathway makes this species plausible at our site (e.g., boat traffic, bait release, connected waterway)?
  2. 02

    Risk-based composite sampling design and execution

    90 minutes

    Students design a sampling scheme modeled on real early-detection monitoring: sub-samples are drawn from the highest-risk introduction points at the site rather than randomly, then pooled into one composite sample. A data-integrity subgroup documents every site and rationale.

    Teacher notes

    • Frame this explicitly as risk-based (not random) sampling: "Real monitoring programs sample where the invader is most likely to show up first — where would that be here, and why?"
    • Require gloves before any equipment contact and sampling upstream/away from a point before it is disturbed by foot traffic.
    • Have the class debate and vote on which 3–4 site features (boat launch, inflow, bait disposal area, high-traffic dock) constitute the highest-risk introduction points, with a written rationale for each.
    • Assign a data-integrity subgroup to log GPS points, site type, and visible signs of human activity (litter, bait containers, boat traffic) for every sub-sample.
    • Model the pooling step yourself, then have the chain-of-custody subgroup verify documentation before sealing and shipping.

    Materials

    • 1 classroom eDNA collection vial and prepaid mailer
    • Nitrile gloves (one pair per student minimum)
    • Sterile sub-sample containers
    • GPS-enabled device or app
    • Chain-of-custody log sheet

    Student prompts

    • Justify why each chosen sub-sampling point represents a high-risk introduction pathway.
    • Record GPS location, site type, and signs of human activity for every sub-sample pooled.
    • What would a purely random sampling scheme have missed compared to this risk-based scheme?
  3. 03

    Detection probability, error cost, and monitoring theory

    50 minutes

    During the turnaround, students study published detection-probability and occupancy-modeling concepts as applied to real invasive-species monitoring programs, and connect false positive/negative risk to the specific regulatory or management actions those errors would trigger.

    Teacher notes

    • Use the wait window for a full lecture: introduce detection probability as p(detect | present) and connect it to why multiple samples across a season increase confidence.
    • Assign a short reading from a state or federal invasive species monitoring report showing real detection-probability estimates.
    • Say: "If detection probability per sample is 0.3, one sample tells you far less than you think — what does that mean for a program relying on a single kit?"
    • Walk through a concrete scenario: what management action would be triggered by a positive detection of the invasive species in this study, and what happens if that detection turns out to be a false positive?
    • Assign lab report introduction and methods sections due before the results reveal.

    Materials

    • Excerpt from a real invasive species monitoring / occupancy-modeling report
    • Diagram of eDNA lab pipeline
    • Vocabulary sheet: detection probability, occupancy modeling, Type I/II error, false positive/negative

    Student prompts

    • Define detection probability and explain why a single sampling event underestimates it for a rare or newly established species.
    • What management action would a positive detection of your invasive species trigger, and what is the cost of that action being based on a false positive?
    • Draft your lab report's introduction and methods sections before seeing the results.
  4. 04

    Results reveal and biosecurity risk assessment

    50 minutes

    The class Field Journal is revealed together. Students evaluate each hypothesis, discuss whether any detection would plausibly trigger a real management response, and identify what additional sampling would be needed before acting on the result.

    Teacher notes

    • Reveal results live; have students mark reject/fail-to-reject for each hypothesis independently before discussion.
    • For any positive invasive detection, run a structured debate: "Is this single result enough to justify a costly management response? What additional evidence would you want first?"
    • For any non-detection, explicitly reinforce that this does not rule out low-level or recent introduction, given known detection probability limits.
    • Require the lab report discussion to name a specific next step a real agency should take given this result (e.g., targeted follow-up sampling, no action, expanded monitoring).
    • Close by asking each team to draft one sentence of a management recommendation memo based on their result.

    Materials

    • Class Field Journal report (projected)
    • Lab report template
    • Management recommendation memo template

    Student prompts

    • For each species, state whether you reject or fail to reject H0, and why.
    • Is this result, by itself, strong enough evidence to justify a management response? Why or why not?
    • What single additional data source would most increase your confidence in acting on this result?
  5. 05

    Lab report finalization and peer review

    50 minutes

    Teams finalize their formal lab reports, incorporating a management recommendation section grounded explicitly in the statistical limitations of a single composite sample, and complete a structured peer review using the rubric.

    Teacher notes

    • Require every report to include a clearly labeled management recommendation section separate from the scientific discussion section.
    • Have peer reviewers specifically check whether the report distinguishes 'no detection' from 'confirmed absence' throughout, penalizing conflation.
    • Ask reviewers to verify at least one cited detection-probability or occupancy source is used correctly in the discussion.
    • Collect final reports and use this session to preview how the next kit's species list could be informed by this round's results.

    Materials

    • Lab report drafts
    • Peer-review rubric copies
    • Management recommendation memo template

    Student prompts

    • Does your management recommendation follow logically from the statistical strength (or weakness) of your evidence?
    • Where in your report might a reader mistake 'fail to reject H0' for 'proven absent'? Revise that language.
    • What would you propose as the next kit's species list, and why?

Student handout

For every student

Thinking prompts

  • Write formal null and alternative hypotheses, with citations, for each of the five target species.
  • State, for your species, which error type (false positive or false negative) is more costly to a management agency and why.
  • Justify the risk-based sub-sampling scheme in terms of realistic invasion introduction pathways.
  • Explain detection probability and why a single sampling event may underestimate it for a rare or newly established species.
  • State, for each species, whether the post-reveal result supports rejecting or failing to reject H0.
  • Draft a one-paragraph management recommendation grounded explicitly in the statistical strength of your evidence.

Data sheet

  • Date, time, and personnel for each sub-sampling event:
  • GPS coordinates and site type (boat launch, inflow, bait disposal area, dock) for each sub-sample:
  • Water temperature, flow, and visible signs of human activity at each site:
  • Number and volume of sub-samples pooled into the composite:
  • Pre-reveal hypothesis table (H0/H1 for all five species, with citations and error-cost notes):
  • Chain-of-custody log with preservation and shipping timestamp:
  • Post-reveal detection and relative signal table for all five species:

Discussion questions

  • Why might a risk-based sampling scheme detect an invasive species that a random scheme would miss?
  • What additional data would a real biosecurity agency require before authorizing a costly management response based on this result?
  • How does detection probability change your interpretation of a single non-detection versus a program of repeated seasonal sampling?
  • What are the ethical and resource tradeoffs of a $200 kit limited to five species in a real invasive-species monitoring context?

Field checklist

  • Null and alternative hypotheses, with citations and error-cost notes, written for all five species before sampling.
  • Class-wide agreement reached on risk-based sub-sampling sites before fieldwork begins.
  • Nitrile gloves worn and equipment kept away from disturbance at each site before it is sampled.
  • GPS, site type, and signs of human activity logged for every sub-sample pooled into the composite.
  • Chain-of-custody log completed and verified before shipping.
  • Lab report introduction and methods drafted before results were revealed.

Analysis

Detection probability and biosecurity risk assessment of composite sample results

  1. 1.For each of the five species, restate H0 and H1 and classify the post-reveal outcome as 'reject H0' or 'fail to reject H0.'
  2. 2.For any positive invasive detection, assess whether the evidence strength would plausibly justify a real management response, citing detection-probability limitations.
  3. 3.For any non-detection, explain why this does not constitute confirmed absence, referencing known detection probability estimates from the literature.
  4. 4.Identify any result plausibly affected by a false positive (primer cross-reactivity with a related native) or false negative (low density, degradation, dilution in composite).
  5. 5.Draft a management recommendation paragraph that explicitly states the confidence level supporting (or not supporting) an action.

Assessment

20-point rubric

Hypothesis formulation with error-cost analysis

4 pts

Falsifiable, cited H0/H1 pairs are written for all five species, each with a stated error-cost asymmetry.

Risk-based sampling design and field protocol

4 pts

Sub-sampling sites are justified by realistic introduction pathways and executed with documented contamination control.

Detection probability and error concepts

4 pts

Detection probability, false positives/negatives, and their management consequences are explained accurately.

Data interpretation and risk assessment

4 pts

Detection results are correctly linked to hypotheses and evaluated for management-decision strength.

Lab report and management recommendation

4 pts

Report follows standard scientific format and includes a recommendation appropriately calibrated to evidence strength.

Go further

Extensions

  • Partner with a state or local invasive species program to compare the class's protocol and results against real agency monitoring standards.
  • Have students calculate, using published detection-probability estimates, how many independent samples per season a real monitoring program would need for a given confidence level.
  • Invite a fisheries or invasive species biologist to critique the class's management recommendation memo.
  • Design a follow-up kit species list informed by this round's results, prioritizing species with the highest management stakes.

For the teacher

Answer key and misconceptions

  • Expected: student H0/H1 pairs should be falsifiable and cite a regional invasive species source; a common error is treating a detection prediction as a certainty rather than a probability statement — correct this explicitly.
  • Common misconception: 'no detection means the invasive isn't here.' Correct framing: detection probability from a single composite sample is well below 1.0, so a non-detection reduces but does not eliminate the possibility of presence.
  • Common misconception: any positive detection should immediately trigger costly management action. Correct framing: real biosecurity decisions weigh detection confidence, primer specificity, and confirmation sampling before committing resources.
  • Expected: strong lab reports explicitly state which error type (false positive or false negative) is more costly for their species and justify the claim in terms of ecological or economic consequences.
  • Common misconception: relative signal strength indicates population size of the invasive species. Correct framing: it is a proxy for shed DNA quantity, useful for flagging presence but not for estimating abundance or infestation severity.

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