Study Design (conbio-study-design)

SkillMedia

Use when defending the study design of a Conservation Biology manuscript, ecological sampling and inference (detection, spatial structure, pseudoreplication), comparative/observational and quasi-experimental designs (BACI), modeling and synthesis design, and human-dimensions methods. The journal judges each appropriate method on its own terms. Strengthens the design; it does not write code.

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the Study Design (conbio-study-design) skill

What this skill tells your AI

The instructions your AI receives, as published by brycewang-stanford/awesome-journal-skills in Conservation-Biology-Skills/skills/conbio-study-design/SKILL.md and read by ahel’s review.

Conservation Biology accepts many methodologies but is demanding about each. The design must credibly connect the conservation question (conbio-topic-selection) to evidence that supports a transferable, decision-relevant conclusion. This skill is mode-aware: pick the section that matches your work and defend it against the strongest alternative explanation.

When to trigger

  • Specifying sampling, comparison, or modeling design before fieldwork or analysis
  • A reviewer questioned detection, replication, spatial autocorrelation, or causal claims
  • Designing an intervention/management evaluation or a synthesis protocol
  • Justifying why your design adjudicates the rival account from conbio-literature-positioning

Field & observational ecology

  • Account for detection. Imperfect detection biases counts — use occupancy, distance sampling, or capture-recapture rather than raw indices when detection varies.
  • Replication and scale. Avoid pseudoreplication; define the independent unit; match the spatial and temporal scale of sampling to the inference. State the sampling frame.
  • Spatial structure. Address spatial autocorrelation and spatial bias (sampling effort, access).

Comparative / quasi-experimental (intervention evaluation)

  • Use BACI / before-after-control-impact, control-impact, or matched designs to attribute change to a conservation action rather than to background trend.
  • Counterfactual thinking. What would have happened without the protected area / policy / harvest rule? Matching, difference-in-differences, or synthetic controls where appropriate.
  • State confounders (accessibility, prior condition) and how the design or analysis handles them.

Modeling & synthesis

  • SDM / niche / population models: justify predictors, address sampling bias and collinearity, validate out-of-sample; state transferability limits before projecting.
  • Systematic review / meta-analysis: follow PRISMA / CEE protocols; preregister where possible; document search, screening, and effect-size extraction.

Human dimensions / social science

  • Match the method (surveys, interviews, choice experiments) to the question; report sampling, ethics, consent, and how respondent identity and sensitive data are protected.

The adjudication test (journal-specific)

For the single strongest rival explanation, write one sentence: "If the rival were true rather than my conclusion, the data would look like ___; instead they look like ___." If you cannot, the design does not yet support a transferable conservation claim.

Anti-patterns

  • Raw counts treated as abundance with no detection model
  • Pseudoreplication; inference at a scale the sampling cannot support
  • "Effect of the intervention" with no counterfactual or control
  • SDM/model projected far outside its training range with no transferability caveat
  • A design that cannot distinguish your conclusion from the leading alternative

Operating pass for Conservation Biology

Treat this skill as an executable review pass, not a prose hint. First lock the species/system threat, conservation decision, and uncertainty relevant to action; then judge whether the current manuscript answers the venue's real reader: conservation-science reviewers who ask whether evidence changes biodiversity, management, or policy action.

  • Do the pass: Return a claim-evidence-risk ledger rather than a prose-only diagnosis; every recommendation must point to a manuscript location or missing artifact.
  • Return a ledger: give claim / evidence / risk / manuscript location rows, so the next agent can edit rather than rediscover the issue.
  • Sibling guard: compare against Biological Conservation for applied conservation breadth, Global Change Biology for climate/ecosystem process, Ecology Letters for theory-forward ecology; if a sibling owns the contribution, recommend re-routing before polishing format.
  • Submission-ready gate: do not give final advice until the pack's resources/official-source-map.md has been checked for upload-week rules and the manuscript has one concrete fix for the largest venue-specific risk.

Output format

【Mode】field-ecology / quasi-experimental / modeling-synthesis / human-dimensions
【Question / estimand】what is being measured or attributed
【Key assumption(s)】detection, scale, counterfactual, transferability — how each is defended
【Rival ruled out】the adjudication sentence
【Robustness/sensitivity】planned checks
【Next】conbio-data-analysis

Supplementary resources

Signals

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Item type
skill
Key
conbio-study-design
Source
github.com/brycewang-stanford/awesome-journal-skills