Lab-to-Field Fitness Transfer Audit

Why It Matters

The Atlas increasingly uses laboratory fitness to support ecological interpretation. That is valuable, but it needs an audit trail: which fitness signals transfer, under what metadata conditions, and where field covariates dominate?

Review Brief

What changed: more topics now use lab-to-field logic, including metal validation, ecotype/environment pages, and long-term perturbation interpretation.

Why review matters: reviewers should define when lab fitness is a strong prior, when it is validated field evidence, and when missing covariates block interpretation.

Evidence to inspect:

• Lab fitness signals versus field ecology for the guardrail.
• Environment Harmonization Labels for field metadata quality.
• lab_field_ecology, field_vs_lab_fitness, and bacdive_metal_validation for known transfer cases.
• harvard_forest_warming for a design-confound caution around omics interpretation.

Questions for reviewers:

• Which lab phenotypes transfer well enough to support field claims?
• What metadata completeness threshold should be required?
• Should failed or blocked transfer cases become a derived benchmark?
• Which missing geochemistry or environment fields would unlock the most claims?

Evidence Base

The strongest starting point is the combination of lab-field ecology, metal validation, BacDive phenotypes, and environment harmonization. The audit should distinguish support for a narrow claim from evidence for broad field prediction.

Work Package

Create a matrix of lab phenotype classes, field environments, available covariates, and predictive performance. Label each claim as supported, conditionally supported, blocked by metadata, or contradicted. Capture the missing data that would most improve each blocked case.

Decision Use

This gives future Atlas pages a clear standard for using lab fitness as ecological evidence. It also identifies which new BERDL joins or field metadata would unlock the most claims.