Reading species models beyond sampled ocean conditions

A complete species-distribution map can conceal large gaps in environmental support. This methods note uses published environmental-novelty, transferability, and structured-validation research to distinguish interpolation from extrapolation in ocean applications. A hypothetical temperature-salinity example separates a new predictor range from a novel combination that lies within every individual range. Further decision cases examine structural disagreement beyond training conditions, clamping, observation bias, and validation splits matched to intended deployment. No real species model is fitted or range shift predicted, and terrestrial or freshwater case-study results are not imported as marine performance rankings. The practical output is a prediction accompanied by its evidence boundary, uncertainty, and sensitivity, making explicit where additional surveys would be more informative than an unqualified probability surface.