When “Data” Are Not Data: The Pitfalls of Using Stock Assessment Model Output to Make Inference about Ecosystem Dynamics

Stock assessment estimates of population abundance (biomass) have been treated as data in subsequent ecosystem modeling efforts.  These ecosystem models frequently overlook the uncertainty in the assessment output, potential bias and correlation among estimates, and the structural assumptions of the original assessment model.  These oversights have led to contradictory conclusions about ecosystem dynamics, ephemeral relationships between environmental covariates and stock dynamics, and a general lack of incorporation of ecosystem dynamics in assessment and management.  We use examples from the literature to demonstrate these problems.  We suggest alternative approaches that could have avoided using assessment model output altogether or suggest analyses that may have exposed the pitfalls of such methods.  Whenever possible, we suggest not using stock assessment model output as data in post hoc analyses.  If using assessment model output as data is unavoidable, then to address some aspects of the uncertainties associated with using assessment model estimates, we suggest collaborating with lead assessment scientists, sensitivity analyses, errors-in-variables methods, and cross-validation methods.  Such additional work is imperative if research that uses stock assessment output as data is to make robust and meaningful contributions to stock assessment methodology and management decisions.