Effects of Mixed‐Metric Data on Production Model Estimation: Simulation Study of a Blue‐Marlin‐Like Stock

An underlying assumption of surplus‐production modeling is that the model's two basic data streams (indices of abundance and records of catch) are expressed in the same metric, either biomass or numbers. For lack of data, that assumption is sometimes violated; recent assessments of blue marlin Makaira nigricans and white marlin Tetrapturus albidus in the Atlantic Ocean, for example, have used indices of abundance based on numbers with indices of catch based on biomass. We examined the effects of using mixed‐metric data in production modeling. Our method was a simulation study based on the life history and fishery characteristics of blue marlin in the Atlantic Ocean. Populations were simulated over a range of growth patterns and with either increasing or declining abundance by the use of a simulation model incorporating sex, size, and age structure; sexually dimorphic growth; variation of size at age; age‐varying natural mortality; and deterministic or stochastic recruitment. Simulated abundance data were aggregated across ages and combined with random errors to represent the data sets used in assessments. A logistic surplus‐production model was then fitted to those simulated data sets. The resulting estimates of maximum sustainable yield and stock status were surprisingly robust to the use of mixed‐metric data. Estimates from consistent data were generally more precise but not necessarily less biased. We thus conclude that this use of mixed‐metric data is acceptable for blue marlin and similar species. However, errors in estimation varied strongly by the growth pattern assumed, which indicates that better knowledge of growth patterns would allow future assessments to better define likely biases arising from the use of mixed‐metric data.