Predicting nonlinear dynamics of short-lived penaeid shrimp species in the Gulf of Mexico

Predicting the dynamics of harvested species is essential for assessing stock status and establishing index-based management strategies. However, conventional approaches for short-lived species predict dynamics poorly, possibly because unobserved interactions with other species and abiotic factors are often treated as noise. Alternatively, the empirical dynamic modeling (EDM) approach, which uses the time delays of the observed states to compensate for unobserved interactions, may improve the predictions for short-lived species. We test this idea using time series data of two federally managed, short-lived penaeid shrimp species, whose abundances were surveyed over 30 years (1987-2018) across the US Gulf of Mexico. We show that (i) abundance dynamics of these annual shrimp stocks are well-predicted by EDM, (ii) the dynamics are spatially similar across most of the gulf, and (iii) the stock dynamics are characterized by nonlinear density-dependent interaction and vary with temperature. Our findings suggest that EDM may be more responsive than single-species, catch-at-age models in assessing the stock dynamics for short-lived penaeid shrimp species. Key words: penaeid shrimp fisheries, short-lived species, nonlinear time-series forecasting, dynamic correlation, spatial synchrony, Gulf of Mexico fisheries management
Introduction Dynamics of short-lived marine species are notoriously difficult to predict, often exhibiting large fluctuations in population size and increased sensitivity to environmental variability compared with longer-lived stocks (Hsieh et [...]