A performance evaluation of surplus production models with time-varying intrinsic growth in dynamic ecosystems

Abstract

We conducted a simulation study to evaluate performance of surplus production models (SPMs) with a time-varying intrinsic growth rate (SPMTVr) for stocks with predation-driven changes in productivity. Data sets were simulated using an age-structured, linked, predator–prey model of Atlantic menhaden (Brevoortia tyrannus), a forage fish native to the Northwest Atlantic, and Atlantic striped bass (Morone saxatilis), its primary predator, with differing time series of fishing mortality on both predator and prey. Simulations generated test data sets for Atlantic menhaden SPMs that included either a static or time-varying intrinsic growth rate parameter. The SPMTVr largely produced more accurate, less variable estimates of exploitation rate and biomass than models with static intrinsic growth. We also applied SPMTVr to empirical Atlantic menhaden catch and survey data for 1964–2016. The SPMTVr fit the survey data well, estimated an intrinsic growth rate time series that mirrored long-term juvenile survey trends, and produced biomass and exploitation rate trends that mirrored a statistical catch-at-age model. The SPMTVr estimated dynamic, maximum sustainable yield (MSY)-based reference points that reflected changing stock productivity.