Predicting recovery trajectories for the large species and large fish indicators

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How quickly and to what level do commercial fish stocks recover following release from fishing? Addressing these questions is imperative for long‐term management of overexploited stocks. We use an innovative multi‐trophic model to predict how fish community structures recover from different fishing scenarios when fishing is reduced. This model realistically captures many properties of Northeast Atlantic shelf communities. In particular, it has a unique stochastic algorithm allowing up to thousands of model species to stably coexist, thus allowing realistic species richness to be modelled. Fish community structure is quantified using the large species indicator (LSI) and large fish indicator (LFI), two complementary size‐based indicators. We discovered that targeting large fish species or non‐selective fishing of all fish species always decreased the LSI and LFI. In addition, equilibrium recovery levels decreased with increasing fishing mortality rate F and duration of fishing, reflecting local population extinctions of large fish species. Importantly, recovery times were typically decadal but can be longer than a century, supporting management on at least decadal time‐scales. Furthermore, model communities with realistic richness had recovery trajectories that followed exponential functions, providing a potential gateway for estimating future states. However, those with unrealistic richness had trajectories that fluctuated more and did not follow exponentials—methodologically, this cautions against using models with unrealistic richness to predict recovery. Lastly, simulations for the North Sea, with LFI dynamics following empirical data from 1920 to 2001, suggest that an average F across species <0.2 year–1 is required for LFI recovery to the reference point.