No abstract

The correct prediction of the shape and strength of density dependence in productivity is key to predicting future stock development and providing the best possible long-term fisheries management advice. Here, we identify unbiased estimators of the relationship between somatic growth, recruitment and density, and apply these to 80 stocks in the Northeast Atlantic. The analyses revealed density-dependent recruitment in 68% of the stocks. Excluding pelagic stocks exhibiting significant trends in spawning stock biomass, the probability of significant density dependence was even higher at 78%. The relationships demonstrated that at the commonly used biomass limit of 0.2 times maximum spawning stock size, only 32% of the stocks attained three quarters of their maximum recruitment. This leaves 68% of the stocks with less than three quarters of their maximum recruitment at this biomass limit. Significantly lower recruitment at high stock size than at intermediate stock size was seen in 38% of the stocks. Density dependence in late growth occurred in 54% of the stocks, whereas early growth was generally density-independent. Pelagic stocks were less likely to exhibit density dependence in recruitment than demersal and benthic stocks. We recommend that both the degree to which productivity is related to density and the | 813 RINDORF et al.

Cod (Gadus morhua) are preyed upon by grey seals (Halichoerus grypus) and there is debate over the impact this has had on the decline of stocks and their prospects for recovery. We analysed a depleted stock to the West of Scotland and show that seal predation rate is consistent with a type II functional response. Forward projections of a model including the functional response under varying levels of fishing and seal population size suggest that stock recovery is possible under current conditions but there is a modest probability that the stock will decline further in both the short and long term. The potential recovery is fragile and sensitive to relatively small increases in either fishing or seal predation. Forward projection models that exclude the functional response estimate a lower probability of stock decline and may underestimate the risk to the stock. At low stock sizes and high fishing mortality rates functional response models project slower recovery but the opposite is true at low fishing mortality

Multispecies stock assessment models require predator diet data, e.g. stomach samples. Diet data can be unavailable, sparse, of small sample size, or very noisy. It is unclear if multispecies interactions can be estimated without bias when interactions are weak. Research is needed about how model performance is affected by the availability or quality of diet data and by the method for fitting it. We developed seven age-structured operating models that simulate trophic interactions for two fish species and different scenarios of diet data availability or quality. The simulated data sets were fitted using four statistical catch-at-age models that estimated fishing, predation and residual natural mortality and differed in the way the diet data was fitted. Fitting the models to diet data averaged over time should be avoided since it resulted in estimation bias. Fitting annual diet composition per stomach produced bias estimates due to the occurrence of zeros in the observed proportions and the statistical assumptions for the diet model. Fitting to annual stomach proportions averaged across stomachs led to unbiased results even if the number of stomachs was small, the interactions were weak or some sampled years and ages were missing. These methods should be preferred when fitting multispecies models.