Large-scale experiment shows that nylon leaders reduce shark bycatch and benefit pelagic longline fishers

We assess the performance of wire leaders, which some jurisdictions have banned to reduce shark mortality from pelagic longline fishing. Experiments were conducted off northeastern Australia on commercial vessels that deployed equal numbers of wire and nylon monofilament leaders randomly along their longlines. Catch rates of several species, including sharks, were lower on nylon than on wire leaders, probably because those animals often escape by biting through the nylon leaders. High bite-off rates indicate that as many animals escape from nylon leaders as are caught on nylon leaders. The fate of escaped animals is not known, although large sharks are more likely to survive than are small animals. By contrast, catch rates of valuable bigeye tuna (Thunnus obesus) were higher on nylon than on wire leaders. Bigeye tuna are probably able to see wire leaders and avoid those hooks. The financial benefits of increased bigeye tuna catches outweigh the costs associated with banning wire leaders, such as increased rates of gear loss. Thus, banning wire leaders is an effective way of reducing shark catches that fishers should be keen to adopt.     

Estimating rates of mortality in stocks of Metapenaeus macleayi in estuaries of eastern Australia

Estimating rates of mortality is important for assessing stocks and for effectively managing seafood resources. This study reports the first estimates of rates of instantaneous fishing mortality (F) and natural mortality (M) for the commercially important school prawn, Metapenaeus macleayi. Replicated tag-recapture experiments were conducted on two stocks (Clarence River and Wallis Lake) to estimate the catchability coefficient (q) and F, whilst M was estimated from meta-analyses. Experiments were conducted across spatial and temporal scales to consider variability between stocks and variability between fisheries targeting this resource. The catchability coefficient was fitted to tag-recapture data in a population model across a range of M values (0.001-0.025 per day) and average daily F values were calculated. Values of q ranged between 2.03E−04 and 5.43E−02 and, 1.29E−04 and 3.41E−03 for the Clarence River and Wallis Lake stocks, respectively. Average daily F ranged between 2.86E−03 and 1.69 for the Clarence stock and 1.71E−03 and 3.44E−02 for the Wallis stock. With one exception (the November 2004 experiment) there were no differences in q and F values between experiments conducted on the Wallis Lake stock. For the Clarence stock values of q and F varied between years and within years. Factors thought to contribute to this variability were changes in prawn behaviour, differences in sizes of prawns tagged between experiments and differences in the survival of tagged prawns. The catchability coefficient for the Clarence River stock was weakly correlated to greater rates of river discharge. Estimates of F for the Wallis stock, the Clarence stock in 2004-05 and estimates of M were comparable to those reported for other penaeid fisheries world wide. There was no consistent pattern in comparisons of q and F values between the predominantly trawling operation of the Clarence River fishery and the seine netting of the fishery in Wallis Lake.     

Performance of deviance information criterion model selection in statistical catch-at-age analysis

Most stock assessments involve fitting alternative models and selecting among them to provide management advice. Incorrect model specification can lead to unreliable population and mortality estimates, and methods to decide among assessment models so as to obtain reliable estimates are needed. We used Monte Carlo simulations to assess whether using deviance information criterion (DIC) model selection and averaging resulted in improved accuracy of important management quantities from statistical catch-at-age models. We challenged DIC with three estimation models (that differed in how they estimated catchability) and three scenarios of data accuracy and time-varying catchability. DIC usually selected the structurally appropriate model, and point estimates from the best model or the model average were relatively unbiased in that the average deviation from the true value was near zero. The distributions of point estimates about true values from DIC-based model averaging and from the best model (lowest DIC) were similar, perhaps because all of the estimation models were quite similar to the data-generating models. DIC seems to provide a useful metric to compare evidence in favor of alternative assessment models. This study is one of the first to evaluate the performance of DIC in models where the purpose is to predict unobserved quantities.     

Higher food abundance reduces the catchability of cod (Gadus morhua) to longlines on the Faroe Plateau

The cod fishery at the Faroes has been managed since 1996 by an effort management system where it is assumed that there is a direct relationship between fishing mortality and fishing effort. We show that this relationship is weak. Due to a factor five variation in the primary production on the Faroe Plateau, the annual growth rate of cod may vary by a factor of five. Commercial catch-per-unit-effort data in combination with stock assessment estimates showed that there was a negative correlation between the annual growth rate of cod and their catchability with longlines, as well as with the total fishing mortality of cod on the Faroe Plateau. Furthermore, mark-recapture experiments showed that longline-caught cod in comparison with trawl-caught cod had a lower condition factor, a lower stomach content of natural prey, and a higher content of longline baits. During the feeding season in September–December, longline-caught cod exhibited a larger displacement distance than trawl-caught cod. These results were largely confirmed by storage tag data. Consequently, during low-productive periods, (i) the longline-dominated cod fishery at the Faroes exerted fishing mortalities that by far exceeded safe biological limits, and (ii) longline catch-per-unit-effort series might overestimate stock size considerably.