Feeding habits of bigeye tuna (Thunnus obesus) in the North Pacific from 2011 to 2013

In the present study, we analysed the stomach contents of 585 bigeye tuna (BET; Thunnus obesus) caught in the Kuroshio–Oyashio transition zone, a high-productivity region in the western North Pacific Ocean, to describe feeding habits and prey size. We identified 46 prey species belonging to 40 genera. Fish otoliths and squid beaks found in stomachs were used to calculate prey body length and weight from allometric relationships. The percentage index of relative importance (%IRI) was calculated from the mean percentage of occurrence, number and weight of each prey species. Squid and fish were the main prey of BET in the sampling area and the highest %IRI prey species during the survey was Eucleoteuthis luminosa (luminous flying squid; 7.6%), followed by Gonatopsis makko (mako armhook squid; 4.8%) and Magnisudis atlantica (duckbill barracudina; 2.3%). The %IRI of E. luminosa decreased and that of M. atlantica increased with increasing BET body length. The size of prey fish increased with increasing BET size, whereas the size of prey squid was similar across BET size. The results indicate ontogenetic shifts in the feeding habits of BET in the study area. These data provide fundamental information that will improve our understanding of oceanic food webs in the Kuroshio–Oyashio transition zone, an important foraging area for many pelagic species.

Making Better Decisions: Can Minimizing Frequentist Risk Help?

The concept of shrinking bet size in Kelly betting to minimize estimated frequentist risk has recently been mooted. This rescaling appears to conflict with Bayesian decision theory through the likelihood principle and the complete class theorem; the Bayesian solution should already be optimal. We show theoretically and through examples that when the modeldetermining the likelihood function is correct, the prior distribution (if not dominated by data) is `correct' in a frequentist sense, and the posterior distribution is proper, then no further rescaling is required. However, if the model or the prior distribution is incorrect, or the posterior distribution improper, frequentist risk minimization can be a useful technique. We discuss how it might best be exploited. Another example, from maintenance, is used to show the wider applicability of the methodology; these conclusionsapply generally to decision-making.

Effects of Alcohol and D-Amphetamine upon Mood and Volition

The purpose was to measure drug effects upon mood self-ratings and upon volitional outcomes presumably related to changes in mood. Alcohol, d-amphetamine and placebo were administered, separately and in combination, to 70 male volunteers who served as their own controls. Measures of volitional behavior included gambling for money, and verbal production on assigned topics. Mood self-ratings were interspersed. Alcohol increased the number of maximum bets but did not significantly increase average bet size or affect verbal production. D-amphetamine significantly increased verbal production but not risk-taking. There was no evidence of drug interaction in either of these measures of volitional behavior. However, there were interesting combinatorial effects upon the various mood dimensions, where the combination of alcohol and d-amphetamine produced additive, non-additive and supra-additive effects. As in some previous studies, drug effects on the mood self-ratings were found to be useful but uncertain predictors of plausibly relevant volitional behaviors.