Labotes surinamensis, are migratory fish that occur worldwide in warm seas, including the Gulf of Mexico and Caribbean. In the north-central Gulf of Mexico, tripletail support small recreational and commercial fisheries from April to Oct. and are commonly caught in bays and estuaries. Few studies have evaluated the life history and biological characteristics of tripletail; therefore, the objective of this study was to examine the age and growth, reproductive biology, and diet of tripletail caught off coastal Alabama. Our primary goal was to use life history information to determine. a minimum size limit for harvest. A secondary goal was to compm•e the results of our study with those of previous tripletail studies. A total of 119 specimens, ranging in size from 293-to 763-mm total length (TL), were collected from recreational anglers and from a wholesale seafood dealer between May 1998 and Aug. 2000. Female specimens were significantly longer and heavier than males. Total length varied greatly with age, although significant overlap in lengths was observed among ages. Age ranged from 0.87 to 4.09 yr. No male was older than 3.15 yr of age, whereas five females were estimated to be more than 4 yr old. Fifty percent of females reached sexual maturity by 494-to 594-mm TL and approximately 1 to 2 yr of age. All males greater than 380 mm were sexually mature. Diets were composed primarily of penaeid shrimps, various pelagic fish species, and portunid crabs, with the proportion of fish consumed increasing with tripletail length. On the basis of the results of this study as well as previous research on the life history and population dynamics of tripletail, the state of Alabama implemented a 406 mm (16 inch) minimum size limit for this species. This size limit is below the female size at 50% maturity (19.5-23.5 inch) and should be increased if large increases in fishing pressure occur.

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Big data, such as vessel monitoring system (VMS) data, can provide valuable information on fishing behaviours. However, conventional methods of detecting behaviours in movement data are challenged when behaviours are briefer than signal resolution. We investigate options for improving detection accuracy for short-set fisheries using 581 648 position records from 181 vessels in the Gulf of Mexico bandit-reel fishery. We first investigate the effects of increasing VMS temporal resolution and find that detection accuracy improves with fishing-set duration. We then assess whether a feature engineering approach—in our case, changing the way pings are labelled when training a classifier—could improve detection accuracy. From a dataset of 12 184 observed sets, we find that the conventional point-labelling method results in only 49% of pings being correctly labelled as ‘fishing’, whereas a novel window-labelling method results in 88% of records being labelled as ‘fishing’. When the labelled data are used to train classifiers, point labelling attains true-positive/balanced-accuracy rates of only 37%/66%, whereas window labelling achieves 68%/83%. Finally, we map fishing distribution using the two methods, and show that point labelling underestimates the extent of fishing grounds by ∼33%, highlighting the benefits of window labelling in particular, and feature engineering approaches in general.

Decision-making agents face a fundamental trade-off between exploring new opportunities with risky outcomes versus exploiting familiar options with more certain but potentially suboptimal outcomes. Although mediation of this trade-off is essential to adaptive behavior and has for decades been assumed to modulate performance, the empirical consequences of human exploratory strategies are unknown beyond laboratory or theoretical settings. Leveraging 540,000 vessel position records from 2494 commercial fishing trips along with corresponding revenues, here we find that during undisturbed conditions, there was no relationship between exploration and performance, contrary to theoretical predictions. However, during a major disturbance event which closed the most-utilized fishing grounds, explorers benefited significantly from less-impacted revenues and were also more likely to continue fishing. We conclude that in stochastic natural systems characterized by non-stationary rewards, the role of exploration in buffering against disturbance may be greater than previously thought in humans.