Analysis of Big Game Fishing Catches of Blue Marlin (Makaira nigricans) in the Madeira Archipelago (Eastern Atlantic) and Factors that Affect Its Presence

The archipelago of Madeira (Portugal) is one of the main European big game fishing locations, where the main target species is the blue marlin (Makaira nigricans). Catch data for these fish were used to analyze their presence over the years, estimate their average weights, and calculate annual fishing success rates. The results showed a marked seasonal effect, with higher average catch rates in summer (June–July), suggesting a migration from the equatorial waters they inhabit at the beginning of the year to northern areas when the waters become warmer. The influences of some environmental factors were analyzed using generalized additive models, and it was observed that the occurrence of blue marlin may be influenced by water temperature, wind, rain, and atmospheric pressure. This fishery did not register a high mortality rate in blue marlin specimens due to the usual practice of catch and release; individuals captured in this fishery can be used as a source of information that allows for follow-up on the status of the blue marlin population in the region.

BILLFISH CATCHES FROM OCEANIC RECREATIONAL FISHING IN THE ROYAL CHARLOTTE BANK, BAHIA, BRAZIL

The aim of this study was to analyze the oceanic recreational fishing in the Royal Charlotte Bank, state of Bahia, Brazil. Only data from an oceanic recreational fishing operator based in the municipality of Canavieiras, southern Bahia, were used, from 2012 to 2017. Overall, 103 fish specimens were caught and released, during this period, belonging to the following species: Makaira nigricans, Kajikia albida, and Istiophorus platypterus. Fishery operations occurred from October to March, with the highest catch in number in December (56.3%). The largest annual catch was recorded in 2013, with 39 individuals. The catch per unit effort ranged from 1.0 to 1.4 fishes per trip, with the highest value in December. Even though data presented here are partial, they can help to establish a strategic scenario for the fishing sector in Bahia, along with data from other fishing sectors (artisanal, industrial, subsistence and scientific).

Oil gland and oil pores in billfishes: in search of a function

ABSTRACTBillfishes are well known for their distinctive elongated rostra, i.e. bills. The functional significance of billfish rostra has been frequently discussed and the recent discovery of an oil gland (glandula oleofera) at the base of the rostrum in swordfish, Xiphias gladius, has added an interesting facet to this discussion regarding the potential co-evolution of gland and rostra. Here, we investigated the oil gland and oil pores (through which the oil is brought to the skin surface) of four billfish species – swordfish, Atlantic blue marlin (Makaira nigricans), Indo-Pacific sailfish (Istiophorus platypterus) and striped marlin (Kajikia audax) – and provide detailed evidence for the presence of an oil gland in the last three. All four species had a high density of oil pores on the forehead which is consistent with the hypothesis of hydrodynamic benefits of the oil. The extension of the pores onto the front half of the rostrum in sailfish and striped marlin, but not in swordfish or blue marlin, suggests that the oil may have additional functions. One such function could be linked to the antibacterial and anti-inflammatory properties of the oil. However, the available evidence on predatory rostrum use (and hence the likelihood of tissue damage) is only partly consistent with the extension of pores on rostra across species. We conclude that the oil gland probably serves multiple, non-mutually exclusive functions. More detailed information on rostrum use in blue marlin and swordfish is needed to better link behavioural and morphological data with the aim of accomplishing a full comparative analysis.

Incorporating depth into habitat use descriptions for sailfish Istiophorus platypterus and habitat overlap with other billfishes in the western North Atlantic

The sailfish Istiophorus platypterus is a circumglobal billfish species. It is commonly targeted in recreational fisheries and caught as by-catch in commercial fisheries, and therefore fisheries management would benefit from an enhanced understanding of basic patterns of the species’ daily and seasonal movements. Between 2002 and 2007, 87 billfish were tagged with pop-off satellite archival tags in the Atlantic waters off the coast of South Carolina, USA, including sailfish (n = 54), blue marlin Makaira nigricans (n = 15), and white marlin Kajikia albida (n = 18). Only fish meeting specific tag program criteria and length of tag attachment were selected for further analysis (sailfish, n = 19; blue marlin, n = 4; white marlin, n = 3). Differential horizontal and vertical movement patterns were observed within sailfish by season. Two- and three-dimensional (3D) analyses showed differential spatial niche use by sailfish. Among the istiophorid species, 3D analysis showed less overlap when occupying similar horizontal areas. The results from this study, in conjunction with similar studies from other areas, provide a better understanding of habitat usage that can be applied to address uncertainties in ecology or management, such as characterization of stock structure, identifying potential spawning habitat or intra-specific competition, providing correction factors for indices of abundance, and characterizing vulnerability to fishing gear.

Identifying the species of harvested tuna and billfish using deep convolutional neural networks

Fish catch species provide essential information for marine resource management. Some international organizations demand fishing vessels to report the species statistics of fish catch. Conventionally, the statistics are recorded manually by observers or fishermen. The accuracy of these statistics is, however, questionable due to the possibility of underreporting or misreporting. This paper proposes to automatically identify the species of common tuna and billfish using machine vision. The species include albacore (Thunnus alalunga), bigeye tuna (Thunnus obesus), yellowfin tuna (Thunnus albacares), blue marlin (Makaira nigricans), Indo-pacific sailfish (Istiophorus platypterus), and swordfish (Xiphias gladius). In this approach, the images of fish catch are acquired on the decks of fishing vessels. Deep convolutional neural network models are then developed to identify the species from the images. The proposed approach achieves an accuracy of at least 96.24%.