Tuna drift gillnet fishery at Chennai, Tamil Nadu- an update

The present study describes the status of multiday drift gillnet fishery for tuna from Chennai fishing harbour based on data for the years 2016 – 2017. The data is also compared with that during 1999- 2006. Both the craft and gear increased in size with consequent extension of fishing grounds and increase in the number of days/ fishing trip. The size of the boats increased to 20-23 m OAL from 11-12 m OAL and weight of the gear from 1 to more than 6 t. Annual average catch increased to 8523 t during 2016-2017 from 595 t during 1999-2006. Average catch per unit effort was 8310 kg as against 730 kg during 1999-2006. Yellowfin tuna, Thunnus albacares and Skipjack tuna, Katsuwonus pelamis were the dominant species. The stock position of skipjack tuna and yellowfin tuna vis-àvis the three indicators indicated that the percentage of mature yellowfin tuna in the catch in 2017 was 68%, fish in optimum length 35% and mega-spawners 33% whereas in skipjack tuna the respective percentages were 99.5, 21.1 and 79.1. Problems and prospects of multiday tuna drift gillnet fishery are also discussed

Fishery, biology and dynamics of dogtooth tuna, Gymnosarda unicolor (Rüppell, 1838) exploited from Indian seas

Dogtooth tuna, Gymnosarda unicolor (Rüppell, 1838) (Fig. 1) is a pelagic tuna preferring waters of temperature between 21 and 26 oC. It is one of the principal species exploited by hook and line (recreational as well as commercial fishery) operated in the oceanic region. Meat of dogtooth tuna is white and so it has great demand and fetch high price (IUCN, 2011). However, occasional ciguatera fish poisoning in humans has been reported on consumption of dogtooth tuna. It is exported in fresh and frozen state and is used for the production of sashimi, canned tuna, and pouch products. Most of the world landings of dogtooth tuna during 1963 -2006 was from the Indian Ocean. Small scale tuna long lines for the species operating in the Indian Ocean belong to Taiwan, Srilanka, Maldives, Japan or Pakista

Fishery, population dynamics and stock structure of frigate tuna Auxis thazard (Lacepede, 1800) exploited from Indian waters

Auxis thazard, commonly known as frigate tuna represents an important group of coastal tuna species occurring in the Indian waters. The species is landed all along the Indian coastline and the major landing is along the south-west coast with Kerala contributing the most. The species is exploited by a variety of gears viz., drift gill nets, shore seines, ring seines and hooks and lines. Though there is recent information on the fishery and the exploitation status of Auxis thazard from Tuticorin (Kasim, 2002; Abdussamad et al., 2005) and Veraval (Ghosh et al., 2010), studies on the catch, population characteristics and stock estimates covering the entire coasts of India are lacking after the work of Silas et al. (1985) and James et al. (1993). These studies date back to two decades, after which there has been a change in the fishing pattern of coastal tunas throughout the country. Therefore, the present study was undertaken to provide an insight into the fishery, population dynamics and stock structure of A. thazard exploited from Indian water

Stock assessment of Indian squid, Uroteuthis (Photololigo) duvaucelii (d'Orbigny [in Férussac & d'Orbigny], 1835) from south-western Bay of Bengal

Stock assessment of the Indian squid Uroteuthis (Photololigo) duvaucelii off north Tamil Nadu coast from commercial trawl landings was studied during the period 2012-2016. The species is mainly caught by trawl net and the annual average landing of the species was 563.3 t contributing to 2 % to the total trawl landing along north Tamil Nadu coast. L∞, K and t0 were estimated as 260 mm, 0.84 yr-1 and -0.105 yr, respectively. Total mortality rate (Z), Natural mortality rate (M), and Fishing mortality rate (F) were 4.43 yr-1, 1.67 yr-1 and 2.78 yr-1, respectively. tmax was estimated to be 3.47 yr. The length atfirst capture (Lc50 = 62 mm) estimated by Length converted catch curve method was found to be lower than Length at first maturity (Lm50 = 80 mm). Furthermore, Ecurr (current exploitation rate) was found be on higher side than the Emax (0.48) and E0.1 (0.40) which indicates that the fishery is in overexploited stage. Thompson and Bell prediction model showed that a marginal decrease (20 %) in current level of exploitation would help in regeneration of stock for long term sustainability of the resources as well as in achieving maximized economic return

Assessment of the fishery and stock of striped bonito, Sarda orientalis (Temminck and Schlegel, 1844) along Kerala coast with a general description of its fishery from Indian coast

The striped bonito Sarda orientalis (Temminck and Schlegel, 1844) has a wide distribution in the Indo- Pacific region from east coast of Africa to the west coast of America (Jones, 1960). It grows to a length of over half a metre and does not form a regular fishery of any appreciable magnitude anywhere

Status and prospects of Large Pelagics fishery in Tamil Nadu and Puducherry

The status of the landing of large pelagic fishery including the resource-wise contribution and their species composition in Tamil Nadu and Puducherry is presented based the on the estimated fish landings data for the period 2007-2019. The large pelagics landing in Tamil Nadu varied from 30,659 t to 83,620 t with an average of 45,330 t. In Puducherry, it varied from 254 t to 5,453 t with an average of 2,515 t. Various crafts and gears involved in the fishery are described while the future prospects and management issues are flagged

Indian tuna fishery - production trend during yesteryears and scope for the future

Fishery for tuna and tuna like fishes in the country has been in vogue from time immemorial and presently involves fishery by coastal based fleets of varying specifications with different craft-gear combinations and longline fishery by large oceanic fishing vessels. The former undertakes short duration fishing trips and exploit mainly surface tunas in the outer shelf and adjacent oceanic waters. The tuna landings though nominal during 1950-2005, registered a continuous increase over the years from a minimum of 848 t (1951) to 46,334 t (2000). With the introduction of targeted fishing for oceanic tunas during 2005-‘06, the landings improved and reached the maximum of 129,801 t in 2008. The fishery was supported by nine species, five coastal/neritic species and four oceanic species. Coastal tunas formed 57% of the tuna catch during 2006-’10 and was represented by the little tuna (Euthynnus affinis), frigate tuna (Auxis thazard), bullet tuna (Auxis rochei), longtail tuna (Thunnus tonggol) and bonito (Sarda orientalis). The oceanic species, which formed 43% of tuna catch, were yellowfin tuna (Thunnus albacares), skipjack tuna (Katsuwonus pelamis), dogtooth tuna (Gymnosarda unicolor) and bigeye tuna (Thunnus obesus). Information collected from different sources suggested that longliners operating in Indian EEZ and adjacent international waters caught around 87,000 t of tuna annually during 2006-'10. Catch was supported by three species dominated by yellowfin tuna and small proportion of big-eye and dogtooth tuna. Since fishery by coastal based units restricted to small areas and share of the catch by longliners from EEZ are not clearly known, systematic assessment of tuna stock in Indian EEZ is very difficult. However, the evaluation of the fishery scenario indicated only limited scope for improving tuna production from certain areas of coastal waters; whereas enormous scope remain for increasing tuna production from the oceanic waters of EEZ. However, since tunas being straddling resources shared by several nations, exploitation at one area will influence the fishery in other areas

Minimum Legal Size proposed for commercially exploited marine finfish and shellfish resources of Tamil Nadu

Marine fisheries in Tamil Nadu have undergone tremendous change in terms of fishing pattern, fishing method, extension of fishing grounds, composition of fish catch and consequent increase in the total fish catch in recent years. The recent demand from industries involved in fish meal and fish oil encourages targeted fishing for by-catch resulting in heavy landing of low value by-catch in certain places along Tamil Nadu coast. These by-catch are often dominated by juveniles of many commercially important marine finfishes and shell fishes. So it warrants some caution and intervention. One of the methods to discourage the indiscriminate exploitation of juveniles is to impose a Minimum Legal Size (MLS) which is the size at which a particular species can be legally retained if caught. The advantage of a MLS is that it aids in the control of two major problems in the fisheries management, growth overfishing and recruitment overfishing either by increasing the minimum size of harvest or by increasing or maintaining the size of the spawning stock. The most common method of increasing the reproductive output through the use of size limits is to set the minimum size at which the females become sexually mature. As the individuals of a species do not attain sexual maturity at the same size, it can be a size at which higher proportions are mature

Prediction and understanding of soft proton contamination in XMM-Newton: a machine learning approach

One of the major and unfortunately unforeseen sources of background for the current generation of X-ray telescopes are few tens to hundreds of keV (soft) protons concentrated by the mirrors. One such telescope is the European Space Agency's (ESA) X-ray Multi-Mirror Mission (XMM-Newton). Its observing time lost due to background contamination is about 40\%. This loss of observing time affects all the major broad science goals of this observatory, ranging from cosmology to astrophysics of neutron stars and black holes. The soft proton background could dramatically impact future large X-ray missions such as the ESA planned Athena mission (http://www.the-athena-x-ray-observatory.eu/). Physical processes that trigger this background are still poorly understood. We use a Machine Learning (ML) approach to delineate related important parameters and to develop a model to predict the background contamination using 12 years of XMM observations. As predictors we use the location of satellite, solar and geomagnetic activity parameters. We revealed that the contamination is most strongly related to the distance in southern direction, $Z$, (XMM observations were in the southern hemisphere), the solar wind radial velocity and the location on the magnetospheric magnetic field lines. We derived simple empirical models for the first two individual predictors and an ML model which utilizes an ensemble of the predictors (Extra Trees Regressor) and gives better performance. Based on our analysis, future missions should minimize observations during times associated with high solar wind speed and avoid closed magnetic field lines, especially at the dusk flank region in the southern hemisphere.Comment: 20 pages, 11 figure