160 research outputs found
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 тАУ 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-├аvis
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 (R├╝ppell, 1838) exploited from Indian seas
Dogtooth tuna, Gymnosarda unicolor (R├╝ppell, 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 F├йrussac & 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. LтИЮ, 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-тАШ06, 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-тАЩ10 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, , (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
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