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http://krishi.icar.gov.in/jspui/handle/123456789/63496
Title: | El Nino Southern Oscillation (ENSO) impact on tuna fisheries in Indian Ocean |
Other Titles: | Not Available |
Authors: | Manjusha,U Pillai,N G K Satheeshkumar,P |
ICAR Data Use Licennce: | Not Available |
Author's Affiliated institute: | Not Available |
Published/ Complete Date: | 2014 |
Project Code: | Not Available |
Keywords: | Climate Indian Ocean ENSO El Nino La Nina Sea surface temperature Tuna |
Publisher: | Springer |
Citation: | Not Available |
Series/Report no.: | Not Available |
Abstract/Description: | El Nino Southern Oscillation (ENSO) is an important driver of interannual variations in climate and ecosystem productivity in tropical regions. However, detailed information about this important phenomenon of the Indian Ocean is scarce. Consequently, the objective of this study is to improve understanding of the impact of warm event El Nino and cool event La Nina on annual tuna landings from the Indian Ocean from 1980 to 2010. In this study, maximum tuna landings were recorded during a weak El Nino year (1456054 t in 2006) and during a weak La Nina year (1243562 t in 2000), although the lowest tuna catch was followed during the strong El Nino year (1204119 t in 2009) and during a strong La Nina year (706546 t in 1988). Validation of predicted tuna landings and SST were showing a significant positive correlation (p < 0.01) was observed all the major tuna species except Southern Bluefin Tuna. Whereas the other relationships such as sea level pressure, Wind actions; Zonal Wind (U), Meridonial Wind (V), and Scalar Wind (W) are less well-defined. In contrast with principal component analysis we find that Principal Components 1 explains 75.5% of the total variance and suggest that sea surface temperature plays a major role in determining tuna availability in the region especially during warm event El Nino years; landings in Indian Ocean tend to be optimum SST 25 to 26°C in ENSO event. Our results confirm the ENSO impact on climate, tuna abundance and production in the Indian Ocean. However, among the oceanic variables SST explained the highest deviance in generalized additive models and therefore considered the best habitat predictor in the Indian Ocean followed by sea level pressure and Winds (U, V, W). |
Description: | Not Available |
ISSN: | Not Available |
Type(s) of content: | Article |
Sponsors: | Not Available |
Language: | English |
Name of Journal: | SpringerPlus |
Volume No.: | 3 |
Page Number: | 44209 |
Name of the Division/Regional Station: | Not Available |
Source, DOI or any other URL: | http://www.springerplus.com/content/3/1/591 http://eprints.cmfri.org.in/10393/1/El_Nino_Southern_Oscillation_(ENSO)_impact_on_tuna_fisheries_in_Indian_Ocean.pdf |
URI: | http://krishi.icar.gov.in/jspui/handle/123456789/63496 |
Appears in Collections: | FS-CMFRI-Publication |
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