Fishery forecast using OCM chlorophyll concentration and AVHRR SST: validation results off Gujarat coast, India

Dwivedi, R. M.; Nayak, Shailesh; Somvanshi, Vishal Singh; Gulati, D.K.; Pattnayak, S. K.

doi:10.1080/0143116031000117029

Cited by 65 publications

(20 citation statements)

References 7 publications

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“…Whale shark distribution has been linked to nutrient-rich waters with elevated chlorophyll levels in other regions, including, but not limited to, Japan, Western Australia, India, and the Galapagos Islands (Iwasaki 1970, Compagno 1984, Arnbom & Papastavrou 1988, Taylor & Pearce 1999, Hsu et al 2007, Kumari & Raman 2010. Similarly, chlorophyll a concentrations have been used to forecast fisheries catches (Solanki 2003) and to delineate mi gratory corridors and foraging habitat used by highly migratory ma rine species, such as tunas and turtles (Polovina et al 2001). At the present time, residency and migratory patterns for whale sharks is poorly un der stood, but it is well documented that whale sharks are opportunistic filter-feeders that are found in highly productive areas.…”

Section: Discussionmentioning

confidence: 99%

Feeding habitat of the whale shark Rhincodon typus in the northern Gulf of Mexico determined using species distribution modelling

McKinney¹,

Hoffmayer²,

Wu³

et al. 2012

Mar. Ecol. Prog. Ser.

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Whale shark Rhincodon typus is a globally distributed species, but there is a lack of knowledge pertaining to their biology, seasonal occurrence, and distribution in the northern Gulf of Mexico (NGOM). Understanding critical habitat for whale sharks is essential on both a regional and global basis for proper management because of their large migratory range. The goal of the present study was to describe the regional distribution of whale shark feeding aggregations in the NGOM by exploiting a presence-only dataset collected as a part of a volunteer sighting survey. Whale shark aggregations have been documented in large numbers in the NGOM since 2003, and species distribution models provide a unique approach to analyzing these presence data. We used maximum entropy and ecological niche factor analysis, 2 algorithms designed for predicting species distribution based only on presence data, to analyze data for the summer period in 2008 and 2009. Cohen's kappa (kappa) and the 'area under the receiver operating characteristic curve' (AUC) were used to evaluate model performance with an external testing dataset. Kappa values ranged from 0.28 to 0.69, and AUC values ranged from 0.73 to 0.80, indicating that the predicted distribution had a fair to substantial agreement with the testing data. Distance to continental shelf edge, distance to adjacent petroleum platforms, and chlorophyll a were the variables most strongly related to whale shark sightings, likely due to an association of these variables with high food availability. Suitable habitat was predicted along the continental shelf edge, with the most suitable habitat predicted south of the Mississippi River Delta. The spatial distribution of suitable habitat is dynamic; therefore, a multi-year study is underway to better delineate temporal trends in regional whale shark distribution and to identify consistent areas of high suitability. Presenceonly habitat models are a powerful tool for delineating important regional habitat for a vulnerable, highly migratory species.

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Section: Discussionmentioning

confidence: 99%

Feeding habitat of the whale shark Rhincodon typus in the northern Gulf of Mexico determined using species distribution modelling

McKinney¹,

Hoffmayer²,

Wu³

et al. 2012

Mar. Ecol. Prog. Ser.

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show abstract

“…Satellite based ocean colour remote sensing provides quantitative information on the constituents of ocean water, such as the chlorophyll-a and total suspended sediment concentration and absorption due to yellow substance on global scale with different spatial and temporal resolutions for better understanding of the marine processes, ecology, and the coastal environmental changes and to study the bio-geo-chemical cycles of carbon, nitrogen and sulfur (Tang et al 2002;Chisholm 2000). Quantitative information of phytoplankton concentration in particular the chlorophyll-a concentration is useful to estimate the primary production estimation in open as well coastal ocean waters and the detection of phytoplankton fronts in the oceanic water helps in identifying the potential fishing zones (Marzeion et al 2005;Chauhan et al 2001;Solanki et al 2003;Nayak et al 2001). …”

Section: Introductionmentioning

confidence: 99%

Phytoplankton Variability in the Bay of Bengal During Winter Monsoon Using Oceansat-1 Ocean Colour Monitor Data

Nagamani

Shikhakolli

Chauhan

2011

J Indian Soc Remote Sens

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“…that are proven to be prospective sites of fish accumulation are identified from Sea Surface Temperature generated using NOAA-AVHRR Satellite data (Solanki et al 2003). Exploration of fishery resources through integration of ocean colour with sea surface temperature showed that these features are known to be sites of productive waters and hence conducive to fish aggregation (R.M.…”

Section: Introductionmentioning

confidence: 99%

Direct and Indirect Validation of Potential Fishing Zone Advisory off the Coast of Uttara Kannada, Karnataka

Deshpande

Radhakrishnan

Bhat

2011

J Indian Soc Remote Sens

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The technique of predicting Potential Fishing Zone using satellite derived sea surface temperature and chlorophyll is becoming an important aspect for the fishermen. In the present study an attempt has been made to compare fish density/catch per unit effort in the areas predicted by Satellite imagery and available to fishermen via electronic display boards at the fish landing centers of Uttara Kannada district, Karnataka with those of non predicted areas. Direct and Indirect validation was done. Direct method means comparing the catch using fishing vessels simultaneously in the notified region with that of catch from non notified region. And in indirect method by comparing catch data from landing centers on notified days with that of non notified days. Direct validation off Karwar showed that catch was significantly higher in notified (PFZ) area with high densities as compared to non notified (non PFZ) regions. When comparisons of landing center data of Karwar, Tadadi and Bhatkal are done it is evident that in all the centers during the period under study, higher catches were observed on notified days than non notified days except in Bhatkal centre in 2009-10.There by validating the accuracy of PFZ predictions and economic gains to fishermen.

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Fishery forecast using OCM chlorophyll concentration and AVHRR SST: validation results off Gujarat coast, India

Cited by 65 publications

References 7 publications

Feeding habitat of the whale shark Rhincodon typus in the northern Gulf of Mexico determined using species distribution modelling

Feeding habitat of the whale shark Rhincodon typus in the northern Gulf of Mexico determined using species distribution modelling

Phytoplankton Variability in the Bay of Bengal During Winter Monsoon Using Oceansat-1 Ocean Colour Monitor Data

Direct and Indirect Validation of Potential Fishing Zone Advisory off the Coast of Uttara Kannada, Karnataka

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