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Please use this identifier to cite or link to this item:
http://krishi.icar.gov.in/jspui/handle/123456789/72873
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Sreekanth GB, Chakraborty SK, Jaiswar AK, Das B, Chakurkar EB | en_US |
dc.date.accessioned | 2022-06-18T05:37:26Z | - |
dc.date.available | 2022-06-18T05:37:26Z | - |
dc.date.issued | 2019-01-01 | - |
dc.identifier.citation | Not Available | en_US |
dc.identifier.issn | Not Available | - |
dc.identifier.uri | http://krishi.icar.gov.in/jspui/handle/123456789/72873 | - |
dc.description | Not Available | en_US |
dc.description.abstract | In this paper, we compared the efficiency of advanced deterministic and stochastic geo-statistical techniques to predict spatial patterns of fish density in the tropical monsoonal estuary, Zuari, using the following environmental descriptors: temperature, salinity, dissolved oxygen, transparency and geographic coordinates. The methods applied in this study were multiple linear regression, Cubist, support vector regression, random forest regression, universal kriging and regression kriging. Fish abundance and environmental data were collected from September, 2013 to August, 2016 in 48 sampling stations distributed along the estuarine gradient. Ranking procedure of various regression methods showed that the Cubist model was the best performing model based on prediction accuracy in the development phase and prediction consistency in the validation phase. Latitude, temperature, salinity and dissolved oxygen had positive influence on fish abundance, while longitude and transparency showed negative impacts. This study offers scope for refining the employed currently models to predict spatial densities of fish populations using a wide range of available biotic and abiotic variables, which will enable to develop an efficient management framework for tropical monsoonal estuaries. | en_US |
dc.description.sponsorship | Not Available | en_US |
dc.language.iso | English | en_US |
dc.publisher | Not Available | en_US |
dc.relation.ispartofseries | Not Available; | - |
dc.subject | algorithms, dissolved oxygen, estuaries, fish, kriging, latitude, longitude, models, oxygen, prediction, regression analysis, salinity, temperature, | en_US |
dc.title | Application of deterministic and stochastic geo-statistical tools for analysing spatial patterns of fish density in a tropical monsoonal estuary. | en_US |
dc.title.alternative | Not Available | en_US |
dc.type | Research Paper | en_US |
dc.publication.projectcode | Not Available | en_US |
dc.publication.journalname | Aquatic Ecology | en_US |
dc.publication.volumeno | 53(1) | en_US |
dc.publication.pagenumber | 49-60 | en_US |
dc.publication.divisionUnit | Not Available | en_US |
dc.publication.sourceUrl | Not Available | en_US |
dc.publication.authorAffiliation | ICAR: Central Institute of Fisheries Education | en_US |
dc.ICARdataUseLicence | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf | en_US |
dc.publication.journaltype | International | en_US |
dc.publication.naasrating | 7.98 | en_US |
dc.publication.impactfactor | 1.641 | en_US |
Appears in Collections: | FS-CIFE-Publication |
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