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Title: | Assessment of fish species assemblage on mesohabitat scale: A case of middle stretch of Narmada River, India. |
Other Titles: | Not Available |
Authors: | Malay Naskar S. K. Sahu A.P. Sharma |
ICAR Data Use Licennce: | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf |
Author's Affiliated institute: | ICAR::Central Inland Fisheries Research Institute |
Published/ Complete Date: | 2015-04-23 |
Project Code: | Not Available |
Keywords: | pool-run run-riffle cluster analysis nonmetric multidimensional scaling analysis of similarity logistic regression |
Publisher: | Taylor and Francis |
Citation: | Naskar, Malay, Sahu , S. K. and Sharma A. P.(2015) Assessment of fish species assemblage on mesohabitat scale: A case of middle stretch of Narmada River, India. AEHMS. 18(2):232-239 |
Series/Report no.: | Not Available; |
Abstract/Description: | In river ecosystems, mesohabitat characteristics (i.e. pool, run, riffle, rapids, etc.) act as proximate variables to fish species occurrence. Fish occurrence and mesohabitat data are very often collected independently for different purposes, which invites challenges to characterize the fish species distribution pattern on mesohabitat scale. The present article delineates quantitative assessment of fish occurrence in relation to mesohabitat using secondary data. Middle stretch of the Narmada River of India has been selected for the study. Geographic information system tools have been used for integration of species and mesohabitat data. Nonmetric Multidimensional Scaling, cluster analysis and Analysis of Similarity techniques have been used for similarity analysis. Logistic regression model has been applied for model-based inferences on family-mesohabitat relationship. Two separate mesohabitat types, viz., Pool-Run and Run-Riffle, have been characterized by the fish species occurrence pattern. Dissimilarity of fish species composition between Pool-Run and Run-Riffle was statistically significant (p-value < 0.05). The family-mesohabiat model predicted that the occurrence probability of a fish species was 14.49 times more in the Pool-Run than that in the Run-Riffle. The predictive accuracy of the model was 69.8%. |
Description: | Not Available |
ISSN: | Not Available |
Type(s) of content: | Research Paper |
Sponsors: | Not Available |
Language: | English |
Name of Journal: | Aquatic Ecosystem Health and Management |
NAAS Rating: | 6.76 |
Volume No.: | 18(2) |
Page Number: | 232-239 |
Name of the Division/Regional Station: | Not Available |
Source, DOI or any other URL: | DOI: 10.1080/ 14634988.2015.1040708 |
URI: | http://krishi.icar.gov.in/jspui/handle/123456789/7679 |
Appears in Collections: | FS-CIFRI-Publication |
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