Day and night trophic variations of dominant fish species in a lagoon influenced by freshwater seeps.

Saved in:
Bibliographic Details
Title: Day and night trophic variations of dominant fish species in a lagoon influenced by freshwater seeps.
Authors: Arceo‐Carranza, D.1, Vega‐Cendejas, M. E.2, Hernández de Santillana, M.2
Source: Journal of Fish Biology. Jan2013, Vol. 82 Issue 1, p54-68. 15p.
Subjects: Freshwater fishes, Biological variation, Lagoons, Biosphere reserves, Correspondence analysis (Communications), Amphipoda
Abstract: The aim of this study was to determine the trophic structure and nycthemeral variations in the diet of dominant fish species ( Ariopsis felis, Bairdiella chrysoura, Micropogonias undulatus, Eucinostomus gula, Eucinostomus argenteus, Lagodon rhomboides and Sphoeroides testudineus) in Celestun Lagoon, a biosphere reserve located in the southern Gulf of Mexico, and influenced by freshwater seeps. A total of 1473 stomachs were analysed and nine trophic groups were recorded. Bray-Curtis analyses with analyses of similarity (ANOSIM) statistical tests were used to determine two groups of feeding guilds: zoobenthivores and omnivores, with significant differences between time and habitat. The relationships between fish feeding habits, size class and environmental variables were investigated using canonical correspondence analysis (CCA). Most of the species showed a low niche breadth with high specialization towards amphipod consumption, with the exception of L. rhomboides (0·60), which indicated generalist feeding. This study in a protected area is an important source of information for drawing up conservation policies in relation to the management of aquatic resources, and will aid in the establishment of priority areas for conservation. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Fish Biology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
Be the first to leave a comment!
You must be logged in first