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  4. Modelling Seasonal Patterns Of Larval Fish Parasitism In Two Northern Nearshore Areas In The Humboldt Current System
 
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Modelling Seasonal Patterns Of Larval Fish Parasitism In Two Northern Nearshore Areas In The Humboldt Current System

Journal
Scientific Reports
Date Issued
2021-01-12
Author(s)
Lissette D. Paredes
Landaeta, Mauricio  
Facultad de Ciencias  
Carlos Molinet
M. Teresa González
DOI
10.1038/s41598-020-79847-1
WoS ID
WOS:000621919500042
Abstract
Macro- and micro-environmental factors modulate parasite loads in fish, determining parasitic abundances, diversity, and interaction dynamics. In this study, seasonal variations in larval ectoparasites on fish larvae in the northern Humboldt Current System (HCS) were evaluated using a delta-gamma generalized linear model to predict their occurrence frequencies. Fish larvae were collected from two nearshore areas during austral spring–summer and autumn–winter. Only five (of 38) larval fish species were parasitized by copepods: Gobiesox marmoratus, Ophiogobius jenynsi, Helcogrammoides cunninghami, Myxodes sp., and Auchenionchus crinitus. A binomial model showed that the presence/absence of parasitized fish larvae varied among the fish species and their larval abundances, while a positive delta-gamma model showed that ectoparasite frequency varied among the seasons and fish species. Seasonal variations in parasitized fish larvae frequency could be associated with host and parasite reproductive processes, which are related to oceanographic features responsible for larval retention and subsequent higher infestation probabilities. Host length was positively correlated with ectoparasite length, suggesting early infection and combined growth until the detachment of the ectoparasite. Our results suggest that infestation patterns in larval fish species can be identified using delta-gamma models and that they respond to local (retention) and high-scale (HCS) processes.
Subjects

Multidisciplinary Sci...

Multidisciplinary

OCDE Subjects

Multidisciplinary

Quartile (Date Issued)
Q1
License
acceso abierto
Open Science Path
https://creativecommons.org/licenses/by/4.0/

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