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Parasites as fish population tags and pseudoreplication problems: the case of striped red mullet Mullus surmuletus in the Spanish Mediterranean
Authors:Ferrer-Castelló E  Raga J A  Aznar F J
Institution:Marine Zoology Unit, Cavanilles Institute of Biodiversity and Evolutionary Biology, University of Valencia, Valencia, Spain. eugenia.ferrer@uv.es
Abstract:Studies of parasites as fish population tags often apply a single round of sampling to identify potential stocks or predict harvest localities. However, the lack of replication generates pseudoreplication, implicitly assuming that infection levels are more similar between samples from the same locality than between samples from different localities. We evaluated this assumption in the case of the striped red mullet Mullus surmuletus in three localities of the Spanish Mediterranean separated by c. 300 km. Samples of 25 fish of similar size were collected in each locality in the summer and autumn of two consecutive years. Prevalence and abundance of three long-lived parasite taxa differed significantly among localities, indicating their potential as stock indicators. However, a cluster analysis (for prevalence) and a MANOVA (for abundance) indicated strong inter-sample variability, even within the same locality, with poor spatial segregation among samples. A linear discriminant analysis (LDA) based on the abundance of 17 parasite taxa correctly assigned over 80% of fish to their locality, and 95% bootstrap confidence intervals of percent classified fish per locality were narrow, indicating good and stable predictive power. However, when a LDA based on data from the first year was used to predict the locality of fish from the second year, predictive power dropped drastically (46% of correct allocation). Overall, we interpret that parasite communities of mullets change at a much lower spatial scale than that adopted in this study. This finding strongly suggests the need for proper replication to make reliable inferences about stock structure in fish populations based on parasitological data.
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