Abstract
In order to identify the best tools for stock assessment studies using fish parasites as biological indicators, different host traits (size, mass and age and their interaction with sex) were evaluated as descriptors of cumulative patterns of both parasite abundance and infracommunity species richness. The effect of such variables was analysed for a sample of 265 specimens of Percophis brasiliensis caught in the Argentine Sea. The abundances and species richness were modelled using generalized linear mixed models ( GLMMs ) with negative binomial and Poisson distribution respectively. Due to collinearity, separate models were fitted for each of the three main explanatory variables (length, mass and age) to identify the optimal set of factors determining the parasite burdens. Optimal GLMMs were selected on the basis of the lowest Akaike information criteria, residual information and simulation studies based on 10 000 iterations. Results indicated that the covariates length and sex consistently appeared in the most parsimonious models suggesting that fish length seems to be a slightly better predictor than age or mass. The biological causes of these patterns are discussed. It is recommended to use fish length as a measure of growth and to restrict comparisons with fish of similar length or to incorporate length as covariate when comparing parasite burdens. Host sex should be also taken into account for those species sexually dimorphic in terms of morphology, behaviour or growth rates.