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首页> 外文期刊>Journal of Fish Biology >Assessing the role of host traits as drivers of the abundance of long-lived parasites in fish-stock assessment studies
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Assessing the role of host traits as drivers of the abundance of long-lived parasites in fish-stock assessment studies

机译:在鱼类种群评估研究中评估寄主性状作为长寿命寄生虫丰富性的驱动因素

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摘要

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.
机译:为了确定使用鱼类寄生虫作为生物指标进行种群评估研究的最佳工具,对不同寄主特征(大小,质量和年龄及其与性别的相互作用)进行了评估,以作为寄生虫丰度和群落下物种丰富度的累积模式的描述。分析了在阿根廷海中捕获的265个巴西天牛的标本样本的这些变量的影响。使用分别具有负二项式和泊松分布的广义线性混合模型(GLMM)对丰度和物种丰富度进行建模。由于共线性,为三个主要的解释变量(长度,质量和年龄)中的每一个拟合了单独的模型,以确定确定寄生虫负担的最佳因素集。基于最低的Akaike信息标准,残差信息和基于10000次迭代的仿真研究,选择了最佳GLMM。结果表明,协变量的长度和性别始终出现在最简约的模型中,这表明鱼的长度似乎比年龄或质量更好。讨论了这些模式的生物学原因。建议在比较寄生虫负担时,以鱼的长度作为生长的量度,并限制与类似长度的鱼的比较,或将长度作为协变量。对于那些在形态,行为或生长率方面具有两性性的物种,也应考虑寄主性。

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