National Centre for Biosystematics, Natural History Museum, University of Oslo, Oslo, Norway.
Int J Parasitol. 2012 Aug;42(9):809-17. doi: 10.1016/j.ijpara.2012.05.012. Epub 2012 Jul 4.
Comparative studies of gyrodactylid monogeneans on different host species or strains rely upon the observation of growth on individual fish maintained within a common environment, summarised using maximum likelihood statistical approaches. Here we describe an agent-based model of gyrodactylid population growth, which we use to evaluate errors due to stochastic reproductive variation in such experimental studies. Parameters for the model use available fecundity and mortality data derived from previously published life tables of Gyrodactylus salaris, and use a new data set of fecundity and mortality statistics for this species on the Neva stock of Atlantic salmon, Salmo salar. Mortality data were analysed using a mark-recapture analysis software package, allowing maximum-likelihood estimation of daily survivorship and mortality. We consistently found that a constant age-specific mortality schedule was most appropriate for G. salaris in experimental datasets, with a daily survivorship of 0.84 at 13°C. This, however, gave unrealistically low population growth rates when used as parameters in the model, and a schedule of constantly increasing mortality was chosen as the best compromise for the model. The model also predicted a realistic age structure for the simulated populations, with 0.32 of the population not yet having given birth for the first time (pre-first birth). The model demonstrated that the population growth rate can be a useful parameter for comparing gyrodactylid populations when these are larger than 20-30 individuals, but that stochastic error rendered the parameter unusable in smaller populations. It also showed that the declining parasite population growth rate typically observed during the course of G. salaris infections cannot be explained through stochastic error and must therefore have a biological basis. Finally, the study showed that most gyrodactylid-host studies of this type are too small to detect subtle differences in local adaptation of gyrodactylid monogeneans between fish stocks.
比较不同宿主物种或株系的旋盘虫单殖吸虫的研究依赖于在共同环境中维持的单个鱼类个体的生长观察,使用最大似然统计方法进行总结。在这里,我们描述了一种旋盘虫种群增长的基于代理的模型,我们使用该模型来评估此类实验研究中由于随机生殖变异引起的误差。模型的参数使用了先前发表的大西洋鲑Gyrodactylus salaris 生命表中得出的可育性和死亡率数据,以及该物种在涅瓦河大西洋鲑种群中的新的可育性和死亡率统计数据集。死亡率数据使用标记重捕分析软件包进行分析,允许对每日存活率和死亡率进行最大似然估计。我们一致发现,在实验数据集上,年龄特异性死亡率时间表最适合 G. salaris,在 13°C 时每日存活率为 0.84。但是,当将其用作模型中的参数时,这会导致种群增长率低得不切实际,因此选择不断增加的死亡率时间表作为模型的最佳折衷方案。该模型还预测了模拟种群的现实年龄结构,其中 0.32 的种群尚未首次分娩(首次分娩前)。该模型表明,当旋盘虫种群大于 20-30 个个体时,种群增长率可以作为比较旋盘虫种群的有用参数,但随机误差使该参数在较小的种群中无法使用。它还表明,在 G. salaris 感染过程中通常观察到的寄生虫种群增长率下降不能通过随机误差来解释,因此必须具有生物学基础。最后,该研究表明,大多数此类旋盘虫-宿主研究规模太小,无法检测到鱼类种群之间旋盘虫单殖吸虫局部适应的细微差异。