title: An agent-based modelling approach to estimate error in gyrodactylid population growth.
abstract: 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.
authors: National Centre for Biosystematics, Natural History Museum, University of Oslo, Oslo, Norway. raul.ramirez@nhm.uio.no
authors: Raúl
authors: R
authors: Ramírez
authors: Philip D
authors: PD
authors: Harris
authors: Tor A
authors: TA
authors: Bakke
mesh_terms: D000818:Animals; D003198:Computer Simulation; D005393:Fish Diseases / Q000469:parasitology*; D006790:Host-Parasite Interactions; D008954:Models, Biological; D011158:Population Growth; D020317:Salmo salar; D012984:Software; D014200:Trematoda / Q000502:physiology*; D014201:Trematode Infections / Q000469:parasitology / Q000662:veterinary*