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Multivariate analyses of morphometrical features from Gyrodactylus spp. (Monogenea) parasitising British salmonids: Light microscope based studies
Authors:Andrew P Shinn  Sophie des Clers  David I Gibson  Christina Sommerville
Institution:(1) Institute of Aquaculture, University of Stirling, FK9 4LA Stirling, UK;(2) Department of Zoology, The Natural History Museum, Cromwell Road, SW7 5BD London, UK;(3) Renewable Resources Assessment Group, Imperial College, SW7 1NA London, UK
Abstract:Species determination within the genus Gyrodactylus Nordmann, 1832 is based upon subtle differences in marginal hook morphology and has long posed taxonomic problems. This study uses univariate and multivariate analyses in an attempt to elucidate the Gyrodactylus species parasitising British salmonids. A total of 389 parasites were collected at 69 of 227 localities sampled throughout the British Isles from four salmonid host species, Salmo salar, Salmo trutta, Oncorhynchus mykiss and a limited number of Salvelinus alpinus. A small number of known species of Gyrodactylus from outside the UK were also added to the data set. Morphometric data on the sclerites were collected from slide preparations of Gyrodactylus using light microscopy. Univariate statistics were used to select 11 of the 18 useful morphometric features defined by Malmberg (1970) on the basis of those with the smallest natural variability and/or measurement error. The data, relating to the 11 variables chosen, were then analysed using principal components analysis (PCA) to describe the forms present. Initial outliers included foreign species of Gyrodactylus and an accidental infection by a gasterosteid form. Two major groups were resolved: one on S. salar and O. mykiss, the specimens from which resembled G. derjavini Mikailov, 1975 and G. caledoniensis Shinn et al. in press; and one on S. trutta, which was identified as G. truttae Gläser, 1974. The analysis, in addition to showing which were useful morphometric features, also demonstrated the limitations of data obtained from the smallest features when using the light microscope.
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