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Parasite abundance distribution as a model of host-parasite relationships between monogeneans Gyrodactylus spp. and cage-reared rainbow trout Oncorhynchus mykiss
Parasite abundance distribution as a model of host-parasite relationships between monogeneans Gyrodactylus spp. and cage-reared rainbow trout Oncorhynchus mykiss
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Parasite abundance distribution as a model of host-parasite relationships between monogeneans Gyrodactylus spp. and cage-reared rainbow trout Oncorhynchus mykiss
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Parasite abundance distribution as a model of host-parasite relationships between monogeneans Gyrodactylus spp. and cage-reared rainbow trout Oncorhynchus mykiss
Parasite abundance distribution as a model of host-parasite relationships between monogeneans Gyrodactylus spp. and cage-reared rainbow trout Oncorhynchus mykiss

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Parasite abundance distribution as a model of host-parasite relationships between monogeneans Gyrodactylus spp. and cage-reared rainbow trout Oncorhynchus mykiss
Parasite abundance distribution as a model of host-parasite relationships between monogeneans Gyrodactylus spp. and cage-reared rainbow trout Oncorhynchus mykiss
Journal Article

Parasite abundance distribution as a model of host-parasite relationships between monogeneans Gyrodactylus spp. and cage-reared rainbow trout Oncorhynchus mykiss

2024
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Overview
Aggregation is a fundamental feature of parasite distribution in the host population, but the biological implications of the aggregation indices used to describe the relationships between the populations of parasites and hosts are not evident. It is speculated that the form of distribution in each case is predicated on the host’s varying resistance to the infection, which is hard to control, making it difficult to adequately interpret the index values. This paper examines several cases from trout farms in Russian Karelia to explore the monogenean Gyrodactylus spp. infection in rainbow trout of varying ages. The genetic homogeneity of cage-reared fish and the direct life cycle of the helminths make the relationship between the species more lucid than in natural host-parasite systems. The results give no ground to speak of any specific patterns: as well as in the natural systems, the infection rates in trout vary widely, i.e., the helminth distribution has not become more uniform; the observed distributions in all cases are adequately approximated by the negative binomial model; the positive abundance-occupancy relationships (AORs) and abundance-variance relationships (AVRs) common for parasitic systems apply to the basic infection parameters. The form of the negative binomial distribution is shaped by two parameters— k and θ , the former being a metric of the infection variability, which depends on the host’s individual resistance, and the latter representing the parasites’ reproduction and establishment success rates. A rise in the parameter k indicates increased aggregation and a higher parameter θ points to a more uniform frequency distribution. These parameters can be used as a representative tool for monitoring the parasite communities in salmonid fishes, including in aquaculture.