A multivariate model to relate hydrological, chemical and biological parameters to salmonid biomass in Italian Alpine rivers

Abstract

A multivariate statistical analysis was performed to assess the relationships between a series of river habitat parameters and the variation in salmonid biomass in 13 stations in Italian Alpine salmonid rivers. Various river data were collected and principal component analysis was used to identify the relevant parameters. The best regression model was calculated using two statistics: Mallows’Cp and R2 adjusted for degrees of freedom. The best model only uses six parameters and explained 89% of variation in fish biomass. Various statistical indices were calculated to evaluate model quality and robustness. A sensitivity analysis was carried out to determine how the model slope would change due to independent measurement errors in the parameters. These effects were mostly negligible. This demonstrated that it is possible to simplify habitat quality evaluation using a subset of environmental parameters which should be useful for river management.