Empirical Models of Fish Response to Lake Acidification

Abstract

A large historical data set from the Adirondack region of New York was compiled to study the relationship between water chemistry variables associated with acid precipitation and the presence/absence of selected fish species. The data set was used to examine simple statistical models for fish presence/absence, as a function of the water chemistry variables, for brook trout (Salvelinus fontinalis), lake trout (Salvelinus namaycush), white sucker (Catostomus commersoni), and yellow perch (Perca flavescens). Of these models, only those for brook trout and lake trout were found to be acceptable based on statistical goodness-of-fit criteria; thus, parameters for models of these two species alone were estimated using maximum likelihood logistic regression. Candidate models for brook trout and lake trout were then examined, with particular consideration for the problems associated with model misspecification, errors-in-variables, and multicollinearity. For each of the two species, a model was recommended that may be used to predict the effect of changes in lake acidification on species presence/absence in lakes in the Adirondack region.