LOGISTIC-REGRESSION AS A TOOL FOR DEFINING HABITAT REQUIREMENTS OF 2 COMMON GAMMARIDS

I. Logistic regression predicts the probability of occurrence of a spe cies as a function of environmental variables. This technique was appl ied to a large data set describing the distribution of two common gamm arid species, Gammarus fossarum and G. pulex, in streams in the Nether lands, to evaluate its usefulness in defining habitat requirements. 2. A method is presented that derives optimum habitat ranges for environ mental variables from logistic regression equations. The calculated op timum habitat ranges, which are related to the maximum likelihood of p resence in the field, agreed with habitat requirements and ecological tolerances in the literature. 3. Single logistic regressions provide g ood descriptions of the optimum habitat requirements and multiple logi stic regressions give insight into the relative importance of each env ironmental variable. It is the combination that makes logistic regress ion a valuable tool for constructing habitat suitability indices. 4. C urrent velocity, pH, Kjeldahl nitrogen, total phosphorus, ammonium nit rogen, conductivity, width and depth are, in this sequence, the most i mportant environmental variables in predicting the probability of occu rrence of G. fossarum, whereas current velocity, Kjeldahl nitrogen, pH and depth are the most important variables for the prediction of the probability of occurrence of G. pulex.