Prediction of macrofungal occurrence in Swedish beech forests from soil and litter variable models

The spatial distribution of 49 macrofungal species in Swedish beech forests was related to the statistical variation in 31 edaphic variables. In order to reduce the multicollinearity problem, the variables were transformed into eight principal components, PCs, which are used in two-group discriminant analysis (on absence/presence patterns) and multiple regression analysis (on number of fruit-bodies). The results suggested that base saturation and organic matter content are of outstanding importance. However, significant relationships were also found with other variables, i.e. Cd or Zn in soil and litter, soil nitrogen mineralization rate, and Na or S in litter. One interesting interpretation of the results is that fungi do not only respond to the main variables of a gradient (soil pH, organic mater, base saturation) but also to other variables. Attempts were made to interpret the PCs to characterize fungal occurrence from the models they formed.