Nowadays it is extremely important to understand ecosystem function and its dynamics to predict future changes and consequently to perform appropriate measures. Hydromeliorations and subsequent decrease in groundwater table are thought to be a major reason for a decline in the vitality of black alder (Alnus glutinosa (L.) Gaertn.) wetland forests in North-eastern Slovenia. In this study radial increments of trees were used as indicators of black alder forest function and its disturbances. The aim of the study was to build a model of annual radial increments of black alder trees, to use this model to identify environmental attributes that most importantly affect ecosystem's function and to predict changes in the forest function under different scenarios of environmental conditions in the future. The model was induced with a machine learning algorithm CIPER and it was based on the data about site conditions and applied management measures in the past 35 years. Groundwater levels in combination with the duration of sun radiation were identified as the most important environmental attributes affecting annual radial increments. Radial increments were the lowest in very wet and cloudy years. On the other hand, radial increments were decreased under drought stress as well. Changes in groundwater level and in duration of sun radiation, as well as increased oscillations of groundwater level, all cause important increase in oscillations of modeled radial increments, indicating higher stress. Radial increments were further negatively affected by late white frosts in the spring.