A combination of functionally different plant traits provides a means to quantitatively predict a broad range of species assemblages in NW Europe

Assembly theory predicts that filtering processes will select species by their attributes to build a community. Some filters increase functional similarity among species, while others lead to dissimilarity. Assuming converging processes to be dominant within habitats, we tested in this study whether species assemblages across a wide range of habitats can be distinguished quantitatively by their mean trait compositions. In addition, we investigated how many and which traits are needed to describe the differences between species assemblages best. The approach has been applied on a dataset that included 12 plant traits and 7644 vegetation releves covering a wide range of habitats in the Netherlands. We demonstrate that due to the dominant role of converging processes 1) the functional composition can explain up to 80% of the floristic differences between species assemblages using seven plant traits, showing that plant trait combinations provide a powerful tool for predicting the occurrence of species assemblages across different habitats; 2) to achieve a high performance, traits should be taken from different strategy components, i.e. traits that are functionally orthogonal, which does not necessarily coincide with low trait-trait correlations; 3) the different strategy components identified in this study correspond to the strategy components of some conventional plant ecological strategy schemes (PESS) schemes to describe the variation between individual species. However, some PESS merge traits into one strategy component that are shown to be functionally different when predicting species assemblages. If such PESS is used to predict assemblages, this leads to a loss in predictive capacity. Potentially, our new approach is globally applicable to quantify community assembly patterns. However this needs to be tested.