No abstract

Benthic suspension feeding mussels are an important functional guild in coastal and estuarine ecosystems. To date we lack information on how various environmental gradients and biotic interactions separately and interactively shape the distribution patterns of mussels in non-tidal environments. Opposing to tidal environments, mussels inhabit solely subtidal zone in non-tidal waterbodies and, thereby, driving factors for mussel populations are expected to differ from the tidal areas. In the present study, we used the boosted regression tree modelling (BRT), an ensemble method for statistical techniques and machine learning, in order to explain the distribution and biomass of the suspension feeding mussel Mytilus trossulus in the non-tidal Baltic Sea. BRT models suggested that (1) distribution patterns of M. trossulus are largely driven by separate effects of direct environmental gradients and partly by interactive effects of resource gradients with direct environmental gradients. (2) Within its suitable habitat range, however, resource gradients had an important role in shaping the biomass distribution of M. trossulus. (3) Contrary to tidal areas, mussels were not competitively superior over macrophytes with patterns indicating either facilitative interactions between mussels and macrophytes or co-variance due to common stressor. To conclude, direct environmental gradients seem to define the distribution pattern of M. trossulus, and within the favourable distribution range, resource gradients in interaction with direct environmental gradients are expected to set the biomass level of mussels.