Establishing Functional Relationships between Abiotic Environment, Macrophyte Coverage, Resource Gradients and the Distribution of Mytilus trossulus in a Brackish Non-Tidal Environment.

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.

Grazing rate of zebra mussel in a shallow eutrophicated bay of the Baltic Sea.

Benthic suspension feeding is an important process in coastal ecosystems. Among all the World's oceans, coastal ecosystems are the most modified by human impact and changing at accelerating pace. It is complicated to understand, how various environmental factors affect feeding rates of suspension feeders in their natural habitats. Thus, shapes of such relationships are poorly described for several intersections of environmental gradients. In this study, relationships between grazing rates of an invasive bivalve Dreissena polymorpha and ambient environmental factors were investigated in a turbid eutrophic bay of the central Baltic Sea using a novel modelling method of Boosted Regression Trees (BRT), a statistical tool able to handle non-normal distributions, complex relationships, and interactive effects. Feeding rates of mussels were derived from field populations by measuring the content of algal pigments in specimens collected from their natural habitat. The content of pigments was converted to feeding rate separately each time using field experiments measuring simultaneously the content of pigments and biodeposition of mussels. The results suggest that feeding rates of D. polymorpha are related to several environmental factors which gradients outreach the optimal range for the local mussel population. All the observed effects were non-linear with complex shapes. Variability along the resource gradient was the most important predictor of mussel feeding, followed by salinity and disturbance caused by wind. The most important interaction occurred between disturbance and resource gradient, while feeding function showed more plasticity along the latter. Mapping of environmental tipping points with the aid of machine learning methods may enable to concentrate the most relevant information about ecological functions worldwide.