Description: Biodiversity is critical for maintaining and stabilizing ecosystem processes. There is a need for high-resolution biodiversity maps that cover large sea areas in order to address ecological questions related to biodiversity-ecosystem functioning relationships and to provide data for marine environmental protection and management decisions. However, traditional sampling-point-wise field work is not suitable for covering extensive areas in high detail. Spatial predictive modeling using biodiversity data from sampling points and georeferenced environmental data layers covering the whole study area is a potential way to create biodiversity maps for large spatial extents. Random forest (RF), generalized additive models (GAM), and boosted regression trees (BRT) were used in this study to produce benthic (macroinvertebrates, macrophytes) biodiversity maps in the northern Baltic Sea. Environmental raster layers (wave exposure, salinity, temperature, etc.) were used as independent variables in the models to predict the spatial distribution of species richness. A validation dataset containing data that was not included in model calibration was used to compare the prediction accuracy of the models. Each model was also evaluated visually to check for possible modeling artifacts that are not revealed by mathematical validation. All three models proved to have high predictive ability. RF and BRT predictions had higher correlations with validation data and lower mean absolute error than those of GAM. Both mathematically and visually, the predictions by RF and BRT were very similar. Depth and seabed sediments were the most influential abiotic variables in predicting the spatial patterns of biodiversity.

Description: Highlights: • We summarized 20 ecosystem services provided by coastal Baltic ecosystems. • Information on how services translate into socio-economic benefits is lacking. • The deep knowledge gap impairs the sustainable management of the benefits. • We propose a framework with four key measures to close this knowledge gap. • Toxins and Nutrients are the most well-document pressures to these services. Abstract: Seagrass meadows, algal forests and mussel beds are widely regarded as foundation species that support communities providing valuable ecosystem services in many coastal regions; however, quantitative evidence of the relationship is scarce. Using the Baltic Sea as a case study, a region of significant socio-economic importance in the northern hemisphere, we systematically synthesized the primary literature and summarized the current knowledge on ecosystem services derived from seagrass, macroalgae, and mussels (see animated video summary of the manuscript: Video abstract). We found 1740 individual ecosystem service records (ESR), 61% of which were related to macroalgae, 26% to mussel beds and 13% to seagrass meadows. The most frequently reported ecosystem services were raw material (533 ESR), habitat provision (262 ESR) and regulation of pollutants (215 ESR). Toxins (356 ESR) and nutrients (302 ESR) were the most well-documented pressures to services provided by coastal ecosystems. Next, we assessed the current state of knowledge as well as knowledge transfer of ecosystem services to policies through natural, social, human and economic dimensions, using a systematic scoring tool, the Eco-GAME matrix. We found good quantitative information about how ecosystems generated the service but almost no knowledge of how they translate into socio-economic benefits (8 out of 657 papers, 1.2%). While we are aware that research on Baltic Sea socio-economic benefits does exist, the link with ecosystems providing the service is mostly missing. To close this knowledge gap, we need a better analytical framework that is capable of directly linking existing quantitative information about ecosystem service generation with human benefit.