Description: Summary: The relationship between community structure and the functioning of ecosystems is the subject of ongoing debate. Biological or functional trait-based approaches that capture life strategy, morphology and behavioural characteristics have received far less attention than taxonomic diversity in this context, despite their more intuitive link to ecosystem functioning. Macrophyte primary production underpins aquatic food webs, regulates benthic and pelagic ecosystems and is a key aspect of the global carbon cycle. This study spans a range of aquatic biomes across Europe and aims to examine potential for predicting primary production of macrophyte communities based on the functional traits of species and identify the traits that are the most informative indicators of macrophyte production. Macrophyte primary production was assessed based on the oxygen production of the whole community, linked to biomasses of selected biological traits derived of its component species and analysed using the novel boosted regression trees modelling technique. Results showed that functional traits derived from macrophyte community data explained most of the variation in primary production of macrophyte communities without the need to incorporate environmental data on the habitats. Macrophyte primary production was influenced by a combination of tolerance, morphology and life habit traits; however tolerance traits contributed most of variability in macrophyte primary production when all traits were analysed jointly. This study also showed the existence of trait clustering as the studied trait categories were not fully independent; strong interlinkages between and within trait categories emerged. Our study suggests that functional trait analysis captures different aspects of ecosystem functioning and thereby enables assessing primary production of macrophyte communities over geographically distinct areas without extensive taxonomic and environmental data. This could result in a novel framework through which a simplification of the general procedure of production estimations and comparisons across environmental gradients can be achieved.

Description: Knowledge and understanding of geographic distributions of species is crucial for many aspects in ecology, conservation, policy making and management. In order to reach such an understanding, it is important to know abiotic variables that impact and drive distributions of native and non-native species. We used an existing long-term macrobenthos database for species presence-absence information and biomass estimates at different environmental gradients in the northern Baltic Sea. Region specific abiotic variables (e.g. salinity, depth) were derived from previously constructed bathymetric and hydrodynamic models. Multidimensional ordination techniques were then applied to investigate potential niche space separation between all native and non-native invertebrates in the northern Baltic Sea. Such an approach allowed to obtain data rich and robust estimates of the current native and non-native species distributions and outline important abiotic parameters influencing the observed pattern. The results showed clear niche space separation between native and non-native species. Non-native species were situated in an environmental space characterized by reduced salinity, high temperatures, high proportion of soft seabed and decreased depth and wave exposure whereas native species displayed an opposite pattern. Different placement of native and non-native species along the studied environmental niche space is likely to be explained by the differences in their evolutionary history, human mediated activities and geological youth of the Baltic Sea. The results of this study can provide early warnings and effectively outline coastal areas in the northern Baltic Sea that are prone to further range expansion of non-native species as climate change is expected to significantly reduce salinity and increase temperature in wide coastal areas, both supporting the disappearance of native and appearance of non-native species.

Description: Aquatic invertebrate communities are influenced by interactions between the abiotic and biotic environment at multiple spatial and temporal scales. Studies of mesozooplankton community patterns in relation to spatial and temporal scales are rare. In this study, we examined scale-specific variability of mesozooplankton in the shallow coastal Baltic Sea and related this variability to key environmental proxies. Seasonality defined the majority of variability in taxonomic composition and abundance patterns, as well as in aggregated parameters of zooplankton. However, these properties also varied spatially at a large, 100-km scale. The variability in all properties except taxonomic composition was negligible at the smaller spatial scale. Taxonomic richness increased until moderate levels of total abundance, whereas peak blooms were always characterized by higher dark diversity. Shannon diversity was unrelated to total abundance. Observed spatio-temporal patterns were strongly related to abiotic forcing and uncoupled from phytoplankton standing stock and primary production. Results show the importance of seasonality over spatial variability and abiotic factors over phytoplankton variability for sub-boreal brackish coastal mesozooplankton at the spatial scales studied. Information loss from spatial generalization can be larger for taxonomic occurrences and rare species than for species abundances and aggregated community parameters such as total abundance or taxonomic richness.

Description: The Baltic Sea is a dynamic environment responding to various drivers operating at different temporal and spatial scales. In response to climate change, the Baltic Sea is warming and the frequency of extreme climatic events is increasing (Lima & Wethey 2012, BACC 2008, Poloczanska et al. 2007). Coastal development, human population growth and globalization intensify stressors associated with human activities, such as nutrient loading, fisheries and proliferation of invasive and bloom-forming species. Such abrupt changes have unforeseen consequences for the biodiversity and the function of food webs and may result in loss of ecological key species, alteration and fragmentation of habitats. To mitigate undesired effects on the Baltic ecosystem, an efficient marine management will depend on the understanding of historical and current drivers, i.e. physical and chemical environmental conditions and human activities that precipitate pressures on the natural environment. This task examined a set of key interactions of selected natural and anthropogenic drivers in space and time, identified in Task 3.1 as well as WP1 and WP2 (e.g. physico-chemical features vs climate forcing; eutrophication vs oxygen deficiency vs bio-invasions; fisheries vs climate change impacts) by using overlay-mapping and sensitivity analyses. The benthic ecosystem models developed under Task 2.1 were used to investigate interactions between sea temperature and eutrophication for various depth strata in coastal (P9) and offshore areas (P1) of the Baltic Sea. This also included investigation on how the frequency and magnitude of deep-water inflow events determines volume and variance of salinity and temperature under the halocline, deep-water oxygen levels and sediment fluxes of nutrients, using observations and model results from 1850 to present (P1, P2, P6, P9, P12). The resulting synthesis on the nature and magnitude of different driver interactions will feed into all other tasks of this WP3 and WP2/WP4. Moreover, the results presented in this report improve the process-based and mechanistic understanding of environmental change in the Baltic Sea ecosystem, thereby fostering the implementation of the Marine Strategy Framework Directive.

Description: Predictive species distribution models are mostly based on statistical dependence between environmental and distributional data and therefore may fail to account for physiological limits and biological interactions that are fundamental when modelling species distributions under future climate conditions. Here, we developed a state-of-the-art method integrating biological theory with survey and experimental data in a way that allows us to explicitly model both physical tolerance limits of species and inherent natural variability in regional conditions and thereby improve the reliability of species distribution predictions under future climate conditions. By using a macroalga-herbivore association (Fucus vesiculosus - Idotea balthica) as a case study, we illustrated how salinity reduction and temperature increase under future climate conditions may significantly reduce the occurrence and biomass of these important coastal species. Moreover, we showed that the reduction of herbivore occurrence is linked to reduction of their host macroalgae. Spatial predictive modelling and experimental biology have been traditionally seen as separate fields but stronger interlinkages between these disciplines can improve species distribution projections under climate change. Experiments enable qualitative prior knowledge to be defined and identify cause-effect relationships, and thereby better foresee alterations in ecosystem structure and functioning under future climate conditions that are not necessarily seen in projections based on non-causal statistical relationships alone.

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.

Description: Highlights: • Effects of microplastic on marine biota reflect the quality of experimental research. • The quality of published experiments can be quantified from an “ideal” experiment. • Previously published experiments have significantly deviated from “ideal”. • Implementation of proposed criteria can improve future microplastic experiments. Abstract: This article presents a novel conceptual blueprint for an ‘ideal’, i.e., ecologically relevant, microplastic effect study. The blueprint considers how microplastics should be characterized and applied in laboratory experiments, and how biological responses should be measured to assure unbiased data that reliably reflect the effects of microplastics on aquatic biota. This ‘ideal’ experiment, although practically unachievable, serves as a backdrop to improve specific aspects of experimental research on microplastic effects. In addition, a systematic and quantitative literature review identified and quantified departures of published experiments from the proposed ‘ideal’ design. These departures are related mainly to the experimental design of microplastic effect studies failing to mimic natural environments, and experiments with limited potential to be scaled-up to ecosystem level. To produce a valid and generalizable assessment of the effect of microplastics on biota, a quantitative meta-analysis was performed that incorporated the departure of studies from the ‘ideal’ experiment (a measure of experimental quality) and inverse variance (a measure of the study precision) as weighting coefficients. Greater weights were assigned to experiments with higher quality and/or with lower variance in the response variables. This double-weighting captures jointly the technical quality, ecological relevance and precision of estimates provided in each study. The blueprint and associated meta-analysis provide an improved baseline for the design of ecologically relevant and technically sound experiments to understand the effects of microplastics on single species, populations and, ultimately, entire ecosystems.