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.