While progress has been made in reducing external nutrient inputs to the Baltic Sea, further actions are needed to meet the goals of the Baltic Sea Action Plan (BSAP), especially for the Baltic Proper, Gulf of Finland, and Gulf of Riga sub-basins. We used the net anthropogenic nitrogen and phosphorus inputs (NANI and NAPI, respectively) nutrient accounting approach to construct three scenarios of reduced NANI-NAPI. Reductions assumed that manure nutrients were redistributed from areas with intense animal production to areas that focus on crop production and would otherwise import synthetic and mineral fertilizers. We also used the Simple as Necessary Baltic Long Term Large Scale (SANBALTS) model to compare eutrophication conditions for the scenarios to current and BSAP-target conditions. The scenarios suggest that reducing NANI-NAPI by redistributing manure nutrients, together with improving agronomic practices, could meet 54–82% of the N reductions targets (28–43 kt N reduction) and 38–64% P reduction targets (4–6.6 kt P reduction), depending on scenario. SANBALTS output showed that even partial fulfillment of nutrient reduction targets could have ameliorating effects on eutrophication conditions. Meeting BSAP targets will require addressing additional sources, such as sewage. A common approach to apportioning sources to external nutrients loads could enable further assessment of the feasibility of eutrophication management targets.
Observed effects of metal mixtures on animals and plants often differ from the estimates, which are commonly calculated by adding up the biological responses of individual metals. This difference from additivity is commonly referred to as being a consequence of specific interactions between metals. The science of how to quantify metal interactions and whether to include them in risk assessment models is in its infancy. This review summarizes the existing predictive tools for evaluating the combined toxicity of metals present in mixtures and indicates the advantages and disadvantages of each method. We intend to provide eco-toxicologists with background information on how to make good use of the tools and how to advance the methods for assessing toxicity of metal mixtures. It is concluded that statistically significant deviations from additivity are not necessarily biologically relevant. Incorporation of interactions between metals in a model does not on forehand mean that the model is more accurate than a model developed based on additivity only. It is recommended to first use a relatively simple method for effect prediction of uninvestigated metal mixtures. To improve the reliability of toxicity modeling for metal mixtures, further efforts should focus on balancing the relationship between the significance of statistics and the biological meaning, and unraveling the toxicity mechanisms of metals and their mixtures.
