1. How changing human lifestyles are shaping Europe’s regional seas Laurence Mee, Coordinator

2. The European Union at 50 Four seas, one economic and social framework Half a billion people Unprecedented mobility Increasing affluence Growing evidence of deterioration of our seas How to sustainably manage our marine natural capital? European Lifestyles and Marine Ecosystems

3. ELME Objective Through improved understanding of the relationship between European lifestyles and the state of marine ecosystems, ELME will model the consequences of alternative scenarios for human development in post- accession Europe on the marine environment. European Lifestyles and Marine Ecosystems

4. Who are we? 28 institutions from 15 countries across Europe in a single consortium Institutions in every European regional sea Leading environmental and social scientists, together with policy specialists gathered in five task teams €2.5 millions core funding from the European Research Area European Lifestyles and Marine Ecosystems

5. Ambitions European Lifestyles and Marine Ecosystems An assessment of the consequences of current human lifestyles on Europe’s regional seas. A region-by-region predictive model of key problems during different European development scenarios. Options for dealing with predicted future change. Will the action plans and conventions be sufficient to prevent further degradation?

6. Why is it difficult to model socio- ecological systems? S-E systems demonstrate: Non-matching scales Surprises (non-linearities) Interconnection with other systems Memory effects Choke points common currency Difficult to find a common currency between the social and natural sciences. Bayesian belief networks are probabilistic models that use probability density functions as a common currency. Methodology

7. Spatial scale Regional Seas scale analysis Requires understanding of sub- systems Methodology

8. Surprises (non-linearities) Methodology Regime shift Systems undergo sudden and often unpredictable changes

9. Systems are Interconnected Methodology Exporting our global footprint

10. Systems have choke points Methodology The web of our life is of a mingled yarn, good and ill together. SHAKESPEARE

11. The D-P-S-I-R model ELME focused on the D-P-S relationship Methodology

12. Why lifestyles? Methodology Individual values Lifestyle Consumption activities Production activities Consumption choices Political choices Policy Socio-economic drivers Environmental change lead(s) to/cause(s)is associated withinfluences

13. Focus and initial priorities Environmental focus: destruction of habitats and species; eutrophication; chemical pollution; and the unsustainable extraction of living resources. Methodology

14. Modelling methods and requirements e.g. Bayesian networks Adapted from Borsuk et al., 2004) ALGAL DENSITY N input PARENT NODE (N input = f (error) DEPENDENT NODE (algal density = f (N input, error) ALGAL DENSITY N input flow temp conditional probability distribution marginal probability distribution Cross disciplinary systems best modelled stochastically rather than deterministically Probability density functions provide a common currency between social and natural sciences

15. Seagrass loss in the Mediterranean Examples of Issues Metadata

16. Time series data Seagrass loss in the Mediterranean

17. Initial conceptual model Sea grass loss in the Mediterranean

18. Bayesian Belief Network Model Sea grass loss in the Mediterranean

19. System loss and recovery Ecosystem degradation in the Black Sea

20. Basis of BBN model for Spanish hake fisheries Fisheries modelling

21. Information gathering for drivers Scenario modelling methodology

22. Scenarios for future change Scenario modelling methodology

23. Scenario development Scenario modelling methodology

24. Scenario development Scenario modelling methodology Identification of Alternative Scenarios by reference to fundamental factors (values & governance) Narrative description of Baseline and Alternative Scenarios in terms of: values and policy demography economy Driver sectors Categorical representation of direction of change (- /0/+): - Baseline v. present - Alternative Scenarios v. Baseline Scenario outcomes in terms of Underlying and Immediate Driver Indicators

25. Scenario development Scenario modelling methodology

26. Modelling system complexity: Baltic Baltic example

27. Baltic memory effects Baltic example BALTIC: Large decrease in P consumption for agriculture Little change in P in system

28. Winners and losers: Baltic Baltic example Winners shown here are benthic microalgae, coastal zoobenthos and sprat Losers are native eelgrass, zostera and large predators such as cod. There are habitat-forming winners and losers, indicating a fundamental change in the natural ecosystem Winners providing goods to the human population (fish in the case of the Baltic) are of lower economic value than the losers.

29. Model outputs: Baltic simulation Baltic example Under most scenarios, the Baltic will remain eutrophic, partly because of phosphorus recycling from the large sediment pool.

30. North Sea conceptual model European Lifestyles and Marine Ecosystems

31. North Sea Winners and Losers European Lifestyles and Marine Ecosystems Winners include phytoplankton and trophic dead-end species such as jellyfish Winners also include transitional waters (estuaries) Losers comprise seabirds that depend on sand eels and small pelagic fish. Bottom water (demersal) fish species such as plaice, cod and haddock are losers as are the other animals and plants that form sea-bed habitats

32. North Sea simulations European Lifestyles and Marine Ecosystems

33. Predicted winners and losers Simulations

34. Joined-up thinking Economic growth is a primary goal or countries joining the EU Affluence brings new lifestyle, including increased protein consumption. Demand can be met by increasing farmed land, intensifying production, or through imports Unless agricultural production is decoupled from nutrient discharge; eutrophication will dominate the future status of the Baltic and Black Sea European Lifestyles and Marine Ecosystems

35. Joined up thinking (2) Increased shipping benefits economic growth Environmental cost is increased dispersion of opportunistic alien species And air pollution including CO2 Urgent measures needed to reduce species transfer European Lifestyles and Marine Ecosystems

36. Joined up thinking (3) Offshore wind farms will help to deliver EU policy goal of 20% renewable energy They may also help create marine protected areas But fishing will be displaced and may be concentrated outside the renewables sites Future fisheries policy will need to consider wider environmental considerations European Lifestyles and Marine Ecosystems

37. Policy context Joined up thinking essential for managing Europe’s Seas Our horizon scanning demonstrates useful simulations of coupled socio-ecological systems are possible and reveals difficult future choices Currently, human impact seems to be coupled to affluence (economic growth) and technology Future policy need to find ways to decouple economic growth from its impact… or to constrain growth itself. European Lifestyles and Marine Ecosystems