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EMBEDDING SCIENCE INTO ICZM – EXAMPLE OF FP6 SPICOSA Josianne G. Støttrup, Grete E. Dinesen, Karen Timmermann, Stiig Markager, Eva Roth and Lars Ravn-Jonsen.

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Presentation on theme: "EMBEDDING SCIENCE INTO ICZM – EXAMPLE OF FP6 SPICOSA Josianne G. Støttrup, Grete E. Dinesen, Karen Timmermann, Stiig Markager, Eva Roth and Lars Ravn-Jonsen."— Presentation transcript:

1 EMBEDDING SCIENCE INTO ICZM – EXAMPLE OF FP6 SPICOSA Josianne G. Støttrup, Grete E. Dinesen, Karen Timmermann, Stiig Markager, Eva Roth and Lars Ravn-Jonsen DTU Aqua, Section for Coastal Ecology National Environmental Research Institute, Aarhus University University of Southern Denmark

2 2DTU Aqua, Technical University of Denmark

3 3 SPICOSA project structure 18 study sites Policy & Socio-economy Model support Data handling Strategy develop. Dissimination Education & guidelines ICZM & scientific support SAF: System Design FormulationAppraisalOutput

4 4DTU Aqua, Technical University of Denmark

5 5 System Design (spring 2008) Policy issues: 1) regulation of nutrient effluents to reduce eutrophication; 2) potential closure of the mussel fishery due to national implementation of international directives; 3) potential resource conflicts between mussel fishers and mussel farmers. NO FISH HYPOXIA EUTRO- PHICATION

6 6DTU Aqua, Technical University of Denmark Virtual system - Model Mussel fishery – entire Limfjord Line mussel culture – central Limfjord System Design

7 7DTU Aqua, Technical University of Denmark Conceptual flow diagram of the ESE-model Nutrient loadingTemperature Empirical relation Primary production Phytoplankton biomass Line mussels Detruitus shallow mussels Medium size Harvest able size Small size Ingestion Mortality + respiration Ingestion Benthic mussels Hypoxia Faecal production Line harvest Mussel bank harvest Line effort Fishing effort Cost- benefit analysis Quotas No.licences Min. biomass Temp fishery closure (HAB)

8 8DTU Aqua, Technical University of Denmark Formulation Step The formulas Structure of the Ecological component using Extend Software

9 9DTU Aqua, Technical University of Denmark Simulation scenarious suggested by stakeholders 1) reductions of Total N and P 2) closure of the wild mussel fishery 3) introduction of line-mussel culture Formulation Step

10 10DTU Aqua, Technical University of Denmark Hindcast – phytoplankton growth Model simulation of phytoplankton growth (---) is calibrated close to the values measured in the real system (---). Appraisal Step

11 11DTU Aqua, Technical University of Denmark OUTPUT step

12 12DTU Aqua, Technical University of Denmark Output Step

13 13DTU Aqua, Technical University of Denmark Phosphor loading Nitrogen loading Output Step

14 14DTU Aqua, Technical University of Denmark RESULTS of Scenario 1. Reductions of total N and P loadings Reductions in N alone to WFD target (47% level) showed: 1.Minor decrease in phytoplankton biomass 2.Decrease (~25%) of shallow and deep water mussel biomass 3.Decrease (~50%) of mussel fishery profit

15 15DTU Aqua, Technical University of Denmark RESULTS of Scenario 1. Reductions of total N and P loadings Reductions in N alone to WFD target (47% level) showed: 1.Minor decrease in phytoplankton biomass 2.Decrease (~25%) of shallow and deep water mussel biomass 3.Decrease (~50%) of mussel fishery profit Reductions in N and P to the 47% level would result in: 1.Minor decrease in phytoplankton biomass (~20%) 2.Decrease (~50%) of shallow and deep water mussel biomass 3.Almost collapse of mussel fishery

16 16DTU Aqua, Technical University of Denmark RESULTS of Scenario 2. Closure of wild mussel fishery 1.a >10 fold increase in hitherto fishable mussel biomass 2.a >10 fold decrease in shallow-water and medium-sized deep- water mussel biomass 3.an annual profit loss of ~€6.2 million

17 17DTU Aqua, Technical University of Denmark Number of mussel farms RESULTS Scenario 3. Introduction of line mussel culture had little impact on wild mussel fishery had little impact on shallow- water mussel biomass

18 18DTU Aqua, Technical University of Denmark Stakeholders Scenario simulation results provided both recognizable and unexpected results, which stimulated discussion among stakeholders credible overview of the ecosystem they were familiar with cognition of a higher ecosystem complexity than hitherto understood changes in stakeholder perceptions The SAF seems well qualified for developing a common understanding of the needs and consequences of change as part of the public consultation process and merging public and scientific information.

19 19DTU Aqua, Technical University of Denmark


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