Run Scenario Simulations
Subtask Description:
Review and evaluate priority and feasibility of scenarios.
Action points of the implementation:
Developed scenarios must be reviewed to determine if they are feasible and prioritize which are most likely to be used. Once these have been selected they should be interpreted in the context of the model. That is, determining how much to change forcing functions in the model to reflect these scenarios and to generate the data accordingly. This may require further data collection or inputs from external models.
Result: Identified scenarios to be applied to the simulation model which will represent the proposed management options.
Area:
Limfjorden, Denmark
Policy Issue:
Interaction between eutrophication and mussel production.
Human Activities:
Fisheries, aquaculture, agriculture, water based recreational activities, transport.
General Information:
In the early 1990’s a regime shift took place in the area, and there was an activity transition from demersal fishery to mussel fishery. Eutrophication, caused by nitrogen and phosphate loadings, is still causing periodical hypoxia, sometimes resulting in major death of mussels, and Harmful Algal Blooms, resulting in periodical commercial bans of the product. In 2006 the mussel landings fell to exceptionally low level and there is high risk of a total collapse of the mussel production. Mussel culture in lines is introduced to the area to replace the fishing activity, but this new venture is not economically viable. The main stakeholder concerns are connected to the impacts of hypoxia, mussel fishery and the lack of finfish and a understanding of their ecosystem functioning.
Example of Implementation:
The scope of the model is to help improve management of the human use of the Limfjord, looking simultaneously at eutrophication and mussel production. The objectives of the model is to enable prediction of the nutrient reduction on mussel growth and harvest either by fishery or aquaculture and socio-economic consequences hereof. Simultaneously, it allows for feed-back scenario predictions of production management of the fishery (e.g. quota) and aquaculture (e.g. number and size of licenses) and of economic (e.g. market demands and prices) and ecological (e.g. oxygen depleting events and harmful algal blooms) externalities. Scenario impact variables included changes in loadings of phosphorous and nitrogen, and in production of mussels in the fishery (changes in mussel production in aquaculture can be tested as well).
Scenarios included the Skive Fjord (mussel fishery downscaled from the Limfjord level to that of the Skive fjord):
- I. Changes in Nintrogen load in the range between 0 and 1, where 1 is equal to the mean value of the hindcast period of 19,800 Tons year-1 and effect on algal biomass, on mussel biomass on the bottom and fishery economy, and on aquaculture harvest and economy.
- II. Changes in Phosphorus load in the range between 0 and 1, where 1 is equal to the mean value of the hindcast period 581 Tons year-1 and effects on algal biomass, on mussel biomass on the bottom and fishery economy, and on aquaculture harvest and economy.
- III. Changes in the mussel fishery in the range between 0 and 1, where 1 is equal to the self-regulation of 45 Tons for each fixed 51 vessel licenses.
The indicators of nitrogen and phosphorous were chosen based on present day values (100 %) and the requirements of the national implementation of the EU Water Framework Directive (WFD).
Comments:
The adjustment of the structure implies additional testing of the revised model and re-assessment of its soundness. However, it is impossible to recalibrate or revalidate the adjusted model, because no data exist for the possible future situation characterised by the scenario.
Contact: Grete E. Dinesen gdi@aqua.dtu.dk